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Author SHA1 Message Date
MervinPraisonandMervin Praison 090b910800 fix(composio): never use api_key as user_id fallback in v3 SDK
The API key is an auth credential, not an entity identifier. Fall back
to "default" only. Add test for explicit user_id and correct the v3
call assertion.

Co-authored-by: Mervin Praison <[email protected]>
2026-07-08 20:02:57 +00:00
MervinPraisonandpraisonai-triage-agent[bot] f2d1d3695d fix(composio): honor explicit api_key and use v3 toolkits API
- _check_composio_available() now accepts an explicit api_key and uses it
  as a fallback, fixing a broken contract where a key passed to
  composio_tools()/ComposioTools was silently ignored.
- Availability check requires the `composio` package only, removing the
  false-positive composio_openai branch that led to silent ImportError.
- get_tools() maps to the Composio v3 SDK (`toolkits`, required `user_id`)
  for the new client while preserving legacy ComposioToolSet behaviour.
- Remove redundant availability check inside _get_client().
- list_apps() handles string app entries defensively.

Co-authored-by: praisonai-triage-agent[bot] <praisonai-triage-agent[bot]@users.noreply.github.com>
2026-07-08 13:44:34 +00:00
MervinPraison 6a560069da feat: port Composio agent-callable tools from core SDK
Add composio_tools(), composio_list_apps(), ComposioTools class,
[composio] optional extra, tests, and README usage docs.
2026-07-08 14:39:10 +01:00
92 changed files with 3017 additions and 12530 deletions

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-12
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@@ -1,12 +0,0 @@
# PraisonAI-Tools environment variables (examples)
#
# Copy to `.env` and fill in the values for the tools you use.
# Never commit real secrets.
# ── Stripe (StripeTool) ─────────────────────────────────────────────
# Stripe secret key. Prefer least-privilege *restricted* keys (rk_...).
# Use test keys (sk_test_/rk_test_) for development and live keys
# (sk_live_/rk_live_) only in production. STRIPE_API_KEY is accepted as a
# fallback if STRIPE_SECRET_KEY is unset.
STRIPE_SECRET_KEY=sk_test_your_key_here
# STRIPE_API_KEY=sk_test_your_key_here
@@ -1,290 +0,0 @@
name: "Claude Code Action"
description: "Run Claude Code in GitHub Actions workflows"
inputs:
anthropic_api_key:
description: "Anthropic API key"
required: false
claude_code_oauth_token:
description: "Claude Code OAuth Token for Claude Pro"
required: false
github_token:
description: "GitHub token for Claude to operate with"
required: false
default: ${{ github.token }}
trigger_phrase:
description: "The trigger phrase to look for in comments, issue/PR bodies, and issue titles"
required: false
default: "@claude"
assignee_trigger:
description: "The assignee username that triggers the action (e.g. @claude). Only used for issue assignment"
required: false
max_turns:
description: "Maximum number of conversation turns Claude can take"
required: false
timeout_minutes:
description: "Timeout in minutes for execution"
required: false
default: "30"
model:
description: "Model to use (provider-specific format required for Bedrock/Vertex)"
required: false
use_bedrock:
description: "Use Amazon Bedrock with OIDC authentication instead of direct Anthropic API"
required: false
default: "false"
use_vertex:
description: "Use Google Vertex AI with OIDC authentication instead of direct Anthropic API"
required: false
default: "false"
allowed_tools:
description: "Additional tools for Claude to use (the base GitHub tools will always be included)"
required: false
default: ""
disallowed_tools:
description: "Tools that Claude should never use"
required: false
default: ""
custom_instructions:
description: "Additional custom instructions to include in the prompt for Claude"
required: false
default: ""
mcp_config:
description: "Additional MCP configuration (JSON string) that merges with the built-in GitHub MCP servers"
required: false
default: ""
claude_env:
description: "Custom environment variables to pass to Claude Code execution (YAML format)"
required: false
default: ""
direct_prompt:
description: "Direct prompt for Claude to execute automatically without needing a trigger (for automated workflows)"
required: false
runs:
using: "composite"
steps:
- name: Install Claude Code
shell: bash
run: npm install -g @anthropic-ai/claude-code
- name: Install GitHub MCP Server
shell: bash
run: |
claude mcp add-json github '{
"command": "docker",
"args": [
"run",
"-i",
"--rm",
"-e",
"GITHUB_PERSONAL_ACCESS_TOKEN",
"ghcr.io/github/github-mcp-server:sha-ff3036d"
],
"env": {
"GITHUB_PERSONAL_ACCESS_TOKEN": "${{ inputs.github_token }}"
}
}'
- name: Extract GitHub Context and Create Prompt
shell: bash
id: prepare_context
env:
# Pass user-controlled inputs via environment variables to prevent script injection (GHSL-2025-093)
EVENT_COMMENT_BODY: ${{ github.event.comment.body }}
EVENT_ISSUE_TITLE: ${{ github.event.issue.title }}
EVENT_ISSUE_BODY: ${{ github.event.issue.body }}
EVENT_ISSUE_NUMBER: ${{ github.event.issue.number }}
EVENT_PR_TITLE: ${{ github.event.pull_request.title }}
EVENT_PR_NUMBER: ${{ github.event.pull_request.number }}
EVENT_REVIEW_BODY: ${{ github.event.review.body }}
EVENT_ASSIGNEE_LOGIN: ${{ github.event.assignee.login }}
INPUT_TRIGGER_PHRASE: ${{ inputs.trigger_phrase }}
INPUT_ASSIGNEE_TRIGGER: ${{ inputs.assignee_trigger }}
INPUT_DIRECT_PROMPT: ${{ inputs.direct_prompt }}
EVENT_ACTION: ${{ github.event.action }}
EVENT_NAME: ${{ github.event_name }}
REPO_NAME: ${{ github.repository }}
run: |
echo "🔍 Extracting GitHub context from event: $EVENT_NAME"
# Function to check for trigger phrase
check_trigger() {
local text="$1"
local trigger="$INPUT_TRIGGER_PHRASE"
if [[ "$text" == *"$trigger"* ]]; then
return 0
fi
return 1
}
# Extract context based on event type
TRIGGER_FOUND="false"
USER_REQUEST=""
CONTEXT_INFO=""
case "$EVENT_NAME" in
"issue_comment")
COMMENT_BODY="$EVENT_COMMENT_BODY"
ISSUE_TITLE="$EVENT_ISSUE_TITLE"
ISSUE_NUMBER="$EVENT_ISSUE_NUMBER"
if check_trigger "$COMMENT_BODY"; then
TRIGGER_FOUND="true"
USER_REQUEST="$COMMENT_BODY"
CONTEXT_INFO="Issue Comment on #$ISSUE_NUMBER: $ISSUE_TITLE"
fi
;;
"pull_request_review_comment")
COMMENT_BODY="$EVENT_COMMENT_BODY"
PR_TITLE="$EVENT_PR_TITLE"
PR_NUMBER="$EVENT_PR_NUMBER"
if check_trigger "$COMMENT_BODY"; then
TRIGGER_FOUND="true"
USER_REQUEST="$COMMENT_BODY"
CONTEXT_INFO="PR Comment on #$PR_NUMBER: $PR_TITLE"
fi
;;
"pull_request_review")
REVIEW_BODY="$EVENT_REVIEW_BODY"
PR_TITLE="$EVENT_PR_TITLE"
PR_NUMBER="$EVENT_PR_NUMBER"
if check_trigger "$REVIEW_BODY"; then
TRIGGER_FOUND="true"
USER_REQUEST="$REVIEW_BODY"
CONTEXT_INFO="PR Review on #$PR_NUMBER: $PR_TITLE"
fi
;;
"issues")
ISSUE_BODY="$EVENT_ISSUE_BODY"
ISSUE_TITLE="$EVENT_ISSUE_TITLE"
ISSUE_NUMBER="$EVENT_ISSUE_NUMBER"
if check_trigger "$ISSUE_TITLE" || check_trigger "$ISSUE_BODY"; then
TRIGGER_FOUND="true"
USER_REQUEST="$ISSUE_BODY"
CONTEXT_INFO="Issue #$ISSUE_NUMBER: $ISSUE_TITLE"
elif [[ "$EVENT_ACTION" == "assigned" && -n "$INPUT_ASSIGNEE_TRIGGER" ]]; then
ASSIGNEE="$EVENT_ASSIGNEE_LOGIN"
if [[ "$ASSIGNEE" == "$INPUT_ASSIGNEE_TRIGGER" ]]; then
TRIGGER_FOUND="true"
USER_REQUEST="$ISSUE_BODY"
CONTEXT_INFO="Issue #$ISSUE_NUMBER assigned to $ASSIGNEE: $ISSUE_TITLE"
fi
fi
;;
esac
# Check for direct prompt override
if [[ -n "$INPUT_DIRECT_PROMPT" ]]; then
TRIGGER_FOUND="true"
USER_REQUEST="$INPUT_DIRECT_PROMPT"
CONTEXT_INFO="Automated GitHub workflow"
fi
if [[ "$TRIGGER_FOUND" != "true" ]]; then
echo "❌ No trigger phrase found or direct prompt provided. Exiting gracefully."
echo "SKIP_EXECUTION=true" >> $GITHUB_ENV
exit 0
fi
echo "✅ Trigger found! Context: $CONTEXT_INFO"
# Create comprehensive prompt
mkdir -p /tmp/claude-action
cat > /tmp/claude-action/github-context-prompt.txt << EOF
You are Claude Code, an AI assistant helping with GitHub workflows and code.
Repository: $REPO_NAME
Context: $CONTEXT_INFO
Event: $EVENT_NAME
User Request:
$USER_REQUEST
Please analyze the request and provide helpful assistance.
CRITICAL INSTRUCTION: If your task involves modifying codebase files to add a feature or fix a bug:
STEP 0 — SETUP GIT IDENTITY:
git config user.name "MervinPraison"
git config user.email "[email protected]"
STEP 1 — READ GUIDELINES:
MANDATORY: Before writing any code, you MUST carefully read "src/praisonai-agents/AGENTS.md" to understand this repository's extremely specific Architecture, Protocol-First design rules, and Agent-Centric Philosophy.
STEP 2 — ARCHITECTURE VALIDATION & ROUTING (MANDATORY before writing code):
Before implementing anything, answer these questions:
- CORE vs WRAPPER vs TOOLS ROUTING:
1. Core SDK (praisonaiagents/): Only core protocols, base classes, decorators. No heavy implementations.
2. Wrapper (praisonai/): CLI, heavy implementations, optional dependencies.
3. Tools (PraisonAI-Tools): Specific integrations, external tools (e.g. SurrealDB, Slack), and community extensions MUST go to the `MervinPraison/PraisonAI-Tools` repository. If the feature is a tool, clone `https://github.com/MervinPraison/PraisonAI-Tools`, implement it there, and create the PR using `gh pr create -R MervinPraison/PraisonAI-Tools`.
- Does it duplicate existing functionality? Check if Agent already supports this via existing params (reflection, planning, tools, hooks, memory).
- Does it inherit from Agent properly? New agent types MUST inherit Agent, not wrap it with composition.
- Does it add new dependencies? Only optional deps allowed, must be lazy-imported.
- Will agent.py grow larger? If the change adds >50 lines to agent.py, find a way to extract instead.
- Is there a name collision with existing exports in __init__.py?
If ANY of these conceptual checks fail (excluding routing), add a comment to the issue explaining why and close it. Do NOT create a PR.
STEP 3 — IMPLEMENT:
- Create a new git branch appropriately named (e.g. \`feature/issue-<number>\`)
- Follow protocol-driven design: protocols in core SDK, heavy implementations in wrapper
- Keep changes small and backward-compatible
STEP 4 — TEST:
- Run: cd src/praisonai-agents && PYTHONPATH=. python -m pytest tests/ -x -q --timeout=30
- Ensure no regressions
STEP 5 — CREATE PR:
- Commit with descriptive message, push the branch
- Use the GitHub CLI (\`gh pr create --title "..." --body "Fixes #<number>"\`) to open a Pull Request
CRITICAL: You MUST create the PR automatically using \`gh pr create\`. Do NOT just provide a link.
Respond naturally and helpfully to the user's request using the available tools.
EOF
echo "PROMPT_FILE=/tmp/claude-action/github-context-prompt.txt" >> $GITHUB_ENV
echo "SKIP_EXECUTION=false" >> $GITHUB_ENV
- name: Run Claude Code
if: env.SKIP_EXECUTION != 'true'
shell: bash
run: |
echo "🚀 Running Claude Code with GitHub context..."
# Build command arguments
CMD_ARGS=("-p" "--verbose" "--output-format" "stream-json")
# Add max turns if specified
if [[ -n "${{ inputs.max_turns }}" ]]; then
CMD_ARGS+=("--max-turns" "${{ inputs.max_turns }}")
fi
# Add allowed tools (include GitHub tools by default)
TOOLS="mcp__github__get_issue,mcp__github__get_issue_comments,mcp__github__update_issue,mcp__github__search_issues,mcp__github__list_issues,mcp__github__create_comment,Read,Write,Edit,Bash"
if [[ -n "${{ inputs.allowed_tools }}" ]]; then
TOOLS="$TOOLS,${{ inputs.allowed_tools }}"
fi
CMD_ARGS+=("--allowedTools" "$TOOLS")
# Add disallowed tools
if [[ -n "${{ inputs.disallowed_tools }}" ]]; then
CMD_ARGS+=("--disallowedTools" "${{ inputs.disallowed_tools }}")
fi
echo "📝 Executing Claude Code with prompt from file..."
# Execute Claude Code with timeout, using stdin for the prompt
TIMEOUT_SECONDS=$((${{ inputs.timeout_minutes }} * 60))
timeout $TIMEOUT_SECONDS claude "${CMD_ARGS[@]}" < "${{ env.PROMPT_FILE }}"
echo "✅ Claude Code execution completed"
env:
ANTHROPIC_API_KEY: ${{ inputs.anthropic_api_key }}
CLAUDE_CODE_OAUTH_TOKEN: ${{ inputs.claude_code_oauth_token }}
GITHUB_TOKEN: ${{ inputs.github_token }}
@@ -1,91 +0,0 @@
name: "Claude Issue Triage Action"
description: "Automatically triage GitHub issues using Claude Code"
inputs:
timeout_minutes:
description: "Timeout in minutes for execution"
required: false
default: "5"
claude_code_oauth_token:
description: "Claude Code OAuth token for Pro subscription access"
required: true
github_token:
description: "GitHub token with repo and issues permissions"
required: true
runs:
using: "composite"
steps:
- name: Checkout repository code
uses: actions/checkout@v4
with:
fetch-depth: 0
- name: Create prompt
id: generate_prompt
shell: bash
run: |
mkdir -p /tmp/claude-prompts
cat > /tmp/claude-prompts/claude-issue-triage-prompt.txt << 'EOF'
You're an issue triage assistant for GitHub issues. Your task is to analyze the issue and select appropriate labels from the provided list.
IMPORTANT: Don't post any comments or messages to the issue. Your only action should be to apply labels.
Issue Information:
- REPO: ${{ github.repository }}
- ISSUE_NUMBER: ${{ github.event.issue.number }}
TASK OVERVIEW:
1. First, fetch the list of labels available in this repository by running: `gh label list`. Run exactly this command with nothing else.
2. Next, use the GitHub tools to get context about the issue:
- You have access to these tools:
- mcp__github__get_issue: Use this to retrieve the current issue's details including title, description, and existing labels
- mcp__github__get_issue_comments: Use this to read any discussion or additional context provided in the comments
- mcp__github__update_issue: Use this to apply labels to the issue (do not use this for commenting)
- mcp__github__search_issues: Use this to find similar issues that might provide context for proper categorization and to identify potential duplicate issues
- mcp__github__list_issues: Use this to understand patterns in how other issues are labeled
- Start by using mcp__github__get_issue to get the issue details
3. Analyze the issue content, considering:
- The issue title and description
- The type of issue (bug report, feature request, question, etc.)
- Technical areas mentioned
- Severity or priority indicators
- User impact
- Components affected
4. Select appropriate labels from the available labels list provided above:
- Choose labels that accurately reflect the issue's nature
- Be specific but comprehensive
- Select priority labels if you can determine urgency (high-priority, med-priority, or low-priority)
- Consider platform labels (android, ios) if applicable
- If you find similar issues using mcp__github__search_issues, consider using a "duplicate" label if appropriate. Only do so if the issue is a duplicate of another OPEN issue.
5. Apply the selected labels:
- Use mcp__github__update_issue to apply your selected labels
- DO NOT post any comments explaining your decision
- DO NOT communicate directly with users
- If no labels are clearly applicable, do not apply any labels
IMPORTANT GUIDELINES:
- Be thorough in your analysis
- Only select labels from the provided list above
- DO NOT post any comments to the issue
- Your ONLY action should be to apply labels using mcp__github__update_issue
- It's okay to not add any labels if none are clearly applicable
EOF
echo "PROMPT<<DELIMITER" >> $GITHUB_OUTPUT
cat /tmp/claude-prompts/claude-issue-triage-prompt.txt >> $GITHUB_OUTPUT
echo "DELIMITER" >> $GITHUB_OUTPUT
- name: Run Claude Code
uses: ./.github/actions/claude-code-action
with:
direct_prompt: ${{ steps.generate_prompt.outputs.PROMPT }}
allowed_tools: "Bash(gh label list),mcp__github__get_issue,mcp__github__get_issue_comments,mcp__github__update_issue,mcp__github__search_issues,mcp__github__list_issues"
timeout_minutes: ${{ inputs.timeout_minutes }}
claude_code_oauth_token: ${{ inputs.claude_code_oauth_token }}
github_token: ${{ inputs.github_token }}
-9
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@@ -1,9 +0,0 @@
{
"templateRepo": "MervinPraison/github-automation-template",
"stack": "claude",
"profile": "tools",
"mode": "hub",
"hubRef": "v1.1.15",
"templateVersion": "1.1.6",
"installedAt": "2026-09-07T12:54:25Z"
}
-4
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@@ -1,4 +0,0 @@
# Final architecture review prompt (referenced by merge-gate.js via gate-config fields).
# Most FINAL review text is assembled dynamically from gate-config.js at runtime.
See `finalClaudeScope`, `finalClaudeProductValue` in `.github/scripts/gate-config.js`.
@@ -1,34 +0,0 @@
#!/usr/bin/env node
const chain = require('./bot-pr-review-chain.js');
let failed = 0;
function assert(name, cond) {
if (!cond) {
console.error('FAIL:', name);
failed++;
} else {
console.log('ok:', name);
}
}
assert('chainKickPosted requires both markers', chain.chainKickPosted([
{ user: { login: 'MervinPraison' }, body: '@coderabbitai review' },
{ user: { login: 'MervinPraison' }, body: '/review' },
]));
assert('chainKickPosted false with only coderabbit', !chain.chainKickPosted([
{ user: { login: 'MervinPraison' }, body: '@coderabbitai review' },
]));
assert('coderabbitKickPosted detects coderabbit', chain.coderabbitKickPosted([
{ user: { login: 'MervinPraison' }, body: '@coderabbitai review' },
]));
assert('qodoKickPosted detects qodo', chain.qodoKickPosted([
{ user: { login: 'github-actions[bot]' }, body: '/review' },
]));
assert('ignores coderabbit bot comment', !chain.coderabbitKickPosted([
{ user: { login: 'coderabbitai[bot]' }, body: '@coderabbitai review' },
]));
assert('bot PR author match', chain.isBotOpenedPr({ user: { login: 'praisonai-triage-agent[bot]' } }));
assert('generic bot type match', chain.isBotOpenedPr({ user: { login: 'my-bot', type: 'Bot' } }));
assert('human author excluded', !chain.isBotOpenedPr({ user: { login: 'MervinPraison', type: 'User' } }));
process.exit(failed ? 1 : 0);
+1 -5
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@@ -4,15 +4,11 @@
module.exports = {
repoFullName: 'MervinPraison/PraisonAI-Tools',
triggerLogins: ['MervinPraison', 'github-actions[bot]'],
productPathPrefixes: ['praisonai_tools/', 'tests/'],
// Workflows stay gated; pyproject.toml is normal for optional tool deps.
sensitivePathPatterns: [
/^\.github\/workflows\//,
/^pyproject\.toml$/,
],
// Tool + tests + docs routinely exceed the UI/SDK 800-line default.
maxAutoAdditions: 2000,
maxAutoFiles: 30,
requiredCheckPatterns: [/^ci$/i, /python/i, /test/i, /lint/i, /ruff/i],
ciWorkflowFile: 'ci.yml',
ciWorkflowName: 'CI',
-15
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@@ -1,15 +0,0 @@
/**
* Load per-repo gate configuration (installed as .github/scripts/gate-config.js).
*/
function loadGateConfig() {
try {
return require('./gate-config.js');
} catch (err) {
if (err.code !== 'MODULE_NOT_FOUND') throw err;
throw new Error(
'Missing .github/scripts/gate-config.js — run install.sh from github-automation-template'
);
}
}
module.exports = { loadGateConfig };
+2 -65
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@@ -41,39 +41,6 @@ const withClaudeReply = [
assert('not stale when Claude replied after FINAL', !mg.isStaleFinalAfterPush(withClaudeReply, '2026-06-12T09:00:00Z'));
assert('claude final reply detected', mg.isClaudeFinalReplyComment(withClaudeReply[1]));
const mervinReply = {
user: { login: 'MervinPraison' },
body: "**Claude finished @MervinPraison's task** —— [View job](https://github.com/)",
created_at: '2026-06-12T08:30:00Z',
};
assert('mervin claude final reply detected', mg.isClaudeFinalReplyComment(mervinReply));
assert(
'not stale when MervinPraison posted Claude finished',
!mg.isStaleFinalAfterPush([...finals, mervinReply], '2026-06-12T09:00:00Z')
);
const conflictRebaseComments = [
{
user: { login: 'MervinPraison' },
body: '@claude You are the FINAL architecture reviewer.',
created_at: '2026-06-12T08:00:00Z',
},
{
user: { login: 'MervinPraison' },
body: '@claude this PR has merge conflicts with `main`.',
created_at: '2026-06-12T08:10:00Z',
},
{
user: { login: 'MervinPraison' },
body: 'Rebase onto main complete. Force-pushed to branch.',
created_at: '2026-06-12T08:20:00Z',
},
];
assert(
'allow stale-FINAL recovery after conflict rebase push',
!mg.shouldSkipStaleFinalRecovery(conflictRebaseComments, '2026-06-12T08:25:00Z').skip
);
assert('cancelled detect-and-trigger does not block', mg.OPTIONAL_CANCELLED_CHECKS.has('detect-and-trigger'));
// Stale-FINAL recovery guards (PR #2560 push loop)
@@ -245,33 +212,6 @@ assert('conflict still blocks without FINAL on HEAD', mg.hasRecentConflictCommen
[conflictTrigger, rebaseDone],
headAfterRebase
));
assert(
'CLEAN + head after conflict clears without completion comment',
!mg.hasRecentConflictComment([conflictTrigger], headAfterRebase, 'CLEAN')
);
assert(
'UNSTABLE + head after conflict clears without completion comment',
!mg.hasRecentConflictComment([conflictTrigger], headAfterRebase, 'UNSTABLE')
);
assert(
'DIRTY still blocks even with head after conflict',
mg.hasRecentConflictComment([conflictTrigger], headAfterRebase, 'DIRTY')
);
assert(
'owner rebase-complete comment clears conflict',
!mg.hasRecentConflictComment(
[
conflictTrigger,
{
user: { login: 'MervinPraison' },
body: '**Rebase complete** — conflicts resolved.',
created_at: conflictIso(-29 * 60 * 1000),
},
finalAfterRebase,
],
headAfterRebase
)
);
// Tests heuristic
assert('product code without tests', mg.missingTestsReason([{ filename: productSample, additions: 3 }]) !== null);
@@ -280,11 +220,8 @@ assert('product code with tests ok', mg.missingTestsReason([
{ filename: 'tests/test_x.py', additions: 10 },
]) === null);
// PR size (threshold from gate-config; Tools allows larger tool+tests+docs PRs)
const sizeLimit = config.maxAutoAdditions ?? 800;
assert('under size limit ok', mg.prSizeReasons([{ additions: sizeLimit }]).length === 0);
assert('large PR blocked', mg.prSizeReasons([{ additions: sizeLimit + 1 }]).length > 0);
assert('typical tool PR under Tools limit', mg.prSizeReasons([{ additions: 1510 }]).length === 0);
// PR size
assert('large PR blocked', mg.prSizeReasons([{ additions: 900 }]).length > 0);
assert('internal PR link accepted', mg.isInternalPullRequestLink(
{ base: { repo: { full_name: config.repoFullName } } },
+6 -64
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@@ -14,8 +14,8 @@ const STALE_FINAL_MAX_PER_WINDOW = 2;
const PUSH_AFTER_FINAL_DEBOUNCE_MS = 15 * 60 * 1000;
const ALLOWED_MERGE_STATES = new Set(['CLEAN', 'UNSTABLE']);
const AGENT_PY_MAX_AUTO_LINES = 100;
const PR_MAX_AUTO_ADDITIONS = config.maxAutoAdditions ?? 800;
const PR_MAX_AUTO_FILES = config.maxAutoFiles ?? 30;
const PR_MAX_AUTO_ADDITIONS = 800;
const PR_MAX_AUTO_FILES = 30;
const MANUAL_ONLY_LABELS = new Set(['security', 'breaking-change', 'needs-manual-review', 'release']);
const WORKFLOW_ONLY_LABEL = 'merge-gate-ci-only';
const CI_ONLY_PATH_PREFIXES = ['.github/workflows/', '.github/actions/', '.github/scripts/merge-gate'];
@@ -67,11 +67,7 @@ function isClaudeTriggerNoise(c) {
function isClaudeFinalReplyComment(c) {
const login = (c.user?.login || '').toLowerCase();
const fromAutomation =
login.includes('praisonai-triage') ||
login.includes('github-actions') ||
AUTO_ACTORS.some((a) => a.toLowerCase() === login);
if (!fromAutomation) return false;
if (!login.includes('praisonai-triage')) return false;
return (c.body || '').includes('Claude finished');
}
@@ -93,47 +89,15 @@ function isConflictRebaseTriggerComment(c) {
function isConflictRebaseCompletionComment(c) {
const login = (c.user?.login || '').toLowerCase();
const allowed =
login.includes('praisonai-triage') ||
login.includes('github-actions') ||
AUTO_ACTORS.some((a) => a.toLowerCase() === login);
if (!allowed) return false;
if (!login.includes('praisonai-triage') && !login.includes('github-actions')) return false;
const body = (c.body || '').toLowerCase();
return (
body.includes('rebase complete') ||
body.includes('rebase onto') ||
body.includes('force-pushed') ||
(body.includes('conflict') && body.includes('resolved'))
);
}
/** HEAD landed after conflict rebase but no FINAL @claude since that push. */
function needsFinalReReviewAfterConflictRebase(comments, headPushedAt) {
if (!headPushedAt) return false;
const headTime = new Date(headPushedAt).getTime();
const conflictTriggers = comments.filter(isConflictRebaseTriggerComment);
if (conflictTriggers.length === 0) return false;
const latestConflict = conflictTriggers.reduce((a, b) =>
new Date(a.created_at) > new Date(b.created_at) ? a : b
);
const conflictTime = new Date(latestConflict.created_at).getTime();
if (headTime <= conflictTime) return false;
const rebaseDone = comments.some(
(c) =>
new Date(c.created_at).getTime() > conflictTime && isConflictRebaseCompletionComment(c)
);
if (!rebaseDone) return false;
const finalsAfterHead = comments.filter(
(c) =>
isFinalClaudeTriggerComment(c) &&
new Date(c.created_at).getTime() >= headTime - 60000
);
return finalsAfterHead.length === 0;
}
function conflictRebaseQuiescent(comments, headPushedAt) {
const conflictTriggers = comments.filter(isConflictRebaseTriggerComment);
if (conflictTriggers.length === 0) return true;
@@ -152,7 +116,7 @@ function conflictRebaseQuiescent(comments, headPushedAt) {
return finalClaudeCompletedOnSha(comments, headPushedAt);
}
function hasRecentConflictComment(comments, headPushedAt = null, mergeStateStatus = null) {
function hasRecentConflictComment(comments, headPushedAt = null) {
const cutoff = Date.now() - CONFLICT_COOLDOWN_MS;
const hasRecentTrigger = comments.some((c) => {
if (!isConflictRebaseTriggerComment(c)) return false;
@@ -163,24 +127,6 @@ function hasRecentConflictComment(comments, headPushedAt = null, mergeStateStatu
if (headPushedAt && conflictRebaseQuiescent(comments, headPushedAt)) {
return false;
}
// GitHub mergeable (CLEAN/UNSTABLE) and HEAD pushed after the conflict trigger → resolved
const status = String(mergeStateStatus || '').toUpperCase();
if (headPushedAt && ALLOWED_MERGE_STATES.has(status)) {
// conflictTriggers is guaranteed non-empty here (hasRecentTrigger is true above);
// the null seed keeps reduce() safe if that invariant ever changes.
const conflictTriggers = comments.filter(isConflictRebaseTriggerComment);
const latestConflict = conflictTriggers.reduce(
(a, b) => (a && new Date(a.created_at) > new Date(b.created_at) ? a : b),
null
);
if (
latestConflict &&
new Date(headPushedAt).getTime() > new Date(latestConflict.created_at).getTime()
) {
return false;
}
}
return true;
}
@@ -292,9 +238,6 @@ function shouldSkipStaleFinalRecovery(comments, headPushedAt, headPusherLogin =
if (headPusherLogin && isClaudeAutomationLogin(headPusherLogin)) {
return { skip: true, reason: 'head pushed by Claude automation' };
}
if (needsFinalReReviewAfterConflictRebase(comments, headPushedAt)) {
return { skip: false, reason: '' };
}
if (isPushSoonAfterLatestFinal(comments, headPushedAt)) {
return {
skip: true,
@@ -729,7 +672,7 @@ async function evaluatePipelineQuiescent(github, owner, repo, prNumber, core, op
reasons.push('fork PR');
}
if (hasRecentConflictComment(ctx.comments, ctx.headPushedAt, status)) {
if (hasRecentConflictComment(ctx.comments, ctx.headPushedAt)) {
reasons.push('recent merge-conflict @claude');
}
if (!skipRecentClaudeCooldown && hasRecentClaudeTrigger(ctx.comments, 35)) {
@@ -902,7 +845,6 @@ module.exports = {
hasRecentConflictComment,
isConflictRebaseTriggerComment,
isConflictRebaseCompletionComment,
needsFinalReReviewAfterConflictRebase,
conflictRebaseQuiescent,
hasHumanChangesRequested,
hasAnyChangesRequested,
-111
View File
@@ -1,111 +0,0 @@
#!/usr/bin/env node
const chain = require('./pr-review-chain.js');
let failed = 0;
function assert(name, cond) {
if (!cond) {
console.error('FAIL:', name);
failed++;
} else {
console.log('ok:', name);
}
}
const coderabbit = {
user: { login: 'coderabbitai[bot]' },
body: '<!-- summarize by coderabbit.ai --> summary',
created_at: '2026-07-02T07:16:00Z',
};
const greptile = {
user: { login: 'greptile-apps[bot]' },
body: '<h3>Greptile Summary</h3><p>Looks good</p>',
created_at: '2026-07-02T07:19:00Z',
};
const copilotKick = {
user: { login: 'MervinPraison' },
body: '@copilot Do a thorough review',
created_at: '2026-07-02T07:20:00Z',
};
const copilotReply = {
user: { login: 'copilot-swe-agent' },
body: 'Copilot review here',
created_at: '2026-07-02T07:22:00Z',
};
assert('prior not ready without greptile', !chain.priorReviewersReady([coderabbit]).ready);
assert('prior ready with coderabbit + greptile', chain.priorReviewersReady([coderabbit, greptile]).ready);
assert('copilot not ready before trigger', !chain.copilotReviewReady([coderabbit, greptile]).ready);
assert(
'copilot ready after reply',
chain.copilotReviewReady([coderabbit, greptile, copilotKick, copilotReply]).ready
);
assert(
'claude not ready before copilot',
!chain.claudeFinalReady([coderabbit, greptile]).ready
);
assert(
'claude ready after full chain',
chain.claudeFinalReady([coderabbit, greptile, copilotKick, copilotReply]).ready
);
assert(
'claude timeout fallback when copilot triggered but silent',
chain.claudeFinalReady([coderabbit, greptile, copilotKick], [], { allowCopilotTimeout: true }).ready
);
assert(
'no timeout fallback without copilot trigger',
!chain.claudeFinalReady([coderabbit, greptile], [], { allowCopilotTimeout: true }).ready
);
assert(
'skipCopilot proceeds after prior reviewers',
chain.claudeFinalReady([coderabbit, greptile], [], { skipCopilot: true }).ready
);
const prev = process.env.REVIEW_CHAIN_SKIP_COPILOT;
process.env.REVIEW_CHAIN_SKIP_COPILOT = '1';
assert(
'REVIEW_CHAIN_SKIP_COPILOT env skips copilot',
chain.claudeFinalReady([coderabbit, greptile], [], {}).ready
);
process.env.REVIEW_CHAIN_SKIP_COPILOT = prev;
const geminiReview = {
user: { login: 'gemini-code-assist[bot]' },
body: '## Code Review\n\nThis pull request decomposes the large main.py file',
submitted_at: '2026-07-03T08:08:00Z',
};
assert(
'gemini pull review counts as prior reviewer',
chain.hasGeminiReview([], [geminiReview])
);
assert(
'prior ready with gemini review only (no gemini comment)',
chain.priorReviewersReady([coderabbit, greptile], [geminiReview], { optionalWaitMs: 0 }).ready
);
const oldPr = new Date(Date.now() - 31 * 60 * 1000).toISOString();
assert(
'prior not ready without coderabbit before timeout',
!chain.priorReviewersReady([greptile], [], { prCreatedAt: new Date().toISOString(), requiredWaitMs: 30 * 60 * 1000 }).ready
);
assert(
'prior timeout when coderabbit silent after 30m',
chain.priorReviewersReady([greptile], [], { prCreatedAt: oldPr, requiredWaitMs: 30 * 60 * 1000 }).ready
);
assert(
'claude FINAL timeout when required reviewer silent and no prior FINAL',
chain.claudeFinalReady([greptile], [], { prCreatedAt: oldPr, requiredWaitMs: 30 * 60 * 1000 }).ready
);
assert(
'claude FINAL timeout auto-skips copilot without explicit skipCopilot',
chain.claudeFinalReady([greptile], [], { prCreatedAt: oldPr, requiredWaitMs: 30 * 60 * 1000 }).copilotSkipped
);
const finalClaude = {
user: { login: 'github-actions[bot]' },
body: '@claude You are the FINAL architecture reviewer for this PR.',
created_at: '2026-07-02T07:25:00Z',
};
assert(
'claude FINAL not re-posted when already triggered',
!chain.claudeFinalReady([greptile, finalClaude], [], { prCreatedAt: oldPr, requiredWaitMs: 0 }).ready
);
process.exit(failed ? 1 : 0);
+1 -50
View File
@@ -29,53 +29,4 @@ try {
assert('PACKAGE_PATHS includes pyproject', rg.PACKAGE_PATHS.includes('pyproject.toml'));
(async () => {
const noonUtc = new Date('2026-07-08T12:00:00Z');
const mockGithub = {
rest: {
actions: {
listWorkflowRuns: async () => ({
data: {
workflow_runs: [
{
conclusion: 'success',
created_at: '2026-07-08T09:00:00Z',
status: 'completed',
},
],
},
}),
},
},
};
assert('PATCH_RELEASE_INTERVAL_DAYS is 3', rg.PATCH_RELEASE_INTERVAL_DAYS === 3);
assert(
'hasSuccessfulReleaseWithinDays blocks recent release',
await rg.hasSuccessfulReleaseWithinDays(mockGithub, 'o', 'r', noonUtc)
);
const oldReleaseGithub = {
rest: {
actions: {
listWorkflowRuns: async () => ({
data: {
workflow_runs: [
{
conclusion: 'success',
created_at: '2026-07-04T09:00:00Z',
status: 'completed',
},
],
},
}),
},
},
};
assert(
'hasSuccessfulReleaseWithinDays allows after 3 days',
!(await rg.hasSuccessfulReleaseWithinDays(oldReleaseGithub, 'o', 'r', noonUtc))
);
process.exit(failed ? 1 : 0);
})();
process.exit(failed ? 1 : 0);
+6 -28
View File
@@ -6,8 +6,6 @@ const https = require('https');
const config = require('./gate-config.js');
const PACKAGE_PATHS = config.packagePaths;
/** Minimum days between successful patch auto-releases. */
const PATCH_RELEASE_INTERVAL_DAYS = 3;
const ACTIVE_RELEASE_STATUSES = new Set([
'queued', 'in_progress', 'waiting', 'pending', 'requested',
]);
@@ -63,18 +61,8 @@ function utcDayStart(now = new Date()) {
return new Date(Date.UTC(now.getUTCFullYear(), now.getUTCMonth(), now.getUTCDate()));
}
function releaseIntervalStart(now = new Date(), intervalDays = PATCH_RELEASE_INTERVAL_DAYS) {
return new Date(now.getTime() - intervalDays * 24 * 60 * 60 * 1000);
}
async function hasSuccessfulReleaseWithinDays(
github,
owner,
repo,
now = new Date(),
intervalDays = PATCH_RELEASE_INTERVAL_DAYS,
) {
const windowStart = releaseIntervalStart(now, intervalDays);
async function hasSuccessfulReleaseToday(github, owner, repo, now = new Date()) {
const dayStart = utcDayStart(now);
const runs = await github.rest.actions.listWorkflowRuns({
owner,
repo,
@@ -83,15 +71,10 @@ async function hasSuccessfulReleaseWithinDays(
per_page: 30,
});
return runs.data.workflow_runs.some(
(r) => r.conclusion === 'success' && new Date(r.created_at) >= windowStart
(r) => r.conclusion === 'success' && new Date(r.created_at) >= dayStart
);
}
/** @deprecated Use hasSuccessfulReleaseWithinDays — kept for selftests. */
async function hasSuccessfulReleaseToday(github, owner, repo, now = new Date()) {
return hasSuccessfulReleaseWithinDays(github, owner, repo, now, 1);
}
async function lastGreenCiSha(github, owner, repo) {
const runs = await github.rest.actions.listWorkflowRuns({
owner,
@@ -133,11 +116,9 @@ async function evaluateReleasePreflight(github, owner, repo, options, core) {
}
const referenceTime = options.now instanceof Date ? options.now : new Date();
if (await hasSuccessfulReleaseWithinDays(github, owner, repo, referenceTime)) {
reasons.push(
`already released within last ${PATCH_RELEASE_INTERVAL_DAYS} days; `
+ `max one patch release every ${PATCH_RELEASE_INTERVAL_DAYS} days`
);
if (await hasSuccessfulReleaseToday(github, owner, repo, referenceTime)) {
const day = referenceTime.toISOString().slice(0, 10);
reasons.push(`already released today (UTC ${day}); max one patch release per day`);
return out;
}
@@ -215,9 +196,6 @@ module.exports = {
bumpPatch,
readVersionsFromTree,
pypiVersionExists,
PATCH_RELEASE_INTERVAL_DAYS,
releaseIntervalStart,
hasSuccessfulReleaseWithinDays,
hasSuccessfulReleaseToday,
utcDayStart,
evaluateReleasePreflight,
+37
View File
@@ -0,0 +1,37 @@
name: Auto Issue Comment
on:
issues:
types: [opened]
jobs:
trigger-claude:
# Skip if issue already has 'claude' label to avoid double-trigger
if: |
!contains(toJSON(github.event.issue.labels), 'claude')
runs-on: ubuntu-latest
permissions:
issues: write
steps:
- name: Add claude label to trigger analysis
uses: actions/github-script@v7
with:
github-token: ${{ secrets.GH_TOKEN }}
script: |
const labels = context.payload.issue.labels.map(l => l.name);
if (labels.includes('claude')) {
console.log('Issue already has claude label, skipping');
return;
}
await github.rest.issues.addLabels({
issue_number: context.issue.number,
owner: context.repo.owner,
repo: context.repo.repo,
labels: ['claude']
});
await github.rest.issues.createComment({
issue_number: context.issue.number,
owner: context.repo.owner,
repo: context.repo.repo,
body: '@claude Read this issue (title + body) and all existing comments. Implement or fix in `praisonai_tools/` with minimal changes; follow README and existing tool patterns (lazy optional deps, clear errors). Open a PR when you have commits.\n\n🤖 Auto-triage: label `claude` was added for filtering.'
});
+788 -12
View File
@@ -1,5 +1,14 @@
name: Auto PR Comment
# Review chain: CodeRabbit/Qodo/Gemini review first → Copilot → Claude (final)
# For human PRs: CodeRabbit/Qodo auto-review → this workflow triggers Copilot → then Claude
# For bot PRs: CodeRabbit/Qodo skip bots, so we trigger them explicitly first
#
# IMPORTANT: @copilot ignores bot comments. All @copilot mentions must use
# PAT_TOKEN so the comment posts as MervinPraison (a real user).
#
# Claude trigger runs IN-BAND (same workflow) to avoid GitHub Actions
# blocking bot-triggered workflows with action_required approval gates.
on:
issue_comment:
types: [created]
@@ -8,26 +17,793 @@ on:
pull_request:
types: [opened, synchronize]
pull_request_target:
types: [opened, synchronize]
types: [synchronize]
schedule:
- cron: '30 * * * *'
- cron: '30 3,9,15,21 * * *'
workflow_dispatch:
env:
REVIEW_CHAIN_SKIP_COPILOT: '1'
inputs:
pr_number:
description: 'PR number for manual FINAL (leave empty to sweep all open PRs)'
required: false
type: number
permissions:
contents: read
issues: write
pull-requests: write
env:
MAX_POLL_ATTEMPTS: 20
POLL_DELAY_MS: 30000
CLAUDE_TRIGGER_LOGINS: '["MervinPraison","github-actions[bot]"]'
# GH_TOKEN (user PAT) posts as MervinPraison for @copilot; fallback to github.token for @claude
GH_TOKEN: ${{ secrets.GH_TOKEN || github.token }}
CLAUDE_UI_SCOPE: 'SCOPE: Focus ONLY on PraisonAI-Tools (praisonai_tools/, tests). Do not expand into praisonaiagents or the monorepo unless the issue explicitly requires it.'
CLAUDE_FINAL_PHASES_COMPACT: "**Phase 1: Review per AGENTS.md** (lazy imports, backward compat, import-time <200ms; SDK/product value gate — genuine agent-tool value, correct tool vs SDK vs Plugins layering, no scope creep)\n**Phase 2: FIX valid issues** found by prior reviewers — push to THIS branch\n**Phase 3: Final verdict** — approve PR if ready, else request changes"
CLAUDE_FINAL_PHASES_DETAILED: "**Phase 1: Review per AGENTS.md**\n1. Protocol-driven: check heavy implementations vs core SDK\n2. Backward compatible: ensure zero feature regressions\n3. Performance: no hot-path regressions (lazy imports, import-time <200ms)\n4. SDK/product value: review whether the change genuinely adds value — correct tool layering (agent-callable integrations here; lifecycle plugins in PraisonAI-Plugins; core SDK in praisonaiagents). Reject scope creep; request changes or recommend closing if value is unclear\n\n**Phase 2: FIX Valid Issues**\n5. For any VALID bugs or architectural flaws found by Gemini, CodeRabbit, Qodo, Copilot, or any other reviewer: implement the fix\n6. Push all code fixes directly to THIS branch (do NOT create a new PR)\n7. Comment a summary of exact files modified and what you skipped\n\n**Phase 3: Final Verdict**\n8. If all issues are resolved, approve the PR / close the Issue\n9. If blocking issues remain, request changes / leave clear action items"
jobs:
review-chain:
# Grant union of callee job permissions (repos with default_workflow_permissions: read
# reject reusable calls when the caller ceiling is lower than any callee job).
# ================================================================
# HUMAN PRs: Trigger @copilot AFTER CodeRabbit posts its summary
# ================================================================
copilot-after-coderabbit:
if: |
github.event_name == 'issue_comment' &&
github.event.issue.pull_request &&
github.event.comment.user.login == 'coderabbitai[bot]' &&
contains(github.event.comment.body, 'summary by coderabbit')
runs-on: ubuntu-latest
permissions:
pull-requests: write
outputs:
pr_number: ${{ steps.trigger.outputs.pr_number }}
triggered: ${{ steps.trigger.outputs.triggered }}
steps:
- name: Post Copilot review request (as user via PAT)
id: trigger
uses: actions/github-script@v7
with:
github-token: ${{ env.GH_TOKEN }}
script: |
const comments = await github.rest.issues.listComments({
issue_number: context.issue.number,
owner: context.repo.owner,
repo: context.repo.repo
});
// Check for duplicates — posted by MervinPraison (PAT) or github-actions[bot] (legacy)
const alreadyPosted = comments.data.some(c =>
c.body.includes('@copilot') &&
(c.user.login === 'MervinPraison' || c.user.login === 'github-actions[bot]')
);
if (alreadyPosted) {
console.log('Copilot already triggered, skipping');
core.setOutput('triggered', 'false');
core.setOutput('pr_number', context.issue.number.toString());
return;
}
await github.rest.issues.createComment({
issue_number: context.issue.number,
owner: context.repo.owner,
repo: context.repo.repo,
body: '@copilot Do a thorough review of this PR. Read ALL existing reviewer comments above from Qodo, Coderabbit, and Gemini first — incorporate their findings.\n\nReview areas:\n1. **Bloat check**: Are changes minimal and focused? Any unnecessary code or scope creep?\n2. **Security**: Any hardcoded secrets, unsafe eval/exec, missing input validation?\n3. **Performance**: Any module-level heavy imports? Hot-path regressions?\n4. **Tests**: Are tests included? Do they cover the changes adequately?\n5. **Backward compat**: Any public API changes without deprecation?\n6. **Code quality**: DRY violations, naming conventions, error handling?\n7. **Address reviewer feedback**: If Qodo, Coderabbit, or Gemini flagged valid issues, include them in your review\n8. Suggest specific improvements with code examples where possible'
});
core.setOutput('triggered', 'true');
core.setOutput('pr_number', context.issue.number.toString());
# Fallback: Trigger @copilot after Qodo review (if Coderabbit doesn't fire)
copilot-after-qodo:
if: |
github.event_name == 'pull_request_review' &&
github.event.review.user.login == 'qodo-code-review[bot]'
runs-on: ubuntu-latest
permissions:
pull-requests: write
outputs:
pr_number: ${{ steps.trigger.outputs.pr_number }}
triggered: ${{ steps.trigger.outputs.triggered }}
steps:
- name: Post Copilot review request (as user via PAT)
id: trigger
uses: actions/github-script@v7
with:
github-token: ${{ env.GH_TOKEN }}
script: |
const comments = await github.rest.issues.listComments({
issue_number: context.issue.number,
owner: context.repo.owner,
repo: context.repo.repo
});
const alreadyPosted = comments.data.some(c =>
c.body.includes('@copilot') &&
(c.user.login === 'MervinPraison' || c.user.login === 'github-actions[bot]')
);
if (alreadyPosted) {
console.log('Copilot already triggered, skipping');
core.setOutput('triggered', 'false');
core.setOutput('pr_number', context.issue.number.toString());
return;
}
await github.rest.issues.createComment({
issue_number: context.issue.number,
owner: context.repo.owner,
repo: context.repo.repo,
body: '@copilot Do a thorough review of this PR. Read ALL existing reviewer comments above first.\n\nReview areas:\n1. **Bloat check**: Are changes minimal and focused?\n2. **Security**: Any hardcoded secrets, unsafe eval/exec, missing input validation?\n3. **Performance**: Any module-level heavy imports? Hot-path regressions?\n4. **Tests**: Are tests included? Do they cover the changes adequately?\n5. **Backward compat**: Any public API changes without deprecation?\n6. **Code quality**: DRY violations, naming conventions, error handling?\n7. Suggest specific improvements with code examples where possible'
});
core.setOutput('triggered', 'true');
core.setOutput('pr_number', context.issue.number.toString());
# ================================================================
# FALLBACK: Claude trigger for cases where Copilot chain fails/skips
# Ensures Claude always runs after sufficient review time
# ================================================================
claude-fallback-timeout:
if: |
github.event_name == 'pull_request' &&
github.event.action == 'opened'
runs-on: ubuntu-latest
timeout-minutes: 20
permissions:
issues: write
pull-requests: write
uses: MervinPraison/github-automation-template/.github/workflows/[email protected]
secrets: inherit
with:
hub_ref: v1.1.20
steps:
- name: Wait for review window (15 min)
run: sleep 900
- name: Check if Claude already triggered
id: check_claude
uses: actions/github-script@v7
env:
TRIGGER_LOGINS: ${{ env.CLAUDE_TRIGGER_LOGINS }}
PR_NUMBER: ${{ github.event.pull_request.number }}
with:
github-token: ${{ env.GH_TOKEN }}
script: |
const pr = parseInt(process.env.PR_NUMBER, 10);
const triggerLogins = JSON.parse(process.env.TRIGGER_LOGINS);
const comments = await github.rest.issues.listComments({
issue_number: pr,
owner: context.repo.owner,
repo: context.repo.repo
});
const alreadyPosted = comments.data.some(c =>
c.body.includes('@claude') && triggerLogins.includes(c.user.login)
);
core.setOutput('already_triggered', alreadyPosted ? 'true' : 'false');
core.setOutput('comments_count', comments.data.length.toString());
const botReviews = comments.data.filter(c =>
['coderabbitai[bot]', 'qodo-code-review[bot]', 'gemini-code-assist[bot]',
'copilot-swe-agent', 'Copilot', 'greptile-apps[bot]'].some(bot =>
c.user.login.toLowerCase().includes(bot.toLowerCase())
)
);
core.setOutput('review_count', botReviews.length.toString());
- name: Aggregate reviews and trigger Claude
if: steps.check_claude.outputs.already_triggered != 'true'
uses: actions/github-script@v7
env:
PR_NUMBER: ${{ github.event.pull_request.number }}
with:
github-token: ${{ env.GH_TOKEN }}
script: |
const pr = parseInt(process.env.PR_NUMBER, 10);
const comments = await github.rest.issues.listComments({issue_number: pr, owner: context.repo.owner, repo: context.repo.repo, per_page: 100});
const reviews = {coderabbit: [], qodo: [], gemini: [], copilot: [], greptile: [], others: []};
comments.data.forEach(c => {
const login = c.user.login.toLowerCase();
const body = c.body.substring(0, 500);
if (login.includes('coderabbit')) reviews.coderabbit.push(body);
else if (login.includes('qodo')) reviews.qodo.push(body);
else if (login.includes('gemini')) reviews.gemini.push(body);
else if (login.includes('copilot')) reviews.copilot.push(body);
else if (login.includes('greptile')) reviews.greptile.push(body);
else if (c.user.type === 'Bot') reviews.others.push(body);
});
const summaryParts = [];
if (reviews.coderabbit.length) summaryParts.push('CodeRabbit: ' + reviews.coderabbit.length + ' comments');
if (reviews.qodo.length) summaryParts.push('Qodo: ' + reviews.qodo.length + ' comments');
if (reviews.gemini.length) summaryParts.push('Gemini: ' + reviews.gemini.length + ' comments');
if (reviews.copilot.length) summaryParts.push('Copilot: ' + reviews.copilot.length + ' comments');
if (reviews.greptile.length) summaryParts.push('Greptile: ' + reviews.greptile.length + ' comments');
const reviewSummary = summaryParts.length ? summaryParts.join(' | ') : 'No bot reviews detected';
const scope = process.env.CLAUDE_UI_SCOPE;
const phases = process.env.CLAUDE_FINAL_PHASES_COMPACT;
const claudeBody = '@claude You are the FINAL architecture reviewer. If the branch is under MervinPraison/PraisonAI-Tools (not a fork), you are able to make modifications to this branch and push directly. ' + scope + ' Read ALL prior reviewer comments. ' + reviewSummary + '.\n\n' +
'Review Context: ' + comments.data.length + ' total comments, ' +
(reviews.coderabbit.length + reviews.qodo.length + reviews.gemini.length + reviews.copilot.length + reviews.greptile.length) + ' bot reviews.\n\n' +
phases;
await github.rest.issues.createComment({issue_number: pr, owner: context.repo.owner, repo: context.repo.repo, body: claudeBody});
console.log('Claude fallback triggered on PR #' + pr + ' with ' + reviewSummary);
# ================================================================
# Claude FINAL review — polls for Copilot's response, then triggers
# This runs IN-BAND under the PAT context (MervinPraison), avoiding
# the action_required approval gate that blocks bot-triggered workflows.
# ================================================================
claude-after-copilot:
needs: [copilot-after-coderabbit]
if: |
always() &&
needs.copilot-after-coderabbit.result == 'success' &&
needs.copilot-after-coderabbit.outputs.triggered == 'true'
runs-on: ubuntu-latest
timeout-minutes: 15
permissions:
issues: write
pull-requests: write
steps:
- uses: actions/checkout@v4
with:
persist-credentials: false
- name: Wait for Copilot to respond (poll)
id: poll
uses: actions/github-script@v7
env:
PR_NUMBER: ${{ needs.copilot-after-coderabbit.outputs.pr_number }}
MAX_POLL_ATTEMPTS: ${{ env.MAX_POLL_ATTEMPTS }}
POLL_DELAY_MS: ${{ env.POLL_DELAY_MS }}
with:
github-token: ${{ env.GH_TOKEN }}
script: |
const pr = parseInt(process.env.PR_NUMBER, 10);
const owner = context.repo.owner;
const repo = context.repo.repo;
// Poll for Copilot's response — check every 30s for up to 10 minutes
const maxAttempts = parseInt(process.env.MAX_POLL_ATTEMPTS, 10);
const delayMs = parseInt(process.env.POLL_DELAY_MS, 10);
for (let i = 0; i < maxAttempts; i++) {
console.log(`Poll attempt ${i + 1}/${maxAttempts}...`);
const comments = await github.rest.issues.listComments({
issue_number: pr,
owner,
repo,
per_page: 50,
sort: 'created',
direction: 'desc'
});
// Look for Copilot's response (copilot-swe-agent or Copilot)
const copilotResponse = comments.data.find(c =>
(c.user.login === 'copilot-swe-agent' ||
c.user.login === 'Copilot' ||
c.user.login.toLowerCase().includes('copilot')) &&
c.user.type === 'Bot'
);
if (copilotResponse) {
console.log(`Copilot responded at ${copilotResponse.created_at}`);
core.setOutput('copilot_responded', 'true');
return;
}
// Also check PR reviews for Copilot
const reviews = await github.rest.pulls.listReviews({
pull_number: pr,
owner,
repo
});
const copilotReview = reviews.data.find(r =>
r.user.login.toLowerCase().includes('copilot')
);
if (copilotReview) {
console.log(`Copilot review submitted at ${copilotReview.submitted_at}`);
core.setOutput('copilot_responded', 'true');
return;
}
if (i < maxAttempts - 1) {
console.log(`Copilot hasn't responded yet, waiting ${delayMs/1000}s...`);
await new Promise(resolve => setTimeout(resolve, delayMs));
}
}
console.log('Copilot did not respond within timeout, triggering Claude anyway');
core.setOutput('copilot_responded', 'timeout');
- name: Check if Claude already triggered
id: check_claude
uses: actions/github-script@v7
env:
PR_NUMBER: ${{ needs.copilot-after-coderabbit.outputs.pr_number }}
TRIGGER_LOGINS: ${{ env.CLAUDE_TRIGGER_LOGINS }}
with:
github-token: ${{ env.GH_TOKEN }}
script: |
const pr = parseInt(process.env.PR_NUMBER, 10);
const triggerLogins = JSON.parse(process.env.TRIGGER_LOGINS);
const comments = await github.rest.issues.listComments({
issue_number: pr,
owner: context.repo.owner,
repo: context.repo.repo
});
const alreadyPosted = comments.data.some(c =>
c.body.includes('@claude') && triggerLogins.includes(c.user.login)
);
core.setOutput('already_triggered', alreadyPosted ? 'true' : 'false');
- name: Trigger Claude final review
if: steps.check_claude.outputs.already_triggered != 'true'
uses: actions/github-script@v7
env:
PR_NUMBER: ${{ needs.copilot-after-coderabbit.outputs.pr_number }}
with:
github-token: ${{ env.GH_TOKEN }}
script: |
const pr = parseInt(process.env.PR_NUMBER, 10);
const scope = process.env.CLAUDE_UI_SCOPE;
const phases = process.env.CLAUDE_FINAL_PHASES_DETAILED;
await github.rest.issues.createComment({
issue_number: pr,
owner: context.repo.owner,
repo: context.repo.repo,
body: '@claude You are the FINAL architecture reviewer. If the branch is under MervinPraison/PraisonAI-Tools (not a fork), you are able to make modifications to this branch and push directly. ' + scope + ' Read ALL comments above from Gemini, Qodo, CodeRabbit, and Copilot carefully before responding.\n\n' + phases
});
console.log(`Claude triggered on PR #${pr}`);
- name: Sync pipeline status labels
if: steps.check_claude.outputs.already_triggered != 'true'
uses: actions/github-script@v7
env:
PR_NUMBER: ${{ needs.copilot-after-coderabbit.outputs.pr_number }}
with:
github-token: ${{ env.GH_TOKEN }}
script: |
const path = require('path');
const ps = require(path.join(process.env.GITHUB_WORKSPACE, '.github/scripts/pipeline-status.js'));
const pr = parseInt(process.env.PR_NUMBER, 10);
await ps.ensurePipelineLabels(github, context.repo.owner, context.repo.repo, core);
await ps.syncPipelineLabels(github, context.repo.owner, context.repo.repo, pr, core);
# ================================================================
# Claude after Qodo fallback path (same polling approach)
# ================================================================
claude-after-copilot-qodo:
needs: [copilot-after-qodo]
if: |
always() &&
needs.copilot-after-qodo.result == 'success' &&
needs.copilot-after-qodo.outputs.triggered == 'true'
runs-on: ubuntu-latest
timeout-minutes: 15
permissions:
issues: write
pull-requests: write
steps:
- name: Wait for Copilot to respond (poll)
id: poll
uses: actions/github-script@v7
env:
PR_NUMBER: ${{ needs.copilot-after-qodo.outputs.pr_number }}
MAX_POLL_ATTEMPTS: ${{ env.MAX_POLL_ATTEMPTS }}
POLL_DELAY_MS: ${{ env.POLL_DELAY_MS }}
with:
github-token: ${{ env.GH_TOKEN }}
script: |
const pr = parseInt(process.env.PR_NUMBER, 10);
const owner = context.repo.owner;
const repo = context.repo.repo;
const maxAttempts = parseInt(process.env.MAX_POLL_ATTEMPTS, 10);
const delayMs = parseInt(process.env.POLL_DELAY_MS, 10);
for (let i = 0; i < maxAttempts; i++) {
console.log(`Poll attempt ${i + 1}/${maxAttempts}...`);
const comments = await github.rest.issues.listComments({
issue_number: pr, owner, repo,
per_page: 50, sort: 'created', direction: 'desc'
});
const copilotResponse = comments.data.find(c =>
(c.user.login === 'copilot-swe-agent' ||
c.user.login === 'Copilot' ||
c.user.login.toLowerCase().includes('copilot')) &&
c.user.type === 'Bot'
);
if (copilotResponse) {
console.log(`Copilot responded at ${copilotResponse.created_at}`);
core.setOutput('copilot_responded', 'true');
return;
}
const reviews = await github.rest.pulls.listReviews({
pull_number: pr, owner, repo
});
const copilotReview = reviews.data.find(r =>
r.user.login.toLowerCase().includes('copilot')
);
if (copilotReview) {
console.log(`Copilot review submitted at ${copilotReview.submitted_at}`);
core.setOutput('copilot_responded', 'true');
return;
}
if (i < maxAttempts - 1) {
await new Promise(resolve => setTimeout(resolve, delayMs));
}
}
console.log('Copilot did not respond within timeout, triggering Claude anyway');
core.setOutput('copilot_responded', 'timeout');
- name: Check if Claude already triggered
id: check_claude
uses: actions/github-script@v7
env:
PR_NUMBER: ${{ needs.copilot-after-qodo.outputs.pr_number }}
TRIGGER_LOGINS: ${{ env.CLAUDE_TRIGGER_LOGINS }}
with:
github-token: ${{ env.GH_TOKEN }}
script: |
const pr = parseInt(process.env.PR_NUMBER, 10);
const triggerLogins = JSON.parse(process.env.TRIGGER_LOGINS);
const comments = await github.rest.issues.listComments({
issue_number: pr,
owner: context.repo.owner,
repo: context.repo.repo
});
const alreadyPosted = comments.data.some(c =>
c.body.includes('@claude') && triggerLogins.includes(c.user.login)
);
core.setOutput('already_triggered', alreadyPosted ? 'true' : 'false');
- name: Trigger Claude final review
if: steps.check_claude.outputs.already_triggered != 'true'
uses: actions/github-script@v7
env:
PR_NUMBER: ${{ needs.copilot-after-qodo.outputs.pr_number }}
with:
github-token: ${{ env.GH_TOKEN }}
script: |
const pr = parseInt(process.env.PR_NUMBER, 10);
const scope = process.env.CLAUDE_UI_SCOPE;
const phases = process.env.CLAUDE_FINAL_PHASES_DETAILED;
await github.rest.issues.createComment({
issue_number: pr,
owner: context.repo.owner,
repo: context.repo.repo,
body: '@claude You are the FINAL architecture reviewer. If the branch is under MervinPraison/PraisonAI-Tools (not a fork), you are able to make modifications to this branch and push directly. ' + scope + ' Read ALL comments above from Gemini, Qodo, CodeRabbit, and Copilot carefully before responding.\n\n' + phases
});
console.log(`Claude triggered on PR #${pr}`);
# ================================================================
# Claude after Gemini — restores the trigger lost from the deleted
# chain-claude-after-copilot.yml workflow.
# Fires when Gemini posts a review comment on a PR or issue.
# ================================================================
claude-after-gemini:
if: |
github.event_name == 'issue_comment' &&
(
github.event.comment.user.login == 'gemini-code-assist[bot]' ||
contains(github.event.comment.body, 'Review completed by Gemini CLI') ||
contains(github.event.comment.body, 'The fix is ready for review. Please test')
)
runs-on: ubuntu-latest
permissions:
issues: write
pull-requests: write
steps:
- name: Check if Claude already triggered
id: check_claude
uses: actions/github-script@v7
env:
TRIGGER_LOGINS: ${{ env.CLAUDE_TRIGGER_LOGINS }}
with:
github-token: ${{ env.GH_TOKEN }}
script: |
const triggerLogins = JSON.parse(process.env.TRIGGER_LOGINS);
const comments = await github.rest.issues.listComments({
issue_number: context.issue.number,
owner: context.repo.owner,
repo: context.repo.repo
});
const alreadyPosted = comments.data.some(c =>
c.body.includes('@claude') && triggerLogins.includes(c.user.login)
);
core.setOutput('already_triggered', alreadyPosted ? 'true' : 'false');
- name: Post Claude analysis request (Lead Engineer)
if: steps.check_claude.outputs.already_triggered != 'true'
uses: actions/github-script@v7
with:
github-token: ${{ env.GH_TOKEN }}
script: |
const scope = process.env.CLAUDE_UI_SCOPE;
const phases = process.env.CLAUDE_FINAL_PHASES_DETAILED;
await github.rest.issues.createComment({
issue_number: context.issue.number,
owner: context.repo.owner,
repo: context.repo.repo,
body: '@claude You are the Lead Engineer. If the branch is under MervinPraison/PraisonAI-Tools (not a fork), you are able to make modifications to this branch and push directly. ' + scope + ' Read ALL analysis and reviews above carefully (Gemini, CodeRabbit, Qodo, Copilot, etc).\n\n' + phases
});
# ================================================================
# Recovery: re-post FINAL @claude after push or when chain missed
# ================================================================
claude-review-recovery:
if: |
github.event_name == 'pull_request_target' &&
github.event.action == 'synchronize'
runs-on: ubuntu-latest
permissions:
issues: write
pull-requests: read
steps:
- uses: actions/checkout@v4
- name: Re-post FINAL Claude review when stale or missing
uses: actions/github-script@v7
with:
github-token: ${{ env.GH_TOKEN }}
script: |
const path = require('path');
const mergeGate = require(path.join(process.env.GITHUB_WORKSPACE, '.github/scripts/merge-gate.js'));
const chain = require(path.join(process.env.GITHUB_WORKSPACE, '.github/scripts/pr-review-chain.js'));
const pr = context.payload.pull_request.number;
const owner = context.repo.owner;
const repo = context.repo.repo;
const comments = await mergeGate.listAllComments(github, owner, repo, pr);
const headPushedAt = (await mergeGate.getHeadCommitDate(github, owner, repo, pr))
|| context.payload.pull_request.updated_at;
const headPusher = context.payload.sender?.login || null;
const hasFinal = mergeGate.hasFinalClaudeReviewTrigger(comments);
const isStale = mergeGate.isStaleFinalAfterPush(comments, headPushedAt);
if (mergeGate.shouldSkipFinalRecovery(comments, headPushedAt)) {
core.info('Recent @claude within 35min and FINAL not stale — skip recovery');
return;
}
if (await mergeGate.hasInProgressClaudeAssistant(github, owner, repo, pr)) {
core.info('Claude workflow in progress — skip recovery');
return;
}
const finalBody = mergeGate.FINAL_CLAUDE_REVIEW_BODY;
const staleOpts = { allowStaleRepost: true, skipCopilot: true, optionalWaitMs: 0 };
const missingOpts = { allowCopilotTimeout: true, optionalWaitMs: 0 };
if (hasFinal && isStale) {
const gate = mergeGate.shouldSkipStaleFinalRecovery(comments, headPushedAt, headPusher);
if (gate.skip) {
core.info(`Skip stale-FINAL recovery: ${gate.reason}`);
return;
}
const result = await chain.maybeTriggerClaudeFinal(
github, owner, repo, pr, finalBody, core, staleOpts
);
if (result.posted) core.info(`Posted stale-FINAL recovery @claude on PR #${pr}`);
return;
}
if (hasFinal) {
core.info('FINAL Claude review current on HEAD — skip recovery');
return;
}
const result = await chain.maybeTriggerClaudeFinal(
github, owner, repo, pr, finalBody, core, missingOpts
);
if (result.posted) core.info(`Posted missing FINAL Claude review on PR #${pr}`);
- name: Sync pipeline status labels
uses: actions/github-script@v7
with:
github-token: ${{ env.GH_TOKEN }}
script: |
const path = require('path');
const ps = require(path.join(process.env.GITHUB_WORKSPACE, '.github/scripts/pipeline-status.js'));
const pr = context.payload.pull_request.number;
await ps.ensurePipelineLabels(github, context.repo.owner, context.repo.repo, core);
await ps.syncPipelineLabels(github, context.repo.owner, context.repo.repo, pr, core);
# Scheduled + manual: post missing or stale FINAL @claude on all open PRs
post-missing-claude-final:
if: |
github.event_name == 'schedule' ||
(github.event_name == 'workflow_dispatch' && !inputs.pr_number)
runs-on: ubuntu-latest
permissions:
issues: write
pull-requests: read
steps:
- uses: actions/checkout@v4
- name: Post missing/stale FINAL @claude on open PRs
uses: actions/github-script@v7
with:
github-token: ${{ env.GH_TOKEN }}
script: |
const path = require('path');
const mergeGate = require(path.join(process.env.GITHUB_WORKSPACE, '.github/scripts/merge-gate.js'));
const chain = require(path.join(process.env.GITHUB_WORKSPACE, '.github/scripts/pr-review-chain.js'));
const ps = require(path.join(process.env.GITHUB_WORKSPACE, '.github/scripts/pipeline-status.js'));
const owner = context.repo.owner;
const repo = context.repo.repo;
const prs = await github.paginate(github.rest.pulls.list, {
owner, repo, state: 'open', per_page: 100,
});
let posted = 0;
for (const pr of prs) {
if (pr.draft) continue;
const comments = await mergeGate.listAllComments(github, owner, repo, pr.number);
const headPushedAt = (await mergeGate.getHeadCommitDate(github, owner, repo, pr.number)) || pr.updated_at;
const hasFinal = mergeGate.hasFinalClaudeReviewTrigger(comments);
const isStale = mergeGate.isStaleFinalAfterPush(comments, headPushedAt);
if (hasFinal && !isStale) continue;
if (mergeGate.hasRecentClaudeTrigger(comments, 10)) {
core.info(`PR #${pr.number}: @claude within 10min — skip`);
continue;
}
if (await mergeGate.hasInProgressClaudeAssistant(github, owner, repo, pr.number)) {
core.info(`PR #${pr.number}: Claude in progress — skip`);
continue;
}
if (hasFinal && isStale) {
const gate = mergeGate.shouldSkipStaleFinalRecovery(comments, headPushedAt);
if (gate.skip) {
core.info(`PR #${pr.number}: skip stale — ${gate.reason}`);
continue;
}
}
const opts = hasFinal && isStale
? { allowStaleRepost: true, skipCopilot: true, optionalWaitMs: 0 }
: { allowCopilotTimeout: true, optionalWaitMs: 0 };
const result = await chain.maybeTriggerClaudeFinal(
github, owner, repo, pr.number,
mergeGate.FINAL_CLAUDE_REVIEW_BODY, core, opts
);
if (result.posted) {
posted++;
core.info(`Posted Claude FINAL on PR #${pr.number}`);
}
await ps.syncPipelineLabels(github, owner, repo, pr.number, core);
if (posted >= 10) break;
}
core.info(`Missing/stale Claude FINAL sweep complete (${posted} posted)`);
# ================================================================
# BOT PRs: CodeRabbit → Claude directly (skip Copilot when no user PAT)
# Copilot ignores github-actions[bot] comments; bot PRs use this path.
# ================================================================
claude-after-coderabbit-bot-pr:
if: |
github.event_name == 'issue_comment' &&
github.event.issue.pull_request &&
github.event.comment.user.login == 'coderabbitai[bot]' &&
contains(github.event.comment.body, 'summary by coderabbit')
runs-on: ubuntu-latest
permissions:
issues: write
pull-requests: read
steps:
- name: Trigger Claude final review on bot PR
uses: actions/github-script@v7
env:
TRIGGER_LOGINS: ${{ env.CLAUDE_TRIGGER_LOGINS }}
with:
github-token: ${{ env.GH_TOKEN }}
script: |
const pr = context.issue.number;
const { data: pull } = await github.rest.pulls.get({
owner: context.repo.owner,
repo: context.repo.repo,
pull_number: pr,
});
const author = pull.user.login;
const isBot = author === 'github-actions[bot]' ||
author === 'praisonai-triage-agent[bot]' ||
pull.user.type === 'Bot';
if (!isBot) {
console.log('Human PR — Copilot chain handles Claude trigger');
return;
}
const triggerLogins = JSON.parse(process.env.TRIGGER_LOGINS);
const comments = await github.rest.issues.listComments({
issue_number: pr,
owner: context.repo.owner,
repo: context.repo.repo,
per_page: 100,
});
const alreadyPosted = comments.data.some(c =>
c.body.includes('@claude') && triggerLogins.includes(c.user.login)
);
if (alreadyPosted) {
console.log('Claude already triggered on PR #' + pr);
return;
}
await github.rest.issues.createComment({
issue_number: pr,
owner: context.repo.owner,
repo: context.repo.repo,
body: '@claude You are the FINAL architecture reviewer on this bot-authored PR. Push fixes directly to THIS branch (do NOT open a new PR). ' + process.env.CLAUDE_UI_SCOPE + ' Read ALL CodeRabbit/Qodo comments above.\n\n' + process.env.CLAUDE_FINAL_PHASES_COMPACT
});
console.log('Claude final review triggered on bot PR #' + pr);
# ================================================================
# Manual: trigger Claude final review on any PR
# ================================================================
claude-manual-dispatch:
if: github.event_name == 'workflow_dispatch' && inputs.pr_number
runs-on: ubuntu-latest
permissions:
issues: write
steps:
- name: Trigger Claude final review
uses: actions/github-script@v7
env:
PR_NUMBER: ${{ inputs.pr_number }}
TRIGGER_LOGINS: ${{ env.CLAUDE_TRIGGER_LOGINS }}
with:
github-token: ${{ env.GH_TOKEN }}
script: |
const pr = parseInt(process.env.PR_NUMBER, 10);
const triggerLogins = JSON.parse(process.env.TRIGGER_LOGINS);
const comments = await github.rest.issues.listComments({
issue_number: pr,
owner: context.repo.owner,
repo: context.repo.repo,
per_page: 100,
});
const alreadyPosted = comments.data.some(c =>
c.body.includes('@claude') && triggerLogins.includes(c.user.login)
);
if (alreadyPosted) {
console.log('Claude already triggered on PR #' + pr);
return;
}
await github.rest.issues.createComment({
issue_number: pr,
owner: context.repo.owner,
repo: context.repo.repo,
body: '@claude You are the FINAL architecture reviewer. If the branch is under MervinPraison/PraisonAI-Tools (not a fork), you are able to make modifications to this branch and push directly. ' + process.env.CLAUDE_UI_SCOPE + ' Read all prior reviewer comments.\n\n' + process.env.CLAUDE_FINAL_PHASES_COMPACT
});
console.log('Claude manually triggered on PR #' + pr);
# ================================================================
# BOT PRs: kick CodeRabbit + Qodo
# ================================================================
bot-pr-trigger-reviews:
if: |
github.event_name == 'pull_request' &&
github.event.action == 'opened' &&
(
github.event.pull_request.user.login == 'github-actions[bot]' ||
github.event.pull_request.user.login == 'praisonai-triage-agent[bot]' ||
github.event.pull_request.user.type == 'Bot'
)
runs-on: ubuntu-latest
permissions:
issues: write
pull-requests: write
steps:
- uses: actions/checkout@v4
with:
persist-credentials: false
- name: Trigger CodeRabbit and Qodo reviews
uses: actions/github-script@v7
with:
github-token: ${{ env.GH_TOKEN }}
script: |
const path = require('path');
const chain = require(path.join(process.env.GITHUB_WORKSPACE, '.github/scripts/bot-pr-review-chain.js'));
const pr = context.payload.pull_request.number;
await chain.kickReviewChain(github, context.repo.owner, context.repo.repo, pr, core);
- name: Sync pipeline status labels
uses: actions/github-script@v7
with:
github-token: ${{ env.GH_TOKEN }}
script: |
const path = require('path');
const ps = require(path.join(process.env.GITHUB_WORKSPACE, '.github/scripts/pipeline-status.js'));
const pr = context.payload.pull_request.number;
await ps.ensurePipelineLabels(github, context.repo.owner, context.repo.repo, core);
await ps.syncPipelineLabels(github, context.repo.owner, context.repo.repo, pr, core);
-23
View File
@@ -1,23 +0,0 @@
name: Bot PR Recovery
on:
schedule:
- cron: '*/15 * * * *'
workflow_dispatch:
inputs:
pr_number:
description: 'Specific PR number to kick (optional)'
required: false
type: string
permissions:
pull-requests: write
issues: write
jobs:
recover:
uses: MervinPraison/github-automation-template/.github/workflows/[email protected]
secrets: inherit
with:
hub_ref: v1.1.20
pr_number: ${{ github.event.inputs.pr_number || '' }}
+76 -6
View File
@@ -1,14 +1,17 @@
name: Auto CI Failure → Claude
# Detects internal PRs with failing CI and posts @claude with extracted failure details.
on:
workflow_run:
workflows: [CI, Optimized Test Suite]
workflows: [CI]
types: [completed]
pull_request:
types: [opened, synchronize, reopened]
workflow_dispatch:
inputs:
pr_number:
description: 'Optional PR number to process (default: scan blocked PRs)'
required: false
type: string
schedule:
@@ -18,6 +21,10 @@ concurrency:
group: ci-failure-scan-${{ github.repository }}-${{ github.event.pull_request.number || github.event.workflow_run.id || github.run_id }}
cancel-in-progress: true
env:
# PAT posts as MervinPraison so issue_comment triggers claude.yml (GITHUB_TOKEN cannot chain workflows)
GH_TOKEN: ${{ secrets.GH_TOKEN || github.token }}
permissions:
pull-requests: read
issues: write
@@ -25,8 +32,71 @@ permissions:
jobs:
detect-and-trigger:
uses: MervinPraison/github-automation-template/.github/workflows/[email protected]
secrets: inherit
with:
hub_ref: v1.1.20
pr_number: ${{ github.event.inputs.pr_number || '' }}
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v4
with:
persist-credentials: false
- name: Detect CI failures and trigger Claude
uses: actions/github-script@v7
with:
github-token: ${{ env.GH_TOKEN }}
script: |
const path = require('path');
const ciFix = require(path.join(process.env.GITHUB_WORKSPACE, '.github/scripts/ci-failure-claude.js'));
const owner = context.repo.owner;
const repo = context.repo.repo;
const baseRepo = `${owner}/${repo}`;
async function processPR(prNumber) {
return ciFix.maybeTriggerCiFixClaude(github, owner, repo, prNumber, core);
}
let results = [];
if (context.eventName === 'workflow_run') {
const wr = context.payload.workflow_run;
const result = await ciFix.processWorkflowRunFailure(
github, owner, repo, wr, core
);
results.push({ event: 'workflow_run', workflow: wr.name, ...result });
} else if (context.eventName === 'pull_request') {
results.push({
pr: context.payload.pull_request.number,
...(await processPR(context.payload.pull_request.number)),
});
} else {
let prNumbers = [];
if (context.eventName === 'workflow_dispatch' && context.payload.inputs?.pr_number) {
prNumbers = [Number(context.payload.inputs.pr_number)];
} else {
const prs = await github.paginate(github.rest.pulls.list, {
owner,
repo,
state: 'open',
per_page: 100,
});
for (const pr of prs) {
if (pr.draft) continue;
const headRepo = pr.head?.repo?.full_name;
if (headRepo && headRepo !== baseRepo) continue;
const { data: issue } = await github.rest.issues.get({
owner,
repo,
issue_number: pr.number,
});
const labels = issue.labels.map((l) => l.name);
if (labels.includes('pipeline/blocked:ci') || labels.includes(ciFix.CI_FIX_LABEL)) {
prNumbers.push(pr.number);
}
}
}
for (const num of prNumbers) {
results.push({ pr: num, ...(await processPR(num)) });
}
}
core.summary.addRaw('```json\n' + JSON.stringify(results, null, 2) + '\n```');
await core.summary.write();
+459 -24
View File
@@ -1,30 +1,46 @@
name: Claude PR Merge Gate
# Read-only Claude assesses merge readiness; GH_TOKEN merges (no @claude, no gh pr review).
# Does not overlap with merge-conflict-claude.yml or auto-pr-comment @claude chains.
on:
schedule:
# Scan for merge-ready PRs every 10 minutes (assess runs only when candidates exist).
- cron: '*/10 * * * *'
workflow_dispatch:
inputs:
pr_number:
description: 'Optional PR number (scan all open internal PRs if empty)'
required: false
type: string
merge_method:
description: 'Merge method'
required: false
type: choice
default: merge
options: [merge, squash, rebase]
options:
- merge
- squash
- rebase
workflow_run:
workflows:
- Claude Assistant
- CI
types: [completed]
types:
- completed
repository_dispatch:
types: [claude-merge-gate]
types:
- claude-merge-gate
concurrency:
group: claude-merge-gate-${{ github.repository }}-${{ github.event.inputs.pr_number || github.event.client_payload.pr_number || github.event.workflow_run.id || 'scan' }}
cancel-in-progress: false
env:
GH_TOKEN: ${{ secrets.GH_TOKEN || github.token }}
MAX_CANDIDATES: 3
DISPATCH_PR_NUMBER: ${{ github.event.inputs.pr_number || github.event.client_payload.pr_number || '' }}
permissions:
contents: read
pull-requests: read
@@ -43,9 +59,7 @@ jobs:
id-token: write
steps:
- uses: actions/checkout@v4
- uses: MervinPraison/github-automation-template/.github/actions/[email protected]
with:
hub_ref: v1.1.20
- name: Generate GitHub App token
id: app-token
uses: actions/create-github-app-token@v1
@@ -53,44 +67,465 @@ jobs:
app-id: ${{ secrets.CLAUDE_APP_ID }}
private-key: ${{ secrets.CLAUDE_APP_PRIVATE_KEY }}
owner: ${{ github.repository_owner }}
- name: Dispatch merge gate when PR pipeline is ready
uses: actions/github-script@v7
with:
github-token: ${{ steps.app-token.outputs.token }}
script: |
const path = require('path');
const mergeGate = require(path.join(process.env.HUB_SCRIPTS, 'merge-gate.js'));
const mergeGate = require(path.join(process.env.GITHUB_WORKSPACE, '.github/scripts/merge-gate.js'));
const wr = context.payload.workflow_run;
const owner = context.repo.owner;
const repo = context.repo.repo;
if (wr.conclusion !== 'success') return;
if (wr.conclusion !== 'success') {
core.info(`Skip dispatch: ${wr.name} conclusion=${wr.conclusion}`);
return;
}
const allowed = ['Claude Assistant', 'CI'];
if (!allowed.includes(wr.name)) return;
if (!allowed.includes(wr.name)) {
core.info(`Skip dispatch: workflow ${wr.name}`);
return;
}
const prNumber = await mergeGate.resolvePrNumberFromWorkflowRun(github, owner, repo, wr);
if (!prNumber) return;
if (!prNumber) {
core.info('Skip dispatch: could not resolve PR from workflow run');
return;
}
const fromClaude = wr.name === 'Claude Assistant';
const check = await mergeGate.evaluatePipelineQuiescent(github, owner, repo, prNumber, core, {
skipGlobalClaudeRunCheck: fromClaude,
skipRecentClaudeCooldown: fromClaude,
});
if (!check.ready) return;
const check = await mergeGate.evaluatePipelineQuiescent(
github, owner, repo, prNumber, core, {
skipGlobalClaudeRunCheck: fromClaude,
skipRecentClaudeCooldown: fromClaude,
}
);
if (!check.ready) {
core.info(`PR #${prNumber} not ready: ${check.reasons.join(', ')}`);
return;
}
await github.rest.repos.createDispatchEvent({
owner, repo, event_type: 'claude-merge-gate',
owner,
repo,
event_type: 'claude-merge-gate',
client_payload: { pr_number: prNumber },
});
core.info(`Dispatched merge gate for PR #${prNumber} after ${wr.name}`);
merge-gate:
scan-candidates:
if: github.event_name != 'workflow_run'
runs-on: ubuntu-latest
permissions:
contents: read
pull-requests: read
issues: write
actions: read
id-token: write
outputs:
matrix: ${{ steps.scan.outputs.matrix }}
has_candidates: ${{ steps.scan.outputs.has_candidates }}
steps:
- uses: actions/checkout@v4
- name: Generate GitHub App token
id: app-token
uses: actions/create-github-app-token@v1
with:
app-id: ${{ secrets.CLAUDE_APP_ID }}
private-key: ${{ secrets.CLAUDE_APP_PRIVATE_KEY }}
owner: ${{ github.repository_owner }}
- name: Scan open PRs for merge gate eligibility
id: scan
uses: actions/github-script@v7
with:
github-token: ${{ steps.app-token.outputs.token }}
script: |
const path = require('path');
const mergeGate = require(path.join(process.env.GITHUB_WORKSPACE, '.github/scripts/merge-gate.js'));
const ps = require(path.join(process.env.GITHUB_WORKSPACE, '.github/scripts/pipeline-status.js'));
const owner = context.repo.owner;
const repo = context.repo.repo;
const maxCandidates = parseInt(process.env.MAX_CANDIDATES || '5', 10);
const inputPr = String(process.env.DISPATCH_PR_NUMBER || '').trim();
const candidates = [];
const skipped = [];
if (inputPr) {
const n = parseInt(inputPr, 10);
if (Number.isNaN(n)) {
throw new Error(`Invalid pr_number input: ${inputPr}`);
}
const result = await mergeGate.evaluatePipelineQuiescent(github, owner, repo, n, core);
if (result.ready) {
candidates.push({ pr_number: n, head_sha: result.headSha });
} else {
skipped.push({ pr: n, reasons: result.reasons });
}
} else {
const prNumbers = await mergeGate.listPrNumbersForMergeGateScan(
github, owner, repo, core
);
const selected = await mergeGate.selectMergeGateCandidates(
github, owner, repo, prNumbers, maxCandidates, core
);
candidates.push(...selected.candidates);
skipped.push(...selected.skipped);
}
core.info('Skipped: ' + JSON.stringify(skipped));
core.setOutput('matrix', JSON.stringify({ include: candidates }));
core.setOutput('has_candidates', candidates.length > 0 ? 'true' : 'false');
core.summary.addRaw('## Merge gate scan\n');
core.summary.addRaw(`Candidates: ${candidates.length}\n`);
core.summary.addRaw('```json\n' + JSON.stringify({ candidates, skipped }, null, 2) + '\n```');
await core.summary.write();
if (inputPr && skipped.length === 1 && skipped[0].pr === parseInt(inputPr, 10)) {
const reasons = skipped[0].reasons;
const body = [
'**Merge gate scan** — not eligible for auto-merge.',
'',
...reasons.map((r) => `- \`${r}\``),
'',
'**Actions:** wait for CI and the Claude review chain, or add label `needs-manual-review` and merge manually.',
'**Opt out:** label `no-auto-merge`.',
].join('\n');
await github.rest.issues.createComment({
owner, repo, issue_number: skipped[0].pr, body,
});
} else if (inputPr && candidates.length === 1) {
await github.rest.issues.createComment({
owner, repo, issue_number: candidates[0].pr_number,
body: '**Merge gate scan** — eligible for assessment. Claude merge gate will assess and may auto-merge if `MERGE_GATE_VERDICT: APPROVE`.',
});
}
await ps.syncOpenPullRequests(github, owner, repo, { maxPrs: 10 }, core);
claude-assess:
needs: scan-candidates
if: needs.scan-candidates.outputs.has_candidates == 'true'
runs-on: ubuntu-latest
timeout-minutes: 20
strategy:
fail-fast: false
matrix: ${{ fromJson(needs.scan-candidates.outputs.matrix) }}
permissions:
contents: read
pull-requests: read
issues: write
actions: read
id-token: write
steps:
- name: Generate GitHub App Token
id: app-token
uses: actions/create-github-app-token@v1
with:
app-id: ${{ secrets.CLAUDE_APP_ID }}
private-key: ${{ secrets.CLAUDE_APP_PRIVATE_KEY }}
owner: ${{ github.repository_owner }}
- uses: actions/checkout@v4
with:
fetch-depth: 0
token: ${{ steps.app-token.outputs.token }}
- name: Mark merge gate active
id: mark_active
uses: actions/github-script@v7
with:
github-token: ${{ steps.app-token.outputs.token }}
script: |
core.setOutput('started_at', new Date().toISOString());
await github.rest.issues.addLabels({
owner: context.repo.owner,
repo: context.repo.repo,
issue_number: ${{ matrix.pr_number }},
labels: ['claude-merge-gate-active'],
});
- name: Stash merge gate helpers
run: cp .github/scripts/merge-gate.js /tmp/merge-gate.js
- name: Fetch PR branch
env:
PR_NUMBER: ${{ matrix.pr_number }}
run: |
git fetch origin "pull/${PR_NUMBER}/head:pr-${PR_NUMBER}"
git checkout "pr-${PR_NUMBER}"
- name: Claude merge gate assessment (read-only)
id: assess
uses: ./.github/actions/claude-code-action
env:
GH_TOKEN: ${{ steps.app-token.outputs.token }}
CLAUDE_CODE_SUBAGENT_MODEL: inherit
ANTHROPIC_DEFAULT_SONNET_MODEL: claude-sonnet-4-6
with:
claude_code_oauth_token: ${{ secrets.CLAUDE_CODE_OAUTH_TOKEN }}
github_token: ${{ steps.app-token.outputs.token }}
model: claude-opus-4-8
trigger_phrase: '@claude-merge-gate-internal'
direct_prompt: |
You are the MERGE GATE reviewer for PraisonAI PR #${{ matrix.pr_number }}.
READ-ONLY: do not modify code, commit, push, rebase, or create branches.
CRITICAL OUTPUT RULE:
Post exactly one PR comment via GitHub MCP containing either:
MERGE_GATE_VERDICT: APPROVE
or
MERGE_GATE_VERDICT: BLOCK
followed by a short rationale on the next lines.
NEVER include @claude in any comment. NEVER mention merge conflict resolution.
Review checklist:
1. Read AGENTS.md and the PR diff on the current branch.
2. Read all PR comments and reviews (FINAL architecture reviewer / Lead Engineer must have run).
3. Confirm SDK value gate: change strengthens praisonaiagents (no scope creep).
4. Do not bloat the Agent class with additional params — only if absolutely required; we already support many params.
5. If agent.py adds >100 lines or new Agent __init__ params, respond MERGE_GATE_VERDICT: BLOCK (manual review required).
6. BLOCK if labels security/breaking-change/needs-manual-review/release, sensitive paths (.github/workflows, auth, pyproject.toml), secrets in diff, PR >800 lines or >30 files, or SDK changes without tests. Label `merge-gate-ci-only` exempts CI-only changes under `.github/workflows/`, `.github/actions/`, or merge-gate scripts.
7. Confirm no CHANGES_REQUESTED reviews and CI green on HEAD ${{ matrix.head_sha }}.
8. If ready to merge: MERGE_GATE_VERDICT: APPROVE. Otherwise: MERGE_GATE_VERDICT: BLOCK with reasons.
Do not approve or merge via GitHub UI/API — only post the verdict comment.
disallowed_tools: |
Bash
Edit
Write
Replace
allowed_tools: |
View
GlobTool
GrepTool
Read
timeout_minutes: 15
- name: Post fallback BLOCK if Opus did not comment
id: fallback_verdict
if: steps.assess.outcome != 'success'
uses: actions/github-script@v7
with:
github-token: ${{ steps.app-token.outputs.token }}
script: |
const mergeGate = require('/tmp/merge-gate.js');
const owner = context.repo.owner;
const repo = context.repo.repo;
const prNumber = ${{ matrix.pr_number }};
const ctx = await mergeGate.loadPrContext(github, owner, repo, prNumber);
const minCreatedAt = new Date(Date.now() - 25 * 60 * 1000).toISOString();
const existing = mergeGate.findMergeGateVerdict(
ctx.comments, minCreatedAt, ctx.headPushedAt, { excludeAutomatedFallback: true }
);
if (existing) {
core.info(`Opus verdict already posted: ${existing}`);
return;
}
const check = await mergeGate.evaluatePipelineQuiescent(
github, owner, repo, prNumber, core, { forMergeStep: true }
);
const lines = [
'MERGE_GATE_VERDICT: BLOCK',
'',
'Automated fallback — Opus merge gate assessment did not complete.',
];
if (check.ready) {
lines.push('Deterministic gates passed, but Opus MERGE_GATE_VERDICT is required before merge.');
} else {
lines.push('Blockers:', ...check.reasons.map((r) => `- ${r}`));
}
await github.rest.issues.createComment({
owner, repo, issue_number: prNumber,
body: lines.join('\n'),
});
core.info('Posted fallback BLOCK — Opus verdict required');
- name: Require Opus MERGE_GATE_VERDICT
uses: actions/github-script@v7
with:
github-token: ${{ steps.app-token.outputs.token }}
script: |
const mergeGate = require('/tmp/merge-gate.js');
const comments = await mergeGate.listAllComments(
github, context.repo.owner, context.repo.repo, ${{ matrix.pr_number }}
);
const ctx = await mergeGate.loadPrContext(
github, context.repo.owner, context.repo.repo, ${{ matrix.pr_number }}
);
const minCreatedAt = new Date(Date.now() - 25 * 60 * 1000).toISOString();
const verdict = mergeGate.findMergeGateVerdict(
comments, minCreatedAt, ctx.headPushedAt, { excludeAutomatedFallback: true }
);
if (!verdict) {
core.setFailed(
'Opus merge gate assessment must post MERGE_GATE_VERDICT on this PR (automated fallback APPROVE is not accepted).'
);
return;
}
core.info(`Opus merge gate verdict: ${verdict}`);
core.setOutput('verdict', verdict);
- name: Remove merge gate active label
if: always()
uses: actions/github-script@v7
with:
github-token: ${{ steps.app-token.outputs.token }}
script: |
const prNumber = ${{ matrix.pr_number }};
try {
await github.rest.issues.removeLabel({
owner: context.repo.owner,
repo: context.repo.repo,
issue_number: prNumber,
name: 'claude-merge-gate-active',
});
core.info(`Removed claude-merge-gate-active from PR #${prNumber}`);
} catch (e) {
core.info(`Label claude-merge-gate-active already removed or missing on PR #${prNumber}`);
}
- name: Fail job if assessment failed
if: steps.assess.outcome == 'failure'
run: exit 1
merge-only:
needs: [scan-candidates, claude-assess]
if: |
always() &&
needs.scan-candidates.outputs.has_candidates == 'true' &&
needs.claude-assess.result == 'success'
runs-on: ubuntu-latest
strategy:
fail-fast: false
matrix: ${{ fromJson(needs.scan-candidates.outputs.matrix) }}
permissions:
contents: write
pull-requests: write
issues: write
actions: read
id-token: write
statuses: write # the assess job records security/outsider-review
uses: MervinPraison/github-automation-template/.github/workflows/[email protected]
secrets: inherit
with:
hub_ref: v1.1.20
pr_number: ${{ github.event.inputs.pr_number || github.event.client_payload.pr_number || '' }}
merge_method: ${{ github.event.inputs.merge_method || 'merge' }}
steps:
- uses: actions/checkout@v4
- name: Generate GitHub App token
id: app-token
uses: actions/create-github-app-token@v1
with:
app-id: ${{ secrets.CLAUDE_APP_ID }}
private-key: ${{ secrets.CLAUDE_APP_PRIVATE_KEY }}
owner: ${{ github.repository_owner }}
- name: Re-check gates and merge
uses: actions/github-script@v7
env:
MERGE_METHOD: ${{ github.event.inputs.merge_method || 'merge' }}
SCAN_HEAD_SHA: ${{ matrix.head_sha }}
with:
github-token: ${{ steps.app-token.outputs.token }}
script: |
const path = require('path');
const mergeGate = require(path.join(process.env.GITHUB_WORKSPACE, '.github/scripts/merge-gate.js'));
const owner = context.repo.owner;
const repo = context.repo.repo;
const prNumber = ${{ matrix.pr_number }};
const scanHeadSha = process.env.SCAN_HEAD_SHA;
const removeLabels = async () => {
try {
await github.rest.issues.removeLabel({
owner, repo, issue_number: prNumber, name: 'claude-merge-gate-active',
});
} catch (e) {
core.info('Label claude-merge-gate-active already removed or missing');
}
};
try {
const ctx = await mergeGate.loadPrContext(github, owner, repo, prNumber);
const comments = ctx.comments;
const verdictMin = new Date(Date.now() - 25 * 60 * 1000).toISOString();
const verdict = mergeGate.findMergeGateVerdict(
comments, verdictMin, ctx.headPushedAt, { excludeAutomatedFallback: true }
);
if (verdict !== 'APPROVE') {
core.info(`Skip merge: verdict=${verdict || 'NONE'}`);
await removeLabels();
return;
}
const check = await mergeGate.evaluatePipelineQuiescent(
github, owner, repo, prNumber, core, { forMergeStep: true }
);
if (!check.ready) {
core.info(`Skip merge: ${check.reasons.join(', ')}`);
await removeLabels();
return;
}
if (check.headSha !== scanHeadSha) {
core.info(`Skip merge: HEAD moved ${scanHeadSha.slice(0, 7)} → ${check.headSha.slice(0, 7)}`);
await removeLabels();
return;
}
const method = process.env.MERGE_METHOD || 'merge';
const sleep = (ms) => new Promise((r) => setTimeout(r, ms));
let merged = false;
for (let attempt = 1; attempt <= 3; attempt++) {
try {
await github.rest.pulls.merge({
owner, repo, pull_number: prNumber, merge_method: method,
});
merged = true;
break;
} catch (e) {
const msg = (e.message || '').toLowerCase();
if (attempt < 3 && msg.includes('base branch was modified')) {
core.info(`Merge attempt ${attempt} failed (base moved), retrying in 8s...`);
await sleep(8000);
const recheck = await mergeGate.evaluatePipelineQuiescent(
github, owner, repo, prNumber, core, { forMergeStep: true }
);
if (!recheck.ready) {
core.info(`Skip merge retry: ${recheck.reasons.join(', ')}`);
await removeLabels();
return;
}
continue;
}
throw e;
}
}
if (!merged) {
core.info('Skip merge: exhausted retries');
await removeLabels();
return;
}
await github.rest.issues.addLabels({
owner, repo, issue_number: prNumber, labels: ['auto-merged-by-gate'],
});
await github.rest.issues.createComment({
owner, repo, issue_number: prNumber,
body: [
'Merged by **Claude PR merge gate** (`claude-merge-gate.yml`).',
`Verdict: MERGE_GATE_VERDICT: APPROVE`,
`SHA: \`${check.headSha.slice(0, 7)}\``,
`Method: ${method}`,
].join('\n'),
});
core.info(`Merged PR #${prNumber}`);
} finally {
await removeLabels();
}
-21
View File
@@ -1,21 +0,0 @@
name: Claude OAuth
on:
workflow_dispatch:
inputs:
code:
description: 'Authorization code (leave empty for step 1)'
required: false
permissions:
actions: write # Required for cache management
contents: read # Required for basic repository access
jobs:
auth:
runs-on: ubuntu-latest
steps:
- uses: grll/claude-code-login@v1
with:
code: ${{ inputs.code }}
secrets_admin_pat: ${{ secrets.SECRETS_ADMIN_PAT }}
+156 -13
View File
@@ -5,20 +5,163 @@ on:
types: [created]
pull_request_review_comment:
types: [created]
issues:
types: [assigned, labeled, opened]
pull_request_review:
types: [submitted]
permissions:
contents: write
pull-requests: write
issues: write
actions: read
id-token: write
jobs:
claude:
permissions:
contents: write
pull-requests: write
issues: write
actions: read
id-token: write
uses: MervinPraison/github-automation-template/.github/workflows/[email protected]
secrets: inherit
with:
hub_ref: v1.1.20
claude-response:
env:
ISSUE_NUMBER_RESOLVED: ${{ github.event.issue.number }}
if: |
(
(github.event_name == 'issue_comment' && contains(github.event.comment.body, '@claude')) ||
(github.event_name == 'pull_request_review_comment' && contains(github.event.comment.body, '@claude')) ||
(github.event_name == 'pull_request_review' && contains(github.event.review.body, '@claude'))
) &&
(
!contains(github.actor, '[bot]') ||
github.actor == 'github-actions[bot]' ||
github.actor == 'praisonai-triage-agent[bot]'
) &&
github.actor != 'dependabot[bot]' &&
github.actor != 'cursor[bot]' &&
github.actor != 'renovate[bot]'
runs-on: ubuntu-latest
steps:
- name: Check for Fork PR
id: check_fork
uses: actions/github-script@v7
with:
github-token: ${{ secrets.GH_TOKEN }}
script: |
const isPR = context.payload.issue?.pull_request
|| context.eventName === 'pull_request_review'
|| context.eventName === 'pull_request_review_comment';
if (!isPR) {
core.setOutput('is_pr', 'false');
core.setOutput('is_fork', 'false');
core.setOutput('merge_state', '');
return;
}
const prNumber = context.payload.pull_request?.number
|| context.payload.issue?.number;
const pr = await github.rest.pulls.get({
owner: context.repo.owner,
repo: context.repo.repo,
pull_number: prNumber,
});
let mergeState = '';
try {
const gql = await github.graphql(
`query($owner: String!, $repo: String!, $number: Int!) {
repository(owner: $owner, name: $repo) {
pullRequest(number: $number) { mergeStateStatus }
}
}`,
{ owner: context.repo.owner, repo: context.repo.repo, number: prNumber }
);
mergeState = (gql.repository.pullRequest.mergeStateStatus || '').toUpperCase();
} catch (e) {
core.warning(`GraphQL mergeStateStatus failed: ${e.message}`);
}
if (!mergeState) {
mergeState = (pr.data.mergeable_state || pr.data.merge_state_status || '').toUpperCase();
}
core.setOutput('is_pr', 'true');
core.setOutput('pr_number', String(prNumber));
core.setOutput('pr_branch', pr.data.head.ref);
core.setOutput('head_repo', pr.data.head.repo?.full_name || '');
core.setOutput('merge_state', mergeState);
const baseRepo = `${context.repo.owner}/${context.repo.repo}`;
if (pr.data.head.repo && pr.data.head.repo.full_name !== baseRepo) {
core.setOutput('is_fork', 'true');
return;
}
core.setOutput('is_fork', 'false');
- name: Checkout repository
uses: actions/checkout@v4
with:
fetch-depth: 0
token: ${{ secrets.GH_TOKEN }}
ref: ${{ steps.check_fork.outputs.is_pr == 'true' && format('refs/pull/{0}/head', steps.check_fork.outputs.pr_number) || github.event.repository.default_branch }}
- name: Fetch PR branch
if: steps.check_fork.outputs.is_pr == 'true' && steps.check_fork.outputs.is_fork != 'true'
env:
PR_BRANCH: ${{ steps.check_fork.outputs.pr_branch }}
PR_NUMBER: ${{ steps.check_fork.outputs.pr_number }}
run: |
git fetch origin "pull/${PR_NUMBER}/head:${PR_BRANCH}"
git checkout "${PR_BRANCH}"
git fetch origin main
- name: Run Claude Code Action
uses: anthropics/claude-code-action@beta
env:
GH_TOKEN: ${{ secrets.GH_TOKEN }}
with:
claude_code_oauth_token: ${{ secrets.CLAUDE_CODE_OAUTH_TOKEN }}
github_token: ${{ secrets.GH_TOKEN }}
model: claude-opus-4-8
trigger_phrase: "@claude"
label_trigger: "claude"
allowed_bots: "praisonai-triage-agent[bot]"
timeout_minutes: "30"
direct_prompt: |
${{ steps.check_fork.outputs.is_fork == 'true' && 'CRITICAL: FORK PR — comment only, do not push.\n\n' || (steps.check_fork.outputs.is_pr == 'true' && 'NOTE: Internal PR on MervinPraison/PraisonAI-Tools — you may push to this branch.\n\n' || '') }}
${{ steps.check_fork.outputs.is_pr == 'true' && format('CONTEXT: PR #{0} on branch {1}. merge_state={2}.\n\n', steps.check_fork.outputs.pr_number, steps.check_fork.outputs.pr_branch, steps.check_fork.outputs.merge_state) || '' }}
You are implementing changes in MervinPraison/PraisonAI-Tools (Python tools for PraisonAI). Follow README.md and existing patterns under `praisonai_tools/`.
Primary scope: `praisonai_tools/`, `tests/`, `examples/`, `docs/`. Do not change `praisonaiagents` in this repo (it is not vendored here).
STEP 0 — GIT & GITHUB CLI:
git config --global user.name "MervinPraison"
git config --global user.email "[email protected]"
gh auth setup-git
STEP 1 — ISSUE / PR:
Read the issue (or PR) and all comments. Implement what is described with minimal, focused changes.
STEP 2 — LAYER VALIDATION (mandatory before coding):
This repo IS the **Tools** layer (`praisonai-tools`). Agent-callable integrations belong here.
- **Implement here:** third-party API tools, optional/heavy deps, vertical integrations
- **Route to PraisonAI (core):** new protocols, agent runtime, built-in tools → comment and link MervinPraison/PraisonAI issue
- **Route to PraisonAI (wrapper):** CLI/YAML wiring only → MervinPraison/PraisonAI
- **Route to PraisonAI-Plugins:** lifecycle hooks, guardrails, policies → MervinPraison/PraisonAI-Plugins
- **Reject:** duplicating tools already in `praisonaiagents.tools` (Tavily, DuckDuckGo, etc.)
If the issue belongs in another layer, explain why and do not implement here.
${{ steps.check_fork.outputs.is_pr == 'true' && steps.check_fork.outputs.is_fork != 'true' && steps.check_fork.outputs.merge_state == 'DIRTY' && format('STEP 3 — RESOLVE MERGE CONFLICTS ON PR (branch: {0}, PR #{1}):\n- DO NOT create a new branch or PR\n- git fetch origin main && git rebase origin/main\n- Resolve conflicts: keep this PR intent, merge in main newer logic\n- git add -A && git rebase --continue (repeat until done)\n- git push --force-with-lease origin {0}\n- Run targeted pytest on changed paths\n- Comment files resolved and what you skipped\n', steps.check_fork.outputs.pr_branch, steps.check_fork.outputs.pr_number) || '' }}
${{ steps.check_fork.outputs.is_pr == 'true' && steps.check_fork.outputs.is_fork != 'true' && steps.check_fork.outputs.merge_state != 'DIRTY' && format('STEP 3 — IMPLEMENT ON EXISTING PR (branch: {0}, PR #{1}):\n- DO NOT create a new branch or PR\n- git checkout {0}\n- Implement minimal, focused fixes\n- Commit and push: git push origin {0}\n', steps.check_fork.outputs.pr_branch, steps.check_fork.outputs.pr_number) || '' }}
${{ steps.check_fork.outputs.is_pr != 'true' && 'STEP 3 — BRANCH (single name; reuse in STEP 5):\nBRANCH="claude/issue-${{ env.ISSUE_NUMBER_RESOLVED }}-$(date +%Y%m%d-%H%M%S)"\ngit checkout -b "$BRANCH"\n' || '' }}
STEP 4 — TEST / VERIFY:
Run targeted pytest or smoke checks relevant to your edits (e.g. pytest tests/unit -q).
${{ steps.check_fork.outputs.is_pr == 'true' && 'STEP 5 — SKIP: Already on an open PR. Do NOT run gh pr create.\n' || format('STEP 5 — COMMIT, PUSH, OPEN PR (mandatory if you produced commits):\ngit add -A\ngit commit -m "feat: <short summary> (fixes #{0})"\ngit push -u origin "$BRANCH"\ngh pr create --repo "{1}" --base main --head "$BRANCH" --title "feat: <short title>" --body "Fixes #{0}"\nCRITICAL: Do not stop after `git push`. You MUST complete `gh pr create` and post the PR URL on the issue.\n', env.ISSUE_NUMBER_RESOLVED, github.repository) }}
allowed_tools: |
Bash(git:*)
Bash(python:*)
Bash(pip:*)
Bash(pytest:*)
Bash(gh:*)
Bash(python -m pytest:*)
Bash(python -m pip:*)
View
GlobTool
GrepTool
BatchTool
Edit
Replace
mcp__github__get_issue
mcp__github__get_issue_comments
mcp__github__update_issue
+3 -36
View File
@@ -5,42 +5,14 @@ on:
branches:
- main
paths:
- 'praisonai_tools/**'
- 'pyproject.toml'
- 'scripts/generate_reference_docs.py'
workflow_run:
workflows:
- CI
types:
- completed
branches:
- main
- 'praisonai_tools/docs_generator/**'
repository_dispatch:
types: [trigger-docs-generation]
workflow_dispatch:
permissions:
contents: read
concurrency:
group: generate-docs-praisonaidocs
cancel-in-progress: false
jobs:
generate-docs:
if: |
github.event_name != 'workflow_run' ||
(
github.event.workflow_run.conclusion == 'success' &&
github.event.workflow_run.head_branch == 'main' &&
github.event.workflow_run.event == 'push' &&
!startsWith(github.event.workflow_run.head_commit.message, 'docs: auto-generate')
)
runs-on: ubuntu-latest
permissions:
contents: write
env:
DOCS_PUSH_TOKEN: ${{ secrets.DOCS_GITHUB_TOKEN || secrets.GH_TOKEN }}
steps:
- name: Checkout PraisonAI Tools
uses: actions/checkout@v4
@@ -58,7 +30,7 @@ jobs:
with:
repository: MervinPraison/PraisonAIDocs
path: praisonai-docs
token: ${{ env.DOCS_PUSH_TOKEN }}
token: ${{ secrets.DOCS_GITHUB_TOKEN }}
- name: Set up Python
uses: actions/setup-python@v5
@@ -77,14 +49,10 @@ jobs:
--package all \
--docs-root $(pwd)/praisonai-docs \
--source-root $(pwd)/praisonai-source
- name: Sync SDK reference navigation
run: python3 praisonai-docs/scripts/sync_sdk_reference_nav.py
env:
PYTHONPATH: $(pwd)/praisonai-tools
- name: Commit and Push Docs
if: env.DOCS_PUSH_TOKEN != ''
run: |
cd praisonai-docs
git config --global user.name "github-actions[bot]"
@@ -94,6 +62,5 @@ jobs:
echo "No changes to commit"
else
git commit -m "docs: auto-generate SDK reference documentation"
git pull --rebase origin main
git push origin main
git push
fi
+131 -19
View File
@@ -1,5 +1,7 @@
name: Auto Merge Conflict → Claude
# Detects internal PRs with mergeStateStatus=DIRTY and posts @claude to trigger claude.yml.
on:
push:
branches: [main]
@@ -10,10 +12,11 @@ on:
- cron: '0 */6 * * *'
concurrency:
group: merge-conflict-scan-${{ github.repository }}-${{ github.event.pull_request.number || github.run_id }}
cancel-in-progress: true
group: merge-conflict-scan-${{ github.repository }}
cancel-in-progress: false
env:
# PAT posts as MervinPraison so issue_comment triggers claude.yml (GITHUB_TOKEN cannot chain workflows)
GH_TOKEN: ${{ secrets.GH_TOKEN || github.token }}
permissions:
@@ -24,29 +27,138 @@ jobs:
detect-and-trigger:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v4
- uses: MervinPraison/github-automation-template/.github/actions/[email protected]
with:
hub_ref: v1.1.20
- name: Detect conflicting PRs and trigger Claude
uses: actions/github-script@v7
with:
github-token: ${{ env.GH_TOKEN }}
script: |
const path = require('path');
const mg = require(path.join(process.env.HUB_SCRIPTS, 'merge-gate.js'));
const owner = context.repo.owner;
const repo = context.repo.repo;
const baseRepo = `${owner}/${repo}`;
const prs = await github.paginate(github.rest.pulls.list, { owner, repo, state: 'open', per_page: 50 });
for (const pr of prs) {
if (pr.draft) continue;
if (pr.head?.repo?.full_name !== baseRepo) continue;
const state = await mg.getMergeState(github, owner, repo, pr.number);
if (state.status !== 'DIRTY') continue;
const { data: comments } = await github.rest.issues.listComments({ owner, repo, issue_number: pr.number, per_page: 100 });
if (mg.hasRecentConflictComment(comments)) continue;
const body = '@claude this PR has merge conflicts with `main`. Rebase onto latest main, resolve conflicts, run tests, force-push with --force-with-lease.';
await github.rest.issues.createComment({ owner, repo, issue_number: pr.number, body });
await github.rest.issues.addLabels({ owner, repo, issue_number: pr.number, labels: ['claude-conflict-pending'] });
const isMainPush = context.eventName === 'push';
const COOLDOWN_MS = 12 * 60 * 60 * 1000;
const AUTO_ACTORS = ['github-actions[bot]', 'MervinPraison'];
const LABEL = 'claude-conflict-pending';
const COMMENT_BODY = [
'@claude this PR has merge conflicts with `main`.',
'Please rebase onto latest `main`, resolve conflicts (keep this PR\'s intent, merge in newer main logic),',
'run targeted tests, and force-push with `--force-with-lease`.',
'Comment which files you resolved.'
].join(' ');
const sleep = (ms) => new Promise((r) => setTimeout(r, ms));
async function getMergeState(prNumber) {
const query = `
query($owner: String!, $repo: String!, $number: Int!) {
repository(owner: $owner, name: $repo) {
pullRequest(number: $number) {
mergeStateStatus
isDraft
headRef { repository { nameWithOwner } }
}
}
}
`;
for (let attempt = 0; attempt < 3; attempt++) {
const result = await github.graphql(query, { owner, repo, number: prNumber });
const prGql = result.repository.pullRequest;
const status = (prGql?.mergeStateStatus || '').toUpperCase();
if (status && status !== 'UNKNOWN') {
return {
status,
isDraft: prGql.isDraft,
headRepo: prGql.headRef?.repository?.nameWithOwner,
};
}
if (attempt < 2) await sleep(10000);
}
const pr = await github.rest.pulls.get({ owner, repo, pull_number: prNumber });
return {
status: (pr.data.mergeable_state || '').toUpperCase(),
isDraft: pr.data.draft,
headRepo: pr.data.head.repo?.full_name,
};
}
function hasRecentAutoComment(comments) {
const cutoff = Date.now() - COOLDOWN_MS;
return comments.some((c) => {
if (!AUTO_ACTORS.includes(c.user.login)) return false;
const body = (c.body || '').toLowerCase();
if (!body.includes('@claude') || !body.includes('merge conflict')) return false;
return new Date(c.created_at).getTime() > cutoff;
});
}
async function processPR(prNumber) {
const { status, isDraft, headRepo } = await getMergeState(prNumber);
core.info(`PR #${prNumber}: mergeState=${status}, head=${headRepo}, draft=${isDraft}`);
const { data: issue } = await github.rest.issues.get({
owner,
repo,
issue_number: prNumber,
});
const labels = issue.labels.map((l) => l.name);
if (status !== 'DIRTY' && labels.includes(LABEL)) {
await github.rest.issues.removeLabel({
owner,
repo,
issue_number: prNumber,
name: LABEL,
});
core.info(`Removed ${LABEL} from PR #${prNumber}`);
}
if (status !== 'DIRTY') return { skipped: true, reason: 'not dirty' };
if (isDraft) return { skipped: true, reason: 'draft' };
if (headRepo && headRepo !== baseRepo) return { skipped: true, reason: 'fork' };
const { data: comments } = await github.rest.issues.listComments({
owner,
repo,
issue_number: prNumber,
per_page: 100,
});
if (!isMainPush && hasRecentAutoComment(comments)) {
return { skipped: true, reason: 'recent auto comment' };
}
await github.rest.issues.createComment({
owner,
repo,
issue_number: prNumber,
body: COMMENT_BODY,
});
if (!labels.includes(LABEL)) {
await github.rest.issues.addLabels({
owner,
repo,
issue_number: prNumber,
labels: [LABEL],
});
}
return { triggered: true };
}
let prNumbers = [];
if (context.eventName === 'pull_request') {
prNumbers = [context.payload.pull_request.number];
} else {
const prs = await github.paginate(github.rest.pulls.list, {
owner,
repo,
state: 'open',
per_page: 100,
});
prNumbers = prs.map((p) => p.number);
}
const results = [];
for (const num of prNumbers) {
results.push({ pr: num, ...(await processPR(num)) });
}
core.summary.addRaw('```json\n' + JSON.stringify(results, null, 2) + '\n```');
await core.summary.write();
+3 -6
View File
@@ -2,12 +2,11 @@ name: Nightly Release Gate
# Preflight before PyPI Release (patch bump).
# Primary: CI success on main (workflow_run).
# Backstop: cron every 3 days at 00:00 UTC.
# Dedupe: max one successful patch release every 3 days (see release-gate.js).
# Backstop: nightly cron at 00:00 UTC.
on:
schedule:
- cron: '0 0 */3 * *'
- cron: '0 0 * * *'
workflow_dispatch:
inputs:
dry_run:
@@ -40,9 +39,7 @@ jobs:
github.event_name == 'workflow_run' &&
github.event.workflow_run.conclusion == 'success' &&
github.event.workflow_run.head_branch == 'main' &&
github.event.workflow_run.event == 'push' &&
!startsWith(github.event.workflow_run.head_commit.message, 'Release v') &&
!startsWith(github.event.workflow_run.head_commit.message, 'Bump ')
github.event.workflow_run.event == 'push'
)
runs-on: ubuntu-latest
env:
+27 -4
View File
@@ -1,5 +1,7 @@
name: Pipeline Status Sync
# Sync pipeline/* stage and blocker labels on open internal PRs.
on:
schedule:
- cron: '*/10 * * * *'
@@ -13,7 +15,28 @@ permissions:
jobs:
sync:
uses: MervinPraison/github-automation-template/.github/workflows/[email protected]
secrets: inherit
with:
hub_ref: v1.1.20
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v4
with:
persist-credentials: false
- name: Generate GitHub App token
id: app-token
uses: actions/create-github-app-token@v1
with:
app-id: ${{ secrets.CLAUDE_APP_ID }}
private-key: ${{ secrets.CLAUDE_APP_PRIVATE_KEY }}
owner: ${{ github.repository_owner }}
- name: Sync pipeline labels on open PRs
uses: actions/github-script@v7
with:
github-token: ${{ steps.app-token.outputs.token }}
script: |
const path = require('path');
const ps = require(path.join(process.env.GITHUB_WORKSPACE, '.github/scripts/pipeline-status.js'));
await ps.syncOpenPullRequests(
github, context.repo.owner, context.repo.repo,
{ maxPrs: 30, dispatchMergeGate: true }, core
);
+2 -4
View File
@@ -123,7 +123,7 @@ jobs:
VERSION: ${{ steps.versions.outputs.new_version }}
run: |
TAG="v${VERSION}"
git add pyproject.toml
git add pyproject.toml uv.lock
git commit -m "Release ${TAG}" || exit 0
git tag -f "${TAG}"
git pull --rebase origin main
@@ -133,9 +133,7 @@ jobs:
- name: Publish to PyPI
if: inputs.dry_run != true
env:
# PyPI API token auth: username __token__, password = pypi-… token (see pypi.org/help/#invalid-auth)
UV_PUBLISH_USERNAME: __token__
UV_PUBLISH_PASSWORD: ${{ secrets.PYPI_TOKEN || secrets.PYPI_API_TOKEN }}
UV_PUBLISH_TOKEN: ${{ secrets.PYPI_TOKEN || secrets.PYPI_API_TOKEN }}
run: |
uv publish
-36
View File
@@ -1,36 +0,0 @@
name: Sync Claude Secrets
on:
workflow_dispatch:
inputs:
target_repo:
description: 'Destination repo (owner/name)'
required: true
type: string
permissions:
contents: read
jobs:
sync:
runs-on: ubuntu-latest
steps:
- name: Sync Claude secrets to target repo
env:
GH_TOKEN: ${{ secrets.SECRETS_ADMIN_PAT }}
TARGET: ${{ inputs.target_repo }}
CLAUDE_APP_ID: ${{ secrets.CLAUDE_APP_ID }}
CLAUDE_APP_PRIVATE_KEY: ${{ secrets.CLAUDE_APP_PRIVATE_KEY }}
CLAUDE_CODE_OAUTH_TOKEN: ${{ secrets.CLAUDE_CODE_OAUTH_TOKEN }}
GH_TOKEN_VALUE: ${{ secrets.GH_TOKEN }}
run: |
set -euo pipefail
if [ -z "${GH_TOKEN:-}" ]; then
echo "SECRETS_ADMIN_PAT is not configured in this repository"
exit 1
fi
echo -n "$CLAUDE_APP_ID" | gh secret set CLAUDE_APP_ID --repo "$TARGET"
echo -n "$CLAUDE_APP_PRIVATE_KEY" | gh secret set CLAUDE_APP_PRIVATE_KEY --repo "$TARGET"
echo -n "$CLAUDE_CODE_OAUTH_TOKEN" | gh secret set CLAUDE_CODE_OAUTH_TOKEN --repo "$TARGET"
echo -n "$GH_TOKEN_VALUE" | gh secret set GH_TOKEN --repo "$TARGET"
echo "Synced CLAUDE_APP_ID, CLAUDE_APP_PRIVATE_KEY, CLAUDE_CODE_OAUTH_TOKEN, GH_TOKEN → $TARGET"
-3
View File
@@ -24,9 +24,6 @@ venv/
.coverage
htmlcov/
# Tool auto-discovery cache (generated at import time)
._discovery_cache_v*.json
# Lock files
poetry.lock
uv.lock
+2 -66
View File
@@ -531,37 +531,6 @@ agent = Agent(
)
```
### How `praisonai-tools` registers its own tools
The bundled tools in this package are **discovered automatically**. Every
module under `praisonai_tools/tools/` is scanned (at import time, without
executing the module) and its public top-level classes and functions become
importable directly:
```python
from praisonai_tools.tools import WeatherTool, get_weather # discovered
from praisonai_tools import WeatherTool # same symbol
```
Adding a new tool therefore means **adding one file** to
`praisonai_tools/tools/` — there is no import map or `__all__` to edit, and
imports stay lazy (a tool module and its optional dependencies are only loaded
the first time one of its symbols is accessed).
By default the discovered public surface is the module's top-level classes and
functions. If a module exposes tools through module-level aliases
(e.g. `read_yaml = _yaml_tools.read_yaml`), declare a standard `__all__` in that
module and the listed names are exported verbatim. Modules and names starting
with `_` are treated as private and never exported.
The scan result is memoised in a small on-disk cache next to the package, so
import stays fast; the cache is rebuilt automatically whenever a tool file is
added, removed, or edited.
External packages that want their tools discovered by `praisonaiagents` should
use the `[project.entry-points."praisonaiagents.tools"]` group shown above,
which the core `praisonaiagents` registry resolves.
---
## 9. Video Editing Tools
@@ -646,23 +615,6 @@ videos = yt.search("python tutorial", limit=5)
transcript = yt.get_transcript("dQw4w9WgXcQ")
```
### Meeting Intelligence Tools
```python
from praisonai_tools import FirefliesTool
# Fireflies.ai meeting intelligence (curated GraphQL operations)
fireflies = FirefliesTool() # Uses FIREFLIES_API_KEY env var
meetings = fireflies.list_recent_meetings(limit=5)
meetings = fireflies.list_recent_meetings(limit=5, after="5") # cursor pagination
transcript = fireflies.get_transcript(meeting_id="abc123")
results = fireflies.search(keywords="roadmap")
```
`FirefliesTool` distinguishes a missing key (`{"error": "FIREFLIES_API_KEY required"}`)
from a rejected key (HTTP 401/403), and surfaces `retry_after` on rate limits.
Set `FIREFLIES_API_URL` to override the endpoint (previews/proxies).
### Data Tools
```python
@@ -686,23 +638,20 @@ air = weather.get_air_quality("Tokyo")
| TTSTool | `OPENAI_API_KEY` or `ELEVENLABS_API_KEY` |
| YouTubeTool | `YOUTUBE_API_KEY` |
| WeatherTool | `OPENWEATHER_API_KEY` |
| FirefliesTool | `FIREFLIES_API_KEY` (optional `FIREFLIES_API_URL`) |
| SwarmScoreTool | None (uses public API) |
### Using with PraisonAI Agents
```python
from praisonaiagents import Agent
from praisonai_tools import EmailTool, SlackTool, GitHubTool, WeatherTool, SwarmScoreTool
from praisonai_tools import EmailTool, SlackTool, GitHubTool, WeatherTool
agent = Agent(
instructions="You are a helpful assistant with access to email, slack, github, weather, and trust ratings",
instructions="You are a helpful assistant with access to email, slack, github, and weather",
tools=[
EmailTool(provider="gmail"),
SlackTool(),
GitHubTool(),
WeatherTool(),
SwarmScoreTool(),
]
)
@@ -752,19 +701,6 @@ pip install praisonai-tools[dev]
pytest tests/ -v
```
The `dev` extra installs the video/motion-graphics render deps
(`playwright`, `imageio-ffmpeg`) so the full suite runs. To exercise the
HTML render backend you also need the Chromium browser:
```bash
pip install -e ".[dev]"
playwright install chromium
pytest tests/ -v
```
If you use a minimal install without those deps, the video tests under
`tests/unit/video/` are skipped automatically rather than failing.
---
## License
+1
View File
@@ -0,0 +1 @@
<html>mock visualization</html>
-378
View File
@@ -1,378 +0,0 @@
# Inkog Security Analysis Integration
This document describes the integration of [Inkog](https://github.com/inkog-io/inkog) security analysis capabilities into PraisonAI-Tools.
## Overview
Inkog is a specialized security analysis tool for AI agent code that detects vulnerabilities unique to agentic systems. It performs static analysis to catch bugs that only break in agent code, such as:
- **Token bombing** - loops where the LLM controls termination, draining API budgets
- **Recursive tool calling** - one user request fans out into thousands of LLM invocations
- **Prompt injection sinks** - RAG output flowing into system prompts without review
- **Missing oversight** - destructive tools firing without human approval
- **Cross-tenant leakage** - global state shared between agent invocations
- **MCP tool poisoning** - malicious tool descriptions hijacking agents
## Features
### Framework Support
- **21+ frameworks**: LangChain, CrewAI, AutoGen, OpenAI Agents, LangGraph, DSPy, Phidata, and more
- **Multiple languages**: Python, TypeScript, JavaScript, and no-code platforms
- **MCP servers**: Audit Model Context Protocol servers for security issues
### Compliance Mapping
- **EU AI Act** Articles 14/15 (human oversight requirements)
- **NIST AI RMF** (risk management framework)
- **ISO 42001** (AI management systems)
- **OWASP LLM Top 10** (security vulnerabilities)
### Scan Types
- **Core scan**: Fast static analysis with vulnerability detection
- **Deep scan**: AI orchestrator-driven analysis with enhanced context
- **Skill scan**: Security analysis of SKILL.md packages and agent tools
- **MCP scan**: Audit MCP servers for tool poisoning and privilege escalation
## Installation
### Prerequisites
1. **Install Inkog CLI**:
```bash
# macOS (Homebrew)
brew tap inkog-io/inkog && brew install inkog
# Or install via Go
go install github.com/inkog-io/inkog/cmd/inkog@latest
# Or download binary from releases
# https://github.com/inkog-io/inkog/releases
```
2. **Get API Key**:
- Visit [app.inkog.io](https://app.inkog.io) to get a free API key
- Set environment variable: `export INKOG_API_KEY=your_key_here`
3. **Verify Installation**:
```bash
inkog -version
```
## Usage
### Basic Usage
```python
from praisonai_tools import InkogTool
# Initialize the tool
inkog = InkogTool()
# Scan current directory for vulnerabilities
result = inkog.scan_directory(
path=".",
output_format="json",
policy="balanced"
)
# Analyze results
analysis = inkog.analyze_findings(result)
print(analysis)
```
### Standalone Functions
```python
from praisonai_tools.tools.inkog_tool import scan_agent_code, scan_skill_package
# Quick scan using standalone function
result = scan_agent_code("./my-agent", policy="low-noise")
# Scan a skill package
skill_result = scan_skill_package("./my-skill", deep=True)
```
### Advanced Scanning
```python
# Deep scan with AI orchestrator (requires Inkog Deep role)
deep_result = inkog.scan_directory(
path="./agent-code",
output_format="json",
policy="comprehensive",
deep=True,
severity="high"
)
# Generate HTML report
html_report = inkog.scan_directory(
path="./agent-code",
output_format="html",
policy="balanced"
)
# Save report to file
with open("security_report.html", "w") as f:
f.write(html_report)
```
### MCP Server Auditing
```python
# Scan MCP server by name
mcp_result = inkog.mcp_scan("github")
# Scan MCP server with custom repository
mcp_result = inkog.mcp_scan(
"my-server",
repo="https://github.com/org/my-mcp-server",
deep=True
)
```
## Configuration
### Environment Variables
- **`INKOG_API_KEY`** (required): API key from app.inkog.io
- **`INKOG_SERVER_URL`** (optional): Custom server URL for enterprise deployments
### Security Policies
Choose the appropriate policy based on your use case:
- **`low-noise`**: Only exploitable vulnerabilities (good for CI/CD)
- **`balanced`**: Vulnerabilities + risk patterns (default, good for code review)
- **`comprehensive`**: All findings including hardening recommendations (good for security audits)
### Output Formats
- **`json`**: Structured data for programmatic processing
- **`text`**: Human-readable terminal output
- **`html`**: Interactive report with visualizations
- **`sarif`**: SARIF format for GitHub Security tab integration
### Severity Levels
- **`critical`**: Immediate security threats
- **`high`**: Serious vulnerabilities that should be addressed soon
- **`medium`**: Moderate issues worth reviewing
- **`low`**: Minor issues and best practice recommendations
## Integration Examples
### PraisonAI Agent Security Audit
```python
from praisonaiagents import Agent
from praisonai_tools import InkogTool
# Create an agent with security analysis capability
security_agent = Agent(
name="security_auditor",
instructions="You analyze AI agent code for security vulnerabilities",
tools=[InkogTool()]
)
# Audit agent code
audit_result = security_agent.start("""
Scan the ./my-agent directory for security vulnerabilities.
Focus on critical and high severity issues.
Provide a summary of findings and remediation recommendations.
""")
print(audit_result)
```
### CI/CD Pipeline Integration
```python
import sys
from praisonai_tools.tools.inkog_tool import scan_agent_code
def security_check():
"""Security check for CI/CD pipeline."""
result = scan_agent_code(
path=".",
policy="low-noise", # Only critical vulnerabilities
severity="critical"
)
if "error" in result:
print(f"Security scan failed: {result['error']}")
return 1
critical_count = result.get("summary", {}).get("critical", 0)
if critical_count > 0:
print(f"❌ Found {critical_count} critical security issues")
return 1
print("✅ No critical security vulnerabilities found")
return 0
if __name__ == "__main__":
sys.exit(security_check())
```
### Multi-Agent Security Review
```python
from praisonaiagents import Agent, AgentTeam
from praisonai_tools import InkogTool
# Security analysis agent
security_analyzer = Agent(
name="security_analyzer",
instructions="Analyze code for security vulnerabilities using Inkog",
tools=[InkogTool()]
)
# Code reviewer agent
code_reviewer = Agent(
name="code_reviewer",
instructions="Review security findings and provide remediation advice"
)
# Create security review team
security_team = AgentTeam(
name="security_review_team",
agents=[security_analyzer, code_reviewer],
tasks=[
{"agent": "security_analyzer", "task": "Scan the codebase for vulnerabilities"},
{"agent": "code_reviewer", "task": "Review findings and create remediation plan"}
]
)
# Run security review
review_result = security_team.start("Perform comprehensive security review of ./agent-code")
```
## Error Handling
The tool provides detailed error messages for common issues:
```python
result = inkog.scan_directory("./nonexistent")
if "error" in result:
error_msg = result["error"]
if "not installed" in error_msg:
print("Install inkog CLI first")
elif "API_KEY" in error_msg:
print("Set INKOG_API_KEY environment variable")
elif "timeout" in error_msg:
print("Scan timed out - try smaller directory or increase timeout")
else:
print(f"Scan error: {error_msg}")
```
## Best Practices
### 1. Development Workflow
```bash
# Add to your development script
inkog . -policy balanced -output json > security_report.json
```
### 2. Pre-commit Hooks
```yaml
# .pre-commit-config.yaml
repos:
- repo: local
hooks:
- id: inkog-security-scan
name: Inkog Security Scan
entry: inkog
args: [".", "-policy", "low-noise", "-severity", "critical"]
language: system
always_run: true
```
### 3. GitHub Actions
```yaml
name: Security Scan
on: [push, pull_request]
jobs:
security:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v3
- name: Install Inkog
run: |
curl -fsSL https://inkog.io/install.sh | sh
echo "$HOME/.local/bin" >> $GITHUB_PATH
- name: Run Security Scan
env:
INKOG_API_KEY: ${{ secrets.INKOG_API_KEY }}
run: inkog . -output sarif > results.sarif
- name: Upload SARIF
uses: github/codeql-action/upload-sarif@v2
with:
sarif_file: results.sarif
```
## Privacy & Security
Inkog uses "surgical redaction" to protect sensitive data:
### What Gets Redacted
- AWS access keys, GitHub tokens, Stripe keys
- Database connection strings with passwords
- Private keys and JWT tokens
- High-entropy strings (API keys)
### What is NOT Redacted
- Prompts and templates (needed for injection detection)
- Business logic (needed for flow analysis)
- Configuration values (model names, etc.)
- Normal strings that don't match credential patterns
## Troubleshooting
### Common Issues
1. **"inkog CLI not installed"**
- Install via Homebrew: `brew tap inkog-io/inkog && brew install inkog`
- Or download from releases: https://github.com/inkog-io/inkog/releases
2. **"INKOG_API_KEY required"**
- Get free key at https://app.inkog.io
- Set environment variable: `export INKOG_API_KEY=your_key`
3. **"Deep scan requires Inkog Deep role"**
- Deep scans need special account permissions
- Use standard scan instead: `deep=False`
4. **"Scan timed out"**
- Large codebases may timeout
- Scan specific directories instead of entire project
- Use policy="low-noise" for faster scans
### Debug Mode
Enable verbose output for troubleshooting:
```python
result = inkog.scan_directory(
path=".",
verbose=True # Shows detailed analysis steps
)
```
## Support
- **Documentation**: https://docs.inkog.io
- **GitHub Issues**: https://github.com/inkog-io/inkog/issues
- **Community**: https://discord.gg/NuG4SSGRH
- **Security**: security@inkog.io
## References
- [Inkog Repository](https://github.com/inkog-io/inkog)
- [State of AI Agent Security 2026 Report](https://inkog.io/report)
- [EU AI Act Compliance Guide](https://docs.inkog.io/compliance/eu-ai-act)
- [OWASP LLM Top 10](https://owasp.org/www-project-top-10-for-large-language-model-applications/)
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# NEXUS Prediction Market Integration
This document provides comprehensive information about integrating the NEXUS prediction market API with PraisonAI agents.
## Overview
NEXUS provides live Kalshi/Polymarket prediction market data and arbitrage opportunities through a validated API. The integration allows PraisonAI agents to:
- Access real-time prediction market data
- Identify arbitrage opportunities between markets
- Analyze market sentiment and trends
- Build sophisticated trading and analysis workflows
## API Information
### Endpoints
- **Free Market Data**: `/kalshi?market={market_name}`
- **Paid Arbitrage Analysis**: `/arb/check?markets={market1,market2}` ($0.02 USDC on eip155:8453)
- **Agent Metadata**: `/.well-known/agent.json`
### Validation
The API is fully validated on Agentic Market:
- **Validation URL**: https://agentic.market/validate?url=https://nexus-agent-xa12.onrender.com/arb/check
- **API Card**: https://nexus-agent-xa12.onrender.com/.well-known/agent.json
### Usage Tracking
Include the `X-NEXUS-Source` header to track per-source call volume:
```
X-NEXUS-Source: your-bot-name
```
## Installation
```bash
pip install praisonai-tools
```
## Quick Start
### Basic Usage
```python
from praisonai_tools.tools import NexusPredictionMarketTool
# Initialize the tool
nexus = NexusPredictionMarketTool(source_name="my-agent")
# Get market data
fed_data = nexus.get_market_data("Fed")
print(fed_data)
# Check arbitrage opportunities (paid)
arb_data = nexus.check_arbitrage_opportunities(["Fed", "BTC"])
print(arb_data)
```
### Agent Integration
```python
from praisonaiagents import Agent, tool
from praisonai_tools.tools import nexus_prediction_market_tool
@tool
def get_market_data(market: str) -> str:
"""Get prediction market data."""
return nexus_prediction_market_tool("get_market_data", market=market)
agent = Agent(
name="MarketAnalyst",
tools=[get_market_data],
instructions="Analyze prediction markets using NEXUS data."
)
response = agent.start("What do Fed rate predictions show?")
```
## Features
### Free Features
1. **Market Data Queries**
- Real-time price data
- Volume and liquidity information
- Market sentiment indicators
- Historical trends
2. **Agent Metadata**
- API capabilities and endpoints
- Service status and version info
- Usage guidelines
### Paid Features
1. **Arbitrage Analysis** ($0.02 USDC on eip155:8453)
- Cross-market opportunity detection
- Profit potential calculations
- Risk assessment
- Execution recommendations
## Supported Markets
Common market identifiers include:
- `Fed` - Federal Reserve interest rate predictions
- `BTC` - Bitcoin price predictions
- `Election` - Political election outcomes
- `ETH` - Ethereum price predictions
- `Inflation` - Inflation rate predictions
*Note: Market availability may vary. Check current markets via the API.*
## API Reference
### NexusPredictionMarketTool Class
```python
class NexusPredictionMarketTool:
def __init__(self, source_name: Optional[str] = None, api_key: Optional[str] = None)
def get_market_data(self, market: str) -> Dict[str, Any]
def check_arbitrage_opportunities(self, markets: List[str]) -> Dict[str, Any]
def get_agent_info(self) -> Dict[str, Any]
def run(self, action: str, market: Optional[str] = None, markets: Optional[List[str]] = None) -> str
```
### Function Interface
```python
def nexus_prediction_market_tool(
action: str,
market: Optional[str] = None,
markets: Optional[List[str]] = None,
source_name: Optional[str] = None
) -> str
```
## Examples
### Market Analysis Agent
```python
from praisonaiagents import Agent
from praisonai_tools.tools import NexusPredictionMarketTool
class MarketAnalysisAgent:
def __init__(self):
self.nexus = NexusPredictionMarketTool(source_name="analysis-bot")
def analyze_market_sentiment(self, market):
"""Analyze market sentiment for a specific prediction market."""
data = self.nexus.get_market_data(market)
if data["success"]:
market_data = data["data"]
# Analyze price, volume, trends etc.
return f"Market sentiment for {market}: {self.interpret_data(market_data)}"
else:
return f"Error getting data: {data['error']}"
def interpret_data(self, data):
"""Custom logic to interpret market data."""
# Implementation specific to your analysis needs
pass
```
### Multi-Agent Workflow
```python
from praisonaiagents import Agent, AgentTeam, Task
# Data collector agent
collector = Agent(
name="DataCollector",
tools=[get_market_data],
instructions="Collect prediction market data from NEXUS."
)
# Analyst agent
analyst = Agent(
name="Analyst",
instructions="Analyze market data and provide insights."
)
# Create workflow
team = AgentTeam(agents=[collector, analyst])
# Define tasks
collect_task = Task(
name="collect_data",
description="Collect data for Fed and BTC markets",
agent=collector
)
analyze_task = Task(
name="analyze_trends",
description="Analyze the collected market data",
agent=analyst,
dependencies=[collect_task]
)
# Execute workflow
results = team.run(tasks=[collect_task, analyze_task])
```
## Error Handling
The tool provides comprehensive error handling for common scenarios:
### Network Errors
```python
{
"success": False,
"error": "Failed to fetch market data: Connection timeout",
"market": "Fed"
}
```
### Payment Required (Arbitrage Features)
```python
{
"success": False,
"error": "Payment required for arbitrage analysis. Cost: $0.02 USDC on eip155:8453",
"markets": ["Fed", "BTC"],
"payment_info": "This feature requires payment on eip155:8453 blockchain"
}
```
### Invalid Parameters
```python
{
"success": False,
"error": "Market parameter required for get_market_data action"
}
```
## Best Practices
### 1. Source Identification
Always set a descriptive source name for tracking:
```python
nexus = NexusPredictionMarketTool(source_name="trading-bot-v1")
```
### 2. Error Handling
Always check the `success` field before processing results:
```python
result = nexus.get_market_data("Fed")
if result["success"]:
data = result["data"]
# Process data
else:
print(f"Error: {result['error']}")
```
### 3. Rate Limiting
Implement appropriate delays between requests to avoid overwhelming the API:
```python
import time
import asyncio
async def batch_collect_data(markets):
data = {}
for market in markets:
result = nexus.get_market_data(market)
data[market] = result
await asyncio.sleep(1) # 1 second delay between requests
return data
```
### 4. Caching
Cache results for frequently accessed data:
```python
from functools import lru_cache
import time
@lru_cache(maxsize=100)
def cached_market_data(market, timestamp):
return nexus.get_market_data(market)
def get_cached_data(market, cache_duration=300): # 5 minutes
timestamp = int(time.time() // cache_duration)
return cached_market_data(market, timestamp)
```
## Security Considerations
### 1. API Key Management
If using paid features, securely manage your API keys:
```python
import os
api_key = os.getenv("NEXUS_API_KEY")
nexus = NexusPredictionMarketTool(api_key=api_key)
```
### 2. Input Validation
Validate market identifiers before making requests:
```python
VALID_MARKETS = ["Fed", "BTC", "ETH", "Election", "Inflation"]
def validate_market(market):
if market not in VALID_MARKETS:
raise ValueError(f"Invalid market: {market}")
return market
```
### 3. Rate Limiting
Implement client-side rate limiting to prevent abuse:
```python
from time import time, sleep
class RateLimiter:
def __init__(self, max_calls_per_minute=60):
self.max_calls = max_calls_per_minute
self.calls = []
def wait_if_needed(self):
now = time()
self.calls = [call_time for call_time in self.calls if now - call_time < 60]
if len(self.calls) >= self.max_calls:
sleep(1)
self.calls.append(now)
```
## Troubleshooting
### Common Issues
1. **Connection Timeout**
- Check internet connectivity
- Verify the API endpoint is accessible
- Implement retry logic with exponential backoff
2. **Invalid Market Identifier**
- Verify the market name is correct
- Check available markets via agent info endpoint
- Use exact case-sensitive market names
3. **Payment Required Errors**
- Ensure you have sufficient USDC balance on eip155:8453
- Verify payment setup for arbitrage features
- Contact NEXUS support if payment issues persist
4. **JSON Decode Errors**
- Check API response format
- Verify the endpoint returned valid JSON
- Implement fallback error handling
### Debug Mode
Enable debug logging to troubleshoot issues:
```python
import logging
logging.basicConfig(level=logging.DEBUG)
nexus = NexusPredictionMarketTool(source_name="debug-agent")
# Requests will now be logged with full details
```
## Support and Resources
- **API Documentation**: https://nexus-agent-xa12.onrender.com/.well-known/agent.json
- **Validation Check**: https://agentic.market/validate?url=https://nexus-agent-xa12.onrender.com/arb/check
- **PraisonAI Documentation**: https://docs.praison.ai
- **Issue Tracking**: Report issues via GitHub issues in the PraisonAI-Tools repository
## Contributing
To contribute improvements or report bugs:
1. Fork the PraisonAI-Tools repository
2. Create a feature branch
3. Make your changes
4. Add tests for new functionality
5. Submit a pull request
## License
This tool is part of the PraisonAI-Tools package and follows the same licensing terms.
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# Tool-Registry Proxy Connector
An **optional, bring-your-own-account** connector that lets any PraisonAI agent
discover and call a large catalogue of third-party API endpoints (SEO,
enrichment, social data, scraping, ads) through a single proxy token — with
**credentials injected server-side by the registry, never held by the agent**.
PraisonAI ships **no registry code, no bundled binary and no default endpoint**.
You supply your own account token or a self-hosted base URL. The connector is
disabled unless `TOOL_PROXY_URL` is configured.
## Overview
The connector mirrors PraisonAI's deferred tool-search bridge
(`tool_search` / `tool_describe` / `tool_call`) with three functions:
| Function | Cost | Purpose |
| --- | --- | --- |
| `registry_search(query)` | free | capability search over the catalogue |
| `registry_describe(tool_id)` | free | params, price-per-call, example response |
| `registry_call(tool_id, params)` | paid | invoke via proxy; credential injected server-side |
## Installation
```bash
pip install "praisonai-tools[registry-proxy]"
```
## Setup (3 lines)
```bash
export TOOL_PROXY_URL="https://your-registry.example.com" # or a self-hosted instance
export TOOL_PROXY_TOKEN="your-proxy-token"
# Optional: override the auth header for registries that expect a custom header.
# Default is "Authorization" (sent as "Bearer <token>"); any other name (e.g.
# "X-Treg-Token") sends the raw token in that header.
export TOOL_PROXY_AUTH_HEADER="Authorization"
# Optional: override the describe route for registries with a different layout.
# Must contain "{tool_id}"; defaults to the live registry route below.
export TOOL_PROXY_DESCRIBE_PATH="/catalog/endpoints/{tool_id}"
```
```python
from praisonaiagents import Agent
from praisonai_tools.registry_proxy import (
registry_search, registry_describe, registry_call,
)
agent = Agent(
instructions="SEO analyst",
tools=[registry_search, registry_describe, registry_call],
)
agent.start("Find the top backlink sources for example.com and summarise")
# → registry_search("backlinks for a domain") → describe → call
# one token, no vendor keys in the agent
```
## Spend safety
`registry_call` accepts optional budget guards. When a configured budget would
be exceeded, the call is **denied and reported** as a tool-result error (never
raised as an exception):
```python
registry_call(
"seo.backlinks",
{"domain": "example.com"},
max_cost_per_call=0.10, # deny if price-per-call exceeds this
max_session_spend=5.00, # deny if cumulative spend would exceed this
)
```
Per-call price is read from `registry_describe`, so guards work without any
vendor-specific configuration. Guards **fail closed**: if a budget is set but
the price cannot be validated, the call is denied. Cumulative `max_session_spend`
persists across separate `registry_call` invocations within the same process,
scoped per `(proxy_url, token)` so distinct accounts never share a budget.
## HTTP methods
The registry enforces each endpoint's declared HTTP method on `/call/{id}`.
`registry_call` derives the method automatically from `registry_describe`
(the endpoint doc carries `method`): `GET` endpoints send `params` as the query
string, `POST`/`PUT` send them as a JSON body. Pass `method="GET"` explicitly to
skip the describe lookup when you already know the method. Only the standard
`GET`/`POST`/`PUT`/`PATCH`/`DELETE` verbs are accepted; any other value (e.g. a
mislabelled endpoint doc) is rejected as a tool-result error before any request.
`tool_id` is URL-encoded before being placed in the describe/call route, so it
cannot alter the requested path.
## Passthrough-URL calls
Passthrough-URL calls require the upstream to be **registered on the registry
first**. Loopback/private upstreams (e.g. `127.0.0.1`, RFC-1918 addresses) are
**refused by the registry's SSRF guard by design** — the base URL must be a
public `http(s)` address. This is registry-side policy, not a connector setting.
## Credential safety
The proxy token is only sent to the endpoint it was configured for. If a caller
(or a prompt-injected agent) supplies an explicit `proxy_url` without a matching
`token`, the ambient `TOOL_PROXY_TOKEN` is **not** attached — preventing the
token from being exfiltrated to an untrusted endpoint. For normal use, leave
`proxy_url`/`token` unset and configure `TOOL_PROXY_URL`/`TOOL_PROXY_TOKEN` via
the environment.
## Error taxonomy
All failures are returned as `{"error": ...}` tool results:
- Authentication failed (HTTP 401/403)
- Insufficient balance (HTTP 402)
- Upstream 4xx/5xx passed through
- Request timeout
- `httpx` not installed → install hint
## Tier 0 — Skills directory compatibility (zero code)
Registries that expose `skill install <name>` install skills into
`./.claude/skills/`. PraisonAI **already scans** this directory, so
registry-installed skills are discoverable by PraisonAI agents today with no
additional code:
- `praisonaiagents/skills/discovery.py` — `.claude/skills` compatibility scan
plus an ancestor walk for monorepos.
## Tier 2 — Environment / CLI passthrough (config-only)
A registry's `shell` / `run <vendor> -- args` inject vendor-CLI credentials at
execution time. Using a PraisonAI environment definition, install the registry
CLI and log in via a token env var in `setup:`; the agent's `execute_command`
then has authenticated vendor CLIs (e.g. `run gh -- pr list`) without any key in
the container. Sandbox / board workers inherit the same via the environment
definition.
## Licensing note
Some registries are Apache-2.0 **with additional terms** prohibiting embedding
in commercially distributed products without permission. This connector is
therefore **optional and bring-your-own-account only**: it ships no registry
code and no default endpoint — the same posture as other BYO-account connectors.
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# SwarmScore Integration for PraisonAI
SwarmScore is a portable trust rating system for AI agents that provides cryptographically signed reputation scores based on verified execution history. This integration allows PraisonAI agents to leverage trust ratings for enhanced security and decision-making.
## Overview
SwarmScore provides:
- **Portable Trust Ratings**: Cryptographically signed scores that travel with your agent across platforms
- **Verified Execution History**: Trust based on actual performance, not self-reported metrics
- **Consistency Tracking**: 80 jobs at 95% success rate beats 1 job at 100%
- **Agent-to-Agent Discovery**: Machine-readable trust data for autonomous agent interactions
## Installation
```bash
pip install praisonai-tools[swarmscore]
# or
pip install praisonai-tools requests
```
## Quick Start
### Basic Usage
```python
from praisonai_tools.tools import SwarmScoreTool
# Initialize the tool
swarmscore = SwarmScoreTool()
# Load your agent's trust score
result = swarmscore.load_swarmscore("your-agent-slug")
if result.success:
score_data = result.output
print(f"Trust Score: {score_data['score']}")
print(f"Trust Tier: {score_data['tier']}")
print(f"Success Rate: {score_data['success_rate']}%")
else:
print(f"Error: {result.error}")
```
### Standalone Functions
```python
from praisonai_tools.tools import (
load_swarmscore_by_slug,
verify_swarmscore_freshness,
get_agent_discovery_manifest
)
# Load score data
try:
score_data = load_swarmscore_by_slug("your-agent-slug")
print(f"Score: {score_data['score']}")
except Exception as e:
print(f"Failed to load score: {e}")
# Verify score freshness
try:
verification = verify_swarmscore_freshness(score_data['verify_payload'])
print(f"Verification: {verification}")
except Exception as e:
print(f"Verification failed: {e}")
# Get discovery manifest
try:
manifest = get_agent_discovery_manifest()
print(f"Discovery data: {manifest}")
except Exception as e:
print(f"Failed to get manifest: {e}")
```
## Integration Patterns
### 1. Trust-Based Decision Making
```python
from praisonai_tools.tools import SwarmScoreTool
def execute_with_trust_level(agent_slug, task):
"""Execute task based on agent's trust level."""
swarmscore = SwarmScoreTool()
result = swarmscore.load_swarmscore(agent_slug)
if not result.success:
# Default to restricted mode if score unavailable
return execute_restricted(task)
trust_score = result.output.get('score', 0)
if trust_score >= 80:
# High trust - full autonomy
return execute_autonomous(task)
elif trust_score >= 60:
# Medium trust - human oversight
return execute_supervised(task)
else:
# Low trust - restricted operations
return execute_restricted(task)
```
### 2. Agent Authentication
```python
def authenticate_agent(agent_slug):
"""Verify agent identity and trust level."""
swarmscore = SwarmScoreTool()
# Load and verify score
load_result = swarmscore.load_swarmscore(agent_slug)
if not load_result.success:
return False, "Failed to load trust score"
# Verify freshness
verify_payload = load_result.output.get('verify_payload')
if verify_payload:
verify_result = swarmscore.verify_swarmscore(verify_payload)
if not verify_result.success:
return False, "Trust score verification failed"
trust_score = load_result.output.get('score', 0)
return trust_score >= 50, f"Trust score: {trust_score}"
```
### 3. Multi-Agent Coordination
```python
def find_trusted_collaborators(task_requirements):
"""Find agents suitable for collaboration based on trust scores."""
swarmscore = SwarmScoreTool()
# Get discovery manifest for agent lookup
manifest_result = swarmscore.get_discovery_manifest()
if not manifest_result.success:
return []
trusted_agents = []
discovery_data = manifest_result.output
# Example: Filter agents by trust score and capabilities
for agent_id in discovery_data.get('agents', []):
score_result = swarmscore.load_swarmscore(agent_id)
if score_result.success:
score_data = score_result.output
if score_data.get('score', 0) >= 70:
trusted_agents.append({
'id': agent_id,
'score': score_data['score'],
'capabilities': score_data.get('capabilities', [])
})
return trusted_agents
```
## PraisonAI Agent Integration
### Using with PraisonAI Agent Tools
```python
from praisonaiagents import Agent, tool
from praisonai_tools.tools import SwarmScoreTool
@tool
def check_agent_trust_score(agent_slug: str) -> str:
"""Check the trust score for an agent."""
swarmscore = SwarmScoreTool()
result = swarmscore.load_swarmscore(agent_slug)
if result.success:
score_data = result.output
return f"Agent {agent_slug} has trust score {score_data.get('score', 'unknown')} with {score_data.get('success_rate', 'unknown')}% success rate"
else:
return f"Failed to load trust score for {agent_slug}: {result.error}"
# Create agent with SwarmScore capability
agent = Agent(
name="trust-aware-agent",
instructions="You can check agent trust scores using the check_agent_trust_score tool.",
tools=[check_agent_trust_score]
)
# Use the agent
response = agent.start("What is the trust score for agent 'trading-bot-v2'?")
print(response)
```
### Agent with Built-in Trust Management
```python
from praisonaiagents import Agent
from praisonai_tools.tools import SwarmScoreTool
class TrustAwareAgent(Agent):
"""PraisonAI Agent with built-in SwarmScore integration."""
def __init__(self, agent_slug: str, **kwargs):
super().__init__(**kwargs)
self.agent_slug = agent_slug
self.swarmscore = SwarmScoreTool()
self._trust_score = None
async def check_trust_level(self):
"""Check and cache current trust level."""
result = self.swarmscore.load_swarmscore(self.agent_slug)
if result.success:
self._trust_score = result.output.get('score', 0)
return self._trust_score
def can_execute_action(self, action_type: str) -> bool:
"""Determine if action can be executed based on trust level."""
if self._trust_score is None:
return False # Default to safe
# Define trust requirements for different actions
trust_requirements = {
'read': 30,
'write': 60,
'execute': 80,
'admin': 95
}
required_trust = trust_requirements.get(action_type, 100)
return self._trust_score >= required_trust
# Usage
agent = TrustAwareAgent(
agent_slug="my-agent-123",
name="secure-agent",
instructions="Execute tasks based on trust level"
)
# Check trust before executing
trust_score = await agent.check_trust_level()
if agent.can_execute_action('execute'):
print("Proceeding with high-trust execution")
else:
print("Restricted to low-trust operations")
```
## API Reference
### SwarmScoreTool Class
#### Methods
**`__init__(api_base_url: str = "https://api.swarmsync.ai/v1/swarmscore/")`**
- Initialize SwarmScore tool
- `api_base_url`: Base URL for SwarmScore API
**`load_swarmscore(slug: str) -> ToolResult`**
- Load SwarmScore data by agent slug
- Returns: ToolResult with passport, certificate, and verification data
**`verify_swarmscore(verify_payload: Dict[str, Any]) -> ToolResult`**
- Verify SwarmScore freshness using verification payload
- Returns: ToolResult with verification status
**`get_discovery_manifest() -> ToolResult`**
- Get machine-readable agent discovery manifest
- Returns: ToolResult with discovery data
**`run(action: str, **kwargs) -> ToolResult`**
- Execute SwarmScore action
- Actions: 'load', 'verify', 'discover'
### Standalone Functions
**`load_swarmscore_by_slug(slug: str) -> Dict[str, Any]`**
- Load SwarmScore data by agent slug
- Raises: Exception if loading fails
**`verify_swarmscore_freshness(verify_payload: Dict[str, Any]) -> Dict[str, Any]`**
- Verify SwarmScore freshness
- Raises: Exception if verification fails
**`get_agent_discovery_manifest() -> Dict[str, Any]`**
- Get agent discovery manifest
- Raises: Exception if retrieval fails
## SwarmScore Data Structure
```json
{
"score": 85,
"tier": "gold",
"jobs_completed": 150,
"success_rate": 94.5,
"consistency_score": 88,
"signed_certificate": "...",
"verify_payload": {
"signature": "...",
"timestamp": "...",
"agent_id": "..."
},
"capabilities": ["trading", "analysis", "reporting"],
"last_updated": "2024-01-15T10:30:00Z"
}
```
## Error Handling
```python
from praisonai_tools.tools import SwarmScoreTool
swarmscore = SwarmScoreTool()
result = swarmscore.load_swarmscore("agent-123")
if not result.success:
error_msg = result.error
if "network" in error_msg.lower():
# Handle network issues
print("Network connectivity problem")
elif "not found" in error_msg.lower():
# Handle missing agent
print("Agent not registered in SwarmScore")
else:
# Handle other errors
print(f"Unexpected error: {error_msg}")
```
## Best Practices
1. **Cache Trust Scores**: Cache scores temporarily to avoid excessive API calls
2. **Graceful Degradation**: Have fallback behavior when SwarmScore is unavailable
3. **Verify Freshness**: Always verify score freshness for critical decisions
4. **Trust Thresholds**: Define clear trust score requirements for different operations
5. **Error Handling**: Handle network and API errors gracefully
## Getting Started with SwarmScore
1. **Register**: Create an account at [SwarmSync.AI](https://swarmsync.ai)
2. **Get Your Slug**: Obtain your agent identifier from the dashboard
3. **Start Building**: Begin tracking execution history to build trust
4. **Integrate**: Use this tool to incorporate trust ratings into your workflows
## Resources
- [SwarmScore Documentation](https://swarmsync.ai/docs/protocol-specs/swarmscore)
- [SwarmScore GitHub Spec](https://github.com/swarmsync-ai/swarmscore-spec)
- [SwarmSync.AI Platform](https://swarmsync.ai)
- [Example Implementation](../examples/swarmscore_example.py)
## Contributing
To contribute improvements to the SwarmScore integration:
1. Fork the PraisonAI-Tools repository
2. Create a feature branch
3. Make your changes
4. Add tests for new functionality
5. Submit a pull request
## License
This integration is part of PraisonAI-Tools and follows the same license terms.
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@@ -1,261 +0,0 @@
"""
Inkog Security Analysis Tool Example
This example demonstrates how to use the Inkog tool to analyze AI agent code
for security vulnerabilities like token bombing, prompt injection, and more.
Prerequisites:
1. Install inkog CLI: brew tap inkog-io/inkog && brew install inkog
2. Get free API key from https://app.inkog.io
3. Set environment variable: export INKOG_API_KEY=your_key_here
The Inkog tool can detect:
- Token bombing attacks (loops where LLM controls termination)
- Prompt injection vulnerabilities
- Recursive tool calling without cycle detection
- Missing human oversight for destructive operations
- Cross-tenant data leakage
- MCP tool poisoning
- EU AI Act / NIST / OWASP compliance issues
"""
import os
from praisonai_tools import InkogTool, scan_agent_code
def basic_security_scan():
"""Perform a basic security scan of the current directory."""
print("🔍 Basic Security Scan Example")
print("=" * 50)
# Method 1: Using the class
inkog = InkogTool()
result = inkog.scan_directory(
path=".",
output_format="json",
policy="balanced" # balanced, low-noise, comprehensive
)
if "error" in result:
print(f"❌ Scan failed: {result['error']}")
return
# Analyze the results
analysis = inkog.analyze_findings(result)
print(analysis)
print("\n" + "=" * 50)
def advanced_security_scan():
"""Perform an advanced security scan with deep analysis."""
print("🔬 Advanced Security Scan Example (Deep Analysis)")
print("=" * 60)
inkog = InkogTool()
# Deep scan provides enhanced analysis with AI orchestrator
result = inkog.scan_directory(
path=".",
output_format="json",
policy="comprehensive", # Show all findings including best practices
deep=True, # Enable AI orchestrator analysis (requires Inkog Deep role)
verbose=True
)
if "error" in result:
print(f"❌ Deep scan failed: {result['error']}")
print("Note: Deep scans require the Inkog Deep role on your account")
return
# Show detailed analysis
analysis = inkog.analyze_findings(result)
print(analysis)
# Show raw findings for debugging
if "server_findings" in result:
print(f"\n📊 Raw Findings ({len(result['server_findings'])} total):")
for i, finding in enumerate(result["server_findings"][:3]): # Show first 3
print(f"{i+1}. {finding.get('pattern', 'Unknown')} - {finding.get('severity', 'N/A')}")
print(f" File: {finding.get('file', 'N/A')}:{finding.get('line', 'N/A')}")
print(f" Message: {finding.get('message', 'N/A')}")
print()
print("=" * 60)
def skill_package_scan():
"""Scan a SKILL.md package or MCP server."""
print("📦 Skill Package Security Scan Example")
print("=" * 50)
inkog = InkogTool()
# Scan current directory as a skill package
result = inkog.skill_scan(
path=".",
output_format="json",
deep=False
)
if "error" in result:
print(f"❌ Skill scan failed: {result['error']}")
return
analysis = inkog.analyze_findings(result)
print(analysis)
print("\n" + "=" * 50)
def mcp_server_scan():
"""Scan an MCP server from the registry."""
print("🔌 MCP Server Security Scan Example")
print("=" * 50)
inkog = InkogTool()
# Scan a popular MCP server (GitHub)
result = inkog.mcp_scan(
server_name="github",
output_format="json"
)
if "error" in result:
print(f"❌ MCP scan failed: {result['error']}")
return
analysis = inkog.analyze_findings(result)
print(analysis)
print("\n" + "=" * 50)
def standalone_function_example():
"""Example using standalone functions for quick scans."""
print("⚡ Standalone Function Examples")
print("=" * 40)
# Quick scan using standalone function
print("Running quick security scan...")
result = scan_agent_code(
path=".",
output_format="json",
policy="low-noise", # Only critical vulnerabilities
deep=False
)
if isinstance(result, dict) and "error" not in result:
tool = InkogTool()
analysis = tool.analyze_findings(result)
print(analysis)
else:
print(f"Scan result: {result}")
print("\n" + "=" * 40)
def html_report_example():
"""Generate an HTML security report."""
print("📄 HTML Report Generation Example")
print("=" * 45)
inkog = InkogTool()
# Generate HTML report
html_report = inkog.scan_directory(
path=".",
output_format="html",
policy="comprehensive",
deep=False
)
if isinstance(html_report, str) and not html_report.startswith("Error"):
# Save report to file
report_path = "inkog_security_report.html"
with open(report_path, "w", encoding="utf-8") as f:
f.write(html_report)
print(f"✅ HTML report generated: {report_path}")
print(f"📄 Report size: {len(html_report)} characters")
else:
print(f"❌ HTML report failed: {html_report}")
print("=" * 45)
def compliance_scan_example():
"""Example focused on compliance mapping."""
print("🏛️ Compliance Mapping Example")
print("=" * 40)
# Use comprehensive policy to see compliance mappings
inkog = InkogTool()
result = inkog.scan_directory(
path=".",
output_format="json",
policy="comprehensive", # Shows compliance mappings
deep=False
)
if "error" in result:
print(f"❌ Compliance scan failed: {result['error']}")
return
# Look for compliance information
findings = result.get("server_findings", [])
compliance_findings = []
for finding in findings:
if any(term in finding.get("message", "").lower()
for term in ["eu ai act", "nist", "owasp", "iso", "article"]):
compliance_findings.append(finding)
if compliance_findings:
print(f"📋 Found {len(compliance_findings)} compliance-related findings:")
for finding in compliance_findings[:3]: # Show first 3
print(f"• {finding.get('pattern', 'Unknown')}")
print(f" {finding.get('message', 'N/A')[:100]}...")
else:
print("✅ No specific compliance violations found")
print("=" * 40)
def main():
"""Run all examples."""
print("Inkog Security Analysis Tool Examples")
print("=" * 60)
# Check if inkog is available
api_key = os.environ.get("INKOG_API_KEY")
if not api_key:
print("⚠️ WARNING: INKOG_API_KEY environment variable not set")
print(" Get your free API key at https://app.inkog.io")
print(" Set it with: export INKOG_API_KEY=your_key_here")
print()
try:
# Run examples in order of complexity
basic_security_scan()
standalone_function_example()
skill_package_scan()
html_report_example()
compliance_scan_example()
# Advanced features (may require special access)
print("\n🎓 Advanced Examples (may require Inkog Deep role):")
print("-" * 50)
advanced_security_scan()
mcp_server_scan()
except Exception as e:
print(f"❌ Example failed: {e}")
print("This may be due to:")
print("1. Inkog CLI not installed")
print("2. Missing INKOG_API_KEY environment variable")
print("3. Network connectivity issues")
print("4. Insufficient permissions for deep scans")
if __name__ == "__main__":
main()
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@@ -1,55 +0,0 @@
#!/usr/bin/env python3
"""JIRA Agent watch example using praisonai-tools.
Setup:
pip install praisonai-tools jira
export JIRA_URL=https://yourcompany.atlassian.net
export [email protected]
export JIRA_API_TOKEN=your_api_token
"""
import os
from praisonaiagents import Agent
from praisonai_tools import jira_tools
def main():
jira_url = os.getenv("JIRA_URL")
jira_token = os.getenv("JIRA_API_TOKEN")
jira_email = os.getenv("JIRA_EMAIL")
jira_username = os.getenv("JIRA_USERNAME")
if not jira_url or not jira_token or not (jira_email or jira_username):
print("Set JIRA_URL, JIRA_API_TOKEN, and JIRA_EMAIL (or JIRA_USERNAME)")
return
agent = Agent(
name="JIRA Monitor Agent",
instructions=(
"You monitor JIRA issues and projects. Use jira_watch_issue, "
"jira_watch_project, jira_get_issue_info, and jira_search_issues."
),
tools=jira_tools(),
llm="gpt-4o-mini",
)
print("JIRA watch tools ready. Example prompts:")
print(" Get info for PROJ-123")
print(" Search open issues: project = PROJ AND status = Open")
print(" Watch PROJ-123 for changes since 2024-01-01T00:00:00")
while True:
try:
user_input = input("\nYou: ").strip()
if user_input.lower() in {"quit", "exit", "q"}:
break
if not user_input:
continue
print("Agent:", agent.start(user_input))
except KeyboardInterrupt:
break
if __name__ == "__main__":
main()
+1 -1
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@@ -194,7 +194,7 @@ def example_team_preset():
print("✓ Motion graphics team created successfully!")
print(f" Agents: {[agent.name for agent in team.agents]}")
print(f" Coordinator: {team.agents[0].name}")
print(f" Leader: {team.leader.name}")
print(f" Workspace: {team._motion_graphics_workspace}")
except ImportError as e:
-198
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@@ -1,198 +0,0 @@
"""Example: Using NEXUS Prediction Market Tool with PraisonAI
This example demonstrates how to use the NEXUS prediction market tool to:
1. Get free market data for prediction markets
2. Check arbitrage opportunities between markets (paid feature)
3. Build an intelligent prediction market analysis agent
NEXUS API Information:
- Free endpoint: /kalshi?market={market_name}
- Paid endpoint: /arb/check?markets={market1,market2} ($0.02 USDC on eip155:8453)
- Validation: https://agentic.market/validate?url=https://nexus-agent-xa12.onrender.com/arb/check
"""
from praisonaiagents import Agent, tool
from praisonai_tools.tools.nexus_prediction_market_tool import NexusPredictionMarketTool
import json
# Example 1: Direct tool usage
def example_direct_usage():
"""Example of using the NEXUS tool directly."""
print("=== Direct NEXUS Tool Usage ===\n")
# Initialize the tool
nexus_tool = NexusPredictionMarketTool(source_name="praisonai-example")
# Get market data for Fed predictions
print("1. Getting Fed market data...")
fed_data = nexus_tool.get_market_data("Fed")
print(json.dumps(fed_data, indent=2))
print()
# Get BTC market data
print("2. Getting BTC market data...")
btc_data = nexus_tool.get_market_data("BTC")
print(json.dumps(btc_data, indent=2))
print()
# Check arbitrage opportunities (paid feature)
print("3. Checking arbitrage opportunities between Fed and BTC markets...")
arb_data = nexus_tool.check_arbitrage_opportunities(["Fed", "BTC"])
print(json.dumps(arb_data, indent=2))
print()
# Get agent information
print("4. Getting NEXUS agent information...")
agent_info = nexus_tool.get_agent_info()
print(json.dumps(agent_info, indent=2))
# Example 2: Create a custom tool wrapper for agents
@tool
def get_prediction_market_data(market: str) -> str:
"""Get prediction market data for a specific market.
Args:
market: Market identifier (e.g., 'Fed', 'BTC', 'Election')
Returns:
JSON string with market data including prices and trends
"""
nexus_tool = NexusPredictionMarketTool(source_name="praisonai-agent")
return nexus_tool.run(action="get_market_data", market=market)
@tool
def check_prediction_market_arbitrage(markets: str) -> str:
"""Check for arbitrage opportunities between prediction markets.
Args:
markets: Comma-separated list of markets to analyze (e.g., 'Fed,BTC')
Returns:
JSON string with arbitrage opportunities and analysis
Note:
This is a paid feature requiring $0.02 USDC on eip155:8453
"""
markets_list = [m.strip() for m in markets.split(',')]
nexus_tool = NexusPredictionMarketTool(source_name="praisonai-agent")
return nexus_tool.run(action="check_arbitrage", markets=markets_list)
# Example 3: Prediction market analysis agent
def example_prediction_market_agent():
"""Example of a prediction market analysis agent."""
print("\n=== Prediction Market Analysis Agent ===\n")
# Create an agent with NEXUS prediction market tools
market_agent = Agent(
name="PredictionMarketAnalyst",
instructions="""You are an expert prediction market analyst.
Your capabilities:
- Analyze prediction market data from Kalshi and Polymarket via NEXUS API
- Identify market trends and sentiment
- Spot potential arbitrage opportunities
- Provide insights on market dynamics
When analyzing markets:
1. First get current market data
2. Analyze the data for trends and insights
3. Look for arbitrage opportunities if requested
4. Provide clear explanations of your findings
Be thorough in your analysis and cite specific data points.""",
tools=[get_prediction_market_data, check_prediction_market_arbitrage],
llm="gpt-4o-mini"
)
# Example queries
queries = [
"Get the current Fed interest rate prediction market data and analyze what it shows about market sentiment.",
"Compare Fed and BTC prediction markets. What insights can you derive?",
"Check if there are any arbitrage opportunities between Fed and BTC markets."
]
for i, query in enumerate(queries, 1):
print(f"Query {i}: {query}")
response = market_agent.start(query)
print(f"Response: {response}\n")
print("-" * 80)
# Example 4: Multi-agent prediction market workflow
def example_multi_agent_workflow():
"""Example of a multi-agent workflow for comprehensive market analysis."""
print("\n=== Multi-Agent Prediction Market Workflow ===\n")
# Data gathering agent
data_agent = Agent(
name="MarketDataCollector",
instructions="""You collect prediction market data from NEXUS API.
Focus on gathering comprehensive data for analysis.""",
tools=[get_prediction_market_data]
)
# Analysis agent
analysis_agent = Agent(
name="MarketAnalyst",
instructions="""You analyze prediction market data to identify trends,
sentiment, and trading opportunities. Provide detailed insights.""",
tools=[]
)
# Arbitrage agent
arbitrage_agent = Agent(
name="ArbitrageSpecialist",
instructions="""You specialize in finding arbitrage opportunities
between prediction markets. Assess risk and profitability.""",
tools=[check_prediction_market_arbitrage]
)
# Example workflow
markets = ["Fed", "BTC", "Election"]
print("Step 1: Collecting market data...")
market_data = {}
for market in markets:
print(f"Collecting data for {market} market...")
data = data_agent.start(f"Get current market data for {market}")
market_data[market] = data
print(f"Data collected for {market}: {len(data)} characters")
print("\nStep 2: Analyzing market trends...")
combined_data = "\n".join([f"{market}: {data}" for market, data in market_data.items()])
analysis = analysis_agent.start(f"Analyze this prediction market data and identify key trends:\n{combined_data}")
print(f"Analysis: {analysis[:200]}...")
print("\nStep 3: Checking arbitrage opportunities...")
arb_analysis = arbitrage_agent.start("Check for arbitrage opportunities between Fed,BTC markets")
print(f"Arbitrage analysis: {arb_analysis[:200]}...")
if __name__ == "__main__":
print("NEXUS Prediction Market Tool Examples")
print("=" * 50)
# Run examples
try:
example_direct_usage()
example_prediction_market_agent()
example_multi_agent_workflow()
except Exception as e:
print(f"Error running examples: {e}")
print("\nNote: Some features require API access or payment.")
print("Free features: Market data queries")
print("Paid features: Arbitrage analysis ($0.02 USDC on eip155:8453)")
print("\n" + "=" * 50)
print("Examples completed!")
print("\nTo use in your own projects:")
print("1. Install: pip install praisonai-tools")
print("2. Import: from praisonai_tools.tools import NexusPredictionMarketTool")
print("3. Use: tool = NexusPredictionMarketTool()")
print("\nFor arbitrage features, ensure you have the required payment setup.")
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#!/usr/bin/env python3
"""
SwarmScore Integration Example for PraisonAI
This example demonstrates how to integrate SwarmScore trust ratings
with PraisonAI agents for portable reputation management.
SwarmScore provides cryptographically signed trust ratings based on
verified execution history, success rates, and consistency.
Requirements:
pip install requests praisonai-tools
Usage:
python swarmscore_example.py
"""
import json
from praisonai_tools.tools import SwarmScoreTool, load_swarmscore_by_slug
def main():
"""Demonstrate SwarmScore integration with PraisonAI."""
print("🔍 SwarmScore Integration Example")
print("=" * 50)
# Initialize SwarmScore tool
swarmscore = SwarmScoreTool()
# Example agent slug (replace with actual agent identifier)
agent_slug = "example-agent-123"
print(f"\n📊 Loading SwarmScore for agent: {agent_slug}")
# Load SwarmScore data
result = swarmscore.load_swarmscore(agent_slug)
if result.success:
print("✅ SwarmScore loaded successfully!")
# Display basic score information
score_data = result.output
if 'score' in score_data:
print(f" Trust Score: {score_data['score']}")
if 'tier' in score_data:
print(f" Trust Tier: {score_data['tier']}")
if 'jobs_completed' in score_data:
print(f" Jobs Completed: {score_data['jobs_completed']}")
if 'success_rate' in score_data:
print(f" Success Rate: {score_data['success_rate']}%")
print("\n🔍 Full SwarmScore data:")
print(json.dumps(score_data, indent=2))
# Verify score freshness
if 'verify_payload' in score_data:
print("\n🔐 Verifying score freshness...")
verify_result = swarmscore.verify_swarmscore(score_data['verify_payload'])
if verify_result.success:
print("✅ Score verification successful!")
print(f" Verification data: {verify_result.output}")
else:
print(f"❌ Score verification failed: {verify_result.error}")
else:
print(f"❌ Failed to load SwarmScore: {result.error}")
print("\n💡 This might happen if:")
print(" • The agent slug doesn't exist in SwarmScore")
print(" • The SwarmScore API is temporarily unavailable")
print(" • Network connectivity issues")
# Get discovery manifest
print("\n🌐 Loading agent discovery manifest...")
manifest_result = swarmscore.get_discovery_manifest()
if manifest_result.success:
print("✅ Discovery manifest loaded!")
print(" This contains machine-readable data for agent-to-agent discovery")
print(f" Manifest keys: {list(manifest_result.output.keys())}")
else:
print(f"❌ Failed to load manifest: {manifest_result.error}")
# Demonstrate standalone function usage
print("\n🛠️ Using standalone functions:")
try:
# This will likely fail with the example slug, but shows the API
score_data = load_swarmscore_by_slug(agent_slug)
print(f"✅ Standalone function succeeded: {score_data}")
except Exception as e:
print(f"❌ Standalone function failed (expected): {e}")
print("\n📚 Next Steps:")
print(" 1. Register your agent at https://swarmsync.ai")
print(" 2. Get your agent slug from the SwarmSync dashboard")
print(" 3. Replace 'example-agent-123' with your actual slug")
print(" 4. Integrate SwarmScore checks into your agent workflows")
print("\n 📖 Documentation: https://swarmsync.ai/docs/protocol-specs/swarmscore")
def agent_workflow_example():
"""Example of how to integrate SwarmScore into an agent workflow."""
print("\n🤖 Agent Workflow Integration Example")
print("=" * 45)
# Simulated agent execution flow
agent_id = "my-trading-agent"
# 1. Load current trust score before executing task
swarmscore = SwarmScoreTool()
score_result = swarmscore.load_swarmscore(agent_id)
if score_result.success:
trust_score = score_result.output.get('score', 0)
print(f"🔍 Agent {agent_id} current trust score: {trust_score}")
# 2. Make decisions based on trust level
if trust_score >= 80:
print("✅ High trust - proceeding with full autonomy")
task_approach = "autonomous"
elif trust_score >= 60:
print("⚠️ Medium trust - requesting human approval for critical actions")
task_approach = "supervised"
else:
print("❌ Low trust - operating in restricted mode")
task_approach = "restricted"
# 3. Execute task based on trust level
print(f"🚀 Executing task with {task_approach} approach...")
# 4. After task completion, the score would be updated by SwarmSync
# (This happens externally based on verified execution results)
print("📝 Task completed - SwarmScore will be updated based on results")
else:
print(f"⚠️ Could not load trust score: {score_result.error}")
print("🔄 Falling back to default security settings")
if __name__ == "__main__":
main()
agent_workflow_example()
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<style>
.lx-highlight { position: relative; border-radius:3px; padding:1px 2px;}
.lx-highlight .lx-tooltip {
visibility: hidden;
opacity: 0;
transition: opacity 0.2s ease-in-out;
background: #333;
color: #fff;
text-align: left;
border-radius: 4px;
padding: 6px 8px;
position: absolute;
z-index: 1000;
bottom: 125%;
left: 50%;
transform: translateX(-50%);
font-size: 12px;
max-width: 240px;
white-space: normal;
box-shadow: 0 2px 6px rgba(0,0,0,0.3);
}
.lx-highlight:hover .lx-tooltip { visibility: visible; opacity:1; }
.lx-animated-wrapper { max-width: 100%; font-family: Arial, sans-serif; }
.lx-controls {
background: #fafafa; border: 1px solid #90caf9; border-radius: 8px;
padding: 12px; margin-bottom: 16px;
}
.lx-button-row {
display: flex; justify-content: center; gap: 8px; margin-bottom: 12px;
}
.lx-control-btn {
background: #4285f4; color: white; border: none; border-radius: 4px;
padding: 8px 16px; cursor: pointer; font-size: 13px; font-weight: 500;
transition: background-color 0.2s;
}
.lx-control-btn:hover { background: #3367d6; }
.lx-progress-container {
margin-bottom: 8px;
}
.lx-progress-slider {
width: 100%; margin: 0; appearance: none; height: 6px;
background: #ddd; border-radius: 3px; outline: none;
}
.lx-progress-slider::-webkit-slider-thumb {
appearance: none; width: 18px; height: 18px; background: #4285f4;
border-radius: 50%; cursor: pointer;
}
.lx-progress-slider::-moz-range-thumb {
width: 18px; height: 18px; background: #4285f4; border-radius: 50%;
cursor: pointer; border: none;
}
.lx-status-text {
text-align: center; font-size: 12px; color: #666; margin-top: 4px;
}
.lx-text-window {
font-family: monospace; white-space: pre-wrap; border: 1px solid #90caf9;
padding: 12px; max-height: 260px; overflow-y: auto; margin-bottom: 12px;
line-height: 1.6;
}
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<div class="lx-animated-wrapper lx-gif-optimized">
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Entity <span id="entityInfo">1/3</span> |
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+98 -26
View File
@@ -37,15 +37,6 @@ from importlib.metadata import version, PackageNotFoundError
from praisonai_tools.tools.base import BaseTool, ToolResult, ToolValidationError, validate_tool
from praisonai_tools.tools.decorator import tool, FunctionTool, is_tool, get_tool_schema
from praisonai_tools.catalogue import (
ToolCatalogueEntry,
list_tools,
get_tool_names,
)
# Imported at top (not below ``__getattr__``) to satisfy ruff E402. This only
# reads the auto-discovered manifest - no tool module is eagerly imported.
from praisonai_tools.tools import __all__ as _tools_all
try:
__version__ = version("praisonai-tools")
@@ -62,20 +53,101 @@ def __getattr__(name):
except AttributeError:
raise AttributeError(f"module {__name__!r} has no attribute {name!r}")
# Catalogue/discovery helpers exported eagerly above (not tool symbols, so they
# are not part of the auto-discovered manifest).
_CATALOGUE_EXPORTS = [
"ToolCatalogueEntry",
"list_tools",
"get_tool_names",
]
# The remainder of ``__all__`` is derived from the tools package's
# automatically-discovered manifest so the two levels cannot drift apart. Only
# source files are parsed (via AST) to build it - no tool module is eagerly
# imported here.
__all__ = sorted(set(_tools_all) | set(_CATALOGUE_EXPORTS))
def __dir__():
return sorted(set(globals()) | set(__all__))
__all__ = [
# Base classes for custom tools
"BaseTool",
"ToolResult",
"ToolValidationError",
"validate_tool",
# Decorator for function-based tools
"tool",
"FunctionTool",
"is_tool",
"get_tool_schema",
# Email Tool
"EmailTool",
"send_email",
"read_emails",
"search_emails",
# Slack Tool
"SlackTool",
"send_slack_message",
"get_slack_channels",
"get_slack_history",
# Discord Tool
"DiscordTool",
"send_discord_webhook",
"send_discord_message",
# GitHub Tool
"GitHubTool",
"search_github_repos",
"get_github_repo",
"create_github_issue",
# Image Tool
"ImageTool",
"generate_image",
# Weather Tool
"WeatherTool",
"get_weather",
"get_forecast",
"get_air_quality",
# YouTube Tool
"YouTubeTool",
"search_youtube",
"get_youtube_video",
"get_youtube_transcript",
# TTS Tool
"TTSTool",
"text_to_speech",
"list_tts_voices",
# Telegram Tool
"TelegramTool",
"send_telegram_message",
# Notion Tool
"NotionTool",
"search_notion",
"create_notion_page",
# PostgreSQL Tool
"PostgresTool",
"query_postgres",
"list_postgres_tables",
# Reddit Tool
"RedditTool",
"search_reddit",
"get_reddit_hot",
# Docker Tool
"DockerTool",
"list_docker_containers",
"run_docker_container",
# Signal Tool
"SignalTool",
"send_signal_message",
"check_signal_connection",
# LINE Tool
"LineTool",
"send_line_message",
"broadcast_line_message",
# iMessage Tool
"iMessageTool",
"send_imessage",
"check_imessage_availability",
# WhatsApp Tool
"WhatsAppTool",
"send_whatsapp_message",
# Marketplace Tools
"PinchworkTool",
"pinchwork_delegate",
"AgentIDTool",
"verify_agent_identity",
"JoyTrustTool",
"check_trust_score",
"AgentFolioTool",
"check_behavioral_trust",
"verify_task_delegation_safety",
# Composio
"ComposioTool",
"ComposioTools",
"composio_execute",
"composio_tools",
"composio_list_apps",
]
-274
View File
@@ -1,274 +0,0 @@
"""Tool discovery / catalogue contract for PraisonAI Tools.
This module provides a single, programmatic way to enumerate every tool that
``praisonai-tools`` ships, plus any third-party tool registered via the
``praisonai.tools`` entry-point group. It exists so that the wider SDK (CLI,
docs, YAML validators, third-party packages) can answer *"what tools can I
actually use here?"* against a live catalogue derived from the real registry
rather than a hand-maintained allowlist that drifts.
Usage:
from praisonai_tools import list_tools
for entry in list_tools():
print(entry.name, entry.module, entry.extras, entry.summary)
Third-party packages can register their own tools by declaring an entry point:
# pyproject.toml (third-party tool package)
[project.entry-points."praisonai.tools"]
my_tool = "my_pkg:MyTool"
Nothing here imports optional/heavy dependencies: the catalogue is built from
the module map alone, so ``list_tools()`` is safe to call without any extras
installed.
"""
from __future__ import annotations
import ast
import os
from dataclasses import dataclass, field
from functools import lru_cache
from typing import Dict, Optional, Tuple
ENTRY_POINT_GROUP = "praisonai.tools"
# Directory that holds the first-party ``*_tool.py`` files. The catalogue is
# derived by scanning this directory, so dropping a new ``*_tool.py`` that
# defines a ``*Tool`` class makes the tool discoverable with no edits to any
# hand-maintained list.
_TOOLS_DIR = os.path.join(os.path.dirname(__file__), "tools")
# Map from the module (as recorded in ``_TOOL_MAP``) to the optional-dependency
# extras required to use tools defined in it. Modules absent from this mapping
# have no extra requirements (they rely only on the standard library or on the
# base dependencies). Keep this aligned with ``[project.optional-dependencies]``
# in ``pyproject.toml``.
_MODULE_EXTRAS = {
"wordpress_tool": ("wordpress",),
"pinchwork_tool": ("pinchwork", "marketplace"),
"agentid_tool": ("agentid", "marketplace"),
"joy_trust_tool": ("joy-trust", "marketplace"),
"agentfolio_tool": ("agentfolio", "marketplace"),
"praisonai_tools.n8n.n8n_workflow": ("n8n",),
"langextract_tool": ("langextract",),
"swarmscore_tool": ("swarmscore",),
"composio_tool": ("composio",),
"stripe_tool": ("stripe",),
}
@dataclass(frozen=True)
class ToolCatalogueEntry:
"""A single discoverable tool.
Attributes:
name: Public name used to import/reference the tool, e.g. ``"QdrantTool"``.
module: Dotted or relative module path that defines the tool.
extras: Optional-dependency extras required to use the tool, e.g.
``("swarmscore",)``. Empty when no extra install is needed.
summary: A one-line human-readable description of the tool.
"""
name: str
module: str
extras: Tuple[str, ...] = field(default_factory=tuple)
summary: str = ""
def _summary_for(name: str) -> str:
"""Derive a concise one-line summary for a tool class name.
Fallback used only when a tool class does not declare a literal
``description``. We avoid importing the tool (which could pull heavy/optional
deps) and instead produce a stable, human-friendly summary from the name.
"""
if name.endswith("Tool"):
base = name[:-4]
else:
base = name
return f"{base} integration tool".strip()
def _first_line(text: str) -> str:
"""Return the first non-empty line of ``text`` (a tool ``description``)."""
for line in text.splitlines():
line = line.strip()
if line:
return line
return ""
def _scan_module(path: str) -> "list[tuple[str, str]]":
"""AST-scan a ``*_tool.py`` file for ``*Tool`` classes and descriptions.
Returns a list of ``(class_name, summary)`` tuples. The file is parsed, not
imported, so this stays cheap and never triggers optional dependencies.
Classes without a literal ``description`` fall back to a name-synthesised
summary.
"""
try:
with open(path, "r", encoding="utf-8") as fh:
tree = ast.parse(fh.read(), filename=path)
except (OSError, SyntaxError): # pragma: no cover - defensive
return []
found = []
for node in tree.body:
if not isinstance(node, ast.ClassDef) or not node.name.endswith("Tool"):
continue
description: Optional[str] = None
for stmt in node.body:
# Accept both plain ``description = "..."`` and annotated
# ``description: str = "..."`` class attributes.
if isinstance(stmt, ast.Assign):
targets = [t.id for t in stmt.targets if isinstance(t, ast.Name)]
value = stmt.value
elif isinstance(stmt, ast.AnnAssign) and isinstance(stmt.target, ast.Name):
targets = [stmt.target.id]
value = stmt.value
else:
continue
if (
"description" in targets
and isinstance(value, ast.Constant)
and isinstance(value.value, str)
):
description = value.value
summary = _first_line(description) if description else _summary_for(node.name)
found.append((node.name, summary or _summary_for(node.name)))
return found
@lru_cache(maxsize=1)
def _scan_source_tree() -> "Dict[str, Tuple[str, str]]":
"""Derive the first-party tool catalogue from the source tree.
Scans every ``praisonai_tools/tools/*_tool.py`` file for ``*Tool`` classes
and returns ``{class_name: (module, summary)}``. Because the mapping is
derived from the files that actually exist, phantom names (advertised tools
with no file) are impossible by construction, and adding a tool is a single
new-file change.
"""
derived: "Dict[str, Tuple[str, str]]" = {}
try:
filenames = sorted(os.listdir(_TOOLS_DIR))
except OSError: # pragma: no cover - defensive
return derived
for filename in filenames:
if not filename.endswith("_tool.py"):
continue
module = filename[:-3] # strip ".py"; relative module name within tools
path = os.path.join(_TOOLS_DIR, filename)
for class_name, summary in _scan_module(path):
derived.setdefault(class_name, (module, summary))
return derived
def _first_party_entries() -> "list[ToolCatalogueEntry]":
"""Build catalogue entries for every first-party tool class.
The catalogue is source-derived: it is built by scanning the actual
``*_tool.py`` files on disk (see ``_scan_source_tree``) rather than a
hand-maintained dictionary, so it can never advertise a tool whose file does
not exist. Summaries come from each tool's own ``description``.
A few tools live in nested packages (e.g. the n8n workflow tool under
``praisonai_tools.n8n``) rather than flat ``*_tool.py`` files; those are
still surfaced via ``_TOOL_MAP`` so their public names remain stable.
"""
entries: "Dict[str, ToolCatalogueEntry]" = {}
for name, (module, summary) in _scan_source_tree().items():
entries[name] = ToolCatalogueEntry(
name=name,
module=module,
extras=_MODULE_EXTRAS.get(module, ()),
summary=summary,
)
# Include tool classes defined outside the flat ``*_tool.py`` layout (e.g.
# nested subpackages such as ``praisonai_tools.n8n``) that the scan cannot
# reach, keeping their names stable. Only *nested* (absolute-module) tools
# are merged here: flat ``*_tool.py`` classes are already source-derived by
# the scan above, so restoring them from ``_TOOL_MAP`` would reintroduce the
# hand-maintained bookkeeping this catalogue exists to eliminate.
try:
from praisonai_tools.tools import _TOOL_MAP
except Exception: # pragma: no cover - defensive
_TOOL_MAP = {}
for name, module in _TOOL_MAP.items():
if not name.endswith("Tool") or name in entries:
continue
if not module.startswith("praisonai_tools."):
continue
entries[name] = ToolCatalogueEntry(
name=name,
module=module,
extras=_MODULE_EXTRAS.get(module, ()),
summary=_summary_for(name),
)
return list(entries.values())
def _entry_point_entries() -> "list[ToolCatalogueEntry]":
"""Build catalogue entries for third-party tools registered via entry points.
Third-party packages register under the ``praisonai.tools`` entry-point
group. We do not import the target object (to keep discovery cheap and
dependency-free); we record the declared name and module value instead.
"""
try:
from importlib.metadata import entry_points
except ImportError: # pragma: no cover - Python < 3.8
return []
entries = []
try:
eps = entry_points()
# importlib.metadata API differs across versions.
if hasattr(eps, "select"):
selected = eps.select(group=ENTRY_POINT_GROUP)
else: # pragma: no cover - Python < 3.10 dict interface
selected = eps.get(ENTRY_POINT_GROUP, [])
except Exception: # pragma: no cover - defensive
return []
for ep in selected:
entries.append(
ToolCatalogueEntry(
name=ep.name,
module=getattr(ep, "value", "") or "",
extras=(),
summary=f"Third-party tool registered via {ENTRY_POINT_GROUP}",
)
)
return entries
def list_tools() -> "list[ToolCatalogueEntry]":
"""Return the full catalogue of available tools.
Includes every first-party tool shipped with ``praisonai-tools`` plus any
third-party tool registered via the ``praisonai.tools`` entry-point group.
Entries are de-duplicated by name (first-party wins) and returned sorted by
name.
"""
seen = {}
for entry in _first_party_entries():
seen[entry.name] = entry
for entry in _entry_point_entries():
seen.setdefault(entry.name, entry)
return sorted(seen.values(), key=lambda e: e.name)
def get_tool_names() -> "set[str]":
"""Return the set of every available tool name.
Convenience helper for validators that only need membership checks (e.g. to
replace a hand-maintained allowlist).
"""
return {entry.name for entry in list_tools()}
+1 -18
View File
@@ -11,7 +11,6 @@ def main():
print("PraisonAI Developer Tools CLI")
print("\nUsage: praisonai-tools [tool] [args]")
print("\nAvailable tools:")
print(" list List the available tool catalogue")
print(" docs-generate Generate SDK reference documentation")
print(" video AI-powered video editing tools")
print(" fcp Final Cut Pro automation tools")
@@ -20,23 +19,7 @@ def main():
tool = sys.argv[1]
tool_args = sys.argv[2:]
if tool == "list":
parser = argparse.ArgumentParser(prog="praisonai-tools list")
parser.add_argument("--extras", action="store_true",
help="Only show tools that require optional-dependency extras")
args = parser.parse_args(tool_args)
from .catalogue import list_tools
entries = list_tools()
if args.extras:
entries = [e for e in entries if e.extras]
width = max((len(e.name) for e in entries), default=0)
for entry in entries:
extras = f" [extras: {', '.join(entry.extras)}]" if entry.extras else ""
print(f"{entry.name.ljust(width)} {entry.summary}{extras}")
print(f"\n{len(entries)} tools")
return 0
elif tool == "docs-generate":
if tool == "docs-generate":
# Handle docs-generate with its own parser for better help
parser = argparse.ArgumentParser(prog="praisonai-tools docs-generate")
parser.add_argument("--package", choices=["praisonaiagents", "praisonai", "typescript", "all"],
+48 -295
View File
@@ -13,7 +13,6 @@ from typing import Any, Dict, List, Optional, Tuple
import ast
import re
import json
import uuid
# =============================================================================
@@ -112,239 +111,45 @@ class LayoutType(Enum):
# UTILS
# =============================================================================
# Generic containers whose *simple* single-level form is safe to keep as-is
# (e.g. ``Optional[str]``, ``Union[str, int]``, ``Dict[str, Any]``). When these
# wrap complex/nested types they are collapsed to just the container name.
_SIMPLE_KEEP_CONTAINERS = ("Optional", "Union", "Dict", "List", "Tuple", "Sequence", "Set")
# Containers that should always collapse to just their name because their inner
# contents commonly contain nested brackets or quoted literals that break MDX.
_ALWAYS_COLLAPSE_CONTAINERS = ("Callable", "Literal", "Coroutine", "Awaitable", "Generator", "AsyncGenerator")
def sanitize_type_for_mdx(type_str: Optional[str]) -> Optional[str]:
"""Sanitize complex type annotations for MDX compatibility.
Rules:
- Simple types pass through unchanged (``str`` -> ``str``).
- Forward references have their quotes removed
(``Optional['Agent']`` -> ``Optional[Agent]``).
- Containers known to hold nested brackets are collapsed to their bare
name (``Callable[[X], Y]`` -> ``Callable``, ``Literal['a']`` ->
``Literal``, ``Coroutine[...]`` -> ``Coroutine``).
- A container wrapping another complex/nested type is collapsed to just
its name (``Optional[Union[str, int]]`` -> ``Optional``).
- A container wrapping only simple types is preserved
(``Optional[str]`` -> ``Optional[str]``,
``Union[str, int]`` -> ``Union[str, int]``).
"""
"""Sanitize complex type annotations for MDX compatibility."""
if not type_str:
return type_str
result = type_str.strip()
# Remove quotes from forward references, e.g. 'Agent' -> Agent
result = re.sub(r"'([A-Za-z_][a-zA-Z0-9_.]*)'", r"\1", result)
# No subscription -> nothing more to simplify.
if "[" not in result:
return result
container = result.split("[", 1)[0].strip()
# Containers that always collapse (Callable, Literal, Coroutine, ...).
if container in _ALWAYS_COLLAPSE_CONTAINERS:
return container
# For keep-able containers, inspect the inner content. If it contains nested
# brackets (another generic) collapse to the bare container name; otherwise
# keep the single-level form intact.
if container in _SIMPLE_KEEP_CONTAINERS:
inner = result[len(container) + 1:]
if inner.endswith("]"):
inner = inner[:-1]
if "[" in inner:
return container
# A bare ``Any`` member makes the type uninformative for the table, so
# collapse ``Union``/``Optional`` to just the container name.
members = [m.strip() for m in inner.split(",")]
if container in ("Union", "Optional") and "Any" in members:
return container
return result
# Unknown container with nested brackets -> keep the base name to stay safe.
if "[[" in result:
return container
result = re.sub(r"'([A-Z][a-zA-Z0-9_]*)'", r"\1", result)
while "[[" in result or " Union[" in result or " Optional[" in result:
new_result = re.sub(r"\[\[(.*?)\]\]", r"[\1]", result)
if new_result == result:
break
result = new_result
if "[" in result:
return result.split("[")[0]
return result
# Plain HTML tags. HTML is case-insensitive, so ``<div>`` and ``<DIV>`` are the
# same element and both must be preserved (never escaped) by escape_mdx.
_HTML_TAGS = {
'div', 'span', 'p', 'a', 'br', 'hr', 'img', 'ul', 'ol', 'li',
'table', 'tr', 'td', 'th', 'thead', 'tbody', 'code', 'pre',
'strong', 'em', 'b', 'i', 'h1', 'h2', 'h3', 'h4', 'h5', 'h6',
}
# Mintlify JSX components. Unlike HTML, JSX component names are CASE-SENSITIVE:
# ``<Badge>`` is a valid component but ``<badge>`` is not and must be escaped as
# prose. These are therefore matched exactly (no case folding).
_MDX_COMPONENTS = {
'Card', 'CardGroup', 'Note', 'Warning', 'Info', 'Tip', 'Check',
'Danger', 'Accordion', 'AccordionGroup', 'Tab', 'Tabs', 'Step',
'Steps', 'Frame', 'Icon', 'Badge', 'Tooltip', 'CodeGroup',
'Expandable', 'ParamField', 'ResponseField', 'Columns', 'Column',
'RequestExample', 'ResponseExample', 'Banner', 'Update', 'View',
'Tree', 'Tile', 'Tiles', 'Panel', 'Color',
}
# Combined allowlist of tags that must NOT be escaped by escape_mdx.
VALID_MDX_TAGS = _HTML_TAGS | _MDX_COMPONENTS
# Lower-cased view of the HTML tags only, so ``<DIV>``/``<Div>`` resolve
# case-insensitively while JSX components stay case-sensitive.
_HTML_TAGS_LOWER = {t.lower() for t in _HTML_TAGS}
def _is_valid_mdx_tag(tag: str) -> bool:
"""Return True if ``tag`` is a tag that must be preserved (not escaped).
HTML tags are matched case-insensitively (HTML is case-insensitive) while
Mintlify JSX components must match exactly, so a mis-cased component such as
``badge`` is treated as prose and escaped rather than emitted as a broken
component.
"""
return tag in _MDX_COMPONENTS or tag.lower() in _HTML_TAGS_LOWER
# Docstring section headers whose indented body is source code and should be
# wrapped in a fenced code block so MDX/Mintlify renders it verbatim.
_CODE_SECTION_HEADERS = ("usage", "example", "examples")
def _wrap_docstring_code_examples(text: str) -> str:
"""Wrap indented code under Usage/Example sections in fenced code blocks.
Detects a header line like ``Usage:`` followed by an indented block and
converts that block into a ```python fenced code block so it survives MDX
escaping untouched.
Existing fenced blocks are passed through verbatim, but any indented
Usage/Example sections that appear *outside* of a fence (including ones
that follow an unrelated fenced block earlier in the docstring) are still
wrapped.
"""
lines = text.split('\n')
out: List[str] = []
i = 0
n = len(lines)
in_fence = False
while i < n:
line = lines[i]
# Pass through content inside an existing fenced code block untouched.
if line.lstrip().startswith("```"):
in_fence = not in_fence
out.append(line)
i += 1
continue
if in_fence:
out.append(line)
i += 1
continue
header = line.strip().rstrip(':').lower()
is_header = (
line.strip().endswith(':')
and header in _CODE_SECTION_HEADERS
and not line.startswith((' ', '\t'))
)
if is_header:
# Collect the following indented block.
block: List[str] = []
j = i + 1
# Skip a single blank separator line if present.
while j < n and not lines[j].strip():
block.append(lines[j])
j += 1
code_lines: List[str] = []
while j < n and (lines[j].startswith((' ', '\t')) or not lines[j].strip()):
code_lines.append(lines[j])
j += 1
# Trim trailing blank lines from the captured code.
while code_lines and not code_lines[-1].strip():
code_lines.pop()
if code_lines:
out.append(line)
out.extend(block)
import textwrap
dedented = textwrap.dedent('\n'.join(code_lines))
out.append("```python")
out.extend(dedented.split('\n'))
out.append("```")
i = j
continue
out.append(line)
i += 1
return '\n'.join(out)
def escape_mdx(text: str) -> str:
"""Escape text for MDX compatibility.
Escapes stray ``{...}`` expressions and unknown ``<tag>`` patterns that
would break Mintlify's MDX parser, while:
- Preserving content inside inline/fenced code blocks.
- Preserving valid Mintlify component tags (see ``VALID_MDX_TAGS``).
- Wrapping indented code under ``Usage:``/``Example:`` docstring
sections in fenced code blocks.
"""
"""Escape text for MDX compatibility."""
if not text:
return text
text = _wrap_docstring_code_examples(text)
# Use a per-call random sentinel so literal documentation text such as
# ``__CODE_BLOCK_0__`` or ``__MDX_TAG_0__`` cannot be mistaken for one of
# our internal placeholders during the restore phase below.
token = uuid.uuid4().hex
code_marker = f"\x00CB{token}"
tag_marker = f"\x00MT{token}"
code_blocks = []
def save_code_block(match):
code_blocks.append(match.group(0))
return f"{code_marker}{len(code_blocks) - 1}\x00"
return f"__CODE_BLOCK_{len(code_blocks)-1}__"
text = re.sub(r"```.*?```", save_code_block, text, flags=re.DOTALL)
text = re.sub(r"`.*?`", save_code_block, text)
text = text.replace('{', '&#123;').replace('}', '&#125;')
# Protect valid Mintlify/HTML component tags so they survive the blanket
# angle-bracket escaping below.
preserved_tags = []
def preserve_valid_tag(match):
full = match.group(0)
tag = match.group(1)
if _is_valid_mdx_tag(tag):
preserved_tags.append(full)
return f"{tag_marker}{len(preserved_tags) - 1}\x00"
return full
# Match opening tags <Tag ...>, closing tags </Tag>, and self-contained <tag>.
text = re.sub(r"</?([A-Za-z][A-Za-z0-9]*)(?:\s[^<>]*?)?/?>", preserve_valid_tag, text)
# Escape all remaining angle brackets (unknown tags / stray brackets).
text = text.replace('<', '&lt;').replace('>', '&gt;')
for i, tag in enumerate(preserved_tags):
text = text.replace(f"{tag_marker}{i}\x00", tag)
for i, block in enumerate(code_blocks):
text = text.replace(f"{code_marker}{i}\x00", block)
text = text.replace(f"__CODE_BLOCK_{i}__", block)
return text
@@ -355,6 +160,18 @@ def validate_mdx(content: str) -> List[str]:
in_code_block = False
in_frontmatter = False
frontmatter_count = 0
VALID_MDX_TAGS = {
'div', 'span', 'p', 'a', 'br', 'hr', 'img', 'ul', 'ol', 'li',
'table', 'tr', 'td', 'th', 'thead', 'tbody', 'code', 'pre',
'strong', 'em', 'b', 'i', 'h1', 'h2', 'h3', 'h4', 'h5', 'h6',
'Card', 'CardGroup', 'Note', 'Warning', 'Info', 'Tip', 'Check',
'Danger', 'Accordion', 'AccordionGroup', 'Tab', 'Tabs', 'Step',
'Steps', 'Frame', 'Icon', 'Badge', 'Tooltip', 'CodeGroup',
'Expandable', 'ParamField', 'ResponseField', 'Columns', 'Column',
'RequestExample', 'ResponseExample', 'Banner', 'Update', 'View',
'Tree', 'Tile', 'Tiles', 'Panel', 'Color'
}
for i, line in enumerate(lines, 1):
stripped = line.strip()
@@ -379,9 +196,7 @@ def validate_mdx(content: str) -> List[str]:
angle_matches = re.findall(r'(?<!`)(<[a-zA-Z_][a-zA-Z0-9_]*>)(?!`)', line)
for match in angle_matches:
tag = match[1:-1]
# Mirror escape_mdx's allowlist exactly so the two stay in lockstep:
# HTML tags are case-insensitive, JSX components are case-sensitive.
if not _is_valid_mdx_tag(tag):
if tag not in VALID_MDX_TAGS and tag.lower() not in {t.lower() for t in VALID_MDX_TAGS if t.islower()}:
errors.append(f"Line {i}: Unescaped JSX-like tag: {match}")
curly_matches = re.findall(r'(?<!`)(?<!=)\{([a-zA-Z_][a-zA-Z0-9_]*)\}(?!`)', line)
@@ -395,13 +210,10 @@ def escape_for_table(text: str, is_type: bool = False) -> str:
"""Escape text for use in markdown tables."""
if not text:
return text
# Always simplify complex type signatures containing nested brackets
# (e.g. ``Callable[[...], ...]``); these break MDX table rendering even
# when the caller did not explicitly flag the value as a type.
if is_type or "[[" in text:
if is_type:
text = sanitize_type_for_mdx(text) or text
text = text.replace('|', '\\|')
# Use HTML entities for angle brackets to avoid tag confusion
text = text.replace('<', '&lt;').replace('>', '&gt;')
@@ -409,48 +221,6 @@ def escape_for_table(text: str, is_type: bool = False) -> str:
return text
def validate_docs_json_structure(config: Dict[str, Any]) -> List[str]:
"""Validate the structure of a docs.json navigation config.
Ensures the expected ``navigation.tabs`` -> ``SDK`` tab -> ``Reference``
group hierarchy exists before it is modified.
Args:
config: Parsed docs.json content.
Returns:
A list of error strings; empty if the structure is valid.
"""
errors: List[str] = []
if not isinstance(config, dict):
return ["docs.json root must be an object"]
navigation = config.get("navigation")
if not isinstance(navigation, dict):
return ["Missing or invalid 'navigation' object"]
tabs = navigation.get("tabs")
if not isinstance(tabs, list):
return ["Missing or invalid 'navigation.tabs' array"]
sdk_tab = next((t for t in tabs if isinstance(t, dict) and t.get("tab") == "SDK"), None)
if sdk_tab is None:
errors.append("Missing 'SDK' tab in navigation.tabs")
return errors
groups = sdk_tab.get("groups")
if not isinstance(groups, list):
errors.append("Missing or invalid 'groups' in SDK tab")
return errors
ref_group = next((g for g in groups if isinstance(g, dict) and g.get("group") == "Reference"), None)
if ref_group is None:
errors.append("Missing 'Reference' group in SDK tab")
return errors
def sanitize_description(text: str, max_length: int = 150) -> str:
"""Sanitize description for YAML frontmatter. Truncates at word boundary."""
if not text:
@@ -1887,9 +1657,6 @@ ICON_MAP = {
"workflows": "route",
"telemetry": "chart-line",
"search": "magnifying-glass",
"hooks": "link",
"mcp": "plug",
"policy": "gavel",
# Modules & Integration
"a2a": "network-wired",
@@ -2456,12 +2223,11 @@ class TypeScriptDocParser:
class MDXGenerator:
"""Generate MDX documentation files."""
def __init__(self, output_dir: Path, package_name: str, config: Dict[str, Any], layout: LayoutType = LayoutType.LEGACY, docs_root: Optional[Path] = None):
def __init__(self, output_dir: Path, package_name: str, config: Dict[str, Any], layout: LayoutType = LayoutType.LEGACY):
self.output_dir = output_dir
self.package_name = package_name
self.config = config
self.layout = layout
self.docs_root = docs_root or output_dir
self.generated_files = set() # Use set for faster lookups and cleanup
# Index for "Used By" cross-references: {function_name: [(caller_name, caller_path), ...]}
self.used_by_index: Dict[str, List[Tuple[str, str]]] = {}
@@ -2579,7 +2345,8 @@ class MDXGenerator:
return generated
def _track_file(self, path: Path):
rel_path = str(path.relative_to(self.docs_root))
docs_root = Path("/Users/praison/PraisonAIDocs")
rel_path = str(path.relative_to(docs_root))
nav_path = rel_path.replace('.mdx', '').replace('\\', '/')
self.generated_files.add(nav_path)
@@ -3125,15 +2892,7 @@ class ReferenceDocsGenerator:
layout: LayoutType = LayoutType.GRANULAR
):
self.docs_root = Path(docs_root)
# Mintlify subpath hosting uses docs/docs.json (see PraisonAIDocs migrate script).
docs_json_in_docs = self.docs_root / "docs" / "docs.json"
docs_json_at_root = self.docs_root / "docs.json"
if docs_json_in_docs.exists():
self.docs_json_path = docs_json_in_docs
elif docs_json_at_root.exists():
self.docs_json_path = docs_json_at_root
else:
self.docs_json_path = docs_json_in_docs
self.docs_json_path = self.docs_root / "docs.json"
self.layout = layout
# Base source root - default to local development path if not provided
@@ -3210,7 +2969,7 @@ class ReferenceDocsGenerator:
workspace_parser = RustWorkspaceParser(config["source"])
# Parse all crates in the workspace
all_modules = workspace_parser.parse_all()
generator = MDXGenerator(config["output"], package_name, config, layout=self.layout, docs_root=self.docs_root)
generator = MDXGenerator(config["output"], package_name, config, layout=self.layout)
generated = 0
for crate_name, modules in all_modules.items():
print(f" Crate: {crate_name} ({len(modules)} modules)")
@@ -3236,7 +2995,7 @@ class ReferenceDocsGenerator:
else:
parser = PythonDocParser(config["source"], config["import_prefix"])
generator = MDXGenerator(config["output"], package_name, config, layout=self.layout, docs_root=self.docs_root)
generator = MDXGenerator(config["output"], package_name, config, layout=self.layout)
modules = parser.get_modules()
print(f"Found {len(modules)} modules")
@@ -3280,13 +3039,14 @@ class ReferenceDocsGenerator:
def cleanup_orphaned_files(self, output_dir: Path, current_files: set):
"""Delete MDX files that are no longer part of the generated set."""
docs_root = Path("/Users/praison/PraisonAIDocs")
for sub_dir in ["functions", "classes", "modules"]:
target_dir = output_dir / sub_dir
if not target_dir.exists():
continue
for mdx_file in target_dir.glob("*.mdx"):
rel_path = str(mdx_file.relative_to(self.docs_root))
rel_path = str(mdx_file.relative_to(docs_root))
nav_path = rel_path.replace('.mdx', '').replace('\\', '/')
if nav_path not in current_files:
print(f" Deleting orphaned file: {mdx_file.name}")
@@ -3335,16 +3095,9 @@ class ReferenceDocsGenerator:
with open(self.docs_json_path, 'w') as f:
json.dump(docs_config, f, indent=2)
if self.layout == LayoutType.GRANULAR:
page_count = sum(len(group.get('pages', [])) for group in package_group['pages'])
else:
page_count = len(package_group['pages'])
print(f" Updated docs.json: {page_count} pages for {package_name}")
except Exception as exc:
print(f" Error updating docs.json for {package_name}: {exc}")
raise
except Exception:
pass
if __name__ == "__main__":
import argparse
@@ -1,43 +0,0 @@
"""Tool-registry proxy connector for PraisonAI Agents.
Optional bring-your-own-account connector that lets an agent discover and call
a large catalogue of third-party API endpoints through a single proxy token,
with credentials injected server-side by the registry (never held by the agent).
Mirrors PraisonAI's deferred tool-search bridge:
registry_search(query) -> capability search over the catalogue
registry_describe(tool_id) -> params, price-per-call, example response
registry_call(tool_id, ...) -> invoke via proxy (credential injected server-side)
The connector is disabled unless ``TOOL_PROXY_URL`` is configured. PraisonAI
ships no registry code, no bundled binary and no default endpoint - the user
supplies their own account token or self-hosted base URL.
Usage:
from praisonai_tools.registry_proxy import (
registry_search, registry_describe, registry_call,
)
agent = Agent(
instructions="SEO analyst",
tools=[registry_search, registry_describe, registry_call],
)
Environment Variables:
TOOL_PROXY_URL: base URL of the tool registry (unset -> connector disabled)
TOOL_PROXY_TOKEN: proxy token sent as the auth header
"""
from .registry_proxy import (
RegistryProxyTool,
registry_search,
registry_describe,
registry_call,
)
__all__ = [
"RegistryProxyTool",
"registry_search",
"registry_describe",
"registry_call",
]
@@ -1,533 +0,0 @@
"""Tool-registry proxy connector implementation.
Three agent-callable functions over a registry's plain-HTTP surface:
- ``registry_search(query)`` free capability search over the catalogue
- ``registry_describe(tool_id)`` free read: params, price-per-call, example
- ``registry_call(tool_id, ...)``paid invoke through the proxy; the registry
injects the upstream vendor credential server-side.
Design notes:
- ``httpx`` is lazy-imported so the connector adds zero import-time overhead and
no hard dependency when unconfigured.
- The connector is disabled unless ``TOOL_PROXY_URL`` is set.
- Errors (auth / insufficient balance / upstream 4xx / timeout) are returned as
``{"error": ...}`` tool results, never raised as exceptions.
- ``registry_call`` supports optional per-call and per-session spend guards; the
price is read from ``registry_describe`` and the call is denied + reported when
a configured budget would be exceeded.
"""
import os
import math
import logging
from typing import Any, Dict, Optional
from urllib.parse import quote
from praisonai_tools.tools.base import BaseTool
from praisonai_tools.tools.decorator import tool
logger = logging.getLogger(__name__)
_INSTALL_HINT = "httpx not installed. Install with: pip install 'praisonai-tools[registry-proxy]'"
# Cumulative spend is tracked per (proxy_url, token) so that ``max_session_spend``
# persists across the short-lived connector instances created by the decorated
# functions, without mixing budgets across distinct accounts/endpoints.
_SESSION_SPEND: Dict[tuple, float] = {}
# The registry enforces the endpoint's declared HTTP method on ``/call/{id}``.
# Restricting to a known set keeps the wire behaviour predictable and returns a
# clear tool-result error instead of forwarding a mislabelled/unexpected verb.
_ALLOWED_METHODS = frozenset({"GET", "POST", "PUT", "PATCH", "DELETE"})
class RegistryProxyTool(BaseTool):
"""Connector for a self-hostable tool registry exposing a plain-HTTP proxy."""
name = "registry_proxy"
description = (
"Discover and call third-party API endpoints through a tool registry "
"proxy; credentials are injected server-side, never held by the agent."
)
def __init__(
self,
proxy_url: Optional[str] = None,
token: Optional[str] = None,
timeout: float = 60.0,
max_cost_per_call: Optional[float] = None,
max_session_spend: Optional[float] = None,
auth_header: Optional[str] = None,
describe_path: Optional[str] = None,
):
url_from_env = proxy_url is None
self.proxy_url = (proxy_url or os.getenv("TOOL_PROXY_URL") or "").rstrip("/")
# Security: only fall back to the environment token when the URL is also
# env-derived (trusted config). An agent-supplied ``proxy_url`` must never
# receive the ambient ``TOOL_PROXY_TOKEN`` - otherwise a prompt-injected
# agent could exfiltrate the token to an attacker-controlled endpoint.
if token is not None:
self.token = token
elif url_from_env:
self.token = os.getenv("TOOL_PROXY_TOKEN")
else:
self.token = None
# Auth header is configurable for wire-compatibility with different
# registry deployments. Default ``Authorization`` sends ``Bearer {token}``;
# a custom header name (e.g. ``X-Treg-Token``) sends the raw token instead.
self.auth_header = auth_header or os.getenv("TOOL_PROXY_AUTH_HEADER") or "Authorization"
# The describe path template is configurable for wire-compatibility with
# different registry deployments. It must contain ``{tool_id}``; the
# default mirrors the live registry route (``/catalog/endpoints/{id}``).
self.describe_path = (
describe_path
or os.getenv("TOOL_PROXY_DESCRIBE_PATH")
or "/catalog/endpoints/{tool_id}"
)
self.timeout = timeout
self.max_cost_per_call = max_cost_per_call
self.max_session_spend = max_session_spend
super().__init__()
@property
def _spend_key(self) -> tuple:
return (self.proxy_url, self.token)
@property
def _session_spend(self) -> float:
return _SESSION_SPEND.get(self._spend_key, 0.0)
@_session_spend.setter
def _session_spend(self, value: float) -> None:
_SESSION_SPEND[self._spend_key] = value
def run(self, action: str, **kwargs: Any) -> Dict[str, Any]:
"""Dispatch to search/describe/call.
Args:
action: One of ``"search"``, ``"describe"`` or ``"call"``.
**kwargs: Arguments forwarded to the selected operation.
"""
if action == "search":
return self.search(kwargs.get("query", ""))
if action == "describe":
return self.describe(kwargs.get("tool_id", ""))
if action == "call":
return self.call(
kwargs.get("tool_id", ""),
kwargs.get("params"),
kwargs.get("method"),
)
return {"error": f"Unknown action '{action}'. Use search, describe or call."}
def _headers(self) -> Dict[str, str]:
headers = {"Content-Type": "application/json"}
if self.token:
if self.auth_header.lower() == "authorization":
headers[self.auth_header] = f"Bearer {self.token}"
else:
headers[self.auth_header] = self.token
return headers
def _require_config(self) -> Optional[Dict[str, Any]]:
if not self.proxy_url:
return {
"error": (
"Tool registry proxy is not configured. Set TOOL_PROXY_URL "
"(and optionally TOOL_PROXY_TOKEN) to enable the connector."
)
}
return None
@staticmethod
def _http_error(exc: Any) -> Dict[str, Any]:
response = getattr(exc, "response", None)
status = getattr(response, "status_code", None)
text = getattr(response, "text", "") if response is not None else str(exc)
if status == 401 or status == 403:
return {"error": f"Authentication failed (HTTP {status}): {text}"}
if status == 402:
return {"error": f"Insufficient balance (HTTP {status}): {text}"}
return {"error": f"HTTP {status}: {text}"}
def search(self, query: str) -> Dict[str, Any]:
"""Search the registry catalogue by capability."""
missing = self._require_config()
if missing:
return missing
if not query:
return {"error": "query is required"}
try:
import httpx
except ImportError:
return {"error": _INSTALL_HINT}
try:
with httpx.Client(timeout=self.timeout) as client:
response = client.get(
f"{self.proxy_url}/catalog/search",
params={"q": query},
headers=self._headers(),
)
response.raise_for_status()
return response.json()
except httpx.TimeoutException:
return {"error": f"Registry search timed out after {self.timeout} seconds"}
except httpx.HTTPStatusError as exc:
return self._http_error(exc)
except Exception as exc: # noqa: BLE001 - surface as tool-result error
logger.error("registry search error: %s", exc)
return {"error": str(exc)}
def describe(self, tool_id: str) -> Dict[str, Any]:
"""Describe one catalogue entry: params, price-per-call, example."""
missing = self._require_config()
if missing:
return missing
if not tool_id:
return {"error": "tool_id is required"}
try:
import httpx
except ImportError:
return {"error": _INSTALL_HINT}
if "{tool_id}" not in self.describe_path:
return {
"error": (
f"Invalid describe path template '{self.describe_path}': "
"it must contain '{tool_id}'."
)
}
try:
path = self.describe_path.format(tool_id=quote(tool_id, safe=""))
except (KeyError, IndexError, ValueError) as exc:
return {
"error": (
f"Invalid describe path template '{self.describe_path}': {exc}"
)
}
if not path.startswith("/"):
path = "/" + path
try:
with httpx.Client(timeout=self.timeout) as client:
response = client.get(
f"{self.proxy_url}{path}",
headers=self._headers(),
)
response.raise_for_status()
return response.json()
except httpx.TimeoutException:
return {"error": f"Registry describe timed out after {self.timeout} seconds"}
except httpx.HTTPStatusError as exc:
return self._http_error(exc)
except Exception as exc: # noqa: BLE001 - surface as tool-result error
logger.error("registry describe error: %s", exc)
return {"error": str(exc)}
@staticmethod
def _unwrap_envelope(data: Any) -> Any:
"""Return the dict that carries the endpoint fields.
The live registry nests ``method``/``cost`` under an ``endpoint`` key
(``{"endpoint": {...}, "provider": {}, ...}``); flatter registry
implementations put them at the top level. Prefer ``data["endpoint"]``
when it is a dict, else use ``data`` itself.
"""
if not isinstance(data, dict):
return data
endpoint = data.get("endpoint")
if isinstance(endpoint, dict):
return endpoint
return data
@classmethod
def _extract_method(cls, data: Any) -> Optional[str]:
"""Read the HTTP method from a describe response, if present.
The live registry's endpoint doc carries ``method: "GET"`` (or POST/PUT)
nested under ``endpoint``; the registry enforces the declared method on
``/call/{id}``. Flat implementations expose it at the top level.
"""
data = cls._unwrap_envelope(data)
if not isinstance(data, dict):
return None
method = data.get("method")
if isinstance(method, str) and method.strip():
return method.strip().upper()
return None
@classmethod
def _extract_price(cls, data: Any) -> Any:
"""Read a price from a response, tolerating field-name/shape variation.
Unwraps the ``endpoint`` envelope, then tries ``price_per_call`` then
``price`` then ``cost`` so the budget check and spend recording share the
same tolerance against the live schema. ``cost`` may be a structured
object (``{"value": 25, "currency": "credit", "usd": 0.0299, ...}``); in
that case prefer ``usd`` since the guard budgets are in USD (``value`` is
in provider credits). Flat numeric forms are returned unchanged.
"""
data = cls._unwrap_envelope(data)
if not isinstance(data, dict):
return None
for key in ("price_per_call", "price", "cost"):
if key in data:
value = data[key]
if isinstance(value, dict):
return value.get("usd")
return value
return None
def _check_budget(self, tool_id: str):
"""Deny + report if a configured spend guard would be exceeded.
Returns ``(denial, price, described)``: ``denial`` is a ``{"error": ...}``
dict when the call must be rejected (else ``None``); ``price`` is the
validated per-call price when a guard applies (else ``None``);
``described`` is the describe response fetched for the guard (else
``None``) so the caller can reuse it (e.g. to derive the HTTP method)
without a second network round-trip.
"""
if self.max_cost_per_call is None and self.max_session_spend is None:
return None, None, None
described = self.describe(tool_id)
if isinstance(described, dict) and "error" in described:
return described, None, None
# Accept the same price field names tolerated by spend recording so the
# budget check does not fail closed on a field-name mismatch against the
# live registry schema (``price_per_call`` -> ``price`` -> ``cost``).
price = self._extract_price(described)
try:
price = float(price)
except (TypeError, ValueError):
# Fail closed: a spend guard is configured but the price cannot be
# validated, so we cannot guarantee the budget - deny the call.
return {
"error": (
"Denied: price (price_per_call/price/cost) is missing or "
"invalid, cannot enforce the configured spend guard."
)
}, None, described
# Fail closed on non-finite (NaN/inf) or negative prices: NaN comparisons
# are always false, so an unvalidated NaN would silently bypass both the
# per-call and session guards and then corrupt ``_session_spend``.
if not math.isfinite(price) or price < 0:
return {
"error": (
"Denied: price (price_per_call/price/cost) is missing or "
"invalid, cannot enforce the configured spend guard."
)
}, None, described
if self.max_cost_per_call is not None and price > self.max_cost_per_call:
return {
"error": (
f"Denied: price per call {price} exceeds max_cost_per_call "
f"{self.max_cost_per_call}."
)
}, price, described
if (
self.max_session_spend is not None
and self._session_spend + price > self.max_session_spend
):
return {
"error": (
f"Denied: session spend would reach "
f"{self._session_spend + price}, exceeding max_session_spend "
f"{self.max_session_spend}."
)
}, price, described
return None, price, described
def call(
self,
tool_id: str,
params: Optional[Dict[str, Any]] = None,
method: Optional[str] = None,
) -> Dict[str, Any]:
"""Invoke an endpoint through the proxy (credential injected server-side).
The registry enforces each endpoint's declared HTTP method on
``/call/{id}``. When ``method`` is not supplied it is derived from
``describe`` (the endpoint doc carries ``method``); GET requests send
``params`` as the query string, POST/PUT (and others) send them as a
JSON body.
"""
missing = self._require_config()
if missing:
return missing
if not tool_id:
return {"error": "tool_id is required"}
denied, quoted_price, described = self._check_budget(tool_id)
if denied:
return denied
# Derive the HTTP method from the endpoint doc when not supplied. Reuse
# the describe fetched by the spend guard when present to avoid a second
# round-trip; otherwise fetch describe only when the method is unknown.
if method is None:
if described is None:
described = self.describe(tool_id)
if isinstance(described, dict) and "error" in described:
return described
method = self._extract_method(described)
method = (method or "POST").strip().upper()
if method not in _ALLOWED_METHODS:
return {
"error": (
f"Unsupported HTTP method '{method}'. Allowed: "
f"{', '.join(sorted(_ALLOWED_METHODS))}."
)
}
try:
import httpx
except ImportError:
return {"error": _INSTALL_HINT}
url = f"{self.proxy_url}/call/{quote(tool_id, safe='')}"
try:
with httpx.Client(timeout=self.timeout) as client:
if method == "GET":
response = client.get(
url, params=params or {}, headers=self._headers()
)
else:
response = client.request(
method, url, json=params or {}, headers=self._headers()
)
response.raise_for_status()
result = response.json()
except httpx.TimeoutException:
return {"error": f"Registry call timed out after {self.timeout} seconds"}
except httpx.HTTPStatusError as exc:
return self._http_error(exc)
except Exception as exc: # noqa: BLE001 - surface as tool-result error
logger.error("registry call error: %s", exc)
return {"error": str(exc)}
# Record cumulative spend. Prefer the charge reported by the proxy; fall
# back to the price quoted at budget-check time so the session budget
# still accrues when the response omits cost fields.
charged = self._extract_price(result)
try:
charged = float(charged)
if not math.isfinite(charged) or charged < 0:
raise ValueError("non-finite or negative charge")
except (TypeError, ValueError):
# The response omitted a usable charge; fall back to the finite,
# non-negative price validated at budget-check time so a malformed
# (NaN/inf/negative) response cannot corrupt cumulative spend.
charged = quoted_price
if charged is not None:
self._session_spend += charged
return result
@tool
def registry_search(
query: str,
proxy_url: Optional[str] = None,
token: Optional[str] = None,
auth_header: Optional[str] = None,
) -> Dict[str, Any]:
"""Search the connected tool registry by capability.
Free read. Returns catalogue matches for a natural-language capability query
such as "backlinks for a domain" or "company enrichment by email".
Args:
query: Capability to search for.
proxy_url: Registry base URL (defaults to TOOL_PROXY_URL env var).
token: Proxy token (defaults to TOOL_PROXY_TOKEN env var).
auth_header: Auth header name (defaults to TOOL_PROXY_AUTH_HEADER env var,
then ``Authorization``).
Returns:
Dict with catalogue matches, or ``{"error": ...}`` on failure.
"""
return RegistryProxyTool(
proxy_url=proxy_url, token=token, auth_header=auth_header
).search(query)
@tool
def registry_describe(
tool_id: str,
proxy_url: Optional[str] = None,
token: Optional[str] = None,
auth_header: Optional[str] = None,
describe_path: Optional[str] = None,
) -> Dict[str, Any]:
"""Describe one registry catalogue entry.
Free read. Returns the endpoint's parameters, price-per-call and an example
response so the model can decide whether and how to invoke it.
Args:
tool_id: Catalogue entry identifier (from ``registry_search``).
proxy_url: Registry base URL (defaults to TOOL_PROXY_URL env var).
token: Proxy token (defaults to TOOL_PROXY_TOKEN env var).
auth_header: Auth header name (defaults to TOOL_PROXY_AUTH_HEADER env var,
then ``Authorization``).
describe_path: Path template for the describe route (defaults to
TOOL_PROXY_DESCRIBE_PATH env var, then ``/catalog/endpoints/{tool_id}``).
Must contain ``{tool_id}``.
Returns:
Dict describing the entry, or ``{"error": ...}`` on failure.
"""
return RegistryProxyTool(
proxy_url=proxy_url, token=token, auth_header=auth_header,
describe_path=describe_path,
).describe(tool_id)
@tool
def registry_call(
tool_id: str,
params: Optional[Dict[str, Any]] = None,
proxy_url: Optional[str] = None,
token: Optional[str] = None,
max_cost_per_call: Optional[float] = None,
max_session_spend: Optional[float] = None,
auth_header: Optional[str] = None,
method: Optional[str] = None,
describe_path: Optional[str] = None,
) -> Dict[str, Any]:
"""Invoke a registry endpoint through the proxy.
Paid call. The registry injects the upstream vendor credential server-side,
so no vendor keys are ever held by the agent. Optional spend guards deny +
report the call when a configured budget would be exceeded.
The registry enforces each endpoint's declared HTTP method. When ``method``
is not supplied it is derived from ``registry_describe`` (the endpoint doc
carries ``method``); GET params are sent as the query string, POST/PUT as a
JSON body.
Note: passthrough-URL calls require the upstream to be registered on the
registry first; loopback/private upstreams are refused by the registry's
SSRF guard by design.
Args:
tool_id: Catalogue entry identifier (from ``registry_search``).
params: Parameters for the upstream endpoint.
proxy_url: Registry base URL (defaults to TOOL_PROXY_URL env var).
token: Proxy token (defaults to TOOL_PROXY_TOKEN env var).
max_cost_per_call: Deny the call if its price exceeds this value.
max_session_spend: Deny the call if it would push cumulative spend past this value.
auth_header: Auth header name (defaults to TOOL_PROXY_AUTH_HEADER env var,
then ``Authorization``). ``Authorization`` sends ``Bearer {token}``;
any other name (e.g. ``X-Treg-Token``) sends the raw token.
method: HTTP method for the endpoint (e.g. ``GET``/``POST``). When
omitted it is derived from the endpoint's describe doc.
describe_path: Path template for the describe route (defaults to
TOOL_PROXY_DESCRIBE_PATH env var, then ``/catalog/endpoints/{tool_id}``).
Returns:
Dict with the endpoint response, or ``{"error": ...}`` on failure/denial.
"""
return RegistryProxyTool(
proxy_url=proxy_url,
token=token,
max_cost_per_call=max_cost_per_call,
max_session_spend=max_session_spend,
auth_header=auth_header,
describe_path=describe_path,
).call(tool_id, params, method)
+857 -46
View File
@@ -14,64 +14,875 @@ Ready-to-use tools:
- WeatherTool: Get weather data
- YouTubeTool: Search YouTube, get transcripts
- TTSTool: Text-to-speech conversion
Tools are discovered automatically: adding a module under
``praisonai_tools/tools/`` exposes its public top-level classes and functions
without any manual registration. Imports remain lazy - a tool module (and its
optional dependencies) is only imported the first time one of its symbols is
accessed.
"""
import os
from praisonai_tools.tools.base import BaseTool, ToolResult, ToolValidationError, validate_tool
from praisonai_tools.tools.decorator import tool, FunctionTool, is_tool, get_tool_schema
from praisonai_tools.tools._discovery import build_manifest
# Symbols exported eagerly above (base classes + decorator helpers).
_BASE_EXPORTS = [
"BaseTool",
"ToolResult",
"ToolValidationError",
"validate_tool",
"tool",
"FunctionTool",
"is_tool",
"get_tool_schema",
]
# Build the discovery manifest once at import time. This only reads/parses
# source files (via AST) - it does NOT import any tool module, so lazy loading
# of heavy optional dependencies is preserved.
_TOOL_MANIFEST, _COLLISIONS = build_manifest(os.path.dirname(__file__))
# Backward-compatible alias. The catalogue/discovery contract in
# ``praisonai_tools.catalogue`` enumerates shipped tools via ``_TOOL_MAP``
# (name -> module). It is now derived from the auto-discovered manifest so the
# two can never drift apart.
_TOOL_MAP = _TOOL_MANIFEST
# Lazy imports for tools to avoid loading dependencies until needed
def __getattr__(name):
"""Lazily import a discovered tool symbol on first access."""
module_name = _TOOL_MANIFEST.get(name)
if module_name is not None:
from importlib import import_module
"""Lazy load tool classes."""
tool_map = {
# Email
"EmailTool": "email_tool",
"send_email": "email_tool",
"read_emails": "email_tool",
"search_emails": "email_tool",
# Slack
"SlackTool": "slack_tool",
"send_slack_message": "slack_tool",
"get_slack_channels": "slack_tool",
"get_slack_history": "slack_tool",
# Discord
"DiscordTool": "discord_tool",
"send_discord_webhook": "discord_tool",
"send_discord_message": "discord_tool",
# GitHub
"GitHubTool": "github_tool",
"search_github_repos": "github_tool",
"get_github_repo": "github_tool",
"create_github_issue": "github_tool",
# Image Generation
"ImageTool": "image_tool",
"generate_image": "image_tool",
# Weather
"WeatherTool": "weather_tool",
"get_weather": "weather_tool",
"get_forecast": "weather_tool",
"get_air_quality": "weather_tool",
# YouTube
"YouTubeTool": "youtube_tool",
"search_youtube": "youtube_tool",
"get_youtube_video": "youtube_tool",
"get_youtube_transcript": "youtube_tool",
# Text-to-Speech
"TTSTool": "tts_tool",
"text_to_speech": "tts_tool",
"list_tts_voices": "tts_tool",
# Telegram
"TelegramTool": "telegram_tool",
"send_telegram_message": "telegram_tool",
# Notion
"NotionTool": "notion_tool",
"search_notion": "notion_tool",
"create_notion_page": "notion_tool",
# PostgreSQL
"PostgresTool": "postgres_tool",
"query_postgres": "postgres_tool",
"list_postgres_tables": "postgres_tool",
# Reddit
"RedditTool": "reddit_tool",
"search_reddit": "reddit_tool",
"get_reddit_hot": "reddit_tool",
# Docker
"DockerTool": "docker_tool",
"list_docker_containers": "docker_tool",
"run_docker_container": "docker_tool",
# MySQL
"MySQLTool": "mysql_tool",
"query_mysql": "mysql_tool",
# SQLite
"SQLiteTool": "sqlite_tool",
"query_sqlite": "sqlite_tool",
# MongoDB
"MongoDBTool": "mongodb_tool",
"query_mongodb": "mongodb_tool",
# Redis
"RedisTool": "redis_tool",
"redis_get": "redis_tool",
"redis_set": "redis_tool",
# DuckDuckGo
"DuckDuckGoTool": "duckduckgo_tool",
"duckduckgo_search": "duckduckgo_tool",
# Tavily
"TavilyTool": "tavily_tool",
"tavily_search": "tavily_tool",
"tavily_extract": "tavily_tool",
# Wikipedia
"WikipediaTool": "wikipedia_tool",
"wikipedia_search": "wikipedia_tool",
# ArXiv
"ArxivTool": "arxiv_tool",
"arxiv_search": "arxiv_tool",
# Calculator
"CalculatorTool": "calculator_tool",
"calculate": "calculator_tool",
# Shell
"ShellTool": "shell_tool",
"shell_execute": "shell_tool",
# File
"FileTool": "file_tool",
"read_file": "file_tool",
"write_file": "file_tool",
# Firecrawl
"FirecrawlTool": "firecrawl_tool",
"firecrawl_scrape": "firecrawl_tool",
# Serper
"SerperTool": "serper_tool",
"serper_search": "serper_tool",
# Jina
"JinaTool": "jina_tool",
"jina_read": "jina_tool",
# Google Calendar
"GoogleCalendarTool": "google_calendar_tool",
"list_calendar_events": "google_calendar_tool",
# Google Sheets
"GoogleSheetsTool": "google_sheets_tool",
"read_google_sheet": "google_sheets_tool",
# Jira
"JiraTool": "jira_tool",
"jira_search": "jira_tool",
"jira_list_boards": "jira_tool",
"jira_get_board": "jira_tool",
"jira_get_board_issues": "jira_tool",
"jira_get_backlog": "jira_tool",
"jira_get_transitions": "jira_tool",
"jira_move_issue": "jira_tool",
"jira_create_task": "jira_tool",
# Trello
"TrelloTool": "trello_tool",
"list_trello_boards": "trello_tool",
# YFinance
"YFinanceTool": "yfinance_tool",
"get_stock_price": "yfinance_tool",
# Pinecone
"PineconeTool": "pinecone_tool",
"pinecone_query": "pinecone_tool",
# Qdrant
"QdrantTool": "qdrant_tool",
"qdrant_search": "qdrant_tool",
# Chroma
"ChromaTool": "chroma_tool",
"chroma_query": "chroma_tool",
# HackerNews
"HackerNewsTool": "hackernews_tool",
"get_hackernews_top": "hackernews_tool",
# Twilio
"TwilioTool": "twilio_tool",
"send_sms": "twilio_tool",
# Spotify
"SpotifyTool": "spotify_tool",
"spotify_search": "spotify_tool",
# Linear
"LinearTool": "linear_tool",
"list_linear_issues": "linear_tool",
# Crawl4AI
"Crawl4AITool": "crawl4ai_tool",
"crawl4ai_crawl": "crawl4ai_tool",
# Exa
"ExaTool": "exa_tool",
"exa_search": "exa_tool",
# DuckDB
"DuckDBTool": "duckdb_tool",
"duckdb_query": "duckdb_tool",
# Neo4j
"Neo4jTool": "neo4j_tool",
"neo4j_query": "neo4j_tool",
# Weaviate
"WeaviateTool": "weaviate_tool",
"weaviate_search": "weaviate_tool",
# LanceDB
"LanceDBTool": "lancedb_tool",
"lancedb_search": "lancedb_tool",
# Supabase
"SupabaseTool": "supabase_tool",
"supabase_select": "supabase_tool",
# Milvus
"MilvusTool": "milvus_tool",
"milvus_search": "milvus_tool",
# Google Maps
"GoogleMapsTool": "google_maps_tool",
"geocode_address": "google_maps_tool",
# Zendesk
"ZendeskTool": "zendesk_tool",
"list_zendesk_tickets": "zendesk_tool",
# Shopify
"ShopifyTool": "shopify_tool",
"list_shopify_products": "shopify_tool",
# Brave Search
"BraveSearchTool": "brave_search_tool",
"brave_search": "brave_search_tool",
# PubMed
"PubMedTool": "pubmed_tool",
"pubmed_search": "pubmed_tool",
# SerpAPI
"SerpAPITool": "serpapi_tool",
"serpapi_search": "serpapi_tool",
# SearxNG
"SearxNGTool": "searxng_tool",
"searxng_search": "searxng_tool",
# LinkUp
"LinkUpTool": "linkup_tool",
"linkup_search": "linkup_tool",
# Baidu Search
"BaiduSearchTool": "baidu_search_tool",
"baidu_search": "baidu_search_tool",
# Valyu
"ValyuTool": "valyu_tool",
"valyu_search": "valyu_tool",
# Gmail
"GmailTool": "gmail_tool",
"list_gmail_emails": "gmail_tool",
"gmail_archive_email": "gmail_tool",
"gmail_label_email": "gmail_tool",
"gmail_mark_read": "gmail_tool",
"gmail_draft_email": "gmail_tool",
"gmail_trash_email": "gmail_tool",
# Outlook
"OutlookTool": "outlook_tool",
"outlook_list_emails": "outlook_tool",
"outlook_send_email": "outlook_tool",
"outlook_search_emails": "outlook_tool",
"outlook_archive_email": "outlook_tool",
"outlook_draft_email": "outlook_tool",
# WhatsApp
"WhatsAppTool": "whatsapp_tool",
"send_whatsapp_message": "whatsapp_tool",
# Signal
"SignalTool": "signal_tool",
"send_signal_message": "signal_tool",
"check_signal_connection": "signal_tool",
# LINE
"LineTool": "line_tool",
"send_line_message": "line_tool",
"broadcast_line_message": "line_tool",
# iMessage
"iMessageTool": "imessage_tool",
"send_imessage": "imessage_tool",
"check_imessage_availability": "imessage_tool",
# Zoom
"ZoomTool": "zoom_tool",
"list_zoom_meetings": "zoom_tool",
# Webex
"WebexTool": "webex_tool",
"list_webex_rooms": "webex_tool",
# X (Twitter)
"XTool": "x_tool",
"post_to_x": "x_tool",
# Newspaper
"NewspaperTool": "newspaper_tool",
"extract_article": "newspaper_tool",
# Trafilatura
"TrafilaturaTool": "trafilatura_tool",
"trafilatura_extract": "trafilatura_tool",
# Spider
"SpiderTool": "spider_tool",
"spider_crawl": "spider_tool",
# BrowserBase
"BrowserBaseTool": "browserbase_tool",
"browserbase_scrape": "browserbase_tool",
# BrightData
"BrightDataTool": "brightdata_tool",
"brightdata_scrape": "brightdata_tool",
# Oxylabs
"OxylabsTool": "oxylabs_tool",
"oxylabs_scrape": "oxylabs_tool",
# ScrapeGraph
"ScrapeGraphTool": "scrapegraph_tool",
"scrapegraph_scrape": "scrapegraph_tool",
# AgentQL
"AgentQLTool": "agentql_tool",
"agentql_query": "agentql_tool",
# DynamoDB
"DynamoDBTool": "dynamodb_tool",
"dynamodb_scan": "dynamodb_tool",
# Firestore
"FirestoreTool": "firestore_tool",
"firestore_list": "firestore_tool",
# GCS
"GCSTool": "gcs_tool",
"gcs_list_objects": "gcs_tool",
# BigQuery
"BigQueryTool": "bigquery_tool",
"bigquery_query": "bigquery_tool",
# SingleStore
"SingleStoreTool": "singlestore_tool",
"singlestore_query": "singlestore_tool",
# SurrealDB
"SurrealDBTool": "surrealdb_tool",
"surrealdb_query": "surrealdb_tool",
# CSV
"CSVTool": "csv_tool",
"read_csv": "csv_tool",
# Pandas
"PandasTool": "pandas_tool",
"pandas_read_csv": "pandas_tool",
# Redshift
"RedshiftTool": "redshift_tool",
"redshift_query": "redshift_tool",
# ElevenLabs
"ElevenLabsTool": "elevenlabs_tool",
"elevenlabs_speak": "elevenlabs_tool",
"elevenlabs_speak_to_file": "elevenlabs_tool",
"elevenlabs_list_voices": "elevenlabs_tool",
"elevenlabs_get_voice": "elevenlabs_tool",
"elevenlabs_list_models": "elevenlabs_tool",
"elevenlabs_get_history": "elevenlabs_tool",
"elevenlabs_get_user_info": "elevenlabs_tool",
# Replicate
"ReplicateTool": "replicate_tool",
"replicate_run": "replicate_tool",
# Fal
"FalTool": "fal_tool",
"fal_run": "fal_tool",
# Giphy
"GiphyTool": "giphy_tool",
"giphy_search": "giphy_tool",
# Apify
"ApifyTool": "apify_tool",
"apify_run_actor": "apify_tool",
# Airflow
"AirflowTool": "airflow_tool",
"list_airflow_dags": "airflow_tool",
# AWS Lambda
"AWSLambdaTool": "aws_lambda_tool",
"invoke_lambda": "aws_lambda_tool",
# AWS SES
"AWSSESTool": "aws_ses_tool",
"ses_send_email": "aws_ses_tool",
# Resend
"ResendTool": "resend_tool",
"resend_send_email": "resend_tool",
# ClickUp
"ClickUpTool": "clickup_tool",
"clickup_list_tasks": "clickup_tool",
# Confluence
"ConfluenceTool": "confluence_tool",
"confluence_search": "confluence_tool",
# Todoist
"TodoistTool": "todoist_tool",
"todoist_list_tasks": "todoist_tool",
# Bitbucket
"BitbucketTool": "bitbucket_tool",
"bitbucket_list_repos": "bitbucket_tool",
# OpenBB
"OpenBBTool": "openbb_tool",
"openbb_stock": "openbb_tool",
# E2B
"E2BTool": "e2b_tool",
"e2b_run_code": "e2b_tool",
# Sleep
"SleepTool": "sleep_tool",
"sleep_wait": "sleep_tool",
# Python
"PythonTool": "python_tool",
"python_execute": "python_tool",
# Capsule
"CapsuleTool": "capsule_tool",
"capsule_run_code": "capsule_tool",
# Mem0
"Mem0Tool": "mem0_tool",
"mem0_add": "mem0_tool",
# PGVector
"PGVectorTool": "pgvector_tool",
"pgvector_search": "pgvector_tool",
# Cassandra
"CassandraTool": "cassandra_tool",
"cassandra_query": "cassandra_tool",
# ClickHouse
"ClickHouseTool": "clickhouse_tool",
"clickhouse_query": "clickhouse_tool",
# Upstash
"UpstashTool": "upstash_tool",
"upstash_get": "upstash_tool",
# Couchbase
"CouchbaseTool": "couchbase_tool",
"couchbase_get": "couchbase_tool",
# Google Drive
"GoogleDriveTool": "google_drive_tool",
"list_drive_files": "google_drive_tool",
# LumaLabs
"LumaLabsTool": "lumalabs_tool",
"lumalabs_generate": "lumalabs_tool",
# Langextract
"LangExtractTool": "langextract_tool",
"langextract_extract": "langextract_tool",
"langextract_render_file": "langextract_tool",
# HeyGen
"HeyGenTool": "heygen_tool",
"heygen_list_avatars": "heygen_tool",
"heygen_list_avatar_groups": "heygen_tool",
"heygen_list_group_avatars": "heygen_tool",
"heygen_get_avatar_details": "heygen_tool",
"heygen_list_voices": "heygen_tool",
"heygen_list_voice_locales": "heygen_tool",
"heygen_generate_video": "heygen_tool",
"heygen_generate_video_with_audio": "heygen_tool",
"heygen_upload_asset": "heygen_tool",
"heygen_video_status": "heygen_tool",
"heygen_wait_for_video": "heygen_tool",
"heygen_list_videos": "heygen_tool",
"heygen_delete_video": "heygen_tool",
"heygen_list_assets": "heygen_tool",
"heygen_delete_asset": "heygen_tool",
"heygen_get_remaining_quota": "heygen_tool",
"heygen_get_user_info": "heygen_tool",
"heygen_list_templates": "heygen_tool",
"heygen_generate_from_template": "heygen_tool",
"heygen_translate_video": "heygen_tool",
# Higgsfield
"HiggsfieldTool": "higgsfield_tool",
"higgsfield_generate": "higgsfield_tool",
"higgsfield_status": "higgsfield_tool",
"higgsfield_upload": "higgsfield_tool",
# OpenCV
"OpenCVTool": "opencv_tool",
"opencv_resize": "opencv_tool",
# CalCom
"CalComTool": "calcom_tool",
"calcom_list_bookings": "calcom_tool",
# Cartesia
"CartesiaTool": "cartesia_tool",
"cartesia_speak": "cartesia_tool",
# Brandfetch
"BrandfetchTool": "brandfetch_tool",
"brandfetch_get_brand": "brandfetch_tool",
# Daytona
"DaytonaTool": "daytona_tool",
"daytona_list_workspaces": "daytona_tool",
# Composio
"ComposioTool": "composio_tool",
"ComposioTools": "composio_tool",
"composio_execute": "composio_tool",
"composio_tools": "composio_tool",
"composio_list_apps": "composio_tool",
# JSON
"JSONTool": "json_tool",
"read_json": "json_tool",
# Zep
"ZepTool": "zep_tool",
"zep_add_memory": "zep_tool",
# WebBrowser
"WebBrowserTool": "webbrowser_tool",
"webbrowser_get_page": "webbrowser_tool",
# WebTools
"WebToolsTool": "webtools_tool",
"webtools_fetch": "webtools_tool",
# LocalFileSystem
"LocalFileSystemTool": "local_filesystem_tool",
"list_local_directory": "local_filesystem_tool",
# Knowledge
"KnowledgeTool": "knowledge_tool",
"knowledge_search": "knowledge_tool",
# Visualization
"VisualizationTool": "visualization_tool",
"create_bar_chart": "visualization_tool",
"SQLiteVectorTool": "sqlite_vector_tool",
"sqlite_vector_query": "sqlite_vector_tool",
"sqlite_vector_add": "sqlite_vector_tool",
# WordPress
"WordPressTool": "wordpress_tool",
"check_wp_duplicate": "wordpress_tool",
"create_wp_post": "wordpress_tool",
# Marketplace Tools
"PinchworkTool": "pinchwork_tool",
"pinchwork_delegate": "pinchwork_tool",
"AgentIDTool": "agentid_tool",
"verify_agent_identity": "agentid_tool",
"JoyTrustTool": "joy_trust_tool",
"check_trust_score": "joy_trust_tool",
"verify_handoff_safety": "joy_trust_tool",
"trust_verified_handoff": "joy_trust_tool",
"is_trust_verification_enabled": "joy_trust_tool",
"get_trust_config": "joy_trust_tool",
"AgentFolioTool": "agentfolio_tool",
"check_behavioral_trust": "agentfolio_tool",
"verify_task_delegation_safety": "agentfolio_tool",
# LinkedIn
"LinkedInTool": "linkedin_tool",
"linkedin_post_text": "linkedin_tool",
"linkedin_post_image": "linkedin_tool",
"linkedin_post_article": "linkedin_tool",
"linkedin_get_profile": "linkedin_tool",
"linkedin_delete_post": "linkedin_tool",
# Facebook
"FacebookTool": "facebook_tool",
"facebook_post_text": "facebook_tool",
"facebook_post_image": "facebook_tool",
"facebook_post_link": "facebook_tool",
"facebook_post_video": "facebook_tool",
"facebook_get_page_info": "facebook_tool",
"facebook_delete_post": "facebook_tool",
# Instagram
"InstagramTool": "instagram_tool",
"instagram_post_image": "instagram_tool",
"instagram_post_carousel": "instagram_tool",
"instagram_post_reel": "instagram_tool",
"instagram_get_media": "instagram_tool",
"instagram_get_account_info": "instagram_tool",
# TikTok
"TikTokTool": "tiktok_tool",
"tiktok_post_video": "tiktok_tool",
"tiktok_post_photo": "tiktok_tool",
"tiktok_get_creator_info": "tiktok_tool",
"tiktok_get_post_status": "tiktok_tool",
# Threads
"ThreadsTool": "threads_tool",
"threads_post_text": "threads_tool",
"threads_post_image": "threads_tool",
"threads_post_video": "threads_tool",
"threads_get_threads": "threads_tool",
"threads_get_profile": "threads_tool",
# Pinterest
"PinterestTool": "pinterest_tool",
"pinterest_create_pin": "pinterest_tool",
"pinterest_list_boards": "pinterest_tool",
"pinterest_get_pin": "pinterest_tool",
"pinterest_delete_pin": "pinterest_tool",
"pinterest_get_account_info": "pinterest_tool",
# Medium
"MediumTool": "medium_tool",
"medium_publish_post": "medium_tool",
"medium_get_user": "medium_tool",
"medium_list_publications": "medium_tool",
"medium_publish_to_publication": "medium_tool",
# n8n Tools
"N8nWorkflowTool": "praisonai_tools.n8n.n8n_workflow",
"n8n_workflow": "praisonai_tools.n8n.n8n_workflow",
"n8n_list_workflows": "praisonai_tools.n8n.n8n_workflow",
}
if name in tool_map:
module_name = tool_map[name]
from importlib import import_module
# Handle absolute module paths (e.g., praisonai_tools.n8n.n8n_workflow)
if module_name.startswith("praisonai_tools."):
module = import_module(module_name)
else:
# Handle relative module paths within tools package
module = import_module(f".{module_name}", __package__)
return getattr(module, name)
raise AttributeError(f"module {__name__!r} has no attribute {name!r}")
def __dir__():
return sorted(set(_BASE_EXPORTS) | set(_TOOL_MANIFEST))
# ``__all__`` is derived from the same manifest as ``__getattr__`` so the two
# can never drift apart.
__all__ = sorted(set(_BASE_EXPORTS) | set(_TOOL_MANIFEST))
__all__ = [
# Base classes
"BaseTool",
"ToolResult",
"ToolValidationError",
"validate_tool",
# Decorator
"tool",
"FunctionTool",
"is_tool",
"get_tool_schema",
# Email Tool
"EmailTool",
"send_email",
"read_emails",
"search_emails",
# Slack Tool
"SlackTool",
"send_slack_message",
"get_slack_channels",
"get_slack_history",
# Discord Tool
"DiscordTool",
"send_discord_webhook",
"send_discord_message",
# GitHub Tool
"GitHubTool",
"search_github_repos",
"get_github_repo",
"create_github_issue",
# Image Tool
"ImageTool",
"generate_image",
# Weather Tool
"WeatherTool",
"get_weather",
"get_forecast",
"get_air_quality",
# YouTube Tool
"YouTubeTool",
"search_youtube",
"get_youtube_video",
"get_youtube_transcript",
# TTS Tool
"TTSTool",
"text_to_speech",
"list_tts_voices",
# Telegram Tool
"TelegramTool",
"send_telegram_message",
# Notion Tool
"NotionTool",
"search_notion",
"create_notion_page",
# PostgreSQL Tool
"PostgresTool",
"query_postgres",
"list_postgres_tables",
# Reddit Tool
"RedditTool",
"search_reddit",
"get_reddit_hot",
# Docker Tool
"DockerTool",
"list_docker_containers",
"run_docker_container",
# MySQL Tool
"MySQLTool",
"query_mysql",
# SQLite Tool
"SQLiteTool",
"query_sqlite",
# MongoDB Tool
"MongoDBTool",
"query_mongodb",
# Redis Tool
"RedisTool",
"redis_get",
"redis_set",
# DuckDuckGo Tool
"DuckDuckGoTool",
"duckduckgo_search",
# Tavily Tool
"TavilyTool",
"tavily_search",
"tavily_extract",
# Wikipedia Tool
"WikipediaTool",
"wikipedia_search",
# ArXiv Tool
"ArxivTool",
"arxiv_search",
# Calculator Tool
"CalculatorTool",
"calculate",
# Shell Tool
"ShellTool",
"shell_execute",
# File Tool
"FileTool",
"read_file",
"write_file",
# Firecrawl Tool
"FirecrawlTool",
"firecrawl_scrape",
# Serper Tool
"SerperTool",
"serper_search",
# Jina Tool
"JinaTool",
"jina_read",
# Google Calendar Tool
"GoogleCalendarTool",
"list_calendar_events",
# Google Sheets Tool
"GoogleSheetsTool",
"read_google_sheet",
# Jira Tool
"JiraTool",
"jira_search",
"jira_list_boards",
"jira_get_board",
"jira_get_board_issues",
"jira_get_backlog",
"jira_get_transitions",
"jira_move_issue",
"jira_create_task",
# Trello Tool
"TrelloTool",
"list_trello_boards",
# YFinance Tool
"YFinanceTool",
"get_stock_price",
# Pinecone Tool
"PineconeTool",
"pinecone_query",
# Qdrant Tool
"QdrantTool",
"qdrant_search",
# Chroma Tool
"ChromaTool",
"chroma_query",
# HackerNews Tool
"HackerNewsTool",
"get_hackernews_top",
# Twilio Tool
"TwilioTool",
"send_sms",
# Spotify Tool
"SpotifyTool",
"spotify_search",
# Linear Tool
"LinearTool",
"list_linear_issues",
# Crawl4AI Tool
"Crawl4AITool",
"crawl4ai_crawl",
# Exa Tool
"ExaTool",
"exa_search",
# DuckDB Tool
"DuckDBTool",
"duckdb_query",
# Neo4j Tool
"Neo4jTool",
"neo4j_query",
# Weaviate Tool
"WeaviateTool",
"weaviate_search",
# LanceDB Tool
"LanceDBTool",
"lancedb_search",
# Supabase Tool
"SupabaseTool",
"supabase_select",
# Milvus Tool
"MilvusTool",
"milvus_search",
# Google Maps Tool
"GoogleMapsTool",
"geocode_address",
# Zendesk Tool
"ZendeskTool",
"list_zendesk_tickets",
# Shopify Tool
"ShopifyTool",
"list_shopify_products",
# SQLite Vector Store (zero deps)
"SQLiteVectorTool",
"sqlite_vector_query",
"sqlite_vector_add",
# WordPress Tool (requires praisonaiwp)
"WordPressTool",
"check_wp_duplicate",
"create_wp_post",
# HeyGen Tool
"HeyGenTool",
"heygen_list_avatars",
"heygen_list_avatar_groups",
"heygen_list_group_avatars",
"heygen_get_avatar_details",
"heygen_list_voices",
"heygen_list_voice_locales",
"heygen_generate_video",
"heygen_generate_video_with_audio",
"heygen_upload_asset",
"heygen_video_status",
"heygen_wait_for_video",
"heygen_list_videos",
"heygen_delete_video",
"heygen_list_assets",
"heygen_delete_asset",
"heygen_get_remaining_quota",
"heygen_get_user_info",
"heygen_list_templates",
"heygen_generate_from_template",
"heygen_translate_video",
# ElevenLabs Tool
"ElevenLabsTool",
"elevenlabs_speak",
"elevenlabs_speak_to_file",
"elevenlabs_list_voices",
"elevenlabs_get_voice",
"elevenlabs_list_models",
"elevenlabs_get_history",
"elevenlabs_get_user_info",
# Higgsfield Tool
"HiggsfieldTool",
"higgsfield_generate",
"higgsfield_status",
"higgsfield_upload",
# Signal Tool
"SignalTool",
"send_signal_message",
"check_signal_connection",
# LINE Tool
"LineTool",
"send_line_message",
"broadcast_line_message",
# iMessage Tool
"iMessageTool",
"send_imessage",
"check_imessage_availability",
# Gmail Tool (extended)
"GmailTool",
"list_gmail_emails",
"gmail_archive_email",
"gmail_label_email",
"gmail_mark_read",
"gmail_draft_email",
"gmail_trash_email",
# Outlook Tool
"OutlookTool",
"outlook_list_emails",
"outlook_send_email",
"outlook_search_emails",
"outlook_archive_email",
"outlook_draft_email",
# Marketplace Tools
"PinchworkTool",
"pinchwork_delegate",
"AgentIDTool",
"verify_agent_identity",
"JoyTrustTool",
"check_trust_score",
"verify_handoff_safety",
"trust_verified_handoff",
"is_trust_verification_enabled",
"get_trust_config",
"AgentFolioTool",
"check_behavioral_trust",
"verify_task_delegation_safety",
# LinkedIn Tool
"LinkedInTool",
"linkedin_post_text",
"linkedin_post_image",
"linkedin_post_article",
"linkedin_get_profile",
"linkedin_delete_post",
# Facebook Tool
"FacebookTool",
"facebook_post_text",
"facebook_post_image",
"facebook_post_link",
"facebook_post_video",
"facebook_get_page_info",
"facebook_delete_post",
# Instagram Tool
"InstagramTool",
"instagram_post_image",
"instagram_post_carousel",
"instagram_post_reel",
"instagram_get_media",
"instagram_get_account_info",
# TikTok Tool
"TikTokTool",
"tiktok_post_video",
"tiktok_post_photo",
"tiktok_get_creator_info",
"tiktok_get_post_status",
# Threads Tool
"ThreadsTool",
"threads_post_text",
"threads_post_image",
"threads_post_video",
"threads_get_threads",
"threads_get_profile",
# Pinterest Tool
"PinterestTool",
"pinterest_create_pin",
"pinterest_list_boards",
"pinterest_get_pin",
"pinterest_delete_pin",
"pinterest_get_account_info",
# Medium Tool
"MediumTool",
"medium_publish_post",
"medium_get_user",
"medium_list_publications",
"medium_publish_to_publication",
# n8n Tool
"N8nWorkflowTool",
"n8n_workflow",
"n8n_list_workflows",
# Langextract Tool
"LangExtractTool",
"langextract_extract",
"langextract_render_file",
]
-208
View File
@@ -1,208 +0,0 @@
"""Automatic tool discovery for praisonai_tools.tools.
Builds a ``name -> module`` manifest by scanning the source of every tool
module in this package *without importing it*. Public top-level classes and
functions (names not starting with ``_``) become part of the public surface.
This preserves the per-symbol lazy import behaviour of the old hand-maintained
``tool_map`` while eliminating the three-place bookkeeping (the map plus two
``__all__`` blocks) that previously had to stay in lock-step. Adding a tool is
now just adding one module under ``praisonai_tools/tools/``.
"""
from __future__ import annotations
import ast
import json
import logging
import os
from typing import Dict, List, Tuple
logger = logging.getLogger(__name__)
# Cache file name written alongside the tools package. Bumping ``_CACHE_VERSION``
# invalidates all previously written caches after a discovery-format change.
_CACHE_VERSION = 1
_CACHE_FILENAME = f"._discovery_cache_v{_CACHE_VERSION}.json"
# Modules in *this* package directory that are infrastructure, not tools.
# Their public symbols are exported explicitly by ``tools/__init__.py`` and
# must not be treated as discovered tools.
_SKIP_MODULES = {"__init__", "base", "decorator", "_discovery"}
# Tools that physically live outside ``praisonai_tools/tools/`` but have always
# been importable from it. Maps public symbol -> absolute module path.
_EXTERNAL_SYMBOLS: Dict[str, str] = {
"N8nWorkflowTool": "praisonai_tools.n8n.n8n_workflow",
"n8n_workflow": "praisonai_tools.n8n.n8n_workflow",
"n8n_list_workflows": "praisonai_tools.n8n.n8n_workflow",
}
def _extract_all(tree: ast.Module) -> List[str] | None:
"""Return the names listed in a module-level ``__all__``, if declared.
Only literal string entries are honoured. Returns ``None`` when the module
does not declare ``__all__`` at the top level.
"""
for node in tree.body:
if isinstance(node, ast.Assign):
targets = node.targets
elif isinstance(node, ast.AnnAssign) and node.value is not None:
targets = [node.target]
else:
continue
for target in targets:
if isinstance(target, ast.Name) and target.id == "__all__":
if isinstance(node.value, (ast.List, ast.Tuple, ast.Set)):
names: List[str] = []
for elt in node.value.elts:
if isinstance(elt, ast.Constant) and isinstance(elt.value, str):
names.append(elt.value)
return names
return None
def _iter_public_symbols(source: str, module_name: str = "<unknown>") -> List[str]:
"""Return the public top-level symbol names exported by ``source``.
Uses AST parsing so the module body is never executed (its heavy/optional
dependencies are not imported at discovery time).
Resolution order:
1. If the module declares ``__all__``, honour it verbatim (author intent).
This lets a module opt its module-level re-export aliases into the public
surface (e.g. ``read_yaml = _yaml_tools.read_yaml``) or, conversely,
narrow what is exported.
2. Otherwise, collect public top-level classes and functions. Bare
assignment aliases are intentionally *not* auto-exported without an
explicit ``__all__``: several ``*_tools.py`` modules bind the same
helper names (``read_csv``/``read_excel``/…) that would otherwise
collide across modules and were never part of the historical public API.
"""
try:
tree = ast.parse(source)
except SyntaxError as exc: # pragma: no cover - defensive
logger.warning(
"Tool discovery: could not parse %r (%s); its tools will not be "
"discoverable. Fix the syntax error to restore them.",
module_name, exc,
)
return []
explicit = _extract_all(tree)
if explicit is not None:
return [name for name in explicit if not name.startswith("_")]
symbols: List[str] = []
for node in tree.body:
if isinstance(node, (ast.FunctionDef, ast.AsyncFunctionDef, ast.ClassDef)):
if not node.name.startswith("_"):
symbols.append(node.name)
return symbols
def _fingerprint(package_dir: str) -> str:
"""Cheap directory fingerprint used to validate the discovery cache.
Reflects the set of ``.py`` files and their size/mtime, so any edit,
addition, or removal of a tool module invalidates the cache (keeping
discovery fully automatic) without re-parsing on every import.
"""
parts: List[str] = [f"v{_CACHE_VERSION}"]
for filename in sorted(os.listdir(package_dir)):
if not filename.endswith(".py"):
continue
try:
st = os.stat(os.path.join(package_dir, filename))
except OSError: # pragma: no cover - defensive
continue
parts.append(f"{filename}:{st.st_size}:{st.st_mtime_ns}")
return "|".join(parts)
def build_manifest(package_dir: str) -> Tuple[Dict[str, str], Dict[str, List[str]]]:
"""Return the discovery manifest for ``package_dir``, using a disk cache.
The manifest is expensive to compute (it AST-parses every tool module), so
the result is memoised in a small JSON file next to the package and reused
while the directory fingerprint is unchanged. The cache is best-effort:
any read/write/validation failure falls back to a live scan, so behaviour
is always correct even on read-only installs.
"""
cache_path = os.path.join(package_dir, _CACHE_FILENAME)
fingerprint = _fingerprint(package_dir)
try:
with open(cache_path, "r", encoding="utf-8") as fh:
cached = json.load(fh)
if cached.get("fingerprint") == fingerprint:
return cached["manifest"], cached["collisions"]
except (OSError, ValueError, KeyError):
pass # No/invalid cache -> scan below.
manifest, collisions = _scan_manifest(package_dir)
try:
tmp_path = f"{cache_path}.{os.getpid()}.tmp"
with open(tmp_path, "w", encoding="utf-8") as fh:
json.dump(
{
"fingerprint": fingerprint,
"manifest": manifest,
"collisions": collisions,
},
fh,
)
os.replace(tmp_path, cache_path)
except OSError: # pragma: no cover - read-only install, cache disabled.
pass
return manifest, collisions
def _scan_manifest(package_dir: str) -> Tuple[Dict[str, str], Dict[str, List[str]]]:
"""AST-scan ``package_dir`` and build the discovery manifest.
Returns a tuple ``(manifest, collisions)`` where ``manifest`` maps each
public symbol name to the module it should be imported from, and
``collisions`` maps any symbol defined in more than one module to the list
of modules that define it (first one wins in the manifest).
"""
manifest: Dict[str, str] = {}
collisions: Dict[str, List[str]] = {}
for filename in sorted(os.listdir(package_dir)):
if not filename.endswith(".py"):
continue
module_name = filename[:-3]
# Skip infrastructure modules and any private (underscore-prefixed)
# module so internal/experimental code does not leak into the public
# surface by convention.
if module_name in _SKIP_MODULES or module_name.startswith("_"):
continue
path = os.path.join(package_dir, filename)
try:
with open(path, "r", encoding="utf-8") as fh:
source = fh.read()
except OSError: # pragma: no cover - defensive
continue
for symbol in _iter_public_symbols(source, module_name):
if symbol in manifest and manifest[symbol] != module_name:
collisions.setdefault(symbol, [manifest[symbol]])
collisions[symbol].append(module_name)
logger.warning(
"Tool discovery: symbol %r defined in both %r and %r; "
"keeping %r. Rename one to avoid shadowing.",
symbol, manifest[symbol], module_name, manifest[symbol],
)
continue
manifest[symbol] = module_name
# External tools that live in sibling packages but are re-exported here.
for symbol, module in _EXTERNAL_SYMBOLS.items():
manifest.setdefault(symbol, module)
return manifest, collisions
+2 -22
View File
@@ -261,17 +261,7 @@ def check_behavioral_trust(
min_trust_score: float = 50.0,
organization_filter: Optional[str] = None
) -> Dict[str, Any]:
"""Check an agent's behavioral trust score across organizations using SATP protocol.
Args:
agent_name: Name/identifier of the agent to check.
task_class: Type of task for scoped trust (e.g., "code_review").
min_trust_score: Minimum trust score threshold (0-100, default: 50.0).
organization_filter: Optional filter for specific organization history.
Returns:
Dictionary with behavioral trust data.
"""
"""Check an agent's behavioral trust score across organizations using SATP protocol."""
return AgentFolioTool().check_behavioral_trust(
agent_name=agent_name,
task_class=task_class,
@@ -286,17 +276,7 @@ def verify_task_delegation_safety(
task_description: str,
required_trust_level: float = 70.0
) -> Dict[str, Any]:
"""Comprehensive safety check before delegating tasks using all trust layers.
Args:
agent_name: Name/identifier of the agent to check.
task_class: Type of task for scoped trust (e.g., "code_review").
task_description: Natural-language description of the task to delegate.
required_trust_level: Minimum trust level required (0-100, default: 70.0).
Returns:
Dictionary with safety assessment and recommendations.
"""
"""Comprehensive safety check before delegating tasks using all trust layers."""
return AgentFolioTool().verify_delegation_safety(
agent_name=agent_name,
task_class=task_class,
+1 -11
View File
@@ -130,15 +130,5 @@ class AgentIDTool(BaseTool):
def verify_agent_identity(agent_url: str) -> Dict[str, Any]:
"""Verify an external agent's identity using AgentID certificates.
Args:
agent_url: URL of the agent to verify.
Returns:
Dictionary with verification result. Always includes ``verified``,
``trust_score``, ``certificate``, ``agent_url`` and ``error``.
Successful verifications also include a ``timestamp`` field; failures
populate ``error`` with a human-readable message.
"""
"""Verify an external agent's identity using AgentID certificates."""
return AgentIDTool().verify(agent_url=agent_url)
+1 -44
View File
@@ -17,51 +17,8 @@ Usage:
return [...]
"""
import logging as _logging
class _SuppressRegistryNoneWarning(_logging.Filter):
"""Drop the benign "Registry is None for tool …" WARNING.
``praisonaiagents.tools.decorator`` logs a WARNING for every ``@tool``
decorated function when no global tool registry exists yet. On a bare
``import`` (library use, scripts, pytest collection) that is the normal
state, not an anomaly - registration happens lazily once an agent/registry
comes up. The message fires once per decorated function, so the noise scales
with the tool catalogue and is the first thing every consumer sees. We drop
only that specific record and leave all other logging untouched.
"""
def filter(self, record: _logging.LogRecord) -> bool:
return not record.getMessage().startswith("Registry is None for tool")
def _silence_registry_none_warning() -> None:
"""Install the filter so bare imports stay quiet at default log levels.
The upstream code emits the record via ``logging.warning`` (the root
logger), and ``praisonaiagents`` configures a handler on the root logger, so
the record surfaces there. We attach the filter to the root logger and its
handlers - it only drops the single "Registry is None for tool …" record and
passes everything else through, so user logging is unaffected. The proper fix
(defer registration / downgrade to debug) belongs in praisonaiagents core.
"""
filt = _SuppressRegistryNoneWarning()
root = _logging.getLogger()
root.addFilter(filt)
for handler in root.handlers:
handler.addFilter(filt)
# ``praisonaiagents`` configures root logging on import; do it first so its
# handlers exist, then attach the filter before any module-level ``@tool``
# decoration runs.
import praisonaiagents # noqa: E402,F401 (import for logging side effects only)
_silence_registry_none_warning()
# Import from praisonaiagents - single source of truth
from praisonaiagents.tools.decorator import ( # noqa: E402
from praisonaiagents.tools.decorator import (
tool,
FunctionTool,
is_tool,
+18 -86
View File
@@ -25,7 +25,7 @@ class FirecrawlTool(BaseTool):
"""Tool for web scraping using Firecrawl."""
name = "firecrawl"
description = "Scrape, crawl, and search the web using Firecrawl."
description = "Scrape and crawl websites using Firecrawl."
def __init__(self, api_key: Optional[str] = None):
self.api_key = api_key or os.getenv("FIRECRAWL_API_KEY")
@@ -38,12 +38,10 @@ class FirecrawlTool(BaseTool):
if not self.api_key:
raise ValueError("FIRECRAWL_API_KEY is required")
try:
from firecrawl import Firecrawl
from firecrawl import FirecrawlApp
except ImportError:
raise ImportError(
"firecrawl-py>=4 not installed. Install with: pip install 'firecrawl-py>=4'"
)
self._client = Firecrawl(api_key=self.api_key)
raise ImportError("firecrawl-py not installed. Install with: pip install firecrawl-py")
self._client = FirecrawlApp(api_key=self.api_key)
return self._client
def run(
@@ -58,8 +56,6 @@ class FirecrawlTool(BaseTool):
return self.scrape(url=url, **kwargs)
elif action == "crawl":
return self.crawl(url=url, **kwargs)
elif action == "search":
return self.search(query=kwargs.get("query") or url, limit=kwargs.get("limit", 5))
else:
return {"error": f"Unknown action: {action}"}
@@ -72,28 +68,16 @@ class FirecrawlTool(BaseTool):
return {"error": "FIRECRAWL_API_KEY not configured"}
try:
# firecrawl-py v2 (>=4): kwargs instead of a params dict; returns a
# typed Document, not a dict.
kwargs: Dict[str, Any] = {}
params = {}
if formats:
kwargs["formats"] = formats
result = self.client.scrape(url, **kwargs)
# v2 returns a Document object; metadata is a typed DocumentMetadata.
# Coerce to a plain dict to keep this tool's return shape stable.
metadata = getattr(result, "metadata", None)
if metadata is not None and hasattr(metadata, "model_dump"):
metadata = metadata.model_dump(exclude_none=True)
elif metadata is None:
metadata = {}
markdown = getattr(result, "markdown", None) or ""
params["formats"] = formats
result = self.client.scrape_url(url, params=params if params else None)
return {
"url": url,
"markdown": markdown[:5000],
"metadata": metadata,
"markdown": result.get("markdown", "")[:5000],
"metadata": result.get("metadata", {}),
}
except Exception as e:
logger.error(f"Firecrawl scrape error: {e}")
@@ -108,77 +92,25 @@ class FirecrawlTool(BaseTool):
return [{"error": "FIRECRAWL_API_KEY not configured"}]
try:
# `limit` may arrive as a string (e.g. "10") or None when invoked by
# an LLM/agent; coerce to int so the SDK call and `data[:limit]` slice
# below don't raise TypeError.
try:
limit = int(limit) if limit is not None else 10
except (ValueError, TypeError):
limit = 10
# firecrawl-py v2 (>=4): kwargs instead of a params dict; returns a
# typed CrawlJob whose `.data` is a list of Document objects.
result = self.client.crawl(
result = self.client.crawl_url(
url,
limit=limit,
params={"limit": limit},
poll_interval=5,
)
data = getattr(result, "data", None) or []
pages = []
for page in data[:limit]:
metadata = getattr(page, "metadata", None)
for page in result.get("data", [])[:limit]:
pages.append({
"url": getattr(metadata, "source_url", None),
"title": getattr(metadata, "title", None),
"markdown": (getattr(page, "markdown", None) or "")[:2000],
"url": page.get("metadata", {}).get("sourceURL"),
"title": page.get("metadata", {}).get("title"),
"markdown": page.get("markdown", "")[:2000],
})
return pages
except Exception as e:
logger.error(f"Firecrawl crawl error: {e}")
return [{"error": str(e)}]
def search(self, query: str, limit: int = 5) -> List[Dict[str, Any]]:
"""Search the web and return results."""
if not query:
return [{"error": "query is required"}]
if not self.api_key:
return [{"error": "FIRECRAWL_API_KEY not configured"}]
try:
# `limit` may arrive as a string or None from an LLM/agent; coerce to
# int so the SDK call and `web[:limit]` slice below don't raise.
try:
limit = int(limit) if limit is not None else 5
except (ValueError, TypeError):
limit = 5
# firecrawl-py v2 returns a typed SearchData object whose results are
# grouped by source; read the web results and coerce to plain dicts.
result = self.client.search(query, limit=limit)
web = getattr(result, "web", None) or []
results = []
for item in web[:limit]:
results.append({
"url": getattr(item, "url", None),
"title": getattr(item, "title", None),
"description": getattr(item, "description", None),
"markdown": (getattr(item, "markdown", None) or "")[:2000],
})
return results
except Exception as e:
logger.error(f"Firecrawl search error: {e}")
return [{"error": str(e)}]
def firecrawl_scrape(url: str) -> Dict[str, Any]:
"""Scrape URL with Firecrawl."""
return FirecrawlTool().scrape(url=url)
def firecrawl_search(query: str, limit: int = 5) -> List[Dict[str, Any]]:
"""Search the web with Firecrawl."""
return FirecrawlTool().search(query=query, limit=limit)
-268
View File
@@ -1,268 +0,0 @@
"""Fireflies.ai Tool for PraisonAI Agents.
Curated GraphQL operations over the Fireflies.ai meeting-intelligence API:
list recent meetings, fetch a transcript, and keyword search.
Design (Option B from the issue): each agent-callable method maps to a small,
pre-approved GraphQL document rather than letting the LLM craft arbitrary
queries. This keeps the surface predictable and robust.
Usage:
from praisonai_tools import FirefliesTool
fireflies = FirefliesTool()
meetings = fireflies.list_recent_meetings(limit=5)
transcript = fireflies.get_transcript(meeting_id="abc123")
Environment Variables:
FIREFLIES_API_KEY: Fireflies API key (sent as ``Authorization: Bearer <key>``)
FIREFLIES_API_URL: Optional endpoint override (defaults to the public API)
"""
import os
import logging
from typing import Any, Dict, List, Optional, Union
from praisonai_tools.tools.base import BaseTool
logger = logging.getLogger(__name__)
DEFAULT_API_URL = "https://api.fireflies.ai/graphql"
class FirefliesTool(BaseTool):
"""Tool for querying Fireflies.ai meeting intelligence via curated GraphQL."""
name = "fireflies"
description = (
"Query Fireflies.ai meeting intelligence: list recent meetings, "
"fetch transcripts, and search by keyword."
)
def __init__(
self,
api_key: Optional[str] = None,
api_url: Optional[str] = None,
):
self.api_key = api_key or os.getenv("FIREFLIES_API_KEY")
self.api_url = api_url or os.getenv("FIREFLIES_API_URL") or DEFAULT_API_URL
super().__init__()
def _graphql(self, query: str, variables: Dict = None) -> Dict:
"""Execute a curated GraphQL document, returning normalized results.
Missing credentials are reported distinctly from HTTP auth failures so
callers can tell a misconfiguration (no key) apart from a rejected key
(401/403).
"""
if not self.api_key:
return {"error": "FIREFLIES_API_KEY required"}
# Never transmit the API key over a plaintext endpoint.
if not self.api_url.lower().startswith("https://"):
return {"error": "FIREFLIES_API_URL must use HTTPS"}
try:
import requests
except ImportError:
return {"error": "requests not installed"}
try:
resp = requests.post(
self.api_url,
headers={
"Authorization": f"Bearer {self.api_key}",
"Content-Type": "application/json",
},
json={"query": query, "variables": variables or {}},
timeout=30,
)
except Exception as e:
return {"error": str(e)}
if resp.status_code in (401, 403):
return {
"error": f"Fireflies authentication failed (HTTP {resp.status_code})",
"status_code": resp.status_code,
}
if resp.status_code == 429:
retry_after = resp.headers.get("Retry-After") or self._graphql_retry_after(resp)
error = {"error": "Fireflies rate limit exceeded", "status_code": 429}
if retry_after:
error["retry_after"] = retry_after
return error
try:
payload = resp.json()
except Exception:
return {
"error": f"Fireflies returned non-JSON response (HTTP {resp.status_code})",
"status_code": resp.status_code,
}
if payload.get("errors"):
messages = [e.get("message", "unknown error") for e in payload["errors"]]
return {"error": "; ".join(messages)}
# Surface any remaining HTTP failure instead of letting an error body be
# normalized into an empty/missing result by the operation handlers.
if resp.status_code >= 400:
return {
"error": f"Fireflies request failed (HTTP {resp.status_code})",
"status_code": resp.status_code,
}
return payload
@staticmethod
def _graphql_retry_after(resp) -> Optional[str]:
"""Extract retryAfter from a GraphQL 429 body when the header is absent."""
try:
body = resp.json()
except Exception:
return None
for err in body.get("errors") or []:
metadata = ((err.get("extensions") or {}).get("metadata")) or {}
if metadata.get("retryAfter"):
return str(metadata["retryAfter"])
return None
def run(
self,
action: str = "list_recent_meetings",
meeting_id: Optional[str] = None,
keywords: Optional[str] = None,
**kwargs,
) -> Union[str, Dict[str, Any], List[Dict[str, Any]]]:
action = action.lower().replace("-", "_")
if action == "list_recent_meetings":
return self.list_recent_meetings(**kwargs)
elif action == "get_transcript":
return self.get_transcript(meeting_id=meeting_id)
elif action == "search":
return self.search(keywords=keywords, **kwargs)
else:
return {"error": f"Unknown action: {action}"}
def list_recent_meetings(
self, limit: int = 10, after: Optional[str] = None
) -> List[Dict[str, Any]]:
"""List recent meetings/transcripts.
Args:
limit: Maximum number of meetings to return.
after: Cursor (skip offset) for pagination. Explicit paging avoids
unbounded scans of the account history.
"""
query = """
query($limit: Int, $skip: Int) {
transcripts(limit: $limit, skip: $skip) {
id
title
date
duration
organizer_email
}
}
"""
limit = max(1, min(limit, 50)) # Fireflies caps page size at 50.
variables: Dict[str, Any] = {"limit": limit}
if after is not None:
try:
variables["skip"] = int(after)
except (TypeError, ValueError):
return [{"error": "after must be an integer cursor"}]
result = self._graphql(query, variables)
if "error" in result:
return [result]
transcripts = result.get("data", {}).get("transcripts") or []
return [
{
"id": t.get("id"),
"title": t.get("title"),
"date": t.get("date"),
"duration": t.get("duration"),
"organizer_email": t.get("organizer_email"),
}
for t in transcripts
]
def get_transcript(self, meeting_id: str) -> Dict[str, Any]:
"""Fetch a single meeting transcript with summary and sentences."""
if not meeting_id:
return {"error": "meeting_id required"}
query = """
query($id: String!) {
transcript(id: $id) {
id
title
date
duration
organizer_email
summary { overview }
sentences {
text
speaker_name
start_time
}
}
}
"""
result = self._graphql(query, {"id": meeting_id})
if "error" in result:
return result
transcript = result.get("data", {}).get("transcript")
if not transcript:
return {"error": "transcript not found"}
summary = transcript.get("summary") or {}
sentences = transcript.get("sentences") or []
return {
"id": transcript.get("id"),
"title": transcript.get("title"),
"date": transcript.get("date"),
"duration": transcript.get("duration"),
"organizer_email": transcript.get("organizer_email"),
"summary": summary.get("overview"),
"sentences": sentences,
"sentence_count": len(sentences),
}
def search(self, keywords: str, limit: int = 10) -> List[Dict[str, Any]]:
"""Search meetings whose transcripts match the given keyword phrase."""
if not keywords:
return [{"error": "keywords required"}]
limit = max(1, min(limit, 50)) # Fireflies caps page size at 50.
query = """
query($keyword: String, $limit: Int) {
transcripts(keyword: $keyword, limit: $limit) {
id
title
date
organizer_email
}
}
"""
result = self._graphql(query, {"keyword": keywords, "limit": limit})
if "error" in result:
return [result]
transcripts = result.get("data", {}).get("transcripts") or []
return [
{
"id": t.get("id"),
"title": t.get("title"),
"date": t.get("date"),
"organizer_email": t.get("organizer_email"),
}
for t in transcripts
]
def list_fireflies_meetings(limit: int = 10) -> List[Dict[str, Any]]:
"""List recent Fireflies meetings."""
return FirefliesTool().list_recent_meetings(limit=limit)
-569
View File
@@ -1,569 +0,0 @@
"""Inkog Security Analysis Tool for PraisonAI Agents.
Security analysis for AI agent code using Inkog.
Detects token bombing, prompt injection, missing oversight, and compliance gaps.
Usage:
from praisonai_tools import InkogTool
inkog = InkogTool()
results = inkog.scan_directory("./my-agent")
# Or use standalone functions
from praisonai_tools.tools.inkog_tool import scan_agent_code
results = scan_agent_code("./my-agent")
Features:
- Static analysis of AI agent code
- Token bombing detection
- Prompt injection vulnerability scanning
- Recursive tool calling detection
- EU AI Act / NIST / OWASP compliance mapping
- Support for 21+ frameworks (LangChain, CrewAI, AutoGen, etc.)
- Multiple output formats (text, JSON, HTML, SARIF)
Environment Variables:
INKOG_API_KEY: API key from app.inkog.io (required)
INKOG_SERVER_URL: Custom server URL (optional)
"""
import os
import json
import logging
import subprocess
from typing import Any, Dict, Optional, Union
from praisonai_tools.tools.base import BaseTool
logger = logging.getLogger(__name__)
def _check_inkog_available(api_key: Optional[str] = None) -> tuple[bool, Optional[str]]:
"""Check if inkog CLI is available and properly configured.
Args:
api_key: Optional API key to validate. Falls back to the
INKOG_API_KEY environment variable when not provided.
Returns:
Tuple of (is_available, error_message)
"""
# Check if inkog CLI is installed
try:
result = subprocess.run(
["inkog", "-version"],
capture_output=True,
text=True,
timeout=10
)
if result.returncode != 0:
return False, "inkog CLI is not properly installed. Install with: brew tap inkog-io/inkog && brew install inkog"
except FileNotFoundError:
return False, "inkog CLI is not installed. Install with: brew tap inkog-io/inkog && brew install inkog"
except subprocess.TimeoutExpired:
return False, "inkog CLI is not responding. Please check installation."
except Exception as e:
return False, f"Error checking inkog installation: {e}"
# Check for API key (instance-provided key takes precedence over env var)
api_key = api_key or os.environ.get("INKOG_API_KEY")
if not api_key:
return False, "INKOG_API_KEY environment variable is required. Get your free key at https://app.inkog.io"
return True, None
class InkogTool(BaseTool):
"""Comprehensive security analysis tool for AI agent code using Inkog.
Inkog provides static analysis specifically designed for AI agents, detecting:
- Token bombing attacks (loops where LLM controls termination)
- Prompt injection vulnerabilities
- Recursive tool calling without cycle detection
- Missing human oversight for destructive operations
- Cross-tenant data leakage
- MCP tool poisoning
Supports 21+ frameworks including LangChain, CrewAI, AutoGen, OpenAI Agents,
and provides compliance mapping to EU AI Act, NIST AI RMF, and OWASP LLM Top 10.
Requires:
- inkog CLI: brew tap inkog-io/inkog && brew install inkog
- INKOG_API_KEY environment variable (free at app.inkog.io)
"""
name = "inkog_security"
description = "Analyze AI agent code for security vulnerabilities using Inkog static analysis."
def __init__(self, api_key: Optional[str] = None, server_url: Optional[str] = None):
"""Initialize InkogTool.
Args:
api_key: Optional API key. If not provided, uses INKOG_API_KEY env var.
server_url: Optional server URL. If not provided, uses INKOG_SERVER_URL env var.
"""
super().__init__()
self._api_key = api_key
self._server_url = server_url
def _get_api_key(self) -> Optional[str]:
"""Get API key from instance or environment."""
return self._api_key or os.environ.get("INKOG_API_KEY")
def _get_server_url(self) -> Optional[str]:
"""Get server URL from instance or environment."""
return self._server_url or os.environ.get("INKOG_SERVER_URL")
def run(
self,
action: str = "scan",
path: str = ".",
output_format: str = "json",
policy: str = "balanced",
severity: str = "low",
deep: bool = False,
**kwargs
) -> Union[str, Dict[str, Any]]:
"""Execute inkog security analysis.
Args:
action: Action to perform ("scan", "skill-scan", "mcp-scan")
path: Path to scan (directory or file)
output_format: Output format ("json", "text", "html", "sarif")
policy: Security policy ("low-noise", "balanced", "comprehensive")
severity: Minimum severity ("critical", "high", "medium", "low")
deep: Enable deep scan with AI orchestrator analysis
**kwargs: Additional arguments
Returns:
Scan results as dict (JSON) or formatted string (text/html)
"""
action = action.lower().replace("-", "_")
if action == "scan":
return self.scan_directory(
path=path,
output_format=output_format,
policy=policy,
severity=severity,
deep=deep
)
elif action == "skill_scan":
return self.skill_scan(
path=path,
output_format=output_format,
deep=deep,
repo=kwargs.get("repo")
)
elif action == "mcp_scan":
return self.mcp_scan(
server_name=kwargs.get("server_name", path),
output_format=output_format,
deep=deep,
repo=kwargs.get("repo")
)
else:
return {"error": f"Unknown action: {action}"}
def scan_directory(
self,
path: str = ".",
output_format: str = "json",
policy: str = "balanced",
severity: str = "low",
deep: bool = False,
verbose: bool = False
) -> Union[Dict[str, Any], str]:
"""Scan a directory or file for AI agent security vulnerabilities.
Args:
path: Path to scan (directory or file)
output_format: Output format ("json", "text", "html", "sarif")
policy: Security policy ("low-noise", "balanced", "comprehensive")
severity: Minimum severity level ("critical", "high", "medium", "low")
deep: Enable deep scan with AI orchestrator analysis
verbose: Enable verbose output
Returns:
Scan results as dict (JSON format) or string (other formats)
"""
is_available, error = _check_inkog_available(self._get_api_key())
if not is_available:
logger.error(error)
return {"error": error}
try:
# Build command
cmd = ["inkog"]
if deep:
cmd.append("-deep")
cmd.extend([
"-output", output_format,
"-policy", policy,
"-severity", severity,
])
if verbose:
cmd.append("-verbose")
# Add server URL if specified
server_url = self._get_server_url()
if server_url:
cmd.extend(["-server", server_url])
# Add path
cmd.append(path)
# Set environment
env = os.environ.copy()
api_key = self._get_api_key()
if api_key:
env["INKOG_API_KEY"] = api_key
# Execute scan
result = subprocess.run(
cmd,
capture_output=True,
text=True,
env=env,
timeout=300 # 5 minutes timeout
)
if result.returncode != 0:
error_msg = f"Inkog scan failed: {result.stderr or result.stdout}"
logger.error(error_msg)
return {"error": error_msg}
# Parse output based on format
if output_format == "json":
try:
return json.loads(result.stdout)
except json.JSONDecodeError as e:
return {"error": f"Failed to parse JSON output: {e}", "raw_output": result.stdout}
else:
return result.stdout
except subprocess.TimeoutExpired:
error_msg = "Inkog scan timed out after 5 minutes"
logger.error(error_msg)
return {"error": error_msg}
except Exception as e:
error_msg = f"Inkog scan error: {str(e)}"
logger.error(error_msg)
return {"error": error_msg}
def skill_scan(
self,
path: str = ".",
output_format: str = "json",
deep: bool = False,
repo: Optional[str] = None
) -> Union[Dict[str, Any], str]:
"""Scan SKILL.md packages and agent tools for security vulnerabilities.
Args:
path: Path to scan or server name
output_format: Output format ("json", "text", "html", "sarif")
deep: Enable deep scan with AI orchestrator analysis
repo: Repository URL to scan
Returns:
Scan results as dict (JSON format) or string (other formats)
"""
is_available, error = _check_inkog_available(self._get_api_key())
if not is_available:
logger.error(error)
return {"error": error}
try:
# Build command
cmd = ["inkog", "skill-scan"]
if deep:
cmd.append("-deep")
cmd.extend(["-output", output_format])
if repo:
cmd.extend(["-repo", repo])
else:
cmd.append(path)
# Set environment
env = os.environ.copy()
api_key = self._get_api_key()
if api_key:
env["INKOG_API_KEY"] = api_key
# Execute scan
result = subprocess.run(
cmd,
capture_output=True,
text=True,
env=env,
timeout=300
)
if result.returncode != 0:
error_msg = f"Inkog skill scan failed: {result.stderr or result.stdout}"
logger.error(error_msg)
return {"error": error_msg}
# Parse output based on format
if output_format == "json":
try:
return json.loads(result.stdout)
except json.JSONDecodeError as e:
return {"error": f"Failed to parse JSON output: {e}", "raw_output": result.stdout}
else:
return result.stdout
except subprocess.TimeoutExpired:
error_msg = "Inkog skill scan timed out after 5 minutes"
logger.error(error_msg)
return {"error": error_msg}
except Exception as e:
error_msg = f"Inkog skill scan error: {str(e)}"
logger.error(error_msg)
return {"error": error_msg}
def mcp_scan(
self,
server_name: str,
output_format: str = "json",
deep: bool = False,
repo: Optional[str] = None
) -> Union[Dict[str, Any], str]:
"""Scan MCP servers for security vulnerabilities.
Args:
server_name: MCP server name to scan
output_format: Output format ("json", "text", "html", "sarif")
deep: Enable deep scan with AI orchestrator analysis
repo: Repository URL for the MCP server source code
Returns:
Scan results as dict (JSON format) or string (other formats)
"""
is_available, error = _check_inkog_available(self._get_api_key())
if not is_available:
logger.error(error)
return {"error": error}
try:
# Build command
cmd = ["inkog", "mcp-scan"]
if deep:
cmd.append("-deep")
cmd.extend(["-output", output_format])
if repo:
cmd.extend(["-repo", repo])
cmd.append(server_name)
# Set environment
env = os.environ.copy()
api_key = self._get_api_key()
if api_key:
env["INKOG_API_KEY"] = api_key
# Execute scan
result = subprocess.run(
cmd,
capture_output=True,
text=True,
env=env,
timeout=300
)
if result.returncode != 0:
error_msg = f"Inkog MCP scan failed: {result.stderr or result.stdout}"
logger.error(error_msg)
return {"error": error_msg}
# Parse output based on format
if output_format == "json":
try:
return json.loads(result.stdout)
except json.JSONDecodeError as e:
return {"error": f"Failed to parse JSON output: {e}", "raw_output": result.stdout}
else:
return result.stdout
except subprocess.TimeoutExpired:
error_msg = "Inkog MCP scan timed out after 5 minutes"
logger.error(error_msg)
return {"error": error_msg}
except Exception as e:
error_msg = f"Inkog MCP scan error: {str(e)}"
logger.error(error_msg)
return {"error": error_msg}
def analyze_findings(self, scan_results: Union[Dict[str, Any], str]) -> str:
"""Analyze scan results and provide a summary.
Args:
scan_results: Results from a JSON format scan. Non-dict inputs
(e.g. text/HTML output) are returned as-is.
Returns:
Human-readable analysis summary
"""
try:
if not isinstance(scan_results, dict):
return str(scan_results)
if "error" in scan_results:
return f"Scan failed: {scan_results['error']}"
summary = scan_results.get("summary", {})
total_findings = summary.get("total_findings", 0)
if total_findings == 0:
return "✅ No security vulnerabilities found in the agent code."
# Build severity breakdown
critical = summary.get("critical", 0)
high = summary.get("high", 0)
medium = summary.get("medium", 0)
low = summary.get("low", 0)
analysis = "🔍 Security Analysis Results:\n"
analysis += f"Total Findings: {total_findings}\n\n"
if critical > 0:
analysis += f"🔴 CRITICAL: {critical} findings - Immediate attention required\n"
if high > 0:
analysis += f"🟠 HIGH: {high} findings - Should be addressed soon\n"
if medium > 0:
analysis += f"🟡 MEDIUM: {medium} findings - Review recommended\n"
if low > 0:
analysis += f"⚪ LOW: {low} findings - Minor issues\n"
# Add key finding types if available
findings = scan_results.get("server_findings", [])
if findings:
patterns = set()
for finding in findings[:5]: # Show top 5 patterns
pattern = finding.get("pattern", "Unknown")
patterns.add(pattern)
if patterns:
analysis += "\nKey Vulnerability Types Detected:\n"
for pattern in sorted(patterns):
analysis += f"• {pattern}\n"
# Risk recommendations
if critical > 0 or high > 0:
analysis += "\n⚠️ Recommendation: Address critical and high severity findings before deployment."
return analysis
except Exception as e:
return f"Error analyzing scan results: {e}"
# Standalone functions for direct import and use
def scan_agent_code(
path: str = ".",
output_format: str = "json",
policy: str = "balanced",
severity: str = "low",
deep: bool = False
) -> Union[Dict[str, Any], str]:
"""Scan AI agent code for security vulnerabilities using Inkog.
Args:
path: Path to scan (directory or file)
output_format: Output format ("json", "text", "html", "sarif")
policy: Security policy ("low-noise", "balanced", "comprehensive")
severity: Minimum severity level ("critical", "high", "medium", "low")
deep: Enable deep scan with AI orchestrator analysis
Returns:
Scan results as dict (JSON format) or string (other formats)
"""
tool = InkogTool()
return tool.scan_directory(
path=path,
output_format=output_format,
policy=policy,
severity=severity,
deep=deep
)
def scan_skill_package(
path: str = ".",
deep: bool = False,
repo: Optional[str] = None
) -> Dict[str, Any]:
"""Scan SKILL.md packages for security vulnerabilities.
Args:
path: Path to scan
deep: Enable deep scan with AI orchestrator analysis
repo: Repository URL to scan
Returns:
Scan results as dict
"""
tool = InkogTool()
return tool.skill_scan(path=path, deep=deep, repo=repo)
def scan_mcp_server(
server_name: str,
deep: bool = False,
repo: Optional[str] = None
) -> Dict[str, Any]:
"""Scan MCP server for security vulnerabilities.
Args:
server_name: MCP server name to scan
deep: Enable deep scan with AI orchestrator analysis
repo: Repository URL for the MCP server
Returns:
Scan results as dict
"""
tool = InkogTool()
return tool.mcp_scan(server_name=server_name, deep=deep, repo=repo)
# Example usage and testing
if __name__ == "__main__":
print("\n" + "="*60)
print("Inkog Security Analysis Tool Demonstration")
print("="*60 + "\n")
# Check if inkog is available
is_available, error = _check_inkog_available()
if not is_available:
print(f"❌ Error: {error}")
print("\nTo use Inkog tools:")
print("1. Install CLI: brew tap inkog-io/inkog && brew install inkog")
print("2. Get API key: https://app.inkog.io")
print("3. Set environment: export INKOG_API_KEY=your_key_here")
else:
print("✅ Inkog is available and configured!")
# Example usage with current directory
try:
print("\nScanning current directory for security vulnerabilities...")
result = scan_agent_code(".", output_format="json", policy="balanced")
if isinstance(result, dict) and "error" not in result:
tool = InkogTool()
analysis = tool.analyze_findings(result)
print(analysis)
else:
print("Scan completed:", result)
except Exception as e:
print(f"Demo error: {e}")
-353
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@@ -1,353 +0,0 @@
"""JIRA watch tools for PraisonAI Agents — monitor issues and projects for changes."""
import logging
import os
import re
import time
from datetime import datetime, timezone
from typing import Optional
from praisonai_tools.tools.decorator import tool
logger = logging.getLogger(__name__)
def _parse_datetime(ts_str: str) -> datetime:
"""Parse a timestamp string into a timezone-aware datetime for safe comparison."""
dt = datetime.fromisoformat(str(ts_str).replace("Z", "+00:00"))
if dt.tzinfo is None:
dt = dt.replace(tzinfo=timezone.utc)
return dt
def _get_jira_connection(
url: Optional[str] = None,
username: Optional[str] = None,
token: Optional[str] = None,
email: Optional[str] = None,
):
"""Create a JIRA connection with cloud or server authentication."""
try:
from jira import JIRA
except ImportError as exc:
raise ImportError(
"JIRA library not installed. Install with: pip install jira"
) from exc
url = url or os.getenv("JIRA_URL")
username = username or os.getenv("JIRA_USERNAME")
token = token or os.getenv("JIRA_API_TOKEN")
email = email or os.getenv("JIRA_EMAIL")
if not url:
raise ValueError("JIRA URL is required (parameter or JIRA_URL env var)")
if email and token:
auth = (email, token)
elif username and token:
auth = (username, token)
else:
raise ValueError(
"JIRA authentication required. Provide either:\n"
"- email + token (for cloud JIRA)\n"
"- username + token (for server JIRA)\n"
"Or set JIRA_EMAIL, JIRA_USERNAME, and JIRA_API_TOKEN"
)
return JIRA(server=url, basic_auth=auth)
def _validate_project_key(project_key: str) -> bool:
"""Validate JIRA project key to prevent JQL injection."""
if not re.match(r"^[A-Z][A-Z0-9_]*$", project_key):
raise ValueError(
f"Invalid project key format: {project_key}. "
"Must start with a letter and contain only uppercase letters, numbers, and underscores."
)
return True
def _validate_issue_key(issue_key: str) -> bool:
"""Validate JIRA issue key to prevent path traversal or API abuse."""
if not re.match(r"^[A-Za-z0-9_-]+$", issue_key):
raise ValueError(
f"Invalid issue key format: {issue_key}. "
"Must contain only alphanumeric characters, underscores, and hyphens."
)
return True
def _validate_timestamp(timestamp: str) -> str:
"""Validate and normalize a timestamp to prevent JQL injection.
Returns a canonical 'YYYY-MM-DD HH:MM' string safe for JQL interpolation.
"""
try:
dt = _parse_datetime(timestamp)
except (ValueError, TypeError) as exc:
raise ValueError(
f"Invalid timestamp format: {timestamp}. "
"Use ISO-8601, e.g. 2024-01-01T00:00:00Z"
) from exc
return dt.strftime("%Y-%m-%d %H:%M")
@tool
def jira_watch_issue(
issue_key: str,
url: Optional[str] = None,
since_timestamp: Optional[str] = None,
username: Optional[str] = None,
token: Optional[str] = None,
email: Optional[str] = None,
) -> str:
"""Check a specific JIRA issue for changes since a timestamp."""
try:
_validate_issue_key(issue_key)
since_dt = _parse_datetime(since_timestamp) if since_timestamp else None
jira = _get_jira_connection(url, username, token, email)
issue = jira.issue(issue_key, expand="changelog")
current_updated = issue.fields.updated
current_status = issue.fields.status.name
if not since_timestamp:
result = f"JIRA issue {issue_key} current state:\n"
result += f"Status: {current_status}\n"
result += f"Summary: {issue.fields.summary}\n"
assignee = issue.fields.assignee.displayName if issue.fields.assignee else "Unassigned"
result += f"Assignee: {assignee}\n"
priority = issue.fields.priority.name if issue.fields.priority else "None"
result += f"Priority: {priority}\n"
result += f"Updated: {current_updated}\n"
return result
changes_detected = []
if _parse_datetime(current_updated) > since_dt:
change_info = {
"timestamp": current_updated,
"status": current_status,
"summary": issue.fields.summary,
"assignee": issue.fields.assignee.displayName if issue.fields.assignee else "Unassigned",
"priority": issue.fields.priority.name if issue.fields.priority else "None",
}
recent_changes = []
if issue.changelog and issue.changelog.histories:
for history in issue.changelog.histories:
try:
history_dt = _parse_datetime(history.created)
except (ValueError, TypeError):
continue
if history_dt > since_dt:
for item in history.items:
recent_changes.append({
"field": item.field,
"from": item.fromString,
"to": item.toString,
"author": history.author.displayName if history.author else "System",
"created": history.created,
})
change_info["recent_changes"] = recent_changes
changes_detected.append(change_info)
comment_changes = []
for comment in jira.comments(issue_key):
try:
comment_dt = _parse_datetime(comment.created)
except (ValueError, TypeError):
continue
if comment_dt > since_dt:
comment_changes.append({
"author": comment.author.displayName if comment.author else "Unknown",
"body": comment.body[:500],
"created": comment.created,
})
if comment_changes:
change_info["recent_comments"] = comment_changes
if changes_detected:
result = f"JIRA issue {issue_key} - changes detected since {since_timestamp}:\n"
for i, change in enumerate(changes_detected, 1):
result += f"\n--- Change {i} at {change['timestamp']} ---\n"
result += f"Status: {change['status']}\n"
result += f"Assignee: {change['assignee']}\n"
result += f"Priority: {change['priority']}\n"
if change.get("recent_changes"):
field_changes = change["recent_changes"]
result += f"Recent field changes ({len(field_changes)}):\n"
for rc in field_changes[-10:]:
result += f" - {rc['field']}: '{rc['from']}' → '{rc['to']}' by {rc['author']}\n"
if change.get("recent_comments"):
result += "Recent comments:\n"
for comment in change["recent_comments"]:
result += f" - {comment['author']} ({comment['created']}): {comment['body'][:200]}...\n"
return result
return f"No changes detected in JIRA issue {issue_key} since {since_timestamp}"
except Exception as e:
logger.error("Failed to watch JIRA issue: %s", e)
return f"Error watching JIRA issue {issue_key}: {e}"
@tool
def jira_watch_project(
project_key: str,
url: Optional[str] = None,
since_timestamp: Optional[str] = None,
username: Optional[str] = None,
token: Optional[str] = None,
email: Optional[str] = None,
) -> str:
"""Check a JIRA project for new issues and updates since a timestamp."""
try:
_validate_project_key(project_key)
since_for_jql = _validate_timestamp(since_timestamp) if since_timestamp else None
jira = _get_jira_connection(url, username, token, email)
project_changes = {
"timestamp": time.strftime("%Y-%m-%d %H:%M:%S"),
"new_issues": [],
"updated_issues": [],
}
if not since_timestamp:
recent_jql = f"project = {project_key} ORDER BY updated DESC"
recent_issues = jira.search_issues(recent_jql, maxResults=10)
result = f"JIRA project {project_key} recent activity ({len(recent_issues)} issues):\n"
for issue in recent_issues:
result += f" {issue.key}: {issue.fields.summary[:60]}...\n"
result += f" Status: {issue.fields.status.name}, Updated: {issue.fields.updated}\n"
return result
new_jql = f'project = {project_key} AND created >= "{since_for_jql}" ORDER BY created DESC'
for issue in jira.search_issues(new_jql, maxResults=50):
project_changes["new_issues"].append({
"key": issue.key,
"summary": issue.fields.summary,
"status": issue.fields.status.name,
"assignee": issue.fields.assignee.displayName if issue.fields.assignee else "Unassigned",
"creator": issue.fields.creator.displayName if issue.fields.creator else "Unknown",
"created": issue.fields.created,
})
updated_jql = (
f'project = {project_key} AND updated >= "{since_for_jql}" '
f'AND created < "{since_for_jql}" ORDER BY updated DESC'
)
for issue in jira.search_issues(updated_jql, maxResults=50):
project_changes["updated_issues"].append({
"key": issue.key,
"summary": issue.fields.summary,
"status": issue.fields.status.name,
"assignee": issue.fields.assignee.displayName if issue.fields.assignee else "Unassigned",
"updated": issue.fields.updated,
})
if project_changes["new_issues"] or project_changes["updated_issues"]:
result = f"JIRA project {project_key} - changes detected since {since_timestamp}:\n"
result += f"\n--- Activity at {project_changes['timestamp']} ---\n"
if project_changes["new_issues"]:
result += f"New issues ({len(project_changes['new_issues'])}):\n"
for issue in project_changes["new_issues"]:
result += f" {issue['key']}: {issue['summary'][:80]}...\n"
result += f" Status: {issue['status']}, Assignee: {issue['assignee']}, Created: {issue['created']}\n"
if project_changes["updated_issues"]:
result += f"Updated issues ({len(project_changes['updated_issues'])}):\n"
for issue in project_changes["updated_issues"]:
result += f" {issue['key']}: {issue['summary'][:80]}...\n"
result += f" Status: {issue['status']}, Updated: {issue['updated']}\n"
return result
return f"No changes detected in JIRA project {project_key} since {since_timestamp}"
except Exception as e:
logger.error("Failed to watch JIRA project: %s", e)
return f"Error watching JIRA project {project_key}: {e}"
@tool
def jira_get_issue_info(
issue_key: str,
url: Optional[str] = None,
username: Optional[str] = None,
token: Optional[str] = None,
email: Optional[str] = None,
) -> str:
"""Get detailed information about a specific JIRA issue."""
try:
_validate_issue_key(issue_key)
jira = _get_jira_connection(url, username, token, email)
issue = jira.issue(issue_key, expand="changelog,comments")
result = f"JIRA Issue: {issue.key}\n"
result += f"Summary: {issue.fields.summary}\n"
result += f"Status: {issue.fields.status.name}\n"
result += f"Priority: {issue.fields.priority.name if issue.fields.priority else 'None'}\n"
assignee = issue.fields.assignee.displayName if issue.fields.assignee else "Unassigned"
result += f"Assignee: {assignee}\n"
reporter = issue.fields.reporter.displayName if issue.fields.reporter else "Unknown"
result += f"Reporter: {reporter}\n"
result += f"Created: {issue.fields.created}\n"
result += f"Updated: {issue.fields.updated}\n"
if issue.fields.description:
desc = issue.fields.description
suffix = "..." if len(desc) > 500 else ""
result += f"Description: {desc[:500]}{suffix}\n"
comments = jira.comments(issue_key)
if comments:
result += f"\nRecent Comments ({len(comments[-3:])}):\n"
for comment in comments[-3:]:
author = comment.author.displayName if comment.author else "Unknown"
result += f" - {author} ({comment.created}): {comment.body[:200]}...\n"
return result
except Exception as e:
logger.error("Failed to get JIRA issue info: %s", e)
return f"Error getting JIRA issue {issue_key}: {e}"
@tool
def jira_search_issues(
jql: str,
url: Optional[str] = None,
max_results: int = 20,
username: Optional[str] = None,
token: Optional[str] = None,
email: Optional[str] = None,
) -> str:
"""Search JIRA issues using JQL (JIRA Query Language)."""
try:
jira = _get_jira_connection(url, username, token, email)
issues = jira.search_issues(jql, maxResults=max_results)
if not issues:
return f"No issues found for JQL: {jql}"
result = f"Found {len(issues)} issues for JQL: {jql}\n\n"
for issue in issues:
assignee = issue.fields.assignee.displayName if issue.fields.assignee else "Unassigned"
result += f"{issue.key}: {issue.fields.summary}\n"
result += f" Status: {issue.fields.status.name}\n"
result += f" Assignee: {assignee}\n"
result += f" Updated: {issue.fields.updated}\n\n"
return result
except Exception as e:
logger.error("Failed to search JIRA issues: %s", e)
return f"Error searching JIRA issues: {e}"
def jira_tools():
"""Return all JIRA watch tools as a collection for agent registration."""
return [
jira_watch_issue,
jira_watch_project,
jira_get_issue_info,
jira_search_issues,
]
@@ -1,175 +0,0 @@
"""Keenable Search Tool for PraisonAI Agents.
Keyless (or keyed) web search using Keenable.
Keenable works with no API key and no extra install: it calls the keyless
public endpoint with the Python standard library (``urllib``). Setting
``KEENABLE_API_KEY`` switches to the authenticated endpoint for higher limits.
Usage:
from praisonai_tools import KeenableSearchTool
keenable = KeenableSearchTool()
results = keenable.search("AI news 2024")
Environment Variables:
KEENABLE_API_KEY: Optional. When set, the authenticated endpoint is used.
"""
import json
import logging
import os
from typing import Any, Dict, List, Optional, Union
from urllib.request import HTTPRedirectHandler
from praisonai_tools.tools.base import BaseTool
logger = logging.getLogger(__name__)
KEENABLE_SEARCH_URL = "https://api.keenable.ai/v1/search"
KEENABLE_PUBLIC_SEARCH_URL = "https://api.keenable.ai/v1/search/public"
KEENABLE_APP_TITLE = "PraisonAI"
KEENABLE_SEARCH_TIMEOUT_SECONDS = 30
KEENABLE_MAX_RESPONSE_BYTES = 1_000_000
KEENABLE_MAX_RESULTS = 50
KEENABLE_MAX_TITLE_CHARS = 256
KEENABLE_MAX_URL_CHARS = 2048
KEENABLE_MAX_SNIPPET_CHARS = 1200
def _truncate_text(value: Any, limit: int) -> str:
"""Trim whitespace and cap ``value`` to ``limit`` characters."""
text = str(value or "").strip()
if len(text) > limit:
return text[:limit - 1] + "\u2026"
return text
class _NoRedirect(HTTPRedirectHandler):
"""Redirect handler that refuses to follow any redirect.
Keenable never redirects. Following a 3xx would resend ``X-API-Key`` to
whatever host it points at, so the redirect is dropped (urllib then raises
the 3xx as an error, surfaced to the caller) and no second request is sent.
"""
def redirect_request(self, *args, **kwargs):
"""Return ``None`` so urllib does not issue a follow-up request."""
return None
class KeenableSearchTool(BaseTool):
"""Tool for keyless (or keyed) web search using Keenable."""
name = "keenable_search"
description = "Search the web using Keenable (keyless; an API key raises limits)."
def __init__(self, api_key: Optional[str] = None):
"""Create the tool, resolving the API key from the argument or env.
Args:
api_key: Optional Keenable API key. Falls back to the
``KEENABLE_API_KEY`` environment variable; keyless if unset.
"""
self.api_key = (api_key or os.getenv("KEENABLE_API_KEY") or "").strip()
super().__init__()
def run(
self,
action: str = "search",
query: Optional[str] = None,
max_results: int = 5,
**kwargs,
) -> Union[str, Dict[str, Any], List[Dict[str, Any]]]:
"""Dispatch a Keenable action; only ``search`` is supported."""
action = action.lower().replace("-", "_")
if action == "search":
return self.search(query=query, max_results=max_results)
return {"error": f"Unknown action: {action}"}
def search(self, query: str, max_results: int = 5) -> List[Dict[str, Any]]:
"""Search the web with Keenable.
Args:
query: Search query string.
max_results: Maximum results to return (capped at 50).
Returns:
List of dicts with ``title``, ``url``, ``snippet`` and ``provider``,
or a single-item list with an ``error`` key on failure.
"""
if not query:
return [{"error": "query is required"}]
result_limit = max(0, min(int(max_results), KEENABLE_MAX_RESULTS))
if result_limit == 0:
return []
from urllib.error import URLError
from urllib.request import Request, build_opener
headers = {
"Content-Type": "application/json",
"Accept": "application/json",
"User-Agent": "praisonai-tools",
# Required on keyless calls; names the app, carries no user identifier.
"X-Keenable-Title": KEENABLE_APP_TITLE,
}
if self.api_key:
headers["X-API-Key"] = self.api_key
body = json.dumps({
"query": query,
"max_results": result_limit,
"snippet_max_length": KEENABLE_MAX_SNIPPET_CHARS,
}).encode("utf-8")
request = Request(
KEENABLE_SEARCH_URL if self.api_key else KEENABLE_PUBLIC_SEARCH_URL,
data=body,
headers=headers,
method="POST",
)
try:
opener = build_opener(_NoRedirect)
with opener.open(request, timeout=KEENABLE_SEARCH_TIMEOUT_SECONDS) as response:
raw = response.read(KEENABLE_MAX_RESPONSE_BYTES + 1)
except URLError as exc:
logger.error(f"Keenable search error: {exc}")
return [{"error": str(exc)}]
except Exception as exc:
logger.error(f"Keenable search error: {exc}")
return [{"error": str(exc)}]
if len(raw) > KEENABLE_MAX_RESPONSE_BYTES:
return [{"error": "Keenable returned an oversized response"}]
try:
payload = json.loads(raw)
except ValueError as exc:
return [{"error": f"Keenable returned invalid JSON: {exc}"}]
if not isinstance(payload, dict) or not isinstance(payload.get("results"), list):
return [{"error": "Keenable returned an invalid response shape"}]
results = []
for result in payload["results"]:
if not isinstance(result, dict):
continue
url = result.get("url")
if not isinstance(url, str) or not url or len(url) > KEENABLE_MAX_URL_CHARS:
continue
# The page text is in `snippet`; `description` is usually empty.
snippet = " ".join(str(result.get("snippet") or result.get("description") or "").split())
results.append({
"title": _truncate_text(result.get("title", ""), KEENABLE_MAX_TITLE_CHARS),
"url": url,
"snippet": _truncate_text(snippet, KEENABLE_MAX_SNIPPET_CHARS),
"provider": "keenable",
})
if len(results) >= result_limit:
break
return results
def keenable_search(query: str, max_results: int = 5) -> List[Dict[str, Any]]:
"""Search the web with Keenable (keyless; KEENABLE_API_KEY raises limits)."""
return KeenableSearchTool().search(query=query, max_results=max_results)
-700
View File
@@ -1,700 +0,0 @@
"""Meeting Agent Tools for PraisonAI Agents.
Eight agent-callable ``@tool`` functions covering the Phase 1 meeting-agent
pipeline: transcription, meetings CRUD, summarisation, action-item extraction,
and RAG indexing/search.
Tools
-----
1. ``transcribe_file`` - Whisper transcription with segment timestamps.
2. ``save_meeting`` - Persist a meeting record (returns ``meeting_id``).
3. ``get_meeting`` - Fetch a full meeting record.
4. ``list_meetings`` - List meetings (limit/offset).
5. ``summarize_transcript`` - Structured summary (map-reduce for long input).
6. ``extract_action_items`` - Structured action items.
7. ``index_meeting`` - Chunk/embed/upsert into a vector store (idempotent).
8. ``search_meetings`` - Ranked cross-meeting semantic search.
Dependency hygiene
-------------------
``openai`` and ``chromadb`` are **lazy-imported inside functions**, never at
module import time. They are optional extras::
pip install praisonai-tools[meeting]
Meetings are persisted in a small SQLite database (Python stdlib) under the app
data dir. This is a thin, swappable persistence layer: when the canonical
PAI-MEET-CORE schema is available it can back these same CRUD wrappers.
All tool outputs use deterministic serialisation (stable field order / sorted
keys) so results are reproducible.
Environment Variables
---------------------
OPENAI_API_KEY Required for transcription/summaries/embeddings.
OPENAI_BASE_URL Optional custom OpenAI-compatible endpoint.
PRAISONAI_MEETINGS_DB Optional path to the SQLite meetings database.
PRAISONAI_MEETINGS_DIR Optional app data dir (db + vector store live here).
"""
from __future__ import annotations
import json
import logging
import os
import sqlite3
import uuid
from contextlib import closing
from pathlib import Path
from typing import Any, Dict, List, Optional
from praisonai_tools.tools.decorator import tool
logger = logging.getLogger(__name__)
# Chunking / embedding defaults (issue spec).
_CHUNK_SIZE_TOKENS = 500
_CHUNK_OVERLAP_TOKENS = 50
_SUMMARY_CHUNK_TOKENS = 6000
_SUMMARY_OVERLAP_TOKENS = 200
_EMBEDDING_MODEL = "text-embedding-3-small"
_CHAT_MODEL = "gpt-4o-mini"
_WHISPER_MODEL = "whisper-1"
_COLLECTION = "meetings"
# Rough token->char ratio used only for deterministic, dependency-free chunking.
_CHARS_PER_TOKEN = 4
# ── Paths / persistence ─────────────────────────────────────────────
def _app_dir() -> Path:
"""Return the app data directory (created if missing)."""
env = os.getenv("PRAISONAI_MEETINGS_DIR")
base = Path(env) if env else Path.home() / ".praisonai" / "meetings"
base.mkdir(parents=True, exist_ok=True)
return base
def _db_path() -> str:
env = os.getenv("PRAISONAI_MEETINGS_DB")
if env:
Path(env).parent.mkdir(parents=True, exist_ok=True)
return env
return str(_app_dir() / "meetings.db")
def _connect() -> sqlite3.Connection:
"""Open the meetings DB, creating the schema on first use."""
conn = sqlite3.connect(_db_path())
conn.row_factory = sqlite3.Row
conn.execute(
"""
CREATE TABLE IF NOT EXISTS meetings (
meeting_id TEXT PRIMARY KEY,
title TEXT NOT NULL,
source TEXT,
metadata TEXT,
created_at TEXT NOT NULL
)
"""
)
return conn
def _row_to_meeting(row: sqlite3.Row) -> Dict[str, Any]:
"""Convert a DB row to a deterministic meeting dict (stable key order)."""
try:
metadata = json.loads(row["metadata"]) if row["metadata"] else {}
except (ValueError, TypeError):
metadata = {}
return {
"created_at": row["created_at"],
"meeting_id": row["meeting_id"],
"metadata": metadata,
"source": row["source"],
"title": row["title"],
}
# ── Lazy clients ────────────────────────────────────────────────────
def _get_openai_client():
"""Lazily construct an OpenAI client. Raises clear errors on misconfig."""
api_key = os.getenv("OPENAI_API_KEY")
if not api_key:
raise ValueError(
"OPENAI_API_KEY is required. Set it in the environment before "
"calling meeting transcription/summarisation/embedding tools."
)
try:
from openai import OpenAI
except ImportError as exc: # pragma: no cover - trivial
raise ImportError(
"openai package required. Install with: pip install praisonai-tools[meeting]"
) from exc
base_url = os.getenv("OPENAI_BASE_URL")
if base_url:
return OpenAI(api_key=api_key, base_url=base_url)
return OpenAI(api_key=api_key)
def _get_vector_collection():
"""Lazily open (or create) the persistent Chroma collection."""
try:
import chromadb
except ImportError as exc: # pragma: no cover - trivial
raise ImportError(
"chromadb package required. Install with: pip install praisonai-tools[meeting]"
) from exc
client = chromadb.PersistentClient(path=str(_app_dir() / "chroma"))
return client.get_or_create_collection(_COLLECTION)
def _embed(texts: List[str]) -> List[List[float]]:
"""Embed a list of texts with the configured embedding model."""
client = _get_openai_client()
resp = client.embeddings.create(model=_EMBEDDING_MODEL, input=texts)
return [item.embedding for item in resp.data]
# ── Chunking helpers ────────────────────────────────────────────────
def _chunk_spans(text: str, size_tokens: int, overlap_tokens: int) -> List[tuple]:
"""Split text into overlapping windows, returning (chunk, char_start, char_end).
Uses a deterministic character-window approximation so no tokenizer
dependency is needed. Character offsets refer to the pre-strip window and
let callers map each chunk back to source positions (e.g. segment times).
"""
if not text:
return []
size = max(1, size_tokens * _CHARS_PER_TOKEN)
overlap = max(0, min(overlap_tokens * _CHARS_PER_TOKEN, size - 1))
step = size - overlap
spans: List[tuple] = []
start = 0
length = len(text)
while start < length:
end = min(start + size, length)
chunk = text[start:end].strip()
if chunk:
spans.append((chunk, start, end))
start += step
return spans
def _chunk_text(text: str, size_tokens: int, overlap_tokens: int) -> List[str]:
"""Split text into overlapping chunks by approximate token size.
Returns a list of non-empty chunk strings (see :func:`_chunk_spans`).
"""
return [chunk for chunk, _s, _e in _chunk_spans(text, size_tokens, overlap_tokens)]
def _segment_char_offsets(segments: List[Dict[str, Any]]) -> List[tuple]:
"""Return (char_start, char_end, seg_start, seg_end) for concatenated segments.
The transcript indexed here is assumed to be the segment texts joined by a
single space, matching how ``transcribe_file`` emits ``segments``.
"""
offsets: List[tuple] = []
pos = 0
for i, seg in enumerate(segments):
seg_text = str(seg.get("text", "")).strip()
if i > 0:
pos += 1 # the joining space
char_start = pos
pos += len(seg_text)
offsets.append(
(char_start, pos, float(seg.get("start", 0.0)), float(seg.get("end", 0.0)))
)
return offsets
def _timestamps_for_span(
char_start: int, char_end: int, seg_offsets: List[tuple]
) -> tuple:
"""Map a chunk's char span to the (start, end) time of the segments it covers."""
if not seg_offsets:
return 0.0, 0.0
start_time: Optional[float] = None
end_time: Optional[float] = None
for cs, ce, s_start, s_end in seg_offsets:
if ce > char_start and cs < char_end: # overlap
if start_time is None:
start_time = s_start
end_time = s_end
if start_time is None:
return 0.0, 0.0
return start_time, end_time if end_time is not None else start_time
# ── LLM JSON helpers ────────────────────────────────────────────────
def _chat_json(system: str, user: str) -> Dict[str, Any]:
"""Call the chat model requesting a JSON object and parse it."""
client = _get_openai_client()
resp = client.chat.completions.create(
model=_CHAT_MODEL,
messages=[
{"role": "system", "content": system},
{"role": "user", "content": user},
],
response_format={"type": "json_object"},
temperature=0,
)
content = resp.choices[0].message.content or "{}"
try:
return json.loads(content)
except (ValueError, TypeError):
return {}
# ── 1. transcribe_file ──────────────────────────────────────────────
@tool
def transcribe_file(media_path: str) -> Dict[str, Any]:
"""Transcribe an audio/video file to text with segment timestamps.
Uses OpenAI Whisper (``whisper-1``) via the audio transcriptions API and
returns word/segment level timing.
Args:
media_path: Path to the audio or video file to transcribe.
Returns:
Dict with ``text``, ``segments`` (start/end/text), ``duration_seconds``
and ``language``. On failure returns ``{"error": "..."}`` with a clear
message (missing file, API 403 key permissions, timeout, empty audio).
"""
path = Path(media_path)
if not media_path or not path.exists():
return {"error": f"Media file not found: {media_path}"}
try:
client = _get_openai_client()
except (ValueError, ImportError) as exc:
return {"error": str(exc)}
def _do_transcribe():
with open(path, "rb") as audio_file:
return client.audio.transcriptions.create(
model=_WHISPER_MODEL,
file=audio_file,
response_format="verbose_json",
timestamp_granularities=["segment"],
)
try:
response = _do_transcribe()
except Exception as exc: # noqa: BLE001 - map to clear messages
message = str(exc)
status = getattr(exc, "status_code", None)
exc_name = type(exc).__name__.lower()
if status == 403 or "403" in message or "permission" in message.lower():
return {"error": "Transcription failed: API key lacks permissions (403)."}
if "timeout" in exc_name or "timeout" in message.lower():
# Retry once, then fail with a clear message.
try:
response = _do_transcribe()
except Exception: # noqa: BLE001
return {"error": "Transcription failed: request timed out after retry."}
else:
return {"error": f"Transcription failed: {message}"}
text = (getattr(response, "text", "") or "").strip()
segments_raw = getattr(response, "segments", None) or []
segments = [
{
"end": float(getattr(seg, "end", 0.0)),
"start": float(getattr(seg, "start", 0.0)),
"text": (getattr(seg, "text", "") or "").strip(),
}
for seg in segments_raw
]
if not text and not segments:
return {"error": "No speech detected in recording"}
return {
"duration_seconds": float(getattr(response, "duration", 0.0) or 0.0),
"language": getattr(response, "language", "unknown") or "unknown",
"segments": segments,
"text": text,
}
# ── 2-4. Meetings CRUD ──────────────────────────────────────────────
@tool
def save_meeting(
title: str,
source: Optional[str] = None,
metadata: Optional[Dict[str, Any]] = None,
) -> Dict[str, Any]:
"""Persist a meeting record and return its generated ``meeting_id``.
Thin wrapper over the meetings persistence layer (SQLite by default).
Args:
title: Human-readable meeting title.
source: Optional origin of the meeting (e.g. file path, URL).
metadata: Optional JSON-serialisable metadata dict.
Returns:
Dict ``{"meeting_id": "<uuid>"}`` or ``{"error": "..."}``.
"""
if not title:
return {"error": "title is required"}
meeting_id = str(uuid.uuid4())
from datetime import datetime, timezone
created_at = datetime.now(timezone.utc).isoformat()
try:
with closing(_connect()) as conn, conn:
conn.execute(
"INSERT INTO meetings (meeting_id, title, source, metadata, created_at) "
"VALUES (?, ?, ?, ?, ?)",
(
meeting_id,
title,
source,
json.dumps(metadata or {}, sort_keys=True),
created_at,
),
)
except Exception as exc: # noqa: BLE001
logger.error("save_meeting error: %s", exc)
return {"error": str(exc)}
return {"meeting_id": meeting_id}
@tool
def get_meeting(meeting_id: str) -> Dict[str, Any]:
"""Fetch a full meeting record by id.
Args:
meeting_id: The meeting identifier returned by ``save_meeting``.
Returns:
The meeting record dict, or ``{"error": "..."}`` if not found.
"""
if not meeting_id:
return {"error": "meeting_id is required"}
try:
with closing(_connect()) as conn:
row = conn.execute(
"SELECT * FROM meetings WHERE meeting_id = ?", (meeting_id,)
).fetchone()
except Exception as exc: # noqa: BLE001
logger.error("get_meeting error: %s", exc)
return {"error": str(exc)}
if row is None:
return {"error": f"Meeting not found: {meeting_id}"}
return _row_to_meeting(row)
@tool
def list_meetings(limit: int = 20, offset: int = 0) -> List[Dict[str, Any]]:
"""List stored meetings, most recent first.
Args:
limit: Maximum number of meetings to return (default 20).
offset: Number of meetings to skip for pagination (default 0).
Returns:
A list of meeting record dicts (possibly empty), or a single-element
list ``[{"error": "..."}]`` on failure.
"""
try:
limit = max(0, int(limit))
offset = max(0, int(offset))
with closing(_connect()) as conn:
rows = conn.execute(
"SELECT * FROM meetings ORDER BY created_at DESC, meeting_id DESC "
"LIMIT ? OFFSET ?",
(limit, offset),
).fetchall()
except Exception as exc: # noqa: BLE001
logger.error("list_meetings error: %s", exc)
return [{"error": str(exc)}]
return [_row_to_meeting(r) for r in rows]
# ── 5. summarize_transcript ─────────────────────────────────────────
def _summarize_chunk(transcript: str) -> Dict[str, Any]:
system = (
"You are a meeting summariser. Return a JSON object with keys: "
"'summary' (2-3 paragraph string), 'decisions' (array of strings), "
"'topics' (array of strings), and 'key_quotes' (array of objects with "
"'speaker' and 'quote'). Base output only on the transcript."
)
return _chat_json(system, transcript)
def _merge_summaries(parts: List[Dict[str, Any]]) -> Dict[str, Any]:
merged_summary = "\n\n".join(
str(p.get("summary", "")).strip() for p in parts if p.get("summary")
)
decisions: List[str] = []
topics: List[str] = []
quotes: List[Dict[str, Any]] = []
for p in parts:
for d in p.get("decisions", []) or []:
if d not in decisions:
decisions.append(d)
for t in p.get("topics", []) or []:
if t not in topics:
topics.append(t)
for q in p.get("key_quotes", []) or []:
quotes.append(
{"quote": q.get("quote", ""), "speaker": q.get("speaker")}
)
return {
"decisions": decisions,
"key_quotes": quotes,
"summary": merged_summary,
"topics": topics,
}
@tool
def summarize_transcript(transcript: str) -> Dict[str, Any]:
"""Summarise a meeting transcript into structured JSON.
For long transcripts a map-reduce strategy is used: the transcript is split
into overlapping chunks, each is summarised, and the partial summaries are
merged.
Args:
transcript: The full plain-text transcript.
Returns:
Dict with ``summary`` (str), ``decisions`` (list), ``topics`` (list) and
``key_quotes`` (list of ``{speaker, quote}``). ``{"error": "..."}`` on
failure.
"""
if not transcript or not transcript.strip():
return {"error": "transcript is required"}
try:
chunks = _chunk_text(
transcript, _SUMMARY_CHUNK_TOKENS, _SUMMARY_OVERLAP_TOKENS
)
if len(chunks) <= 1:
result = _summarize_chunk(transcript)
else:
partials = [_summarize_chunk(c) for c in chunks]
result = _merge_summaries(partials)
except (ValueError, ImportError) as exc:
return {"error": str(exc)}
except Exception as exc: # noqa: BLE001
logger.error("summarize_transcript error: %s", exc)
return {"error": str(exc)}
return {
"decisions": result.get("decisions", []) or [],
"key_quotes": result.get("key_quotes", []) or [],
"summary": result.get("summary", "") or "",
"topics": result.get("topics", []) or [],
}
# ── 6. extract_action_items ─────────────────────────────────────────
@tool
def extract_action_items(transcript: str) -> Dict[str, Any]:
"""Extract action items from a transcript as structured JSON.
Args:
transcript: The full plain-text transcript.
Returns:
Dict ``{"action_items": [{description, owner, due_date, priority}, ...]}``
or ``{"error": "..."}`` on failure.
"""
if not transcript or not transcript.strip():
return {"error": "transcript is required"}
system = (
"You extract action items from meeting transcripts. Return a JSON object "
"with a single key 'action_items': an array of objects each with keys "
"'description' (string), 'owner' (string or null), 'due_date' (ISO date "
"string or null), and 'priority' (one of 'low', 'medium', 'high' or null). "
"Only include real, actionable items."
)
try:
result = _chat_json(system, transcript)
except (ValueError, ImportError) as exc:
return {"error": str(exc)}
except Exception as exc: # noqa: BLE001
logger.error("extract_action_items error: %s", exc)
return {"error": str(exc)}
items = result.get("action_items", []) or []
normalised = [
{
"description": it.get("description", ""),
"due_date": it.get("due_date"),
"owner": it.get("owner"),
"priority": it.get("priority"),
}
for it in items
if isinstance(it, dict)
]
return {"action_items": normalised}
# ── 7. index_meeting ────────────────────────────────────────────────
@tool
def index_meeting(
meeting_id: str,
transcript: Optional[str] = None,
segments: Optional[List[Dict[str, Any]]] = None,
) -> Dict[str, Any]:
"""Chunk, embed and upsert a meeting transcript into the vector store.
Idempotent: existing chunks for ``meeting_id`` are replaced only *after* the
new embeddings are computed, so a failed re-index never leaves the meeting
unsearchable.
Args:
meeting_id: The meeting identifier.
transcript: Optional transcript text. If omitted, the transcript is read
from the stored meeting metadata (``metadata['transcript']``).
segments: Optional ``transcribe_file`` segments (``start``/``end``/``text``).
When provided, each indexed chunk is tagged with the real
``timestamp_start``/``timestamp_end`` of the segments it covers.
Falls back to stored ``metadata['segments']`` when omitted.
Returns:
Dict ``{"chunks_indexed": N}`` or ``{"error": "..."}``.
"""
if not meeting_id:
return {"error": "meeting_id is required"}
meeting = get_meeting(meeting_id)
if "error" in meeting:
return meeting
text = transcript
title = meeting.get("title", "")
meta = meeting.get("metadata") or {}
if not text:
text = meta.get("transcript")
if not text or not str(text).strip():
return {"error": "No transcript available to index"}
if segments is None:
segments = meta.get("segments")
seg_offsets = _segment_char_offsets(segments) if segments else []
try:
collection = _get_vector_collection()
spans = _chunk_spans(text, _CHUNK_SIZE_TOKENS, _CHUNK_OVERLAP_TOKENS)
if not spans:
return {"chunks_indexed": 0}
chunks = [c for c, _s, _e in spans]
# Embed first; only replace existing chunks once embedding succeeds so a
# failure never destroys the previously searchable version.
embeddings = _embed(chunks)
ids = [f"{meeting_id}:{i}" for i in range(len(chunks))]
metadatas = []
for i, (_chunk, cs, ce) in enumerate(spans):
ts_start, ts_end = _timestamps_for_span(cs, ce, seg_offsets)
metadatas.append(
{
"chunk_index": i,
"meeting_id": meeting_id,
"timestamp_end": ts_end,
"timestamp_start": ts_start,
"title": title,
}
)
# Delete existing chunks for this meeting so re-index is idempotent.
collection.delete(where={"meeting_id": meeting_id})
collection.add(
ids=ids,
documents=chunks,
embeddings=embeddings,
metadatas=metadatas,
)
except (ValueError, ImportError) as exc:
return {"error": str(exc)}
except Exception as exc: # noqa: BLE001
logger.error("index_meeting error: %s", exc)
return {"error": str(exc)}
return {"chunks_indexed": len(chunks)}
# ── 8. search_meetings ──────────────────────────────────────────────
@tool
def search_meetings(query: str, limit: int = 5) -> List[Dict[str, Any]]:
"""Semantic search across indexed meetings, returning ranked snippets.
Args:
query: The natural-language search query.
limit: Maximum number of results to return (default 5).
Returns:
A list of ``{meeting_id, title, snippet, score, timestamp_start,
timestamp_end}`` dicts ranked by relevance (best first), or
``[{"error": "..."}]`` on failure.
"""
if not query or not query.strip():
return [{"error": "query is required"}]
try:
limit = max(1, int(limit))
collection = _get_vector_collection()
query_embedding = _embed([query])[0]
results = collection.query(
query_embeddings=[query_embedding], n_results=limit
)
except (ValueError, ImportError) as exc:
return [{"error": str(exc)}]
except Exception as exc: # noqa: BLE001
logger.error("search_meetings error: %s", exc)
return [{"error": str(exc)}]
documents = (results.get("documents") or [[]])[0]
metadatas = (results.get("metadatas") or [[]])[0]
distances = (results.get("distances") or [[]])[0]
items: List[Dict[str, Any]] = []
for i, doc in enumerate(documents):
meta = metadatas[i] if i < len(metadatas) else {}
distance = distances[i] if i < len(distances) else None
# Chroma's default space is squared-L2 (unbounded above). Map to a
# bounded, monotonically decreasing relevance score in (0, 1].
score = (
round(1.0 / (1.0 + float(distance)), 6) if distance is not None else None
)
snippet = (doc or "")[:280]
items.append(
{
"meeting_id": meta.get("meeting_id"),
"score": score,
"snippet": snippet,
"timestamp_end": meta.get("timestamp_end", 0.0),
"timestamp_start": meta.get("timestamp_start", 0.0),
"title": meta.get("title"),
}
)
return items
@@ -1,253 +0,0 @@
"""NEXUS Prediction Market Tool for PraisonAI
Provides access to live Kalshi/Polymarket prediction market data and arbitrage opportunities
through the NEXUS API (https://nexus-agent-xa12.onrender.com).
Features:
- Free market data queries
- Paid arbitrage opportunity detection
- Real-time prediction market insights
API Documentation:
- Free endpoint: /kalshi?market={market_name}
- Paid endpoint: /arb/check?markets={market1,market2}
- Validation: https://agentic.market/validate?url=https://nexus-agent-xa12.onrender.com/arb/check
"""
from typing import Optional, List, Dict, Any
import requests
import json
from praisonai_tools.tools.base import BaseTool
class NexusPredictionMarketTool(BaseTool):
"""Tool for accessing NEXUS prediction market data and arbitrage opportunities."""
name: str = "nexus_prediction_market"
description: str = """Access live Kalshi/Polymarket prediction market data and arbitrage opportunities.
Features:
- Query free market data for specific markets (Fed, BTC, etc.)
- Check arbitrage opportunities between prediction markets (requires payment)
- Get real-time market insights and pricing data
Use cases:
- Market research and analysis
- Arbitrage opportunity identification
- Prediction market trend monitoring
"""
def __init__(self, source_name: Optional[str] = None, api_key: Optional[str] = None):
"""Initialize the NEXUS Prediction Market Tool.
Args:
source_name: Optional source identifier for tracking (sent as X-NEXUS-Source header)
api_key: Optional API key for paid features (if implemented)
"""
super().__init__()
self.base_url = "https://nexus-agent-xa12.onrender.com"
self.source_name = source_name or "praisonai-agent"
self.api_key = api_key
self.headers = {
"X-NEXUS-Source": self.source_name,
"User-Agent": "PraisonAI-NEXUS-Tool/1.0",
"Accept": "application/json"
}
if self.api_key:
self.headers["Authorization"] = f"Bearer {self.api_key}"
def get_market_data(self, market: str) -> Dict[str, Any]:
"""Get free market data for a specific prediction market.
Args:
market: Market identifier (e.g., 'Fed', 'BTC', 'Election')
Returns:
Dict containing market data including prices, volumes, and trends
"""
try:
url = f"{self.base_url}/kalshi"
params = {"market": market}
response = requests.get(url, params=params, headers=self.headers, timeout=30)
response.raise_for_status()
return {
"success": True,
"market": market,
"data": response.json(),
"source": "nexus-free-api"
}
except requests.RequestException as e:
return {
"success": False,
"error": f"Failed to fetch market data: {str(e)}",
"market": market
}
except json.JSONDecodeError as e:
return {
"success": False,
"error": f"Invalid JSON response: {str(e)}",
"market": market
}
def check_arbitrage_opportunities(self, markets: List[str]) -> Dict[str, Any]:
"""Check for arbitrage opportunities between prediction markets (paid feature).
Args:
markets: List of market identifiers to analyze for arbitrage
Returns:
Dict containing arbitrage opportunities and analysis
Note:
This is a paid feature requiring $0.02 USDC on eip155:8453
"""
try:
url = f"{self.base_url}/arb/check"
markets_param = ",".join(markets)
params = {"markets": markets_param}
response = requests.get(url, params=params, headers=self.headers, timeout=30)
response.raise_for_status()
return {
"success": True,
"markets": markets,
"arbitrage_data": response.json(),
"source": "nexus-paid-api",
"note": "This is a paid feature ($0.02 USDC on eip155:8453)"
}
except requests.RequestException as e:
if e.response and e.response.status_code == 402:
return {
"success": False,
"error": "Payment required for arbitrage analysis. Cost: $0.02 USDC on eip155:8453",
"markets": markets,
"payment_info": "This feature requires payment on eip155:8453 blockchain"
}
return {
"success": False,
"error": f"Failed to check arbitrage opportunities: {str(e)}",
"markets": markets
}
except json.JSONDecodeError as e:
return {
"success": False,
"error": f"Invalid JSON response: {str(e)}",
"markets": markets
}
def get_agent_info(self) -> Dict[str, Any]:
"""Get NEXUS agent information and capabilities.
Returns:
Dict containing agent metadata and API information
"""
try:
url = f"{self.base_url}/.well-known/agent.json"
response = requests.get(url, headers=self.headers, timeout=30)
response.raise_for_status()
return {
"success": True,
"agent_info": response.json(),
"source": "nexus-agent-metadata"
}
except requests.RequestException as e:
return {
"success": False,
"error": f"Failed to fetch agent info: {str(e)}"
}
except json.JSONDecodeError as e:
return {
"success": False,
"error": f"Invalid JSON response: {str(e)}"
}
def run(self,
action: str,
market: Optional[str] = None,
markets: Optional[List[str]] = None) -> str:
"""Execute NEXUS prediction market operations.
Args:
action: Action to perform ('get_market_data', 'check_arbitrage', 'get_agent_info')
market: Single market identifier (for get_market_data)
markets: List of markets (for check_arbitrage)
Returns:
JSON string with operation results
"""
try:
if action == "get_market_data":
if not market:
return json.dumps({
"success": False,
"error": "Market parameter required for get_market_data action"
})
result = self.get_market_data(market)
elif action == "check_arbitrage":
if not markets or not isinstance(markets, list):
return json.dumps({
"success": False,
"error": "Markets parameter (list) required for check_arbitrage action"
})
result = self.check_arbitrage_opportunities(markets)
elif action == "get_agent_info":
result = self.get_agent_info()
else:
return json.dumps({
"success": False,
"error": f"Unknown action: {action}. Available actions: get_market_data, check_arbitrage, get_agent_info"
})
return json.dumps(result, indent=2)
except Exception as e:
return json.dumps({
"success": False,
"error": f"Unexpected error: {str(e)}"
})
# For backward compatibility and ease of use
def nexus_prediction_market_tool(
action: str,
market: Optional[str] = None,
markets: Optional[List[str]] = None,
source_name: Optional[str] = None
) -> str:
"""Function-based interface for NEXUS prediction market operations.
Args:
action: Action to perform ('get_market_data', 'check_arbitrage', 'get_agent_info')
market: Single market identifier (for get_market_data)
markets: List of markets (for check_arbitrage)
source_name: Optional source identifier for tracking
Returns:
JSON string with operation results
Examples:
# Get Fed market data
result = nexus_prediction_market_tool("get_market_data", market="Fed")
# Check arbitrage between Fed and BTC markets
result = nexus_prediction_market_tool("check_arbitrage", markets=["Fed", "BTC"])
# Get agent info
result = nexus_prediction_market_tool("get_agent_info")
"""
tool = NexusPredictionMarketTool(source_name=source_name)
return tool.run(action=action, market=market, markets=markets)
__all__ = ["NexusPredictionMarketTool", "nexus_prediction_market_tool"]
+1 -14
View File
@@ -97,18 +97,5 @@ class PinchworkTool(BaseTool):
def pinchwork_delegate(task: str, skills_required: Optional[List[str]] = None, budget: float = 0.0) -> str:
"""Delegate a task to the Pinchwork agent marketplace.
Args:
task: Description of the task to delegate.
skills_required: List of required skills for the agent (optional).
budget: Maximum budget for the task (default: 0.0).
Returns:
On success, the result string from the marketplace agent that
completed the task. On failure, an ``"Error: ..."`` message string
describing the problem (missing task input, the ``httpx`` dependency
being unavailable, a connection or HTTP status error, or an
unexpected exception).
"""
"""Delegate a task to the Pinchwork agent marketplace."""
return PinchworkTool().delegate(task=task, skills_required=skills_required, budget=budget)
+7 -146
View File
@@ -17,17 +17,6 @@ Environment Variables:
REDDIT_CLIENT_ID: Reddit API client ID
REDDIT_CLIENT_SECRET: Reddit API client secret
REDDIT_USER_AGENT: User agent string (optional)
REDDIT_USERNAME: Reddit username (required for write actions)
REDDIT_PASSWORD: Reddit password (required for write actions)
REDDIT_ALLOW_WRITE: Set to "1" to enable write actions (post/comment)
Write actions (submit_post, post_comment) are disabled by default to reduce
spam/abuse surface. They are only permitted when ``REDDIT_ALLOW_WRITE=1`` (or
``allow_write=True``) and Reddit account credentials are configured. You are
responsible for complying with Reddit's API terms when enabling writes.
Reddit rate-limits misconfigured clients aggressively. Use a descriptive
User-Agent referencing your app id, e.g. ``script:my-app:v1.0 (by /u/you)``.
"""
import os
@@ -43,20 +32,13 @@ class RedditTool(BaseTool):
"""Tool for interacting with Reddit."""
name = "reddit"
description = (
"Search Reddit, get posts from subreddits, and read comments. "
"Can also comment on posts and submit new posts when write actions "
"are enabled (REDDIT_ALLOW_WRITE=1 with account credentials)."
)
description = "Search Reddit, get posts from subreddits, and read comments."
def __init__(
self,
client_id: Optional[str] = None,
client_secret: Optional[str] = None,
user_agent: Optional[str] = None,
username: Optional[str] = None,
password: Optional[str] = None,
allow_write: Optional[bool] = None,
):
"""Initialize RedditTool.
@@ -64,30 +46,13 @@ class RedditTool(BaseTool):
client_id: Reddit API client ID
client_secret: Reddit API client secret
user_agent: User agent string
username: Reddit username (required for write actions)
password: Reddit password (required for write actions)
allow_write: Enable write actions. Defaults to the
``REDDIT_ALLOW_WRITE`` env var ("1"/"true" enables).
"""
self.client_id = client_id or os.getenv("REDDIT_CLIENT_ID")
self.client_secret = client_secret or os.getenv("REDDIT_CLIENT_SECRET")
self.user_agent = user_agent or os.getenv("REDDIT_USER_AGENT") or self._default_user_agent()
self.username = username or os.getenv("REDDIT_USERNAME")
self.password = password or os.getenv("REDDIT_PASSWORD")
if allow_write is None:
allow_write = os.getenv("REDDIT_ALLOW_WRITE", "").lower() in ("1", "true", "yes")
self.allow_write = allow_write
self.user_agent = user_agent or os.getenv("REDDIT_USER_AGENT", "PraisonAI/1.0")
self._reddit = None
super().__init__()
def _default_user_agent(self) -> str:
"""Build a compliant User-Agent referencing the app id.
Reddit recommends ``<platform>:<app id>:<version> (by /u/<user>)``.
"""
app_id = self.client_id or "unknown"
return f"script:praisonai-{app_id}:1.0 (by PraisonAI)"
@property
def reddit(self):
"""Lazy-load Reddit client."""
@@ -100,31 +65,13 @@ class RedditTool(BaseTool):
if not self.client_id or not self.client_secret:
raise ValueError("REDDIT_CLIENT_ID and REDDIT_CLIENT_SECRET required")
kwargs = {
"client_id": self.client_id,
"client_secret": self.client_secret,
"user_agent": self.user_agent,
}
if self.username and self.password:
kwargs["username"] = self.username
kwargs["password"] = self.password
self._reddit = praw.Reddit(**kwargs)
self._reddit = praw.Reddit(
client_id=self.client_id,
client_secret=self.client_secret,
user_agent=self.user_agent,
)
return self._reddit
def _check_write_allowed(self) -> Optional[Dict[str, Any]]:
"""Return an error dict if write actions are not permitted, else None."""
if not self.allow_write:
return {
"error": "Write actions disabled. Set REDDIT_ALLOW_WRITE=1 to enable "
"posting/commenting.",
}
if not self.username or not self.password:
return {
"error": "REDDIT_USERNAME and REDDIT_PASSWORD required for write actions.",
}
return None
def run(
self,
action: str = "search",
@@ -151,15 +98,6 @@ class RedditTool(BaseTool):
return self.get_comments(post_id=post_id, limit=limit)
elif action == "subreddit_info":
return self.get_subreddit_info(subreddit=subreddit)
elif action == "post_comment":
return self.post_comment(post_id=post_id, body=kwargs.get("body"))
elif action == "submit_post":
return self.submit_post(
subreddit=subreddit,
title=kwargs.get("title"),
body=kwargs.get("body"),
url=kwargs.get("url"),
)
else:
return {"error": f"Unknown action: {action}"}
@@ -346,83 +284,6 @@ class RedditTool(BaseTool):
logger.error(f"Reddit get_subreddit_info error: {e}")
return {"error": str(e)}
def post_comment(self, post_id: str, body: str) -> Dict[str, Any]:
"""Reply with a comment to a post (write action).
Gated behind ``REDDIT_ALLOW_WRITE=1`` and account credentials.
Args:
post_id: Reddit post ID to comment on
body: Comment text
Returns:
Result with the new comment id, or an error dict
"""
denied = self._check_write_allowed()
if denied:
return denied
if not post_id:
return {"error": "post_id is required"}
if not body:
return {"error": "body is required"}
try:
submission = self.reddit.submission(id=post_id)
comment = submission.reply(body)
return {
"success": True,
"id": comment.id,
"permalink": f"https://reddit.com{comment.permalink}",
}
except Exception as e:
logger.error(f"Reddit post_comment error: {e}")
return {"error": str(e)}
def submit_post(
self,
subreddit: str,
title: str,
body: Optional[str] = None,
url: Optional[str] = None,
) -> Dict[str, Any]:
"""Submit a new post to a subreddit (write action).
Gated behind ``REDDIT_ALLOW_WRITE=1`` and account credentials.
Args:
subreddit: Target subreddit name
title: Post title
body: Self-post text (mutually exclusive with url)
url: Link URL (mutually exclusive with body)
Returns:
Result with the new post id, or an error dict
"""
denied = self._check_write_allowed()
if denied:
return denied
if not subreddit:
return {"error": "subreddit is required"}
if not title:
return {"error": "title is required"}
if url and body:
return {"error": "provide either body or url, not both"}
try:
sub = self.reddit.subreddit(subreddit)
if url:
submission = sub.submit(title, url=url)
else:
submission = sub.submit(title, selftext=body or "")
return {
"success": True,
"id": submission.id,
"permalink": f"https://reddit.com{submission.permalink}",
}
except Exception as e:
logger.error(f"Reddit submit_post error: {e}")
return {"error": str(e)}
def _format_post(self, post, include_body: bool = False) -> Dict[str, Any]:
"""Format a Reddit post."""
result = {
-338
View File
@@ -1,338 +0,0 @@
"""Stripe Tool for PraisonAI Agents.
Narrow, audited Stripe operations — retrieve customers/payment intents,
list payment links, and create payment links with required correlation
metadata and optional idempotency keys.
Design constraint: prefer narrow, audited operations over a "god tool"
that dumps the entire Stripe surface. One verb per action.
Usage:
from praisonai_tools import StripeTool
stripe = StripeTool() # reads STRIPE_SECRET_KEY (or STRIPE_API_KEY)
customer = stripe.run(action="get_customer", customer_id="cus_123")
link = stripe.run(
action="create_payment_link",
price_id="price_123",
quantity=1,
correlation_id="order-42",
)
Environment Variables:
STRIPE_SECRET_KEY: Stripe secret key. Restricted keys are recommended.
Accepts test (``sk_test_``/``rk_test_``) or live
(``sk_live_``/``rk_live_``) keys. STRIPE_API_KEY is also accepted
as a fallback.
Security notes:
* Secrets are read from the environment only and never logged.
* Responses include a ``mode`` banner (``test``/``live``) derived from
the key prefix so live operations are visible to callers.
* Structured logs record only the operation, mode, idempotency key, and
the Stripe object id — never full request/response payloads.
"""
import os
import logging
from typing import Any, Dict, List, Optional, Union
from praisonai_tools.tools.base import BaseTool
logger = logging.getLogger(__name__)
API_BASE = "https://api.stripe.com/v1"
_TEST_PREFIXES = ("sk_test_", "rk_test_")
_LIVE_PREFIXES = ("sk_live_", "rk_live_")
class StripeTool(BaseTool):
"""Tool for narrow, audited Stripe operations."""
name = "stripe"
description = (
"Retrieve Stripe customers and payment intents, list payment links, "
"and create payment links with required correlation metadata."
)
def __init__(self, api_key: Optional[str] = None):
self.api_key = (
api_key
or os.getenv("STRIPE_SECRET_KEY")
or os.getenv("STRIPE_API_KEY")
)
super().__init__()
# ------------------------------------------------------------------
# Internal helpers
# ------------------------------------------------------------------
def _mode(self) -> str:
"""Return ``test``, ``live``, or ``unknown`` from the key prefix."""
key = self.api_key or ""
if key.startswith(_LIVE_PREFIXES):
return "live"
if key.startswith(_TEST_PREFIXES):
return "test"
return "unknown"
def _require_key(self) -> Optional[Dict[str, str]]:
if not self.api_key:
return {"error": "STRIPE_SECRET_KEY (or STRIPE_API_KEY) is required"}
return None
@staticmethod
def _import_requests():
try:
import requests
return requests
except ImportError:
return None
def _request(
self,
method: str,
endpoint: str,
data: Optional[Dict[str, Any]] = None,
idempotency_key: Optional[str] = None,
) -> Dict[str, Any]:
"""Make a request to the Stripe REST API.
Centralises key validation, the optional ``requests`` import, the
HTTP call, auditable logging, and error handling.
"""
err = self._require_key()
if err:
return err
requests = self._import_requests()
if requests is None:
return {"error": "requests package is not installed"}
headers = {"Authorization": f"Bearer {self.api_key}"}
if idempotency_key:
headers["Idempotency-Key"] = idempotency_key
try:
resp = requests.request(
method,
f"{API_BASE}/{endpoint}",
headers=headers,
data=data,
timeout=30,
)
body = resp.json()
except requests.exceptions.RequestException as e:
logger.error("Stripe request error: %s", e)
return {"error": f"API request failed: {e}"}
except ValueError as e:
logger.error("Stripe JSON decode error: %s", e)
return {"error": "Failed to decode API response"}
if isinstance(body, dict) and "error" in body:
stripe_err = body["error"]
message = stripe_err.get("message", "Stripe API error")
logger.error(
"Stripe API error: op=%s mode=%s type=%s",
endpoint, self._mode(), stripe_err.get("type"),
)
return {"error": message}
# Defensive: a non-2xx status without Stripe's usual ``error`` object
# must not be treated as a successful payload.
if resp.status_code >= 400:
logger.error(
"Stripe HTTP error: op=%s mode=%s status=%s",
endpoint, self._mode(), resp.status_code,
)
return {"error": f"Stripe API returned HTTP {resp.status_code}"}
obj_id = body.get("id") if isinstance(body, dict) else None
logger.info(
"Stripe op=%s mode=%s idempotency_key=%s object_id=%s",
endpoint, self._mode(), idempotency_key, obj_id,
)
return body
def _banner(self, payload: Dict[str, Any]) -> Dict[str, Any]:
"""Attach a live/test mode banner to a successful response."""
if isinstance(payload, dict) and "error" not in payload:
payload = {"mode": self._mode(), **payload}
return payload
# ------------------------------------------------------------------
# Dispatcher
# ------------------------------------------------------------------
def run(
self,
action: str = "get_customer",
customer_id: Optional[str] = None,
payment_intent_id: Optional[str] = None,
price_id: Optional[str] = None,
quantity: int = 1,
correlation_id: Optional[str] = None,
idempotency_key: Optional[str] = None,
limit: int = 10,
**kwargs,
) -> Union[Dict[str, Any], List[Dict[str, Any]]]:
"""Dispatch to the appropriate Stripe action.
Actions:
get_customer — Retrieve a customer by id (read).
get_payment_intent — Retrieve a payment intent by id (read).
list_payment_links — List payment links (read).
create_payment_link — Create a payment link (write, guarded).
"""
action = action.lower().replace("-", "_")
if action == "get_customer":
return self.get_customer(customer_id=customer_id)
elif action == "get_payment_intent":
return self.get_payment_intent(payment_intent_id=payment_intent_id)
elif action == "list_payment_links":
return self.list_payment_links(limit=limit)
elif action == "create_payment_link":
return self.create_payment_link(
price_id=price_id,
quantity=quantity,
correlation_id=correlation_id,
idempotency_key=idempotency_key,
)
else:
return {"error": f"Unknown action: {action}"}
# ------------------------------------------------------------------
# Phase 1 — Read-mostly safety
# ------------------------------------------------------------------
def get_customer(self, customer_id: Optional[str] = None) -> Dict[str, Any]:
"""Retrieve a customer by id.
Args:
customer_id: The Stripe customer id (``cus_...``).
"""
if not customer_id:
return {"error": "customer_id is required"}
result = self._request("get", f"customers/{customer_id}")
if "error" in result:
return result
return self._banner({
"id": result.get("id"),
"email": result.get("email"),
"name": result.get("name"),
"created": result.get("created"),
"currency": result.get("currency"),
"delinquent": result.get("delinquent"),
})
def get_payment_intent(
self, payment_intent_id: Optional[str] = None
) -> Dict[str, Any]:
"""Retrieve a payment intent by id.
Args:
payment_intent_id: The Stripe payment intent id (``pi_...``).
"""
if not payment_intent_id:
return {"error": "payment_intent_id is required"}
result = self._request("get", f"payment_intents/{payment_intent_id}")
if "error" in result:
return result
return self._banner({
"id": result.get("id"),
"amount": result.get("amount"),
"currency": result.get("currency"),
"status": result.get("status"),
"customer": result.get("customer"),
"created": result.get("created"),
})
def list_payment_links(self, limit: int = 10) -> Union[Dict[str, Any], List[Dict[str, Any]]]:
"""List payment links.
Args:
limit: Maximum number of payment links to return (1–100).
"""
limit = max(1, min(int(limit), 100))
result = self._request("get", f"payment_links?limit={limit}")
if "error" in result:
return result
links = [
{
"id": link.get("id"),
"url": link.get("url"),
"active": link.get("active"),
"metadata": link.get("metadata", {}),
}
for link in result.get("data", [])
]
return self._banner({"payment_links": links})
# ------------------------------------------------------------------
# Phase 2 — Mutations with guardrails
# ------------------------------------------------------------------
def create_payment_link(
self,
price_id: Optional[str] = None,
quantity: int = 1,
correlation_id: Optional[str] = None,
idempotency_key: Optional[str] = None,
) -> Dict[str, Any]:
"""Create a payment link.
A ``correlation_id`` is required and stored as payment-link metadata
so every created link is traceable back to the request that made it.
An optional ``idempotency_key`` is surfaced to make retries safe.
Args:
price_id: An existing Stripe Price id (``price_...``).
quantity: Quantity for the line item (>= 1).
correlation_id: Required correlation id stored as metadata.
idempotency_key: Optional Stripe ``Idempotency-Key`` header value.
"""
if not price_id:
return {"error": "price_id is required"}
if not correlation_id:
return {"error": "correlation_id is required (stored as metadata)"}
try:
quantity = int(quantity)
except (TypeError, ValueError):
return {"error": "quantity must be an integer"}
if quantity < 1:
return {"error": "quantity must be >= 1"}
data = {
"line_items[0][price]": price_id,
"line_items[0][quantity]": quantity,
"metadata[correlation_id]": correlation_id,
}
result = self._request(
"post",
"payment_links",
data=data,
idempotency_key=idempotency_key,
)
if "error" in result:
return result
return self._banner({
"id": result.get("id"),
"url": result.get("url"),
"active": result.get("active"),
"metadata": result.get("metadata", {}),
})
def get_stripe_customer(
customer_id: str, api_key: Optional[str] = None
) -> Dict[str, Any]:
"""Retrieve a Stripe customer by id."""
return StripeTool(api_key=api_key).get_customer(customer_id=customer_id)
-259
View File
@@ -1,259 +0,0 @@
"""SwarmScore integration tool for PraisonAI.
SwarmScore is a portable trust rating system for AI agents based on verified execution history.
This tool allows agents to:
- Load their SwarmScore rating and certificate
- Verify SwarmScore freshness
- Access discovery manifest for agent-to-agent lookup
More information: https://swarmsync.ai/docs/protocol-specs/swarmscore
"""
import json
import logging
from typing import Dict, Any
from urllib.parse import urlparse, quote
try:
import requests
except ImportError:
requests = None
from .base import BaseTool, ToolResult
logger = logging.getLogger(__name__)
class SwarmScoreTool(BaseTool):
"""Tool for integrating with SwarmScore trust ratings."""
name = "swarmscore"
description = "Load and verify SwarmScore trust ratings for AI agents"
def __init__(self, api_base_url: str = "https://api.swarmsync.ai/v1/swarmscore/"):
"""Initialize SwarmScore tool.
Args:
api_base_url: Base URL for SwarmScore API
"""
if requests is None:
raise ImportError("requests is required for SwarmScoreTool. Install with: pip install requests")
super().__init__()
self.api_base_url = api_base_url.rstrip('/')
def load_swarmscore(self, slug: str) -> ToolResult:
"""Load SwarmScore data by agent slug.
Args:
slug: Agent slug identifier
Returns:
ToolResult containing SwarmScore data including passport, certificate, and verification payload
"""
try:
url = f"{self.api_base_url}/load-by-slug/{quote(slug, safe='')}"
response = requests.get(url, timeout=30)
response.raise_for_status()
data = response.json()
return ToolResult(
output=data,
success=True,
metadata={"message": f"Successfully loaded SwarmScore for agent '{slug}'"}
)
except json.JSONDecodeError as e:
logger.error(f"Invalid JSON response for SwarmScore {slug}: {e}")
return ToolResult(
output=None,
success=False,
error="Invalid response format from SwarmScore API"
)
except requests.exceptions.RequestException as e:
logger.error(f"Failed to load SwarmScore for {slug}: {e}")
return ToolResult(
output=None,
success=False,
error=f"Failed to load SwarmScore: {str(e)}"
)
def verify_swarmscore(self, verify_payload: Dict[str, Any]) -> ToolResult:
"""Verify SwarmScore freshness using verification payload.
Args:
verify_payload: Verification payload from load_swarmscore response
Returns:
ToolResult containing verification status
"""
try:
url = f"{self.api_base_url}/verify"
response = requests.post(
url,
json=verify_payload,
headers={"Content-Type": "application/json"},
timeout=30
)
response.raise_for_status()
data = response.json()
return ToolResult(
output=data,
success=True,
metadata={"message": "SwarmScore verification completed"}
)
except json.JSONDecodeError as e:
logger.error(f"Invalid JSON response for SwarmScore verification: {e}")
return ToolResult(
output=None,
success=False,
error="Invalid response format from verification API"
)
except requests.exceptions.RequestException as e:
logger.error(f"Failed to verify SwarmScore: {e}")
return ToolResult(
output=None,
success=False,
error=f"Failed to verify SwarmScore: {str(e)}"
)
def get_discovery_manifest(self) -> ToolResult:
"""Get machine-readable agent discovery manifest.
Returns:
ToolResult containing discovery manifest data
"""
try:
parsed = urlparse(self.api_base_url)
base = f"{parsed.scheme}://{parsed.netloc}"
url = f"{base}/.well-known/agent-card.json"
response = requests.get(url, timeout=30)
response.raise_for_status()
data = response.json()
return ToolResult(
output=data,
success=True,
metadata={"message": "Retrieved SwarmScore discovery manifest"}
)
except json.JSONDecodeError as e:
logger.error(f"Invalid JSON in discovery manifest: {e}")
return ToolResult(
output=None,
success=False,
error="Invalid discovery manifest format"
)
except requests.exceptions.RequestException as e:
logger.error(f"Failed to get discovery manifest: {e}")
return ToolResult(
output=None,
success=False,
error=f"Failed to get discovery manifest: {str(e)}"
)
def run(self, action: str = "load", **kwargs) -> ToolResult:
"""Execute SwarmScore action.
Args:
action: Action to perform ('load', 'verify', or 'discover')
**kwargs: Action-specific parameters
Returns:
ToolResult with action results
"""
if action == "load":
slug = kwargs.get("slug")
if not slug:
return ToolResult(
output=None,
success=False,
error="Missing required parameter 'slug' for load action"
)
return self.load_swarmscore(slug)
elif action == "verify":
verify_payload = kwargs.get("verify_payload")
if not verify_payload:
return ToolResult(
output=None,
success=False,
error="Missing required parameter 'verify_payload' for verify action"
)
return self.verify_swarmscore(verify_payload)
elif action == "discover":
return self.get_discovery_manifest()
else:
return ToolResult(
output=None,
success=False,
error=f"Unknown action '{action}'. Supported actions: load, verify, discover"
)
# Standalone functions for easy agent integration
def load_swarmscore_by_slug(slug: str) -> Dict[str, Any]:
"""Load SwarmScore data by agent slug.
Args:
slug: Agent slug identifier
Returns:
Dictionary containing SwarmScore data
Raises:
Exception: If loading fails
"""
tool = SwarmScoreTool()
result = tool.load_swarmscore(slug)
if not result.success:
raise Exception(result.error)
return result.output
def verify_swarmscore_freshness(verify_payload: Dict[str, Any]) -> Dict[str, Any]:
"""Verify SwarmScore freshness.
Args:
verify_payload: Verification payload from load response
Returns:
Dictionary containing verification results
Raises:
Exception: If verification fails
"""
tool = SwarmScoreTool()
result = tool.verify_swarmscore(verify_payload)
if not result.success:
raise Exception(result.error)
return result.output
def get_agent_discovery_manifest() -> Dict[str, Any]:
"""Get machine-readable agent discovery manifest.
Returns:
Dictionary containing discovery manifest
Raises:
Exception: If retrieval fails
"""
tool = SwarmScoreTool()
result = tool.get_discovery_manifest()
if not result.success:
raise Exception(result.error)
return result.output
-484
View File
@@ -1,484 +0,0 @@
"""You.com search and content tools for PraisonAI Agents.
Migrated from ``praisonaiagents.tools.youdotcom_tools`` (MervinPraison/PraisonAI#6168).
You.com provides AI-powered web search, news search, content extraction, and image search.
This module requires the YDC_API_KEY environment variable to be set.
Usage:
from praisonai_tools.tools.youdotcom_tool import ydc_search, ydc_news, ydc_contents
# Search the web (unified web + news)
results = ydc_search("AI news 2024")
# Get live news
news = ydc_news("technology trends")
# Extract content from URLs
content = ydc_contents(["https://example.com"])
# Or use the class directly
from praisonai_tools.tools.youdotcom_tool import YouTools
you = YouTools()
results = you.search("AI news")
"""
from typing import List, Dict, Any, Optional, Union
import logging
import os
from importlib import util
class YouTools:
"""Comprehensive tools for web search and content using You.com API.
You.com provides AI-powered search capabilities optimized for LLM applications.
Features:
- Unified web and news search with LLM-ready snippets
- Live news search from authoritative sources
- Content extraction from URLs (HTML/Markdown)
- Image search
- Advanced search operators support
- Geographic and language targeting
- Freshness controls
Requires:
- youdotcom package: pip install youdotcom
- YDC_API_KEY environment variable
"""
def __init__(self, api_key: Optional[str] = None):
"""Initialize YouTools.
Args:
api_key: Optional API key. If not provided, uses YDC_API_KEY env var.
"""
self._api_key = api_key
self._client = None
def _get_api_key(self) -> Optional[str]:
"""Get API key from instance or environment."""
return self._api_key or os.environ.get("YDC_API_KEY")
def _get_client(self):
"""Get or create You.com client."""
if self._client is None:
if util.find_spec("youdotcom") is None:
return None, "youdotcom package is not installed. Please install it using: pip install youdotcom"
api_key = self._get_api_key()
if not api_key:
return None, "YDC_API_KEY environment variable is not set. Please set it to use You.com tools."
from youdotcom import You
self._client = You(api_key_auth=api_key)
return self._client, None
def search(
self,
query: str,
count: int = 10,
freshness: Optional[str] = None,
country: Optional[str] = None,
language: Optional[str] = None,
offset: int = 0,
safesearch: str = "moderate",
livecrawl: Optional[str] = None,
livecrawl_formats: Optional[str] = None,
) -> Dict[str, Any]:
"""Search the web using You.com's unified search API.
Returns both web and news results in a single call with LLM-ready snippets.
Args:
query: Search query (supports operators like site:, filetype:, +term, -term)
count: Max results per section (default 10, max 100)
freshness: Filter by recency - "day", "week", "month", "year" or "YYYY-MM-DDtoYYYY-MM-DD"
country: ISO country code (e.g., "US", "GB", "FR")
language: BCP 47 language code (e.g., "EN", "JP", "DE")
offset: Pagination offset (0-9), results = offset * count
safesearch: Content filter - "off", "moderate", "strict"
livecrawl: Fetch full content - "web", "news", or "all"
livecrawl_formats: Content format - "html" or "markdown"
Returns:
Dict containing:
- results: {web: [...], news: [...]}
- metadata: {query, search_uuid, latency}
Search Operators:
- site:domain.com - Search within specific domain
- filetype:pdf - Filter by file type
- +term - Must include term
- -term - Exclude term
- AND, OR, NOT - Boolean operators
"""
client, error = self._get_client()
if error:
logging.error(error)
return {"error": error}
try:
kwargs = {"query": query, "count": count, "offset": offset}
if freshness:
kwargs["freshness"] = freshness
if country:
kwargs["country"] = country
if language:
kwargs["language"] = language
if safesearch:
kwargs["safesearch"] = safesearch
if livecrawl:
kwargs["livecrawl"] = livecrawl
if livecrawl_formats:
kwargs["livecrawl_formats"] = livecrawl_formats
response = client.search.unified(**kwargs)
# Convert response to dict if it's a model object
if hasattr(response, 'model_dump'):
return response.model_dump()
elif hasattr(response, 'to_dict'):
return response.to_dict()
elif hasattr(response, '__dict__'):
return self._convert_response(response)
return response
except Exception as e:
error_msg = f"You.com search error: {str(e)}"
logging.error(error_msg)
return {"error": error_msg}
def _convert_response(self, response) -> Dict[str, Any]:
"""Convert SDK response object to dictionary."""
result = {}
if hasattr(response, 'results'):
results = response.results
result['results'] = {}
if hasattr(results, 'web') and results.web:
result['results']['web'] = [
{
'url': getattr(r, 'url', ''),
'title': getattr(r, 'title', ''),
'description': getattr(r, 'description', ''),
'snippets': getattr(r, 'snippets', []),
'thumbnail_url': getattr(r, 'thumbnail_url', None),
'page_age': getattr(r, 'page_age', None),
'favicon_url': getattr(r, 'favicon_url', None),
'authors': getattr(r, 'authors', []),
}
for r in results.web
]
if hasattr(results, 'news') and results.news:
result['results']['news'] = [
{
'url': getattr(r, 'url', ''),
'title': getattr(r, 'title', ''),
'description': getattr(r, 'description', ''),
'thumbnail_url': getattr(r, 'thumbnail_url', None),
'page_age': getattr(r, 'page_age', None),
}
for r in results.news
]
if hasattr(response, 'metadata'):
meta = response.metadata
result['metadata'] = {
'query': getattr(meta, 'query', ''),
'search_uuid': getattr(meta, 'search_uuid', ''),
'latency': getattr(meta, 'latency', 0),
}
return result
def get_contents(
self,
urls: Union[str, List[str]],
format: str = "markdown",
) -> Dict[str, Any]:
"""Fetch content from URLs using You.com's content extraction API.
Args:
urls: Single URL or list of URLs to fetch content from
format: Content format - "html" or "markdown" (default: markdown)
Returns:
Dict containing array of results with:
- url: The fetched URL
- title: Page title
- html: HTML content (if format="html")
- markdown: Markdown content (if format="markdown")
- metadata: {site_name, favicon_url}
"""
client, error = self._get_client()
if error:
logging.error(error)
return {"error": error}
try:
if isinstance(urls, str):
urls = [urls]
# Use the contents endpoint
response = client.search.contents(urls=urls, format=format)
# Convert response
if hasattr(response, 'model_dump'):
return {"results": response.model_dump()}
elif isinstance(response, list):
return {"results": [
{
'url': getattr(r, 'url', ''),
'title': getattr(r, 'title', ''),
'html': getattr(r, 'html', None),
'markdown': getattr(r, 'markdown', None),
'metadata': {
'site_name': getattr(getattr(r, 'metadata', None), 'site_name', None) if hasattr(r, 'metadata') else None,
'favicon_url': getattr(getattr(r, 'metadata', None), 'favicon_url', None) if hasattr(r, 'metadata') else None,
}
}
for r in response
]}
return {"results": response}
except Exception as e:
error_msg = f"You.com contents error: {str(e)}"
logging.error(error_msg)
return {"error": error_msg}
def live_news(
self,
query: str,
count: Optional[int] = None,
) -> Dict[str, Any]:
"""Search for live news using You.com's news API.
Note: This API may require early access. Contact [email protected] for access.
Args:
query: News search query
count: Maximum number of news results to return
Returns:
Dict containing:
- news: {query, results: [...], metadata}
- Each result has: title, description, url, page_age, source_name, thumbnail
"""
client, error = self._get_client()
if error:
logging.error(error)
return {"error": error}
try:
kwargs = {"q": query}
if count:
kwargs["count"] = count
# Try to access live news endpoint
if hasattr(client, 'livenews'):
response = client.livenews.get(**kwargs)
else:
# Fallback: use unified search with news focus
return self.search(query=query, count=count or 10)
if hasattr(response, 'model_dump'):
return response.model_dump()
elif hasattr(response, 'news'):
news = response.news
return {
'news': {
'query': getattr(getattr(news, 'query', None), 'original', query) if hasattr(news, 'query') else query,
'results': [
{
'title': getattr(r, 'title', ''),
'description': getattr(r, 'description', ''),
'url': getattr(r, 'url', ''),
'page_age': getattr(r, 'page_age', None),
'age': getattr(r, 'age', None),
'source_name': getattr(r, 'source_name', None),
'thumbnail': getattr(getattr(r, 'thumbnail', None), 'src', None) if hasattr(r, 'thumbnail') else None,
}
for r in getattr(news, 'results', [])
],
'metadata': {
'request_uuid': getattr(getattr(news, 'metadata', None), 'request_uuid', None) if hasattr(news, 'metadata') else None,
}
}
}
return response
except Exception as e:
error_msg = f"You.com live news error: {str(e)}"
logging.error(error_msg)
return {"error": error_msg}
def images(
self,
query: str,
) -> Dict[str, Any]:
"""Search for images using You.com's image search API.
Note: This API may require early access. Contact [email protected] for access.
Args:
query: Image search query
Returns:
Dict containing:
- images: {results: [...]}
- metadata: {query, search_uuid}
- Each result has: title, page_url, image_url
"""
client, error = self._get_client()
if error:
logging.error(error)
return {"error": error}
try:
if hasattr(client, 'images'):
response = client.images.get(q=query)
else:
return {"error": "Image search not available in this SDK version"}
if hasattr(response, 'model_dump'):
return response.model_dump()
elif hasattr(response, 'images'):
images = response.images
return {
'images': {
'results': [
{
'title': getattr(r, 'title', ''),
'page_url': getattr(r, 'page_url', ''),
'image_url': getattr(r, 'image_url', ''),
}
for r in getattr(images, 'results', [])
]
},
'metadata': {
'query': getattr(getattr(response, 'metadata', None), 'query', query) if hasattr(response, 'metadata') else query,
'search_uuid': getattr(getattr(response, 'metadata', None), 'search_uuid', None) if hasattr(response, 'metadata') else None,
}
}
return response
except Exception as e:
error_msg = f"You.com images error: {str(e)}"
logging.error(error_msg)
return {"error": error_msg}
def __enter__(self):
"""Context manager entry."""
return self
def __exit__(self, exc_type, exc_val, exc_tb):
"""Context manager exit."""
if self._client is not None:
# Close client if it has a close method
if hasattr(self._client, 'close'):
self._client.close()
elif hasattr(self._client, '__exit__'):
self._client.__exit__(exc_type, exc_val, exc_tb)
return False
# Standalone functions for direct import
def ydc_search(
query: str,
count: int = 10,
freshness: Optional[str] = None,
country: Optional[str] = None,
language: Optional[str] = None,
offset: int = 0,
safesearch: str = "moderate",
livecrawl: Optional[str] = None,
livecrawl_formats: Optional[str] = None,
) -> Dict[str, Any]:
"""Search the web using You.com's unified search API.
This is a convenience function that creates a YouTools instance.
For repeated calls, consider using YouTools class directly.
Args:
query: Search query (supports operators like site:, filetype:, +term, -term)
count: Max results per section (default 10, max 100)
freshness: Filter by recency - "day", "week", "month", "year"
country: ISO country code (e.g., "US", "GB")
language: BCP 47 language code (e.g., "EN", "JP")
offset: Pagination offset (0-9)
safesearch: Content filter - "off", "moderate", "strict"
livecrawl: Fetch full content - "web", "news", or "all"
livecrawl_formats: Content format - "html" or "markdown"
Returns:
Dict containing search results with web and news sections
"""
tools = YouTools()
return tools.search(
query=query,
count=count,
freshness=freshness,
country=country,
language=language,
offset=offset,
safesearch=safesearch,
livecrawl=livecrawl,
livecrawl_formats=livecrawl_formats,
)
def ydc_contents(
urls: Union[str, List[str]],
format: str = "markdown",
) -> Dict[str, Any]:
"""Fetch content from URLs using You.com's content extraction API.
Args:
urls: Single URL or list of URLs to fetch content from
format: Content format - "html" or "markdown"
Returns:
Dict containing extracted content for each URL
"""
tools = YouTools()
return tools.get_contents(urls=urls, format=format)
def ydc_news(
query: str,
count: Optional[int] = None,
) -> Dict[str, Any]:
"""Search for live news using You.com's news API.
Args:
query: News search query
count: Maximum number of results
Returns:
Dict containing news results
"""
tools = YouTools()
return tools.live_news(query=query, count=count)
def ydc_images(
query: str,
) -> Dict[str, Any]:
"""Search for images using You.com's image search API.
Args:
query: Image search query
Returns:
Dict containing image results
"""
tools = YouTools()
return tools.images(query=query)
# Alias for simple usage
ydc = ydc_search
__all__ = ["YouTools", "ydc_search", "ydc_contents", "ydc_news", "ydc_images", "ydc"]
@@ -35,11 +35,6 @@ def motion_graphics_team(
- Researcher: Optional web search for content research
- CodeExplorer: Optional git repository exploration
- Animator: HTML/GSAP composition authoring and rendering
The team runs with ``process="hierarchical"``: the ``manager_llm``
orchestrates the worker agents at runtime rather than exposing a static
``leader`` reference. The coordinator is the semantic leader and is always
the first agent in ``team.agents``.
Args:
research: Include research specialist
@@ -51,12 +46,6 @@ def motion_graphics_team(
Returns:
AgentTeam configured for motion graphics creation
Note:
The team uses ``process="hierarchical"`` where the ``manager_llm``
orchestrates the worker agents at runtime. The coordinator is the
semantic leader and is always the first agent (``team.agents[0]``);
there is no static ``team.leader`` reference in this mode.
"""
if AgentTeam is None:
raise ImportError(
+2 -32
View File
@@ -1,6 +1,6 @@
[project]
name = "praisonai-tools"
version = "0.2.46"
version = "0.2.29"
description = "Extended tools for PraisonAI Agents"
authors = [
{name = "Mervin Praison"}
@@ -27,22 +27,11 @@ dependencies = [
[project.scripts]
praisonai-tools = "praisonai_tools.cli:main"
# Discovery contract for third-party tool packages. They register agent-callable
# tools under the ``praisonai.tools`` entry-point group so that
# ``pip install some-praisonai-tool`` makes them discoverable via
# ``praisonai_tools.list_tools()`` without editing core, e.g.:
#
# [project.entry-points."praisonai.tools"]
# my_tool = "my_pkg:MyTool"
[project.optional-dependencies]
dev = [
"pytest>=8.0.0",
"pytest-asyncio>=0.23.0",
"httpx>=0.27.0",
"playwright>=1.40",
"imageio-ffmpeg>=0.5",
]
wordpress = [
"praisonaiwp[ai]>=0.1.0",
@@ -65,15 +54,9 @@ agentfolio = [
n8n = [
"httpx>=0.27.0",
]
registry-proxy = [
"httpx>=0.24.0",
]
langextract = [
"langextract>=0.1.0",
]
swarmscore = [
"requests>=2.28.0",
]
video-motion = [
"playwright>=1.40",
"imageio-ffmpeg>=0.5",
@@ -81,13 +64,6 @@ video-motion = [
composio = [
"composio>=0.5.0",
]
meeting = [
"openai>=1.12.0",
"chromadb>=0.4.0",
]
stripe = [
"requests>=2.28.0",
]
[project.urls]
Homepage = "https://docs.praison.ai"
@@ -104,10 +80,4 @@ packages = ["praisonai_tools"]
[tool.pytest.ini_options]
testpaths = ["tests"]
asyncio_mode = "auto"
[tool.ruff.lint]
# Pin the rule set to the historical default (Pyflakes + a subset of
# pycodestyle) so an unpinned ruff upgrade does not spuriously fail CI by
# enabling thousands of new default rules across the pre-existing codebase.
select = ["E4", "E7", "E9", "F"]
asyncio_mode = "auto"
View File
Whitespace-only changes.
-55
View File
@@ -1,55 +0,0 @@
"""Compatibility shim for the reference docs generator.
The canonical implementation lives in
``praisonai_tools/docs_generator/generator.py``. This module re-exports the MDX
escaping / validation helpers so that test suites and tooling which import from
``scripts/generate_reference_docs.py`` resolve the same, single source of truth.
The generator module only depends on the Python standard library, so it is
loaded directly by file path. This avoids importing the top-level
``praisonai_tools`` package (which eagerly pulls in optional heavy
dependencies such as ``praisonaiagents``) and keeps this shim usable in a
lightweight docs/CI environment.
"""
from __future__ import annotations
import importlib.util
from pathlib import Path
_GENERATOR_PATH = (
Path(__file__).resolve().parent.parent
/ "praisonai_tools"
/ "docs_generator"
/ "generator.py"
)
_spec = importlib.util.spec_from_file_location(
"praisonai_tools_docs_generator", _GENERATOR_PATH
)
_generator = importlib.util.module_from_spec(_spec)
# Register before executing so dataclasses can resolve the module namespace.
import sys as _sys # noqa: E402
_sys.modules[_spec.name] = _generator
_spec.loader.exec_module(_generator)
ICON_MAP = _generator.ICON_MAP
VALID_MDX_TAGS = _generator.VALID_MDX_TAGS
escape_for_table = _generator.escape_for_table
escape_mdx = _generator.escape_mdx
sanitize_description = _generator.sanitize_description
sanitize_type_for_mdx = _generator.sanitize_type_for_mdx
validate_docs_json_structure = _generator.validate_docs_json_structure
validate_mdx = _generator.validate_mdx
__all__ = [
"ICON_MAP",
"VALID_MDX_TAGS",
"escape_for_table",
"escape_mdx",
"sanitize_description",
"sanitize_type_for_mdx",
"validate_docs_json_structure",
"validate_mdx",
]
+6 -14
View File
@@ -164,11 +164,8 @@ class TestMotionGraphicsTeam:
custom_param="test"
)
# Hierarchical teams forward process + manager_llm alongside
# any user-supplied kwargs, so assert individual entries.
assert team.kwargs["custom_param"] == "test"
assert team.kwargs["process"] == "hierarchical"
assert team.kwargs["manager_llm"] == "gpt-4"
# Check that custom parameters are passed through
assert team.kwargs == {"custom_param": "test"}
# Check that workspace is set
assert team._motion_graphics_workspace == Path(tmpdir)
@@ -212,20 +209,15 @@ class TestMotionGraphicsTeam:
@patch('praisonai_tools.video.motion_graphics.team.search_web', MockSearch())
@patch('praisonai_tools.video.motion_graphics.team.create_motion_graphics_agent')
def test_coordinator_is_leader(self, mock_create_agent):
"""Test that coordinator is the semantic leader (first agent).
In hierarchical process mode the manager LLM orchestrates workers,
so the coordinator is the first agent rather than a static
``team.leader`` reference.
"""
"""Test that coordinator is set as team leader."""
mock_animator = MockAgent(name="animator")
mock_create_agent.return_value = mock_animator
with tempfile.TemporaryDirectory() as tmpdir:
team = motion_graphics_team(workspace=tmpdir)
coordinator = team.agents[0]
assert coordinator.name == "coordinator"
assert team.leader is not None
assert team.leader.name == "coordinator"
@patch('praisonai_tools.video.motion_graphics.team.AgentTeam', MockAgentTeam)
@patch('praisonai_tools.video.motion_graphics.team.Agent', MockAgent)
@@ -286,7 +278,7 @@ class TestMotionGraphicsTeam:
with tempfile.TemporaryDirectory() as tmpdir:
team = motion_graphics_team(workspace=tmpdir)
coordinator = team.agents[0]
coordinator = team.leader
instructions = coordinator.instructions.lower()
assert "coordinator" in instructions
-79
View File
@@ -1,79 +0,0 @@
"""Tests for the tool discovery / catalogue contract."""
def test_list_tools_importable_from_top_level():
from praisonai_tools import list_tools, ToolCatalogueEntry, get_tool_names
assert callable(list_tools)
assert callable(get_tool_names)
assert ToolCatalogueEntry is not None
def test_list_tools_returns_entries():
from praisonai_tools import list_tools
from praisonai_tools.catalogue import ToolCatalogueEntry
entries = list_tools()
assert isinstance(entries, list)
assert len(entries) > 100 # ships a large catalogue
assert all(isinstance(e, ToolCatalogueEntry) for e in entries)
def test_entries_only_expose_tool_classes():
from praisonai_tools import list_tools
for entry in list_tools():
assert entry.name.endswith("Tool"), entry.name
def test_entries_are_sorted_and_unique():
from praisonai_tools import list_tools
names = [e.name for e in list_tools()]
assert names == sorted(names)
assert len(names) == len(set(names))
def test_catalogue_derived_from_tool_map_source_of_truth():
from praisonai_tools import list_tools
from praisonai_tools.tools import _TOOL_MAP
expected = {name for name in _TOOL_MAP if name.endswith("Tool")}
actual = {e.name for e in list_tools()}
# Every class in the map must be catalogued (third-party EPs may add more).
assert expected <= actual
def test_previously_missing_optional_tool_is_now_discoverable():
# QdrantTool was a valid tool absent from the wrapper's hand-maintained
# allowlist; it must now be discoverable via the catalogue.
from praisonai_tools import get_tool_names
names = get_tool_names()
assert "QdrantTool" in names
def test_extras_are_populated_for_optional_tools():
from praisonai_tools import list_tools
by_name = {e.name for e in list_tools()}
entries = {e.name: e for e in list_tools()}
assert "SwarmScoreTool" in by_name
assert "swarmscore" in entries["SwarmScoreTool"].extras
def test_entries_have_summary_and_module():
from praisonai_tools import list_tools
for entry in list_tools():
assert entry.module
assert entry.summary
def test_list_tools_does_not_require_optional_deps():
# Building the catalogue must not import any tool module / optional dep.
from praisonai_tools import list_tools
entries = list_tools()
assert entries # smoke: no ImportError raised
-109
View File
@@ -1,109 +0,0 @@
"""CI guard: the catalogue must never advertise a phantom tool.
A "phantom" is a tool name surfaced by ``get_tool_names()`` / ``list_tools()``
whose class cannot be resolved because no implementation file (or class) exists.
Because the catalogue is now source-derived (see ``praisonai_tools.catalogue``),
phantoms should be impossible by construction; this test enforces that during
any future refactor.
Missing *optional dependencies* are explicitly tolerated: a tool whose file and
class exist but which needs an un-installed extra will raise ``ImportError`` /
``ModuleNotFoundError`` for the extra, not an ``AttributeError``. Only the
latter (name resolves to nothing) counts as a phantom.
"""
import importlib
import praisonai_tools
from praisonai_tools import get_tool_names, list_tools
from praisonai_tools.catalogue import _scan_source_tree
def _is_missing_optional_dependency(exc: BaseException, tool_module: str) -> bool:
"""True if the import failure is due to a missing *optional* dependency.
A missing optional dependency raises ``ModuleNotFoundError`` for a module
that is *not* the tool's own module. If the tool's own file were missing the
name would simply not resolve (``AttributeError``) rather than importing and
then failing on a third-party import.
"""
if not isinstance(exc, ModuleNotFoundError):
return False
missing = getattr(exc, "name", "") or ""
# ``tool_module`` may be relative (flat ``*_tool.py`` under
# ``praisonai_tools.tools``) or already absolute (nested subpackages such as
# ``praisonai_tools.n8n.n8n_workflow``). Resolve to the tool's own dotted
# module either way so a *missing first-party* module is treated as a
# phantom, not an optional dependency.
own = (
tool_module
if tool_module.startswith("praisonai_tools.")
else f"praisonai_tools.tools.{tool_module}"
)
return missing != own and not own.startswith(f"{missing}.")
def test_every_catalogue_name_resolves_or_needs_optional_dep():
entries = {e.name: e for e in list_tools()}
phantoms = []
for name in sorted(get_tool_names()):
module = entries.get(name).module if name in entries else ""
try:
getattr(praisonai_tools, name)
except AttributeError as exc:
phantoms.append((name, module, repr(exc)))
except Exception as exc: # ImportError / ModuleNotFoundError, etc.
if not _is_missing_optional_dependency(exc, module):
phantoms.append((name, module, repr(exc)))
assert not phantoms, f"catalogue advertises unresolvable (phantom) tools: {phantoms}"
def test_no_phantom_modules_in_scan():
"""Every source-derived tool maps to a file that actually exists on disk."""
import os
tools_dir = os.path.join(os.path.dirname(praisonai_tools.__file__), "tools")
for name, (module, _summary) in _scan_source_tree().items():
path = os.path.join(tools_dir, f"{module}.py")
assert os.path.isfile(path), f"{name} maps to missing file {module}.py"
def test_dropping_a_tool_file_is_auto_discovered():
"""Files on disk defining a *Tool class are catalogued without _TOOL_MAP edits.
Guards the core promise of the issue: adding a tool is a single-file change.
``ClaudeMemoryTool``/``CrowPayTool``/``NightmarketTool`` exist on disk but
were historically absent from ``_TOOL_MAP``; they must still be discoverable.
"""
names = get_tool_names()
for expected in ("ClaudeMemoryTool", "CrowPayTool", "NightmarketTool"):
# Only assert for the ones whose files are present in this checkout.
derived = _scan_source_tree()
if expected in derived:
assert expected in names, f"{expected} exists on disk but is not catalogued"
def test_summaries_come_from_real_description():
entries = {e.name: e for e in list_tools()}
# CalculatorTool declares a literal description; the summary must match it,
# not the name-synthesised fallback ("Calculator integration tool").
calc = entries.get("CalculatorTool")
assert calc is not None
assert calc.summary == "Perform mathematical calculations."
assert "integration tool" not in calc.summary
def test_annotated_description_summaries_are_extracted():
"""Tools declaring ``description: str = "..."`` must surface the real text.
``CapsuleTool`` and ``NexusPredictionMarketTool`` use annotated assignments;
their catalogue summaries must come from the literal, not the name-based
fallback.
"""
entries = {e.name: e for e in list_tools()}
for name in ("CapsuleTool", "NexusPredictionMarketTool"):
entry = entries.get(name)
if entry is None:
continue
assert entry.summary
assert "integration tool" not in entry.summary
-305
View File
@@ -1,305 +0,0 @@
"""Tests for Inkog Security Analysis Tool."""
from unittest.mock import patch, MagicMock
from praisonai_tools.tools.inkog_tool import InkogTool, _check_inkog_available, scan_agent_code
class TestInkogTool:
"""Test suite for InkogTool."""
def test_init(self):
"""Test InkogTool initialization."""
# Test default initialization
tool = InkogTool()
assert tool.name == "inkog_security"
assert "security" in tool.description.lower()
# Test with custom parameters
tool = InkogTool(api_key="test_key", server_url="http://test.com")
assert tool._api_key == "test_key"
assert tool._server_url == "http://test.com"
@patch.dict("os.environ", {"INKOG_API_KEY": "test_env_key"})
def test_get_api_key(self):
"""Test API key retrieval."""
tool = InkogTool()
assert tool._get_api_key() == "test_env_key"
# Instance key takes precedence
tool = InkogTool(api_key="instance_key")
assert tool._get_api_key() == "instance_key"
@patch.dict("os.environ", {"INKOG_SERVER_URL": "http://env.com"})
def test_get_server_url(self):
"""Test server URL retrieval."""
tool = InkogTool()
assert tool._get_server_url() == "http://env.com"
# Instance URL takes precedence
tool = InkogTool(server_url="http://instance.com")
assert tool._get_server_url() == "http://instance.com"
def test_analyze_findings_empty(self):
"""Test analyze_findings with empty results."""
tool = InkogTool()
# Test with error
error_results = {"error": "test error"}
analysis = tool.analyze_findings(error_results)
assert "Scan failed" in analysis
assert "test error" in analysis
# Test with no findings
empty_results = {"summary": {"total_findings": 0}}
analysis = tool.analyze_findings(empty_results)
assert "No security vulnerabilities found" in analysis
def test_analyze_findings_with_data(self):
"""Test analyze_findings with security findings."""
tool = InkogTool()
results = {
"summary": {
"total_findings": 5,
"critical": 2,
"high": 2,
"medium": 1,
"low": 0
},
"server_findings": [
{"pattern": "Token Bombing"},
{"pattern": "Prompt Injection"},
{"pattern": "Recursive Tool Calling"}
]
}
analysis = tool.analyze_findings(results)
assert "Total Findings: 5" in analysis
assert "CRITICAL: 2 findings" in analysis
assert "HIGH: 2 findings" in analysis
assert "MEDIUM: 1 findings" in analysis
assert "Token Bombing" in analysis
assert "Immediate attention required" in analysis
def test_analyze_findings_string_input(self):
"""String (text/HTML) scan output is returned as-is, even when it
contains the word 'error' (regression: no TypeError)."""
tool = InkogTool()
text_output = "Finding: potential error in tool loop termination."
analysis = tool.analyze_findings(text_output)
assert analysis == text_output
class TestInkogAvailability:
"""Test inkog availability checking."""
@patch("subprocess.run")
def test_check_inkog_available_success(self, mock_run):
"""Test successful inkog availability check."""
# Mock successful version check
mock_run.return_value = MagicMock(returncode=0)
with patch.dict("os.environ", {"INKOG_API_KEY": "test_key"}):
is_available, error = _check_inkog_available()
assert is_available is True
assert error is None
@patch("subprocess.run")
def test_check_inkog_not_installed(self, mock_run):
"""Test inkog not installed."""
mock_run.side_effect = FileNotFoundError()
is_available, error = _check_inkog_available()
assert is_available is False
assert "not installed" in error.lower()
@patch("subprocess.run")
def test_check_inkog_no_api_key(self, mock_run):
"""Test inkog available but no API key."""
mock_run.return_value = MagicMock(returncode=0)
with patch.dict("os.environ", {}, clear=True):
is_available, error = _check_inkog_available()
assert is_available is False
assert "INKOG_API_KEY" in error
@patch("subprocess.run")
def test_check_inkog_available_with_instance_api_key(self, mock_run):
"""Instance-provided api_key satisfies the availability check."""
mock_run.return_value = MagicMock(returncode=0)
with patch.dict("os.environ", {}, clear=True):
is_available, error = _check_inkog_available(api_key="instance_key")
assert is_available is True
assert error is None
class TestInkogScanOperations:
"""Test inkog scan operations."""
@patch("praisonai_tools.tools.inkog_tool._check_inkog_available")
@patch("subprocess.run")
@patch.dict("os.environ", {"INKOG_API_KEY": "test_key"})
def test_scan_directory_json_success(self, mock_run, mock_check):
"""Test successful directory scan with JSON output."""
mock_check.return_value = (True, None)
mock_run.return_value = MagicMock(
returncode=0,
stdout='{"summary": {"total_findings": 0}}'
)
tool = InkogTool()
result = tool.scan_directory(path="./test", output_format="json")
assert isinstance(result, dict)
assert "summary" in result
assert result["summary"]["total_findings"] == 0
@patch("praisonai_tools.tools.inkog_tool._check_inkog_available")
@patch("subprocess.run")
@patch.dict("os.environ", {"INKOG_API_KEY": "test_key"})
def test_scan_directory_text_success(self, mock_run, mock_check):
"""Test successful directory scan with text output."""
mock_check.return_value = (True, None)
mock_run.return_value = MagicMock(
returncode=0,
stdout="No vulnerabilities found."
)
tool = InkogTool()
result = tool.scan_directory(path="./test", output_format="text")
assert isinstance(result, str)
assert "vulnerabilities" in result.lower()
@patch("praisonai_tools.tools.inkog_tool._check_inkog_available")
def test_scan_directory_not_available(self, mock_check):
"""Test scan when inkog is not available."""
mock_check.return_value = (False, "inkog not installed")
tool = InkogTool()
result = tool.scan_directory()
assert isinstance(result, dict)
assert "error" in result
assert "not installed" in result["error"]
@patch("praisonai_tools.tools.inkog_tool._check_inkog_available")
@patch("subprocess.run")
def test_scan_directory_command_failure(self, mock_run, mock_check):
"""Test scan when inkog command fails."""
mock_check.return_value = (True, None)
mock_run.return_value = MagicMock(
returncode=1,
stderr="Command failed",
stdout=""
)
tool = InkogTool()
result = tool.scan_directory()
assert isinstance(result, dict)
assert "error" in result
assert "failed" in result["error"].lower()
@patch("praisonai_tools.tools.inkog_tool._check_inkog_available")
@patch("subprocess.run")
@patch.dict("os.environ", {"INKOG_API_KEY": "test_key"})
def test_skill_scan_success(self, mock_run, mock_check):
"""Test successful skill package scan."""
mock_check.return_value = (True, None)
mock_run.return_value = MagicMock(
returncode=0,
stdout='{"scan_type": "skill", "findings": []}'
)
tool = InkogTool()
result = tool.skill_scan(path="./skill", deep=True)
assert isinstance(result, dict)
assert "scan_type" in result or "findings" in result
@patch("praisonai_tools.tools.inkog_tool._check_inkog_available")
@patch("subprocess.run")
@patch.dict("os.environ", {"INKOG_API_KEY": "test_key"})
def test_mcp_scan_success(self, mock_run, mock_check):
"""Test successful MCP server scan."""
mock_check.return_value = (True, None)
mock_run.return_value = MagicMock(
returncode=0,
stdout='{"mcp_server": "github", "vulnerabilities": []}'
)
tool = InkogTool()
result = tool.mcp_scan("github", deep=True)
assert isinstance(result, dict)
# Should have some scan results structure
def test_run_method_routing(self):
"""Test the run method routes to correct functions."""
tool = InkogTool()
with patch.object(tool, 'scan_directory') as mock_scan:
mock_scan.return_value = {"test": "result"}
tool.run(action="scan", path="./test")
mock_scan.assert_called_once_with(
path="./test",
output_format="json",
policy="balanced",
severity="low",
deep=False
)
with patch.object(tool, 'skill_scan') as mock_skill:
mock_skill.return_value = {"test": "result"}
tool.run(action="skill-scan", path="./test")
mock_skill.assert_called_once_with(
path="./test",
output_format="json",
deep=False,
repo=None
)
class TestStandaloneFunctions:
"""Test standalone function interfaces."""
@patch("praisonai_tools.tools.inkog_tool.InkogTool")
def test_scan_agent_code(self, mock_tool_class):
"""Test scan_agent_code standalone function."""
mock_tool = MagicMock()
mock_tool.scan_directory.return_value = {"result": "test"}
mock_tool_class.return_value = mock_tool
scan_agent_code("./test", deep=True)
mock_tool_class.assert_called_once()
mock_tool.scan_directory.assert_called_once_with(
path="./test",
output_format="json",
policy="balanced",
severity="low",
deep=True
)
if __name__ == "__main__":
# Run basic smoke test
print("Running Inkog Tool smoke tests...")
# Test basic initialization
tool = InkogTool()
print(f"✓ Tool name: {tool.name}")
print(f"✓ Tool description contains 'security': {'security' in tool.description.lower()}")
# Test availability check (will likely fail without actual installation)
is_available, error = _check_inkog_available()
if is_available:
print("✓ Inkog is available and configured")
else:
print(f"⚠ Inkog not available: {error}")
print("This is expected if inkog CLI is not installed")
print("Smoke tests completed!")
+48 -69
View File
@@ -1,15 +1,15 @@
"""Tests for LangExtract Tool."""
import os
import tempfile
import os
from unittest.mock import Mock, patch
from praisonai_tools.tools.langextract_tool import (
LangExtractTool,
_create_annotated_document,
_get_langextract,
langextract_extract,
langextract_render_file,
_get_langextract,
_create_annotated_document
)
@@ -96,19 +96,19 @@ class TestLangExtractTool:
mock_lx.io.save_annotated_documents = Mock()
mock_lx.visualize = Mock(return_value="<html>mock visualization</html>")
with patch('webbrowser.open') as mock_open, \
tempfile.TemporaryDirectory() as temp_dir:
output_path = os.path.join(temp_dir, "test.html")
result = self.tool.extract(
text="test text",
auto_open=True,
output_path=output_path
)
assert result["success"] is True
assert "auto_opened" in result
mock_open.assert_called_once()
with patch('webbrowser.open') as mock_open:
with tempfile.TemporaryDirectory() as temp_dir:
output_path = os.path.join(temp_dir, "test.html")
result = self.tool.extract(
text="test text",
auto_open=True,
output_path=output_path
)
assert result["success"] is True
assert "auto_opened" in result
mock_open.assert_called_once()
def test_render_file_missing_path(self):
"""Test render_file with missing file_path."""
@@ -144,17 +144,13 @@ class TestLangExtractTool:
temp_file_path = temp_file.name
try:
with tempfile.TemporaryDirectory() as temp_dir:
output_path = os.path.join(temp_dir, "render.html")
result = self.tool.render_file(
file_path=temp_file_path,
extractions=["important terms"],
output_path=output_path
)
assert result["success"] is True
assert result["text_length"] > 0
result = self.tool.render_file(
file_path=temp_file_path,
extractions=["important terms"]
)
assert result["success"] is True
assert result["text_length"] > 0
finally:
os.unlink(temp_file_path)
@@ -165,10 +161,10 @@ class TestHelperFunctions:
def test_get_langextract_not_installed(self):
"""Test _get_langextract when module not installed."""
with patch.dict('sys.modules', {'langextract': None}), \
patch('builtins.__import__', side_effect=ImportError):
result = _get_langextract()
assert result is None
with patch.dict('sys.modules', {'langextract': None}):
with patch('builtins.__import__', side_effect=ImportError):
result = _get_langextract()
assert result is None
@patch('praisonai_tools.tools.langextract_tool._get_langextract')
def test_create_annotated_document(self, mock_get_lx):
@@ -269,32 +265,19 @@ class TestIntegration:
key_terms = ["John Doe", "OpenAI Corporation", "January 1, 2024", "Net 30 days"]
with tempfile.TemporaryDirectory() as temp_dir:
output_path = os.path.join(temp_dir, "contract-001.html")
result = langextract_extract(
text=contract_text,
extractions=key_terms,
document_id="contract-001",
output_path=output_path,
auto_open=False
)
assert result["success"] is True
assert result["document_id"] == "contract-001"
assert result["extractions_count"] == len(key_terms)
@patch('praisonai_tools.tools.langextract_tool._get_langextract')
@patch('praisonai_tools.tools.langextract_tool._create_annotated_document')
def test_agent_usage_pattern(self, mock_create_doc, mock_get_lx):
"""Test typical agent usage pattern."""
# Mock langextract so the test runs without the optional dependency
mock_lx = Mock()
mock_get_lx.return_value = mock_lx
mock_create_doc.return_value = Mock()
mock_lx.io.save_annotated_documents = Mock()
mock_lx.visualize = Mock(return_value="<html>mock visualization</html>")
result = langextract_extract(
text=contract_text,
extractions=key_terms,
document_id="contract-001",
auto_open=False
)
assert result["success"] is True
assert result["document_id"] == "contract-001"
assert result["extractions_count"] == len(key_terms)
def test_agent_usage_pattern(self):
"""Test typical agent usage pattern."""
# This would be how an agent uses the tool
from praisonai_tools import langextract_extract
@@ -302,17 +285,13 @@ class TestIntegration:
analysis_text = "The quarterly report shows revenue of $1.2M and profit of $300K."
findings = ["$1.2M", "$300K", "quarterly report"]
with tempfile.TemporaryDirectory() as temp_dir:
output_path = os.path.join(temp_dir, "financial-analysis.html")
result = langextract_extract(
text=analysis_text,
extractions=findings,
document_id="financial-analysis",
output_path=output_path,
auto_open=False,
)
result = langextract_extract(
text=analysis_text,
extractions=findings,
document_id="financial-analysis",
auto_open=False,
)
assert result["success"] is True
assert result["document_id"] == "financial-analysis"
assert result["extractions_count"] == len(findings)
assert result["success"] is True
assert result["document_id"] == "financial-analysis"
assert result["extractions_count"] == len(findings)
+1 -1
View File
@@ -162,7 +162,7 @@ def test_trust_config_functions():
config = get_trust_config()
assert config.enabled is False
assert config.provider == "joy"
assert config.min_score == 1.5
assert config.min_score == 3.0
# Test with environment variables
old_provider = os.environ.get('PRAISONAI_TRUST_PROVIDER')
-244
View File
@@ -1,244 +0,0 @@
"""Tests for NEXUS Prediction Market Tool"""
import pytest
import json
import requests
from unittest.mock import Mock, patch
from praisonai_tools.tools.nexus_prediction_market_tool import (
NexusPredictionMarketTool,
nexus_prediction_market_tool
)
class TestNexusPredictionMarketTool:
"""Test cases for NEXUS Prediction Market Tool"""
def test_tool_initialization(self):
"""Test tool initialization with default and custom parameters."""
# Default initialization
tool = NexusPredictionMarketTool()
assert tool.name == "nexus_prediction_market"
assert tool.source_name == "praisonai-agent"
assert "X-NEXUS-Source" in tool.headers
assert tool.base_url == "https://nexus-agent-xa12.onrender.com"
# Custom initialization
custom_tool = NexusPredictionMarketTool(
source_name="test-bot",
api_key="test-key"
)
assert custom_tool.source_name == "test-bot"
assert custom_tool.headers["X-NEXUS-Source"] == "test-bot"
assert "Authorization" in custom_tool.headers
@patch('praisonai_tools.tools.nexus_prediction_market_tool.requests.get')
def test_get_market_data_success(self, mock_get):
"""Test successful market data retrieval."""
# Mock successful response
mock_response = Mock()
mock_response.status_code = 200
mock_response.json.return_value = {
"market": "Fed",
"price": 0.75,
"volume": 1000000,
"trend": "bullish"
}
mock_response.raise_for_status.return_value = None
mock_get.return_value = mock_response
tool = NexusPredictionMarketTool()
result = tool.get_market_data("Fed")
assert result["success"] is True
assert result["market"] == "Fed"
assert "data" in result
assert result["source"] == "nexus-free-api"
# Verify request was made correctly
mock_get.assert_called_once()
args, kwargs = mock_get.call_args
assert "kalshi" in args[0]
assert kwargs["params"]["market"] == "Fed"
assert "X-NEXUS-Source" in kwargs["headers"]
@patch('praisonai_tools.tools.nexus_prediction_market_tool.requests.get')
def test_get_market_data_failure(self, mock_get):
"""Test market data retrieval failure."""
# Mock failed response
mock_get.side_effect = requests.exceptions.ConnectionError("Network error")
tool = NexusPredictionMarketTool()
result = tool.get_market_data("Fed")
assert result["success"] is False
assert "error" in result
assert result["market"] == "Fed"
@patch('praisonai_tools.tools.nexus_prediction_market_tool.requests.get')
def test_check_arbitrage_opportunities_success(self, mock_get):
"""Test successful arbitrage checking."""
# Mock successful response
mock_response = Mock()
mock_response.status_code = 200
mock_response.json.return_value = {
"opportunities": [
{
"markets": ["Fed", "BTC"],
"profit_potential": 0.05,
"risk_level": "medium"
}
]
}
mock_response.raise_for_status.return_value = None
mock_get.return_value = mock_response
tool = NexusPredictionMarketTool()
result = tool.check_arbitrage_opportunities(["Fed", "BTC"])
assert result["success"] is True
assert result["markets"] == ["Fed", "BTC"]
assert "arbitrage_data" in result
assert result["source"] == "nexus-paid-api"
# Verify request was made correctly
mock_get.assert_called_once()
args, kwargs = mock_get.call_args
assert "arb/check" in args[0]
assert kwargs["params"]["markets"] == "Fed,BTC"
@patch('praisonai_tools.tools.nexus_prediction_market_tool.requests.get')
def test_check_arbitrage_payment_required(self, mock_get):
"""Test arbitrage checking when payment is required."""
# Mock payment required response
mock_response = Mock()
mock_response.status_code = 402
http_error = requests.exceptions.HTTPError("Payment Required")
http_error.response = mock_response
mock_get.side_effect = http_error
tool = NexusPredictionMarketTool()
result = tool.check_arbitrage_opportunities(["Fed", "BTC"])
assert result["success"] is False
assert "payment required" in result["error"].lower()
assert result["markets"] == ["Fed", "BTC"]
@patch('praisonai_tools.tools.nexus_prediction_market_tool.requests.get')
def test_get_agent_info_success(self, mock_get):
"""Test successful agent info retrieval."""
# Mock successful response
mock_response = Mock()
mock_response.status_code = 200
mock_response.json.return_value = {
"name": "NEXUS",
"description": "Prediction market data API",
"version": "1.0"
}
mock_response.raise_for_status.return_value = None
mock_get.return_value = mock_response
tool = NexusPredictionMarketTool()
result = tool.get_agent_info()
assert result["success"] is True
assert "agent_info" in result
assert result["source"] == "nexus-agent-metadata"
# Verify request was made correctly
mock_get.assert_called_once()
args, kwargs = mock_get.call_args
assert ".well-known/agent.json" in args[0]
def test_run_method_get_market_data(self):
"""Test run method with get_market_data action."""
tool = NexusPredictionMarketTool()
with patch.object(tool, 'get_market_data') as mock_method:
mock_method.return_value = {"success": True, "test": "data"}
result = tool.run("get_market_data", market="Fed")
result_data = json.loads(result)
assert result_data["success"] is True
mock_method.assert_called_once_with("Fed")
def test_run_method_check_arbitrage(self):
"""Test run method with check_arbitrage action."""
tool = NexusPredictionMarketTool()
with patch.object(tool, 'check_arbitrage_opportunities') as mock_method:
mock_method.return_value = {"success": True, "test": "data"}
result = tool.run("check_arbitrage", markets=["Fed", "BTC"])
result_data = json.loads(result)
assert result_data["success"] is True
mock_method.assert_called_once_with(["Fed", "BTC"])
def test_run_method_get_agent_info(self):
"""Test run method with get_agent_info action."""
tool = NexusPredictionMarketTool()
with patch.object(tool, 'get_agent_info') as mock_method:
mock_method.return_value = {"success": True, "test": "data"}
result = tool.run("get_agent_info")
result_data = json.loads(result)
assert result_data["success"] is True
mock_method.assert_called_once()
def test_run_method_invalid_action(self):
"""Test run method with invalid action."""
tool = NexusPredictionMarketTool()
result = tool.run("invalid_action")
result_data = json.loads(result)
assert result_data["success"] is False
assert "unknown action" in result_data["error"].lower()
def test_run_method_missing_parameters(self):
"""Test run method with missing required parameters."""
tool = NexusPredictionMarketTool()
# Missing market parameter
result = tool.run("get_market_data")
result_data = json.loads(result)
assert result_data["success"] is False
assert "market parameter required" in result_data["error"].lower()
# Missing markets parameter
result = tool.run("check_arbitrage")
result_data = json.loads(result)
assert result_data["success"] is False
assert "markets parameter" in result_data["error"].lower()
class TestNexusPredictionMarketFunction:
"""Test cases for the function-based interface"""
def test_function_interface(self):
"""Test the function-based interface."""
with patch('praisonai_tools.tools.nexus_prediction_market_tool.NexusPredictionMarketTool') as mock_class:
mock_instance = Mock()
mock_instance.run.return_value = '{"success": true}'
mock_class.return_value = mock_instance
result = nexus_prediction_market_tool(
action="get_market_data",
market="Fed",
source_name="test-source"
)
assert result == '{"success": true}'
mock_class.assert_called_once_with(source_name="test-source")
mock_instance.run.assert_called_once_with(
action="get_market_data",
market="Fed",
markets=None
)
if __name__ == "__main__":
pytest.main([__file__])
-901
View File
@@ -1,901 +0,0 @@
"""Unit tests for the tool-registry proxy connector."""
import os
import pytest
from unittest.mock import Mock, patch, MagicMock
@pytest.fixture(autouse=True)
def reset_session_spend():
"""Isolate cumulative-spend state between tests."""
from praisonai_tools.registry_proxy import registry_proxy as mod
mod._SESSION_SPEND.clear()
yield
mod._SESSION_SPEND.clear()
@pytest.fixture
def mock_httpx():
"""Mock httpx module with proper exception classes."""
mock_module = MagicMock()
mock_module.TimeoutException = type("TimeoutException", (Exception,), {})
class MockHTTPStatusError(Exception):
def __init__(self, message, request=None, response=None):
super().__init__(message)
self.request = request
self.response = response
mock_module.HTTPStatusError = MockHTTPStatusError
with patch.dict("sys.modules", {"httpx": mock_module}):
yield mock_module
class TestConfiguration:
def test_disabled_when_unconfigured(self):
from praisonai_tools.registry_proxy import RegistryProxyTool
with patch.dict(os.environ, {}, clear=True):
tool = RegistryProxyTool()
result = tool.search("backlinks for a domain")
assert "not configured" in result["error"]
def test_reads_env_vars(self):
from praisonai_tools.registry_proxy import RegistryProxyTool
with patch.dict(os.environ, {
"TOOL_PROXY_URL": "https://registry.example.com/",
"TOOL_PROXY_TOKEN": "secret-token",
}):
tool = RegistryProxyTool()
assert tool.proxy_url == "https://registry.example.com"
assert tool.token == "secret-token"
assert tool._headers()["Authorization"] == "Bearer secret-token"
def test_explicit_args_override_env(self):
from praisonai_tools.registry_proxy import RegistryProxyTool
tool = RegistryProxyTool(proxy_url="https://self.host/", token="tok")
assert tool.proxy_url == "https://self.host"
assert tool.token == "tok"
def test_env_token_not_leaked_to_supplied_url(self):
"""Security: an agent-supplied proxy_url must not receive the env token."""
from praisonai_tools.registry_proxy import RegistryProxyTool
with patch.dict(os.environ, {
"TOOL_PROXY_URL": "https://trusted.example.com",
"TOOL_PROXY_TOKEN": "secret-token",
}):
tool = RegistryProxyTool(proxy_url="https://attacker.example.com")
assert tool.proxy_url == "https://attacker.example.com"
assert tool.token is None
assert "Authorization" not in tool._headers()
def test_env_token_used_for_env_url(self):
from praisonai_tools.registry_proxy import RegistryProxyTool
with patch.dict(os.environ, {
"TOOL_PROXY_URL": "https://trusted.example.com",
"TOOL_PROXY_TOKEN": "secret-token",
}):
tool = RegistryProxyTool()
assert tool._headers()["Authorization"] == "Bearer secret-token"
class TestAuthHeader:
def test_auth_header_configurable(self):
"""Default sends Bearer; a custom header name sends the raw token."""
from praisonai_tools.registry_proxy import RegistryProxyTool
default = RegistryProxyTool(proxy_url="https://r.example.com", token="tok")
assert default._headers()["Authorization"] == "Bearer tok"
assert "X-Treg-Token" not in default._headers()
custom = RegistryProxyTool(
proxy_url="https://r.example.com", token="tok", auth_header="X-Treg-Token"
)
headers = custom._headers()
assert headers["X-Treg-Token"] == "tok"
assert "Authorization" not in headers
def test_auth_header_from_env(self):
from praisonai_tools.registry_proxy import RegistryProxyTool
with patch.dict(os.environ, {
"TOOL_PROXY_URL": "https://trusted.example.com",
"TOOL_PROXY_TOKEN": "secret-token",
"TOOL_PROXY_AUTH_HEADER": "X-Treg-Token",
}):
tool = RegistryProxyTool()
headers = tool._headers()
assert headers["X-Treg-Token"] == "secret-token"
assert "Authorization" not in headers
class TestSearch:
def test_search_success(self, mock_httpx):
from praisonai_tools.registry_proxy import RegistryProxyTool
response = Mock()
response.json.return_value = {"matches": [{"id": "seo.backlinks"}]}
response.raise_for_status.return_value = None
client = Mock()
client.get.return_value = response
mock_httpx.Client.return_value.__enter__.return_value = client
tool = RegistryProxyTool(proxy_url="https://r.example.com", token="t")
result = tool.search("backlinks for a domain")
assert result["matches"][0]["id"] == "seo.backlinks"
client.get.assert_called_once_with(
"https://r.example.com/catalog/search",
params={"q": "backlinks for a domain"},
headers={"Content-Type": "application/json", "Authorization": "Bearer t"},
)
def test_search_requires_query(self):
from praisonai_tools.registry_proxy import RegistryProxyTool
tool = RegistryProxyTool(proxy_url="https://r.example.com")
assert tool.search("")["error"] == "query is required"
class TestDescribe:
def test_describe_success(self, mock_httpx):
from praisonai_tools.registry_proxy import RegistryProxyTool
response = Mock()
response.json.return_value = {"id": "seo.backlinks", "price_per_call": 0.01}
response.raise_for_status.return_value = None
client = Mock()
client.get.return_value = response
mock_httpx.Client.return_value.__enter__.return_value = client
tool = RegistryProxyTool(proxy_url="https://r.example.com")
result = tool.describe("seo.backlinks")
assert result["price_per_call"] == 0.01
client.get.assert_called_once_with(
"https://r.example.com/catalog/endpoints/seo.backlinks",
headers={"Content-Type": "application/json"},
)
def test_describe_uses_endpoints_path(self, mock_httpx):
"""The real registry route is /catalog/endpoints/{id}, not /catalog/{id}."""
from praisonai_tools.registry_proxy import RegistryProxyTool
response = Mock()
response.json.return_value = {"id": "diffbot.people.enrich", "method": "GET"}
response.raise_for_status.return_value = None
client = Mock()
client.get.return_value = response
mock_httpx.Client.return_value.__enter__.return_value = client
tool = RegistryProxyTool(proxy_url="https://r.example.com", token="t")
tool.describe("diffbot.people.enrich")
client.get.assert_called_once_with(
"https://r.example.com/catalog/endpoints/diffbot.people.enrich",
headers={"Content-Type": "application/json", "Authorization": "Bearer t"},
)
def test_describe_path_configurable(self, mock_httpx):
from praisonai_tools.registry_proxy import RegistryProxyTool
response = Mock()
response.json.return_value = {"id": "seo.backlinks"}
response.raise_for_status.return_value = None
client = Mock()
client.get.return_value = response
mock_httpx.Client.return_value.__enter__.return_value = client
tool = RegistryProxyTool(
proxy_url="https://r.example.com",
describe_path="/catalog/{tool_id}",
)
tool.describe("seo.backlinks")
client.get.assert_called_once_with(
"https://r.example.com/catalog/seo.backlinks",
headers={"Content-Type": "application/json"},
)
def test_describe_path_from_env(self, mock_httpx):
from praisonai_tools.registry_proxy import RegistryProxyTool
response = Mock()
response.json.return_value = {"id": "seo.backlinks"}
response.raise_for_status.return_value = None
client = Mock()
client.get.return_value = response
mock_httpx.Client.return_value.__enter__.return_value = client
with patch.dict(os.environ, {
"TOOL_PROXY_URL": "https://r.example.com",
"TOOL_PROXY_DESCRIBE_PATH": "/v2/endpoints/{tool_id}",
}):
tool = RegistryProxyTool()
tool.describe("seo.backlinks")
client.get.assert_called_once_with(
"https://r.example.com/v2/endpoints/seo.backlinks",
headers={"Content-Type": "application/json"},
)
def test_describe_path_missing_placeholder_errors(self, mock_httpx):
"""A template lacking {tool_id} must return an error, not silently misroute."""
from praisonai_tools.registry_proxy import RegistryProxyTool
client = Mock()
mock_httpx.Client.return_value.__enter__.return_value = client
tool = RegistryProxyTool(
proxy_url="https://r.example.com",
describe_path="/catalog/static",
)
result = tool.describe("seo.backlinks")
assert "must contain '{tool_id}'" in result["error"]
client.get.assert_not_called()
def test_describe_path_malformed_template_errors(self, mock_httpx):
"""A malformed template must return an error instead of raising."""
from praisonai_tools.registry_proxy import RegistryProxyTool
client = Mock()
mock_httpx.Client.return_value.__enter__.return_value = client
tool = RegistryProxyTool(
proxy_url="https://r.example.com",
describe_path="/catalog/{tool_id}/{unknown}",
)
result = tool.describe("seo.backlinks")
assert "Invalid describe path template" in result["error"]
client.get.assert_not_called()
def test_describe_encodes_tool_id(self, mock_httpx):
"""A tool_id with path-changing characters is URL-encoded."""
from praisonai_tools.registry_proxy import RegistryProxyTool
response = Mock()
response.json.return_value = {"id": "x"}
response.raise_for_status.return_value = None
client = Mock()
client.get.return_value = response
mock_httpx.Client.return_value.__enter__.return_value = client
tool = RegistryProxyTool(proxy_url="https://r.example.com")
tool.describe("../admin?x=1")
client.get.assert_called_once_with(
"https://r.example.com/catalog/endpoints/..%2Fadmin%3Fx%3D1",
headers={"Content-Type": "application/json"},
)
class TestCall:
def test_call_success(self, mock_httpx):
"""Explicit method=POST skips describe and posts a JSON body."""
from praisonai_tools.registry_proxy import RegistryProxyTool
response = Mock()
response.json.return_value = {"data": {"backlinks": 42}}
response.raise_for_status.return_value = None
client = Mock()
client.request.return_value = response
mock_httpx.Client.return_value.__enter__.return_value = client
tool = RegistryProxyTool(proxy_url="https://r.example.com", token="t")
result = tool.call("seo.backlinks", {"domain": "example.com"}, method="POST")
assert result["data"]["backlinks"] == 42
client.request.assert_called_once_with(
"POST",
"https://r.example.com/call/seo.backlinks",
json={"domain": "example.com"},
headers={"Content-Type": "application/json", "Authorization": "Bearer t"},
)
client.get.assert_not_called()
def test_call_requires_tool_id(self):
from praisonai_tools.registry_proxy import RegistryProxyTool
tool = RegistryProxyTool(proxy_url="https://r.example.com")
assert tool.call("")["error"] == "tool_id is required"
def test_call_normalizes_explicit_method_whitespace(self, mock_httpx):
"""An explicit method with whitespace/casing is normalized (GET -> query)."""
from praisonai_tools.registry_proxy import RegistryProxyTool
response = Mock()
response.json.return_value = {"data": {"ok": True}}
response.raise_for_status.return_value = None
client = Mock()
client.get.return_value = response
mock_httpx.Client.return_value.__enter__.return_value = client
tool = RegistryProxyTool(proxy_url="https://r.example.com")
result = tool.call("t.id", {"q": "x"}, method=" get ")
assert result["data"]["ok"] is True
client.get.assert_called_once_with(
"https://r.example.com/call/t.id",
params={"q": "x"},
headers={"Content-Type": "application/json"},
)
client.request.assert_not_called()
def test_call_rejects_unsupported_method(self, mock_httpx):
"""An unsupported/mislabelled method is rejected before any request."""
from praisonai_tools.registry_proxy import RegistryProxyTool
client = Mock()
mock_httpx.Client.return_value.__enter__.return_value = client
tool = RegistryProxyTool(proxy_url="https://r.example.com")
result = tool.call("t.id", {}, method="TRACE")
assert "Unsupported HTTP method 'TRACE'" in result["error"]
client.get.assert_not_called()
client.request.assert_not_called()
def test_call_encodes_tool_id_in_url(self, mock_httpx):
"""A tool_id with path-changing characters is URL-encoded on /call."""
from praisonai_tools.registry_proxy import RegistryProxyTool
response = Mock()
response.json.return_value = {"data": "ok"}
response.raise_for_status.return_value = None
client = Mock()
client.request.return_value = response
mock_httpx.Client.return_value.__enter__.return_value = client
tool = RegistryProxyTool(proxy_url="https://r.example.com")
tool.call("../admin", {}, method="POST")
client.request.assert_called_once_with(
"POST",
"https://r.example.com/call/..%2Fadmin",
json={},
headers={"Content-Type": "application/json"},
)
def test_call_derives_post_method_from_describe(self, mock_httpx):
from praisonai_tools.registry_proxy import RegistryProxyTool
describe_resp = Mock()
describe_resp.json.return_value = {"id": "seo.backlinks", "method": "POST"}
describe_resp.raise_for_status.return_value = None
call_resp = Mock()
call_resp.json.return_value = {"data": {"backlinks": 42}}
call_resp.raise_for_status.return_value = None
client = Mock()
client.get.return_value = describe_resp
client.request.return_value = call_resp
mock_httpx.Client.return_value.__enter__.return_value = client
tool = RegistryProxyTool(proxy_url="https://r.example.com", token="t")
result = tool.call("seo.backlinks", {"domain": "example.com"})
assert result["data"]["backlinks"] == 42
client.request.assert_called_once_with(
"POST",
"https://r.example.com/call/seo.backlinks",
json={"domain": "example.com"},
headers={"Content-Type": "application/json", "Authorization": "Bearer t"},
)
def test_call_uses_declared_method(self, mock_httpx):
"""describe says GET -> GET with query params (no JSON body)."""
from praisonai_tools.registry_proxy import RegistryProxyTool
describe_resp = Mock()
describe_resp.json.return_value = {
"id": "diffbot.people.enrich", "method": "GET"
}
describe_resp.raise_for_status.return_value = None
call_resp = Mock()
call_resp.json.return_value = {"data": {"name": "Jane"}}
call_resp.raise_for_status.return_value = None
client = Mock()
client.get.side_effect = [describe_resp, call_resp]
mock_httpx.Client.return_value.__enter__.return_value = client
tool = RegistryProxyTool(proxy_url="https://r.example.com", token="t")
result = tool.call("diffbot.people.enrich", {"query": "type=email"})
assert result["data"]["name"] == "Jane"
client.request.assert_not_called()
# First get = describe, second get = the GET call with query params.
assert client.get.call_count == 2
call_args = client.get.call_args_list[1]
assert call_args.args[0] == "https://r.example.com/call/diffbot.people.enrich"
assert call_args.kwargs["params"] == {"query": "type=email"}
def test_call_explicit_get_skips_describe(self, mock_httpx):
from praisonai_tools.registry_proxy import RegistryProxyTool
call_resp = Mock()
call_resp.json.return_value = {"data": "ok"}
call_resp.raise_for_status.return_value = None
client = Mock()
client.get.return_value = call_resp
mock_httpx.Client.return_value.__enter__.return_value = client
tool = RegistryProxyTool(proxy_url="https://r.example.com", token="t")
result = tool.call("diffbot.people.enrich", {"q": "x"}, method="GET")
assert result["data"] == "ok"
client.get.assert_called_once_with(
"https://r.example.com/call/diffbot.people.enrich",
params={"q": "x"},
headers={"Content-Type": "application/json", "Authorization": "Bearer t"},
)
def test_call_defaults_to_post_when_method_absent(self, mock_httpx):
"""describe omits method -> default to POST with JSON body."""
from praisonai_tools.registry_proxy import RegistryProxyTool
describe_resp = Mock()
describe_resp.json.return_value = {"id": "seo.backlinks"}
describe_resp.raise_for_status.return_value = None
call_resp = Mock()
call_resp.json.return_value = {"data": "ok"}
call_resp.raise_for_status.return_value = None
client = Mock()
client.get.return_value = describe_resp
client.request.return_value = call_resp
mock_httpx.Client.return_value.__enter__.return_value = client
tool = RegistryProxyTool(proxy_url="https://r.example.com")
result = tool.call("seo.backlinks", {"domain": "x"})
assert result["data"] == "ok"
client.request.assert_called_once_with(
"POST",
"https://r.example.com/call/seo.backlinks",
json={"domain": "x"},
headers={"Content-Type": "application/json"},
)
def test_guarded_call_works_on_get_endpoint(self, mock_httpx):
"""Regression: spend guard + GET endpoint end-to-end (describe fetched once)."""
from praisonai_tools.registry_proxy import RegistryProxyTool
describe_resp = Mock()
describe_resp.json.return_value = {
"id": "diffbot.people.enrich", "method": "GET", "price_per_call": 0.05
}
describe_resp.raise_for_status.return_value = None
call_resp = Mock()
call_resp.json.return_value = {"data": "ok", "price_per_call": 0.05}
call_resp.raise_for_status.return_value = None
client = Mock()
client.get.side_effect = [describe_resp, call_resp]
mock_httpx.Client.return_value.__enter__.return_value = client
tool = RegistryProxyTool(
proxy_url="https://r.example.com", max_session_spend=1.0
)
result = tool.call("diffbot.people.enrich", {"query": "type=email"})
assert result["data"] == "ok"
assert tool._session_spend == pytest.approx(0.05)
client.request.assert_not_called()
# describe reused from the guard: exactly one describe + one GET call.
assert client.get.call_count == 2
assert client.get.call_args_list[1].kwargs["params"] == {"query": "type=email"}
# The live registry (v0.11.0) nests the endpoint fields under an ``endpoint``
# key and expresses cost as a structured object; fixtures mirror that shape so
# unit tests exercise the real wire schema, not a flattened approximation.
_LIVE_ENDPOINT_DOC = {
"endpoint": {
"id": "diffbot.people.enrich",
"method": "GET",
"cost": {
"type": "per_call",
"value": 25,
"currency": "credit",
"per": 1,
"usd": 0.0299,
},
},
"provider": {},
"siblings": [],
"call_template": "…",
"example_response": {},
"hints": [],
}
class TestExtractors:
def test_extract_method_nested_endpoint_envelope(self):
from praisonai_tools.registry_proxy import RegistryProxyTool
assert RegistryProxyTool._extract_method(
{"endpoint": {"method": "GET"}}
) == "GET"
# Flat form still works.
assert RegistryProxyTool._extract_method({"method": "post"}) == "POST"
# Absent -> None (default POST applies downstream).
assert RegistryProxyTool._extract_method({"endpoint": {}}) is None
assert RegistryProxyTool._extract_method({}) is None
def test_extract_price_structured_cost_usd(self):
from praisonai_tools.registry_proxy import RegistryProxyTool
# Nested endpoint.cost.usd is preferred (guard budgets are USD).
assert RegistryProxyTool._extract_price(_LIVE_ENDPOINT_DOC) == 0.0299
assert RegistryProxyTool._extract_price(
{"cost": {"usd": 0.0299, "value": 25}}
) == 0.0299
# Flat numeric forms unchanged.
assert RegistryProxyTool._extract_price({"price_per_call": 0.05}) == 0.05
assert RegistryProxyTool._extract_price({"price": 0.02}) == 0.02
assert RegistryProxyTool._extract_price({"cost": 0.03}) == 0.03
# Nested flat number under the envelope.
assert RegistryProxyTool._extract_price(
{"endpoint": {"price_per_call": 0.07}}
) == 0.07
# Non-numeric/absent -> None (fail-closed downstream).
assert RegistryProxyTool._extract_price({"cost": {"value": 25}}) is None
assert RegistryProxyTool._extract_price({}) is None
class TestLiveEnvelope:
def test_call_auto_derives_get_from_live_shape(self, mock_httpx):
"""The live nested envelope must yield an auto-derived GET (no method=)."""
from praisonai_tools.registry_proxy import RegistryProxyTool
describe_resp = Mock()
describe_resp.json.return_value = _LIVE_ENDPOINT_DOC
describe_resp.raise_for_status.return_value = None
call_resp = Mock()
call_resp.json.return_value = {"data": {"name": "Jane"}}
call_resp.raise_for_status.return_value = None
client = Mock()
client.get.side_effect = [describe_resp, call_resp]
mock_httpx.Client.return_value.__enter__.return_value = client
tool = RegistryProxyTool(proxy_url="https://r.example.com", token="t")
result = tool.call("diffbot.people.enrich", {"query": "type=email"})
assert result["data"]["name"] == "Jane"
client.request.assert_not_called()
assert client.get.call_count == 2
call_args = client.get.call_args_list[1]
assert call_args.args[0] == "https://r.example.com/call/diffbot.people.enrich"
assert call_args.kwargs["params"] == {"query": "type=email"}
def test_guard_quotes_real_price_from_live_shape(self, mock_httpx):
"""Guard must quote the structured cost's usd, not fail-closed."""
from praisonai_tools.registry_proxy import RegistryProxyTool
describe_resp = Mock()
describe_resp.json.return_value = _LIVE_ENDPOINT_DOC
describe_resp.raise_for_status.return_value = None
client = Mock()
client.get.return_value = describe_resp
mock_httpx.Client.return_value.__enter__.return_value = client
tool = RegistryProxyTool(
proxy_url="https://r.example.com", max_cost_per_call=0.01
)
result = tool.call("diffbot.people.enrich", {"query": "type=email"})
assert "exceeds max_cost_per_call" in result["error"]
assert "0.0299" in result["error"]
assert "cannot enforce" not in result["error"]
client.request.assert_not_called()
class TestErrorTaxonomy:
def test_auth_error(self, mock_httpx):
from praisonai_tools.registry_proxy import RegistryProxyTool
resp = Mock()
resp.status_code = 401
resp.text = "Unauthorized"
client = Mock()
client.get.side_effect = mock_httpx.HTTPStatusError("401", response=resp)
mock_httpx.Client.return_value.__enter__.return_value = client
tool = RegistryProxyTool(proxy_url="https://r.example.com", token="bad")
result = tool.search("x")
assert "Authentication failed" in result["error"]
def test_insufficient_balance_error(self, mock_httpx):
from praisonai_tools.registry_proxy import RegistryProxyTool
resp = Mock()
resp.status_code = 402
resp.text = "Payment Required"
client = Mock()
client.request.side_effect = mock_httpx.HTTPStatusError("402", response=resp)
mock_httpx.Client.return_value.__enter__.return_value = client
tool = RegistryProxyTool(proxy_url="https://r.example.com")
result = tool.call("seo.backlinks", {}, method="POST")
assert "Insufficient balance" in result["error"]
def test_upstream_4xx_passthrough(self, mock_httpx):
from praisonai_tools.registry_proxy import RegistryProxyTool
resp = Mock()
resp.status_code = 404
resp.text = "Not Found"
client = Mock()
client.request.side_effect = mock_httpx.HTTPStatusError("404", response=resp)
mock_httpx.Client.return_value.__enter__.return_value = client
tool = RegistryProxyTool(proxy_url="https://r.example.com")
result = tool.call("seo.backlinks", {}, method="POST")
assert "HTTP 404" in result["error"]
def test_timeout_error(self, mock_httpx):
from praisonai_tools.registry_proxy import RegistryProxyTool
client = Mock()
client.get.side_effect = mock_httpx.TimeoutException("timed out")
mock_httpx.Client.return_value.__enter__.return_value = client
tool = RegistryProxyTool(proxy_url="https://r.example.com", timeout=5.0)
result = tool.search("x")
assert "timed out after 5.0" in result["error"]
def test_missing_httpx(self):
from praisonai_tools.registry_proxy import RegistryProxyTool
tool = RegistryProxyTool(proxy_url="https://r.example.com")
with patch.dict("sys.modules", {"httpx": None}):
with patch("builtins.__import__", side_effect=ImportError("no httpx")):
result = tool.search("x")
assert "httpx not installed" in result["error"]
assert "praisonai-tools[registry-proxy]" in result["error"]
class TestSpendGuards:
def test_max_cost_per_call_denies(self, mock_httpx):
from praisonai_tools.registry_proxy import RegistryProxyTool
describe_resp = Mock()
describe_resp.json.return_value = {"id": "seo.backlinks", "price_per_call": 0.50}
describe_resp.raise_for_status.return_value = None
client = Mock()
client.get.return_value = describe_resp
mock_httpx.Client.return_value.__enter__.return_value = client
tool = RegistryProxyTool(proxy_url="https://r.example.com", max_cost_per_call=0.10)
result = tool.call("seo.backlinks", {})
assert "exceeds max_cost_per_call" in result["error"]
client.request.assert_not_called()
def test_max_session_spend_denies(self, mock_httpx):
from praisonai_tools.registry_proxy import RegistryProxyTool
describe_resp = Mock()
describe_resp.json.return_value = {"price_per_call": 0.60}
describe_resp.raise_for_status.return_value = None
client = Mock()
client.get.return_value = describe_resp
mock_httpx.Client.return_value.__enter__.return_value = client
tool = RegistryProxyTool(proxy_url="https://r.example.com", max_session_spend=1.0)
tool._session_spend = 0.50
result = tool.call("seo.backlinks", {})
assert "max_session_spend" in result["error"]
client.request.assert_not_called()
def test_within_budget_allows_and_tracks_spend(self, mock_httpx):
from praisonai_tools.registry_proxy import RegistryProxyTool
describe_resp = Mock()
describe_resp.json.return_value = {"price_per_call": 0.05}
describe_resp.raise_for_status.return_value = None
call_resp = Mock()
call_resp.json.return_value = {"data": "ok", "price_per_call": 0.05}
call_resp.raise_for_status.return_value = None
client = Mock()
client.get.return_value = describe_resp
client.request.return_value = call_resp
mock_httpx.Client.return_value.__enter__.return_value = client
tool = RegistryProxyTool(proxy_url="https://r.example.com", max_session_spend=1.0)
result = tool.call("seo.backlinks", {})
assert result["data"] == "ok"
assert tool._session_spend == pytest.approx(0.05)
@pytest.mark.parametrize("field", ["price_per_call", "price", "cost"])
def test_budget_check_accepts_price_and_cost_fields(self, mock_httpx, field):
"""Budget check tolerates price_per_call/price/cost, matching recording."""
from praisonai_tools.registry_proxy import RegistryProxyTool
describe_resp = Mock()
describe_resp.json.return_value = {"id": "seo.backlinks", field: 0.05}
describe_resp.raise_for_status.return_value = None
call_resp = Mock()
call_resp.json.return_value = {"data": "ok", field: 0.05}
call_resp.raise_for_status.return_value = None
client = Mock()
client.get.return_value = describe_resp
client.request.return_value = call_resp
mock_httpx.Client.return_value.__enter__.return_value = client
tool = RegistryProxyTool(proxy_url="https://r.example.com", max_session_spend=1.0)
result = tool.call("seo.backlinks", {})
assert result["data"] == "ok"
assert tool._session_spend == pytest.approx(0.05)
def test_missing_price_fails_closed(self, mock_httpx):
from praisonai_tools.registry_proxy import RegistryProxyTool
describe_resp = Mock()
describe_resp.json.return_value = {"id": "seo.backlinks"}
describe_resp.raise_for_status.return_value = None
client = Mock()
client.get.return_value = describe_resp
mock_httpx.Client.return_value.__enter__.return_value = client
tool = RegistryProxyTool(proxy_url="https://r.example.com", max_cost_per_call=0.10)
result = tool.call("seo.backlinks", {})
assert "cannot enforce" in result["error"]
client.request.assert_not_called()
@pytest.mark.parametrize("bad_price", ["NaN", "Infinity", "-Infinity", -0.01])
def test_non_finite_or_negative_price_fails_closed(self, mock_httpx, bad_price):
"""NaN/inf/negative prices must be rejected, not silently bypass the guard."""
from praisonai_tools.registry_proxy import RegistryProxyTool
describe_resp = Mock()
describe_resp.json.return_value = {"price_per_call": bad_price}
describe_resp.raise_for_status.return_value = None
client = Mock()
client.get.return_value = describe_resp
mock_httpx.Client.return_value.__enter__.return_value = client
tool = RegistryProxyTool(proxy_url="https://r.example.com", max_cost_per_call=0.10)
result = tool.call("seo.backlinks", {})
assert "cannot enforce" in result["error"]
client.request.assert_not_called()
def test_non_finite_response_charge_does_not_corrupt_spend(self, mock_httpx):
"""A NaN/inf charge in the call response must not poison cumulative spend."""
from praisonai_tools.registry_proxy import RegistryProxyTool
describe_resp = Mock()
describe_resp.json.return_value = {"price_per_call": 0.20}
describe_resp.raise_for_status.return_value = None
call_resp = Mock()
call_resp.json.return_value = {"data": "ok", "price_per_call": "NaN"}
call_resp.raise_for_status.return_value = None
client = Mock()
client.get.return_value = describe_resp
client.request.return_value = call_resp
mock_httpx.Client.return_value.__enter__.return_value = client
tool = RegistryProxyTool(proxy_url="https://r.example.com", max_session_spend=1.0)
result = tool.call("seo.backlinks", {})
assert result["data"] == "ok"
assert tool._session_spend == 0.20
def test_session_spend_persists_across_registry_call(self, mock_httpx):
"""max_session_spend must accumulate across separate registry_call calls."""
from praisonai_tools.registry_proxy import registry_call
describe_resp = Mock()
describe_resp.json.return_value = {"price_per_call": 0.60}
describe_resp.raise_for_status.return_value = None
call_resp = Mock()
call_resp.json.return_value = {"data": "ok", "price_per_call": 0.60}
call_resp.raise_for_status.return_value = None
client = Mock()
client.get.return_value = describe_resp
client.request.return_value = call_resp
mock_httpx.Client.return_value.__enter__.return_value = client
first = registry_call(
"seo.backlinks", {},
proxy_url="https://r.example.com", token="t",
max_session_spend=1.0,
)
assert first["data"] == "ok"
second = registry_call(
"seo.backlinks", {},
proxy_url="https://r.example.com", token="t",
max_session_spend=1.0,
)
assert "max_session_spend" in second["error"]
class TestDecoratedFunctions:
@patch("praisonai_tools.registry_proxy.registry_proxy.RegistryProxyTool")
def test_registry_search_function(self, mock_cls):
from praisonai_tools.registry_proxy import registry_search
instance = Mock()
instance.search.return_value = {"matches": []}
mock_cls.return_value = instance
registry_search("q", proxy_url="https://r", token="t")
mock_cls.assert_called_once_with(
proxy_url="https://r", token="t", auth_header=None
)
instance.search.assert_called_once_with("q")
@patch("praisonai_tools.registry_proxy.registry_proxy.RegistryProxyTool")
def test_registry_call_function_passes_guards(self, mock_cls):
from praisonai_tools.registry_proxy import registry_call
instance = Mock()
instance.call.return_value = {"data": "ok"}
mock_cls.return_value = instance
registry_call(
"seo.backlinks",
{"domain": "x"},
proxy_url="https://r",
token="t",
max_cost_per_call=0.1,
max_session_spend=1.0,
)
mock_cls.assert_called_once_with(
proxy_url="https://r",
token="t",
max_cost_per_call=0.1,
max_session_spend=1.0,
auth_header=None,
describe_path=None,
)
instance.call.assert_called_once_with("seo.backlinks", {"domain": "x"}, None)
@patch("praisonai_tools.registry_proxy.registry_proxy.RegistryProxyTool")
def test_registry_call_function_passes_method(self, mock_cls):
from praisonai_tools.registry_proxy import registry_call
instance = Mock()
instance.call.return_value = {"data": "ok"}
mock_cls.return_value = instance
registry_call(
"diffbot.people.enrich",
{"query": "type=email"},
proxy_url="https://r",
token="t",
method="GET",
)
instance.call.assert_called_once_with(
"diffbot.people.enrich", {"query": "type=email"}, "GET"
)
def test_smoke_import():
from praisonai_tools.registry_proxy import (
RegistryProxyTool,
registry_search,
registry_describe,
registry_call,
)
assert callable(registry_search)
assert callable(registry_describe)
assert callable(registry_call)
assert RegistryProxyTool().name == "registry_proxy"
@pytest.mark.integration
def test_live_smoke():
"""Gated live smoke test; skipped unless TOOL_PROXY_URL is configured."""
proxy_url = os.getenv("TOOL_PROXY_URL")
if not proxy_url:
pytest.skip("TOOL_PROXY_URL not set")
from praisonai_tools.registry_proxy import registry_search
result = registry_search("backlinks for a domain")
assert isinstance(result, dict)
assert "error" not in result
-25
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@@ -1,25 +0,0 @@
"""Tier 0: pin that registry-installed skills (./.claude/skills/) are discoverable.
Registries that expose ``skill install <name>`` install into ``./.claude/skills/``.
PraisonAI's skill discovery already scans that directory, so registry-installed
skills are discoverable with zero connector code. This test pins that contract.
"""
import os
import pytest
def test_claude_skills_dir_is_scanned(tmp_path, monkeypatch):
discovery = pytest.importorskip("praisonaiagents.skills.discovery")
skills_dir = tmp_path / ".claude" / "skills" / "my-registry-skill"
skills_dir.mkdir(parents=True)
monkeypatch.chdir(tmp_path)
dirs = discovery.get_default_skill_dirs()
claude_skills = tmp_path / ".claude" / "skills"
assert any(os.path.samefile(str(d), str(claude_skills)) for d in dirs), (
"PraisonAI must scan ./.claude/skills/ so registry-installed skills are "
"discoverable with zero connector code."
)
-451
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@@ -1,451 +0,0 @@
"""Tests for SwarmScore tool integration."""
import json
import pytest
import requests as real_requests
from urllib.parse import urlparse
from unittest.mock import Mock, patch
from praisonai_tools.tools.swarmscore_tool import (
SwarmScoreTool,
load_swarmscore_by_slug,
verify_swarmscore_freshness,
get_agent_discovery_manifest
)
from praisonai_tools.tools.base import ToolResult
class TestSwarmScoreTool:
"""Test cases for SwarmScoreTool class."""
def setup_method(self):
"""Set up test fixtures."""
self.tool = SwarmScoreTool()
self.sample_score_data = {
"score": 85,
"tier": "gold",
"jobs_completed": 150,
"success_rate": 94.5,
"verify_payload": {
"signature": "test_signature",
"timestamp": "2024-01-15T10:30:00Z",
"agent_id": "test-agent-123"
}
}
@patch('praisonai_tools.tools.swarmscore_tool.requests')
def test_load_swarmscore_success(self, mock_requests):
"""Test successful SwarmScore loading."""
# Setup mock response
mock_response = Mock()
mock_response.json.return_value = self.sample_score_data
mock_response.raise_for_status.return_value = None
mock_requests.get.return_value = mock_response
# Execute
result = self.tool.load_swarmscore("test-agent")
# Verify
assert result.success is True
assert result.output == self.sample_score_data
assert "test-agent" in result.metadata["message"]
mock_requests.get.assert_called_once()
@patch('praisonai_tools.tools.swarmscore_tool.requests')
def test_load_swarmscore_slug_url_encoded(self, mock_requests):
"""Slugs with special characters must be URL-encoded to avoid malformed paths."""
mock_response = Mock()
mock_response.json.return_value = self.sample_score_data
mock_response.raise_for_status.return_value = None
mock_requests.get.return_value = mock_response
result = self.tool.load_swarmscore("acme/agent one")
assert result.success is True
called_url = mock_requests.get.call_args[0][0]
assert called_url.endswith("/load-by-slug/acme%2Fagent%20one")
@patch('praisonai_tools.tools.swarmscore_tool.requests')
def test_load_swarmscore_network_error(self, mock_requests):
"""Test SwarmScore loading with network error."""
# Setup mock to raise exception
mock_requests.exceptions = real_requests.exceptions
mock_requests.get.side_effect = real_requests.exceptions.RequestException("Network error")
# Execute
result = self.tool.load_swarmscore("test-agent")
# Verify
assert result.success is False
assert "Network error" in result.error
@patch('praisonai_tools.tools.swarmscore_tool.requests')
def test_load_swarmscore_invalid_json(self, mock_requests):
"""Test SwarmScore loading with invalid JSON response."""
# Setup mock response with invalid JSON
mock_response = Mock()
mock_requests.exceptions = real_requests.exceptions
mock_response.json.side_effect = json.JSONDecodeError("Invalid JSON", "", 0)
mock_response.raise_for_status.return_value = None
mock_requests.get.return_value = mock_response
# Execute
result = self.tool.load_swarmscore("test-agent")
# Verify
assert result.success is False
assert "Invalid response format" in result.error
@patch('praisonai_tools.tools.swarmscore_tool.requests')
def test_verify_swarmscore_success(self, mock_requests):
"""Test successful SwarmScore verification."""
# Setup mock response
verify_data = {"verified": True, "timestamp": "2024-01-15T10:30:00Z"}
mock_response = Mock()
mock_response.json.return_value = verify_data
mock_response.raise_for_status.return_value = None
mock_requests.post.return_value = mock_response
# Execute
verify_payload = self.sample_score_data["verify_payload"]
result = self.tool.verify_swarmscore(verify_payload)
# Verify
assert result.success is True
assert result.output == verify_data
mock_requests.post.assert_called_once()
@patch('praisonai_tools.tools.swarmscore_tool.requests')
def test_verify_swarmscore_error(self, mock_requests):
"""Test SwarmScore verification with error."""
# Setup mock to raise exception
mock_requests.exceptions = real_requests.exceptions
mock_requests.post.side_effect = real_requests.exceptions.RequestException("Verification failed")
# Execute
result = self.tool.verify_swarmscore({"test": "payload"})
# Verify
assert result.success is False
assert "Verification failed" in result.error
@patch('praisonai_tools.tools.swarmscore_tool.requests')
def test_get_discovery_manifest_success(self, mock_requests):
"""Test successful discovery manifest retrieval."""
# Setup mock response
manifest_data = {
"agents": ["agent1", "agent2"],
"capabilities": ["trading", "analysis"],
"version": "1.0"
}
mock_response = Mock()
mock_response.json.return_value = manifest_data
mock_response.raise_for_status.return_value = None
mock_requests.get.return_value = mock_response
# Execute
result = self.tool.get_discovery_manifest()
# Verify
assert result.success is True
assert result.output == manifest_data
mock_requests.get.assert_called_once()
@patch('praisonai_tools.tools.swarmscore_tool.requests')
def test_get_discovery_manifest_url_derivation(self, mock_requests):
"""Discovery manifest URL must resolve to the domain root regardless of version prefix."""
mock_response = Mock()
mock_response.json.return_value = {"agents": []}
mock_response.raise_for_status.return_value = None
mock_requests.get.return_value = mock_response
for base_url in [
"https://api.swarmsync.ai/v1/swarmscore/",
"https://api.swarmsync.ai/v2/swarmscore/",
"https://staging.swarmsync.ai/api/swarmscore/",
"https://api.swarmsync.ai/swarmscore",
]:
mock_requests.get.reset_mock()
tool = SwarmScoreTool(api_base_url=base_url)
result = tool.get_discovery_manifest()
assert result.success is True
called_url = mock_requests.get.call_args[0][0]
expected_root = f"{urlparse(base_url).scheme}://{urlparse(base_url).netloc}"
assert called_url == f"{expected_root}/.well-known/agent-card.json"
@patch('praisonai_tools.tools.swarmscore_tool.requests')
def test_get_discovery_manifest_error(self, mock_requests):
"""Test discovery manifest retrieval with error."""
# Setup mock to raise exception
mock_requests.exceptions = real_requests.exceptions
mock_requests.get.side_effect = real_requests.exceptions.RequestException("Manifest error")
# Execute
result = self.tool.get_discovery_manifest()
# Verify
assert result.success is False
assert "Manifest error" in result.error
def test_run_load_action(self):
"""Test run method with load action."""
with patch.object(self.tool, 'load_swarmscore') as mock_load:
mock_load.return_value = ToolResult(output=self.sample_score_data, success=True)
result = self.tool.run("load", slug="test-agent")
assert result.success is True
mock_load.assert_called_once_with("test-agent")
def test_run_verify_action(self):
"""Test run method with verify action."""
with patch.object(self.tool, 'verify_swarmscore') as mock_verify:
mock_verify.return_value = ToolResult(output={"verified": True}, success=True)
verify_payload = {"test": "payload"}
result = self.tool.run("verify", verify_payload=verify_payload)
assert result.success is True
mock_verify.assert_called_once_with(verify_payload)
def test_run_discover_action(self):
"""Test run method with discover action."""
with patch.object(self.tool, 'get_discovery_manifest') as mock_discover:
mock_discover.return_value = ToolResult(output={"agents": []}, success=True)
result = self.tool.run("discover")
assert result.success is True
mock_discover.assert_called_once()
def test_run_default_action(self):
"""Bare run() defaults to 'load' and degrades gracefully without a slug."""
result = self.tool.run()
assert result.success is False
assert "Missing required parameter 'slug'" in result.error
def test_run_invalid_action(self):
"""Test run method with invalid action."""
result = self.tool.run("invalid_action")
assert result.success is False
assert "Unknown action" in result.error
def test_run_missing_parameters(self):
"""Test run method with missing required parameters."""
# Test load without slug
result = self.tool.run("load")
assert result.success is False
assert "Missing required parameter 'slug'" in result.error
# Test verify without verify_payload
result = self.tool.run("verify")
assert result.success is False
assert "Missing required parameter 'verify_payload'" in result.error
class TestStandaloneFunctions:
"""Test cases for standalone utility functions."""
def setup_method(self):
"""Set up test fixtures."""
self.sample_data = {
"score": 75,
"tier": "silver",
"verify_payload": {"test": "payload"}
}
@patch('praisonai_tools.tools.swarmscore_tool.SwarmScoreTool')
def test_load_swarmscore_by_slug_success(self, mock_tool_class):
"""Test successful standalone load function."""
# Setup mock
mock_tool = Mock()
mock_tool.load_swarmscore.return_value = ToolResult(
output=self.sample_data,
success=True
)
mock_tool_class.return_value = mock_tool
# Execute
result = load_swarmscore_by_slug("test-agent")
# Verify
assert result == self.sample_data
mock_tool.load_swarmscore.assert_called_once_with("test-agent")
@patch('praisonai_tools.tools.swarmscore_tool.SwarmScoreTool')
def test_load_swarmscore_by_slug_failure(self, mock_tool_class):
"""Test standalone load function with failure."""
# Setup mock
mock_tool = Mock()
mock_tool.load_swarmscore.return_value = ToolResult(
output=None,
success=False,
error="Load failed"
)
mock_tool_class.return_value = mock_tool
# Execute and verify exception
with pytest.raises(Exception, match="Load failed"):
load_swarmscore_by_slug("test-agent")
@patch('praisonai_tools.tools.swarmscore_tool.SwarmScoreTool')
def test_verify_swarmscore_freshness_success(self, mock_tool_class):
"""Test successful standalone verify function."""
# Setup mock
verify_data = {"verified": True}
mock_tool = Mock()
mock_tool.verify_swarmscore.return_value = ToolResult(
output=verify_data,
success=True
)
mock_tool_class.return_value = mock_tool
# Execute
payload = {"test": "payload"}
result = verify_swarmscore_freshness(payload)
# Verify
assert result == verify_data
mock_tool.verify_swarmscore.assert_called_once_with(payload)
@patch('praisonai_tools.tools.swarmscore_tool.SwarmScoreTool')
def test_verify_swarmscore_freshness_failure(self, mock_tool_class):
"""Test standalone verify function with failure."""
# Setup mock
mock_tool = Mock()
mock_tool.verify_swarmscore.return_value = ToolResult(
output=None,
success=False,
error="Verification failed"
)
mock_tool_class.return_value = mock_tool
# Execute and verify exception
with pytest.raises(Exception, match="Verification failed"):
verify_swarmscore_freshness({"test": "payload"})
@patch('praisonai_tools.tools.swarmscore_tool.SwarmScoreTool')
def test_get_agent_discovery_manifest_success(self, mock_tool_class):
"""Test successful standalone discovery function."""
# Setup mock
manifest_data = {"agents": ["test1", "test2"]}
mock_tool = Mock()
mock_tool.get_discovery_manifest.return_value = ToolResult(
output=manifest_data,
success=True
)
mock_tool_class.return_value = mock_tool
# Execute
result = get_agent_discovery_manifest()
# Verify
assert result == manifest_data
mock_tool.get_discovery_manifest.assert_called_once()
@patch('praisonai_tools.tools.swarmscore_tool.SwarmScoreTool')
def test_get_agent_discovery_manifest_failure(self, mock_tool_class):
"""Test standalone discovery function with failure."""
# Setup mock
mock_tool = Mock()
mock_tool.get_discovery_manifest.return_value = ToolResult(
output=None,
success=False,
error="Discovery failed"
)
mock_tool_class.return_value = mock_tool
# Execute and verify exception
with pytest.raises(Exception, match="Discovery failed"):
get_agent_discovery_manifest()
class TestToolInitialization:
"""Test tool initialization and dependencies."""
def test_tool_initialization_default(self):
"""Test tool initialization with default parameters."""
tool = SwarmScoreTool()
assert "api.swarmsync.ai" in tool.api_base_url
assert not tool.api_base_url.endswith('/')
def test_tool_initialization_custom_url(self):
"""Test tool initialization with custom URL."""
custom_url = "https://custom.api.com/v1/swarmscore/"
tool = SwarmScoreTool(api_base_url=custom_url)
assert tool.api_base_url == "https://custom.api.com/v1/swarmscore"
@patch('praisonai_tools.tools.swarmscore_tool.requests', None)
def test_tool_initialization_missing_requests(self):
"""Test tool initialization without requests library."""
with pytest.raises(ImportError, match="requests is required"):
SwarmScoreTool()
class TestIntegrationScenarios:
"""Test realistic integration scenarios."""
@patch('praisonai_tools.tools.swarmscore_tool.requests')
def test_full_workflow_success(self, mock_requests):
"""Test complete workflow: load -> verify -> discover."""
tool = SwarmScoreTool()
# Setup mock responses
load_data = {
"score": 90,
"tier": "platinum",
"verify_payload": {"signature": "test123"}
}
verify_data = {"verified": True}
manifest_data = {"agents": ["agent1"]}
mock_responses = [
Mock(json=lambda: load_data, raise_for_status=lambda: None),
Mock(json=lambda: verify_data, raise_for_status=lambda: None),
Mock(json=lambda: manifest_data, raise_for_status=lambda: None)
]
# Configure mock to return different responses for different calls
mock_requests.exceptions = real_requests.exceptions
mock_requests.get.side_effect = [mock_responses[0], mock_responses[2]]
mock_requests.post.return_value = mock_responses[1]
# Execute workflow
load_result = tool.load_swarmscore("test-agent")
assert load_result.success is True
assert load_result.output["score"] == 90
verify_result = tool.verify_swarmscore(load_data["verify_payload"])
assert verify_result.success is True
assert verify_result.output["verified"] is True
manifest_result = tool.get_discovery_manifest()
assert manifest_result.success is True
assert "agent1" in manifest_result.output["agents"]
@patch('praisonai_tools.tools.swarmscore_tool.requests')
def test_error_recovery(self, mock_requests):
"""Test graceful error handling and recovery."""
tool = SwarmScoreTool()
# First call fails, second succeeds
mock_requests.exceptions = real_requests.exceptions
mock_requests.get.side_effect = [
real_requests.exceptions.RequestException("Network timeout"),
Mock(
json=lambda: {"score": 80},
raise_for_status=lambda: None
)
]
# First attempt fails
result1 = tool.load_swarmscore("test-agent")
assert result1.success is False
assert "Network timeout" in result1.error
# Second attempt succeeds
result2 = tool.load_swarmscore("test-agent")
assert result2.success is True
assert result2.output["score"] == 80
-185
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@@ -1,185 +0,0 @@
"""Regression tests for automatic tool discovery.
These guard the "shipped but not importable" gap: every public tool symbol that
ships under ``praisonai_tools/tools/`` must be reachable through both public
import surfaces, and adding a new tool module must require no other edits.
"""
import ast
import importlib
import os
import pytest
import praisonai_tools
from praisonai_tools import tools as tools_pkg
from praisonai_tools.tools._discovery import (
build_manifest,
_iter_public_symbols,
_SKIP_MODULES,
)
TOOLS_DIR = os.path.dirname(tools_pkg.__file__)
def _public_symbols(path):
with open(path, "r", encoding="utf-8") as fh:
source = fh.read()
return _iter_public_symbols(source, os.path.basename(path)[:-3])
def _tool_modules():
for filename in sorted(os.listdir(TOOLS_DIR)):
module_name = filename[:-3]
if (
filename.endswith(".py")
and module_name not in _SKIP_MODULES
and not module_name.startswith("_")
):
yield module_name
def test_no_discovery_collisions():
_, collisions = build_manifest(TOOLS_DIR)
assert collisions == {}, f"Colliding tool symbols across modules: {collisions}"
def test_every_shipped_module_parses():
"""Every shipped tool module must parse.
Discovery deliberately swallows a per-module ``SyntaxError`` (logging a
warning) so one broken module cannot break the whole package import. The
downside is that a broken module silently drops out of the manifest and its
tools resolve as ``AttributeError`` rather than surfacing the real parse
error. This test closes that gap loudly at CI time: it parses each module
directly (not via the swallowing discovery helper) so a genuinely broken
shipped module fails here with the pointing ``SyntaxError``.
"""
for module in _tool_modules():
path = os.path.join(TOOLS_DIR, module + ".py")
with open(path, "r", encoding="utf-8") as fh:
source = fh.read()
try:
ast.parse(source)
except SyntaxError as exc: # pragma: no cover - fails only if a module breaks
pytest.fail(f"tools/{module}.py has a syntax error: {exc}")
def test_manifest_covers_every_shipped_symbol():
manifest, _ = build_manifest(TOOLS_DIR)
for module in _tool_modules():
path = os.path.join(TOOLS_DIR, module + ".py")
for symbol in _public_symbols(path):
assert symbol in manifest, (
f"{symbol!r} defined in tools/{module}.py is not discoverable"
)
def test_all_matches_manifest():
manifest, _ = build_manifest(TOOLS_DIR)
base = {
"BaseTool", "ToolResult", "ToolValidationError", "validate_tool",
"tool", "FunctionTool", "is_tool", "get_tool_schema",
}
expected = base | set(manifest)
assert set(tools_pkg.__all__) == expected
# The top-level package mirrors the tools package surface and additionally
# exposes the catalogue/discovery helpers (which are not tool symbols).
catalogue_exports = {"ToolCatalogueEntry", "list_tools", "get_tool_names"}
assert set(praisonai_tools.__all__) == set(tools_pkg.__all__) | catalogue_exports
@pytest.mark.parametrize("name", [
"EmailTool", "SlackTool", "GitHubTool", "WeatherTool", "YouTubeTool",
"send_email", "get_weather", "search_youtube",
# Symbol from a module that declares an explicit __all__ (author intent).
"NexusPredictionMarketTool",
# External symbol living outside tools/ (exercises the absolute-path
# import branch in __getattr__ and the _EXTERNAL_SYMBOLS mapping).
"N8nWorkflowTool",
])
def test_known_symbols_resolve_both_surfaces(name):
assert getattr(tools_pkg, name) is getattr(praisonai_tools, name)
def test_explicit_all_is_respected():
"""A module declaring __all__ contributes exactly those public names."""
manifest, _ = build_manifest(TOOLS_DIR)
# nexus_prediction_market_tool.py declares __all__ with these two names.
assert manifest.get("NexusPredictionMarketTool") == "nexus_prediction_market_tool"
assert manifest.get("nexus_prediction_market_tool") == "nexus_prediction_market_tool"
def test_lazy_import_not_eager(monkeypatch):
"""Importing the package must not eagerly import a heavy tool module."""
import sys
# A representative heavy/optional tool module should not be imported until
# one of its symbols is accessed.
target = "praisonai_tools.tools.docker_tool"
sys.modules.pop(target, None)
importlib.reload(tools_pkg)
assert target not in sys.modules
# Accessing a symbol triggers the lazy import.
_ = tools_pkg.DockerTool
assert target in sys.modules
def test_drop_in_new_tool(tmp_path, monkeypatch):
"""A new module dropped into tools/ is importable with no other edits."""
if not os.access(TOOLS_DIR, os.W_OK):
pytest.skip("TOOLS_DIR is not writable (read-only install)")
echo_path = os.path.join(TOOLS_DIR, "echo_discovery_probe.py")
source = (
"from praisonai_tools.tools.decorator import tool\n\n\n"
"@tool\n"
"def echo_discovery_probe(text: str) -> str:\n"
" '''Echo the given text.'''\n"
" return text\n"
)
with open(echo_path, "w", encoding="utf-8") as fh:
fh.write(source)
try:
importlib.reload(tools_pkg)
fn = tools_pkg.echo_discovery_probe
assert fn("hi") == "hi"
assert "echo_discovery_probe" in tools_pkg.__all__
finally:
os.remove(echo_path)
importlib.reload(tools_pkg)
def test_manifest_cache_roundtrip(tmp_path):
"""The disk cache is written, reused, and invalidated on directory change."""
from praisonai_tools.tools import _discovery
pkg = tmp_path / "toolsdir"
pkg.mkdir()
(pkg / "sample_tool.py").write_text("class SampleTool:\n pass\n")
manifest, _ = _discovery.build_manifest(str(pkg))
assert manifest.get("SampleTool") == "sample_tool"
cache_file = pkg / _discovery._CACHE_FILENAME
assert cache_file.exists(), "cache should be written after first scan"
# Second call must serve from cache (fingerprint unchanged) and match.
manifest2, _ = _discovery.build_manifest(str(pkg))
assert manifest2 == manifest
# Adding a module changes the fingerprint -> cache is rebuilt automatically.
(pkg / "second_tool.py").write_text("def second_tool():\n return 1\n")
manifest3, _ = _discovery.build_manifest(str(pkg))
assert "second_tool" in manifest3
def test_manifest_cache_corrupt_falls_back(tmp_path):
"""A corrupt cache file must not break discovery."""
from praisonai_tools.tools import _discovery
pkg = tmp_path / "toolsdir"
pkg.mkdir()
(pkg / "sample_tool.py").write_text("class SampleTool:\n pass\n")
(pkg / _discovery._CACHE_FILENAME).write_text("{ not valid json")
manifest, _ = _discovery.build_manifest(str(pkg))
assert manifest.get("SampleTool") == "sample_tool"
-279
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@@ -1,279 +0,0 @@
"""Unit tests for FirefliesTool."""
import os
from unittest.mock import MagicMock, patch
from praisonai_tools.tools.fireflies_tool import (
FirefliesTool,
list_fireflies_meetings,
DEFAULT_API_URL,
)
def _mock_response(payload, status_code=200, headers=None):
resp = MagicMock()
resp.json.return_value = payload
resp.status_code = status_code
resp.headers = headers or {}
return resp
# ── Configuration ───────────────────────────────────────────────────
class TestConfiguration:
def test_api_key_from_arg(self):
tool = FirefliesTool(api_key="ff_xyz")
assert tool.api_key == "ff_xyz"
def test_api_key_from_env(self):
with patch.dict(os.environ, {"FIREFLIES_API_KEY": "envkey"}, clear=True):
tool = FirefliesTool()
assert tool.api_key == "envkey"
def test_default_api_url(self):
with patch.dict(os.environ, {}, clear=True):
tool = FirefliesTool(api_key="x")
assert tool.api_url == DEFAULT_API_URL
def test_api_url_override_from_env(self):
with patch.dict(
os.environ, {"FIREFLIES_API_URL": "https://proxy.local/graphql"}, clear=True
):
tool = FirefliesTool(api_key="x")
assert tool.api_url == "https://proxy.local/graphql"
# ── _graphql wiring ─────────────────────────────────────────────────
class TestGraphQL:
def test_missing_key_returns_distinct_error(self):
with patch.dict(os.environ, {}, clear=True):
tool = FirefliesTool()
assert tool._graphql("query { x }") == {"error": "FIREFLIES_API_KEY required"}
def test_sends_bearer_header(self):
tool = FirefliesTool(api_key="ff_xyz")
with patch("requests.post") as post:
post.return_value = _mock_response({"data": {"ok": True}})
tool._graphql("query { x }", {"v": 1})
kwargs = post.call_args.kwargs
assert kwargs["headers"]["Authorization"] == "Bearer ff_xyz"
assert kwargs["json"] == {"query": "query { x }", "variables": {"v": 1}}
def test_maps_401_to_auth_error(self):
tool = FirefliesTool(api_key="bad")
with patch("requests.post", return_value=_mock_response({}, status_code=401)):
result = tool._graphql("query { x }")
assert result["status_code"] == 401
assert "authentication failed" in result["error"]
def test_maps_403_to_auth_error(self):
tool = FirefliesTool(api_key="bad")
with patch("requests.post", return_value=_mock_response({}, status_code=403)):
result = tool._graphql("query { x }")
assert result["status_code"] == 403
def test_rate_limit_surfaces_retry_after(self):
tool = FirefliesTool(api_key="x")
resp = _mock_response({}, status_code=429, headers={"Retry-After": "12"})
with patch("requests.post", return_value=resp):
result = tool._graphql("query { x }")
assert result["status_code"] == 429
assert result["retry_after"] == "12"
def test_graphql_errors_are_flattened(self):
tool = FirefliesTool(api_key="x")
payload = {"errors": [{"message": "boom"}, {"message": "bad"}]}
with patch("requests.post", return_value=_mock_response(payload)):
assert tool._graphql("query { x }") == {"error": "boom; bad"}
def test_handles_request_exception(self):
tool = FirefliesTool(api_key="x")
with patch("requests.post", side_effect=RuntimeError("net")):
assert tool._graphql("q") == {"error": "net"}
def test_rejects_non_https_url(self):
tool = FirefliesTool(api_key="x", api_url="http://insecure.local/graphql")
with patch("requests.post") as post:
result = tool._graphql("query { x }")
post.assert_not_called()
assert result == {"error": "FIREFLIES_API_URL must use HTTPS"}
def test_rate_limit_from_graphql_payload(self):
tool = FirefliesTool(api_key="x")
payload = {
"errors": [{"extensions": {"metadata": {"retryAfter": 30}}}]
}
resp = _mock_response(payload, status_code=429)
with patch("requests.post", return_value=resp):
result = tool._graphql("query { x }")
assert result["status_code"] == 429
assert result["retry_after"] == "30"
def test_generic_http_error_surfaces_status(self):
tool = FirefliesTool(api_key="x")
resp = _mock_response({"data": {"transcripts": None}}, status_code=500)
with patch("requests.post", return_value=resp):
result = tool._graphql("query { x }")
assert result["status_code"] == 500
assert "HTTP 500" in result["error"]
# ── list_recent_meetings ────────────────────────────────────────────
class TestListRecentMeetings:
def test_returns_normalised_meetings(self):
tool = FirefliesTool(api_key="x")
payload = {
"data": {
"transcripts": [
{
"id": "m1",
"title": "Standup",
"date": "2026-01-01",
"duration": 15,
"organizer_email": "[email protected]",
}
]
}
}
with patch("requests.post", return_value=_mock_response(payload)):
meetings = tool.list_recent_meetings(limit=5)
assert len(meetings) == 1
assert meetings[0]["title"] == "Standup"
assert meetings[0]["organizer_email"] == "[email protected]"
def test_after_cursor_maps_to_skip(self):
tool = FirefliesTool(api_key="x")
with patch(
"requests.post", return_value=_mock_response({"data": {"transcripts": []}})
) as post:
tool.list_recent_meetings(limit=5, after="10")
sent = post.call_args.kwargs["json"]["variables"]
assert sent == {"limit": 5, "skip": 10}
def test_invalid_after_cursor(self):
tool = FirefliesTool(api_key="x")
assert tool.list_recent_meetings(after="notint") == [
{"error": "after must be an integer cursor"}
]
def test_propagates_error(self):
tool = FirefliesTool(api_key="x")
with patch("requests.post", side_effect=RuntimeError("net")):
assert tool.list_recent_meetings() == [{"error": "net"}]
def test_limit_clamped_to_50(self):
tool = FirefliesTool(api_key="x")
with patch(
"requests.post", return_value=_mock_response({"data": {"transcripts": []}})
) as post:
tool.list_recent_meetings(limit=500)
assert post.call_args.kwargs["json"]["variables"]["limit"] == 50
# ── get_transcript ──────────────────────────────────────────────────
class TestGetTranscript:
def test_requires_meeting_id(self):
tool = FirefliesTool(api_key="x")
assert tool.get_transcript(meeting_id="") == {"error": "meeting_id required"}
def test_returns_normalised_transcript(self):
tool = FirefliesTool(api_key="x")
payload = {
"data": {
"transcript": {
"id": "m1",
"title": "Standup",
"date": "2026-01-01",
"duration": 15,
"organizer_email": "[email protected]",
"summary": {"overview": "We talked."},
"sentences": [
{"text": "Hi", "speaker_name": "A", "start_time": 0.0}
],
}
}
}
with patch("requests.post", return_value=_mock_response(payload)):
transcript = tool.get_transcript(meeting_id="m1")
assert transcript["summary"] == "We talked."
assert transcript["sentence_count"] == 1
def test_not_found(self):
tool = FirefliesTool(api_key="x")
with patch(
"requests.post",
return_value=_mock_response({"data": {"transcript": None}}),
):
assert tool.get_transcript(meeting_id="missing") == {
"error": "transcript not found"
}
# ── search ──────────────────────────────────────────────────────────
class TestSearch:
def test_requires_keywords(self):
tool = FirefliesTool(api_key="x")
assert tool.search(keywords="") == [{"error": "keywords required"}]
def test_returns_results(self):
tool = FirefliesTool(api_key="x")
payload = {
"data": {
"transcripts": [
{
"id": "m1",
"title": "Roadmap",
"date": "2026-01-01",
"organizer_email": "[email protected]",
}
]
}
}
with patch("requests.post", return_value=_mock_response(payload)) as post:
results = tool.search(keywords="roadmap", limit=3)
sent = post.call_args.kwargs["json"]["variables"]
assert sent == {"keyword": "roadmap", "limit": 3}
assert results[0]["title"] == "Roadmap"
# ── run() dispatcher ────────────────────────────────────────────────
class TestRunDispatcher:
def test_unknown_action(self):
tool = FirefliesTool(api_key="x")
assert tool.run(action="bogus") == {"error": "Unknown action: bogus"}
def test_routes_get_transcript(self):
tool = FirefliesTool(api_key="x")
with patch.object(tool, "get_transcript", return_value={"ok": True}) as m:
out = tool.run(action="get-transcript", meeting_id="m1")
m.assert_called_once_with(meeting_id="m1")
assert out == {"ok": True}
def test_routes_search(self):
tool = FirefliesTool(api_key="x")
with patch.object(tool, "search", return_value=[]) as m:
tool.run(action="search", keywords="hi", limit=5)
m.assert_called_once_with(keywords="hi", limit=5)
# ── Module-level helper ─────────────────────────────────────────────
class TestListFirefliesMeetingsHelper:
def test_delegates_to_tool(self):
with patch.object(
FirefliesTool, "list_recent_meetings", return_value=["x"]
) as m:
assert list_fireflies_meetings(limit=5) == ["x"]
m.assert_called_once_with(limit=5)
-314
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@@ -1,314 +0,0 @@
"""Unit tests for JIRA watch tools."""
import sys
from unittest.mock import MagicMock, Mock, patch
import pytest
# Optional dependency — stub so @patch("jira.JIRA") resolves in CI without jira installed.
sys.modules.setdefault("jira", MagicMock())
from praisonai_tools.tools.jira_watch_tool import ( # noqa: E402
jira_watch_issue,
jira_watch_project,
jira_get_issue_info,
jira_search_issues,
jira_tools,
_get_jira_connection,
_validate_project_key,
_validate_issue_key,
_validate_timestamp,
)
class TestJIRAConnection:
@patch("jira.JIRA")
def test_connection_with_email_token(self, mock_jira):
_get_jira_connection(
url="https://test.atlassian.net",
email="[email protected]",
token="test_token",
)
mock_jira.assert_called_once_with(
server="https://test.atlassian.net",
basic_auth=("[email protected]", "test_token"),
)
@patch("jira.JIRA")
def test_connection_with_username_token(self, mock_jira):
_get_jira_connection(
url="https://test.atlassian.net",
username="test_user",
token="test_token",
)
mock_jira.assert_called_once_with(
server="https://test.atlassian.net",
basic_auth=("test_user", "test_token"),
)
def test_connection_missing_auth(self, monkeypatch):
for var in ("JIRA_EMAIL", "JIRA_USERNAME", "JIRA_API_TOKEN"):
monkeypatch.delenv(var, raising=False)
with pytest.raises(ValueError, match="JIRA authentication required"):
_get_jira_connection(url="https://test.atlassian.net")
def test_connection_missing_url(self, monkeypatch):
monkeypatch.delenv("JIRA_URL", raising=False)
with pytest.raises(ValueError, match="JIRA URL is required"):
_get_jira_connection(email="[email protected]", token="token")
class TestJIRAGetIssueInfo:
@patch("praisonai_tools.tools.jira_watch_tool._get_jira_connection")
def test_get_issue_info_success(self, mock_connection):
mock_jira = Mock()
mock_connection.return_value = mock_jira
mock_issue = Mock()
mock_issue.key = "PROJ-123"
mock_issue.fields.summary = "Test issue"
mock_issue.fields.status.name = "Open"
mock_issue.fields.priority.name = "High"
mock_issue.fields.assignee.displayName = "John Doe"
mock_issue.fields.reporter.displayName = "Jane Smith"
mock_issue.fields.created = "2024-01-01T10:00:00"
mock_issue.fields.updated = "2024-01-02T15:30:00"
mock_issue.fields.description = "Test description"
mock_jira.issue.return_value = mock_issue
mock_jira.comments.return_value = []
result = jira_get_issue_info(
issue_key="PROJ-123",
url="https://test.atlassian.net",
email="[email protected]",
token="test_token",
)
assert "PROJ-123" in result
assert "Test issue" in result
assert "Open" in result
class TestJIRASearchIssues:
@patch("praisonai_tools.tools.jira_watch_tool._get_jira_connection")
def test_search_issues_success(self, mock_connection):
mock_jira = Mock()
mock_connection.return_value = mock_jira
mock_issue = Mock()
mock_issue.key = "PROJ-123"
mock_issue.fields.summary = "First issue"
mock_issue.fields.status.name = "Open"
mock_issue.fields.assignee.displayName = "John Doe"
mock_issue.fields.updated = "2024-01-01T10:00:00"
mock_jira.search_issues.return_value = [mock_issue]
result = jira_search_issues(
jql="project = PROJ",
url="https://test.atlassian.net",
email="[email protected]",
token="test_token",
)
assert "Found 1 issues" in result
assert "PROJ-123" in result
class TestJIRAWatchIssue:
@patch("praisonai_tools.tools.jira_watch_tool._get_jira_connection")
def test_watch_issue_current_state(self, mock_connection):
mock_jira = Mock()
mock_connection.return_value = mock_jira
mock_issue = Mock()
mock_issue.fields.updated = "2024-01-01T10:00:00"
mock_issue.fields.status.name = "Open"
mock_issue.fields.summary = "Test issue"
mock_issue.fields.assignee.displayName = "John Doe"
mock_issue.fields.priority.name = "High"
mock_jira.issue.return_value = mock_issue
result = jira_watch_issue(
issue_key="PROJ-123",
url="https://test.atlassian.net",
email="[email protected]",
token="test_token",
)
assert "current state" in result
assert "PROJ-123" in result
class TestJIRAWatchProject:
@patch("praisonai_tools.tools.jira_watch_tool._get_jira_connection")
def test_watch_project_recent_activity(self, mock_connection):
mock_jira = Mock()
mock_connection.return_value = mock_jira
mock_issue = Mock()
mock_issue.key = "PROJ-123"
mock_issue.fields.summary = "Test issue"
mock_issue.fields.status.name = "Open"
mock_issue.fields.updated = "2024-01-01T10:00:00"
mock_jira.search_issues.return_value = [mock_issue]
result = jira_watch_project(
project_key="PROJ",
url="https://test.atlassian.net",
email="[email protected]",
token="test_token",
)
assert "recent activity" in result
assert "PROJ-123" in result
class TestJIRAValidation:
def test_validate_project_key_valid(self):
assert _validate_project_key("PROJ")
assert _validate_project_key("MY_PROJECT")
def test_validate_project_key_invalid(self):
with pytest.raises(ValueError):
_validate_project_key("proj")
with pytest.raises(ValueError):
_validate_project_key("PROJ OR 1=1")
def test_validate_issue_key_valid(self):
assert _validate_issue_key("PROJ-123")
assert _validate_issue_key("abc_123")
def test_validate_issue_key_invalid(self):
with pytest.raises(ValueError):
_validate_issue_key("../secret")
with pytest.raises(ValueError):
_validate_issue_key('PROJ-1" OR "1"="1')
def test_validate_timestamp_valid(self):
assert _validate_timestamp("2024-01-01T00:00:00Z") == "2024-01-01 00:00"
assert _validate_timestamp("2024-01-01T10:30:00") == "2024-01-01 10:30"
def test_validate_timestamp_rejects_injection(self):
with pytest.raises(ValueError):
_validate_timestamp('2024-01-01" OR project = SECRET AND created >= "2024-01-01')
class TestJIRAWatchSinceTimestamp:
@patch("praisonai_tools.tools.jira_watch_tool._get_jira_connection")
def test_watch_issue_no_change(self, mock_connection):
mock_jira = Mock()
mock_connection.return_value = mock_jira
mock_issue = Mock()
mock_issue.fields.updated = "2024-01-01T10:00:00+00:00"
mock_issue.fields.status.name = "Open"
mock_issue.fields.summary = "Test issue"
mock_issue.changelog.histories = []
mock_jira.issue.return_value = mock_issue
result = jira_watch_issue(
issue_key="PROJ-123",
url="https://test.atlassian.net",
email="[email protected]",
token="test_token",
since_timestamp="2024-06-01T00:00:00Z",
)
assert "No changes detected" in result
@patch("praisonai_tools.tools.jira_watch_tool._get_jira_connection")
def test_watch_issue_change_detected(self, mock_connection):
mock_jira = Mock()
mock_connection.return_value = mock_jira
mock_issue = Mock()
mock_issue.fields.updated = "2024-06-15T10:00:00+00:00"
mock_issue.fields.status.name = "Done"
mock_issue.fields.summary = "Test issue"
mock_issue.fields.assignee.displayName = "John Doe"
mock_issue.fields.priority.name = "High"
mock_issue.changelog.histories = []
mock_jira.issue.return_value = mock_issue
mock_jira.comments.return_value = []
result = jira_watch_issue(
issue_key="PROJ-123",
url="https://test.atlassian.net",
email="[email protected]",
token="test_token",
since_timestamp="2024-01-01T00:00:00Z",
)
assert "changes detected" in result
assert "PROJ-123" in result
@patch("praisonai_tools.tools.jira_watch_tool._get_jira_connection")
def test_watch_issue_reports_all_in_window_changes(self, mock_connection):
mock_jira = Mock()
mock_connection.return_value = mock_jira
mock_issue = Mock()
mock_issue.fields.updated = "2024-06-15T10:00:00+00:00"
mock_issue.fields.status.name = "Done"
mock_issue.fields.summary = "Test issue"
mock_issue.fields.assignee.displayName = "John Doe"
mock_issue.fields.priority.name = "High"
histories = []
for idx in range(5):
hist = Mock()
hist.created = f"2024-06-1{idx}T10:00:00+00:00"
hist.author.displayName = "Editor"
item = Mock()
item.field = f"field{idx}"
item.fromString = "old"
item.toString = "new"
hist.items = [item]
histories.append(hist)
mock_issue.changelog.histories = histories
mock_jira.issue.return_value = mock_issue
mock_jira.comments.return_value = []
result = jira_watch_issue(
issue_key="PROJ-123",
url="https://test.atlassian.net",
email="[email protected]",
token="test_token",
since_timestamp="2024-01-01T00:00:00Z",
)
for idx in range(5):
assert f"field{idx}" in result
@patch("praisonai_tools.tools.jira_watch_tool._get_jira_connection")
def test_watch_project_since_timestamp_no_injection(self, mock_connection):
mock_jira = Mock()
mock_connection.return_value = mock_jira
mock_jira.search_issues.return_value = []
result = jira_watch_project(
project_key="PROJ",
url="https://test.atlassian.net",
email="[email protected]",
token="test_token",
since_timestamp="2024-01-01T00:00:00Z",
)
assert "No changes detected" in result
for call in mock_jira.search_issues.call_args_list:
assert '2024-01-01 00:00' in call.args[0]
@patch("praisonai_tools.tools.jira_watch_tool._get_jira_connection")
def test_watch_project_rejects_bad_timestamp(self, mock_connection):
mock_connection.return_value = Mock()
result = jira_watch_project(
project_key="PROJ",
url="https://test.atlassian.net",
email="[email protected]",
token="test_token",
since_timestamp='bad" OR "1"="1',
)
assert "Error" in result
def test_jira_tools_collection():
tools = jira_tools()
assert isinstance(tools, list)
assert len(tools) == 4
@@ -1,273 +0,0 @@
"""Unit tests for KeenableSearchTool."""
import json
import os
from unittest.mock import MagicMock, patch
from praisonai_tools.tools.keenable_search_tool import (
KEENABLE_MAX_RESULTS,
KEENABLE_MAX_SNIPPET_CHARS,
KEENABLE_MAX_TITLE_CHARS,
KEENABLE_MAX_URL_CHARS,
KEENABLE_PUBLIC_SEARCH_URL,
KEENABLE_SEARCH_URL,
KeenableSearchTool,
_NoRedirect,
keenable_search,
)
class _FakeResponse:
"""Minimal stand-in for an ``http.client.HTTPResponse`` context manager."""
def __init__(self, raw: bytes):
self._raw = raw
def read(self, amt=None):
"""Return at most ``amt`` bytes, honouring the caller's read cap."""
if amt is None:
return self._raw
return self._raw[:amt]
def __enter__(self):
return self
def __exit__(self, *_args):
return False
def _payload(results):
return json.dumps({"results": results}).encode("utf-8")
# ── Import + schema (CI smoke) ──────────────────────────────────────
class TestImportAndSchema:
def test_import_via_package(self):
from praisonai_tools import KeenableSearchTool as PkgTool
assert PkgTool is KeenableSearchTool
def test_schema_generation(self):
tool = KeenableSearchTool()
schema = tool.get_schema()
assert schema["function"]["name"] == "keenable_search"
assert "description" in schema["function"]
assert "action" in schema["function"]["parameters"]["properties"]
# ── Endpoint selection ──────────────────────────────────────────────
class TestEndpointSelection:
def test_public_endpoint_without_key(self):
with patch.dict(os.environ, {}, clear=True):
tool = KeenableSearchTool()
assert tool.api_key == ""
captured = {}
def fake_open(request, timeout=None):
captured["url"] = request.full_url
captured["headers"] = dict(request.header_items())
return _FakeResponse(_payload([]))
opener = MagicMock()
opener.open.side_effect = fake_open
with patch("urllib.request.build_opener", return_value=opener):
tool.search("python", max_results=3)
assert captured["url"] == KEENABLE_PUBLIC_SEARCH_URL
header_names = {k.lower() for k in captured["headers"]}
assert "x-api-key" not in header_names
assert "X-keenable-title" in captured["headers"] or "X-Keenable-Title" in captured["headers"]
def test_authenticated_endpoint_with_key(self):
tool = KeenableSearchTool(api_key="secret-key")
captured = {}
def fake_open(request, timeout=None):
captured["url"] = request.full_url
captured["headers"] = dict(request.header_items())
return _FakeResponse(_payload([]))
opener = MagicMock()
opener.open.side_effect = fake_open
with patch("urllib.request.build_opener", return_value=opener):
tool.search("python", max_results=3)
assert captured["url"] == KEENABLE_SEARCH_URL
# urllib title-cases header keys.
assert captured["headers"].get("X-api-key") == "secret-key"
# ── Result mapping + bounds ─────────────────────────────────────────
class TestResultMapping:
def _run(self, tool, results):
opener = MagicMock()
opener.open.return_value = _FakeResponse(_payload(results))
with patch("urllib.request.build_opener", return_value=opener):
return tool.search("q", max_results=10)
def test_maps_fields(self):
out = self._run(
KeenableSearchTool(),
[{"title": "T", "url": "https://example.com", "snippet": "hello world"}],
)
assert out == [{
"title": "T",
"url": "https://example.com",
"snippet": "hello world",
"provider": "keenable",
}]
def test_skips_entries_without_url(self):
out = self._run(
KeenableSearchTool(),
[{"title": "no url"}, {"title": "ok", "url": "https://a.com"}],
)
assert len(out) == 1
assert out[0]["url"] == "https://a.com"
def test_respects_max_results(self):
tool = KeenableSearchTool()
many = [{"url": f"https://a.com/{i}"} for i in range(10)]
opener = MagicMock()
opener.open.return_value = _FakeResponse(_payload(many))
with patch("urllib.request.build_opener", return_value=opener):
out = tool.search("q", max_results=3)
assert len(out) == 3
def test_zero_max_results_short_circuits(self):
out = KeenableSearchTool().search("q", max_results=0)
assert out == []
def test_empty_query_errors(self):
out = KeenableSearchTool().search("", max_results=5)
assert out == [{"error": "query is required"}]
# ── Error handling ──────────────────────────────────────────────────
class TestErrorHandling:
def test_invalid_shape_errors(self):
tool = KeenableSearchTool()
opener = MagicMock()
opener.open.return_value = _FakeResponse(b'{"not_results": 1}')
with patch("urllib.request.build_opener", return_value=opener):
out = tool.search("q")
assert out and "error" in out[0]
def test_oversized_response_errors(self):
tool = KeenableSearchTool()
oversized = b"x" * (1_000_001 + 1)
opener = MagicMock()
opener.open.return_value = _FakeResponse(oversized)
with patch("urllib.request.build_opener", return_value=opener):
out = tool.search("q")
assert out == [{"error": "Keenable returned an oversized response"}]
def test_http_error_is_captured(self):
tool = KeenableSearchTool()
opener = MagicMock()
opener.open.side_effect = RuntimeError("boom")
with patch("urllib.request.build_opener", return_value=opener):
out = tool.search("q")
assert out == [{"error": "boom"}]
# ── Protective bounds + redirect refusal ────────────────────────────
class TestProtections:
def _capture_body(self, tool, requested):
"""Run a search and return the decoded JSON request body sent."""
captured = {}
def fake_open(request, timeout=None):
captured["body"] = json.loads(request.data.decode("utf-8"))
return _FakeResponse(_payload([]))
opener = MagicMock()
opener.open.side_effect = fake_open
with patch("urllib.request.build_opener", return_value=opener):
tool.search("q", max_results=requested)
return captured["body"]
def test_caps_requested_results_at_limit(self):
"""max_results above the hard cap is clamped before the request."""
body = self._capture_body(KeenableSearchTool(), requested=1000)
assert body["max_results"] == KEENABLE_MAX_RESULTS
def test_truncates_oversized_title(self):
"""Titles longer than the cap are truncated with an ellipsis."""
opener = MagicMock()
opener.open.return_value = _FakeResponse(
_payload([{"title": "T" * 5000, "url": "https://a.com"}])
)
with patch("urllib.request.build_opener", return_value=opener):
out = KeenableSearchTool().search("q")
assert len(out[0]["title"]) == KEENABLE_MAX_TITLE_CHARS
assert out[0]["title"].endswith("…")
def test_truncates_oversized_snippet(self):
"""Snippets longer than the cap are truncated with an ellipsis."""
opener = MagicMock()
opener.open.return_value = _FakeResponse(
_payload([{"snippet": "s " * 5000, "url": "https://a.com"}])
)
with patch("urllib.request.build_opener", return_value=opener):
out = KeenableSearchTool().search("q")
assert len(out[0]["snippet"]) == KEENABLE_MAX_SNIPPET_CHARS
assert out[0]["snippet"].endswith("…")
def test_skips_oversized_url(self):
"""Results whose URL exceeds the length cap are dropped."""
long_url = "https://a.com/" + "x" * KEENABLE_MAX_URL_CHARS
opener = MagicMock()
opener.open.return_value = _FakeResponse(
_payload([{"url": long_url}, {"url": "https://ok.com"}])
)
with patch("urllib.request.build_opener", return_value=opener):
out = KeenableSearchTool().search("q")
assert out == [{
"title": "",
"url": "https://ok.com",
"snippet": "",
"provider": "keenable",
}]
def test_read_is_capped_at_limit(self):
"""The body read is bounded, so an oversized stream still errors out."""
tool = KeenableSearchTool()
# Far larger than the cap; _FakeResponse.read honours the byte count,
# so this verifies the read limit rather than a pre-sized buffer.
opener = MagicMock()
opener.open.return_value = _FakeResponse(b"x" * 5_000_000)
with patch("urllib.request.build_opener", return_value=opener):
out = tool.search("q")
assert out == [{"error": "Keenable returned an oversized response"}]
def test_refuses_redirects(self):
"""The redirect handler drops 3xx responses so no follow-up is sent."""
handler = _NoRedirect()
# Returning None is urllib's signal to NOT build/send a second request.
assert handler.redirect_request(
MagicMock(), MagicMock(), 302, "Found", {}, "https://evil.example"
) is None
# ── Module-level convenience function ───────────────────────────────
class TestConvenienceFunction:
def test_keenable_search_function(self):
opener = MagicMock()
opener.open.return_value = _FakeResponse(_payload([{"url": "https://a.com"}]))
with patch("urllib.request.build_opener", return_value=opener):
out = keenable_search("q", max_results=2)
assert out[0]["provider"] == "keenable"
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"""Unit tests for meeting_tools.
All external clients (OpenAI, Chroma) are mocked so no network or heavy
dependency is required. The SQLite persistence is redirected to a temp dir.
"""
from types import SimpleNamespace
from unittest.mock import MagicMock, patch
import pytest
from praisonai_tools.tools import meeting_tools as mt
@pytest.fixture(autouse=True)
def _isolated_app_dir(tmp_path, monkeypatch):
"""Point the meetings DB and vector store at a temp dir per test."""
monkeypatch.setenv("PRAISONAI_MEETINGS_DIR", str(tmp_path))
monkeypatch.setenv("PRAISONAI_MEETINGS_DB", str(tmp_path / "meetings.db"))
monkeypatch.setenv("OPENAI_API_KEY", "test-key")
yield
# ── transcribe_file ─────────────────────────────────────────────────
class TestTranscribeFile:
def test_missing_file(self):
result = mt.transcribe_file.__wrapped__("/no/such/file.mp3")
assert "error" in result
assert "not found" in result["error"].lower()
def _fake_response(self):
return SimpleNamespace(
text="Good morning everyone",
duration=12.5,
language="en",
segments=[
SimpleNamespace(start=0.0, end=4.2, text="Good morning everyone"),
],
)
def test_success(self, tmp_path):
audio = tmp_path / "a.mp3"
audio.write_bytes(b"fake")
client = MagicMock()
client.audio.transcriptions.create.return_value = self._fake_response()
with patch.object(mt, "_get_openai_client", return_value=client):
result = mt.transcribe_file.__wrapped__(str(audio))
assert result["text"] == "Good morning everyone"
assert result["language"] == "en"
assert result["duration_seconds"] == 12.5
assert result["segments"][0]["start"] == 0.0
assert result["segments"][0]["end"] == 4.2
def test_403_error_mapping(self, tmp_path):
audio = tmp_path / "a.mp3"
audio.write_bytes(b"fake")
exc = Exception("403 forbidden")
setattr(exc, "status_code", 403)
client = MagicMock()
client.audio.transcriptions.create.side_effect = exc
with patch.object(mt, "_get_openai_client", return_value=client):
result = mt.transcribe_file.__wrapped__(str(audio))
assert "403" in result["error"] or "permission" in result["error"].lower()
def test_timeout_retries_once_then_fails(self, tmp_path):
audio = tmp_path / "a.mp3"
audio.write_bytes(b"fake")
class TimeoutError_(Exception):
pass
client = MagicMock()
client.audio.transcriptions.create.side_effect = TimeoutError_("timeout")
with patch.object(mt, "_get_openai_client", return_value=client):
result = mt.transcribe_file.__wrapped__(str(audio))
assert "timed out" in result["error"].lower()
assert client.audio.transcriptions.create.call_count == 2
def test_empty_audio(self, tmp_path):
audio = tmp_path / "a.mp3"
audio.write_bytes(b"fake")
client = MagicMock()
client.audio.transcriptions.create.return_value = SimpleNamespace(
text="", duration=0.0, language="en", segments=[]
)
with patch.object(mt, "_get_openai_client", return_value=client):
result = mt.transcribe_file.__wrapped__(str(audio))
assert result["error"] == "No speech detected in recording"
# ── Meetings CRUD ───────────────────────────────────────────────────
class TestMeetingsCRUD:
def test_save_and_get(self):
saved = mt.save_meeting.__wrapped__(
title="Weekly standup", source="file.mp3", metadata={"team": "eng"}
)
mid = saved["meeting_id"]
assert mid
record = mt.get_meeting.__wrapped__(mid)
assert record["title"] == "Weekly standup"
assert record["source"] == "file.mp3"
assert record["metadata"] == {"team": "eng"}
def test_save_requires_title(self):
assert "error" in mt.save_meeting.__wrapped__(title="")
def test_get_not_found(self):
assert "error" in mt.get_meeting.__wrapped__("nope")
def test_list(self):
mt.save_meeting.__wrapped__(title="A")
mt.save_meeting.__wrapped__(title="B")
meetings = mt.list_meetings.__wrapped__(limit=10, offset=0)
assert len(meetings) == 2
titles = {m["title"] for m in meetings}
assert titles == {"A", "B"}
def test_list_pagination(self):
for i in range(3):
mt.save_meeting.__wrapped__(title=f"M{i}")
page = mt.list_meetings.__wrapped__(limit=1, offset=1)
assert len(page) == 1
# ── summarize_transcript ────────────────────────────────────────────
class TestSummarize:
def test_requires_transcript(self):
assert "error" in mt.summarize_transcript.__wrapped__("")
def test_single_chunk(self):
payload = {
"summary": "It was a good meeting.",
"decisions": ["Ship on Friday"],
"topics": ["release"],
"key_quotes": [{"speaker": "Alex", "quote": "Ship it"}],
}
with patch.object(mt, "_chat_json", return_value=payload):
result = mt.summarize_transcript.__wrapped__("short transcript")
assert result["summary"] == "It was a good meeting."
assert result["decisions"] == ["Ship on Friday"]
assert result["topics"] == ["release"]
assert result["key_quotes"][0]["quote"] == "Ship it"
def test_map_reduce_merges_chunks(self):
long_text = "word " * 8000 # forces multiple summary chunks
calls = []
def fake_chat(system, user):
idx = len(calls)
calls.append(user)
return {
"summary": f"para{idx}",
"decisions": [f"d{idx}"],
"topics": ["t"],
"key_quotes": [{"speaker": None, "quote": f"q{idx}"}],
}
with patch.object(mt, "_chat_json", side_effect=fake_chat):
result = mt.summarize_transcript.__wrapped__(long_text)
assert len(calls) > 1
assert "para0" in result["summary"]
assert "t" in result["topics"] # deduped
assert result["topics"].count("t") == 1
assert len(result["decisions"]) == len(calls)
# ── extract_action_items ────────────────────────────────────────────
class TestActionItems:
def test_requires_transcript(self):
assert "error" in mt.extract_action_items.__wrapped__("")
def test_returns_valid_schema(self):
payload = {
"action_items": [
{
"description": "Fix API bug",
"owner": "Alex",
"due_date": "2026-09-05",
"priority": "high",
}
]
}
with patch.object(mt, "_chat_json", return_value=payload):
result = mt.extract_action_items.__wrapped__("transcript")
item = result["action_items"][0]
assert set(item.keys()) == {"description", "owner", "due_date", "priority"}
assert item["owner"] == "Alex"
def test_handles_empty(self):
with patch.object(mt, "_chat_json", return_value={}):
result = mt.extract_action_items.__wrapped__("transcript")
assert result["action_items"] == []
# ── Fake in-memory vector collection ────────────────────────────────
class _FakeCollection:
"""Minimal Chroma-like collection using cosine-ish distance on tags."""
def __init__(self):
self.store = {} # id -> (document, metadata, embedding)
def delete(self, where=None):
if not where:
self.store.clear()
return
mid = where.get("meeting_id")
for k in [k for k, v in self.store.items() if v[1].get("meeting_id") == mid]:
del self.store[k]
def add(self, ids, documents, embeddings, metadatas):
for i, _id in enumerate(ids):
self.store[_id] = (documents[i], metadatas[i], embeddings[i])
def query(self, query_embeddings, n_results):
q = query_embeddings[0]
def dist(emb):
return sum((a - b) ** 2 for a, b in zip(q, emb))
ranked = sorted(self.store.items(), key=lambda kv: dist(kv[1][2]))
ranked = ranked[:n_results]
return {
"documents": [[v[0] for _, v in ranked]],
"metadatas": [[v[1] for _, v in ranked]],
"distances": [[dist(v[2]) for _, v in ranked]],
}
class TestIndexAndSearch:
def _embed_map(self):
# deterministic embeddings keyed by content keyword
def fake_embed(texts):
out = []
for t in texts:
if "apple" in t.lower():
out.append([1.0, 0.0])
elif "banana" in t.lower():
out.append([0.0, 1.0])
else:
out.append([0.5, 0.5])
return out
return fake_embed
def test_index_and_rank(self):
coll = _FakeCollection()
m1 = mt.save_meeting.__wrapped__(title="Apple meeting")["meeting_id"]
m2 = mt.save_meeting.__wrapped__(title="Banana meeting")["meeting_id"]
with patch.object(mt, "_get_vector_collection", return_value=coll), patch.object(
mt, "_embed", side_effect=self._embed_map()
):
mt.index_meeting.__wrapped__(m1, transcript="all about apple pie")
mt.index_meeting.__wrapped__(m2, transcript="all about banana bread")
results = mt.search_meetings.__wrapped__("apple", limit=2)
assert results[0]["meeting_id"] == m1
assert results[0]["score"] is not None
assert results[0]["title"] == "Apple meeting"
def test_reindex_does_not_duplicate(self):
coll = _FakeCollection()
mid = mt.save_meeting.__wrapped__(title="M")["meeting_id"]
with patch.object(mt, "_get_vector_collection", return_value=coll), patch.object(
mt, "_embed", side_effect=self._embed_map()
):
r1 = mt.index_meeting.__wrapped__(mid, transcript="apple " * 600)
count_after_first = len(coll.store)
r2 = mt.index_meeting.__wrapped__(mid, transcript="apple " * 600)
count_after_second = len(coll.store)
assert r1["chunks_indexed"] == r2["chunks_indexed"]
assert count_after_first == count_after_second
def test_index_missing_transcript(self):
mid = mt.save_meeting.__wrapped__(title="M")["meeting_id"]
result = mt.index_meeting.__wrapped__(mid)
assert "error" in result
def test_search_requires_query(self):
assert "error" in mt.search_meetings.__wrapped__("")[0]
def test_segments_map_to_chunk_timestamps(self):
coll = _FakeCollection()
mid = mt.save_meeting.__wrapped__(title="Timed")["meeting_id"]
segments = [
{"start": 0.0, "end": 5.0, "text": "apple " * 200},
{"start": 5.0, "end": 12.0, "text": "banana " * 200},
]
transcript = " ".join(s["text"].strip() for s in segments)
with patch.object(mt, "_get_vector_collection", return_value=coll), patch.object(
mt, "_embed", side_effect=self._embed_map()
):
mt.index_meeting.__wrapped__(mid, transcript=transcript, segments=segments)
results = mt.search_meetings.__wrapped__("banana", limit=1)
assert results[0]["meeting_id"] == mid
# The best match ("banana") must carry a non-zero timestamp derived
# from the second segment, not the recording start.
assert results[0]["timestamp_start"] > 0.0
assert results[0]["timestamp_end"] >= results[0]["timestamp_start"]
def test_failed_reindex_preserves_existing_chunks(self):
coll = _FakeCollection()
mid = mt.save_meeting.__wrapped__(title="M")["meeting_id"]
with patch.object(mt, "_get_vector_collection", return_value=coll), patch.object(
mt, "_embed", side_effect=self._embed_map()
):
mt.index_meeting.__wrapped__(mid, transcript="apple " * 600)
assert len(coll.store) > 0
original = dict(coll.store)
def boom(_texts):
raise RuntimeError("embedding backend down")
with patch.object(mt, "_get_vector_collection", return_value=coll), patch.object(
mt, "_embed", side_effect=boom
):
result = mt.index_meeting.__wrapped__(mid, transcript="apple " * 600)
assert "error" in result
# Previous chunks must survive a failed re-index.
assert coll.store == original
def test_search_score_bounded_for_large_distance(self):
coll = _FakeCollection()
mid = mt.save_meeting.__wrapped__(title="Far")["meeting_id"]
def far_embed(texts):
# Query and doc are far apart -> squared-L2 distance > 1.
return [[10.0, 10.0] for _ in texts]
with patch.object(mt, "_get_vector_collection", return_value=coll), patch.object(
mt, "_embed", side_effect=lambda t: [[0.0, 0.0] for _ in t]
):
mt.index_meeting.__wrapped__(mid, transcript="apple pie")
with patch.object(mt, "_get_vector_collection", return_value=coll), patch.object(
mt, "_embed", side_effect=far_embed
):
results = mt.search_meetings.__wrapped__("pie", limit=1)
assert 0.0 < results[0]["score"] <= 1.0
# ── Lazy import hygiene ─────────────────────────────────────────────
def test_no_heavy_deps_at_import_time():
import sys
# meeting_tools is already imported at top; ensure it did not pull heavy deps.
mod = sys.modules["praisonai_tools.tools.meeting_tools"]
src = open(mod.__file__).read()
# No top-level (unindented) imports of openai/chromadb.
for line in src.splitlines():
if line.startswith("import openai") or line.startswith("from openai"):
raise AssertionError("openai imported at module top level")
if line.startswith("import chromadb") or line.startswith("from chromadb"):
raise AssertionError("chromadb imported at module top level")
def test_all_tools_are_registerable():
import praisonai_tools
for name in (
"transcribe_file",
"save_meeting",
"get_meeting",
"list_meetings",
"summarize_transcript",
"extract_action_items",
"index_meeting",
"search_meetings",
):
exported = getattr(praisonai_tools, name, None)
assert exported is not None, f"{name} is not exported"
assert exported is getattr(mt, name), f"{name} export is shadowed"
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"""Unit tests for RedditTool."""
import os
from unittest.mock import MagicMock, patch
from praisonai_tools.tools.reddit_tool import RedditTool
# ── Import + schema (CI smoke) ──────────────────────────────────────
class TestImportAndSchema:
def test_import_via_package(self):
from praisonai_tools import RedditTool as PkgRedditTool
assert PkgRedditTool is RedditTool
def test_schema_generation(self):
tool = RedditTool(client_id="cid", client_secret="secret")
schema = tool.get_schema()
assert schema["function"]["name"] == "reddit"
assert "description" in schema["function"]
assert "action" in schema["function"]["parameters"]["properties"]
# ── User-Agent ──────────────────────────────────────────────────────
class TestUserAgent:
def test_default_user_agent_references_app_id(self):
with patch.dict(os.environ, {}, clear=True):
tool = RedditTool(client_id="myappid", client_secret="secret")
assert "myappid" in tool.user_agent
def test_explicit_user_agent_wins(self):
tool = RedditTool(client_id="c", client_secret="s", user_agent="custom:ua:1.0")
assert tool.user_agent == "custom:ua:1.0"
def test_env_user_agent_used(self):
with patch.dict(os.environ, {"REDDIT_USER_AGENT": "env:ua:1.0"}, clear=True):
tool = RedditTool(client_id="c", client_secret="s")
assert tool.user_agent == "env:ua:1.0"
# ── Write flag gating ───────────────────────────────────────────────
class TestWriteGating:
def test_write_disabled_by_default(self):
with patch.dict(os.environ, {}, clear=True):
tool = RedditTool(client_id="c", client_secret="s")
assert tool.allow_write is False
def test_env_enables_write(self):
with patch.dict(os.environ, {"REDDIT_ALLOW_WRITE": "1"}, clear=True):
tool = RedditTool(client_id="c", client_secret="s")
assert tool.allow_write is True
def test_post_comment_blocked_when_write_disabled(self):
with patch.dict(os.environ, {}, clear=True):
tool = RedditTool(client_id="c", client_secret="s")
result = tool.post_comment(post_id="abc", body="hi")
assert "REDDIT_ALLOW_WRITE" in result["error"]
def test_submit_post_blocked_when_write_disabled(self):
with patch.dict(os.environ, {}, clear=True):
tool = RedditTool(client_id="c", client_secret="s")
result = tool.submit_post(subreddit="test", title="T", body="B")
assert "REDDIT_ALLOW_WRITE" in result["error"]
def test_write_requires_account_credentials(self):
tool = RedditTool(client_id="c", client_secret="s", allow_write=True)
result = tool.post_comment(post_id="abc", body="hi")
assert "REDDIT_USERNAME" in result["error"]
# ── Write actions (mocked praw) ─────────────────────────────────────
def _writable_tool():
return RedditTool(
client_id="c",
client_secret="s",
username="u",
password="p",
allow_write=True,
)
class TestPostComment:
def test_requires_post_id(self):
tool = _writable_tool()
assert tool.post_comment(post_id="", body="hi") == {"error": "post_id is required"}
def test_requires_body(self):
tool = _writable_tool()
assert tool.post_comment(post_id="abc", body="") == {"error": "body is required"}
def test_success(self):
tool = _writable_tool()
comment = MagicMock()
comment.id = "c1"
comment.permalink = "/r/test/comments/abc/x/c1/"
submission = MagicMock()
submission.reply.return_value = comment
reddit = MagicMock()
reddit.submission.return_value = submission
with patch.object(RedditTool, "reddit", new=reddit):
result = tool.post_comment(post_id="abc", body="hello")
submission.reply.assert_called_once_with("hello")
assert result["success"] is True
assert result["id"] == "c1"
class TestSubmitPost:
def test_requires_subreddit(self):
tool = _writable_tool()
assert tool.submit_post(subreddit="", title="T") == {"error": "subreddit is required"}
def test_requires_title(self):
tool = _writable_tool()
assert tool.submit_post(subreddit="test", title="") == {"error": "title is required"}
def test_body_and_url_mutually_exclusive(self):
tool = _writable_tool()
result = tool.submit_post(subreddit="test", title="T", body="B", url="http://x")
assert "not both" in result["error"]
def test_selftext_success(self):
tool = _writable_tool()
submission = MagicMock()
submission.id = "p1"
submission.permalink = "/r/test/comments/p1/"
sub = MagicMock()
sub.submit.return_value = submission
reddit = MagicMock()
reddit.subreddit.return_value = sub
with patch.object(RedditTool, "reddit", new=reddit):
result = tool.submit_post(subreddit="test", title="T", body="B")
sub.submit.assert_called_once_with("T", selftext="B")
assert result["id"] == "p1"
def test_link_success(self):
tool = _writable_tool()
submission = MagicMock()
submission.id = "p2"
submission.permalink = "/r/test/comments/p2/"
sub = MagicMock()
sub.submit.return_value = submission
reddit = MagicMock()
reddit.subreddit.return_value = sub
with patch.object(RedditTool, "reddit", new=reddit):
result = tool.submit_post(subreddit="test", title="T", url="http://x")
sub.submit.assert_called_once_with("T", url="http://x")
assert result["id"] == "p2"
# ── run() dispatcher ────────────────────────────────────────────────
class TestRunDispatcher:
def test_unknown_action(self):
tool = RedditTool(client_id="c", client_secret="s")
assert tool.run(action="bogus") == {"error": "Unknown action: bogus"}
def test_routes_post_comment(self):
tool = RedditTool(client_id="c", client_secret="s")
with patch.object(tool, "post_comment", return_value={"ok": True}) as m:
tool.run(action="post_comment", post_id="abc", body="hi")
m.assert_called_once_with(post_id="abc", body="hi")
def test_routes_submit_post(self):
tool = RedditTool(client_id="c", client_secret="s")
with patch.object(tool, "submit_post", return_value={"ok": True}) as m:
tool.run(action="submit-post", subreddit="test", title="T", body="B")
m.assert_called_once_with(subreddit="test", title="T", body="B", url=None)
-248
View File
@@ -1,248 +0,0 @@
"""Unit tests for StripeTool."""
import os
from unittest.mock import MagicMock, patch
from praisonai_tools.tools.stripe_tool import StripeTool, get_stripe_customer
def _mock_response(payload, status_code=200):
resp = MagicMock()
resp.json.return_value = payload
resp.status_code = status_code
return resp
# ── Key handling / mode banner ──────────────────────────────────────
class TestKeyAndMode:
def test_env_secret_key_fallback(self):
with patch.dict(os.environ, {"STRIPE_SECRET_KEY": "sk_test_x"}, clear=True):
tool = StripeTool()
assert tool.api_key == "sk_test_x"
assert tool._mode() == "test"
def test_stripe_api_key_fallback(self):
with patch.dict(os.environ, {"STRIPE_API_KEY": "sk_live_x"}, clear=True):
tool = StripeTool()
assert tool.api_key == "sk_live_x"
assert tool._mode() == "live"
def test_restricted_key_prefixes(self):
assert StripeTool(api_key="rk_test_x")._mode() == "test"
assert StripeTool(api_key="rk_live_x")._mode() == "live"
def test_unknown_mode(self):
assert StripeTool(api_key="weird")._mode() == "unknown"
def test_missing_key_returns_error(self):
with patch.dict(os.environ, {}, clear=True):
tool = StripeTool()
assert tool.get_customer(customer_id="cus_1") == {
"error": "STRIPE_SECRET_KEY (or STRIPE_API_KEY) is required"
}
# ── get_customer ────────────────────────────────────────────────────
class TestGetCustomer:
def test_requires_customer_id(self):
tool = StripeTool(api_key="sk_test_x")
assert tool.get_customer(customer_id="") == {"error": "customer_id is required"}
def test_returns_normalised_customer_with_banner(self):
tool = StripeTool(api_key="sk_test_x")
payload = {
"id": "cus_1",
"email": "[email protected]",
"name": "Alice",
"created": 123,
"currency": "usd",
"delinquent": False,
}
with patch("requests.request", return_value=_mock_response(payload)) as req:
result = tool.get_customer(customer_id="cus_1")
args, kwargs = req.call_args
assert args[0] == "get"
assert args[1].endswith("/customers/cus_1")
assert kwargs["headers"]["Authorization"] == "Bearer sk_test_x"
assert result["mode"] == "test"
assert result["id"] == "cus_1"
assert result["email"] == "[email protected]"
def test_propagates_stripe_error(self):
tool = StripeTool(api_key="sk_test_x")
payload = {"error": {"message": "No such customer", "type": "invalid_request_error"}}
with patch("requests.request", return_value=_mock_response(payload)):
assert tool.get_customer(customer_id="cus_x") == {"error": "No such customer"}
def test_handles_request_exception(self):
import requests
tool = StripeTool(api_key="sk_test_x")
with patch(
"requests.request",
side_effect=requests.exceptions.RequestException("boom"),
):
result = tool.get_customer(customer_id="cus_1")
assert result["error"].startswith("API request failed")
def test_non_2xx_without_error_object_is_failure(self):
# A non-2xx response whose body lacks Stripe's usual ``error`` object
# must not be treated as a successful payload.
tool = StripeTool(api_key="sk_test_x")
with patch(
"requests.request",
return_value=_mock_response({"unexpected": "shape"}, status_code=502),
):
result = tool.get_customer(customer_id="cus_1")
assert result == {"error": "Stripe API returned HTTP 502"}
# ── get_payment_intent ──────────────────────────────────────────────
class TestGetPaymentIntent:
def test_requires_id(self):
tool = StripeTool(api_key="sk_test_x")
assert tool.get_payment_intent(payment_intent_id="") == {
"error": "payment_intent_id is required"
}
def test_returns_normalised_intent(self):
tool = StripeTool(api_key="sk_test_x")
payload = {
"id": "pi_1",
"amount": 500,
"currency": "usd",
"status": "succeeded",
"customer": "cus_1",
"created": 1,
}
with patch("requests.request", return_value=_mock_response(payload)):
result = tool.get_payment_intent(payment_intent_id="pi_1")
assert result["status"] == "succeeded"
assert result["amount"] == 500
assert result["mode"] == "test"
# ── list_payment_links ──────────────────────────────────────────────
class TestListPaymentLinks:
def test_returns_links(self):
tool = StripeTool(api_key="sk_test_x")
payload = {
"data": [
{"id": "plink_1", "url": "https://pay/1", "active": True, "metadata": {}},
{"id": "plink_2", "url": "https://pay/2", "active": False, "metadata": {}},
]
}
with patch("requests.request", return_value=_mock_response(payload)):
result = tool.list_payment_links(limit=2)
assert result["mode"] == "test"
assert len(result["payment_links"]) == 2
assert result["payment_links"][0]["id"] == "plink_1"
def test_clamps_limit(self):
tool = StripeTool(api_key="sk_test_x")
with patch("requests.request", return_value=_mock_response({"data": []})) as req:
tool.list_payment_links(limit=999)
assert "limit=100" in req.call_args[0][1]
def test_propagates_error(self):
tool = StripeTool(api_key="sk_test_x")
payload = {"error": {"message": "bad"}}
with patch("requests.request", return_value=_mock_response(payload)):
assert tool.list_payment_links() == {"error": "bad"}
# ── create_payment_link (guardrails) ────────────────────────────────
class TestCreatePaymentLink:
def test_requires_price_id(self):
tool = StripeTool(api_key="sk_test_x")
assert tool.create_payment_link(
price_id="", correlation_id="c1"
) == {"error": "price_id is required"}
def test_requires_correlation_id(self):
tool = StripeTool(api_key="sk_test_x")
assert tool.create_payment_link(price_id="price_1") == {
"error": "correlation_id is required (stored as metadata)"
}
def test_rejects_bad_quantity(self):
tool = StripeTool(api_key="sk_test_x")
assert tool.create_payment_link(
price_id="price_1", correlation_id="c1", quantity=0
) == {"error": "quantity must be >= 1"}
def test_success_sends_metadata_and_idempotency_key(self):
tool = StripeTool(api_key="sk_test_x")
payload = {
"id": "plink_1",
"url": "https://pay/1",
"active": True,
"metadata": {"correlation_id": "order-42"},
}
with patch("requests.request", return_value=_mock_response(payload)) as req:
result = tool.create_payment_link(
price_id="price_1",
quantity=2,
correlation_id="order-42",
idempotency_key="idem-1",
)
args, kwargs = req.call_args
assert args[0] == "post"
assert args[1].endswith("/payment_links")
assert kwargs["data"]["line_items[0][price]"] == "price_1"
assert kwargs["data"]["line_items[0][quantity]"] == 2
assert kwargs["data"]["metadata[correlation_id]"] == "order-42"
assert kwargs["headers"]["Idempotency-Key"] == "idem-1"
assert result["id"] == "plink_1"
assert result["mode"] == "test"
# ── run() dispatcher ────────────────────────────────────────────────
class TestRunDispatcher:
def test_unknown_action(self):
tool = StripeTool(api_key="sk_test_x")
assert tool.run(action="bogus") == {"error": "Unknown action: bogus"}
def test_routes_get_customer(self):
tool = StripeTool(api_key="sk_test_x")
with patch.object(tool, "get_customer", return_value={"ok": True}) as m:
tool.run(action="get_customer", customer_id="cus_1")
m.assert_called_once_with(customer_id="cus_1")
def test_routes_create_payment_link(self):
tool = StripeTool(api_key="sk_test_x")
with patch.object(tool, "create_payment_link", return_value={"ok": True}) as m:
tool.run(
action="create-payment-link",
price_id="price_1",
quantity=1,
correlation_id="c1",
idempotency_key="i1",
)
m.assert_called_once_with(
price_id="price_1", quantity=1, correlation_id="c1", idempotency_key="i1"
)
# ── Module-level helper ─────────────────────────────────────────────
class TestHelper:
def test_delegates_to_tool(self):
with patch.object(StripeTool, "get_customer", return_value={"id": "cus_1"}) as m:
assert get_stripe_customer("cus_1", api_key="sk_test_x") == {"id": "cus_1"}
m.assert_called_once_with(customer_id="cus_1")
@@ -1,50 +0,0 @@
"""CI-covered guard for automatic tool discovery.
The full discovery regression suite lives at ``tests/test_tool_discovery.py``,
but the CI workflow only runs ``pytest tests/unit --ignore=tests/unit/video``.
That means the most important safety net there - proving every shipped tool
module actually parses (so discovery never silently drops a tool) - would not
execute in CI. This thin module re-runs that guard from inside the CI-covered
path so a syntactically broken shipped module fails loudly at CI time with the
pointing ``SyntaxError`` instead of surfacing later as a mystery
``AttributeError`` on ``from praisonai_tools import SomeTool``.
"""
import ast
import os
import pytest
from praisonai_tools import tools as tools_pkg
from praisonai_tools.tools._discovery import _SKIP_MODULES, build_manifest
TOOLS_DIR = os.path.dirname(tools_pkg.__file__)
def _tool_modules():
for filename in sorted(os.listdir(TOOLS_DIR)):
module_name = filename[:-3]
if (
filename.endswith(".py")
and module_name not in _SKIP_MODULES
and not module_name.startswith("_")
):
yield module_name
def test_every_shipped_module_parses_in_ci():
"""Every shipped tool module must parse under the running interpreter."""
for module in _tool_modules():
path = os.path.join(TOOLS_DIR, module + ".py")
with open(path, "r", encoding="utf-8") as fh:
source = fh.read()
try:
ast.parse(source)
except SyntaxError as exc: # pragma: no cover - fails only if a module breaks
pytest.fail(f"tools/{module}.py has a syntax error: {exc}")
def test_no_discovery_collisions_in_ci():
"""No public tool symbol may be defined in two shipped modules."""
_, collisions = build_manifest(TOOLS_DIR)
assert collisions == {}, f"Colliding tool symbols across modules: {collisions}"
-81
View File
@@ -1,81 +0,0 @@
"""Unit tests for You.com tools (no network, no API key required)."""
from unittest.mock import MagicMock, patch
from praisonai_tools.tools.youdotcom_tool import (
YouTools,
ydc,
ydc_search,
ydc_contents,
ydc_news,
ydc_images,
)
_FIND_SPEC = "praisonai_tools.tools.youdotcom_tool.util.find_spec"
def test_missing_api_key_returns_error(monkeypatch):
monkeypatch.delenv("YDC_API_KEY", raising=False)
with patch(_FIND_SPEC, return_value=object()):
for fn, arg in (
(ydc_search, "q"),
(ydc_contents, "https://example.com"),
(ydc_news, "q"),
(ydc_images, "q"),
):
result = fn(arg)
assert result == {
"error": "YDC_API_KEY environment variable is not set. Please set it to use You.com tools."
}
def test_explicit_api_key_used_without_env(monkeypatch):
monkeypatch.delenv("YDC_API_KEY", raising=False)
fake_module = MagicMock()
with patch(_FIND_SPEC, return_value=object()), patch.dict(
"sys.modules", {"youdotcom": fake_module}
):
client, error = YouTools(api_key="k")._get_client()
assert error is None
assert client is fake_module.You.return_value
fake_module.You.assert_called_once_with(api_key_auth="k")
def test_ydc_alias():
assert ydc is ydc_search
def test_search_uses_client_and_returns_dict():
response = MagicMock()
response.model_dump.return_value = {"results": {"web": [], "news": []}}
client = MagicMock()
client.search.unified.return_value = response
with patch.object(YouTools, "_get_client", return_value=(client, None)):
result = YouTools().search("ai", count=3, freshness="week")
assert result == {"results": {"web": [], "news": []}}
kwargs = client.search.unified.call_args.kwargs
assert kwargs["query"] == "ai"
assert kwargs["count"] == 3
assert kwargs["freshness"] == "week"
def test_search_exception_is_reported_as_error():
client = MagicMock()
client.search.unified.side_effect = RuntimeError("boom")
with patch.object(YouTools, "_get_client", return_value=(client, None)):
result = YouTools().search("ai")
assert "boom" in result["error"]
def test_discovered_via_package():
import praisonai_tools.tools as tools_pkg
assert tools_pkg.YouTools is YouTools
assert tools_pkg.ydc_search is ydc_search
assert tools_pkg.ydc is ydc_search
-45
View File
@@ -1,45 +0,0 @@
"""Pytest configuration for video/motion-graphics tests.
Most tests in this tree are fully mocked (protocols, dataclasses, mocked
backends) and run without the optional ``video-motion`` dependencies. Only a
subset actually constructs :class:`HtmlRenderBackend`, which hard-requires
``playwright`` and ``imageio-ffmpeg`` at construction time.
Rather than skipping the whole tree when those packages are absent (for example
a minimal ``pip install -e ".[dev]"`` where the wheels could not be resolved),
gate *only* the dependency-bound tests. Mark them with
``@pytest.mark.requires_video_deps`` and this hook skips just those when the
extras are missing, preserving coverage for the dependency-independent tests.
"""
import importlib.util
import pytest
_VIDEO_DEPS = ("playwright", "imageio_ffmpeg")
_MISSING_VIDEO_DEPS = [
name for name in _VIDEO_DEPS if importlib.util.find_spec(name) is None
]
VIDEO_DEPS_AVAILABLE = not _MISSING_VIDEO_DEPS
def pytest_configure(config):
config.addinivalue_line(
"markers",
"requires_video_deps: mark test as requiring the optional "
"video-motion extras (playwright, imageio-ffmpeg).",
)
def pytest_collection_modifyitems(config, items):
if VIDEO_DEPS_AVAILABLE:
return
skip_reason = (
"video-motion extra not installed "
"(pip install -e '.[dev,video-motion]'); missing: "
+ ", ".join(_MISSING_VIDEO_DEPS)
)
skip_marker = pytest.mark.skip(reason=skip_reason)
for item in items:
if "requires_video_deps" in item.keywords:
item.add_marker(skip_marker)
-1
View File
@@ -13,7 +13,6 @@ except ImportError:
@pytest.mark.skipif(not BACKEND_AVAILABLE, reason="Motion graphics backend not available")
@pytest.mark.requires_video_deps
class TestBackendSafety:
"""Test workspace safety features."""
+27 -48
View File
@@ -1,11 +1,10 @@
"""Unit tests for HTML render backend."""
import asyncio
import tempfile
from pathlib import Path
from unittest.mock import AsyncMock, Mock, patch
import pytest
import tempfile
import asyncio
from pathlib import Path
from unittest.mock import Mock, patch, AsyncMock
from praisonai_tools.video.motion_graphics.backend_html import HtmlRenderBackend
from praisonai_tools.video.motion_graphics.protocols import RenderOpts
@@ -14,32 +13,22 @@ from praisonai_tools.video.motion_graphics.protocols import RenderOpts
class TestHtmlRenderBackend:
"""Test HTML render backend."""
@pytest.mark.requires_video_deps
def test_import_error_handling(self):
"""Test that import errors are handled properly."""
with (
patch('praisonai_tools.video.motion_graphics.backend_html.async_playwright', None),
pytest.raises(ImportError, match="Playwright not installed"),
):
HtmlRenderBackend()
# Ensure the playwright guard passes so the imageio-ffmpeg guard is the
# one under test, regardless of whether the optional deps are installed.
with (
patch('praisonai_tools.video.motion_graphics.backend_html.async_playwright', Mock()),
patch('praisonai_tools.video.motion_graphics.backend_html.imageio_ffmpeg', None),
pytest.raises(ImportError, match="imageio-ffmpeg not installed"),
):
HtmlRenderBackend()
with patch('praisonai_tools.video.motion_graphics.backend_html.async_playwright', None):
with pytest.raises(ImportError, match="Playwright not installed"):
HtmlRenderBackend()
with patch('praisonai_tools.video.motion_graphics.backend_html.imageio_ffmpeg', None):
with pytest.raises(ImportError, match="imageio-ffmpeg not installed"):
HtmlRenderBackend()
def test_init_success(self):
"""Test successful initialization."""
with (
patch('praisonai_tools.video.motion_graphics.backend_html.async_playwright', Mock()),
patch('praisonai_tools.video.motion_graphics.backend_html.imageio_ffmpeg', Mock()),
):
backend = HtmlRenderBackend()
assert backend is not None
with patch('praisonai_tools.video.motion_graphics.backend_html.async_playwright', Mock()):
with patch('praisonai_tools.video.motion_graphics.backend_html.imageio_ffmpeg', Mock()):
backend = HtmlRenderBackend()
assert backend is not None
class TestLinting:
@@ -47,11 +36,9 @@ class TestLinting:
def setup_method(self):
"""Set up test fixtures."""
with (
patch('praisonai_tools.video.motion_graphics.backend_html.async_playwright', Mock()),
patch('praisonai_tools.video.motion_graphics.backend_html.imageio_ffmpeg', Mock()),
):
self.backend = HtmlRenderBackend()
with patch('praisonai_tools.video.motion_graphics.backend_html.async_playwright', Mock()):
with patch('praisonai_tools.video.motion_graphics.backend_html.imageio_ffmpeg', Mock()):
self.backend = HtmlRenderBackend()
@pytest.mark.asyncio
async def test_lint_missing_index_html(self):
@@ -211,11 +198,9 @@ class TestRendering:
def setup_method(self):
"""Set up test fixtures."""
with (
patch('praisonai_tools.video.motion_graphics.backend_html.async_playwright', Mock()),
patch('praisonai_tools.video.motion_graphics.backend_html.imageio_ffmpeg', Mock()),
):
self.backend = HtmlRenderBackend()
with patch('praisonai_tools.video.motion_graphics.backend_html.async_playwright', Mock()):
with patch('praisonai_tools.video.motion_graphics.backend_html.imageio_ffmpeg', Mock()):
self.backend = HtmlRenderBackend()
@pytest.mark.asyncio
async def test_render_missing_index_html(self):
@@ -336,10 +321,8 @@ class TestRendering:
mock_process.returncode = 0
mock_subprocess.return_value = mock_process
with (
patch.object(self.backend, '_get_ffmpeg_path', return_value='ffmpeg'),
tempfile.TemporaryDirectory() as tmpdir,
):
with patch.object(self.backend, '_get_ffmpeg_path', return_value='ffmpeg'):
with tempfile.TemporaryDirectory() as tmpdir:
# Create fake frame files
frame_dir = Path(tmpdir)
frame_paths = []
@@ -374,10 +357,8 @@ class TestRendering:
mock_process.returncode = 1
mock_subprocess.return_value = mock_process
with (
patch.object(self.backend, '_get_ffmpeg_path', return_value='ffmpeg'),
tempfile.TemporaryDirectory() as tmpdir,
):
with patch.object(self.backend, '_get_ffmpeg_path', return_value='ffmpeg'):
with tempfile.TemporaryDirectory() as tmpdir:
frame_path = Path(tmpdir) / "frame_000000.png"
frame_path.write_bytes(b"fake")
@@ -397,10 +378,8 @@ class TestRendering:
mock_process.kill = Mock()
mock_subprocess.return_value = mock_process
with (
patch.object(self.backend, '_get_ffmpeg_path', return_value='ffmpeg'),
tempfile.TemporaryDirectory() as tmpdir,
):
with patch.object(self.backend, '_get_ffmpeg_path', return_value='ffmpeg'):
with tempfile.TemporaryDirectory() as tmpdir:
frame_path = Path(tmpdir) / "frame_000000.png"
frame_path.write_bytes(b"fake")
+3 -11
View File
@@ -6,11 +6,11 @@ from pathlib import Path
from unittest.mock import patch
from praisonai_tools.video.motion_graphics.agent import (
RenderTools,
_resolve_backend,
create_motion_graphics_agent,
RenderTools,
_resolve_backend
)
from praisonai_tools.video.motion_graphics.protocols import LintResult, RenderResult
from praisonai_tools.video.motion_graphics.protocols import RenderResult, LintResult
class MockAgent:
@@ -96,7 +96,6 @@ class TestRenderTools:
class TestResolveBackend:
"""Test backend resolution."""
@pytest.mark.requires_video_deps
def test_resolve_string_backend(self):
"""Test resolving string backend specification."""
backend = _resolve_backend("html")
@@ -120,7 +119,6 @@ class TestResolveBackend:
class TestCreateMotionGraphicsAgent:
"""Test motion graphics agent factory."""
@pytest.mark.requires_video_deps
@patch('praisonai_tools.video.motion_graphics.agent.Agent', MockAgent)
@patch('praisonai_tools.video.motion_graphics.agent.FileTools', MockFileTools)
def test_create_agent_defaults(self):
@@ -139,7 +137,6 @@ class TestCreateMotionGraphicsAgent:
"lint_composition", "render_composition"} <= tool_names
assert "motion graphics specialist" in agent.instructions.lower()
@pytest.mark.requires_video_deps
@patch('praisonai_tools.video.motion_graphics.agent.Agent', MockAgent)
@patch('praisonai_tools.video.motion_graphics.agent.FileTools', MockFileTools)
def test_create_agent_custom_params(self):
@@ -162,7 +159,6 @@ class TestCreateMotionGraphicsAgent:
with pytest.raises(ImportError, match="praisonaiagents not available"):
create_motion_graphics_agent()
@pytest.mark.requires_video_deps
@patch('praisonai_tools.video.motion_graphics.agent.Agent', MockAgent)
@patch('praisonai_tools.video.motion_graphics.agent.FileTools', MockFileTools)
def test_create_agent_auto_workspace(self):
@@ -187,7 +183,6 @@ class TestCreateMotionGraphicsAgent:
assert agent._motion_graphics_backend is mock_backend
@pytest.mark.requires_video_deps
@patch('praisonai_tools.video.motion_graphics.agent.Agent', MockAgent)
@patch('praisonai_tools.video.motion_graphics.agent.FileTools', MockFileTools)
def test_create_agent_workspace_creation(self):
@@ -200,7 +195,6 @@ class TestCreateMotionGraphicsAgent:
assert workspace_path.exists()
assert agent._motion_graphics_workspace == workspace_path
@pytest.mark.requires_video_deps
@patch('praisonai_tools.video.motion_graphics.agent.Agent', MockAgent)
@patch('praisonai_tools.video.motion_graphics.agent.FileTools', MockFileTools)
def test_create_agent_skill_included(self):
@@ -213,7 +207,6 @@ class TestCreateMotionGraphicsAgent:
assert "timeline" in agent.instructions
assert "window.__timelines" in agent.instructions
@pytest.mark.requires_video_deps
@patch('praisonai_tools.video.motion_graphics.agent.Agent', MockAgent)
@patch('praisonai_tools.video.motion_graphics.agent.FileTools', MockFileTools)
def test_create_agent_output_validation(self):
@@ -226,7 +219,6 @@ class TestCreateMotionGraphicsAgent:
assert "Never fabricate file paths" in agent.instructions
assert "3 failed attempts" in agent.instructions
@pytest.mark.requires_video_deps
@patch('praisonai_tools.video.motion_graphics.agent.Agent', MockAgent)
@patch('praisonai_tools.video.motion_graphics.agent.FileTools', MockFileTools)
def test_agent_tools_configuration(self):
@@ -3,10 +3,10 @@
import pytest
from pathlib import Path
from praisonai_tools.video.motion_graphics.protocols import (
LintResult,
RenderBackendProtocol,
RenderOpts,
LintResult,
RenderResult,
RenderBackendProtocol
)
@@ -112,7 +112,6 @@ class TestRenderResult:
class TestRenderBackendProtocol:
"""Test RenderBackendProtocol protocol."""
@pytest.mark.requires_video_deps
def test_protocol_runtime_checkable(self):
"""Test that protocol is runtime checkable."""
from praisonai_tools.video.motion_graphics.backend_html import HtmlRenderBackend
+2 -3
View File
@@ -1,13 +1,12 @@
"""Tests for render retry functionality."""
import pytest
import tempfile
from pathlib import Path
import pytest
try:
from praisonai_tools.video.motion_graphics.agent import RenderTools
from praisonai_tools.video.motion_graphics.protocols import RenderOpts, RenderResult
from praisonai_tools.video.motion_graphics.protocols import RenderResult, RenderOpts
AGENT_AVAILABLE = True
except ImportError:
AGENT_AVAILABLE = False
+1
View File
@@ -0,0 +1 @@
<html>mock visualization</html>