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Author SHA1 Message Date
Mervin Praison 911483c92c Release v3.0.0 2025-12-31 18:55:59 +00:00
Mervin Praison 4ffb9d6e3f Release v2.9.2 2025-12-31 17:17:17 +00:00
Mervin Praison b686e5b00f Release v2.9.1 2025-12-31 16:42:54 +00:00
Mervin Praison d8d84ee3e3 Release v2.9.0 2025-12-31 15:49:07 +00:00
Mervin Praison 9f2c4d10b5 Release v2.8.9 2025-12-31 14:05:30 +00:00
Mervin Praison 42a86c831f Release v2.8.8 2025-12-31 12:46:10 +00:00
Mervin Praison 48443b11d6 Release v2.8.7 2025-12-31 12:28:44 +00:00
Mervin Praison 71745aa14a Release v2.8.6 2025-12-31 12:27:20 +00:00
Mervin Praison 4f309ec16d Release v2.8.5 2025-12-31 12:00:29 +00:00
Mervin Praison e48afc8993 Release v2.8.4 2025-12-31 11:39:37 +00:00
Mervin Praison 90950f8889 Release v2.8.3 2025-12-31 11:02:57 +00:00
Mervin Praison 56f36e2593 feat: bump version to 1.4.0 and add AI SDK integration dependencies
- Update package.json version from 1.3.6 to 1.4.0
- Update FEATURE_PARITY_TRACKER.json to v1.3.0 (Phase 5 Complete)
- Add AI SDK wrapper features: generateText, streamText, generateObject, streamObject, generateImage, embed, embedMany
- Add server adapters for http, express, hono, fastify, nest
- Add Next.js integration with createRouteHandler and createPagesHandler
- Add MCP client tools: createMCP, getMCPClient, mcpToolsToAITools
2025-12-31 01:39:39 +00:00
Mervin Praison 7aa67ad27c Release v2.8.2 2025-12-30 23:17:48 +00:00
Mervin Praison 307df443ef Release v2.8.1 2025-12-30 17:47:16 +00:00
Mervin Praison 6434a87b60 chore: remove completed AI SDK verification doc and bump version to 1.3.6
- Remove ai-sdk-backbone-verification.md (all tasks completed)
- Update package.json version from 1.3.5 to 1.3.6
- Refactor agent classes to use lazy-loaded AI SDK backend via resolveBackend()
- Convert direct createProvider() calls to async getProvider() pattern
- Add provider promise caching to prevent duplicate backend initialization
- Update ContextAgent, EnhancedAgent, ImageAgent, and PromptExpanderAgent classes
2025-12-30 17:15:40 +00:00
Mervin Praison 97d5b6db0d feat: add AI SDK backend support and embedding capabilities to Agent class
- Add AI SDK backend resolution with lazy initialization via getBackend()
- Add embed() method supporting single/batch text embeddings
- Add getBackendSource() to check backend type (ai-sdk/native/custom/legacy)
- Add getModel() to retrieve agent's model string
- Parse model string to extract provider/model ID for backend selection
- Use AI SDK backend for non-OpenAI providers (streaming and non-streaming)
- Export backend resolver an
2025-12-30 16:52:46 +00:00
Mervin Praison 4996a9f9fa Merge remote-tracking branch 'origin/pr-1097-fixes' 2025-12-30 16:15:49 +00:00
Mervin Praison 54f4a96cba test: add comprehensive ImportError tests for MCP optional import
- Add test for MCP class ImportError when mcp package unavailable
- Add test for SSEMCPClient ImportError when mcp unavailable
- Add test for HTTPStreamMCPClient ImportError when mcp unavailable
- Add test for HTTPStreamMCPClient ImportError when aiohttp unavailable
- Fix unused import lint warnings (remove sys, add noqa for MCP)

These tests verify that actionable error messages with install instructions
are shown when users try to use MCP functionality without the mcp package.
2025-12-30 16:14:15 +00:00
Mervin Praison e59be8f0fd Merge pull request #1096 from majiayu000/fix/issue-1091-mcp-optional-import
fix: make MCP package import optional to prevent errors when not installed
2025-12-30 16:09:06 +00:00
3086 changed files with 43941 additions and 536425 deletions

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-51
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@@ -1,51 +0,0 @@
# PraisonAI Environment Variables
# Copy this file to .env and update with your actual values
# === Required ===
OPENAI_API_KEY=sk-... # OpenAI key for LLM calls. Get yours at https://platform.openai.com
# === Required for Claw web-search tool ===
TAVILY_API_KEY=tvly-... # Get yours at https://app.tavily.com (free tier available)
# === Optional: Claw dashboard security ===
PRAISONAI_ALLOW_LOCAL_TOOLS=0 # Set to 1 to enable local shell tools (security risk)
# === Optional: Alternative LLM Providers ===
ANTHROPIC_API_KEY=sk-ant-... # Anthropic Claude models
GOOGLE_API_KEY=... # Google Gemini models
GROQ_API_KEY=gsk_... # Groq (fast inference)
COHERE_API_KEY=... # Cohere models
AZURE_OPENAI_API_KEY=... # Azure OpenAI
AZURE_OPENAI_ENDPOINT=... # Azure OpenAI endpoint
# === Optional: Memory backends ===
MEM0_API_KEY=... # Mem0 memory service
REDIS_URL=redis://localhost:6379 # Redis for state management
# === Optional: Observability ===
LANGFUSE_SECRET_KEY=sk-lf-... # Langfuse tracing
LANGFUSE_PUBLIC_KEY=pk-lf-... # Langfuse public key
# === Optional: Bot platforms ===
TELEGRAM_BOT_TOKEN=... # Telegram bot token
DISCORD_BOT_TOKEN=... # Discord bot token
SLACK_BOT_TOKEN=xoxb-... # Slack bot token
SLACK_APP_TOKEN=xapp-... # Slack app token
WHATSAPP_ACCESS_TOKEN=... # WhatsApp bot access token
WHATSAPP_PHONE_NUMBER_ID=... # WhatsApp phone number ID
# === Optional: Database ===
DATABASE_URL=sqlite:///~/.praison/database.sqlite # Database connection string
# === Optional: Tool Security ===
# ALLOWED_TOOLS=search,send_message # Whitelist specific tools to prevent name collisions
# Useful in multi-environment setups with overlapping tool names
# Leave unset to use all tools (with collision warnings)
# Do NOT set to empty string: that's treated as configuration error
# In CI, unknown tool names in the whitelist cause strict startup failure
# HERMES_ONLY_TOOLS=search,send_message # (Deprecated) Backward compatibility alias for ALLOWED_TOOLS
# === Optional: Development ===
LOGLEVEL=INFO # Logging level (DEBUG, INFO, WARNING, ERROR)
CHAINLIT_AUTH_SECRET=... # Chainlit authentication secret
DEBUG=false # Enable debug mode
+21 -61
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@@ -5,9 +5,6 @@ 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
@@ -70,8 +67,6 @@ runs:
- name: Install GitHub MCP Server
shell: bash
env:
INPUT_GITHUB_TOKEN: ${{ inputs.github_token }}
run: |
claude mcp add-json github '{
"command": "docker",
@@ -84,7 +79,7 @@ runs:
"ghcr.io/github/github-mcp-server:sha-ff3036d"
],
"env": {
"GITHUB_PERSONAL_ACCESS_TOKEN": "'"${INPUT_GITHUB_TOKEN}"'"
"GITHUB_PERSONAL_ACCESS_TOKEN": "${{ inputs.github_token }}"
}
}'
@@ -209,44 +204,14 @@ runs:
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.
Please analyze the request and provide helpful assistance. You have access to repository tools and can help with:
- Code analysis and implementation
- GitHub workflows and automation
- Pull request reviews and feedback
- Issue resolution and bug fixes
- Documentation updates
- Testing and deployment
Respond naturally and helpfully to the user's request using the available tools.
EOF
@@ -256,14 +221,6 @@ runs:
- name: Run Claude Code
if: env.SKIP_EXECUTION != 'true'
shell: bash
env:
ANTHROPIC_API_KEY: ${{ inputs.anthropic_api_key }}
CLAUDE_CODE_OAUTH_TOKEN: ${{ inputs.claude_code_oauth_token }}
GITHUB_TOKEN: ${{ inputs.github_token }}
INPUT_MAX_TURNS: ${{ inputs.max_turns }}
INPUT_ALLOWED_TOOLS: ${{ inputs.allowed_tools }}
INPUT_DISALLOWED_TOOLS: ${{ inputs.disallowed_tools }}
INPUT_TIMEOUT_MINUTES: ${{ inputs.timeout_minutes }}
run: |
echo "🚀 Running Claude Code with GitHub context..."
@@ -271,26 +228,29 @@ runs:
CMD_ARGS=("-p" "--verbose" "--output-format" "stream-json")
# Add max turns if specified
if [[ -n "$INPUT_MAX_TURNS" ]]; then
CMD_ARGS+=("--max-turns" "$INPUT_MAX_TURNS")
if [[ -n "${{ inputs.max_turns }}" ]]; then
CMD_ARGS+=("--max-turns" "${{ inputs.max_turns }}")
fi
# Add allowed tools (include GitHub tools by default)
TOOLS="mcp__github__get_issue,mcp__github__get_issue_comments,mcp__github__update_issue,mcp__github__search_issues,mcp__github__list_issues,mcp__github__create_comment,Read,Write,Edit,Bash"
if [[ -n "$INPUT_ALLOWED_TOOLS" ]]; then
TOOLS="$TOOLS,$INPUT_ALLOWED_TOOLS"
if [[ -n "${{ inputs.allowed_tools }}" ]]; then
TOOLS="$TOOLS,${{ inputs.allowed_tools }}"
fi
CMD_ARGS+=("--allowedTools" "$TOOLS")
# Add disallowed tools
if [[ -n "$INPUT_DISALLOWED_TOOLS" ]]; then
CMD_ARGS+=("--disallowedTools" "$INPUT_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=$(($INPUT_TIMEOUT_MINUTES * 60))
timeout $TIMEOUT_SECONDS claude "${CMD_ARGS[@]}" < "$PROMPT_FILE"
TIMEOUT_SECONDS=$((${{ inputs.timeout_minutes }} * 60))
timeout $TIMEOUT_SECONDS claude "${CMD_ARGS[@]}" < "${{ env.PROMPT_FILE }}"
echo "✅ Claude Code execution completed"
echo "✅ Claude Code execution completed"
env:
ANTHROPIC_API_KEY: ${{ inputs.anthropic_api_key }}
GITHUB_TOKEN: ${{ inputs.github_token }}
@@ -6,8 +6,8 @@ inputs:
description: "Timeout in minutes for execution"
required: false
default: "5"
claude_code_oauth_token:
description: "Claude Code OAuth token for Pro subscription access"
anthropic_api_key:
description: "Anthropic API key"
required: true
github_token:
description: "GitHub token with repo and issues permissions"
@@ -19,11 +19,9 @@ runs:
- name: Checkout repository code
uses: actions/checkout@v4
with:
persist-credentials: false
fetch-depth: 0
- name: Create prompt
id: generate_prompt
- name: Create prompt file
shell: bash
run: |
mkdir -p /tmp/claude-prompts
@@ -77,16 +75,13 @@ runs:
- 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 }}
prompt_file: /tmp/claude-prompts/claude-issue-triage-prompt.txt
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"
install_github_mcp: "true"
timeout_minutes: ${{ inputs.timeout_minutes }}
claude_code_oauth_token: ${{ inputs.claude_code_oauth_token }}
anthropic_api_key: ${{ inputs.anthropic_api_key }}
github_token: ${{ inputs.github_token }}
+6 -15
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@@ -22,12 +22,6 @@ inputs:
To enable observability with Google Cloud, include:
{"telemetry": {"enabled": true, "target": "gcp"}, "sandbox": false}
required: false
model:
description: |
The Gemini model to use. Options: gemini-2.5-pro, gemini-2.5-flash, gemini-2.5-flash-lite.
Use flash-lite for highest free-tier quota (1,000 RPD).
required: false
default: 'gemini-3.1-flash-lite-preview'
version:
description: |
The version of @google/gemini-cli to execute.
@@ -57,15 +51,13 @@ runs:
- name: Install Gemini CLI
id: install
env:
INPUT_VERSION: ${{ inputs.version }}
run: |
if [[ "$INPUT_VERSION" == "latest" || "$INPUT_VERSION" =~ ^[0-9]+\.[0-9]+\.[0-9]+(-[a-zA-Z0-9\.-]+)?(\+[a-zA-Z0-9\.-]+)?$ ]]; then
echo "Installing Gemini CLI from npm: @google/gemini-cli@$INPUT_VERSION"
npm install -g @google/gemini-cli@$INPUT_VERSION
if [[ "${{ inputs.version }}" == "latest" || "${{ inputs.version }}" =~ ^[0-9]+\.[0-9]+\.[0-9]+(-[a-zA-Z0-9\.-]+)?(\+[a-zA-Z0-9\.-]+)?$ ]]; then
echo "Installing Gemini CLI from npm: @google/gemini-cli@${{ inputs.version }}"
npm install -g @google/gemini-cli@${{ inputs.version }}
else
echo "Installing Gemini CLI from GitHub: github:google-gemini/gemini-cli#$INPUT_VERSION"
npm install -g github:google-gemini/gemini-cli#$INPUT_VERSION
echo "Installing Gemini CLI from GitHub: github:google-gemini/gemini-cli#${{ inputs.version }}"
npm install -g github:google-gemini/gemini-cli#${{ inputs.version }}
fi
echo "Verifying installation:"
if command -v gemini >/dev/null 2>&1; then
@@ -78,11 +70,10 @@ runs:
- name: Run Gemini CLI
run: |
gemini --yolo --model "$GEMINI_MODEL" --prompt "$PROMPT"
gemini --yolo --prompt "$PROMPT"
shell: bash
env:
GEMINI_API_KEY: ${{ inputs.GEMINI_API_KEY }}
GEMINI_MODEL: ${{ inputs.model }}
PROMPT: ${{ inputs.prompt }}
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-72
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@@ -1,72 +0,0 @@
framework: "praisonai"
process: workflow
topic: "Autonomous Issue Resolution"
planning: false
roles:
issue_analyst:
role: "GitHub Issue Analyst"
goal: "Read the GitHub issue, understand the required changes, and map the problem to the local codebase"
backstory: "You are an expert software analyst who reads bug reports and feature requests. You excel at taking a problem description and finding exactly which files in the codebase need to be modified. Your primary job is discovery and planning."
tools:
- "execute_command"
software_engineer:
role: "Autonomous Software Engineer"
goal: "Implement required code changes on a branch, run tests, commit, and push"
backstory: "You are a senior software engineer. You always branch first, implement changes using shell commands, verify with git diff, run tests, then commit and push. You never create a Pull Request unless the issue body explicitly requests one."
tools:
- "execute_command"
- "github_create_branch"
- "github_commit_and_push"
- "github_create_pull_request"
steps:
- name: Analyze Issue
agent: issue_analyst
action: >
Thoroughly analyze the issue and the repository. Follow these steps in order.
First, set up git identity: execute_command 'git config user.name PraisonAI' then
execute_command 'git config user.email [email protected]'. Do NOT pass cwd.
Second, read the issue: execute_command 'cat .github/triage-context.md'. Do NOT pass cwd.
Third, read architecture guidelines: execute_command 'cat src/praisonai-agents/AGENTS.md'.
Fourth, decide if this issue requires code changes:
- If YES: identify the exact files and lines that must change. Output a concrete file-level plan.
- If NO (question, discussion, duplicate, invalid): say so clearly. No code changes needed.
Output: routing decision (Core SDK / Wrapper / Tools / No-change), validation result, and exact files/lines to change.
expected_output: A decision on whether code changes are needed, and if so a concrete file-level plan.
- name: Implement Fix
agent: software_engineer
action: >
You are working inside the repository at /Users/praison/praisonai-package.
Do NOT ask for confirmation. Do NOT use placeholder paths. Act immediately.
Read the analyst's output first. If the analyst said NO code changes are needed, stop here and
output a brief explanation — do NOT create a branch or PR.
If code changes ARE needed, follow these steps:
Step 1 — Create branch: github_create_branch with branch_name=praisonai/issue-{{ISSUE_NUMBER}}.
Step 2 — Implement changes using execute_command (no cwd argument).
To insert a line: python3 -c "lines=open('FILE').readlines(); lines.insert(N,'LINE\n'); open('FILE','w').writelines(lines)"
To replace text: python3 -c "t=open('FILE').read(); open('FILE','w').write(t.replace('OLD','NEW'))"
After each edit verify: execute_command 'git diff'
Step 3 — Run tests: execute_command 'python3 -m pytest src/praisonai-agents/tests/ -x -q --timeout=30 -p no:warnings'
Step 4 — Commit and push: github_commit_and_push with a descriptive commit_message.
Step 5 — Check if the issue body EXPLICITLY contains the phrase "create pull request" or "create PR"
(case-insensitive). ONLY in that case create a PR using github_create_pull_request with
title='fix: resolve issue #{{ISSUE_NUMBER}}',
body='Fixes #{{ISSUE_NUMBER}}.\n\nAutonomously resolved by PraisonAI.',
head_branch=praisonai/issue-{{ISSUE_NUMBER}}, base_branch=main.
Otherwise do NOT create a PR — just confirm the branch was pushed successfully.
expected_output: Either "No code changes needed", or "Branch pushed, no PR requested", or "Branch pushed and PR created at URL".
-116
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@@ -1,116 +0,0 @@
framework: "praisonai"
topic: "Pull Request Code Review Analysis"
roles:
security_reviewer:
role: "Security Code Reviewer"
goal: "Identify security vulnerabilities, authentication issues, input validation problems, and unsafe code practices in the PR changes"
backstory: "You are a cybersecurity expert specializing in code analysis. You have extensive experience in identifying common security flaws like injection attacks, authentication bypasses, exposed secrets, and unsafe data handling patterns."
tools:
- "execute_command"
performance_reviewer:
role: "Performance Code Reviewer"
goal: "Analyze code changes for performance implications, identify bottlenecks, inefficient algorithms, and resource usage issues"
backstory: "You are a performance optimization specialist with deep knowledge of algorithm efficiency, memory management, and system performance. You excel at spotting code that could cause performance degradation."
tools:
- "execute_command"
maintainability_reviewer:
role: "Code Quality & Maintainability Reviewer"
goal: "Evaluate code structure, readability, documentation, naming conventions, and adherence to best practices"
backstory: "You are a software engineering expert focused on code quality and maintainability. You ensure code follows established patterns, is well-documented, and will be easy for future developers to understand and modify."
tools:
- "execute_command"
lead_reviewer:
role: "Lead Technical Reviewer"
goal: "Synthesize all review feedback, make final recommendations, and post comprehensive review comments to the GitHub PR"
backstory: "You are a senior technical lead responsible for final review decisions. You coordinate input from security, performance, and maintainability reviewers to provide balanced, actionable feedback to the development team."
tools:
- "execute_command"
steps:
- name: security_analysis
agent: security_reviewer
action: |
Analyze the PR diff for security issues:
1. Extract PR details: `echo "$PR_DATA"`
2. Get changed files: `echo "$CHANGED_FILES"`
3. Review full diff: `gh pr diff ${PR_NUMBER}`
4. Look for:
- Hardcoded secrets, API keys, passwords
- SQL injection vulnerabilities
- XSS vulnerabilities
- Authentication/authorization bypasses
- Unsafe file operations
- Command injection risks
- Missing input validation
- Exposed sensitive data
5. Document findings with file paths and line numbers
expected_output: "Detailed security analysis report with specific vulnerabilities found, severity levels, and remediation suggestions"
- name: performance_analysis
agent: performance_reviewer
action: |
Analyze the PR diff for performance issues:
1. Review algorithm complexity changes
2. Check for inefficient database queries
3. Identify memory leaks or excessive allocations
4. Look for hot-path regressions
5. Check for blocking I/O operations
6. Analyze module-level imports that could slow startup
7. Review caching implementations
8. Check for recursive operations without termination
9. Document performance concerns with impact estimates
expected_output: "Performance analysis report highlighting bottlenecks, efficiency concerns, and optimization recommendations"
- name: maintainability_analysis
agent: maintainability_reviewer
action: |
Analyze the PR diff for code quality and maintainability:
1. Check naming conventions consistency
2. Evaluate code structure and organization
3. Review documentation completeness
4. Check for DRY violations
5. Analyze error handling patterns
6. Review test coverage for changes
7. Check adherence to repository coding standards
8. Evaluate API design consistency
9. Look for technical debt introduction
expected_output: "Code quality analysis with specific recommendations for improving maintainability and readability"
- name: final_review
agent: lead_reviewer
action: |
Synthesize all reviews and post final comprehensive feedback:
1. Collect input from security, performance, and maintainability reviews
2. Prioritize findings by severity (Critical, High, Medium, Low)
3. Create structured review comment using this format:
## 📋 Review Summary
[2-3 sentence overview and assessment]
## 🔍 General Feedback
[Overall patterns and observations]
## 🎯 Specific Feedback
### 🔴 Critical (if any)
[Security vulnerabilities, breaking changes, major bugs]
### 🟡 High (if any)
[Performance issues, design flaws, significant bugs]
### 🟢 Medium (if any)
[Code quality improvements, minor optimizations]
### 🔵 Low (if any)
[Documentation, naming suggestions, minor refactoring]
## ✅ Highlights (if any)
[Positive aspects worth mentioning]
4. Post comprehensive review: `echo "[REVIEW_CONTENT]" | gh pr comment ${PR_NUMBER} -F -`
5. If critical issues found, suggest not merging until resolved
expected_output: "Final review comment posted to GitHub PR with comprehensive analysis from all reviewers"
dependencies: [security_analysis, performance_analysis, maintainability_analysis]
-3
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@@ -1,3 +0,0 @@
# GitHub Issue #1350: Add debug log on successful branch checkout
The github_create_branch function in src/praisonai-agents/praisonaiagents/tools/github_tools.py should call logger.debug after a successful checkout.
+11 -31
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@@ -1,46 +1,26 @@
name: Auto Issue Comment
name: Auto Issue Comment with PR Creation
on:
workflow_dispatch:
# issues:
# types: [opened]
issues:
types: [opened]
jobs:
# Trigger Claude by adding the 'claude' label (only if not already labeled)
# Note: @claude in comments only works from human users (not bots)
# The claude.yml workflow listens for issues:labeled event with 'claude' label
trigger-claude:
# Skip if issue was already created with 'claude' label to avoid double-trigger
if: |
!contains(toJSON(github.event.issue.labels), 'claude')
add-comment:
runs-on: ubuntu-latest
permissions:
issues: write
contents: write
pull-requests: write
actions: read
steps:
- name: Add claude label to trigger analysis
- name: Add automated comment
uses: actions/github-script@v7
with:
github-token: ${{ secrets.GH_TOKEN }}
script: |
// Check if 'claude' label already exists on this issue
const labels = context.payload.issue.labels.map(l => l.name);
if (labels.includes('claude')) {
console.log('Issue already has claude label, skipping');
return;
}
// Add label to trigger claude.yml via issues:labeled event
await github.rest.issues.addLabels({
github.rest.issues.createComment({
issue_number: context.issue.number,
owner: context.repo.owner,
repo: context.repo.repo,
labels: ['claude']
});
// Also post instructions as a comment for context
await github.rest.issues.createComment({
issue_number: context.issue.number,
owner: context.repo.owner,
repo: context.repo.repo,
body: '🤖 Auto-triaging with Claude. Analyzing issue and implementing a fix...\n\nClaude will:\n1. Classify this issue\n2. Search codebase for root cause\n3. Implement a minimal fix following AGENTS.md\n4. Create a PR with the changes'
});
body: '@claude review this issue and do a detailed analysis and fix this if the existing code doesn\'t have the solution implemented. Making sure it has backward compatibility, no existing features removed. After making those changes, again review the applied changes. Use @web to search if you dont know any information or to find the latest documentation or to find the latest version. Run the code if you think you need to run it to test it. Minimal code change to start with if required any changes. MAINLY IT SHOULD NOT IMPACT ON THE CURRENT SPEED OF EXECUTION of existing features, not increasing the overhead. **Please create a PR using gh tool with your changes**.'
})
+5 -507
View File
@@ -1,525 +1,23 @@
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]
pull_request_review:
types: [submitted]
pull_request:
types: [opened]
env:
MAX_POLL_ATTEMPTS: 20
POLL_DELAY_MS: 30000
CLAUDE_TRIGGER_LOGINS: '["MervinPraison","github-actions[bot]"]'
jobs:
# ================================================================
# 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, 'summarize by coderabbit')
add-comment:
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
- name: Add automated comment
uses: actions/github-script@v7
with:
github-token: ${{ secrets.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({
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: ${{ secrets.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
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 }}
with:
github-token: ${{ secrets.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');
core.setOutput('comments_count', comments.data.length.toString());
// Collect all bot reviewer comments for context
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
with:
github-token: ${{ secrets.GH_TOKEN }}
script: |
const comments = await github.rest.issues.listComments({issue_number: context.issue.number, 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 claudeBody = '@claude You are the FINAL architecture reviewer. If the branch is under MervinPraison/PraisonAI (not a fork), you are able to make modifications to this branch and push directly. SCOPE: Focus ONLY on Python packages (praisonaiagents, praisonai). Do NOT modify praisonai-rust or praisonai-ts. ' + 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' +
'Phase 1: Review per AGENTS.md principles (protocol-driven, backward compatible, no perf impact).\n' +
'Phase 2: FIX valid issues found by prior reviewers.\n' +
'Phase 3: Provide final verdict (approve or request changes).';
await github.rest.issues.createComment({issue_number: context.issue.number, owner: context.repo.owner, repo: context.repo.repo, body: claudeBody});
console.log('Claude fallback triggered on PR #' + context.issue.number + ' 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:
- 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: ${{ secrets.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: ${{ secrets.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: ${{ secrets.GH_TOKEN }}
script: |
const pr = parseInt(process.env.PR_NUMBER, 10);
await github.rest.issues.createComment({
issue_number: pr,
owner: context.repo.owner,
repo: context.repo.repo,
body: '@claude You are the FINAL architecture reviewer. If the branch is under MervinPraison/PraisonAI (not a fork), you are able to make modifications to this branch and push directly. SCOPE: Focus ONLY on Python packages (praisonaiagents, praisonai). Do NOT modify praisonai-rust or praisonai-ts. Read ALL comments above from Gemini, Qodo, CodeRabbit, and Copilot carefully before responding.\n\n**Phase 1: Review per AGENTS.md**\n1. Protocol-driven: check heavy implementations vs core SDK\n2. Backward compatible: ensure zero feature regressions\n3. Performance: no hot-path regressions\n\n**Phase 2: FIX Valid Issues**\n4. For any VALID bugs or architectural flaws found by Gemini, CodeRabbit, Qodo, Copilot, or any other reviewer: implement the fix\n5. Push all code fixes directly to THIS branch (do NOT create a new PR)\n6. Comment a summary of exact files modified and what you skipped\n\n**Phase 3: Final Verdict**\n7. If all issues are resolved, approve the PR / close the Issue\n8. If blocking issues remain, request changes / leave clear action items'
});
console.log(`Claude triggered on PR #${pr}`);
# ================================================================
# 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: ${{ secrets.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: ${{ secrets.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: ${{ secrets.GH_TOKEN }}
script: |
const pr = parseInt(process.env.PR_NUMBER, 10);
await github.rest.issues.createComment({
issue_number: pr,
owner: context.repo.owner,
repo: context.repo.repo,
body: '@claude You are the FINAL architecture reviewer. If the branch is under MervinPraison/PraisonAI (not a fork), you are able to make modifications to this branch and push directly. SCOPE: Focus ONLY on Python packages (praisonaiagents, praisonai). Do NOT modify praisonai-rust or praisonai-ts. Read ALL comments above from Gemini, Qodo, CodeRabbit, and Copilot carefully before responding.\n\n**Phase 1: Review per AGENTS.md**\n1. Protocol-driven: check heavy implementations vs core SDK\n2. Backward compatible: ensure zero feature regressions\n3. Performance: no hot-path regressions\n\n**Phase 2: FIX Valid Issues**\n4. For any VALID bugs or architectural flaws found by Gemini, CodeRabbit, Qodo, Copilot, or any other reviewer: implement the fix\n5. Push all code fixes directly to THIS branch (do NOT create a new PR)\n6. Comment a summary of exact files modified and what you skipped\n\n**Phase 3: Final Verdict**\n7. If all issues are resolved, approve the PR / close the Issue\n8. If blocking issues remain, request changes / leave clear action items'
});
console.log(`Claude triggered on PR #${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: ${{ secrets.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: ${{ secrets.GH_TOKEN }}
script: |
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 (not a fork), you are able to make modifications to this branch and push directly. SCOPE: Focus ONLY on Python packages (praisonaiagents, praisonai). Do NOT modify praisonai-rust or praisonai-ts. Read ALL analysis and reviews above carefully (Gemini, CodeRabbit, Qodo, Copilot, etc).\n\n**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\n\n**Phase 2: FIX Valid Issues**\n4. For any VALID bugs or architectural flaws found by Gemini, CodeRabbit, Qodo, Copilot, or any other reviewer: implement the fix\n5. Push all code fixes directly to THIS branch (do NOT create a new PR)\n6. Comment a summary of exact files modified and what you skipped\n\n**Phase 3: Final Verdict**\n7. If all issues are resolved, approve the PR / close the Issue\n8. If blocking issues remain, request changes / leave clear action items'
});
# ================================================================
# BOT PRs: CodeRabbit/Qodo skip bot-authored PRs by default.
# Trigger them explicitly. Do NOT trigger Copilot here — it will
# be triggered by copilot-after-coderabbit/qodo when they finish.
# ================================================================
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:
pull-requests: write
steps:
- name: Trigger CodeRabbit and Qodo reviews
uses: actions/github-script@v7
with:
github-token: ${{ secrets.GH_TOKEN }}
script: |
const pr = context.payload.pull_request.number;
const owner = context.repo.owner;
const repo = context.repo.repo;
// 1. Trigger CodeRabbit review
await github.rest.issues.createComment({
issue_number: pr, owner, repo,
body: '@coderabbitai review'
});
console.log(`Triggered CodeRabbit for bot PR #${pr}`);
// 2. Trigger Qodo review
await github.rest.issues.createComment({
issue_number: pr, owner, repo,
body: '/review'
});
console.log(`Triggered Qodo for bot PR #${pr}`);
// 3. Trigger Gemini review (commented out)
// await github.rest.issues.createComment({
// issue_number: pr, owner, repo,
// body: '@gemini review this PR'
// });
// console.log(`Triggered Gemini for bot PR #${pr}`);
// NOTE: @copilot is NOT triggered here.
// It will be triggered by copilot-after-coderabbit or copilot-after-qodo
// once those bots finish, ensuring Copilot always reviews LAST.
console.log('Copilot will be triggered after CodeRabbit/Qodo complete.');
body: '@claude review this pull request and do a detailed analysis and fix this if the existing code doesn\'t have the solution implemented. Making sure it has backward compatibility, no existing features removed. After making those changes, again review the applied changes. Use @web to search if you dont know any information or to find the latest documentation or to find the latest version. Run the code if you think you need to run it to test it. Minimal code change to start with if required any changes. MAINLY IT SHOULD NOT IMPACT ON THE CURRENT SPEED OF EXECUTION of existing features, not increasing the overhead.'
})
-153
View File
@@ -1,153 +0,0 @@
name: Performance Benchmarks
on:
workflow_dispatch:
inputs:
iterations:
description: 'Number of benchmark iterations'
required: false
default: '100'
fail_on_regression:
description: 'Fail if performance regresses'
required: false
default: 'true'
jobs:
benchmark:
runs-on: ubuntu-latest
timeout-minutes: 30
steps:
- name: Checkout repository
uses: actions/checkout@v4
with:
persist-credentials: false
- name: Set up Python 3.12
uses: actions/setup-python@v5
with:
python-version: '3.12'
cache: 'pip'
- name: Install dependencies
run: |
python -m pip install --upgrade pip
pip install -e src/praisonai-agents[all]
pip install agno crewai langgraph
- name: Run Import Time Benchmark
id: import_time
env:
FAIL_ON_REGRESSION: ${{ inputs.fail_on_regression }}
run: |
cd src/praisonai-agents
python benchmarks/import_time.py 2>&1 | tee import_time_output.txt
# Extract import time
IMPORT_TIME=$(grep -oP 'Median:\s+\K[\d.]+' import_time_output.txt || echo "0")
echo "import_time=$IMPORT_TIME" >> $GITHUB_OUTPUT
# Check threshold (200ms)
if (( $(echo "$IMPORT_TIME > 200" | bc -l) )); then
echo "::warning::Import time ${IMPORT_TIME}ms exceeds 200ms threshold"
if [ "$FAIL_ON_REGRESSION" == "true" ]; then
echo "import_passed=false" >> $GITHUB_OUTPUT
fi
else
echo "import_passed=true" >> $GITHUB_OUTPUT
fi
- name: Run Memory Usage Benchmark
id: memory
env:
FAIL_ON_REGRESSION: ${{ inputs.fail_on_regression }}
run: |
cd src/praisonai-agents
python benchmarks/memory_usage.py 2>&1 | tee memory_output.txt
# Extract peak memory
PEAK_MEMORY=$(grep -oP 'Peak:\s+\K[\d.]+' memory_output.txt || echo "0")
echo "peak_memory=$PEAK_MEMORY" >> $GITHUB_OUTPUT
# Check threshold (30MB)
if (( $(echo "$PEAK_MEMORY > 30" | bc -l) )); then
echo "::warning::Memory usage ${PEAK_MEMORY}MB exceeds 30MB threshold"
if [ "$FAIL_ON_REGRESSION" == "true" ]; then
echo "memory_passed=false" >> $GITHUB_OUTPUT
fi
else
echo "memory_passed=true" >> $GITHUB_OUTPUT
fi
- name: Run Simple Benchmark
id: simple
run: |
cd src/praisonai-agents
python benchmarks/simple_benchmark.py 2>&1 | tee simple_output.txt
# Extract PraisonAI time
PRAISON_TIME=$(grep -oP 'PraisonAI\s+\K[\d.]+' simple_output.txt | head -1 || echo "0")
echo "praison_time=$PRAISON_TIME" >> $GITHUB_OUTPUT
- name: Run Tools Benchmark
id: tools
run: |
cd src/praisonai-agents
python benchmarks/tools_benchmark.py 2>&1 | tee tools_output.txt
# Extract PraisonAI time with tools
PRAISON_TOOLS_TIME=$(grep -oP 'PraisonAI\s+\K[\d.]+' tools_output.txt | head -1 || echo "0")
echo "praison_tools_time=$PRAISON_TOOLS_TIME" >> $GITHUB_OUTPUT
- name: Run Parameter Impact Benchmark
id: param_impact
env:
INPUT_ITERATIONS: ${{ inputs.iterations }}
run: |
cd src/praisonai-agents
python benchmarks/param_impact_benchmark.py --no-save --iterations "$INPUT_ITERATIONS" 2>&1 | tee param_impact_output.txt
- name: Check Lazy Imports
id: lazy_imports
run: |
cd src/praisonai-agents
python -c "
import sys
from praisonaiagents import Agent
agent = Agent(name='Test', output='silent')
# Check litellm is NOT loaded
if 'litellm' in sys.modules:
print('FAIL: litellm loaded during silent agent creation')
exit(1)
else:
print('PASS: litellm not loaded (lazy import working)')
"
- name: Generate Benchmark Summary
if: always()
run: |
echo "## Performance Benchmark Results" >> $GITHUB_STEP_SUMMARY
echo "" >> $GITHUB_STEP_SUMMARY
echo "| Metric | Value | Threshold | Status |" >> $GITHUB_STEP_SUMMARY
echo "|--------|-------|-----------|--------|" >> $GITHUB_STEP_SUMMARY
echo "| Import Time | ${{ steps.import_time.outputs.import_time }}ms | <200ms | ${{ steps.import_time.outputs.import_passed == 'true' && '✅' || '❌' }} |" >> $GITHUB_STEP_SUMMARY
echo "| Peak Memory | ${{ steps.memory.outputs.peak_memory }}MB | <30MB | ${{ steps.memory.outputs.memory_passed == 'true' && '✅' || '❌' }} |" >> $GITHUB_STEP_SUMMARY
echo "| Agent Instantiation | ${{ steps.simple.outputs.praison_time }}μs | - | ℹ️ |" >> $GITHUB_STEP_SUMMARY
echo "| Agent with Tools | ${{ steps.tools.outputs.praison_tools_time }}μs | - | ℹ️ |" >> $GITHUB_STEP_SUMMARY
echo "" >> $GITHUB_STEP_SUMMARY
echo "### Lazy Import Check" >> $GITHUB_STEP_SUMMARY
echo "✅ litellm not loaded during silent agent creation" >> $GITHUB_STEP_SUMMARY
- name: Fail on Regression
if: inputs.fail_on_regression == 'true'
run: |
if [ "${{ steps.import_time.outputs.import_passed }}" == "false" ]; then
echo "::error::Import time regression detected"
exit 1
fi
if [ "${{ steps.memory.outputs.memory_passed }}" == "false" ]; then
echo "::error::Memory usage regression detected"
exit 1
fi
echo "All performance checks passed!"
-2
View File
@@ -18,8 +18,6 @@ jobs:
steps:
- name: Checkout repository
uses: actions/checkout@v4
with:
persist-credentials: false
- name: Set up Docker Buildx
uses: docker/setup-buildx-action@v3
+4 -16
View File
@@ -2,9 +2,8 @@ name: Claude Issue Triage
description: "Automatically triage GitHub issues using Claude Code"
on:
workflow_dispatch:
# issues:
# types: [opened]
issues:
types: [opened]
jobs:
triage-issue:
@@ -13,23 +12,12 @@ jobs:
permissions:
contents: read
issues: write
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 }}
- name: Checkout repository
uses: actions/checkout@11bd71901bbe5b1630ceea73d27597364c9af683 # v4
with:
token: ${{ steps.app-token.outputs.token }}
- name: Run Claude Issue Triage
uses: ./.github/actions/claude-issue-triage-action
with:
claude_code_oauth_token: ${{ secrets.CLAUDE_CODE_OAUTH_TOKEN }}
github_token: ${{ steps.app-token.outputs.token }}
anthropic_api_key: ${{ secrets.ANTHROPIC_API_KEY }}
github_token: ${{ secrets.GITHUB_TOKEN }}
+109 -243
View File
@@ -6,272 +6,35 @@ on:
pull_request_review_comment:
types: [created]
issues:
types: [assigned, labeled, opened]
types: [opened, assigned, labeled]
pull_request_review:
types: [submitted]
jobs:
# ================================================================
# Job 1: Lightweight triage for ALL new issues (including external users)
# Posts welcome comment + adds triage labels. No Claude code execution.
# ================================================================
issue-triage:
if: |
github.event_name == 'issues' &&
github.event.action == 'opened' &&
!contains(toJSON(github.event.issue.labels), 'claude')
runs-on: ubuntu-latest
permissions:
issues: write
contents: read
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 }}
- name: Triage and acknowledge issue
uses: actions/github-script@v7
with:
github-token: ${{ steps.app-token.outputs.token }}
script: |
const issue = context.payload.issue;
const title = (issue.title || '').toLowerCase();
const body = (issue.body || '').toLowerCase();
const content = title + ' ' + body;
const isOwner = ['OWNER', 'MEMBER', 'COLLABORATOR'].includes(
issue.author_association
);
// --- Label triage ---
const labels = [];
// Kind labels
if (content.includes('feature request') || content.includes('[feature')) {
labels.push('enhancement');
} else if (content.includes('bug') || content.includes('error') || content.includes('crash') || content.includes('traceback')) {
labels.push('bug');
} else if (content.includes('question') || content.includes('how do i') || content.includes('how to')) {
labels.push('question');
}
// Area labels
if (content.includes('security') || content.includes('cve') || content.includes('vulnerability')) {
labels.push('security');
}
if (content.includes('performance') || content.includes('slow') || content.includes('memory leak')) {
labels.push('performance');
}
if (content.includes('documentation') || content.includes('docs')) {
labels.push('documentation');
}
if (content.includes('typescript') || content.includes('javascript') || content.includes('npm')) {
labels.push('javascript');
}
// Apply labels
if (labels.length > 0) {
await github.rest.issues.addLabels({
issue_number: issue.number,
owner: context.repo.owner,
repo: context.repo.repo,
labels
});
}
// --- Acknowledgment comment (external users only) ---
if (!isOwner) {
await github.rest.issues.createComment({
issue_number: issue.number,
owner: context.repo.owner,
repo: context.repo.repo,
body: [
`👋 Thanks for opening this issue, @${issue.user.login}!`,
'',
'A maintainer will review this shortly. In the meantime:',
'- Make sure you\'ve included steps to reproduce (for bugs)',
'- Check [existing issues](https://github.com/MervinPraison/PraisonAI/issues) for duplicates',
'- Review the [documentation](https://docs.praison.ai) for related guides',
'',
'_A maintainer can trigger deeper analysis by commenting `@claude` on this issue._'
].join('\n')
});
}
// --- For owner: add 'claude' label to trigger the code-fix job ---
if (isOwner) {
await github.rest.issues.addLabels({
issue_number: issue.number,
owner: context.repo.owner,
repo: context.repo.repo,
labels: ['claude']
});
}
# ================================================================
# Job 2: Full Claude code-fix (owner/collaborator only)
# Triggers on: labeled 'claude', @claude comments, assignments
# ================================================================
claude-response:
# Allow: human users, github-actions[bot] (auto-comments/labels)
# Block: dependabot, cursor, renovate, other bots
# Skip 'opened' events — triage job handles those above
# Prevent certain bots from triggering this action (but allow github-actions[bot] for auto-comments)
if: |
github.event.action != 'opened' &&
(github.event.action != 'labeled' || github.event.label.name == 'claude') &&
(github.event_name != 'issue_comment' || contains(github.event.comment.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]'
github.actor != 'renovate[bot]' &&
!(contains(github.actor, '[bot]') && github.actor != 'github-actions[bot]')
runs-on: ubuntu-latest
permissions:
contents: write
pull-requests: write
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 }}
- name: Check for Fork PR
id: check_fork
uses: actions/github-script@v7
with:
script: |
const isPR = context.eventName === 'pull_request' || (context.payload.issue && context.payload.issue.pull_request);
if (isPR) {
const prNumber = context.payload.pull_request ? 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
});
core.setOutput('pr_branch', pr.data.head.ref);
if (pr.data.head.repo && pr.data.head.repo.full_name !== context.repo.full_name) {
core.setOutput('is_fork', 'true');
core.setOutput('clone_url', pr.data.head.repo.clone_url);
core.setOutput('branch', pr.data.head.ref);
return;
}
}
core.setOutput('is_fork', 'false');
- name: Checkout repository
uses: actions/checkout@v4
with:
persist-credentials: false
fetch-depth: 0
token: ${{ steps.app-token.outputs.token }}
- name: Fetch PR branch and Setup Remote
if: github.event.issue.pull_request
env:
PR_BRANCH: ${{ steps.check_fork.outputs.pr_branch }}
IS_FORK: ${{ steps.check_fork.outputs.is_fork }}
run: |
# Fetch PR head from base repo and put it into local branch
git fetch origin pull/${{ github.event.issue.number }}/head:"${PR_BRANCH}"
# If it's a fork, make origin point to local to trick claude-code-action's `git fetch origin <branch>`
if [ "${IS_FORK}" = "true" ]; then
git remote set-url origin file://$(pwd)
fi
- uses: anthropics/claude-code-action@beta
env:
GH_TOKEN: ${{ steps.app-token.outputs.token }}
with:
allowed_bots: 'praisonai-triage-agent[bot]'
claude_code_oauth_token: ${{ secrets.CLAUDE_CODE_OAUTH_TOKEN }}
github_token: ${{ steps.app-token.outputs.token }}
claude_code_oauth_token: ${{ secrets.CLAUDE_ACCESS_TOKEN }}
github_token: ${{ secrets.GITHUB_TOKEN }}
trigger_phrase: "@claude"
label_trigger: "claude"
direct_prompt: |
${{ steps.check_fork.outputs.is_fork == 'true' && 'CRITICAL: THIS IS A PULL REQUEST FROM A FORK. YOU DO NOT HAVE PUSH PERMISSIONS TO THIS REPOSITORY. ONLY READ FILES, VALIDATE CODE, AND PROVIDE YOUR COMMENTS/FEEDBACK DIRECTLY IN THIS PR VIA COMMENTS. DO NOT ATTEMPT TO PUSH OR CREATE PULL REQUESTS.\n\n' || 'NOTE: The branch is under MervinPraison/PraisonAI (not a fork). You are able to make modifications and push directly to this branch.\n\n' }}
You are working on the PraisonAI SDK. Follow AGENTS.md strictly.
STEP 0 — SETUP GIT IDENTITY & AUTH (GLOBAL — required for all repos):
git config --global user.name "MervinPraison"
git config --global user.email "[email protected]"
gh auth setup-git
STEP 1 — READ GUIDELINES:
Read AGENTS.md to understand the architecture rules.
SCOPE: Focus ONLY on Python packages (praisonaiagents, praisonai). Do NOT modify or touch praisonai-rust or praisonai-ts packages.
STEP 2 — ARCHITECTURE VALIDATION & ROUTING (MANDATORY before writing code):
Before implementing anything, answer these questions:
- CORE vs WRAPPER vs TOOLS vs DOCS vs PLUGINS 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): Capabilities Agents actively call during execution (e.g. SurrealDB tool, Slack tool).
4. Documentation (PraisonAIDocs): Documentation pages, guides, API references.
5. Plugins (PraisonAI-Plugins): Framework lifecycle extensions replacing systemic behavior (e.g. tracing, logging, metrics, hooks, guardrails).
For items routed to an EXTERNAL repository (Tools, Docs, Plugins), follow STEP 3-ALT below.
- 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 (for changes in THIS repo — PraisonAI):
- Create a fix branch: git checkout -b claude/issue-$ISSUE_NUMBER-$(date +%Y%m%d)
- Implement a minimal, focused fix
- Follow protocol-driven design: protocols in core SDK, heavy implementations in wrapper
- Keep changes small and backward-compatible
- Commit: git add -A && git commit -m "fix: <description> (fixes #$ISSUE_NUMBER)"
- Push: git push origin claude/issue-$ISSUE_NUMBER-$(date +%Y%m%d)
CRITICAL: After pushing, you MUST immediately run: gh pr create --title "fix: <title>" --body "Fixes #$ISSUE_NUMBER" --head claude/issue-$ISSUE_NUMBER-$(date +%Y%m%d)
Do NOT stop after pushing. Do NOT say "manually create a PR". Always create the PR automatically.
STEP 3-ALT — IMPLEMENT IN EXTERNAL REPO (for PraisonAI-Tools, PraisonAIDocs, PraisonAI-Plugins):
When work must happen in a different repository, follow these steps EXACTLY. Do NOT attempt to use `cd`, as directory state is not preserved. Use `git -C` for all commands.
a) Clone the repository:
gh repo clone MervinPraison/<REPO_NAME> /tmp/<REPO_NAME>
b) Copy GitHub authentication from the main repository so push works seamlessly:
git -C /tmp/<REPO_NAME> config http."https://github.com/".extraheader "$(git config --get http."https://github.com/".extraheader)"
c) Create a feature branch (NEVER commit to main):
git -C /tmp/<REPO_NAME> checkout -b claude/issue-$ISSUE_NUMBER-$(date +%Y%m%d)
d) Make your changes using absolute paths (e.g. edit /tmp/<REPO_NAME>/docs.json)
e) Commit:
git -C /tmp/<REPO_NAME> add -A
git -C /tmp/<REPO_NAME> commit -m "feat: <description> (fixes #$ISSUE_NUMBER)"
f) Push the branch:
git -C /tmp/<REPO_NAME> push origin claude/issue-$ISSUE_NUMBER-$(date +%Y%m%d)
g) Create PR in the EXTERNAL repo:
gh pr create -R MervinPraison/<REPO_NAME> --head claude/issue-$ISSUE_NUMBER-$(date +%Y%m%d) --title "feat: <title>" --body "Fixes MervinPraison/PraisonAI#$ISSUE_NUMBER
<body>"
STEP 4 — TEST:
- For SDK changes: cd src/praisonai-agents && PYTHONPATH=. python -m pytest tests/ -x -q --timeout=30
- For docs changes: verify files exist and are valid markdown/MDX
- Ensure no regressions
STEP 5 — CREATE PR:
- Commit with descriptive message, push, and create PR using `gh pr create`
- For external repos, use `gh pr create -R MervinPraison/<REPO_NAME>`
CRITICAL: You MUST create the PR automatically using `gh pr create`. Do NOT just provide a link or say "manual push required".
NOTE: If you worked on an external repo, the wrapper action will report "No commits" for the main repo at the end. This is expected, do not worry about it.
allowed_tools: |
Bash(git:*)
Bash(python:*)
@@ -292,3 +55,106 @@ jobs:
mcp__github__get_issue_comments
mcp__github__update_issue
timeout_minutes: 30
post-review-comment:
needs: claude-response
if: success() && needs.claude-response.result == 'success'
runs-on: ubuntu-latest
permissions:
contents: read
pull-requests: write
issues: write
steps:
- name: Check for existing review comment
id: check-comment
uses: actions/github-script@v7
with:
github-token: ${{ secrets.GH_TOKEN }}
script: |
const reviewText = '@claude review if the changes made in the above branch are as per the requirements and make changes to the above branch if issues still exist.';
let comments = [];
let issueNumber;
try {
// Determine issue/PR number based on event type
if (context.eventName === 'pull_request_review_comment' || context.eventName === 'pull_request_review') {
issueNumber = context.payload.pull_request?.number || context.issue.number;
} else if (context.eventName === 'issue_comment' && context.payload.issue.pull_request) {
// This is a comment on a PR (not an issue)
issueNumber = context.payload.issue.number;
} else {
// This is a regular issue
issueNumber = context.issue.number;
}
comments = await github.rest.issues.listComments({
owner: context.repo.owner,
repo: context.repo.repo,
issue_number: issueNumber
});
// Look for Claude's completed review comments
const claudeReviewComments = comments.data.filter(comment =>
(comment.user.login === 'claude[bot]' || comment.body.includes('✅') || comment.body.includes('## Summary')) &&
!comment.body.includes('⏳') &&
!comment.body.includes('🔄') &&
!comment.body.includes('Loading...')
);
// Check if our review request comment already exists
const existingReviewRequest = comments.data.find(comment =>
comment.body.includes(reviewText)
);
// Post if Claude has completed a review AND we haven't posted the review request yet
const shouldPost = claudeReviewComments.length > 0 && !existingReviewRequest;
core.setOutput('should-post', shouldPost);
console.log(`Claude review completed: ${claudeReviewComments.length > 0}`);
console.log(`Review request exists: ${!!existingReviewRequest}`);
console.log(`Should post comment: ${shouldPost}`);
} catch (error) {
console.log('Error checking comments:', error);
core.setOutput('should-post', false); // If we can't check, don't post
}
- name: Wait 30 seconds before posting comment
if: steps.check-comment.outputs.should-post == 'true'
run: sleep 30
- name: Post review comment
if: steps.check-comment.outputs.should-post == 'true'
uses: actions/github-script@v7
with:
github-token: ${{ secrets.GH_TOKEN }}
script: |
let issueNumber;
let isPR = false;
// Determine issue/PR number and type based on event type
if (context.eventName === 'pull_request_review_comment' || context.eventName === 'pull_request_review') {
issueNumber = context.payload.pull_request?.number || context.issue.number;
isPR = true;
} else if (context.eventName === 'issue_comment' && context.payload.issue.pull_request) {
// This is a comment on a PR (not an issue)
issueNumber = context.payload.issue.number;
isPR = true;
} else {
// This is a regular issue - don't post review comment
issueNumber = context.issue.number;
isPR = false;
}
// Only post review comment on PRs, not regular issues
if (isPR) {
console.log(`Posting review comment on PR #${issueNumber}`);
await github.rest.issues.createComment({
issue_number: issueNumber,
owner: context.repo.owner,
repo: context.repo.repo,
body: '@claude review if the changes made in the above branch are as per the requirements and make changes to the above branch if issues still exist. MAINLY IT SHOULD NOT IMPACT ON THE CURRENT SPEED OF EXECUTION of existing features, not increasing the overhead.'
});
} else {
console.log(`Skipping review comment for regular issue #${issueNumber}`);
}
+62
View File
@@ -0,0 +1,62 @@
name: Run tests and upload coverage
on:
push:
branches: [ main, develop ]
pull_request:
branches: [ main, develop ]
jobs:
test:
name: Run tests and collect coverage
runs-on: ubuntu-latest
timeout-minutes: 15
steps:
- name: Checkout
uses: actions/checkout@v4
with:
fetch-depth: 2
- name: Set up Python
uses: actions/setup-python@v5
with:
python-version: 3.11
- name: Install UV
run: |
curl -LsSf https://astral.sh/uv/install.sh | sh
echo "$HOME/.local/bin" >> $GITHUB_PATH
- name: Install dependencies
run: |
cd src/praisonai
uv pip install --system ."[ui,gradio,api,agentops,google,openai,anthropic,cohere,chat,code,realtime,call,crewai,autogen]"
uv pip install --system duckduckgo_search
uv pip install --system pytest pytest-cov pytest-asyncio
# Install knowledge dependencies from praisonai-agents
uv pip install --system "praisonaiagents[knowledge]"
- name: Set environment variables
run: |
echo "OPENAI_API_KEY=${{ secrets.OPENAI_API_KEY || 'sk-test-key-for-github-actions-testing-only-not-real' }}" >> $GITHUB_ENV
echo "OPENAI_API_BASE=${{ secrets.OPENAI_API_BASE || 'https://api.openai.com/v1' }}" >> $GITHUB_ENV
echo "OPENAI_MODEL_NAME=${{ secrets.OPENAI_MODEL_NAME || 'gpt-5-nano' }}" >> $GITHUB_ENV
echo "LOGLEVEL=DEBUG" >> $GITHUB_ENV
echo "PYTHONPATH=${{ github.workspace }}/src/praisonai-agents:$PYTHONPATH" >> $GITHUB_ENV
- name: Run tests
run: |
cd src/praisonai
# Run tests - allow some failures for now while we fix remaining issues
pytest --cov=praisonai --cov-branch --cov-report=xml tests/unit/ --tb=no -q || echo "Some tests failed, but coverage was collected"
- name: Upload results to Codecov
uses: codecov/codecov-action@v5
with:
token: ${{ secrets.CODECOV_TOKEN }}
file: src/praisonai/coverage.xml
flags: unit-tests
name: unit-tests-coverage
fail_ci_if_error: false
verbose: true
-4
View File
@@ -20,10 +20,6 @@ jobs:
steps:
- name: Checkout repository
uses: actions/checkout@v4
with:
persist-credentials: false
with:
persist-credentials: false
- name: Set up Docker Buildx
uses: docker/setup-buildx-action@v3
@@ -1,10 +1,8 @@
name: Gemini Automated Issue Triage
# on:
# issue_comment:
# types: [created]
on:
workflow_dispatch:
issue_comment:
types: [created]
jobs:
triage-issue:
@@ -34,10 +32,6 @@ jobs:
- name: Checkout repository
uses: actions/checkout@v4
with:
persist-credentials: false
with:
persist-credentials: false
with:
token: ${{ steps.generate_token.outputs.token }}
+16 -18
View File
@@ -2,8 +2,8 @@ name: Gemini Issue Review
on:
workflow_dispatch:
# issue_comment:
# types: [created]
issue_comment:
types: [created]
permissions:
contents: write
@@ -20,8 +20,7 @@ jobs:
!contains(github.event.comment.body, '@gemini triage') &&
(github.event.comment.author_association == 'OWNER' ||
github.event.comment.author_association == 'MEMBER' ||
github.event.comment.author_association == 'COLLABORATOR' ||
github.event.comment.author_association == 'CONTRIBUTOR'))
github.event.comment.author_association == 'COLLABORATOR'))
runs-on: ubuntu-latest
env:
GEMINI_API_KEY: ${{ secrets.GEMINI_API_KEY }}
@@ -35,17 +34,13 @@ jobs:
- name: Checkout repository
uses: actions/checkout@v4
with:
persist-credentials: false
with:
persist-credentials: false
with:
token: ${{ steps.generate_token.outputs.token }}
- name: Set up Git
run: |
git config --local user.email "[email protected].github.com"
git config --local user.name "MervinPraison"
git config --local user.email "gemini-bot@github.com"
git config --local user.name "Gemini Bot"
- name: Get issue data
id: issue_data
@@ -80,16 +75,16 @@ jobs:
echo "ADDITIONAL_INSTRUCTIONS=$ADDITIONAL_INSTRUCTIONS" >> $GITHUB_OUTPUT
- name: Run Gemini CLI
uses: google-github-actions/run-gemini-cli@v0
uses: ./.github/actions/gemini
env:
GH_TOKEN: ${{ steps.generate_token.outputs.token }}
GITHUB_TOKEN: ${{ steps.generate_token.outputs.token }}
ISSUE_NUMBER: ${{ steps.issue_data.outputs.ISSUE_NUMBER }}
ADDITIONAL_INSTRUCTIONS: ${{ steps.issue_data.outputs.ADDITIONAL_INSTRUCTIONS }}
REPOSITORY: ${{ github.repository }}
with:
gemini_api_key: ${{ secrets.GEMINI_API_KEY }}
gemini_model: 'gemini-2.5-flash'
GEMINI_API_KEY: ${{ secrets.GEMINI_API_KEY }}
OTLP_GCP_WIF_PROVIDER: ${{ secrets.OTLP_GCP_WIF_PROVIDER }}
OTLP_GOOGLE_CLOUD_PROJECT: ${{ secrets.OTLP_GOOGLE_CLOUD_PROJECT }}
prompt: |
You are a helpful GitHub issue assistant. Your task is to analyze and help with GitHub issues.
@@ -108,8 +103,6 @@ jobs:
- Search codebase for related files using `glob`, `search_file_content`, `list_directory`
**STEP 2: If Code Changes Are Needed**
MANDATORY FIRST STEP: Before writing any code, you MUST use `read_file` to carefully read "src/praisonai-agents/AGENTS.md". You must honor this repository's extremely specific Architecture, Protocol-First design rules, and Agent-Centric Philosophy!
Create a new branch with 'gemini/' prefix:
- Use: `git checkout -b gemini/issue-${ISSUE_NUMBER}-description`
- Example: `git checkout -b gemini/issue-123-fix-sequential-tools`
@@ -168,7 +161,7 @@ jobs:
Please proceed with helping resolve this issue following this exact workflow.
settings: |
settings_json: |
{
"coreTools": [
"run_shell_command(echo)",
@@ -200,5 +193,10 @@ jobs:
"web_fetch",
"google_web_search",
"save_memory"
]
],
"telemetry": {
"enabled": false,
"otlpGcpWifProvider": "${{ secrets.OTLP_GCP_WIF_PROVIDER }}",
"googleCloudProject": "${{ secrets.OTLP_GOOGLE_CLOUD_PROJECT }}"
}
}
+2 -8
View File
@@ -1,8 +1,8 @@
name: Gemini PR Review
on:
# issue_comment:
# types: [created]
issue_comment:
types: [created]
workflow_dispatch:
inputs:
pr_number:
@@ -46,10 +46,6 @@ jobs:
- name: Checkout PR code
uses: actions/checkout@v4
with:
persist-credentials: false
with:
persist-credentials: false
with:
token: ${{ steps.generate_token.outputs.token }}
ref: ${{ steps.checkout_ref.outputs.ref }}
@@ -163,8 +159,6 @@ jobs:
- Analyze the code changes thoroughly
**STEP 2: If Code Improvements Are Needed**
MANDATORY FIRST STEP: Before writing any code, you MUST use `read_file` to carefully read "src/praisonai-agents/AGENTS.md". You must honor this repository's extremely specific Architecture, Protocol-First design rules, and Agent-Centric Philosophy!
**IMPORTANT:** DO NOT create a new branch! Work on the EXISTING PR branch.
- Use: `git fetch origin` to get latest changes
- Get PR branch name: `gh pr view ${PR_NUMBER} --json headRefName`
@@ -1,158 +0,0 @@
name: Cross-Repo Integration Tests
on:
push:
branches: [ main ]
paths:
- 'src/praisonai/praisonai/integration/**'
- 'src/praisonai/tests/integration/test_aiui_*'
- 'src/praisonai/pyproject.toml'
pull_request:
branches: [ main ]
paths:
- 'src/praisonai/praisonai/integration/**'
- 'src/praisonai/tests/integration/test_aiui_*'
- 'src/praisonai/pyproject.toml'
workflow_dispatch:
jobs:
cross-repo-integration:
runs-on: ubuntu-latest
timeout-minutes: 30
steps:
- name: Checkout PraisonAI
uses: actions/checkout@v4
with:
path: PraisonAI
ref: ${{ github.event_name == 'pull_request' && github.event.pull_request.head.sha || github.sha }}
- name: Checkout PraisonAIUI
uses: actions/checkout@v4
with:
repository: MervinPraison/PraisonAIUI
path: PraisonAIUI
ref: main
- name: Set up Python
uses: actions/setup-python@v4
with:
python-version: '3.11'
- name: Install dependencies
run: |
python -m pip install --upgrade pip
# Install PraisonAI packages in development mode
cd PraisonAI/src/praisonai-agents
pip install -e .
cd ../praisonai
pip install -e ".[ui,dev]"
# Install PraisonAIUI in development mode
cd ../../../PraisonAIUI
pip install -e .
- name: Verify versions
run: |
python -c "import praisonaiagents; print(f'praisonaiagents: {praisonaiagents.__version__}')"
python -c "import praisonai; print(f'praisonai: {praisonai.__version__}')"
python -c "import praisonaiui; print(f'praisonaiui: {praisonaiui.__version__}')"
- name: Run PraisonAI integration tests
run: |
cd PraisonAI/src/praisonai
python -m pytest tests/integration/test_aiui_* -v --timeout=300
- name: Run PraisonAIUI integration tests
run: |
cd PraisonAIUI
if [ -f tests/integration/test_agentic_roundtrip.py ]; then
python -m pytest tests/integration/test_agentic_roundtrip.py -v --timeout=300
fi
if [ -f tests/test_feature_sdk_backends.py ]; then
python -m pytest tests/test_feature_sdk_backends.py -v --timeout=300
fi
- name: Test Pattern C CLI
run: |
cd PraisonAI/src/praisonai
# Test that ui-gateway command exists
python -m praisonai serve --help | grep ui-gateway
- name: Test public API exports
run: |
cd PraisonAI/src/praisonai
python -c "from praisonai import run_integrated_gateway; print('✓ run_integrated_gateway imported')"
python -c "from praisonai import configure_host; print('✓ configure_host imported')"
- name: Integration smoke test
env:
PRAISONAI_TEST_MODE: "1"
PYTHONPATH: ${{ github.workspace }}/PraisonAI/src/praisonai:${{ github.workspace }}/PraisonAI/src/praisonai-agents:${{ github.workspace }}/PraisonAIUI
run: |
cd PraisonAI/src/praisonai
python -c "
import sys
sys.path.insert(0, '.')
from praisonai.integration.host_app import configure_host
from praisonai import run_integrated_gateway
print('✓ Integration imports successful')
# Test configure_host with new parameters
try:
configure_host(
style='dashboard',
context_paths=['AGENTS.md'],
title='Test App'
)
print('✓ configure_host with new parameters works')
except Exception as e:
print(f'× configure_host failed: {e}')
sys.exit(1)
"
# Optional job with API key for agentic tests (if secret is available)
agentic-integration:
runs-on: ubuntu-latest
timeout-minutes: 30
if: ${{ vars.RUN_AGENTIC_TESTS == 'true' }}
needs: cross-repo-integration
steps:
- name: Checkout PraisonAI
uses: actions/checkout@v4
with:
path: PraisonAI
ref: ${{ github.event_name == 'pull_request' && github.event.pull_request.head.sha || github.sha }}
- name: Checkout PraisonAIUI
uses: actions/checkout@v4
with:
repository: MervinPraison/PraisonAIUI
path: PraisonAIUI
ref: main
- name: Set up Python
uses: actions/setup-python@v4
with:
python-version: '3.11'
- name: Install dependencies
run: |
python -m pip install --upgrade pip
cd PraisonAI/src/praisonai-agents
pip install -e .
cd ../praisonai
pip install -e ".[ui,dev]"
cd ../../../PraisonAIUI
pip install -e .
- name: Run agentic integration test
env:
OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }}
run: |
cd PraisonAI/src/praisonai
if [ -n "$OPENAI_API_KEY" ]; then
python -m pytest tests/integration/test_aiui_host_agentic.py -v --timeout=600
else
echo "OPENAI_API_KEY not available, skipping agentic tests"
fi
@@ -1,71 +0,0 @@
name: PraisonAI Issue Triage
on:
issue_comment:
types: [created]
workflow_dispatch:
inputs:
issue_number:
description: 'Issue Number'
required: true
type: string
jobs:
triage:
runs-on: ubuntu-latest
if: >
github.event_name == 'workflow_dispatch' ||
(github.event_name == 'issue_comment' &&
!github.event.issue.pull_request &&
contains(github.event.comment.body, '@praisonai') &&
github.actor != 'github-actions[bot]' &&
github.event.comment.user.type != 'Bot' &&
(github.event.comment.author_association == 'OWNER' ||
github.event.comment.author_association == 'MEMBER' ||
github.event.comment.author_association == 'COLLABORATOR'))
steps:
- name: Checkout Repository
uses: actions/checkout@v4
with:
persist-credentials: false
fetch-depth: 0
- name: Generate GitHub App Token
id: generate_token
uses: tibdex/github-app-token@v2
with:
app_id: ${{ secrets.PRAISONAI_APP_ID }}
private_key: ${{ secrets.PRAISONAI_APP_PRIVATE_KEY }}
- name: Set up Python
uses: actions/setup-python@v5
with:
python-version: '3.11'
- name: Set up Git
run: |
git config --local user.email "[email protected]"
git config --local user.name "PraisonAI Bot"
- name: Install PraisonAI
run: |
pip install uv
cd src/praisonai-agents && uv pip install --system -e ".[all]"
cd ../praisonai && uv pip install --system -e ".[all]"
- name: Run PraisonAI Issue Triage
env:
GITHUB_TOKEN: ${{ steps.generate_token.outputs.token }}
GH_TOKEN: ${{ steps.generate_token.outputs.token }}
OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }}
PRAISONAI_AUTO_APPROVE: "true"
ISSUE_NUMBER_INPUT: ${{ inputs.issue_number }}
ISSUE_NUMBER_EVENT: ${{ github.event.issue.number }}
run: |
if [ "${{ github.event_name }}" = "workflow_dispatch" ]; then
export ISSUE_NUMBER="$ISSUE_NUMBER_INPUT"
else
export ISSUE_NUMBER="$ISSUE_NUMBER_EVENT"
fi
praisonai github triage --issue $ISSUE_NUMBER --agent-file .github/praisonai-issue-triage.yaml
-73
View File
@@ -1,73 +0,0 @@
name: PraisonAI PR Reviewer
on:
pull_request:
types: [opened, synchronize, reopened, ready_for_review]
issue_comment:
types: [created]
workflow_dispatch:
inputs:
pr_number:
description: 'Pull Request Number'
required: true
type: string
jobs:
review:
runs-on: ubuntu-latest
if: >
(github.event_name == 'pull_request' && github.event.pull_request.draft == false) ||
github.event_name == 'workflow_dispatch' ||
(github.event_name == 'issue_comment' &&
github.event.issue.pull_request &&
contains(github.event.comment.body, '@praisonai') &&
github.actor != 'github-actions[bot]' &&
github.event.comment.user.type != 'Bot' &&
(github.event.comment.author_association == 'OWNER' ||
github.event.comment.author_association == 'MEMBER' ||
github.event.comment.author_association == 'COLLABORATOR'))
steps:
- name: Determine checkout ref
id: dest
env:
ISSUE_NUMBER: ${{ github.event.issue.number }}
PR_NUMBER_INPUT: ${{ inputs.pr_number }}
PR_HEAD_SHA: ${{ github.event.pull_request.head.sha }}
run: |
if [ "${{ github.event_name }}" = "issue_comment" ]; then
echo "ref=refs/pull/$ISSUE_NUMBER/head" >> "$GITHUB_OUTPUT"
elif [ "${{ github.event_name }}" = "workflow_dispatch" ]; then
echo "ref=refs/pull/$PR_NUMBER_INPUT/head" >> "$GITHUB_OUTPUT"
else
echo "ref=$PR_HEAD_SHA" >> "$GITHUB_OUTPUT"
fi
- name: Checkout Repository
uses: actions/checkout@v4
with:
persist-credentials: false
ref: ${{ steps.dest.outputs.ref }}
fetch-depth: 0
- name: Generate GitHub App Token
id: generate_token
uses: tibdex/github-app-token@v2
with:
app_id: ${{ secrets.PRAISONAI_APP_ID }}
private_key: ${{ secrets.PRAISONAI_APP_PRIVATE_KEY }}
- name: Set up Python
uses: actions/setup-python@v5
with:
python-version: '3.11'
- name: Install PraisonAI
run: pip install "praisonai[all]"
- name: Run PraisonAI PR Review
env:
GITHUB_TOKEN: ${{ steps.generate_token.outputs.token }}
OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }}
run: |
praisonai workflow run .github/praisonai-reviewer.yaml
+38 -12
View File
@@ -1,22 +1,25 @@
name: Python Package (Multi-Version)
# This workflow will install Python dependencies, run tests and lint with a variety of Python versions
# For more information see: https://docs.github.com/en/actions/automating-builds-and-tests/building-and-testing-python
name: Python package
on:
schedule:
- cron: '0 4 * * 1' # Weekly Monday 4am UTC
workflow_dispatch:
push:
branches: [ "develop" ]
pull_request:
branches: [ "develop" ]
jobs:
build:
runs-on: ubuntu-latest
strategy:
fail-fast: false
matrix:
python-version: ["3.10", "3.11", "3.12"]
python-version: ["3.10", "3.11"]
steps:
- uses: actions/checkout@v4
with:
persist-credentials: false
- name: Set up Python ${{ matrix.python-version }}
uses: actions/setup-python@v5
with:
@@ -27,16 +30,39 @@ jobs:
echo "OPENAI_API_KEY=${{ secrets.OPENAI_API_KEY || 'sk-test-key-for-github-actions-testing-only-not-real' }}" >> $GITHUB_ENV
echo "OPENAI_API_BASE=${{ secrets.OPENAI_API_BASE || 'https://api.openai.com/v1' }}" >> $GITHUB_ENV
echo "OPENAI_MODEL_NAME=${{ secrets.OPENAI_MODEL_NAME || 'gpt-5-nano' }}" >> $GITHUB_ENV
echo "PYTHONPATH=${{ github.workspace }}/src/praisonai-agents:$PYTHONPATH" >> $GITHUB_ENV
echo "LOGLEVEL=DEBUG" >> $GITHUB_ENV
- name: Install dependencies
run: |
cd src/praisonai
python -m pip install --upgrade pip
python -m pip install flake8 pytest
python -m pip install ."[ui,gradio,api,agentops,google,openai,anthropic,cohere,chat,code,realtime,call,crewai,autogen]"
python -m pip install duckduckgo_search pytest pytest-asyncio pytest-cov
python -m pip install duckduckgo_search
python -m pip install pytest-asyncio pytest-cov
# Install knowledge dependencies from praisonai-agents
python -m pip install "praisonaiagents[knowledge]"
- name: Run tests
if [ -f requirements.txt ]; then pip install -r requirements.txt; fi
- name: Debug API Key Status
run: |
cd src/praisonai && python -m pytest tests/unit/ -v --tb=short --disable-warnings --timeout=60 || echo "Some tests failed"
echo "🔍 Checking API key availability..."
if [ -n "${{ secrets.OPENAI_API_KEY }}" ]; then
echo "✅ GitHub secret OPENAI_API_KEY is available"
echo "🔑 API key starts with: $(echo "$OPENAI_API_KEY" | cut -c1-7)..."
else
echo "⚠️ GitHub secret OPENAI_API_KEY is NOT set - using fallback"
echo "🔑 Using fallback key: sk-test-key..."
fi
echo "🌐 API Base: $OPENAI_API_BASE"
echo "🤖 Model: $OPENAI_MODEL_NAME"
# - name: Lint with flake8
# run: |
# # stop the build if there are Python syntax errors or undefined names
# flake8 . --count --select=E9,F63,F7,F82 --show-source --statistics
# # exit-zero treats all errors as warnings. The GitHub editor is 127 chars wide
# flake8 . --count --exit-zero --max-complexity=10 --max-line-length=127 --statistics
- name: Test with pytest
run: |
cd src/praisonai && python tests/test_runner.py --pattern fast
-2
View File
@@ -22,8 +22,6 @@ jobs:
steps:
- uses: actions/checkout@v4
with:
persist-credentials: false
- name: Set up Python
uses: actions/setup-python@v5
with:
+30 -56
View File
@@ -26,10 +26,6 @@ jobs:
# First checkout the upstream repo at the specified tag
- name: Checkout upstream repo
uses: actions/checkout@v4
with:
persist-credentials: false
with:
persist-credentials: false
with:
repository: MervinPraison/PraisonAI
ref: ${{ github.event.inputs.tag }}
@@ -38,20 +34,14 @@ jobs:
# Get the commit hash from the tag
- name: Get commit hash
id: get_commit
env:
INPUT_TAG: ${{ github.event.inputs.tag }}
run: |
COMMIT_HASH=$(git rev-parse HEAD)
echo "commit_hash=$COMMIT_HASH" >> $GITHUB_OUTPUT
echo "Found commit: $COMMIT_HASH for tag $INPUT_TAG"
echo "Found commit: $COMMIT_HASH for tag ${{ github.event.inputs.tag }}"
# Now checkout the fork at main branch
- name: Checkout fork
uses: actions/checkout@v4
with:
persist-credentials: false
with:
persist-credentials: false
with:
repository: ${{ github.event.inputs.fork_owner }}/PraisonAI
ref: main
@@ -61,8 +51,8 @@ jobs:
# Sync with upstream commit
- name: Sync with upstream
run: |
git config --global user.name "MervinPraison"
git config --global user.email "[email protected].github.com"
git config --global user.name "GitHub Actions"
git config --global user.email "actions@github.com"
# Add upstream remote
git remote add upstream https://github.com/MervinPraison/PraisonAI.git
@@ -70,11 +60,8 @@ jobs:
# Fetch from upstream
git fetch upstream --tags --force
- name: Hard reset to tag commit
env:
COMMIT_HASH: ${{ steps.get_commit.outputs.commit_hash }}
run: |
git reset --hard $COMMIT_HASH
# Reset to upstream commit
git reset --hard ${{ steps.get_commit.outputs.commit_hash }}
- name: Setup Python
uses: actions/setup-python@v5
@@ -449,10 +436,6 @@ jobs:
# First checkout the fork's main branch
- name: Checkout fork repo
uses: actions/checkout@v4
with:
persist-credentials: false
with:
persist-credentials: false
with:
fetch-depth: 0
token: ${{ secrets.PAT_TOKEN }}
@@ -462,64 +445,55 @@ jobs:
# Add upstream and get commit from tag
- name: Get upstream tag commit
id: get_upstream_commit
env:
INPUT_TAG: ${{ github.event.inputs.tag }}
run: |
# Add upstream remote
git remote add upstream https://github.com/MervinPraison/PraisonAI.git
# Delete local tag if it exists
git tag -d "$INPUT_TAG" || true
git tag -d ${{ github.event.inputs.tag }} || true
# Fetch from upstream including tags with force
git fetch upstream --tags --force
# Verify tag exists in upstream
if ! git ls-remote --tags upstream | grep -q "refs/tags/$INPUT_TAG$"; then
echo "::error::Tag $INPUT_TAG not found in upstream repository"
if ! git ls-remote --tags upstream | grep -q "refs/tags/${{ github.event.inputs.tag }}$"; then
echo "::error::Tag ${{ github.event.inputs.tag }} not found in upstream repository"
exit 1
fi
# Get the commit hash from the upstream tag
UPSTREAM_COMMIT=$(git rev-list -n 1 refs/tags/"$INPUT_TAG")
UPSTREAM_COMMIT=$(git rev-list -n 1 refs/tags/${{ github.event.inputs.tag }})
if [ -z "$UPSTREAM_COMMIT" ]; then
echo "::error::Could not find commit for tag $INPUT_TAG"
echo "::error::Could not find commit for tag ${{ github.event.inputs.tag }}"
exit 1
fi
echo "upstream_commit=$UPSTREAM_COMMIT" >> $GITHUB_OUTPUT
echo "Found commit: $UPSTREAM_COMMIT for tag $INPUT_TAG"
echo "Found commit: $UPSTREAM_COMMIT for tag ${{ github.event.inputs.tag }}"
# Create tag at the same commit
- name: Create tag at commit
run: |
git config --global user.name "GitHub Actions"
git config --global user.email "[email protected]"
# Remove tag if it exists locally
git tag -d ${{ github.event.inputs.tag }} || true
# Remove tag if it exists remotely
git push origin :refs/tags/${{ github.event.inputs.tag }} || true
# Fetch the specific commit from upstream
git fetch upstream ${{ steps.get_upstream_commit.outputs.upstream_commit }} --force
# Reset to upstream commit
git reset --hard ${{ steps.get_upstream_commit.outputs.upstream_commit }}
# Create and push tag
git tag -a ${{ github.event.inputs.tag }} -m "Release ${{ github.event.inputs.tag }} (synced from upstream MervinPraison/PraisonAI@${{ github.event.inputs.tag }})"
git push origin ${{ github.event.inputs.tag }}
env:
GIT_ASKPASS: /bin/echo
PAT_TOKEN: ${{ secrets.PAT_TOKEN }}
INPUT_TAG: ${{ github.event.inputs.tag }}
run: |
git config --global user.name "MervinPraison"
git config --global user.email "[email protected]"
# Remove tag if it exists locally
git tag -d "$INPUT_TAG" || true
# Remove tag if it exists remotely
git push origin :refs/tags/"$INPUT_TAG" || true
- name: Fetch tag from upstream
env:
UPSTREAM_COMMIT: ${{ steps.get_upstream_commit.outputs.upstream_commit }}
run: |
git fetch upstream $UPSTREAM_COMMIT --force
- name: Reset to upstream commit
env:
UPSTREAM_COMMIT: ${{ steps.get_upstream_commit.outputs.upstream_commit }}
run: |
git reset --hard $UPSTREAM_COMMIT
# Create and push tag
git tag -a "$INPUT_TAG" -m "Release $INPUT_TAG (synced from upstream MervinPraison/PraisonAI@$INPUT_TAG)"
git push origin "$INPUT_TAG"
# Create the release
- name: Create Release
+13 -22
View File
@@ -37,10 +37,6 @@ jobs:
steps:
- name: Checkout code
uses: actions/checkout@v4
with:
persist-credentials: false
with:
persist-credentials: false
- name: Set up Python ${{ matrix.python-version }}
uses: actions/setup-python@v5
@@ -58,7 +54,7 @@ jobs:
cd src/praisonai
uv pip install --system ."[ui,gradio,api,agentops,google,openai,anthropic,cohere,chat,code,realtime,call,crewai,autogen]"
uv pip install --system duckduckgo_search
uv pip install --system pytest pytest-asyncio pytest-cov pytest-benchmark pytest-timeout
uv pip install --system pytest pytest-asyncio pytest-cov pytest-benchmark
# Install knowledge dependencies from praisonai-agents
uv pip install --system "praisonaiagents[knowledge]"
@@ -71,53 +67,48 @@ jobs:
fi
- name: Run Comprehensive Test Suite
env:
INPUT_TEST_TYPE: ${{ github.event.inputs.test_type || 'all' }}
run: |
# Determine test type from input or default to 'all'
TEST_TYPE="$INPUT_TEST_TYPE"
TEST_TYPE="${{ github.event.inputs.test_type || 'all' }}"
echo "🧪 Running comprehensive test suite (type: $TEST_TYPE)"
case $TEST_TYPE in
"unit")
cd src/praisonai && python -m pytest tests/unit/ -v --tb=short --disable-warnings --cov=praisonai --cov-report=xml --cov-branch || echo "Some unit tests failed"
cd src/praisonai && python -m pytest tests/unit/ -v --tb=short --disable-warnings --cov=praisonai --cov-report=xml --cov-branch
;;
"integration")
cd src/praisonai && python -m pytest tests/integration/ -v --tb=short --disable-warnings --cov=praisonai --cov-report=xml --cov-branch || echo "Some integration tests failed"
cd src/praisonai && python -m pytest tests/integration/ -v --tb=short --disable-warnings --cov=praisonai --cov-report=xml --cov-branch
;;
"fast")
cd src/praisonai && python tests/test_runner.py --pattern fast || echo "Some fast tests failed"
cd src/praisonai && python tests/test_runner.py --pattern fast
;;
"performance")
cd src/praisonai && python tests/test_runner.py --pattern "performance" || echo "Some performance tests failed"
cd src/praisonai && python tests/test_runner.py --pattern "performance"
;;
"frameworks")
cd src/praisonai && python tests/test_runner.py --pattern frameworks || echo "Some framework tests failed"
cd src/praisonai && python tests/test_runner.py --pattern frameworks
;;
"autogen")
cd src/praisonai && python tests/test_runner.py --pattern autogen || echo "Some autogen tests failed"
cd src/praisonai && python tests/test_runner.py --pattern autogen
;;
"crewai")
cd src/praisonai && python tests/test_runner.py --pattern crewai || echo "Some crewai tests failed"
cd src/praisonai && python tests/test_runner.py --pattern crewai
;;
"all"|*)
cd src/praisonai && python tests/test_runner.py --pattern all || echo "Some tests failed"
cd src/praisonai && python tests/test_runner.py --pattern all
;;
esac
- name: Generate Comprehensive Test Report
if: always()
env:
INPUT_TEST_TYPE: ${{ github.event.inputs.test_type || 'all' }}
EVENT_NAME: ${{ github.event_name }}
run: |
echo "# 📋 Comprehensive Test Report" > comprehensive_report.md
echo "" >> comprehensive_report.md
echo "**Python Version:** ${{ matrix.python-version }}" >> comprehensive_report.md
echo "**Test Type:** $INPUT_TEST_TYPE" >> comprehensive_report.md
echo "**Trigger:** $EVENT_NAME" >> comprehensive_report.md
echo "**Status:** 🟢 All Tests Passed" >> comprehensive_report.md
echo "**Test Type:** ${{ github.event.inputs.test_type || 'all' }}" >> comprehensive_report.md
echo "**Trigger:** ${{ github.event_name }}" >> comprehensive_report.md
echo "**Date:** $(date -u)" >> comprehensive_report.md
echo "" >> comprehensive_report.md
echo "## 🧪 Test Categories Covered:" >> comprehensive_report.md
+245 -31
View File
@@ -1,45 +1,41 @@
name: Core Tests
on:
on:
push:
branches: [ main, develop ]
paths:
- 'src/**'
- 'pyproject.toml'
- '.github/workflows/test-core.yml'
pull_request:
branches: [ main, develop ]
paths:
- 'src/**'
- 'pyproject.toml'
- '.github/workflows/test-core.yml'
workflow_dispatch:
jobs:
test-core:
runs-on: ubuntu-latest
timeout-minutes: 20
timeout-minutes: 15
strategy:
matrix:
python-version: [3.11]
steps:
- uses: actions/checkout@v4
with:
persist-credentials: false
- name: Set up Python 3.11
- name: Checkout code
uses: actions/checkout@v4
- name: Set up Python ${{ matrix.python-version }}
uses: actions/setup-python@v5
with:
python-version: '3.11'
python-version: ${{ matrix.python-version }}
- name: Install UV
run: |
curl -LsSf https://astral.sh/uv/install.sh | sh
echo "$HOME/.local/bin" >> $GITHUB_PATH
- name: Install dependencies
run: |
cd src/praisonai
uv pip install --system ."[ui,gradio,api,agentops,google,openai,anthropic,cohere,chat,code,realtime,call,crewai,autogen]"
uv pip install --system duckduckgo_search
uv pip install --system pytest pytest-asyncio pytest-cov pytest-timeout
# Install knowledge dependencies from praisonai-agents
uv pip install --system "praisonaiagents[knowledge]"
- name: Set environment variables
@@ -47,28 +43,246 @@ jobs:
echo "OPENAI_API_KEY=${{ secrets.OPENAI_API_KEY || 'sk-test-key-for-github-actions-testing-only-not-real' }}" >> $GITHUB_ENV
echo "OPENAI_API_BASE=${{ secrets.OPENAI_API_BASE || 'https://api.openai.com/v1' }}" >> $GITHUB_ENV
echo "OPENAI_MODEL_NAME=${{ secrets.OPENAI_MODEL_NAME || 'gpt-5-nano' }}" >> $GITHUB_ENV
echo "LOGLEVEL=DEBUG" >> $GITHUB_ENV
echo "PYTHONPATH=${{ github.workspace }}/src/praisonai-agents:$PYTHONPATH" >> $GITHUB_ENV
# Also export to current shell session for immediate availability
export OPENAI_API_KEY="${{ secrets.OPENAI_API_KEY || 'sk-test-key-for-github-actions-testing-only-not-real' }}"
export OPENAI_API_BASE="${{ secrets.OPENAI_API_BASE || 'https://api.openai.com/v1' }}"
export OPENAI_MODEL_NAME="${{ secrets.OPENAI_MODEL_NAME || 'gpt-5-nano' }}"
export LOGLEVEL=DEBUG
# Verify immediate availability
echo "🔧 Immediate verification in same step:"
echo " OPENAI_API_KEY length in current session: ${#OPENAI_API_KEY}"
echo " OPENAI_API_KEY starts with sk-: $(echo "$OPENAI_API_KEY" | grep -q '^sk-' && echo 'YES' || echo 'NO')"
- name: Debug API Key Status
run: |
echo "🔍 Checking API key availability..."
if [ -n "${{ secrets.OPENAI_API_KEY }}" ]; then
echo "✅ GitHub secret OPENAI_API_KEY is available"
echo "🔑 API key starts with: $(echo "$OPENAI_API_KEY" | cut -c1-7)..."
else
echo "⚠️ GitHub secret OPENAI_API_KEY is NOT set - using fallback"
echo "🔑 Using fallback key: sk-test-key..."
fi
echo "🌐 API Base: $OPENAI_API_BASE"
echo "🤖 Model: $OPENAI_MODEL_NAME"
echo "🐛 Log Level: $LOGLEVEL"
echo "📊 Environment Check:"
echo " - OPENAI_API_KEY length: ${#OPENAI_API_KEY}"
echo " - OPENAI_API_BASE: $OPENAI_API_BASE"
echo " - OPENAI_MODEL_NAME: $OPENAI_MODEL_NAME"
echo " - LOGLEVEL: $LOGLEVEL"
echo "🔍 Is API key actually set?"
echo " - API key starts with sk-: $(echo "$OPENAI_API_KEY" | grep -q '^sk-' && echo 'YES' || echo 'NO')"
echo " - API key is not test key: $([ "$OPENAI_API_KEY" != 'sk-test-key-for-github-actions-testing-only-not-real' ] && echo 'YES' || echo 'NO')"
- name: Debug Environment Variables Raw
run: |
echo "🔧 Raw environment variable check:"
echo "OPENAI_API_KEY set: $(if [ -n "$OPENAI_API_KEY" ]; then echo 'YES'; else echo 'NO'; fi)"
echo "OPENAI_API_KEY length: ${#OPENAI_API_KEY}"
echo "OPENAI_API_KEY first 10 chars: ${OPENAI_API_KEY:0:10}"
echo "OPENAI_API_KEY last 5 chars: ${OPENAI_API_KEY: -5}"
printenv | grep OPENAI || echo "No OPENAI env vars found"
- name: Debug Python Environment Variables
run: |
python -c "
import os
print('🐍 Python Environment Variable Check:')
api_key = os.environ.get('OPENAI_API_KEY', 'NOT_SET')
if api_key != 'NOT_SET':
print(f' ✅ OPENAI_API_KEY: {api_key[:7]}... (length: {len(api_key)})')
else:
print(' ❌ OPENAI_API_KEY: NOT_SET')
print(f' 🌐 OPENAI_API_BASE: {os.environ.get(\"OPENAI_API_BASE\", \"NOT_SET\")}')
print(f' 🤖 OPENAI_MODEL_NAME: {os.environ.get(\"OPENAI_MODEL_NAME\", \"NOT_SET\")}')
print(f' 📋 All OPENAI env vars:')
for key, value in os.environ.items():
if key.startswith('OPENAI'):
print(f' {key}: {value[:10] if len(value) > 10 else value}...')
"
- name: Validate API Key
run: |
echo "🔑 Testing API key validity with minimal OpenAI call..."
python -c "
import os
try:
from openai import OpenAI
client = OpenAI(api_key=os.environ.get('OPENAI_API_KEY'))
response = client.models.list()
print('✅ API Key is VALID - OpenAI responded successfully')
print(f'📊 Available models: {len(list(response.data))} models found')
except Exception as e:
print(f'❌ API Key is INVALID - Error: {e}')
print('🔍 This explains why all API-dependent tests are failing')
print('💡 The GitHub secret OPENAI_API_KEY needs to be updated with a valid key')
"
continue-on-error: true
- name: Debug PraisonAI API Key Usage
env:
OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY || 'sk-test-key-for-github-actions-testing-only-not-real' }}
OPENAI_API_BASE: ${{ secrets.OPENAI_API_BASE || 'https://api.openai.com/v1' }}
OPENAI_MODEL_NAME: ${{ secrets.OPENAI_MODEL_NAME || 'gpt-5-nano' }}
LOGLEVEL: DEBUG
run: |
echo "🔍 Testing PraisonAI API key usage directly..."
cd src/praisonai
python -c "
import os
import sys
sys.path.insert(0, '.')
# Attempt to import SecretStr, otherwise use a dummy class
try:
from pydantic.types import SecretStr
except ImportError:
class SecretStr: # Dummy class if pydantic is not available in this minimal context
def __init__(self, value): self._value = value
def get_secret_value(self): return self._value
def get_key_display_value(key_value):
if isinstance(key_value, SecretStr):
return key_value.get_secret_value()[:10] if key_value.get_secret_value() else 'EMPTY_SECRET'
elif isinstance(key_value, str):
return key_value[:10] if key_value != 'nokey' and key_value != 'NOT_SET' else key_value
return 'INVALID_TYPE'
print('🔧 Direct PraisonAI API Key Check:')
env_api_key = os.environ.get(\"OPENAI_API_KEY\", \"NOT_SET\")
print(f'Environment OPENAI_API_KEY: {get_key_display_value(env_api_key)}...')
from praisonai import PraisonAI
praisonai = PraisonAI()
print(f'PraisonAI config_list: {praisonai.config_list}')
api_key_from_config = praisonai.config_list[0].get('api_key', 'NOT_SET')
print(f'API key from PraisonAI config: {get_key_display_value(api_key_from_config)}...')
from praisonai.inc.models import PraisonAIModel
print('\\n🧪 Testing PraisonAIModel with explicit API key (CrewAI method):')
model_with_explicit_key = PraisonAIModel(
model='openai/gpt-5-nano',
base_url=praisonai.config_list[0].get('base_url'),
api_key=api_key_from_config # This will be a string from praisonai.config_list
)
print(f' Model: {model_with_explicit_key.model}')
print(f' Model name: {model_with_explicit_key.model_name}')
print(f' API key var: {model_with_explicit_key.api_key_var}')
# model_with_explicit_key.api_key is now a string, or 'nokey'
print(f' API key (explicitly passed to PraisonAIModel): {get_key_display_value(model_with_explicit_key.api_key)}...')
print(f' Base URL: {model_with_explicit_key.base_url}')
try:
llm_instance = model_with_explicit_key.get_model()
print(f' ✅ LLM instance created successfully: {type(llm_instance).__name__}')
# langchain_openai.ChatOpenAI stores the key in openai_api_key as SecretStr
llm_api_key_attr = getattr(llm_instance, 'openai_api_key', 'NOT_FOUND')
if llm_api_key_attr != 'NOT_FOUND':
print(f' LLM instance API key: {get_key_display_value(llm_api_key_attr)}...')
else:
print(f' LLM instance API key attribute not found.')
except Exception as e:
print(f' ❌ Failed to create LLM instance: {e}')
import traceback
traceback.print_exc()
"
continue-on-error: true
- name: Run Unit Tests
run: |
cd src/praisonai && python -m pytest tests/unit/ -v --tb=short --disable-warnings \
--cov=praisonai --cov-report=xml --cov-branch \
--timeout=60 || echo "Some unit tests failed"
cd src/praisonai && python -m pytest tests/unit/ -v --tb=short --disable-warnings --cov=praisonai --cov-report=term-missing --cov-report=xml --cov-branch || echo "Some tests failed - see output above"
continue-on-error: true
- name: Run Integration Tests
- name: Run Integration Tests
run: |
cd src/praisonai && python -m pytest tests/integration/ -v --tb=short --disable-warnings \
--timeout=60 \
--ignore=tests/integration/test_tracker_complex_tasks.py \
--ignore=tests/integration/test_serve_integration.py \
|| echo "Some integration tests failed"
cd src/praisonai && python -m pytest tests/integration/ -v --tb=short --disable-warnings
- name: Upload coverage to Codecov
if: always()
- name: Debug Directory Structure
run: |
echo "🔍 Debugging directory structure for CrewAI tests..."
cd src/praisonai
echo "Current working directory: $(pwd)"
echo "📁 Contents of current directory:"
ls -la
echo ""
echo "📁 Contents of tests directory:"
ls -la tests/ || echo "❌ tests/ directory not found"
echo ""
echo "📁 Contents of tests/integration:"
ls -la tests/integration/ || echo "❌ tests/integration/ directory not found"
echo ""
echo "📁 Looking for crewai directory:"
find . -name "crewai" -type d 2>/dev/null || echo "❌ No crewai directories found"
echo ""
echo "📁 Full directory tree of tests:"
tree tests/ || find tests/ -type d 2>/dev/null || echo "❌ Cannot explore tests directory"
- name: Test AutoGen Framework
run: |
echo "🤖 Testing AutoGen Framework Integration..."
cd src/praisonai && python tests/test_runner.py --pattern autogen --verbose
- name: Test CrewAI Framework
run: |
echo "⛵ Testing CrewAI Framework Integration..."
cd src/praisonai
echo "🔍 Trying test runner first..."
python tests/test_runner.py --pattern crewai --verbose || {
echo "❌ Test runner failed, trying direct pytest..."
echo "📁 Current directory: $(pwd)"
echo "📁 Looking for CrewAI tests..."
find . -name "*crewai*" -type f 2>/dev/null
echo "🧪 Trying direct pytest on integration/crewai..."
python -m pytest tests/integration/crewai/ -v --tb=short --disable-warnings || {
echo "❌ Direct path failed, trying relative path..."
python -m pytest integration/crewai/ -v --tb=short --disable-warnings || {
echo "❌ All CrewAI test attempts failed"
exit 1
}
}
}
- name: Run Legacy Tests with API Key
env:
OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY || 'sk-test-key-for-github-actions-testing-only-not-real' }}
OPENAI_API_BASE: ${{ secrets.OPENAI_API_BASE || 'https://api.openai.com/v1' }}
OPENAI_MODEL_NAME: ${{ secrets.OPENAI_MODEL_NAME || 'gpt-5-nano' }}
LOGLEVEL: DEBUG
run: |
echo "🧪 Running legacy tests with real API key..."
echo "🔧 Final environment check before pytest:"
echo " OPENAI_API_KEY set: $([ -n "$OPENAI_API_KEY" ] && echo 'YES' || echo 'NO')"
echo " OPENAI_API_KEY length: ${#OPENAI_API_KEY}"
echo " OPENAI_API_KEY starts with sk-: $(echo "$OPENAI_API_KEY" | grep -q '^sk-' && echo 'YES' || echo 'NO')"
export OPENAI_API_KEY="$OPENAI_API_KEY"
export OPENAI_API_BASE="$OPENAI_API_BASE"
export OPENAI_MODEL_NAME="$OPENAI_MODEL_NAME"
cd src/praisonai && python -m pytest tests/test.py -v --tb=short --disable-warnings -m "not real" --timeout=60
- name: Upload coverage reports to Codecov
if: matrix.python-version == '3.11'
uses: codecov/codecov-action@v5
with:
token: ${{ secrets.CODECOV_TOKEN || '' }}
files: src/praisonai/coverage.xml
token: ${{ secrets.CODECOV_TOKEN }}
file: src/praisonai/coverage.xml
flags: core-tests
fail_ci_if_error: false
name: core-tests-coverage
fail_ci_if_error: false
verbose: true
- name: Upload Coverage Reports (Artifacts)
if: matrix.python-version == '3.11'
uses: actions/upload-artifact@v4
with:
name: coverage-reports
path: |
src/praisonai/.coverage
src/praisonai/htmlcov/
src/praisonai/coverage.xml
retention-days: 7
+6 -9
View File
@@ -1,9 +1,14 @@
name: Extended Tests
on:
push:
branches: [ main ]
pull_request:
branches: [ main ]
schedule:
# Run nightly at 2 AM UTC
- cron: '0 2 * * *'
workflow_dispatch:
workflow_dispatch: # Allow manual triggering
jobs:
test-examples:
@@ -13,10 +18,6 @@ jobs:
steps:
- name: Checkout code
uses: actions/checkout@v4
with:
persist-credentials: false
with:
persist-credentials: false
- name: Set up Python
uses: actions/setup-python@v5
@@ -81,10 +82,6 @@ jobs:
steps:
- name: Checkout code
uses: actions/checkout@v4
with:
persist-credentials: false
with:
persist-credentials: false
- name: Set up Python
uses: actions/setup-python@v5
+1 -5
View File
@@ -33,10 +33,6 @@ jobs:
steps:
- name: Checkout code
uses: actions/checkout@v4
with:
persist-credentials: false
with:
persist-credentials: false
- name: Set up Python ${{ matrix.python-version }}
uses: actions/setup-python@v5
@@ -54,7 +50,7 @@ jobs:
cd src/praisonai
uv pip install --system ."[ui,gradio,api,agentops,google,openai,anthropic,cohere,chat,code,realtime,call,crewai,autogen]"
uv pip install --system duckduckgo_search
uv pip install --system pytest pytest-asyncio pytest-cov pytest-timeout
uv pip install --system pytest pytest-asyncio pytest-cov
- name: Set environment variables
run: |
-560
View File
@@ -1,560 +0,0 @@
name: Optimized Test Suite
on:
push:
branches: [ main, develop ]
paths:
- 'src/**'
- 'pyproject.toml'
- '.github/workflows/test-optimized.yml'
pull_request:
branches: [ main, develop ]
paths:
- 'src/**'
- 'pyproject.toml'
- '.github/workflows/test-optimized.yml'
schedule:
# Nightly extended tests at 3 AM UTC
- cron: '0 3 * * *'
workflow_dispatch:
inputs:
tier:
description: 'Test tier to run'
required: true
default: 'main'
type: choice
options:
- smoke
- main
- extended
- nightly
env:
PYTHONPATH: ${{ github.workspace }}/src/praisonai-agents
# Test gating environment variables
PRAISONAI_ALLOW_NETWORK: '0'
PRAISONAI_LIVE_TESTS: '0'
jobs:
# ============================================
# SMOKE TESTS - Fast unit tests, no network
# Target: <= 2 minutes
# ============================================
smoke:
runs-on: ubuntu-latest
timeout-minutes: 5
steps:
- uses: actions/checkout@v4
with:
persist-credentials: false
- name: Set up Python 3.11
uses: actions/setup-python@v5
with:
python-version: '3.11'
- name: Cache pip packages
uses: actions/cache@v4
with:
path: ~/.cache/pip
key: ${{ runner.os }}-pip-smoke-${{ hashFiles('**/pyproject.toml') }}
restore-keys: |
${{ runner.os }}-pip-smoke-
${{ runner.os }}-pip-
- name: Install minimal dependencies
run: |
pip install --upgrade pip
# Install praisonai-agents with all deps (required for tests)
cd src/praisonai-agents
pip install -e ".[all]"
cd ../praisonai
pip install -e ".[chat,code]"
pip install pytest pytest-asyncio pytest-timeout prompt_toolkit
- name: Run Smoke Tests
env:
PRAISONAI_TEST_TIER: smoke
PRAISONAI_ALLOW_NETWORK: '0'
run: |
cd src/praisonai
# Run only CLI tests for smoke - fast and critical path
python -m pytest tests/unit/cli/ \
-m "not slow and not network" \
-q --tb=line \
--timeout=30 \
--ignore=tests/fixtures \
--ignore=tests/unit/cli/test_message_queue.py \
--maxfail=5 \
|| echo "Some smoke tests failed"
- name: Smoke Test Summary
if: always()
run: echo "✅ Smoke tests completed"
# ============================================
# MAIN TESTS - Unit + safe integration
# Target: <= 5 minutes
# ============================================
main:
needs: smoke
runs-on: ubuntu-latest
timeout-minutes: 10
strategy:
matrix:
python-version: ['3.11']
steps:
- uses: actions/checkout@v4
with:
persist-credentials: false
- name: Set up Python ${{ matrix.python-version }}
uses: actions/setup-python@v5
with:
python-version: ${{ matrix.python-version }}
- name: Cache pip packages
uses: actions/cache@v4
with:
path: ~/.cache/pip
key: ${{ runner.os }}-pip-main-${{ hashFiles('**/pyproject.toml') }}
restore-keys: |
${{ runner.os }}-pip-main-
${{ runner.os }}-pip-
- name: Install dependencies
run: |
pip install --upgrade pip
# Install praisonai-agents with all deps (required for tests)
cd src/praisonai-agents
pip install -e ".[all]"
cd ../praisonai
pip install -e ".[crewai,autogen]"
pip install pytest pytest-asyncio pytest-timeout pytest-cov pytest-xdist
- name: Run Main Tests
env:
PRAISONAI_TEST_TIER: main
PRAISONAI_ALLOW_NETWORK: '0'
OPENAI_API_KEY: 'test-key'
ANTHROPIC_API_KEY: 'test-key'
GOOGLE_API_KEY: 'test-key'
run: |
cd src/praisonai
python -m pytest tests/unit/ tests/integration/ \
-m "not provider_anthropic and not provider_google and not provider_ollama and not provider_grok_xai and not provider_groq and not provider_cohere" \
-q --tb=line \
--timeout=60 \
--ignore=tests/fixtures \
--ignore=tests/e2e \
--ignore=tests/live \
--ignore=tests/unit/jobs \
--ignore=tests/unit/api \
--cov=praisonai \
--cov-report=xml \
-n 4 \
--maxfail=10 \
|| echo "Some tests failed"
- name: Upload coverage
if: matrix.python-version == '3.11'
uses: codecov/codecov-action@v5
with:
token: ${{ secrets.CODECOV_TOKEN || '' }}
files: src/praisonai/coverage.xml
flags: main-tests
fail_ci_if_error: false
# ============================================
# OPENAI LIVE TESTS - Real OpenAI API calls
# Only runs if OPENAI_API_KEY secret is set
# Safe for forks (skips gracefully if no key)
# ============================================
openai-live:
needs: smoke
runs-on: ubuntu-latest
timeout-minutes: 8
# This job always runs but steps are conditional on secret availability
steps:
- name: Check if OpenAI key is available
id: check-key
run: |
if [ -n "${{ secrets.OPENAI_API_KEY }}" ]; then
echo "has_key=true" >> $GITHUB_OUTPUT
else
echo "has_key=false" >> $GITHUB_OUTPUT
echo "⚠️ OPENAI_API_KEY not set - skipping live tests"
fi
- uses: actions/checkout@v4
with:
persist-credentials: false
if: steps.check-key.outputs.has_key == 'true'
- name: Set up Python 3.11
if: steps.check-key.outputs.has_key == 'true'
uses: actions/setup-python@v5
with:
python-version: '3.11'
- name: Cache pip packages
if: steps.check-key.outputs.has_key == 'true'
uses: actions/cache@v4
with:
path: ~/.cache/pip
key: ${{ runner.os }}-pip-openai-${{ hashFiles('**/pyproject.toml') }}
restore-keys: |
${{ runner.os }}-pip-
- name: Install dependencies
if: steps.check-key.outputs.has_key == 'true'
run: |
pip install --upgrade pip
cd src/praisonai-agents
pip install -e ".[all]"
cd ../praisonai
pip install -e ".[openai]"
pip install pytest pytest-asyncio pytest-timeout
- name: Run OpenAI Live Tests
if: steps.check-key.outputs.has_key == 'true'
env:
PRAISONAI_TEST_TIER: extended
PRAISONAI_ALLOW_NETWORK: '1'
PRAISONAI_LIVE_TESTS: '1'
PRAISONAI_TEST_PROVIDERS: 'openai'
OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }}
OPENAI_MODEL_NAME: ${{ secrets.OPENAI_MODEL_NAME || 'gpt-4o-mini' }}
run: |
cd src/praisonai
python -m pytest tests/ \
-m "provider_openai or real" \
-v --tb=short \
--timeout=120 \
--ignore=tests/fixtures \
|| echo "Some OpenAI tests failed"
- name: Skip notice
if: steps.check-key.outputs.has_key == 'false'
run: echo "✅ OpenAI live tests skipped (no API key available - this is expected for forks)"
# ============================================
# EXTENDED PROVIDER TESTS - Nightly only
# Runs all provider-specific tests
# ============================================
extended-anthropic:
if: github.event_name == 'schedule' || github.event.inputs.tier == 'extended' || github.event.inputs.tier == 'nightly'
runs-on: ubuntu-latest
timeout-minutes: 10
steps:
- name: Check if Anthropic key is available
id: check-key
run: |
if [ -n "${{ secrets.ANTHROPIC_API_KEY }}" ]; then
echo "has_key=true" >> $GITHUB_OUTPUT
else
echo "has_key=false" >> $GITHUB_OUTPUT
echo "⚠️ ANTHROPIC_API_KEY not set - skipping tests"
fi
- uses: actions/checkout@v4
with:
persist-credentials: false
if: steps.check-key.outputs.has_key == 'true'
- name: Set up Python 3.11
if: steps.check-key.outputs.has_key == 'true'
uses: actions/setup-python@v5
with:
python-version: '3.11'
- name: Install dependencies
if: steps.check-key.outputs.has_key == 'true'
run: |
pip install --upgrade pip
cd src/praisonai-agents
pip install -e ".[all]"
cd ../praisonai
pip install -e ".[anthropic]"
pip install pytest pytest-asyncio pytest-timeout
- name: Run Anthropic Tests
if: steps.check-key.outputs.has_key == 'true'
env:
PRAISONAI_ALLOW_NETWORK: '1'
PRAISONAI_LIVE_TESTS: '1'
PRAISONAI_TEST_PROVIDERS: 'anthropic'
ANTHROPIC_API_KEY: ${{ secrets.ANTHROPIC_API_KEY }}
run: |
cd src/praisonai
python -m pytest tests/ \
-m "provider_anthropic" \
-v --tb=short \
--timeout=120 \
--ignore=tests/fixtures \
|| echo "Anthropic tests completed"
- name: Skip notice
if: steps.check-key.outputs.has_key == 'false'
run: echo "✅ Anthropic tests skipped (no API key available)"
extended-google:
if: github.event_name == 'schedule' || github.event.inputs.tier == 'extended' || github.event.inputs.tier == 'nightly'
runs-on: ubuntu-latest
timeout-minutes: 10
steps:
- name: Check if Google key is available
id: check-key
env:
GOOGLE_API_KEY: ${{ secrets.GOOGLE_API_KEY }}
run: |
if [ -n "$GOOGLE_API_KEY" ]; then
echo "has_key=true" >> $GITHUB_OUTPUT
else
echo "has_key=false" >> $GITHUB_OUTPUT
echo "⚠️ GOOGLE_API_KEY not set - skipping tests"
fi
- uses: actions/checkout@v4
with:
persist-credentials: false
if: steps.check-key.outputs.has_key == 'true'
- name: Set up Python 3.11
if: steps.check-key.outputs.has_key == 'true'
uses: actions/setup-python@v5
with:
python-version: '3.11'
- name: Install dependencies
if: steps.check-key.outputs.has_key == 'true'
run: |
pip install --upgrade pip
cd src/praisonai-agents
pip install -e ".[all]"
cd ../praisonai
pip install -e ".[google]"
pip install pytest pytest-asyncio pytest-timeout
- name: Run Google/Gemini Tests
if: steps.check-key.outputs.has_key == 'true'
env:
PRAISONAI_ALLOW_NETWORK: '1'
PRAISONAI_LIVE_TESTS: '1'
PRAISONAI_TEST_PROVIDERS: 'google'
GOOGLE_API_KEY: ${{ secrets.GOOGLE_API_KEY }}
run: |
cd src/praisonai
python -m pytest tests/ \
-m "provider_google" \
-v --tb=short \
--timeout=120 \
--ignore=tests/fixtures \
|| echo "Google tests completed"
- name: Skip notice
if: steps.check-key.outputs.has_key == 'false'
run: echo "✅ Google tests skipped (no API key available)"
extended-groq:
if: github.event_name == 'schedule' || github.event.inputs.tier == 'extended' || github.event.inputs.tier == 'nightly'
runs-on: ubuntu-latest
timeout-minutes: 10
steps:
- name: Check if Groq key is available
id: check-key
env:
GROQ_API_KEY: ${{ secrets.GROQ_API_KEY }}
run: |
if [ -n "$GROQ_API_KEY" ]; then
echo "has_key=true" >> $GITHUB_OUTPUT
else
echo "has_key=false" >> $GITHUB_OUTPUT
echo "⚠️ GROQ_API_KEY not set - skipping tests"
fi
- uses: actions/checkout@v4
with:
persist-credentials: false
if: steps.check-key.outputs.has_key == 'true'
- name: Set up Python 3.11
if: steps.check-key.outputs.has_key == 'true'
uses: actions/setup-python@v5
with:
python-version: '3.11'
- name: Install dependencies
if: steps.check-key.outputs.has_key == 'true'
run: |
pip install --upgrade pip
cd src/praisonai-agents
pip install -e ".[all]"
cd ../praisonai
pip install -e .
pip install pytest pytest-asyncio pytest-timeout
- name: Run Groq Tests
if: steps.check-key.outputs.has_key == 'true'
env:
PRAISONAI_ALLOW_NETWORK: '1'
PRAISONAI_LIVE_TESTS: '1'
PRAISONAI_TEST_PROVIDERS: 'groq'
GROQ_API_KEY: ${{ secrets.GROQ_API_KEY }}
run: |
cd src/praisonai
python -m pytest tests/ \
-m "provider_groq" \
-v --tb=short \
--timeout=120 \
--ignore=tests/fixtures \
|| echo "Groq tests completed"
- name: Skip notice
if: steps.check-key.outputs.has_key == 'false'
run: echo "✅ Groq tests skipped (no API key available)"
extended-xai:
if: github.event_name == 'schedule' || github.event.inputs.tier == 'extended' || github.event.inputs.tier == 'nightly'
runs-on: ubuntu-latest
timeout-minutes: 10
steps:
- name: Check if xAI key is available
id: check-key
env:
XAI_API_KEY: ${{ secrets.XAI_API_KEY }}
run: |
if [ -n "$XAI_API_KEY" ]; then
echo "has_key=true" >> $GITHUB_OUTPUT
else
echo "has_key=false" >> $GITHUB_OUTPUT
echo "⚠️ XAI_API_KEY not set - skipping tests"
fi
- uses: actions/checkout@v4
with:
persist-credentials: false
if: steps.check-key.outputs.has_key == 'true'
- name: Set up Python 3.11
if: steps.check-key.outputs.has_key == 'true'
uses: actions/setup-python@v5
with:
python-version: '3.11'
- name: Install dependencies
if: steps.check-key.outputs.has_key == 'true'
run: |
pip install --upgrade pip
cd src/praisonai-agents
pip install -e ".[all]"
cd ../praisonai
pip install -e .
pip install pytest pytest-asyncio pytest-timeout
- name: Run xAI/Grok Tests
if: steps.check-key.outputs.has_key == 'true'
env:
PRAISONAI_ALLOW_NETWORK: '1'
PRAISONAI_LIVE_TESTS: '1'
PRAISONAI_TEST_PROVIDERS: 'grok_xai'
XAI_API_KEY: ${{ secrets.XAI_API_KEY }}
run: |
cd src/praisonai
python -m pytest tests/ \
-m "provider_grok_xai" \
-v --tb=short \
--timeout=120 \
--ignore=tests/fixtures \
|| echo "xAI tests completed"
- name: Skip notice
if: steps.check-key.outputs.has_key == 'false'
run: echo "✅ xAI tests skipped (no API key available)"
extended-cohere:
if: github.event_name == 'schedule' || github.event.inputs.tier == 'extended' || github.event.inputs.tier == 'nightly'
runs-on: ubuntu-latest
timeout-minutes: 10
steps:
- name: Check if Cohere key is available
id: check-key
env:
COHERE_API_KEY: ${{ secrets.COHERE_API_KEY }}
run: |
if [ -n "$COHERE_API_KEY" ]; then
echo "has_key=true" >> $GITHUB_OUTPUT
else
echo "has_key=false" >> $GITHUB_OUTPUT
echo "⚠️ COHERE_API_KEY not set - skipping tests"
fi
- uses: actions/checkout@v4
with:
persist-credentials: false
if: steps.check-key.outputs.has_key == 'true'
- name: Set up Python 3.11
if: steps.check-key.outputs.has_key == 'true'
uses: actions/setup-python@v5
with:
python-version: '3.11'
- name: Install dependencies
if: steps.check-key.outputs.has_key == 'true'
run: |
pip install --upgrade pip
cd src/praisonai-agents
pip install -e ".[all]"
cd ../praisonai
pip install -e ".[cohere]"
pip install pytest pytest-asyncio pytest-timeout
- name: Run Cohere Tests
if: steps.check-key.outputs.has_key == 'true'
env:
PRAISONAI_ALLOW_NETWORK: '1'
PRAISONAI_LIVE_TESTS: '1'
PRAISONAI_TEST_PROVIDERS: 'cohere'
COHERE_API_KEY: ${{ secrets.COHERE_API_KEY }}
run: |
cd src/praisonai
python -m pytest tests/ \
-m "provider_cohere" \
-v --tb=short \
--timeout=120 \
--ignore=tests/fixtures \
|| echo "Cohere tests completed"
- name: Skip notice
if: steps.check-key.outputs.has_key == 'false'
run: echo "✅ Cohere tests skipped (no API key available)"
# ============================================
# TEST SUMMARY
# ============================================
test-summary:
needs: [smoke, main]
if: always()
runs-on: ubuntu-latest
steps:
- name: Test Summary
run: |
echo "# 📊 Test Suite Summary" >> $GITHUB_STEP_SUMMARY
echo "" >> $GITHUB_STEP_SUMMARY
echo "| Job | Status |" >> $GITHUB_STEP_SUMMARY
echo "|-----|--------|" >> $GITHUB_STEP_SUMMARY
echo "| Smoke | ${{ needs.smoke.result }} |" >> $GITHUB_STEP_SUMMARY
echo "| Main | ${{ needs.main.result }} |" >> $GITHUB_STEP_SUMMARY
echo "" >> $GITHUB_STEP_SUMMARY
echo "## Test Tiers" >> $GITHUB_STEP_SUMMARY
echo "- **smoke**: Fast unit tests, no network (≤2 min)" >> $GITHUB_STEP_SUMMARY
echo "- **main**: Unit + integration, no network (≤5 min)" >> $GITHUB_STEP_SUMMARY
echo "- **openai-live**: OpenAI API tests (when key available)" >> $GITHUB_STEP_SUMMARY
echo "- **extended-***: Provider-specific tests (nightly)" >> $GITHUB_STEP_SUMMARY
+8 -20
View File
@@ -34,21 +34,14 @@ jobs:
steps:
- name: 🚨 Cost Warning
env:
INPUT_FRAMEWORK: ${{ github.event.inputs.framework }}
INPUT_CONFIRM_COSTS: ${{ github.event.inputs.confirm_costs }}
run: |
echo "⚠️ WARNING: This workflow will make real API calls!"
echo "💰 This may incur charges on your API accounts"
echo "🎯 Framework: $INPUT_FRAMEWORK"
echo "✅ Cost confirmation: $INPUT_CONFIRM_COSTS"
echo "🎯 Framework: ${{ github.event.inputs.framework }}"
echo "✅ Cost confirmation: ${{ github.event.inputs.confirm_costs }}"
- name: Checkout code
uses: actions/checkout@v4
with:
persist-credentials: false
with:
persist-credentials: false
- name: Set up Python ${{ matrix.python-version }}
uses: actions/setup-python@v5
@@ -100,23 +93,21 @@ jobs:
- name: Generate Real Test Report
if: always()
env:
INPUT_FRAMEWORK: ${{ github.event.inputs.framework }}
run: |
echo "# 🔥 Real End-to-End Test Report" > real_test_report.md
echo "" >> real_test_report.md
echo "⚠️ **WARNING: This report represents tests that made real API calls**" >> real_test_report.md
echo "" >> real_test_report.md
echo "**Framework Tested:** $INPUT_FRAMEWORK" >> real_test_report.md
echo "**Framework Tested:** ${{ github.event.inputs.framework }}" >> real_test_report.md
echo "**Python Version:** ${{ matrix.python-version }}" >> real_test_report.md
echo "**Date:** $(date -u)" >> real_test_report.md
echo "**Triggered by:** $GITHUB_ACTOR" >> real_test_report.md
echo "**Triggered by:** ${{ github.actor }}" >> real_test_report.md
echo "" >> real_test_report.md
echo "## 🧪 Test Results" >> real_test_report.md
echo "" >> real_test_report.md
if [ "$INPUT_FRAMEWORK" == "autogen" ] || [ "$INPUT_FRAMEWORK" == "all" ]; then
if [ "${{ github.event.inputs.framework }}" == "autogen" ] || [ "${{ github.event.inputs.framework }}" == "all" ]; then
echo "### AutoGen Real Tests:" >> real_test_report.md
echo "- Environment verification" >> real_test_report.md
echo "- Agent creation with real API calls" >> real_test_report.md
@@ -124,7 +115,7 @@ jobs:
echo "" >> real_test_report.md
fi
if [ "$INPUT_FRAMEWORK" == "crewai" ] || [ "$INPUT_FRAMEWORK" == "all" ]; then
if [ "${{ github.event.inputs.framework }}" == "crewai" ] || [ "${{ github.event.inputs.framework }}" == "all" ]; then
echo "### CrewAI Real Tests:" >> real_test_report.md
echo "- Environment verification" >> real_test_report.md
echo "- Crew creation with real API calls" >> real_test_report.md
@@ -159,14 +150,11 @@ jobs:
steps:
- name: 🛡️ Safety Check Failed
env:
INPUT_FRAMEWORK: ${{ github.event.inputs.framework }}
INPUT_CONFIRM_COSTS: ${{ github.event.inputs.confirm_costs }}
run: |
echo "🚨 Real tests not executed due to safety checks:"
echo ""
echo "✅ Costs confirmed: $INPUT_CONFIRM_COSTS"
echo "✅ Framework selected: $INPUT_FRAMEWORK"
echo "✅ Costs confirmed: ${{ github.event.inputs.confirm_costs }}"
echo "✅ Framework selected: ${{ github.event.inputs.framework }}"
echo ""
echo "To run real tests:"
echo "1. Select a framework (autogen, crewai, or all)"
-218
View File
@@ -1,218 +0,0 @@
name: Windows Tests
on:
push:
branches: [main, develop]
paths:
- 'src/**'
- 'pyproject.toml'
- '.github/workflows/test-windows.yml'
pull_request:
branches: [main, develop]
paths:
- 'src/**'
- 'pyproject.toml'
- '.github/workflows/test-windows.yml'
workflow_dispatch:
jobs:
test-windows:
runs-on: windows-latest
timeout-minutes: 5
env:
OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }}
OPENAI_MODEL_NAME: gpt-4o-mini
PYTHONUTF8: 1
steps:
- uses: actions/checkout@v4
with:
persist-credentials: false
- name: Set up Python 3.11
uses: actions/setup-python@v5
with:
python-version: "3.11"
- name: Install praisonaiagents
run: |
python -m pip install --upgrade pip
cd src/praisonai-agents
pip install -e .
shell: bash
- name: Install praisonai wrapper
run: |
cd src/praisonai
pip install -e .
shell: bash
# ==================== CORE IMPORTS ====================
- name: Test core imports
run: |
python -c "from praisonaiagents import Agent, Agents, Workflow; print('Core imports OK')"
python -c "from praisonaiagents import tool, Tools; print('Tool imports OK')"
python -c "from praisonaiagents import Task; print('Task imports OK')"
# ==================== AGENT FEATURES ====================
- name: Test Agent instantiation
run: |
python -c "
from praisonaiagents import Agent
a = Agent(name='Test', instructions='You are helpful')
print('Agent created:', a.name)
a2 = Agent(name='ToolAgent', instructions='Use tools', tools=[])
print('Agent with tools:', a2.name)
"
- name: Test Agents orchestration
run: |
python -c "
from praisonaiagents import Agent, Agents, Task
a1 = Agent(name='Agent1', instructions='First agent')
a2 = Agent(name='Agent2', instructions='Second agent')
t = Task(description='Do something', agent=a1)
agents = Agents(agents=[a1, a2], tasks=[t])
print('Agents:', len(agents.agents), 'Tasks:', len(agents.tasks))
"
# ==================== WORKFLOW FEATURES ====================
- name: Test Workflow
run: |
python -c "
from praisonaiagents import Workflow
w = Workflow(name='test')
print('Workflow:', w.name)
"
# ==================== MEMORY FEATURES ====================
- name: Test Memory classes
run: |
python -c "
from praisonaiagents.memory import FileMemory
from praisonaiagents.config import MemoryConfig
cfg = MemoryConfig(backend='file', user_id='test_user')
print('MemoryConfig backend:', cfg.backend)
mem = FileMemory(user_id='test_user', base_path='.praison/test_memory')
print('FileMemory user:', mem.user_id)
"
# ==================== TOOL DECORATOR ====================
- name: Test tool decorator
run: |
python -c "
from praisonaiagents import tool
@tool
def my_tool(query: str) -> str:
'''A test tool'''
return f'Echo: {query}'
result = my_tool('hello')
print('Tool result:', result)
"
# ==================== CONFIG CLASSES ====================
- name: Test config classes
run: |
python -c "
from praisonaiagents.config import OutputConfig, ExecutionConfig, PlanningConfig
out_cfg = OutputConfig(verbose=True, stream=True)
print('OutputConfig verbose:', out_cfg.verbose)
exec_cfg = ExecutionConfig(max_iter=50, max_retry_limit=5)
print('ExecutionConfig max_iter:', exec_cfg.max_iter)
plan_cfg = PlanningConfig(reasoning=True, auto_approve=False)
print('PlanningConfig reasoning:', plan_cfg.reasoning)
"
# ==================== HANDOFF ====================
- name: Test Handoff
run: |
python -c "
from praisonaiagents import Handoff, handoff, Agent
a1 = Agent(name='Agent1', instructions='First')
a2 = Agent(name='Agent2', instructions='Second')
# Using Handoff class directly
h = Handoff(agent=a2)
print('Handoff tool name:', h.tool_name)
# Using handoff function
h2 = handoff(a1, tool_name_override='custom_handoff')
print('Custom handoff name:', h2.tool_name)
"
# ==================== ASYNC FEATURES ====================
- name: Test async imports
run: |
python -c "
import asyncio
from praisonaiagents import Agent
async def test_async():
agent = Agent(name='AsyncAgent', instructions='Test')
assert hasattr(agent, 'arun'), 'Missing arun'
assert hasattr(agent, 'astart'), 'Missing astart'
print('Async methods available')
asyncio.run(test_async())
"
# ==================== CLI COMMANDS ====================
- name: Test CLI help
run: praisonai --help
- name: Test CLI session list
run: praisonai session list
continue-on-error: true
- name: Test CLI queue list
run: praisonai queue list
continue-on-error: true
# ==================== PACKAGING TESTS ====================
- name: Test packaging/daemon entry points
run: |
echo "Testing both entry point methods..."
python -m praisonai --version
praisonai --version
- name: Test doctor packaging command
run: |
echo "Testing doctor packaging diagnostics..."
praisonai doctor packaging --json
# ==================== REAL API TESTS ====================
- name: Real API test - Agent run
if: env.OPENAI_API_KEY != ''
run: |
python -c "
from praisonaiagents import Agent
agent = Agent(name='TestAgent', instructions='Reply with exactly: WINDOWS_OK', llm='gpt-4o-mini')
result = agent.run('Say WINDOWS_OK')
print('Result:', result)
print('Real API test passed')
"
- name: Real API test - Multi-agent
if: env.OPENAI_API_KEY != ''
run: |
python -c "
from praisonaiagents import Agent, Agents, Task
researcher = Agent(name='Researcher', instructions='You research topics', llm='gpt-4o-mini')
writer = Agent(name='Writer', instructions='You write content', llm='gpt-4o-mini')
task = Task(description='Say hello world', agent=researcher)
agents = Agents(agents=[researcher, writer], tasks=[task])
result = agents.start()
print('Multi-agent result type:', type(result))
print('Multi-agent test passed')
"
+516
View File
@@ -0,0 +1,516 @@
name: Quick Validation Tests
on: [push, pull_request]
jobs:
quick-test:
runs-on: ubuntu-latest
timeout-minutes: 15
steps:
- name: Checkout code
uses: actions/checkout@v4
- name: Set up Python
uses: actions/setup-python@v5
with:
python-version: 3.11
- name: Install UV
run: |
curl -LsSf https://astral.sh/uv/install.sh | sh
echo "$HOME/.local/bin" >> $GITHUB_PATH
- name: Install dependencies
run: |
cd src/praisonai
uv pip install --system ."[ui,gradio,api,agentops,google,openai,anthropic,cohere,chat,code,realtime,call,crewai,autogen]"
uv pip install --system duckduckgo_search
uv pip install --system pytest pytest-asyncio pytest-cov pytest-timeout
# Install knowledge dependencies from praisonai-agents
uv pip install --system "praisonaiagents[knowledge]"
- name: Set environment variables
run: |
echo "OPENAI_API_KEY=${{ secrets.OPENAI_API_KEY || 'sk-test-key-for-github-actions-testing-only-not-real' }}" >> $GITHUB_ENV
echo "OPENAI_API_BASE=${{ secrets.OPENAI_API_BASE || 'https://api.openai.com/v1' }}" >> $GITHUB_ENV
echo "OPENAI_MODEL_NAME=${{ secrets.OPENAI_MODEL_NAME || 'gpt-5-nano' }}" >> $GITHUB_ENV
echo "LOGLEVEL=DEBUG" >> $GITHUB_ENV
echo "PYTHONPATH=${{ github.workspace }}/src/praisonai-agents:$PYTHONPATH" >> $GITHUB_ENV
- name: Backup Root Config Files
run: |
echo "🔄 Backing up root configuration files to prevent default file resolution interference..."
echo "ℹ️ PraisonAI automatically uses 'agents.yaml' in working directory when no file specified"
echo "ℹ️ This can interfere with test files that specify their own YAML files"
if [ -f "agents.yaml" ]; then
mv agents.yaml agents.yaml.backup
echo "✅ Moved root agents.yaml to agents.yaml.backup"
echo " - This prevents default file fallback during tests"
fi
if [ -f "tools.py" ]; then
mv tools.py tools.py.backup
echo "✅ Moved tools.py to tools.py.backup"
fi
- name: Debug API Key Status
run: |
echo "🔍 Checking API key availability..."
if [ -n "${{ secrets.OPENAI_API_KEY }}" ]; then
echo "✅ GitHub secret OPENAI_API_KEY is available"
echo "🔑 API key starts with: $(echo "$OPENAI_API_KEY" | cut -c1-7)..."
else
echo "⚠️ GitHub secret OPENAI_API_KEY is NOT set - using fallback"
echo "🔑 Using fallback key: sk-test-key..."
fi
echo "🌐 API Base: $OPENAI_API_BASE"
echo "🤖 Model: $OPENAI_MODEL_NAME"
echo "🐛 Log Level: $LOGLEVEL"
echo "📊 Environment Check:"
echo " - OPENAI_API_KEY length: ${#OPENAI_API_KEY}"
echo " - OPENAI_API_BASE: $OPENAI_API_BASE"
echo " - OPENAI_MODEL_NAME: $OPENAI_MODEL_NAME"
echo " - LOGLEVEL: $LOGLEVEL"
- name: Debug Python Environment Variables
run: |
python -c "
import os
print('🐍 Python Environment Variable Check:')
api_key = os.environ.get('OPENAI_API_KEY', 'NOT_SET')
if api_key != 'NOT_SET':
print(f' ✅ OPENAI_API_KEY: {api_key[:7]}... (length: {len(api_key)})')
else:
print(' ❌ OPENAI_API_KEY: NOT_SET')
print(f' 🌐 OPENAI_API_BASE: {os.environ.get(\"OPENAI_API_BASE\", \"NOT_SET\")}')
print(f' 🤖 OPENAI_MODEL_NAME: {os.environ.get(\"OPENAI_MODEL_NAME\", \"NOT_SET\")}')
print(f' 📋 All OPENAI env vars:')
for key, value in os.environ.items():
if key.startswith('OPENAI'):
print(f' {key}: {value[:10] if len(value) > 10 else value}...')
"
- name: Find Researcher Role Source
run: |
echo "🔍 Hunting for the mysterious 'Researcher' role..."
cd src/praisonai
python -c "
import os
import yaml
import glob
print('📋 Searching for Researcher role in all YAML files:')
yaml_files = glob.glob('src/praisonai/tests/*.yaml')
for yaml_file in yaml_files:
try:
with open(yaml_file, 'r') as f:
config = yaml.safe_load(f)
# Check if any role contains 'researcher'
roles = config.get('roles', {})
for role_key, role_data in roles.items():
role_name = role_data.get('role', '')
if 'researcher' in role_key.lower() or 'researcher' in role_name.lower():
print(f' 🎯 FOUND in {yaml_file}:')
print(f' Framework: {config.get(\"framework\", \"NOT_SET\")}')
print(f' Role key: {role_key}')
print(f' Role name: {role_name}')
print(f' All roles: {list(roles.keys())}')
print()
except Exception as e:
print(f' ❌ Error reading {yaml_file}: {e}')
print('🔍 Checking for default configurations...')
# Check if there are any default configs or hardcoded roles
try:
import praisonai
print(f' PraisonAI package location: {praisonai.__file__}')
# Check if there are any example YAML files in the package
package_dir = os.path.dirname(praisonai.__file__)
for root, dirs, files in os.walk(package_dir):
for file in files:
if file.endswith(('.yaml', '.yml')):
file_path = os.path.join(root, file)
print(f' 📁 Found YAML in package: {file_path}')
except Exception as e:
print(f' ❌ Error checking package: {e}')
"
continue-on-error: true
- name: Trace AutoGen Execution Path
run: |
echo "🔍 Tracing AutoGen execution to find where it diverges..."
cd src/praisonai
python -c "
import os
import sys
sys.path.insert(0, '.')
try:
from praisonai import PraisonAI
from praisonai.agents_generator import AgentsGenerator
# Test the exact execution path
print('🎯 Testing AutoGen execution path:')
praisonai = PraisonAI(agent_file='tests/autogen-agents.yaml')
print(f' 1. PraisonAI framework: \"{praisonai.framework}\"')
agents_gen = AgentsGenerator(
agent_file='tests/autogen-agents.yaml',
framework=praisonai.framework,
config_list=praisonai.config_list
)
print(f' 2. AgentsGenerator framework: \"{agents_gen.framework}\"')
# Load the YAML to check what it contains
import yaml
with open('src/praisonai/tests/autogen-agents.yaml', 'r') as f:
config = yaml.safe_load(f)
framework = agents_gen.framework or config.get('framework')
print(f' 3. Final framework decision: \"{framework}\"')
print(f' 4. Available frameworks:')
# Check framework availability
try:
import autogen
print(f' ✅ AutoGen available')
except ImportError:
print(f' ❌ AutoGen NOT available')
try:
from praisonaiagents import Agent
print(f' ✅ PraisonAI agents available')
except ImportError:
print(f' ❌ PraisonAI agents NOT available')
try:
from crewai import Agent
print(f' ✅ CrewAI available')
except ImportError:
print(f' ❌ CrewAI NOT available')
print(f' 5. Roles in YAML: {list(config.get(\"roles\", {}).keys())}')
# Now test the actual framework execution
if framework == 'autogen':
print(f' 6. ✅ Should execute _run_autogen')
elif framework == 'praisonai':
print(f' 6. ❌ Would execute _run_praisonai (WRONG!)')
else:
print(f' 6. ❌ Would execute _run_crewai (DEFAULT FALLBACK)')
except Exception as e:
print(f'❌ Error tracing execution: {e}')
import traceback
traceback.print_exc()
"
continue-on-error: true
- name: Debug YAML Loading and Roles
run: |
echo "🔍 Tracing YAML file loading and role creation..."
cd src/praisonai
python -c "
import os
import sys
import yaml
sys.path.insert(0, '.')
print('📁 Available YAML files in src/praisonai/tests/:')
import glob
yaml_files = glob.glob('tests/*.yaml')
for f in yaml_files:
print(f' {f}')
print()
print('📋 Content of autogen-agents.yaml:')
with open('tests/autogen-agents.yaml', 'r') as f:
config = yaml.safe_load(f)
print(f' Framework: {config.get(\"framework\")}')
print(f' Topic: {config.get(\"topic\")}')
print(f' Roles: {list(config.get(\"roles\", {}).keys())}')
for role_key, role_data in config.get('roles', {}).items():
print(f' {role_key} -> {role_data.get(\"role\", \"NO_ROLE\")}')
print()
print('🔍 Checking if execution uses a different YAML:')
# Check other YAML files for 'Researcher' role
for yaml_file in yaml_files:
try:
with open(yaml_file, 'r') as f:
test_config = yaml.safe_load(f)
roles = test_config.get('roles', {})
for role_key, role_data in roles.items():
if 'researcher' in role_key.lower() or 'researcher' in role_data.get('role', '').lower():
print(f' 🎯 FOUND Researcher in {yaml_file}!')
print(f' Framework: {test_config.get(\"framework\")}')
print(f' Role key: {role_key} -> {role_data.get(\"role\")}')
except:
pass
"
continue-on-error: true
- name: Debug Framework Detection
run: |
echo "🔍 Testing framework detection and config flow..."
python -c "
import os
import sys
import yaml
sys.path.insert(0, '.')
print('🔧 Testing framework detection:')
# Load the YAML file
with open('tests/autogen-agents.yaml', 'r') as f:
config = yaml.safe_load(f)
print(f' 📋 YAML framework: {config.get(\"framework\", \"NOT_SET\")}')
print(f' 📋 YAML topic: {config.get(\"topic\", \"NOT_SET\")}')
try:
from praisonai import PraisonAI
from praisonai.agents_generator import AgentsGenerator
# Test PraisonAI initialization
praisonai = PraisonAI(agent_file='tests/autogen-agents.yaml')
print(f' 🎯 PraisonAI framework: {praisonai.framework}')
# Test AgentsGenerator initialization
agents_gen = AgentsGenerator(
agent_file='tests/autogen-agents.yaml',
framework=praisonai.framework,
config_list=praisonai.config_list
)
print(f' ⚙️ AgentsGenerator framework: {agents_gen.framework}')
print(f' ⚙️ Final framework decision: {agents_gen.framework or config.get(\"framework\")}')
# Check config_list
print(f' 🔑 Config list model: {praisonai.config_list[0].get(\"model\")}')
print(f' 🔑 Config list API key: {praisonai.config_list[0].get(\"api_key\", \"NOT_SET\")[:10]}...')
except Exception as e:
print(f'❌ Error in framework detection: {e}')
"
continue-on-error: true
- name: Debug PraisonAIModel API Key Flow
run: |
echo "🔍 Testing PraisonAIModel API key handling..."
cd src/praisonai
python -c "
import os
import sys
sys.path.insert(0, '.')
print('🔑 Environment API Key Check:')
env_key = os.environ.get('OPENAI_API_KEY', 'NOT_FOUND')
print(f' OPENAI_API_KEY: {env_key[:10] if env_key != \"NOT_FOUND\" else \"NOT_FOUND\"}...')
try:
from praisonai.inc.models import PraisonAIModel
# Test PraisonAIModel with openai/gpt-5-nano (from YAML)
model = PraisonAIModel(model='openai/gpt-5-nano')
print('🤖 PraisonAIModel Configuration:')
print(f' model: {model.model}')
print(f' model_name: {model.model_name}')
print(f' api_key_var: {model.api_key_var}')
print(f' api_key: {model.api_key[:10] if model.api_key != \"nokey\" else \"DEFAULT_NOKEY\"}...')
print(f' base_url: {model.base_url}')
if model.api_key == 'nokey':
print('❌ FOUND THE ISSUE: PraisonAIModel is using default \"nokey\" instead of environment variable!')
else:
print('✅ PraisonAIModel has valid API key from environment')
except Exception as e:
print(f'❌ Error testing PraisonAIModel: {e}')
"
continue-on-error: true
- name: Validate API Key
run: |
echo "🔑 Testing API key validity with minimal OpenAI call..."
python -c "
import os
try:
from openai import OpenAI
client = OpenAI(api_key=os.environ.get('OPENAI_API_KEY'))
# Make a minimal API call to test key validity
response = client.models.list()
print('✅ API Key is VALID - OpenAI responded successfully')
print(f'📊 Available models: {len(list(response.data))} models found')
except Exception as e:
print(f'❌ API Key is INVALID - Error: {e}')
print('🔍 This explains why all API-dependent tests are failing')
print('💡 The GitHub secret OPENAI_API_KEY needs to be updated with a valid key')
"
continue-on-error: true
- name: Test Direct PraisonAI Execution
run: |
echo "🧪 Testing direct PraisonAI execution (what works locally)..."
python -m praisonai src/praisonai/tests/autogen-agents.yaml
continue-on-error: true
- name: Comprehensive Execution Debug
run: |
echo "🔍 Comprehensive debugging of PraisonAI execution path..."
cd src/praisonai
python -c "
import os
import sys
import yaml
sys.path.insert(0, '.')
print('=' * 60)
print('🔍 COMPREHENSIVE EXECUTION DEBUG')
print('=' * 60)
# Check current working directory
print(f'📁 Current working directory: {os.getcwd()}')
# List files in current directory
print('📋 Files in current directory:')
for f in os.listdir('.'):
print(f' {f}')
print()
print('📋 Files in src/praisonai/tests/ directory:')
for f in os.listdir('tests'):
if f.endswith('.yaml'):
print(f' src/praisonai/tests/{f}')
# Check if root agents.yaml exists
print()
if os.path.exists('agents.yaml'):
print('❌ ROOT agents.yaml EXISTS (this is the problem!)')
with open('agents.yaml', 'r') as f:
root_config = yaml.safe_load(f)
print(f' Root framework: {root_config.get(\"framework\")}')
print(f' Root roles: {list(root_config.get(\"roles\", {}).keys())}')
else:
print('✅ ROOT agents.yaml does NOT exist (good!)')
# Test the actual execution path
print()
print('🎯 Testing EXACT execution path:')
try:
from praisonai import PraisonAI
from praisonai.agents_generator import AgentsGenerator
# Test with full path
test_file = 'src/praisonai/tests/autogen-agents.yaml'
print(f' Using test file: {test_file}')
print(f' File exists: {os.path.exists(test_file)}')
# Load the test file directly
with open(test_file, 'r') as f:
test_config = yaml.safe_load(f)
print(f' Test file framework: {test_config.get(\"framework\")}')
print(f' Test file roles: {list(test_config.get(\"roles\", {}).keys())}')
# Create PraisonAI instance
praisonai = PraisonAI(agent_file=test_file)
print(f' PraisonAI.agent_file: {praisonai.agent_file}')
print(f' PraisonAI.framework: {praisonai.framework}')
# Create AgentsGenerator
agents_gen = AgentsGenerator(
agent_file=test_file,
framework=praisonai.framework,
config_list=praisonai.config_list
)
print(f' AgentsGenerator.agent_file: {agents_gen.agent_file}')
print(f' AgentsGenerator.framework: {agents_gen.framework}')
# Test what would happen in generate_crew_and_kickoff
print()
print('🔧 Testing generate_crew_and_kickoff logic:')
# Simulate the loading logic
if agents_gen.agent_yaml:
loaded_config = yaml.safe_load(agents_gen.agent_yaml)
print(' Would load from agent_yaml')
else:
if agents_gen.agent_file == '/app/api:app' or agents_gen.agent_file == 'api:app':
agents_gen.agent_file = 'agents.yaml'
print(f' Would change agent_file to: {agents_gen.agent_file}')
try:
with open(agents_gen.agent_file, 'r') as f:
loaded_config = yaml.safe_load(f)
print(f' Successfully loaded: {agents_gen.agent_file}')
except FileNotFoundError:
print(f' FileNotFoundError: {agents_gen.agent_file}')
loaded_config = None
if loaded_config:
final_framework = agents_gen.framework or loaded_config.get('framework')
print(f' Final framework decision: {final_framework}')
print(f' Loaded roles: {list(loaded_config.get(\"roles\", {}).keys())}')
if 'researcher' in loaded_config.get('roles', {}):
print(' ❌ FOUND Researcher role in loaded config!')
else:
print(' ✅ No Researcher role in loaded config')
except Exception as e:
print(f'❌ Error during execution debug: {e}')
import traceback
traceback.print_exc()
"
continue-on-error: true
- name: Run Fast Tests
run: |
# Run the fastest, most essential tests with coverage
cd src/praisonai && python -m pytest tests/unit/test_core_agents.py -v --tb=short --disable-warnings --cov=praisonai --cov-report=xml --cov-branch
- name: Run Real API Tests
run: |
echo "🔑 Running real API tests with actual OpenAI API key..."
cd src/praisonai && python -m pytest tests/test_agents_playbook.py -v --tb=short --disable-warnings -m real
continue-on-error: true
- name: Run E2E Real Tests
run: |
echo "🧪 Running E2E real tests..."
cd src/praisonai && python -m pytest tests/e2e/ -v --tb=short --disable-warnings -m real
continue-on-error: true
- name: Run Legacy Example Tests
run: |
cd src/praisonai && python -m pytest tests/test.py -v --tb=short --disable-warnings -m "not real" --timeout=60
continue-on-error: true
- name: Upload coverage reports to Codecov
uses: codecov/codecov-action@v5
with:
token: ${{ secrets.CODECOV_TOKEN }}
file: src/praisonai/coverage.xml
flags: quick-validation
name: quick-validation-coverage
fail_ci_if_error: false
verbose: true
- name: Restore Root Config Files
run: |
echo "🔄 Restoring root configuration files..."
if [ -f "agents.yaml.backup" ]; then
mv agents.yaml.backup agents.yaml
echo "✅ Restored agents.yaml"
fi
if [ -f "tools.py.backup" ]; then
mv tools.py.backup tools.py
echo "✅ Restored tools.py"
fi
if: always() # Always run this step, even if previous steps failed
-57
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@@ -1,57 +0,0 @@
name: Update API Reference
on:
push:
branches: [ "main" ]
paths:
- 'src/praisonai-agents/praisonaiagents/**/*.py'
- 'src/praisonai/praisonai/**/*.py'
- 'src/praisonai-ts/src/**/*.ts'
- '.github/workflows/update-api-md.yml'
permissions:
contents: write
jobs:
update-api-md:
runs-on: ubuntu-latest
steps:
- name: Checkout repository
uses: actions/checkout@v4
with:
ref: main
persist-credentials: true
fetch-depth: 0
- name: Set up Python
uses: actions/setup-python@v5
with:
python-version: '3.11'
- name: Generate api.md
run: |
cd $GITHUB_WORKSPACE
python3 src/praisonai/scripts/generate_api_md.py
- name: Check for changes
id: check_changes
run: |
if git diff --quiet api.md; then
echo "changes=false" >> $GITHUB_OUTPUT
echo "No changes to api.md"
else
echo "changes=true" >> $GITHUB_OUTPUT
echo "api.md has been updated"
git diff api.md | head -50
fi
- name: Commit and push changes
if: steps.check_changes.outputs.changes == 'true'
uses: stefanzweifel/git-auto-commit-action@v5
with:
commit_message: "docs: auto-update api.md [skip ci]"
file_pattern: 'api.md'
commit_user_name: "MervinPraison"
commit_user_email: "[email protected]"
commit_author: "MervinPraison <[email protected]>"
-83
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@@ -1,83 +0,0 @@
name: Update Documentation Parity Tracker
on:
push:
branches: [ "main" ]
paths:
- 'src/praisonai-agents/praisonaiagents/**/*.py'
- 'src/praisonai-ts/src/**/*.ts'
- 'src/praisonai-rust/src/**/*.rs'
- 'src/praisonai/praisonai/_dev/parity/**/*.py'
- '.github/workflows/update-docs-parity.yml'
workflow_dispatch: # Allow manual trigger
permissions:
contents: write
jobs:
update-docs-parity:
runs-on: ubuntu-latest
steps:
- name: Checkout repository
uses: actions/checkout@v4
with:
ref: main
persist-credentials: true
fetch-depth: 0
- name: Checkout PraisonAIDocs
id: checkout_docs
continue-on-error: true
uses: actions/checkout@v4
with:
repository: MervinPraison/PraisonAIDocs
path: PraisonAIDocs
token: ${{ secrets.SECRETS_ADMIN_PAT }}
- name: Set up Python
uses: actions/setup-python@v5
with:
python-version: '3.11'
- name: Install dependencies
run: |
pip install pyyaml
- name: Generate docs parity trackers
if: steps.checkout_docs.outcome == 'success'
run: |
cd $GITHUB_WORKSPACE
python3 src/praisonai/scripts/generate_docs_parity.py --docs-root PraisonAIDocs/docs --copy-docs
- name: Check for changes
id: check_changes
run: |
if git diff --quiet src/praisonai-agents/DOCS_PARITY.md src/praisonai-ts/DOCS_PARITY.md src/praisonai-rust/DOCS_PARITY.md 2>/dev/null; then
echo "changes=false" >> $GITHUB_OUTPUT
echo "No changes to docs parity trackers"
else
echo "changes=true" >> $GITHUB_OUTPUT
echo "Docs parity trackers have been updated"
git diff --stat src/praisonai-agents/DOCS_PARITY.md src/praisonai-ts/DOCS_PARITY.md src/praisonai-rust/DOCS_PARITY.md
fi
- name: Commit and push changes to praisonai-package
if: steps.check_changes.outputs.changes == 'true'
uses: stefanzweifel/git-auto-commit-action@v5
with:
commit_message: "docs: auto-update documentation parity trackers [skip ci]"
file_pattern: 'src/praisonai-agents/DOCS_PARITY.md src/praisonai-ts/DOCS_PARITY.md src/praisonai-rust/DOCS_PARITY.md'
commit_user_name: "MervinPraison"
commit_user_email: "[email protected]"
commit_author: "MervinPraison <[email protected]>"
- name: Commit and push changes to PraisonAIDocs
if: steps.check_changes.outputs.changes == 'true' && steps.checkout_docs.outcome == 'success'
run: |
cd PraisonAIDocs
git config user.name "MervinPraison"
git config user.email "[email protected]"
git add docs/features/DOCS_PARITY.md docs/js/DOCS_PARITY.md docs/rust/DOCS_PARITY.md
git diff --staged --quiet || git commit -m "docs: auto-update documentation parity trackers [skip ci]"
git push
@@ -1,61 +0,0 @@
name: Update Feature Parity Tracker
on:
push:
branches: [ "main" ]
paths:
- 'src/praisonai-agents/praisonaiagents/**/*.py'
- 'src/praisonai-ts/src/**/*.ts'
- 'src/praisonai-rust/src/**/*.rs'
- '.github/workflows/update-parity-tracker.yml'
permissions:
contents: write
jobs:
update-parity-tracker:
runs-on: ubuntu-latest
steps:
- name: Checkout repository
uses: actions/checkout@v4
with:
ref: main
persist-credentials: true
fetch-depth: 0
- name: Set up Python
uses: actions/setup-python@v5
with:
python-version: '3.11'
- name: Install dependencies
run: pip install pyyaml
- name: Generate parity trackers
run: |
cd $GITHUB_WORKSPACE
python3 src/praisonai/scripts/generate_parity_tracker.py
- name: Check for changes
id: check_changes
run: |
if git diff --quiet src/praisonai-ts/FEATURE_PARITY_TRACKER.json src/praisonai-ts/PARITY.md src/praisonai-rust/FEATURE_PARITY_TRACKER.json src/praisonai-rust/PARITY.md 2>/dev/null; then
echo "changes=false" >> $GITHUB_OUTPUT
echo "No changes to parity trackers"
else
echo "changes=true" >> $GITHUB_OUTPUT
echo "Parity trackers have been updated"
git diff src/praisonai-ts/FEATURE_PARITY_TRACKER.json | head -50
fi
- name: Commit and push changes
if: steps.check_changes.outputs.changes == 'true'
uses: stefanzweifel/git-auto-commit-action@v5
with:
commit_message: "docs: auto-update feature parity trackers [skip ci]"
file_pattern: 'src/praisonai-ts/FEATURE_PARITY_TRACKER.json src/praisonai-ts/PARITY.md src/praisonai-rust/FEATURE_PARITY_TRACKER.json src/praisonai-rust/PARITY.md'
commit_user_name: "MervinPraison"
commit_user_email: "[email protected]"
commit_author: "MervinPraison <[email protected]>"
+1 -17
View File
@@ -20,8 +20,6 @@ watch.sh
docs.sh
other
output
!src/praisonai/praisonai/cli/output/
!src/praisonai-agents/praisonaiagents/output/
.files
threads.db
@@ -84,18 +82,4 @@ issue_details.json
# MCP Registry tokens
.mcpregistry_*
*.log
.internal
.praisonai
# Rust / Cargo
target/
Cargo.lock
**/*.rs.bk
*.pdb
.windsurf
src/praisonai/build*.egg-info/
src/praisonai/PraisonAI.egg-info/
jobs/*
*.egg-info
*.log
+2999 -581
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File diff suppressed because it is too large. Load diff
-1316
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File diff suppressed because it is too large. Load diff
+71
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@@ -0,0 +1,71 @@
"""
Auto-generated API server for PraisonAI agents.
"""
from flask import Flask, request, jsonify
from flask_cors import CORS
from praisonai import PraisonAI
import os
app = Flask(__name__)
# CORS configuration
CORS(app)
# Authentication
AUTH_ENABLED = False
AUTH_TOKEN = None
def check_auth():
"""Check authentication if enabled."""
if not AUTH_ENABLED:
return True
token = request.headers.get('Authorization', '').replace('Bearer ', '')
return token == AUTH_TOKEN
@app.route('/health', methods=['GET'])
def health():
"""Health check endpoint."""
return jsonify({"status": "ok", "service": "praisonai-api"})
@app.route('/chat', methods=['POST'])
def chat():
"""Chat endpoint for agent interaction."""
if not check_auth():
return jsonify({"error": "Unauthorized"}), 401
data = request.get_json()
if not data or 'message' not in data:
return jsonify({"error": "Message required"}), 400
try:
praisonai = PraisonAI(agent_file="agents.yaml")
result = praisonai.run()
return jsonify({
"response": result,
"status": "success"
})
except Exception as e:
return jsonify({
"error": str(e),
"status": "error"
}), 500
@app.route('/agents', methods=['GET'])
def list_agents():
"""List available agents."""
if not check_auth():
return jsonify({"error": "Unauthorized"}), 401
return jsonify({
"agents": ["default"],
"agent_file": "agents.yaml"
})
if __name__ == '__main__':
app.run(
host='0.0.0.0',
port=8080,
debug=False
)
-6
View File
@@ -13,12 +13,6 @@ GOOGLE_API_KEY=your_google_api_key_here
GROQ_API_KEY=your_groq_api_key_here
COHERE_API_KEY=your_cohere_api_key_here
# Bot Tokens (for messaging bot services)
SLACK_BOT_TOKEN=xoxb-your-slack-bot-token
SLACK_APP_TOKEN=xapp-your-slack-app-token
DISCORD_BOT_TOKEN=your-discord-bot-token
TELEGRAM_BOT_TOKEN=your-telegram-bot-token
# Optional: Service Configuration
FLASK_ENV=development
CHAINLIT_HOST=0.0.0.0
+1 -1
View File
@@ -16,7 +16,7 @@ RUN mkdir -p /root/.praison
# Install Python packages (using latest versions)
RUN pip install --no-cache-dir \
praisonai_tools \
"praisonai>=4.6.52" \
"praisonai>=3.0.0" \
"praisonai[chat]" \
"embedchain[github,youtube]"
-61
View File
@@ -1,61 +0,0 @@
# PraisonAI 🦞 Claw — All-in-one: dashboard + bots + gateway + agents
#
# Build: docker build -f docker/Dockerfile.claw -t praisonai:claw ..
# Run: docker run -p 8082:8082 -e OPENAI_API_KEY=sk-xxx praisonai:claw
# Health: curl http://localhost:8082/health
#
# Override CMD for other modes:
# Bot: docker run -e ... praisonai:claw praisonai bot telegram
# Gateway: docker run -e ... praisonai:claw praisonai gateway start
# Serve: docker run -e ... praisonai:claw praisonai serve agents.yaml
# Shell: docker run --rm -it praisonai:claw bash
FROM python:3.12-slim AS base
# ── Environment ──────────────────────────────────────────────────────────────
ENV PYTHONDONTWRITEBYTECODE=1 \
PYTHONUNBUFFERED=1 \
AIUI_PORT=8082 \
AIUI_HOST=0.0.0.0 \
AIUI_DATA_DIR=/data
WORKDIR /app
# ── System dependencies ─────────────────────────────────────────────────────
# tini: PID 1 signal handling (graceful shutdown on Fly/Railway/k8s)
# curl: HEALTHCHECK probe
# build-essential: compile native Python wheels (chromadb, etc.)
RUN apt-get update && apt-get install -y --no-install-recommends \
tini \
curl \
build-essential \
&& rm -rf /var/lib/apt/lists/*
# ── Install PraisonAI 🦞 ────────────────────────────────────────────────────
# Single command installs: AIUI dashboard, agents SDK (memory/knowledge/llm/mcp),
# bot channels (Telegram/Discord/Slack), gateway, search tools, and more.
RUN pip install --no-cache-dir "praisonai[claw]"
# ── Data volume ──────────────────────────────────────────────────────────────
# Persistence for sessions, config, memory, knowledge stores
RUN mkdir -p /data
VOLUME /data
# ── Entrypoint ───────────────────────────────────────────────────────────────
# Ensures /data exists and forwards all signals via tini
RUN printf '#!/bin/sh\n\
set -e\n\
mkdir -p /data 2>/dev/null || true\n\
exec "$@"\n' > /usr/local/bin/entrypoint.sh \
&& chmod +x /usr/local/bin/entrypoint.sh
EXPOSE 8082
# ── Health check ─────────────────────────────────────────────────────────────
HEALTHCHECK --interval=30s --timeout=5s --start-period=20s --retries=3 \
CMD curl -f http://localhost:8082/health || exit 1
# ── Run ──────────────────────────────────────────────────────────────────────
# Default: AIUI dashboard via praisonai claw. Override CMD for bot/gateway/serve.
ENTRYPOINT ["/usr/bin/tini", "--", "/usr/local/bin/entrypoint.sh"]
CMD ["praisonai", "claw", "--port", "8082"]
+1 -1
View File
@@ -20,7 +20,7 @@ RUN mkdir -p /root/.praison
# Install Python packages (using latest versions)
RUN pip install --no-cache-dir \
praisonai_tools \
"praisonai>=4.6.52" \
"praisonai>=3.0.0" \
"praisonai[ui]" \
"praisonai[chat]" \
"praisonai[realtime]" \
+1 -1
View File
@@ -16,7 +16,7 @@ RUN mkdir -p /root/.praison
# Install Python packages (using latest versions)
RUN pip install --no-cache-dir \
praisonai_tools \
"praisonai>=4.6.52" \
"praisonai>=3.0.0" \
"praisonai[ui]" \
"praisonai[crewai]"
-15
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@@ -1,15 +0,0 @@
# Bot Environment Variables
# Copy to .env and fill in your values
# Required: LLM API Key
OPENAI_API_KEY=your_openai_api_key_here
# Slack Bot (Socket Mode)
SLACK_BOT_TOKEN=xoxb-your-slack-bot-token
SLACK_APP_TOKEN=xapp-your-slack-app-token
# Discord Bot
DISCORD_BOT_TOKEN=your-discord-bot-token
# Telegram Bot
TELEGRAM_BOT_TOKEN=your-telegram-bot-token
-42
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@@ -1,42 +0,0 @@
# Dockerfile for PraisonAI Slack Bot
# Secrets are passed at runtime via environment variables
FROM python:3.11-slim
WORKDIR /app
# Install system dependencies
RUN apt-get update && apt-get install -y --no-install-recommends \
gcc \
python3-dev \
curl \
git \
&& rm -rf /var/lib/apt/lists/*
# Create praison config directory
RUN mkdir -p /root/.praison
# Install praisonai with bot dependencies
RUN pip install --no-cache-dir \
praisonai \
slack-bolt \
slack-sdk \
"discord.py>=2.0.0" \
"python-telegram-bot>=20.0"
# Set environment variables for directory management
ENV PRAISON_CONFIG_DIR=/root/.praison
ENV DOCKER_CONTAINER=true
# Bot tokens should be passed at runtime (not baked into image)
# SLACK_BOT_TOKEN=xoxb-...
# SLACK_APP_TOKEN=xapp-...
# Optional: Copy custom agent configuration
# COPY agent.yaml /app/agent.yaml
# Expose no ports - Socket Mode doesn't need them
# For webhook mode, expose port 3000
# Default command - tokens from environment
CMD ["praisonai", "bot", "slack"]
-66
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@@ -1,66 +0,0 @@
# PraisonAI Bot Docker Deployment
Deploy Slack, Discord, or Telegram bots using Docker.
## Quick Start
```bash
# 1. Copy environment template
cp .env.template .env
# 2. Edit .env with your tokens
nano .env
# 3. Run specific bot
docker compose up slack-bot -d
# Or run all bots
docker compose up -d
```
## Environment Variables
| Variable | Required | Description |
|----------|----------|-------------|
| `OPENAI_API_KEY` | Yes | LLM API key |
| `SLACK_BOT_TOKEN` | For Slack | Bot token (xoxb-...) |
| `SLACK_APP_TOKEN` | For Slack | App token (xapp-...) |
| `DISCORD_BOT_TOKEN` | For Discord | Bot token |
| `TELEGRAM_BOT_TOKEN` | For Telegram | Bot token |
## Slack Setup
1. Create app at https://api.slack.com/apps
2. Enable **Socket Mode** → Generate App-Level Token with `connections:write`
3. Add **OAuth Scopes**: `chat:write`, `app_mentions:read`, `im:history`
4. Enable **Event Subscriptions** → Subscribe to `app_mention`, `message.im`
5. **Install to Workspace**
6. Copy Bot Token and App Token to `.env`
## Commands
```bash
# Start Slack bot
docker compose up slack-bot -d
# View logs
docker compose logs -f slack-bot
# Stop bot
docker compose down slack-bot
# Rebuild after updates
docker compose build --no-cache slack-bot
```
## Custom Agent Configuration
Mount your agent config:
```yaml
services:
slack-bot:
volumes:
- ./agent.yaml:/app/agent.yaml
command: ["praisonai", "bot", "slack", "--agent", "/app/agent.yaml"]
```
-53
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@@ -1,53 +0,0 @@
version: '3.8'
# PraisonAI Bot Services
# Run specific bots: docker compose up slack-bot
# Run all bots: docker compose up
services:
# Slack Bot
slack-bot:
build:
context: ../..
dockerfile: docker/bots/Dockerfile
volumes:
- praison_data:/root/.praison
environment:
OPENAI_API_KEY: ${OPENAI_API_KEY}
SLACK_BOT_TOKEN: ${SLACK_BOT_TOKEN}
SLACK_APP_TOKEN: ${SLACK_APP_TOKEN}
PRAISON_CONFIG_DIR: /root/.praison
command: [ "praisonai", "bot", "slack" ]
restart: unless-stopped
# Discord Bot
discord-bot:
build:
context: ../..
dockerfile: docker/bots/Dockerfile
volumes:
- praison_data:/root/.praison
environment:
OPENAI_API_KEY: ${OPENAI_API_KEY}
DISCORD_BOT_TOKEN: ${DISCORD_BOT_TOKEN}
PRAISON_CONFIG_DIR: /root/.praison
command: [ "praisonai", "bot", "discord" ]
restart: unless-stopped
# Telegram Bot
telegram-bot:
build:
context: ../..
dockerfile: docker/bots/Dockerfile
volumes:
- praison_data:/root/.praison
environment:
OPENAI_API_KEY: ${OPENAI_API_KEY}
TELEGRAM_BOT_TOKEN: ${TELEGRAM_BOT_TOKEN}
PRAISON_CONFIG_DIR: /root/.praison
command: [ "praisonai", "bot", "telegram" ]
restart: unless-stopped
volumes:
praison_data:
driver: local
+4 -30
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@@ -1,29 +1,6 @@
version: '3.8'
services:
# PraisonAI 🦞 Claw — Recommended all-in-one service
claw:
build:
context: ..
dockerfile: docker/Dockerfile.claw
volumes:
- claw_data:/data
ports:
- "8082:8082"
environment:
OPENAI_API_KEY: ${OPENAI_API_KEY}
restart: unless-stopped
healthcheck:
test: [ "CMD", "curl", "-f", "http://localhost:8082/health" ]
interval: 30s
timeout: 5s
start_period: 20s
retries: 3
networks:
- praison_network
# ─── Legacy services (kept for backward compatibility) ─────────────────
# PraisonAI UI Service
ui:
build:
@@ -45,7 +22,7 @@ services:
CHAINLIT_DB_DIR: /root/.praison
command: praisonai ui --host 0.0.0.0
healthcheck:
test: [ "CMD", "curl", "-f", "http://localhost:8082" ]
test: ["CMD", "curl", "-f", "http://localhost:8082"]
interval: 10s
timeout: 5s
retries: 3
@@ -72,7 +49,7 @@ services:
CHAINLIT_DB_DIR: /root/.praison
command: praisonai chat --host 0.0.0.0 --port 8083
healthcheck:
test: [ "CMD", "curl", "-f", "http://localhost:8083" ]
test: ["CMD", "curl", "-f", "http://localhost:8083"]
interval: 10s
timeout: 5s
retries: 3
@@ -92,7 +69,7 @@ services:
OPENAI_API_KEY: ${OPENAI_API_KEY}
PRAISON_CONFIG_DIR: /root/.praison
healthcheck:
test: [ "CMD", "curl", "-f", "http://localhost:8080/health" ]
test: ["CMD", "curl", "-f", "http://localhost:8080/health"]
interval: 10s
timeout: 5s
retries: 3
@@ -112,14 +89,11 @@ services:
PRAISON_CONFIG_DIR: /root/.praison
networks:
- praison_network
# For bot services (Slack, Discord, Telegram), see docker/bots/
volumes:
claw_data:
driver: local
praison_data:
driver: local
networks:
praison_network:
driver: bridge
driver: bridge
+53
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@@ -0,0 +1,53 @@
# Templates CLI
```bash
praisonai templates list
```
```bash
praisonai templates search video
```
```bash
praisonai templates info ai-video-editor
```
```bash
praisonai templates run ai-video-editor --input video.mp4 --output edited.mp4
```
```bash
praisonai templates run ai-video-editor --input video.mp4 --output edited.mp4 --offline
```
```bash
praisonai templates run ai-video-editor --input video.mp4 --output edited.mp4 --strict-tools
```
```bash
praisonai templates run ai-video-editor --input video.mp4 --tools ./my_tools.py
```
```bash
praisonai templates run ai-video-editor --input video.mp4 --tools-dir ./tools
```
```bash
praisonai templates run ai-video-editor --input video.mp4 --tools-source praisonai_tools.video
```
```bash
praisonai templates run ai-video-editor --input video.mp4 --no-template-tools-py
```
```bash
praisonai templates init my-project --template ai-video-editor
```
```bash
praisonai templates cache clear
```
```bash
praisonai templates cache list
```
+104
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@@ -0,0 +1,104 @@
# Templates Module
## Loading Templates
```python
from praisonai.templates.loader import TemplateLoader
loader = TemplateLoader()
# Load from local path
template = loader.load("./my-template")
# Load from URI
template = loader.load("ai-video-editor")
# Load offline
template = loader.load("ai-video-editor", offline=True)
# Check requirements
missing = loader.check_requirements(template)
```
## Template Discovery
```python
from praisonai.templates.discovery import TemplateDiscovery
discovery = TemplateDiscovery(
include_package=True,
include_defaults=True,
)
# Find template
result = discovery.find_template("ai-video-editor")
# List all templates
templates = discovery.list_templates()
```
## Template Config
```python
from praisonai.templates.loader import TemplateConfig
# Access template properties
template.name
template.description
template.version
template.author
template.requires
template.workflow_file
template.agents_file
template.path
```
## Tool Override Integration
```python
from praisonai.templates.tool_override import (
create_tool_registry_with_overrides,
resolve_tools,
)
# Build registry with template sources
tools_sources = template.requires.get("tools_sources", [])
registry = create_tool_registry_with_overrides(
tools_sources=tools_sources,
template_dir=str(template.path),
include_defaults=True,
)
# Resolve tool names
tools = resolve_tools(["shell_tool"], registry=registry)
```
## TEMPLATE.yaml Schema
```yaml
name: my-template
version: "1.0.0"
description: Template description
requires:
tools: [shell_tool]
packages: [praisonai-tools]
env: [OPENAI_API_KEY]
tools_sources:
- praisonai_tools.video
- ./local_tools.py
workflow: workflow.yaml
agents: agents.yaml
config:
input:
type: string
required: true
output:
type: string
defaults:
preset: podcast
```
+65
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@@ -0,0 +1,65 @@
# Tools CLI
```bash
praisonai tools list
```
```bash
praisonai tools info shell_tool
```
```bash
praisonai tools info internet_search
```
```bash
praisonai tools search "web"
```
```bash
praisonai tools search "file"
```
```bash
praisonai tools doctor
```
```bash
praisonai tools doctor --json
```
```bash
praisonai tools resolve shell_tool
```
```bash
praisonai tools resolve internet_search --template ai-video-editor
```
```bash
praisonai tools resolve my_tool --tools ./my_tools.py
```
```bash
praisonai tools resolve my_tool --tools-dir ./tools
```
```bash
praisonai tools discover
```
```bash
praisonai tools discover --include praisonai_tools.video
```
```bash
praisonai tools discover --entrypoints
```
```bash
praisonai tools show-sources
```
```bash
praisonai tools show-sources --template ai-video-editor
```
+90
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@@ -0,0 +1,90 @@
# Tools Module
## Tool Registry
```python
from praisonai.templates.tool_override import (
create_tool_registry_with_overrides,
resolve_tools,
)
# Create registry with defaults
registry = create_tool_registry_with_overrides(include_defaults=True)
# Create registry with overrides
registry = create_tool_registry_with_overrides(
override_files=["my_tools.py"],
override_dirs=["./tools"],
include_defaults=True,
)
# Create registry with tools_sources
registry = create_tool_registry_with_overrides(
tools_sources=["praisonai_tools.video"],
template_dir="./my-template",
include_defaults=True,
)
# Resolve tool names to callables
tools = resolve_tools(
["shell_tool", "internet_search"],
registry=registry,
)
```
## Tool Override Loader
```python
from praisonai.templates.tool_override import ToolOverrideLoader
loader = ToolOverrideLoader()
# Load from file
tools = loader.load_from_file("my_tools.py")
# Load from directory
tools = loader.load_from_directory("./tools")
# Load from module
tools = loader.load_from_module("praisonai_tools.video")
# Get default tool directories
dirs = loader.get_default_tool_dirs()
```
## Resolution Order
1. CLI `--tools` files (highest priority)
2. CLI `--tools-dir` directories
3. Template `tools_sources` (from TEMPLATE.yaml)
4. Template-local `tools.py`
5. Default dirs (`~/.praison/tools`, `~/.config/praison/tools`)
6. Package discovery (`praisonai_tools`)
7. Built-in tools (lowest priority)
## Creating Custom Tools
```python
from praisonai_tools import tool
@tool
def my_custom_tool(query: str) -> str:
"""My custom tool description.
Args:
query: The search query
"""
return f"Result for: {query}"
```
## Template tools_sources
```yaml
# TEMPLATE.yaml
requires:
tools: [shell_tool]
tools_sources:
- praisonai_tools.video
- ./local_tools.py
- ./tools_dir/
```
-16
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@@ -23,7 +23,6 @@ examples/
| Category | Examples | Docs |
|----------|----------|------|
| **Consolidated Params** | [consolidated_params/](consolidated_params/) | [📖](https://docs.praison.ai/api/consolidated-params) |
| **Agents** | [python/agents/](python/agents/) | [📖](https://docs.praison.ai/concepts/agents) |
| **Workflows** | [python/workflows/](python/workflows/) | [📖](https://docs.praison.ai/features/workflows) |
| **Model Router** | [python/agents/router-agent-cost-optimization.py](python/agents/router-agent-cost-optimization.py) | [📖](https://docs.praison.ai/features/model-router) |
@@ -36,21 +35,6 @@ examples/
| **Serve** | [serve/](serve/) | [📖](https://docs.praison.ai/cli/serve) |
| **Endpoints** | [serve/](serve/) | [📖](https://docs.praison.ai/cli/endpoints) |
## Consolidated Params Examples
Agent-centric API with unified parameter resolution. Precedence: Instance > Config > Array > Dict > String > Bool > Default
| Example | Description |
|---------|-------------|
| [basic_agent.py](consolidated_params/basic_agent.py) | Minimal agent with memory |
| [basic_agents.py](consolidated_params/basic_agents.py) | Multi-agent with memory+planning |
| [basic_workflow.py](consolidated_params/basic_workflow.py) | Workflow with consolidated params |
| [basic_memory.py](consolidated_params/basic_memory.py) | Memory presets (file, redis, postgres) |
| [basic_guardrails.py](consolidated_params/basic_guardrails.py) | Guardrails with callable or config |
| [basic_workflow_agentlike.py](consolidated_params/basic_workflow_agentlike.py) | Workflow with agent-like params |
| [basic_step_override.py](consolidated_params/basic_step_override.py) | Step-level override of workflow defaults |
| [advanced_workflow_full_features.py](consolidated_params/advanced_workflow_full_features.py) | All consolidated params |
## Serve Examples
| Example | Description | CLI Command |
-30
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@@ -1,30 +0,0 @@
framework: ag2
topic: "Research the latest developments in AI agents"
# Install: pip install "praisonai[ag2]"
# Run: praisonai --framework ag2 examples/ag2/ag2_basic.yaml
# or praisonai run examples/ag2/ag2_basic.yaml --framework ag2
roles:
research_agent:
role: "AI Research Specialist"
goal: "Research and summarise the latest developments in AI agent frameworks"
backstory: |
You are an experienced AI researcher with deep knowledge of multi-agent
systems, large language models, and the latest trends in AI tooling.
You excel at synthesising complex technical topics into clear summaries.
tasks:
research_task:
description: |
Research and summarise the latest developments in AI agent frameworks
for the topic: {topic}
Focus on:
1. Key frameworks and their unique capabilities
2. Recent innovations and improvements
3. Community adoption and ecosystem growth
4. Practical use cases and success stories
expected_output: |
A concise research summary covering the key developments,
major frameworks, and practical insights. Include 3-5 bullet
points of the most important findings.
-42
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@@ -1,42 +0,0 @@
framework: ag2
topic: "Cloud-native AI deployment strategies on AWS"
# AG2 exclusive feature: native AWS Bedrock support via LLMConfig(api_type="bedrock")
#
# Prerequisites:
# pip install "praisonai[ag2]"
# aws configure (or set AWS_ACCESS_KEY_ID, AWS_SECRET_ACCESS_KEY, AWS_DEFAULT_REGION)
#
# Run:
# praisonai --framework ag2 examples/ag2/ag2_bedrock.yaml
#
# The AG2 adapter detects api_type="bedrock" from the llm config and uses
# LLMConfig(api_type="bedrock", model=...) — no OPENAI_API_KEY required.
# AWS credentials are sourced from boto3 (env vars, ~/.aws/credentials, IAM role).
roles:
cloud_architect:
role: "AWS Cloud Architect"
goal: "Design and explain cloud-native AI deployment strategies on AWS"
backstory: |
You are an AWS Solutions Architect specialising in AI/ML workloads.
You have deep expertise in Amazon Bedrock, SageMaker, ECS, and Lambda,
and you help organisations deploy AI agents at scale securely and cost-effectively.
llm:
model: "bedrock/anthropic.claude-3-5-sonnet-20241022-v2:0"
api_type: "bedrock"
aws_region: "us-east-1"
tasks:
architecture_task:
description: |
Design a cloud-native deployment strategy for AI agents on AWS for: {topic}
Cover:
1. Recommended AWS services (Bedrock, ECS, Lambda, etc.)
2. Scalability and cost optimisation patterns
3. Security and compliance considerations
4. A simple reference architecture overview
expected_output: |
A concise architecture guide with service recommendations,
a high-level deployment diagram description, and key
best practices for production AI agent deployments on AWS.
-54
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@@ -1,54 +0,0 @@
framework: ag2
topic: "The impact of open-source AI on enterprise software development"
# Install: pip install "praisonai[ag2]"
# Run: praisonai --framework ag2 examples/ag2/ag2_multi_agent.yaml
# or praisonai run examples/ag2/ag2_multi_agent.yaml --framework ag2
#
# This example demonstrates AG2's GroupChat multi-agent coordination.
# Both agents participate in a collaborative conversation managed by
# a GroupChatManager until the task is complete.
roles:
researcher:
role: "Research Specialist"
goal: "Gather and analyse information on the given topic"
backstory: |
You are a meticulous researcher who excels at finding relevant
information, analysing trends, and presenting data-backed insights.
You always cite your reasoning and structure your findings clearly.
tasks:
research_task:
description: |
Research the topic: {topic}
Investigate:
1. Current state and adoption rates
2. Key players and projects driving the trend
3. Technical advantages and challenges
4. Business impact and cost implications
expected_output: |
A structured research briefing with findings on the topic,
including key data points, trends, and technical observations.
writer:
role: "Technical Content Writer"
goal: "Transform research findings into clear, engaging written content"
backstory: |
You are a skilled technical writer who turns complex research into
accessible, well-structured articles. You focus on clarity, logical
flow, and actionable takeaways for a professional audience.
tasks:
writing_task:
description: |
Using the research findings provided by the Research Specialist,
write a concise article on: {topic}
The article should:
1. Open with a compelling hook
2. Present key findings logically
3. Include practical implications for developers
4. Close with a forward-looking conclusion
expected_output: |
A 400-500 word article suitable for a technical blog,
with clear sections, professional tone, and concrete takeaways.
-244
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@@ -1,244 +0,0 @@
"""
Agent-Centric API Example
Demonstrates the consolidated feature parameters for PraisonAI Agents.
These params provide a cleaner, more intuitive API with progressive disclosure.
Precedence Rule: Instance > Config > Array > String > Bool > Default
Consolidated Params Support:
- memory: bool | str URL | str preset | [preset, overrides] | MemoryConfig | Instance
- knowledge: bool | str path | [sources...] | KnowledgeConfig | Instance
- planning: bool | str LLM | [preset, overrides] | PlanningConfig
- reflection: bool | str preset | [preset, overrides] | ReflectionConfig
- guardrails: bool | callable | str prompt | GuardrailConfig
- web: bool | str provider | [provider, overrides] | WebConfig
- output: str preset | [preset, overrides] | OutputConfig
- execution: str preset | [preset, overrides] | ExecutionConfig
"""
from praisonaiagents import (
Agent,
# Config classes for progressive disclosure
MemoryConfig,
KnowledgeConfig,
PlanningConfig,
ReflectionConfig,
GuardrailConfig,
WebConfig,
)
def example_simple_enable():
"""Example 1: Simple boolean enable (easiest)"""
print("\n=== Example 1: Simple Boolean Enable ===")
agent = Agent(
instructions="You are a helpful assistant",
memory=True, # Enable memory with defaults
reflection=True, # Enable self-reflection
web=WebConfig(fetch=False), # Enable web search + fetch
)
print(f"Agent created with memory={agent._memory_instance is not None}")
print(f" self_reflect={agent.self_reflect}")
print(f" web_search={agent.web_search}")
def example_with_config():
"""Example 2: Using config objects (more control)"""
print("\n=== Example 2: Using Config Objects ===")
agent = Agent(
instructions="You are a research assistant",
memory=MemoryConfig(
backend="file",
user_id="researcher_001",
auto_memory=True,
),
reflection=ReflectionConfig(
min_iterations=1,
max_iterations=5,
llm="gpt-4o-mini",
),
web=WebConfig(
search=True,
fetch=False, # Only search, no full page fetch
max_results=3,
),
)
print(f"Agent created with user_id={agent.user_id}")
print(f" {agent.max_reflect}")
print(f" web_search={agent.web_search}, web_fetch={agent.web_fetch}")
def example_guardrails():
"""Example 3: Guardrails with callable or config"""
print("\n=== Example 3: Guardrails ===")
# Option A: Direct callable
def my_validator(output):
"""Simple validator that checks response length."""
is_valid = len(output.raw) < 1000
return (is_valid, output if is_valid else "Response too long")
agent_a = Agent(
instructions="Be concise",
guardrails=my_validator, # Direct callable
)
print(f"Agent A: guardrail is callable = {callable(agent_a.guardrail)}")
# Option B: Using GuardrailConfig
agent_b = Agent(
instructions="Be helpful and safe",
guardrails=GuardrailConfig(
llm_validator="Ensure the response is helpful, accurate, and safe",
max_retries=3,
),
)
print(f"Agent B: guardrail = {agent_b.guardrail}")
print(f" max_retries = {agent_b.max_guardrail_retries}")
def example_planning():
"""Example 4: Planning mode"""
print("\n=== Example 4: Planning Mode ===")
agent = Agent(
instructions="You are a project planner",
planning=PlanningConfig(
reasoning=True,
read_only=True, # Plan mode - only read operations
),
)
print(f"Agent created with planning={agent.planning}")
print(f" plan_mode={agent.plan_mode}")
print(f" planning_reasoning={agent.planning_reasoning}")
def example_backward_compatible():
"""Example 5: Using new consolidated params"""
print("\n=== Example 5: Consolidated Params ===")
# New consolidated params
agent = Agent(
instructions="Test agent",
reflection=True,
web=WebConfig(search=True, fetch=False),
)
print(f"Consolidated params work: self_reflect={agent.self_reflect}")
print(f" web_search={agent.web_search}, web_fetch={agent.web_fetch}")
def example_real_chat():
"""Example 6: Real chat with new API"""
print("\n=== Example 6: Real Chat ===")
agent = Agent(
instructions="You are a helpful math tutor. Be concise.",
reflection=False,
web=False,
)
response = agent.start("What is the square root of 144?")
print(f"Response: {response}")
def example_string_presets():
"""Example 7: String presets (NEW - user-friendly shortcuts)"""
print("\n=== Example 7: String Presets ===")
# Output presets: minimal, normal, verbose, debug, silent
agent = Agent(
instructions="You are a verbose assistant",
output="verbose", # String preset for output
execution="fast", # String preset for execution
web=["tavily", {"fetch": False}], # String preset with override for web provider
)
print(f"Output preset 'verbose': verbose={agent.verbose}, metrics={agent.metrics}")
print(f"Execution preset 'fast': max_iter={agent.max_iter}")
print(f"Web preset 'tavily': web_search={agent.web_search}")
def example_array_overrides():
"""Example 8: Array with overrides (NEW - preset + customization)"""
print("\n=== Example 8: Array Overrides ===")
# Array format: [preset, {overrides}]
agent = Agent(
instructions="You are a streaming assistant",
output=["verbose", {"stream": True}], # Verbose preset + enable streaming
execution=["fast", {"max_iter": 15}], # Fast preset + custom max_iter
)
print(f"Output array override: verbose={agent.verbose}, stream={agent.stream}")
print(f"Execution array override: max_iter={agent.max_iter}")
def example_url_parsing():
"""Example 9: URL parsing for memory (NEW - connection strings)"""
print("\n=== Example 9: URL Parsing ===")
# Memory supports URL connection strings
# Supported: postgresql://, redis://, sqlite:///, mongodb://
agent = Agent(
instructions="You are a database-backed assistant",
memory="postgresql://postgres:password@localhost:5432/praisonai",
)
print("Memory URL parsed: memory enabled")
# Also works with presets
agent2 = Agent(
instructions="You are a redis-backed assistant",
memory="redis", # Preset name
)
print("Memory preset 'redis': configured")
def example_knowledge_sources():
"""Example 10: Knowledge with sources (list and string)"""
print("\n=== Example 10: Knowledge Sources ===")
# Single path string
agent1 = Agent(
instructions="You are a document assistant",
knowledge="docs/", # Single path
)
print(f"Knowledge single path: knowledge={agent1.knowledge}")
# List of sources
agent2 = Agent(
instructions="You are a multi-source assistant",
knowledge=["docs/", "data.pdf", "https://example.com/api"],
)
print(f"Knowledge list: knowledge={agent2.knowledge}")
# With config for advanced settings
agent3 = Agent(
instructions="You are an advanced RAG assistant",
knowledge=KnowledgeConfig(
sources=["docs/"],
retrieval_k=10,
rerank=True,
),
)
print("Knowledge config: configured with rerank")
if __name__ == "__main__":
print("=" * 60)
print("PraisonAI Agent-Centric API Examples")
print("=" * 60)
example_simple_enable()
example_with_config()
example_guardrails()
example_planning()
example_backward_compatible()
example_real_chat()
example_string_presets()
example_array_overrides()
example_url_parsing()
example_knowledge_sources()
print("\n" + "=" * 60)
print("All examples completed!")
print("=" * 60)
@@ -75,7 +75,7 @@ async def main():
Use read_file to read files.
Use list_files to list directory contents.""",
tools=tools,
output="verbose" # Use new consolidated param
verbose=True
)
print()
-31
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@@ -1,31 +0,0 @@
# Approval Examples
Minimal examples showing how to route tool-execution approvals through
different backends.
## Quick Start
```bash
pip install praisonaiagents praisonai[bot]
export OPENAI_API_KEY=sk-...
```
| Backend | Script | Extra env vars |
|----------|-----------------------|--------------------------------------------------|
| Slack | `slack_approval.py` | `SLACK_BOT_TOKEN`, `SLACK_CHANNEL` |
| Telegram | `telegram_approval.py`| `TELEGRAM_BOT_TOKEN`, `TELEGRAM_CHAT_ID` |
| Discord | `discord_approval.py` | `DISCORD_BOT_TOKEN`, `DISCORD_CHANNEL_ID` |
| HTTP | `http_approval.py` | *(none — opens a local web dashboard)* |
| Agent | `agent_approval.py` | *(none — AI reviewer agent decides)* |
## SSL Verification
For corporate proxy / CA issues, Discord and Telegram backends support
optional SSL bypass:
```bash
export PRAISONAI_DISCORD_SSL_VERIFY=false
export PRAISONAI_TELEGRAM_SSL_VERIFY=false
```
Default is `true` (secure).
-26
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@@ -1,26 +0,0 @@
"""
Agent Approval Example
======================
Uses an AI agent as an automated reviewer to approve/deny tool calls.
Requires:
pip install praisonaiagents
export OPENAI_API_KEY=sk-...
"""
from praisonaiagents import Agent
from praisonaiagents.approval import AgentApproval
from praisonaiagents.tools.shell_tools import execute_command
reviewer = AgentApproval(
instructions="Only approve read-only commands like 'ls' or 'cat'. Deny destructive commands.",
)
agent = Agent(
name="DevOps",
instructions="You are a DevOps assistant. Use shell tools when asked.",
tools=[execute_command],
approval=reviewer,
)
agent.start("List files in the current directory")
-24
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@@ -1,24 +0,0 @@
"""
Discord Approval Example
========================
Routes tool approvals to a Discord channel.
Requires:
pip install praisonaiagents praisonai[bot]
export DISCORD_BOT_TOKEN=MTIz...
export DISCORD_CHANNEL_ID=1234567890
export OPENAI_API_KEY=sk-...
"""
from praisonaiagents import Agent
from praisonaiagents.tools.shell_tools import execute_command
from praisonai.bots import DiscordApproval
agent = Agent(
name="DevOps",
instructions="You are a DevOps assistant. Use shell tools when asked.",
tools=[execute_command],
approval=DiscordApproval(),
)
agent.start("List files in the current directory")
-22
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@@ -1,22 +0,0 @@
"""
HTTP Approval Example
=====================
Opens a local web dashboard for tool approvals.
Requires:
pip install praisonaiagents praisonai[bot]
export OPENAI_API_KEY=sk-...
"""
from praisonaiagents import Agent
from praisonaiagents.tools.shell_tools import execute_command
from praisonai.bots import HTTPApproval
agent = Agent(
name="DevOps",
instructions="You are a DevOps assistant. Use shell tools when asked.",
tools=[execute_command],
approval=HTTPApproval(),
)
agent.start("List files in the current directory")
-24
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@@ -1,24 +0,0 @@
"""
Slack Approval Example
======================
Routes tool approvals to a Slack channel.
Requires:
pip install praisonaiagents praisonai[bot]
export SLACK_BOT_TOKEN=xoxb-...
export SLACK_CHANNEL=C0123456789
export OPENAI_API_KEY=sk-...
"""
from praisonaiagents import Agent
from praisonaiagents.tools.shell_tools import execute_command
from praisonai.bots import SlackApproval
agent = Agent(
name="DevOps",
instructions="You are a DevOps assistant. Use shell tools when asked.",
tools=[execute_command],
approval=SlackApproval(),
)
agent.start("List files in the current directory")
-24
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@@ -1,24 +0,0 @@
"""
Telegram Approval Example
=========================
Routes tool approvals to a Telegram chat.
Requires:
pip install praisonaiagents praisonai[bot]
export TELEGRAM_BOT_TOKEN=123456:ABC-...
export TELEGRAM_CHAT_ID=987654321
export OPENAI_API_KEY=sk-...
"""
from praisonaiagents import Agent
from praisonaiagents.tools.shell_tools import execute_command
from praisonai.bots import TelegramApproval
agent = Agent(
name="DevOps",
instructions="You are a DevOps assistant. Use shell tools when asked.",
tools=[execute_command],
approval=TelegramApproval(),
)
agent.start("List files in the current directory")
+49 -51
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@@ -2,10 +2,10 @@
"""
Basic Background Tasks Example for PraisonAI Agents.
This example demonstrates how to use the background task system with Agent:
1. Create an Agent with background task support
2. Run agent tasks asynchronously
3. Track task progress
This example demonstrates how to use the background task system to:
1. Run tasks asynchronously
2. Track task progress
3. Cancel running tasks
4. Handle task completion
Usage:
@@ -13,73 +13,71 @@ Usage:
"""
import asyncio
from praisonaiagents import Agent
import time
from praisonaiagents.background import BackgroundRunner, BackgroundConfig, TaskStatus
async def main():
print("=" * 60)
print("Agent-Centric Background Tasks Demo")
print("Background Tasks Demo")
print("=" * 60)
# Create a background runner with config (used standalone, not passed to Agent)
runner = BackgroundRunner(config=BackgroundConfig(max_concurrent_tasks=3))
# Create an Agent
agent = Agent(
name="AsyncAssistant",
instructions="You are a helpful research assistant.",
)
print("\n--- Agent with Background Support Created ---")
print(f"Agent: {agent.name}")
print(f"Background runner: {runner is not None}")
# Create a background runner with config
config = BackgroundConfig(max_concurrent_tasks=3)
runner = BackgroundRunner(config=config)
# Define some example tasks
async def research_task(topic: str) -> str:
"""Simulate a research task."""
print(f" 🔄 Researching '{topic}'...")
await asyncio.sleep(1.5)
return f"Research on '{topic}' completed with 5 key findings"
def slow_task(duration: float, name: str) -> str:
"""A slow task that simulates work."""
print(f" 🔄 Task '{name}' starting (will take {duration}s)")
time.sleep(duration)
return f"Task '{name}' completed after {duration}s"
async def analysis_task(data: str) -> str:
"""Simulate an analysis task."""
print(f" 🔄 Analyzing data...")
await asyncio.sleep(1.0)
return f"Analysis complete: {data}"
async def async_task(duration: float, name: str) -> str:
"""An async task that simulates work."""
print(f" 🔄 Async task '{name}' starting (will take {duration}s)")
await asyncio.sleep(duration)
return f"Async task '{name}' completed after {duration}s"
# Submit tasks via background runner
print("\n--- Submitting Background Tasks ---")
# Submit tasks
print("\n--- Submitting Tasks ---")
task1 = await runner.submit(
research_task,
args=("AI trends 2025",),
name="research_ai"
)
print(f"✅ Submitted research task: {task1.id[:8]}")
task1 = await runner.submit(slow_task, args=(1.0, "quick-job"), name="task1")
print(f"✅ Submitted task 1: {task1.id[:8]}")
task2 = await runner.submit(
analysis_task,
args=("market data",),
name="analyze_market"
)
print(f"✅ Submitted analysis task: {task2.id[:8]}")
task2 = await runner.submit(slow_task, args=(2.0, "medium-job"), name="task2")
print(f"✅ Submitted task 2: {task2.id[:8]}")
task3 = await runner.submit(async_task, args=(1.5, "async-job"), name="task3")
print(f"✅ Submitted async task 3: {task3.id[:8]}")
# List all tasks
print("\n--- Task Status ---")
for task in runner.tasks:
print(f" [{task.id[:8]}] {task.status.value}")
# Wait for tasks to complete
print("\n--- Waiting for Tasks ---")
await task1.wait(timeout=10.0)
await task2.wait(timeout=10.0)
# Wait for task 1 to complete
print("\n--- Waiting for Task 1 ---")
await task1.wait(timeout=5.0)
print(f"✅ Task 1 result: {task1.result}")
# Final results
print("\n--- Results ---")
for task in [task1, task2]:
status = "✅" if task.status == TaskStatus.COMPLETED else "❌"
print(f" {status} {task.result}")
# Check status of all tasks
print("\n--- Updated Task Status ---")
for task in [task1, task2, task3]:
status = "✅" if task.status == TaskStatus.COMPLETED else "🔄"
print(f" {status} [{task.id[:8]}] {task.status.value}")
# Wait for all remaining tasks
print("\n--- Waiting for All Tasks ---")
await task2.wait(timeout=10.0)
await task3.wait(timeout=10.0)
# Final status
print("\n--- Final Results ---")
for task in [task1, task2, task3]:
if task.result:
print(f" ✅ {task.result}")
# Cleanup
runner.clear_completed()
-23
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@@ -1,23 +0,0 @@
"""Calculator with Tests - Editor Output Example.
Builds a calculator module, writes unit tests, runs them, generates a
coverage-style report, and reads it back.
"""
from praisonaiagents import Agent
from praisonaiagents.tools import (
write_file, read_file, execute_command
)
agent = Agent(
instructions="You are a helpful coding assistant.",
output="editor",
tools=[write_file, read_file, execute_command],
approval=True,
)
agent.start(
"Build a mini calculator - create /tmp/calculator.py with add, subtract, "
"multiply, divide functions, write unit tests in /tmp/test_calculator.py "
"using unittest, run the tests to make sure they pass, then generate a "
"coverage-style report in /tmp/calc_report.md listing which functions were "
"tested and read it back"
)
-22
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@@ -1,22 +0,0 @@
"""Fibonacci Generator - Editor Output Example.
Creates a Fibonacci script, runs it, writes a summary, and reads back
both files to verify everything looks good.
"""
from praisonaiagents import Agent
from praisonaiagents.tools import (
write_file, read_file, execute_command, list_files
)
agent = Agent(
instructions="You are a helpful coding assistant.",
output="editor",
tools=[write_file, read_file, execute_command, list_files],
approval=False,
)
agent.start(
"Create a Python file at /tmp/fibonacci.py that generates the first 20 "
"Fibonacci numbers, run it to verify the output is correct, then write "
"a summary to /tmp/fib_summary.md explaining the algorithm you used and "
"the output, finally read back both files to confirm everything looks good"
)
-36
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@@ -1,36 +0,0 @@
"""Multi-Step Research - Editor Output Example.
Researches Python frameworks, creates comparison code, runs it, writes a
markdown report, reads it back, lists files, and gets system info.
"""
from praisonaiagents import Agent
from praisonaiagents.tools import (
write_file, read_file, execute_command, list_files, get_system_info
)
try:
from praisonaiagents.tools import web_search
tools = [web_search, write_file, read_file, execute_command,
list_files, get_system_info]
except ImportError:
tools = [write_file, read_file, execute_command,
list_files, get_system_info]
agent = Agent(
instructions="You are a helpful research assistant.",
output="editor",
tools=tools,
approval=False,
)
agent.start(
"Research the top 3 Python web frameworks (Django, FastAPI, Flask), then: "
"1) Search the web for each framework's latest version and key features, "
"2) Create a file called /tmp/framework_comparison.py that contains a "
"Python dictionary with the comparison data, "
"3) Execute the code to verify the dictionary is valid, "
"4) Write a markdown report to /tmp/framework_report.md summarizing your "
"findings in a table format, "
"5) Read back the report file to verify it was written correctly, "
"6) List the files in /tmp to confirm both files exist, "
"7) Get system info to note what OS this report was generated on"
)
-21
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@@ -1,21 +0,0 @@
"""System Audit - Editor Output Example.
Runs system commands, gathers info, writes a report, and reads it back.
"""
from praisonaiagents import Agent
from praisonaiagents.tools import (
write_file, read_file, execute_command
)
agent = Agent(
instructions="You are a helpful system administration assistant.",
output="editor",
tools=[write_file, read_file, execute_command],
approval=True,
)
agent.start(
"Investigate my system - get the current date, check disk usage, find out "
"what Python version is installed, list running processes sorted by memory, "
"then write all findings to /tmp/system_audit.md as a neat report and read "
"it back to verify"
)
-28
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@@ -1,28 +0,0 @@
"""Weather Search - Editor Output Example.
Searches for weather, creates JSON data, writes a parser script, executes
it, and lists created files.
"""
from praisonaiagents import Agent
from praisonaiagents.tools import (
write_file, execute_command, list_files
)
try:
from praisonaiagents.tools import web_search
tools = [web_search, write_file, execute_command, list_files]
except ImportError:
tools = [write_file, execute_command, list_files]
agent = Agent(
instructions="You are a helpful research assistant.",
output="editor",
tools=tools,
approval=False,
)
agent.start(
"Search the web for the current weather in Tokyo, create a JSON file at "
"/tmp/weather_data.json with the findings, then write a Python script at "
"/tmp/parse_weather.py that reads the JSON and prints a formatted weather "
"report, execute the script, and list all files you created in /tmp"
)
-146
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@@ -1,146 +0,0 @@
#!/usr/bin/env python3
"""
PraisonAI Benchmark Example
This example demonstrates how to use the benchmark system programmatically
to compare performance across different execution paths.
Usage:
python benchmark_example.py
Requirements:
- OPENAI_API_KEY environment variable set
- praisonai package installed
"""
import os
import sys
# Ensure the package is importable
sys.path.insert(0, os.path.join(os.path.dirname(__file__), '../../src/praisonai'))
from praisonai.cli.features.benchmark import BenchmarkHandler, BenchmarkReport
def run_quick_comparison():
"""Run a quick comparison of key execution paths."""
print("=" * 60)
print("Quick Benchmark Comparison")
print("=" * 60)
handler = BenchmarkHandler()
# Run benchmark with 2 iterations on key paths
report = handler.run_full_benchmark(
prompt="What is 2+2?",
iterations=2,
paths=["openai_sdk", "praisonai_agent"],
verbose=True
)
# Print comparison table
print("\n" + handler.create_comparison_table(report))
return report
def run_full_benchmark():
"""Run full benchmark suite across all paths."""
print("=" * 60)
print("Full Benchmark Suite")
print("=" * 60)
handler = BenchmarkHandler()
# Run full benchmark
report = handler.run_full_benchmark(
prompt="Hi",
iterations=3,
verbose=True
)
# Print full report
handler.print_report(report)
return report
def run_agent_benchmark():
"""Benchmark PraisonAI Agent specifically."""
print("=" * 60)
print("Agent Benchmark")
print("=" * 60)
handler = BenchmarkHandler()
# Benchmark agent vs SDK
report = handler.run_full_benchmark(
prompt="Explain Python in one sentence",
iterations=3,
paths=["openai_sdk", "praisonai_agent"],
verbose=True
)
# Show timeline diagrams
for name, result in report.results.items():
print(f"\n### {name}")
print(handler.create_timeline_diagram(result))
# Show variance analysis
print(handler.create_variance_table(report))
return report
def save_benchmark_results(report: BenchmarkReport, output_path: str):
"""Save benchmark results to JSON file."""
import json
with open(output_path, 'w') as f:
json.dump(report.to_dict(), f, indent=2)
print(f"\nResults saved to: {output_path}")
def main():
"""Main entry point."""
import argparse
parser = argparse.ArgumentParser(description="PraisonAI Benchmark Example")
parser.add_argument(
"--mode",
choices=["quick", "full", "agent"],
default="quick",
help="Benchmark mode: quick (2 paths), full (all paths), agent (agent focus)"
)
parser.add_argument(
"--output",
type=str,
default=None,
help="Output JSON file path"
)
args = parser.parse_args()
# Check for API key
if not os.environ.get("OPENAI_API_KEY"):
print("Error: OPENAI_API_KEY environment variable not set")
sys.exit(1)
# Run selected benchmark
if args.mode == "quick":
report = run_quick_comparison()
elif args.mode == "full":
report = run_full_benchmark()
elif args.mode == "agent":
report = run_agent_benchmark()
# Save results if requested
if args.output:
save_benchmark_results(report, args.output)
print("\n✅ Benchmark complete!")
if __name__ == "__main__":
main()
@@ -1,43 +0,0 @@
"""
Basic Caching Configuration Example
Demonstrates using caching for response and prompt caching.
"""
import os
from praisonaiagents import Agent, CachingConfig
# Ensure API key is set from environment
assert os.getenv("OPENAI_API_KEY"), "OPENAI_API_KEY must be set"
# Default caching (enabled)
agent_cached = Agent(
instructions="You are a helpful assistant.",
caching=True,
)
# Disable caching
agent_no_cache = Agent(
instructions="You are a helpful assistant.",
caching=False,
)
# Custom caching configuration
agent_custom = Agent(
instructions="You are a helpful assistant.",
caching=CachingConfig(
enabled=True,
prompt_caching=True, # Enable prompt caching for supported providers
),
)
if __name__ == "__main__":
print("Testing CachingConfig...")
print(f"Cached agent cache: {agent_cached.cache}")
print(f"No-cache agent cache: {agent_no_cache.cache}")
print(f"Custom agent cache: {agent_custom.cache}")
result = agent_cached.chat("What is caching?")
print(f"Result: {result}")
print("\nCachingConfig tests passed!")
+3 -22
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@@ -2,14 +2,12 @@
Embeddings Capability Example
Demonstrates text embedding generation using PraisonAI capabilities.
Both `embed` and `embedding` work identically - use whichever you prefer.
"""
from praisonai import embed, embedding # Both work from top-level
# Or: from praisonai.capabilities import embed, embedding
from praisonai.capabilities import embed
# Single text embedding using embed()
print("=== Single Text Embedding (using embed) ===")
# Single text embedding
print("=== Single Text Embedding ===")
result = embed(
input="Hello, world!",
model="text-embedding-3-small"
@@ -18,14 +16,6 @@ print(f"Embedding dimensions: {len(result.embeddings[0])}")
print(f"First 5 values: {result.embeddings[0][:5]}")
print(f"Usage: {result.usage}")
# Same thing using embedding() alias
print("\n=== Single Text Embedding (using embedding alias) ===")
result = embedding(
input="Hello, world!",
model="text-embedding-3-small"
)
print(f"Embedding dimensions: {len(result.embeddings[0])}")
# Multiple text embeddings
print("\n=== Multiple Text Embeddings ===")
result = embed(
@@ -35,12 +25,3 @@ result = embed(
print(f"Number of embeddings: {len(result.embeddings)}")
for i, emb in enumerate(result.embeddings):
print(f" Text {i+1}: {len(emb)} dimensions")
# With custom dimensions (for models that support it)
print("\n=== Custom Dimensions ===")
result = embed(
input="Hello world",
model="text-embedding-3-large",
dimensions=256
)
print(f"Reduced dimensions: {len(result.embeddings[0])}")
+1 -1
View File
@@ -163,7 +163,7 @@ def main():
list_all_templates_tool,
get_template_details_tool
],
output="verbose" # Use new consolidated param
verbose=True
)
# Example queries
+29 -34
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@@ -2,10 +2,10 @@
"""
Basic Checkpoints Example for PraisonAI Agents.
This example demonstrates how to use the shadow git checkpointing system with Agent:
1. Create an Agent with checkpoint support
2. Save checkpoints before making changes
3. List available checkpoints
This example demonstrates how to use the shadow git checkpointing system to:
1. Save checkpoints before making changes
2. List available checkpoints
3. View diffs between checkpoints
4. Restore to a previous checkpoint
Usage:
@@ -16,7 +16,6 @@ import asyncio
import tempfile
from pathlib import Path
from praisonaiagents import Agent
from praisonaiagents.checkpoints import CheckpointService
@@ -24,7 +23,7 @@ async def main():
# Create a temporary workspace for demonstration
with tempfile.TemporaryDirectory() as workspace:
print("=" * 60)
print("Agent-Centric Checkpointing Demo")
print("Shadow Git Checkpointing Demo")
print("=" * 60)
print(f"\nWorkspace: {workspace}")
@@ -33,34 +32,24 @@ async def main():
test_file.write_text("# Initial content\nprint('Hello, World!')\n")
print(f"\n✅ Created initial file: {test_file.name}")
# Create checkpoint service (used standalone, not passed to Agent)
checkpoint_service = CheckpointService(workspace_dir=workspace)
# Create an Agent
agent = Agent(
name="RefactorBot",
instructions="You are a code refactoring assistant.",
)
print("\n--- Agent with Checkpoint Support Created ---")
print(f"Agent: {agent.name}")
print(f"Checkpoint service initialized: {checkpoint_service is not None}")
# Initialize the checkpoint service
service = CheckpointService(workspace_dir=workspace)
try:
# Initialize the shadow git repository
print("\n--- Initializing Checkpoint Service ---")
await checkpoint_service.initialize()
await service.initialize()
print("✅ Shadow git repository initialized")
# Save first checkpoint
print("\n--- Saving Checkpoint 1: Initial State ---")
result1 = await checkpoint_service.save("Initial state")
result1 = await service.save("Initial state")
print(f"✅ Checkpoint saved: {result1.checkpoint.id[:8]}")
print(f" Message: {result1.checkpoint.message}")
# Make some changes (simulating agent modifications)
print("\n--- Simulating Agent Changes ---")
test_file.write_text("# Refactored content\nprint('Hello, PraisonAI!')\nprint('Checkpoints are awesome!')\n")
# Make some changes
print("\n--- Making Changes ---")
test_file.write_text("# Modified content\nprint('Hello, PraisonAI!')\nprint('Checkpoints are awesome!')\n")
print("✅ Modified example.py")
# Create a new file
@@ -69,32 +58,38 @@ async def main():
print("✅ Created utils.py")
# Save second checkpoint
print("\n--- Saving Checkpoint 2: After Refactoring ---")
result2 = await checkpoint_service.save("Added features")
print("\n--- Saving Checkpoint 2: After Changes ---")
result2 = await service.save("Added features")
print(f"✅ Checkpoint saved: {result2.checkpoint.id[:8]}")
# List all checkpoints
print("\n--- Listing All Checkpoints ---")
checkpoints_list = await checkpoint_service.list_checkpoints()
for i, cp in enumerate(checkpoints_list, 1):
print(f" {i}. [{cp.id[:8]}] {cp.message}")
checkpoints = await service.list_checkpoints()
for i, cp in enumerate(checkpoints, 1):
print(f" {i}. [{cp.id[:8]}] {cp.message} ({cp.timestamp})")
# Show diff
print("\n--- Current Diff ---")
diff = await checkpoint_service.diff()
print("\n--- Current Diff (uncommitted changes) ---")
diff = await service.diff()
if diff.files:
for f in diff.files:
print(f" {f.status}: {f.path}")
else:
print(" No uncommitted changes")
# Make more changes
test_file.write_text("# Bad changes\nprint('This will be reverted')\n")
print("\n✅ Made problematic changes to example.py")
# Make more changes to show diff
test_file.write_text("# Even more changes\nprint('This will be reverted')\n")
print("\n✅ Made more changes to example.py")
diff = await service.diff()
print("\n--- New Diff ---")
if diff.files:
for f in diff.files:
print(f" {f.status}: {f.path}")
# Restore to checkpoint 2
print(f"\n--- Restoring to Checkpoint: {result2.checkpoint.id[:8]} ---")
await checkpoint_service.restore(result2.checkpoint.id)
await service.restore(result2.checkpoint.id)
print("✅ Restored successfully!")
# Verify restoration
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#!/bin/bash
# Calculator with tests: code + unit tests + test execution + coverage report
# Tests: multiple file creation, test execution, report generation, file reading
praisonai "Build a mini calculator - create /tmp/calculator.py with add, subtract, multiply, divide functions, write unit tests in /tmp/test_calculator.py using unittest, run the tests to make sure they pass, then generate a coverage-style report in /tmp/calc_report.md listing which functions were tested and read it back" --trust
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#!/bin/bash
# Fibonacci generator: code creation, execution, documentation, verification
# Tests: file creation, code execution, markdown writing, file reading
praisonai "Create a Python file at /tmp/fibonacci.py that generates the first 20 Fibonacci numbers, run it to verify the output is correct, then write a summary to /tmp/fib_summary.md explaining the algorithm you used and the output, finally read back both files to confirm everything looks good" --trust
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#!/bin/bash
# Multi-step research: web search, file creation, code execution, reporting
# Tests: web search, file write, code execution, markdown report, file read, directory listing, system info
praisonai "Research the top 3 Python web frameworks (Django, FastAPI, Flask), then: 1) Search the web for each framework's latest version and key features, 2) Create a file called /tmp/framework_comparison.py that contains a Python dictionary with the comparison data, 3) Execute the code to verify the dictionary is valid, 4) Write a markdown report to /tmp/framework_report.md summarizing your findings in a table format, 5) Read back the report file to verify it was written correctly, 6) List the files in /tmp to confirm both files exist, 7) Get system info to note what OS this report was generated on, 8) Analyze the Python code you wrote for any issues, 9) Format the Python code properly, 10) Finally search for any recent news about Python 3.13 features" --trust
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#!/bin/bash
# System audit: multiple command executions, report generation
# Tests: command execution (date, disk, python, processes), file creation, file reading
praisonai "Investigate my system - get the current date, check disk usage, find out what Python version is installed, list running processes sorted by memory, then write all findings to /tmp/system_audit.md as a neat report and read it back to verify" --trust
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#!/bin/bash
# Todo app: multi-file app creation, execution, documentation, verification
# Tests: multiple file creation, code execution, markdown docs, directory listing
praisonai "Write a todo list app at /tmp/todo.py with functions to add, remove, and list tasks stored in /tmp/todos.json, run the script with some sample tasks added, then create documentation at /tmp/todo_docs.md explaining usage with examples, and verify all three files exist" --trust
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#!/bin/bash
# Weather search: web search, JSON creation, Python script, execution
# Tests: web search, JSON file creation, Python scripting, code execution, directory listing
praisonai "Search the web for the current weather in Tokyo, create a JSON file at /tmp/weather_data.json with the findings, then write a Python script at /tmp/parse_weather.py that reads the JSON and prints a formatted weather report, execute the script, and list all files you created in /tmp" --trust
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"""
Basic Context Compaction Example for PraisonAI Agents.
This example demonstrates how to use context compaction with Agent:
1. Create an Agent with context= parameter for compaction
2. Use different compaction strategies via ManagerConfig
3. Monitor compaction results
This example demonstrates how to use context compaction to:
1. Manage conversation context length
2. Use different compaction strategies
3. Track compaction results
4. Preserve important messages
Usage:
python basic_compaction.py
"""
from praisonaiagents import Agent
from praisonaiagents.context import ManagerConfig
from praisonaiagents.compaction import (
ContextCompactor, CompactionConfig, CompactionStrategy, CompactionResult
)
def main():
print("=" * 60)
print("Agent-Centric Context Compaction Demo")
print("Context Compaction Demo")
print("=" * 60)
# ==========================================================================
# Available Strategies
# Sample Messages
# ==========================================================================
print("\n--- Available Compaction Strategies ---")
strategies = [
("truncate", "Remove oldest messages first"),
("sliding_window", "Keep most recent messages within limit"),
("summarize", "Replace old messages with summary"),
("smart", "Intelligently select messages to keep"),
messages = [
{"role": "system", "content": "You are a helpful AI assistant."},
{"role": "user", "content": "Hello! Can you help me with Python?"},
{"role": "assistant", "content": "Of course! I'd be happy to help you with Python. What would you like to know?"},
{"role": "user", "content": "How do I read a file in Python?"},
{"role": "assistant", "content": "To read a file in Python, you can use the built-in open() function. Here's an example:\n\nwith open('filename.txt', 'r') as f:\n content = f.read()\n\nThis opens the file, reads its content, and automatically closes it."},
{"role": "user", "content": "What about writing to a file?"},
{"role": "assistant", "content": "To write to a file, use the 'w' mode:\n\nwith open('filename.txt', 'w') as f:\n f.write('Hello, World!')\n\nUse 'a' mode to append instead of overwriting."},
{"role": "user", "content": "Can you explain list comprehensions?"},
{"role": "assistant", "content": "List comprehensions are a concise way to create lists. Instead of:\n\nresult = []\nfor x in range(10):\n result.append(x * 2)\n\nYou can write:\n\nresult = [x * 2 for x in range(10)]"},
]
for name, desc in strategies:
print(f" {name}: {desc}")
print(f"\n--- Original Messages ---")
print(f" Message count: {len(messages)}")
# ==========================================================================
# Agent with Context Compaction via context= param
# Basic Compaction
# ==========================================================================
print("\n--- Creating Agent with Context Compaction ---")
print("\n--- Basic Compaction (Truncate Strategy) ---")
# Use context= parameter with ManagerConfig for compaction
agent = Agent(
name="LongChat",
instructions="You are a helpful assistant for extended conversations.",
context=ManagerConfig(
auto_compact=True,
compact_threshold=0.8,
strategy="sliding_window",
)
compactor = ContextCompactor(
max_tokens=50, # Low limit to trigger compaction
strategy=CompactionStrategy.TRUNCATE,
preserve_system=True,
preserve_recent=2
)
print(f"Agent: {agent.name}")
print(f"Context manager: {agent.context_manager is not None}")
if agent.context_manager:
print(f"Auto-compact: {agent.context_manager.config.auto_compact}")
print(f"Threshold: {agent.context_manager.config.compact_threshold}")
print(f"Strategy: {agent.context_manager.config.strategy}")
# Check stats before
stats = compactor.get_stats(messages)
print(f" Total tokens: {stats['total_tokens']}")
print(f" Max tokens: {stats['max_tokens']}")
print(f" Needs compaction: {stats['needs_compaction']}")
# Compact
compacted, result = compactor.compact(messages)
print(f"\n After compaction:")
print(f" Messages: {len(messages)} -> {len(compacted)}")
print(f" Tokens: {result.original_tokens} -> {result.compacted_tokens}")
print(f" Saved: {result.tokens_saved} tokens")
print(f" Compression: {result.compression_ratio:.1%}")
# ==========================================================================
# Different Strategy Examples via context= param
# Sliding Window Strategy
# ==========================================================================
print("\n--- Strategy Examples ---")
print("\n--- Sliding Window Strategy ---")
# Sliding window strategy
sliding_agent = Agent(
name="SlidingAgent",
instructions="You are helpful.",
context=ManagerConfig(
auto_compact=True,
strategy="sliding_window",
)
compactor = ContextCompactor(
max_tokens=50,
strategy=CompactionStrategy.SLIDING,
preserve_system=True,
preserve_recent=3
)
print(f" Sliding: strategy={sliding_agent.context_manager.config.strategy}")
# Summarize strategy
summarize_agent = Agent(
name="SummarizeAgent",
instructions="You are helpful.",
context=ManagerConfig(
auto_compact=True,
strategy="summarize",
)
)
print(f" Summarize: strategy={summarize_agent.context_manager.config.strategy}")
compacted, result = compactor.compact(messages)
# Smart strategy
smart_agent = Agent(
name="SmartAgent",
instructions="You are helpful.",
context=ManagerConfig(
auto_compact=True,
strategy="smart",
)
)
print(f" Smart: strategy={smart_agent.context_manager.config.strategy}")
print(f" Messages kept: {result.messages_kept}")
print(f" Messages removed: {result.messages_removed}")
print(f" Strategy: {result.strategy_used.value}")
# ==========================================================================
# Context Manager Stats Demo
# Summarize Strategy
# ==========================================================================
print("\n--- Context Manager Stats Demo ---")
print("\n--- Summarize Strategy ---")
# Access context manager stats
if agent.context_manager:
stats = agent.context_manager.get_stats()
print(f" Model: {stats.get('model', 'N/A')}")
print(f" Model limit: {stats.get('model_limit', 'N/A')}")
print(f" Output reserve: {stats.get('output_reserve', 'N/A')}")
print(f" Usable budget: {stats.get('usable_budget', 'N/A')}")
else:
print(" Context manager not initialized")
compactor = ContextCompactor(
max_tokens=50,
strategy=CompactionStrategy.SUMMARIZE,
preserve_system=True,
preserve_recent=2
)
compacted, result = compactor.compact(messages)
print(f" Messages kept: {result.messages_kept}")
print(f" Strategy: {result.strategy_used.value}")
# Show what messages remain
print(f"\n Remaining message roles:")
for msg in compacted:
role = msg.get("role", "unknown")
content_preview = msg.get("content", "")[:50]
print(f" [{role}] {content_preview}...")
# ==========================================================================
# No Compaction Needed
# ==========================================================================
print("\n--- No Compaction Needed ---")
compactor = ContextCompactor(
max_tokens=10000, # High limit
strategy=CompactionStrategy.TRUNCATE
)
compacted, result = compactor.compact(messages)
print(f" Was compacted: {result.was_compacted}")
print(f" Messages unchanged: {len(compacted) == len(messages)}")
# ==========================================================================
# Result Serialization
# ==========================================================================
print("\n--- Result Serialization ---")
compactor = ContextCompactor(max_tokens=50)
_, result = compactor.compact(messages)
data = result.to_dict()
print(f" Original tokens: {data['original_tokens']}")
print(f" Compacted tokens: {data['compacted_tokens']}")
print(f" Compression ratio: {data['compression_ratio']:.2f}")
print("\n" + "=" * 60)
print("Demo Complete!")
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# Consolidated Params Examples
Examples demonstrating the **Agent-Centric API** with consolidated parameters.
## Precedence Ladder
```
Instance > Config > Array > Dict > String > Bool > Default
```
## Quick Reference
| Feature | Presets | Example |
|---------|---------|---------|
| `memory` | file, sqlite, redis, postgres, mem0, mongodb | `memory="sqlite"` |
| `output` | minimal, normal, verbose, debug, silent | `output="verbose"` |
| `execution` | fast, balanced, thorough, unlimited | `execution="balanced"` |
| `planning` | reasoning, read_only, auto | `planning="reasoning"` |
| `reflection` | minimal, standard, thorough | `reflection="standard"` |
| `guardrails` | strict, permissive, safety | `guardrails="strict"` |
| `web` | duckduckgo, tavily, google, bing, serper | `web="duckduckgo"` |
| `context` | sliding_window, summarize, truncate | `context="sliding_window"` |
| `autonomy` | suggest, auto_edit, full_auto | `autonomy="suggest"` |
| `caching` | enabled, disabled, prompt | `caching="prompt"` |
## Examples
### Basic Examples (Single Feature)
| File | Feature | Description |
|------|---------|-------------|
| `basic_agent.py` | Agent | Minimal agent with memory |
| `basic_memory.py` | memory | SQLite memory preset |
| `basic_output.py` | output | Verbose output preset |
| `basic_execution.py` | execution | Execution control |
| `basic_guardrails.py` | guardrails | Callable validator |
| `basic_reflection.py` | reflection | Self-reflection preset |
| `basic_web.py` | web | Web search preset |
| `basic_planning.py` | planning | Planning preset |
| `basic_autonomy.py` | autonomy | Autonomy preset |
| `basic_caching.py` | caching | Caching preset |
| `basic_knowledge.py` | knowledge | RAG with sources |
| `basic_context.py` | context | Context management |
| `basic_hooks.py` | hooks | Lifecycle callbacks |
### Multi-Agent Examples
| File | Description |
|------|-------------|
| `basic_agents.py` | Multi-agent with memory and planning |
### Workflow Examples
| File | Description |
|------|-------------|
| `basic_workflow.py` | Simple workflow with output preset |
| `basic_workflow_agentlike.py` | Workflow with agent-like params |
| `basic_step_override.py` | Step-level param overrides |
| `advanced_workflow_full_features.py` | All consolidated params |
### Advanced Examples
| File | Description |
|------|-------------|
| `advanced_output_execution.py` | Combined output + execution |
## Usage Forms
Each consolidated param supports multiple input forms:
```python
# Bool - enable with defaults
memory=True
# String preset
memory="sqlite"
# Dict config
memory={"backend": "sqlite", "user_id": "user123"}
# Config instance
memory=MemoryConfig(backend="sqlite", user_id="user123")
# Array with overrides (for some params)
guardrails=["strict", {"max_retries": 10}]
```
## Running Examples
```bash
# Set API key
export OPENAI_API_KEY=your_key_here
# Run any example
python basic_agent.py
```
@@ -1,23 +0,0 @@
"""Advanced memory example - with config and overrides."""
from praisonaiagents import Agent, MemoryConfig
# With full config
agent = Agent(
instructions="You are a helpful assistant with memory.",
memory=MemoryConfig(
backend="redis",
user_id="user123",
session_id="session456",
auto_memory=True,
),
)
# With array [preset, overrides]
agent_override = Agent(
instructions="You are a helpful assistant.",
memory=MemoryConfig(backend="redis", user_id="custom_user"),
)
if __name__ == "__main__":
response = agent.chat("Remember that my favorite color is blue.")
print(response)
@@ -1,17 +0,0 @@
"""
Advanced Output + Execution Example - Agent-Centric API
Demonstrates preset + override array syntax.
"""
from praisonaiagents import Agent
# Advanced: Preset with overrides using array syntax
agent = Agent(
instructions="You are a helpful assistant.",
output=["verbose", {"stream": True, "metrics": True}],
execution=["thorough", {"max_iter": 30}],
)
response = agent.start("Explain quantum computing in simple terms.")
print(response)
@@ -1,55 +0,0 @@
"""Advanced Workflow with all consolidated params configured."""
from praisonaiagents import Agent
from praisonaiagents import AgentFlow, Task
from praisonaiagents.workflows.workflow_configs import (
WorkflowPlanningConfig, WorkflowMemoryConfig,
)
# Full-featured workflow with all consolidated params
workflow = AgentFlow(
name="FullFeaturedWorkflow",
description="Demonstrates all agent-like consolidated params",
steps=[
Task(
name="researcher",
action="Research: {{input}}",
agent=Agent(instructions="You are a researcher."),
knowledge=["research_docs/"], # Step-specific knowledge
web="duckduckgo", # Use DuckDuckGo for this step
),
Task(
name="analyzer",
action="Analyze the research",
agent=Agent(instructions="You are an analyst."),
reflection="thorough", # Thorough reflection for analysis
guardrails="strict", # Strict validation
),
Task(
name="writer",
action="Write the final report",
agent=Agent(instructions="You are a writer."),
autonomy=True, # Enable autonomy for writing
),
],
# Workflow-level consolidated params
output="verbose",
planning=WorkflowPlanningConfig(enabled=True, reasoning=True),
memory=WorkflowMemoryConfig(backend="file"),
# Agent-like params
autonomy=True,
knowledge=["shared_docs/"],
guardrails=True,
web=True,
reflection=True,
)
if __name__ == "__main__":
print(f"Workflow: {workflow.name}")
print(f"Output verbose: {workflow._verbose}")
print(f"Planning enabled: {workflow._planning_enabled}")
print(f"Memory config: {workflow._memory_config}")
print(f"Autonomy: {workflow.autonomy}")
print(f"Knowledge: {workflow.knowledge}")
print(f"Guardrails: {workflow.guardrails}")
print(f"Web: {workflow.web}")
print(f"Reflection: {workflow.reflection}")
@@ -1,12 +0,0 @@
"""Basic Agent example with consolidated params."""
from praisonaiagents import Agent
# Minimal agent with memory
agent = Agent(
instructions="You are a helpful assistant.",
memory=True,
)
if __name__ == "__main__":
response = agent.chat("Hello!")
print(response)
@@ -1,17 +0,0 @@
"""Basic Agents (multi-agent) example with consolidated params."""
from praisonaiagents import Agent, AgentTeam
# Create agents
writer = Agent(instructions="You write content.")
editor = Agent(instructions="You edit content.")
# Multi-agent with consolidated params
agents = AgentTeam(
agents=[writer, editor],
memory=True,
planning=True,
)
if __name__ == "__main__":
result = agents.start("Write a haiku about AI")
print(result)
@@ -1,18 +0,0 @@
"""
Basic Autonomy Example - Agent-Centric API
Demonstrates autonomy with consolidated params.
Presets: suggest, auto_edit, full_auto
"""
from praisonaiagents import Agent
# Basic: Enable autonomy with preset
agent = Agent(
instructions="You are an autonomous assistant.",
autonomy="suggest", # Presets: suggest, auto_edit, full_auto
)
if __name__ == "__main__":
response = agent.start("Help me organize my project files.")
print(response)
@@ -1,23 +0,0 @@
"""
Basic Caching Example - Agent-Centric API
Demonstrates caching with consolidated params.
Presets: enabled, disabled, prompt
"""
from praisonaiagents import Agent
# Basic: Enable caching with preset
agent = Agent(
instructions="You are a helpful assistant with caching enabled.",
caching="prompt", # Presets: enabled, disabled, prompt
)
if __name__ == "__main__":
# First call - will cache
response = agent.start("What is the capital of France?")
print(response)
# Second call - may use cache
response = agent.start("What is the capital of France?")
print(response)
@@ -1,18 +0,0 @@
"""
Basic Context Example - Agent-Centric API
Demonstrates context management with consolidated params.
Presets: sliding_window, summarize, truncate
"""
from praisonaiagents import Agent
# Basic: Enable context management with preset
agent = Agent(
instructions="You are a helpful assistant with context management.",
context="sliding_window", # Presets: sliding_window, summarize, truncate
)
if __name__ == "__main__":
response = agent.start("Tell me a long story about a dragon.")
print(response)
@@ -1,16 +0,0 @@
"""
Basic Execution Example - Agent-Centric API
Demonstrates execution preset usage.
"""
from praisonaiagents import Agent
# Basic: Use fast execution preset
agent = Agent(
instructions="You are a helpful assistant.",
execution="fast", # Presets: fast, balanced, thorough, unlimited
)
response = agent.start("What is the capital of France?")
print(response)
@@ -1,26 +0,0 @@
"""
Basic Guardrails Example - Agent-Centric API
Demonstrates guardrails with callable validator.
"""
from praisonaiagents import Agent
# Define a simple guardrail validator
def validate_response(output):
"""Validate that response doesn't contain forbidden words."""
forbidden = ["error", "fail", "cannot"]
text = str(output).lower()
for word in forbidden:
if word in text:
return (False, f"Response contains forbidden word: {word}")
return (True, output)
# Basic: Use callable guardrail
agent = Agent(
instructions="You are a helpful assistant.",
guardrails=validate_response,
)
response = agent.start("What is 2 + 2?")
print(response)
@@ -1,28 +0,0 @@
"""
Basic Hooks Example - Agent-Centric API
Demonstrates lifecycle hooks with consolidated params.
Valid keys: on_step, on_tool_call, middleware
"""
from praisonaiagents import Agent
# Define hook callbacks
def on_step_callback(step_info):
print(f"Step: {step_info}")
def on_tool_call_callback(tool_info):
print(f"Tool called: {tool_info}")
# Basic: Enable hooks with dict
agent = Agent(
instructions="You are a helpful assistant.",
hooks={
"on_step": on_step_callback,
"on_tool_call": on_tool_call_callback,
},
)
if __name__ == "__main__":
response = agent.start("What is 2 + 2?")
print(response)
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