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Author SHA1 Message Date
DhivyaandDhivya-Bharathy 8536325cc1 fix(examples): phase-3 API alignment for consolidated params on v4.6.52 (#1864)
Co-authored-by: Dhivya-Bharathy <[email protected]>
2026-06-08 07:47:16 +01:00
praisonai-triage-agent[bot]andMervin Praison 8b4db44159 fix: resolve Gemini reviewer issues - remove redundant arguments and fix temp file pollution
- Remove redundant argument from workflow.run() in basic_workflow.py since variables are already set in constructor
- Fix temp file pollution by using system temp directory instead of repository directory in auto_rag_agent_basic.py and knowledge-agents-task.py

Co-authored-by: Mervin Praison <[email protected]>
2026-06-05 10:18:45 +00:00
Dhivya-Bharathy 3d3fdd045e fix(examples): align AgentTeam memory and knowledge configs with v4.6.52 API 2026-06-05 15:37:37 +05:30
praisonai-triage-agent[bot]andMervin Praison bfa9d0ca48 fix: correct TypeError in 3 example files by using proper parameter names
- Fix MemoryConfig(memory=...) → user_id=... in agent_centric_api.py
- Fix Session(memory=...) → user_id=... in session-example.py
- Fix build_context_for_task(memory=...) → user_id=... in memory-quality-example.py

Co-authored-by: Mervin Praison <[email protected]>
2026-06-05 11:26:13 +05:30
Dhivya-Bharathy 3f14324036 fix(examples): resolve syntax errors and align with consolidated-params API 2026-06-04 16:30:02 +05:30
2830 changed files with 81662 additions and 388517 deletions

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<!-- wp:paragraph -->
<p>praisonai-mcp is Tier 2e — the heavy MCP server host: full <code>MCPServer</code>, tool/resource/prompt registries, recipe bridge, HTTP-stream auth, and MCP client config management. Depends only on <code>praisonaiagents</code>. v0.0.2. Protocol: MCP 2025-11-25.</p>
<!-- /wp:paragraph -->
<!-- wp:merpress/mermaidjs {"align":"full"} -->
<div class="wp-block-merpress-mermaidjs diagram-source-mermaid alignfull"><pre class="mermaid">%%{init: {"theme": "base", "themeVariables": {"background": "transparent", "lineColor": "#000000"}}}%%
flowchart TB
CLIENT[Cursor Claude Desktop]
subgraph T1 [praisonaiagents]
SDK[MCP client ToolsMCPServer]
SEC[mcp_security shared]
end
subgraph T2e [praisonai-mcp]
HOST[MCPServer]
REG[tool resource prompt registry]
TR[stdio http-stream]
AUTH[api-key oauth scopes]
CFG[mcp list add sync]
end
subgraph T2a [praisonai-code optional]
LIGHT[serve mcp light]
BRIDGE[_mcp_bridge]
end
subgraph T3 [praisonai wrapper optional]
CAP[capabilities recipe]
end
CLIENT --> TR
TR --> HOST
HOST --> REG
REG -.->|adapters| CAP
CFG -.->|_code_bridge| LIGHT
BRIDGE --> CFG
SDK --> LIGHT
SEC --> TR
classDef agent fill:#8B0000,color:#fff
classDef tool fill:#189AB4,color:#fff
class CLIENT agent
class SDK agent
class HOST agent
class REG tool
class TR tool
class AUTH tool
class CFG tool
class LIGHT tool
class SEC tool
</pre></div>
<!-- /wp:merpress/mermaidjs -->
<!-- wp:heading -->
<h2 class="wp-block-heading">Three MCP layers (do not conflate)</h2>
<!-- /wp:heading -->
<!-- wp:table -->
<figure class="wp-block-table"><table><thead><tr><th>Layer</th><th>Package</th><th>Role</th><th>Entry</th></tr></thead><tbody><tr><td>Client</td><td><code>praisonaiagents/mcp/</code></td><td>Connect agents to external MCP servers; OAuth storage</td><td><code>pip install "praisonaiagents[mcp]"</code></td></tr><tr><td>Light server</td><td><code>praisonai-code</code></td><td>Config-driven basic tool hosting</td><td><code>praisonai serve mcp</code></td></tr><tr><td>Heavy host</td><td><code>praisonai-mcp</code></td><td>Full server, adapters, recipe bridge, HTTP auth</td><td><code>praisonai mcp serve</code></td></tr></tbody></table></figure>
<!-- /wp:table -->
<!-- wp:heading -->
<h2 class="wp-block-heading">Install matrix</h2>
<!-- /wp:heading -->
<!-- wp:table -->
<figure class="wp-block-table"><table><thead><tr><th>Install</th><th><code>praisonai mcp</code></th><th><code>praisonai serve mcp</code></th><th><code>praisonai-mcp</code> script</th></tr></thead><tbody><tr><td><code>pip install praisonai-mcp</code></td><td>—</td><td>—</td><td>✅</td></tr><tr><td><code>pip install "praisonai-mcp[all]"</code></td><td>—</td><td>—</td><td>✅ HTTP + auth</td></tr><tr><td><code>pip install praisonai-code</code> only</td><td>hidden</td><td>✅ light</td><td>—</td></tr><tr><td><code>pip install "praisonai[mcp]"</code></td><td>✅</td><td>✅</td><td>✅</td></tr><tr><td><code>pip install praisonai</code></td><td>✅</td><td>✅</td><td>✅</td></tr></tbody></table></figure>
<!-- /wp:table -->
<!-- wp:paragraph -->
<p>1. Standalone heavy host</p>
<!-- /wp:paragraph -->
<!-- wp:code -->
<pre class="wp-block-code"><code>pip install "praisonai-mcp[all]"
export OPENAI_API_KEY=sk-...
praisonai-mcp --version
praisonai-mcp serve --transport stdio
praisonai-mcp list-tools
praisonai-mcp doctor</code></pre>
<!-- /wp:code -->
<!-- wp:paragraph -->
<p>2. Full stack (same commands via <code>praisonai mcp …</code>)</p>
<!-- /wp:paragraph -->
<!-- wp:code -->
<pre class="wp-block-code"><code>pip install praisonai
# or MCP-only extra
pip install "praisonai[mcp]"
praisonai mcp serve --transport stdio
praisonai mcp list-tools
praisonai mcp doctor</code></pre>
<!-- /wp:code -->
<!-- wp:paragraph -->
<p>3. Light server only (no praisonai-mcp required)</p>
<!-- /wp:paragraph -->
<!-- wp:code -->
<pre class="wp-block-code"><code>pip install praisonai-code "praisonaiagents[mcp]"
praisonai serve mcp --port 8080
# Uses agents ToolsMCPServer — not the heavy MCPServer</code></pre>
<!-- /wp:code -->
<!-- wp:separator -->
<hr class="wp-block-separator has-alpha-channel-opacity"/>
<!-- /wp:separator -->
<!-- wp:heading -->
<h2 class="wp-block-heading">Section 1 — STDIO host (Cursor / Claude Desktop)</h2>
<!-- /wp:heading -->
<!-- wp:code -->
<pre class="wp-block-code"><code># Heavy host — full PraisonAI tool registry
praisonai-mcp serve --transport stdio
# or
praisonai mcp serve --transport stdio
# Generate client config
praisonai mcp config-generate --client cursor --transport stdio
praisonai mcp config-generate --client claude-desktop --transport stdio</code></pre>
<!-- /wp:code -->
<!-- wp:paragraph -->
<p>STDIO uses JSON-RPC over stdin/stdout. Logs go to stderr only — never corrupt the protocol stream.</p>
<!-- /wp:paragraph -->
<!-- wp:heading -->
<h2 class="wp-block-heading">Section 2 — HTTP Stream host</h2>
<!-- /wp:heading -->
<!-- wp:paragraph -->
<p>Streamable HTTP (MCP 2025-11-25) — not legacy standalone SSE. Requires <code>[server]</code> extra (starlette + uvicorn).</p>
<!-- /wp:paragraph -->
<!-- wp:code -->
<pre class="wp-block-code"><code>praisonai mcp serve \
--transport http-stream \
--host 127.0.0.1 \
--port 8080 \
--endpoint /mcp \
--api-key my-secret-key \
--response-mode batch
# Endpoints: POST/GET/DELETE /mcp, plus /health</code></pre>
<!-- /wp:code -->
<!-- wp:paragraph -->
<p>Non-localhost binds require <code>--api-key</code> or <code>--keys-file</code>. Origin validation uses shared helpers from <code>praisonaiagents.mcp.mcp_security</code>.</p>
<!-- /wp:paragraph -->
<!-- wp:heading -->
<h2 class="wp-block-heading">Section 3 — Recipe → MCP bridge</h2>
<!-- /wp:heading -->
<!-- wp:paragraph -->
<p>Turn any PraisonAI recipe into a scoped MCP server with allow/deny lists and safe mode.</p>
<!-- /wp:paragraph -->
<!-- wp:code -->
<pre class="wp-block-code"><code>praisonai mcp serve-recipe support-reply --transport stdio
praisonai mcp validate-recipe support-reply
praisonai mcp inspect-recipe support-reply
praisonai mcp config-generate-recipe support-reply --client claude-desktop</code></pre>
<!-- /wp:code -->
<!-- wp:paragraph -->
<p>Default denied tools include <code>shell.exec</code>, <code>file.delete</code>, <code>eval</code>, and similar destructive operations.</p>
<!-- /wp:paragraph -->
<!-- wp:heading -->
<h2 class="wp-block-heading">Section 4 — MCP client config management</h2>
<!-- /wp:heading -->
<!-- wp:paragraph -->
<p>Config subcommands (<code>list</code>, <code>add</code>, <code>remove</code>, <code>sync</code>, <code>test</code>) require <code>praisonai-code</code> via <code>_code_bridge</code>.</p>
<!-- /wp:paragraph -->
<!-- wp:code -->
<pre class="wp-block-code"><code>praisonai mcp list
praisonai mcp add filesystem \
--command npx \
--args "-y @modelcontextprotocol/server-filesystem ."
praisonai mcp test filesystem
praisonai mcp sync
praisonai mcp tools
praisonai mcp status</code></pre>
<!-- /wp:code -->
<!-- wp:heading -->
<h2 class="wp-block-heading">Section 5 — Built-in registry (tools, resources, prompts)</h2>
<!-- /wp:heading -->
<!-- wp:table -->
<figure class="wp-block-table"><table><thead><tr><th>Type</th><th>Examples</th><th>Adapter</th></tr></thead><tbody><tr><td>Tools</td><td><code>praisonai.chat.*</code>, <code>praisonai.workflow.*</code>, agent run helpers</td><td><code>mcp_server/adapters/capabilities.py</code>, <code>cli_tools.py</code></td></tr><tr><td>Resources</td><td><code>praisonai://memory/sessions</code>, <code>praisonai://workflows</code>, <code>praisonai://agents</code></td><td><code>adapters/resources.py</code></td></tr><tr><td>Prompts</td><td><code>deep-research</code>, <code>code-review</code>, <code>workflow-auto</code></td><td><code>adapters/prompts.py</code></td></tr></tbody></table></figure>
<!-- /wp:table -->
<!-- wp:code -->
<pre class="wp-block-code"><code># Inspect what the host exposes
praisonai-mcp list-tools
praisonai-mcp list-resources
praisonai-mcp list-prompts
# Host tool search (MCPServerCLI)
praisonai-mcp tools search "workflow"</code></pre>
<!-- /wp:code -->
<!-- wp:heading -->
<h2 class="wp-block-heading">Section 6 — Security &amp; auth</h2>
<!-- /wp:heading -->
<!-- wp:table -->
<figure class="wp-block-table"><table><thead><tr><th>Concern</th><th>Package</th><th>Module</th></tr></thead><tbody><tr><td>Origin validation, session IDs</td><td><code>praisonaiagents</code></td><td><code>mcp/mcp_security.py</code></td></tr><tr><td>API keys, scoped keys file</td><td><code>praisonai-mcp</code></td><td><code>mcp_server/auth/api_key.py</code></td></tr><tr><td>OAuth 2.1 + PKCE</td><td><code>praisonai-mcp</code></td><td><code>mcp_server/auth/oauth.py</code></td></tr><tr><td>OIDC discovery</td><td><code>praisonai-mcp</code></td><td><code>mcp_server/auth/oidc.py</code></td></tr><tr><td>Scope enforcement</td><td><code>praisonai-mcp</code></td><td><code>mcp_server/auth/scopes.py</code></td></tr></tbody></table></figure>
<!-- /wp:table -->
<!-- wp:code -->
<pre class="wp-block-code"><code># Scoped keys file (--keys-file)
[
{"key": "monitor-key", "name": "monitor", "scopes": ["tools:read", "resources:read"]},
{"key": "admin-key", "name": "admin", "scopes": ["*"]}
]
# Env vars
export MCP_API_KEY=your-key
export PRAISONAI_MCP_MAX_SESSIONS=1000</code></pre>
<!-- /wp:code -->
<!-- wp:heading -->
<h2 class="wp-block-heading">Section 7 — CLI routing (lazy load)</h2>
<!-- /wp:heading -->
<!-- wp:table -->
<figure class="wp-block-table"><table><thead><tr><th>Registry</th><th>Commands</th><th>Gate</th></tr></thead><tbody><tr><td>MCP-resident Typer</td><td>list, add, remove, sync, test, serve, doctor</td><td><code>mcp_package_available()</code></td></tr><tr><td>MCPServerCLI host</td><td>serve, list-tools, list-resources, config-generate, tasks, auth</td><td>Direct via <code>praisonai-mcp &lt;cmd&gt;</code></td></tr><tr><td>Code-resident light</td><td><code>serve mcp</code></td><td>Always available with code + agents</td></tr><tr><td>Wrapper-resident</td><td>dashboard, schedule, langfuse</td><td><code>wrapper_package_available()</code></td></tr></tbody></table></figure>
<!-- /wp:table -->
<!-- wp:paragraph -->
<p>Standalone <code>praisonai-code</code> hides <code>mcp</code> from <code>--help</code> when <code>praisonai-mcp</code> is not installed. Host commands like <code>praisonai-mcp serve</code> skip the <code>mcp</code> prefix; <code>praisonai mcp serve</code> goes through the Typer group.</p>
<!-- /wp:paragraph -->
<!-- wp:heading -->
<h2 class="wp-block-heading">Section 8 — Python API</h2>
<!-- /wp:heading -->
<!-- wp:code -->
<pre class="wp-block-code"><code>import praisonai_mcp
from praisonai_mcp.mcp_server import MCPServer
from praisonai_mcp.mcp_server.registry import register_tool
from praisonai_mcp.mcp_server.adapters import register_all
@register_tool("custom.greet")
def greet(name: str) -> str:
"""Greet a person by name."""
return f"Hello, {name}!"
register_all()
server = MCPServer(name="praisonai")
server.run(transport="stdio")</code></pre>
<!-- /wp:code -->
<!-- wp:code -->
<pre class="wp-block-code"><code># Recipe host
from praisonai_mcp.mcp_server import RecipeMCPAdapter
adapter = RecipeMCPAdapter("support-reply")
adapter.load()
adapter.to_mcp_server().run(transport="stdio")
# Shim path still works
from praisonai.mcp_server import MCPServer</code></pre>
<!-- /wp:code -->
<!-- wp:heading -->
<h2 class="wp-block-heading">Section 9 — Standalone (no wrapper)</h2>
<!-- /wp:heading -->
<!-- wp:code -->
<pre class="wp-block-code"><code>pip install praisonaiagents "praisonai-mcp[all]"
export OPENAI_API_KEY=sk-...
praisonai-mcp serve --transport stdio
praisonai-mcp list-tools
praisonai-mcp doctor
praisonai-mcp --help</code></pre>
<!-- /wp:code -->
<!-- wp:paragraph -->
<p>Heavy MCP hosting needs only <code>praisonaiagents</code> + <code>praisonai-mcp</code>. Full capability registry (workflows, deploy, extended tools) activates when the wrapper is co-installed via <code>_wrapper_bridge</code>.</p>
<!-- /wp:paragraph -->
<!-- wp:heading -->
<h2 class="wp-block-heading">Bridges (no PyPI cycles)</h2>
<!-- /wp:heading -->
<!-- wp:table -->
<figure class="wp-block-table"><table><thead><tr><th>Bridge</th><th>Direction</th><th>Use</th></tr></thead><tbody><tr><td><code>_mcp_bridge</code></td><td>code → mcp</td><td>Route <code>praisonai mcp</code> into Typer group</td></tr><tr><td><code>_code_bridge</code></td><td>mcp → code</td><td>Config loader, paths, output controller</td></tr><tr><td><code>_wrapper_bridge</code></td><td>mcp → wrapper</td><td>Capabilities, recipe, deploy adapters</td></tr></tbody></table></figure>
<!-- /wp:table -->
<!-- wp:heading -->
<h2 class="wp-block-heading">Backward-compat shims</h2>
<!-- /wp:heading -->
<!-- wp:table -->
<figure class="wp-block-table"><table><thead><tr><th>Old path</th><th>Still works via</th></tr></thead><tbody><tr><td><code>praisonai.mcp_server.*</code></td><td><code>alias_package</code> → <code>praisonai_mcp.mcp_server</code></td></tr><tr><td><code>praisonai.cli.commands.mcp</code></td><td><code>sys.modules</code> shim → mcp Typer group</td></tr><tr><td><code>from praisonai.mcp_server import MCPServer</code></td><td>Lazy re-export through shim</td></tr></tbody></table></figure>
<!-- /wp:table -->
<!-- wp:heading -->
<h2 class="wp-block-heading">Seven-package publish order</h2>
<!-- /wp:heading -->
<!-- wp:code -->
<pre class="wp-block-code"><code>praisonaiagents → praisonai-code → praisonai-bot → praisonai-train → praisonai-browser → praisonai-mcp → praisonai (wrapper)</code></pre>
<!-- /wp:code -->
<!-- wp:paragraph -->
<p>Wrapper pins <code>praisonai-mcp&gt;=X</code> after mcp is on PyPI. CI: <code>.github/workflows/pypi-release.yml</code>. Import gate: <code>scripts/check_c12_mcp_imports.sh</code>.</p>
<!-- /wp:paragraph -->
<!-- wp:heading -->
<h2 class="wp-block-heading">Summary</h2>
<!-- /wp:heading -->
<!-- wp:table -->
<figure class="wp-block-table"><table><thead><tr><th>Item</th><th>Value</th></tr></thead><tbody><tr><td>Tier</td><td>2e</td></tr><tr><td>PyPI</td><td><code>praisonai-mcp</code> v0.0.2</td></tr><tr><td>Runtime deps</td><td><code>praisonaiagents</code>, <code>mcp</code>, rich, typer</td></tr><tr><td>HTTP extra</td><td><code>[server]</code> — starlette, uvicorn</td></tr><tr><td>Auth extra</td><td><code>[auth]</code> — httpx</td></tr><tr><td>Transports</td><td><code>stdio</code>, <code>http-stream</code></td></tr><tr><td>Light alternative</td><td><code>praisonai serve mcp</code> (code tier)</td></tr><tr><td>CLI entry</td><td><code>praisonai-mcp</code> or <code>praisonai mcp</code></td></tr></tbody></table></figure>
<!-- /wp:table -->
<!-- wp:paragraph -->
<p>Previous: <a href="https://mer.vin/2026/07/praisonai-train-praisonai-train-fine-tuning-agent-training-in-depth/">praisonai-train</a> · Next: praisonai wrapper</p>
<!-- /wp:paragraph -->
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<!-- wp:paragraph -->
<p>praisonai is Tier 3 — the integration wrapper that wires <code>praisonaiagents</code> + five Tier-2 packages (<code>praisonai-code</code>, <code>praisonai-bot</code>, <code>praisonai-train</code>, <code>praisonai-browser</code>, <code>praisonai-mcp</code>) into one install, with dashboard, framework adapters, jobs API, serve orchestration, and backward-compat shims. v4.6.150.</p>
<!-- /wp:paragraph -->
<!-- wp:merpress/mermaidjs {"align":"full"} -->
<div class="wp-block-merpress-mermaidjs diagram-source-mermaid alignfull"><pre class="mermaid">%%{init: {"theme": "base", "themeVariables": {"background": "transparent", "lineColor": "#000000"}}}%%
flowchart TB
subgraph T1 [Tier 1 praisonaiagents]
A[Agent tools memory MCP client]
end
subgraph T2 [Tier 2 packages]
C[praisonai-code run chat code]
B[praisonai-bot gateway channels]
TR[praisonai-train fine-tune agents]
BR[praisonai-browser CDP Playwright]
MCP[praisonai-mcp server host]
end
subgraph T3 [Tier 3 praisonai wrapper]
W[dashboard jobs frameworks serve shims]
end
A --> C
A --> B
A --> TR
A --> BR
A --> MCP
W --> C
W --> B
W --> TR
W --> BR
W --> MCP
W --> A
classDef agent fill:#8B0000,color:#fff
classDef tool fill:#189AB4,color:#fff
class A agent
class W agent
class C tool
class B tool
class TR tool
class BR tool
class MCP tool
</pre></div>
<!-- /wp:merpress/mermaidjs -->
<!-- wp:heading -->
<h2 class="wp-block-heading">Seven-package stack</h2>
<!-- /wp:heading -->
<!-- wp:code -->
<pre class="wp-block-code"><code>praisonaiagents → praisonai-code + praisonai-bot + praisonai-train + praisonai-browser + praisonai-mcp → praisonai (wrapper)</code></pre>
<!-- /wp:code -->
<!-- wp:paragraph -->
<p>Each Tier-2 package is installable standalone with its own console script. The wrapper pins all of them and preserves every old import path via shims. Use the wrapper when you need several surfaces together — HTTP serve, dashboard, framework YAML, jobs/recipe — without managing tier pins yourself.</p>
<!-- /wp:paragraph -->
<!-- wp:heading -->
<h2 class="wp-block-heading">Product catalog (C0–C12 shipped)</h2>
<!-- /wp:heading -->
<!-- wp:table -->
<figure class="wp-block-table"><table><thead><tr><th>Package</th><th>Epic</th><th>Choose this when…</th><th>Standalone install</th></tr></thead><tbody><tr><td><code>praisonaiagents</code></td><td>Tier 1</td><td>Building or embedding agents in code — Agent, tools, memory, hooks</td><td><code>pip install praisonaiagents</code></td></tr><tr><td><code>praisonai-code</code></td><td>C0–C8</td><td>Terminal agentic CLI — run, chat, code, warm daemon</td><td><code>pip install praisonai-code</code></td></tr><tr><td><code>praisonai-bot</code></td><td>C9</td><td>Messaging bots + WebSocket gateway</td><td><code>pip install "praisonai-bot[gateway,bot]"</code></td></tr><tr><td><code>praisonai-train</code></td><td>C10</td><td>Agent training loops + GPU LLM fine-tuning</td><td><code>pip install praisonai-train</code> or <code>[llm]</code></td></tr><tr><td><code>praisonai-browser</code></td><td>C11</td><td>Chrome extension bridge, CDP, Playwright agents</td><td><code>pip install "praisonai-browser[all]"</code></td></tr><tr><td><code>praisonai-mcp</code></td><td>C12</td><td>MCP server for Cursor, Claude Desktop, Windsurf</td><td><code>pip install "praisonai-mcp[all]"</code></td></tr><tr><td><code>praisonai</code></td><td>Tier 3</td><td>Full product / umbrella — serve, dashboard, frameworks, jobs</td><td><code>pip install praisonai</code></td></tr></tbody></table></figure>
<!-- /wp:table -->
<!-- wp:heading -->
<h2 class="wp-block-heading">Three-layer products (do not conflate)</h2>
<!-- /wp:heading -->
<!-- wp:table -->
<figure class="wp-block-table"><table><thead><tr><th>Product</th><th>Layer 1 (agents)</th><th>Layer 2 (dedicated pkg)</th><th>Layer 3 (wrapper)</th></tr></thead><tbody><tr><td>Browser</td><td><code>tools/protocols/browser.py</code></td><td><code>praisonai-browser</code></td><td>shims + optional full stack</td></tr><tr><td>MCP</td><td><code>praisonaiagents/mcp</code> client + light server</td><td><code>praisonai-mcp</code> heavy host</td><td>capability bodies via <code>_wrapper_bridge</code></td></tr><tr><td>Bots</td><td>bots/gateway protocols</td><td><code>praisonai-bot</code></td><td>shims only</td></tr><tr><td>Train</td><td>Agent + hooks in agents</td><td><code>praisonai-train</code></td><td>shims + <code>setup-conda-env</code></td></tr></tbody></table></figure>
<!-- /wp:table -->
<!-- wp:heading -->
<h2 class="wp-block-heading">Install matrix</h2>
<!-- /wp:heading -->
<!-- wp:paragraph -->
<p>1. Base install (full seven-package stack)</p>
<!-- /wp:paragraph -->
<!-- wp:code -->
<pre class="wp-block-code"><code>pip install praisonai
export OPENAI_API_KEY=sk-...
praisonai doctor
praisonai version show</code></pre>
<!-- /wp:code -->
<!-- wp:paragraph -->
<p>2. Targeted extras</p>
<!-- /wp:paragraph -->
<!-- wp:code -->
<pre class="wp-block-code"><code>pip install "praisonai[claw]" # dashboard + bots + gateway
pip install "praisonai[all]" # onboarding + messaging + search stack
pip install "praisonai[train]" # LLM fine-tuning (Unsloth stack)
pip install "praisonai[mcp]" # full MCP server host
pip install "praisonai[browser]" # extension bridge + CDP + Playwright
pip install "praisonai[crewai]" # multi-framework YAML</code></pre>
<!-- /wp:code -->
<!-- wp:table -->
<figure class="wp-block-table"><table><thead><tr><th>Package</th><th>Min version (wrapper pin)</th><th>Console script</th></tr></thead><tbody><tr><td><code>praisonaiagents</code></td><td>≥ 1.6.153</td><td>—</td></tr><tr><td><code>praisonai-code</code></td><td>≥ 0.0.49</td><td><code>praisonai-code</code></td></tr><tr><td><code>praisonai-bot</code></td><td>≥ 0.0.34</td><td><code>praisonai-bot</code></td></tr><tr><td><code>praisonai-train</code></td><td>≥ 0.0.5</td><td><code>praisonai-train</code></td></tr><tr><td><code>praisonai-browser</code></td><td>≥ 0.0.2</td><td><code>praisonai-browser</code></td></tr><tr><td><code>praisonai-mcp</code></td><td>≥ 0.0.2</td><td><code>praisonai-mcp</code></td></tr><tr><td><code>praisonai</code></td><td>4.6.150</td><td><code>praisonai</code></td></tr></tbody></table></figure>
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<hr class="wp-block-separator has-alpha-channel-opacity"/>
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<h2 class="wp-block-heading">Section 1 — What wrapper adds (not in Tier-2 alone)</h2>
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<figure class="wp-block-table"><table><thead><tr><th>Feature</th><th>Command / path</th><th>Owner</th><th>Extracted?</th></tr></thead><tbody><tr><td>Unified CLI router</td><td><code>praisonai …</code></td><td>code Typer + 6 resident registries</td><td>—</td></tr><tr><td>HTTP serve orchestration</td><td><code>praisonai serve agents|recipe|a2a|…</code></td><td>wrapper <code>cli/features/serve.py</code></td><td>Deferred (C15 epic)</td></tr><tr><td>Dashboard launcher</td><td><code>praisonai dashboard</code></td><td>wrapper</td><td>Stay wrapper</td></tr><tr><td>Framework adapters</td><td><code>praisonai --framework crewai</code></td><td>wrapper <code>framework_adapters/</code></td><td>Stay wrapper (impls in external PraisonAI-Frameworks)</td></tr><tr><td>Jobs API</td><td><code>praisonai.jobs</code> · port 8005</td><td>wrapper</td><td>Deferred (with serve/recipe)</td></tr><tr><td>Recipe NL → YAML</td><td><code>praisonai recipe …</code></td><td>wrapper</td><td>Deferred</td></tr><tr><td>Scheduler CLI</td><td><code>praisonai schedule …</code></td><td>wrapper</td><td>Stay wrapper (3-layer split with bot)</td></tr><tr><td>Sandbox execution</td><td><code>praisonai sandbox …</code></td><td>wrapper <code>sandbox/</code></td><td>C13 candidate</td></tr><tr><td>Cloud deploy</td><td><code>praisonai deploy …</code></td><td>wrapper <code>deploy/</code></td><td>C13 candidate</td></tr><tr><td>Langfuse / Langflow / n8n</td><td><code>langfuse</code>, <code>flow</code>, <code>n8n</code></td><td>wrapper</td><td>Stay wrapper</td></tr><tr><td>Backward-compat shims</td><td><code>praisonai.bots</code> → <code>praisonai_bot</code></td><td>wrapper <code>cli/_shim.py</code></td><td>Permanent</td></tr></tbody></table></figure>
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<p>Tier-2 packages own their domains; the wrapper owns integration surfaces that span multiple tiers.</p>
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<h2 class="wp-block-heading">Section 2 — Terminal hot path (via code tier)</h2>
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<!-- wp:code -->
<pre class="wp-block-code"><code>pip install praisonai
export OPENAI_API_KEY=sk-...
praisonai run "Summarise the latest AI agent trends"
praisonai chat
praisonai code
praisonai daemon start --background
praisonai run "Hello" # auto-forwards to warm runtime</code></pre>
<!-- /wp:code -->
<!-- wp:code -->
<pre class="wp-block-code"><code># Python SDK (Tier 1 — same everywhere)
from praisonaiagents import Agent
agent = Agent(instructions="You are a helpful AI assistant")
agent.start("Write a movie script about a robot on Mars")</code></pre>
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<p>Deep dive: <a href="https://mer.vin/2026/07/praisonai-code-praisonai-code-terminal-cli-in-depth/">praisonai-code in-depth</a></p>
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<h2 class="wp-block-heading">Section 3 — Train (via praisonai-train tier)</h2>
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<!-- wp:code -->
<pre class="wp-block-code"><code># LLM fine-tuning (Unsloth) — lazy ML deps
praisonai train llm dataset.json
praisonai train llm --model llama-3.1 dataset.json
# Agent training — LLM-as-judge
praisonai train agents --input "What is Python?" --iterations 3
# Human feedback loop
praisonai train agents --input "Explain quantum computing" --human
# Session management
praisonai train list
praisonai train apply train-abc123 --run "And Germany?"
# Standalone script (no wrapper prefix)
praisonai-train agents --input "Hello" --iterations 2</code></pre>
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<!-- wp:paragraph -->
<p>Deep dive: <a href="https://mer.vin/2026/07/praisonai-train-praisonai-train-fine-tuning-agent-training-in-depth/">praisonai-train in-depth</a></p>
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<!-- wp:heading -->
<h2 class="wp-block-heading">Section 4 — Bots &amp; gateway (via bot tier)</h2>
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<!-- wp:code -->
<pre class="wp-block-code"><code>pip install "praisonai[bot]"
export OPENAI_API_KEY=sk-...
export TELEGRAM_BOT_TOKEN=...
praisonai onboard
praisonai bot start --platform telegram
praisonai gateway start --config ~/.praisonai/bot.yaml
praisonai gateway install --config ~/.praisonai/bot.yaml
praisonai pairing approve telegram ABC12345</code></pre>
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<!-- wp:paragraph -->
<p>Deep dive: <a href="https://mer.vin/2026/07/praisonai-bot-praisonai-bot-gateway-channels-in-depth/">praisonai-bot in-depth</a></p>
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<h2 class="wp-block-heading">Section 5 — MCP server host (via mcp tier)</h2>
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<figure class="wp-block-table"><table><thead><tr><th>Command</th><th>Layer</th><th>Package</th></tr></thead><tbody><tr><td><code>praisonai serve mcp</code></td><td>Light server</td><td><code>praisonai-code</code> + agents</td></tr><tr><td><code>praisonai mcp serve</code></td><td>Heavy host</td><td><code>praisonai-mcp</code></td></tr><tr><td><code>praisonai-mcp serve</code></td><td>Heavy host (direct)</td><td><code>praisonai-mcp</code></td></tr></tbody></table></figure>
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<pre class="wp-block-code"><code># Heavy MCP host — full tool/resource/prompt registry
praisonai mcp serve --transport stdio
praisonai mcp serve --transport http-stream --port 8080 --api-key secret
# Recipe → scoped MCP server
praisonai mcp serve-recipe support-reply --transport stdio
# Client config management (needs praisonai-code co-installed)
praisonai mcp list
praisonai mcp add filesystem --command npx --args "-y @modelcontextprotocol/server-filesystem ."
# Generate Cursor / Claude Desktop config
praisonai mcp config-generate --client cursor --transport stdio</code></pre>
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<!-- wp:paragraph -->
<p>Deep dive: <a href="https://mer.vin/2026/07/praisonai-mcp-praisonai-mcp-server-host-client-config-in-depth/">praisonai-mcp in-depth</a></p>
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<!-- wp:heading -->
<h2 class="wp-block-heading">Section 6 — Browser automation (via browser tier)</h2>
<!-- /wp:heading -->
<!-- wp:code -->
<pre class="wp-block-code"><code>pip install "praisonai[browser]"
# Extension bridge server + LLM browser agent
praisonai browser start
praisonai browser run "Find the latest Python release notes"
# Diagnostics
praisonai browser doctor
# Lightweight tool shim (code tier — no praisonai-browser required)
praisonai browser-tool snapshot https://example.com
# Standalone script
praisonai-browser start
praisonai-browser run "Click the login button"</code></pre>
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<!-- wp:paragraph -->
<p>Three layers: agents protocols → <code>praisonai browser-tool</code> (praisonai-tools) → <code>praisonai browser</code> (extension bridge, CDP, Playwright).</p>
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<!-- wp:paragraph -->
<p>Deep dive: <a href="https://mer.vin/2026/07/praisonai-browser-praisonai-browser-browser-automation-in-depth/">praisonai-browser in-depth</a></p>
<!-- /wp:paragraph -->
<!-- wp:heading -->
<h2 class="wp-block-heading">Section 7 — Dashboard stack</h2>
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<!-- wp:code -->
<pre class="wp-block-code"><code>pip install "praisonai[claw,flow,ui]"
# Individual services
praisonai claw # :8082 — ops dashboard
praisonai flow # :7861 — Langflow
praisonai ui # :8081 — clean chat
# Unified launcher (wrapper-only)
praisonai dashboard # :3000
praisonai dashboard --port 9000 --no-auto-start</code></pre>
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<figure class="wp-block-table"><table><thead><tr><th>Port</th><th>Service</th></tr></thead><tbody><tr><td>3000</td><td>Dashboard hub</td></tr><tr><td>7860/7861</td><td>Langflow</td></tr><tr><td>8081</td><td>UI chat</td></tr><tr><td>8082</td><td>Claw</td></tr><tr><td>8765</td><td>Gateway WebSocket</td></tr><tr><td>8005</td><td>Jobs API</td></tr><tr><td>8080</td><td>MCP HTTP stream (optional)</td></tr></tbody></table></figure>
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<!-- wp:heading -->
<h2 class="wp-block-heading">Section 8 — Multi-framework YAML</h2>
<!-- /wp:heading -->
<!-- wp:code -->
<pre class="wp-block-code"><code>pip install "praisonai[crewai]"
export OPENAI_API_KEY=sk-...
praisonai --framework crewai --auto "Create a movie script"
praisonai run --file agents.yaml --framework crewai
pip install "praisonai[autogen]"
praisonai --framework autogen agents.yaml</code></pre>
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<!-- wp:paragraph -->
<p>Protocols live in <code>praisonaiagents/frameworks/</code>; adapter implementations in wrapper <code>framework_adapters/</code>. Entry-point group: <code>praisonai.framework_adapters</code>.</p>
<!-- /wp:paragraph -->
<!-- wp:heading -->
<h2 class="wp-block-heading">Section 9 — Scheduler (24/7 agents)</h2>
<!-- /wp:heading -->
<!-- wp:code -->
<pre class="wp-block-code"><code>praisonai schedule add --agent my_agent.yaml --expr "hourly"
praisonai schedule list
praisonai schedule start</code></pre>
<!-- /wp:code -->
<!-- wp:code -->
<pre class="wp-block-code"><code># Python
from praisonai.scheduler import AgentScheduler
from praisonaiagents import Agent
agent = Agent(name="NewsChecker", instructions="Check latest AI news")
scheduler = AgentScheduler(agent=agent, task="Summarise top 3 AI stories")
scheduler.start("hourly", run_immediately=True)</code></pre>
<!-- /wp:code -->
<!-- wp:paragraph -->
<p>Three scheduler layers: job store (<code>praisonaiagents.scheduler</code>) → CLI (<code>praisonai schedule</code>, wrapper) → gateway tick delivery (<code>praisonai_bot.scheduler.executor</code>).</p>
<!-- /wp:paragraph -->
<!-- wp:heading -->
<h2 class="wp-block-heading">Section 10 — Jobs API &amp; wrapper-only surfaces</h2>
<!-- /wp:heading -->
<!-- wp:paragraph -->
<p>Jobs, recipe, serve, sandbox, and deploy remain wrapper-owned today (deferred or C13 candidates).</p>
<!-- /wp:paragraph -->
<!-- wp:code -->
<pre class="wp-block-code"><code># Jobs API (wrapper — port 8005)
python -m uvicorn praisonai.jobs.server:create_app --port 8005 --factory
praisonai run submit "Analyse AI trends"
praisonai run submit "Analyse news" --recipe news-analyzer --wait
export PRAISONAI_JOBS_API_KEY=your-secret
# HTTP serve (wrapper orchestration — Typer shell in code tier)
praisonai serve agents --port 8080
praisonai serve recipe support-reply
# Sandbox / deploy (wrapper today — C13 extraction candidates)
praisonai sandbox run "print hello" --backend docker
praisonai deploy agents.yaml --provider aws</code></pre>
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<!-- wp:heading -->
<h2 class="wp-block-heading">Section 11 — Lazy CLI routing (six resident registries)</h2>
<!-- /wp:heading -->
<!-- wp:table -->
<figure class="wp-block-table"><table><thead><tr><th>Registry</th><th>Count</th><th>Examples</th><th>Loaded from</th><th>Gate</th></tr></thead><tbody><tr><td>Code-resident</td><td>~40</td><td>run, chat, code, daemon, serve, config</td><td><code>praisonai_code.cli.commands.*</code></td><td>always</td></tr><tr><td>Bot-resident</td><td>8</td><td>bot, gateway, onboard, kanban, claw</td><td><code>praisonai_bot.cli.commands.*</code></td><td><code>bot_package_available()</code></td></tr><tr><td>Train-resident</td><td>1</td><td>train</td><td><code>praisonai_train.cli.commands.*</code></td><td><code>train_package_available()</code></td></tr><tr><td>Browser-resident</td><td>1</td><td>browser</td><td><code>praisonai_browser.cli.commands.*</code></td><td><code>browser_package_available()</code></td></tr><tr><td>MCP-resident</td><td>1</td><td>mcp</td><td><code>praisonai_mcp.cli.commands.*</code></td><td><code>mcp_package_available()</code></td></tr><tr><td>Wrapper-resident</td><td>22</td><td>dashboard, schedule, flow, langfuse, recipe</td><td><code>praisonai.cli.commands.*</code></td><td><code>wrapper_available()</code></td></tr></tbody></table></figure>
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<!-- wp:code -->
<pre class="wp-block-code"><code>praisonai --help # 70+ commands, lazy-loaded
praisonai doctor
praisonai train --help
praisonai mcp --help
praisonai browser --help
praisonai dashboard --help</code></pre>
<!-- /wp:code -->
<!-- wp:paragraph -->
<p>Standalone <code>praisonai-code</code> hides bot/train/browser/mcp/wrapper commands from <code>--help</code> when those packages are absent.</p>
<!-- /wp:paragraph -->
<!-- wp:heading -->
<h2 class="wp-block-heading">Section 12 — Shim map (backward compat)</h2>
<!-- /wp:heading -->
<!-- wp:table -->
<figure class="wp-block-table"><table><thead><tr><th>Old import / path</th><th>Canonical target</th></tr></thead><tbody><tr><td><code>praisonai.cli.main</code></td><td><code>praisonai_code.cli.main</code></td></tr><tr><td><code>praisonai.runtime.*</code></td><td><code>praisonai_code.runtime.*</code></td></tr><tr><td><code>praisonai.bots.*</code></td><td><code>praisonai_bot.bots.*</code></td></tr><tr><td><code>praisonai.gateway.*</code></td><td><code>praisonai_bot.gateway.*</code></td></tr><tr><td><code>praisonai.train.*</code></td><td><code>praisonai_train.train.*</code></td></tr><tr><td><code>praisonai.browser.*</code></td><td><code>praisonai_browser.*</code></td></tr><tr><td><code>praisonai.mcp_server.*</code></td><td><code>praisonai_mcp.mcp_server.*</code></td></tr><tr><td><code>praisonai.scheduler.executor</code></td><td><code>praisonai_bot.scheduler.executor</code></td></tr><tr><td><code>setup-conda-env</code></td><td><code>praisonai_train.setup.setup_conda_env</code></td></tr></tbody></table></figure>
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<!-- wp:code -->
<pre class="wp-block-code"><code># These must keep working
from praisonai.cli.main import PraisonAI
from praisonai.bots import Bot
from praisonai.gateway import WebSocketGateway
from praisonai.train.agents import AgentTrainer
from praisonai.mcp_server import MCPServer
python -m praisonai run "hello"
python -m praisonai.runtime</code></pre>
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<!-- wp:heading -->
<h2 class="wp-block-heading">Section 13 — Bridges (no PyPI cycles)</h2>
<!-- /wp:heading -->
<!-- wp:table -->
<figure class="wp-block-table"><table><thead><tr><th>Bridge</th><th>Direction</th><th>Use</th></tr></thead><tbody><tr><td><code>_wrapper_bridge</code></td><td>code → wrapper</td><td>serve handlers, frameworks, jobs</td></tr><tr><td><code>_bot_bridge</code></td><td>code → bot</td><td>bot/gateway CLI routing</td></tr><tr><td><code>_train_bridge</code></td><td>code → train</td><td>train CLI routing</td></tr><tr><td><code>_browser_bridge</code></td><td>code → browser</td><td>browser CLI routing</td></tr><tr><td><code>_mcp_bridge</code></td><td>code → mcp</td><td>mcp CLI routing</td></tr><tr><td><code>_code_bridge</code></td><td>tier-2 → code</td><td>config kernel, legacy dispatch</td></tr><tr><td><code>_wrapper_bridge</code></td><td>tier-2 → wrapper</td><td>capabilities, recipe, jobs/UI</td></tr></tbody></table></figure>
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<!-- wp:heading -->
<h2 class="wp-block-heading">When to use wrapper vs a Tier-2 package alone</h2>
<!-- /wp:heading -->
<!-- wp:table -->
<figure class="wp-block-table"><table><thead><tr><th>Your goal</th><th>Install</th></tr></thead><tbody><tr><td>Only terminal agents</td><td><code>praisonai-code</code> (+ optional <code>praisonaiagents</code>)</td></tr><tr><td>Only bots on Telegram/Slack</td><td><code>praisonai-bot</code></td></tr><tr><td>Only train / fine-tune</td><td><code>praisonai-train</code></td></tr><tr><td>Only automate browser</td><td><code>praisonai-browser</code></td></tr><tr><td>Only MCP server for IDE</td><td><code>praisonai-mcp</code></td></tr><tr><td>Several of the above + serve / dashboard / framework YAML</td><td><code>pip install praisonai</code></td></tr></tbody></table></figure>
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<!-- wp:heading -->
<h2 class="wp-block-heading">What stays in wrapper (not extracted)</h2>
<!-- /wp:heading -->
<!-- wp:table -->
<figure class="wp-block-table"><table><thead><tr><th>Surface</th><th>Why it stays</th></tr></thead><tbody><tr><td><code>dashboard</code> / <code>flow</code> / <code>ui</code></td><td>Langflow extra + launcher glue — not a standalone PyPI product</td></tr><tr><td><code>claw</code></td><td>Default app lives in <code>praisonai-bot</code>; wrapper is a thin shim</td></tr><tr><td><code>framework_adapters/</code></td><td>Thin registry; heavy impls in external PraisonAI-Frameworks</td></tr><tr><td><code>schedule</code> CLI</td><td>Three-layer split: agents store + wrapper CLI + bot executor</td></tr><tr><td><code>serve</code> / <code>recipe</code> / <code>jobs</code></td><td>~14k LOC deferred epic — high coupling (C15)</td></tr><tr><td><code>sandbox</code> / <code>deploy</code></td><td>Still in wrapper today; C13 extraction candidates</td></tr><tr><td><code>standardise</code> / suite runner</td><td>Maintainer/docs tooling — internal only</td></tr><tr><td><code>persist</code> / enterprise adapters</td><td><strong>Rejected</strong> — agents already ship File/SQLite defaults; no crisp standalone story</td></tr></tbody></table></figure>
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<!-- wp:heading -->
<h2 class="wp-block-heading">Roadmap — C13+ candidates</h2>
<!-- /wp:heading -->
<!-- wp:table -->
<figure class="wp-block-table"><table><thead><tr><th>Package</th><th>Status</th><th>Choose when…</th><th>Standalone install (planned)</th></tr></thead><tbody><tr><td><code>praisonai-sandbox</code></td><td><strong>C13 preferred</strong> (execution goal)</td><td>Isolated agent code execution — Docker/E2B/Modal/Daytona/Sandlock</td><td><code>pip install praisonai-sandbox[docker]</code></td></tr><tr><td><code>praisonai-deploy</code></td><td><strong>C13 alt</strong> (deploy goal)</td><td>Ship <code>agents.yaml</code> to Docker/AWS/GCP/Azure</td><td><code>pip install praisonai-deploy</code></td></tr><tr><td><code>praisonai-replay</code></td><td>Conditional C14+</td><td>Deterministic replay from run ledger / traces</td><td>After product sign-off</td></tr><tr><td><code>praisonai-serve</code></td><td>Deferred C15</td><td>HTTP API hosting without full umbrella (~14k LOC)</td><td>With recipe/jobs decision</td></tr><tr><td><code>praisonai-recipe</code></td><td>Deferred</td><td>NL → agent YAML without jobs UI</td><td>Tied to jobs + serve</td></tr><tr><td><code>praisonai-jobs</code></td><td>Deferred</td><td>Async long-running agent jobs API</td><td>Extract with serve or stay wrapper</td></tr></tbody></table></figure>
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<!-- wp:paragraph -->
<p>C13 decision rule: <strong>sandbox</strong> = where code runs; <strong>deploy</strong> = where the agent service lives. Ship one first after product sign-off.</p>
<!-- /wp:paragraph -->
<!-- wp:heading -->
<h2 class="wp-block-heading">Standalone extraction litmus test</h2>
<!-- /wp:heading -->
<!-- wp:table -->
<figure class="wp-block-table"><table><thead><tr><th>Criterion</th><th>Pass (browser/MCP)</th><th>Fail (example)</th></tr></thead><tbody><tr><td>Named user goal without full <code>praisonai</code></td><td><code>pip install praisonai-browser</code> → automate Chrome</td><td><code>pip install praisonai-persist</code> → ???</td></tr><tr><td>Coherent product boundary</td><td>One Typer group / one console script</td><td>Whole <code>cli/features/</code> orchestration layer</td></tr><tr><td>PyPI deps: <code>praisonaiagents</code> only</td><td>Tier-2 + lazy <code>_wrapper_bridge</code></td><td>Hard <code>import praisonai</code> at module level</td></tr><tr><td>Worth a separate install</td><td>User who never wants dashboard/serve/bots</td><td>Internal docs tooling</td></tr><tr><td>Extraction shape</td><td>C10 single PR (~3–11k LOC)</td><td>Mega-epic without product sign-off</td></tr></tbody></table></figure>
<!-- /wp:table -->
<!-- wp:heading -->
<h2 class="wp-block-heading">When to use which tier</h2>
<!-- /wp:heading -->
<!-- wp:table -->
<figure class="wp-block-table"><table><thead><tr><th>Scenario</th><th>Install</th></tr></thead><tbody><tr><td>Pure Python agents, minimal deps</td><td><code>pip install praisonaiagents</code></td></tr><tr><td>Terminal coding agent, CI, headless</td><td><code>pip install praisonai-code</code></td></tr><tr><td>Telegram/Discord gateway only</td><td><code>pip install "praisonai-bot[gateway,bot]"</code></td></tr><tr><td>Agent training (no GPU)</td><td><code>pip install praisonai-train</code></td></tr><tr><td>LLM fine-tuning (GPU)</td><td><code>pip install "praisonai-train[llm]"</code></td></tr><tr><td>MCP server for Cursor/Claude</td><td><code>pip install "praisonai-mcp[all]"</code></td></tr><tr><td>Browser automation (extension/CDP)</td><td><code>pip install "praisonai-browser[all]"</code></td></tr><tr><td>CrewAI/AutoGen YAML</td><td><code>pip install "praisonai[crewai]"</code></td></tr><tr><td>Full ops + channels + dashboard</td><td><code>pip install "praisonai[claw]"</code></td></tr><tr><td>Everything in one install</td><td><code>pip install praisonai</code></td></tr><tr><td>Library author / embedding</td><td><code>praisonaiagents</code> only</td></tr></tbody></table></figure>
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<!-- wp:heading -->
<h2 class="wp-block-heading">Seven-package publish order</h2>
<!-- /wp:heading -->
<!-- wp:code -->
<pre class="wp-block-code"><code>praisonaiagents
→ praisonai-code + praisonai-bot + praisonai-train + praisonai-browser + praisonai-mcp
→ praisonai (wrapper pins all tier-2 deps last)</code></pre>
<!-- /wp:code -->
<!-- wp:paragraph -->
<p>CI: <code>.github/workflows/pypi-release.yml</code> · selective publish: <code>publish_all.py --changed-only</code> (default). Playbook per package: manifest → TDD compat tests → git mv → shims → <code>_X_RESIDENT_COMMANDS</code> → CI shard → PyPI.</p>
<!-- /wp:paragraph -->
<!-- wp:heading -->
<h2 class="wp-block-heading">Summary</h2>
<!-- /wp:heading -->
<!-- wp:table -->
<figure class="wp-block-table"><table><thead><tr><th>Item</th><th>Value</th></tr></thead><tbody><tr><td>Tier</td><td>3 (integration wrapper)</td></tr><tr><td>PyPI</td><td><code>praisonai</code> v4.6.150</td></tr><tr><td>Shipped tier-2 deps</td><td>code, bot, train, browser, mcp (C0–C12)</td></tr><tr><td>Resident registries</td><td>6 (code + bot + train + browser + mcp + wrapper)</td></tr><tr><td>Wrapper-only (~140k LOC)</td><td>serve, recipe, jobs, dashboard, sandbox, deploy, frameworks</td></tr><tr><td>Next extraction</td><td>C13: sandbox or deploy (product sign-off)</td></tr><tr><td>One-liner still works</td><td><code>pip install praisonai</code></td></tr></tbody></table></figure>
<!-- /wp:table -->
<!-- wp:paragraph -->
<p>Architecture overview: Seven-package C7–C12 extraction · Post-C12 roadmap (C13+)</p>
<!-- /wp:paragraph -->
<!-- wp:paragraph -->
<p>Series: <a href="https://mer.vin/2026/07/praisonai-code-praisonai-code-terminal-cli-in-depth/">praisonai-code</a> · <a href="https://mer.vin/2026/07/praisonai-bot-praisonai-bot-gateway-channels-in-depth/">praisonai-bot</a> · <a href="https://mer.vin/2026/07/praisonai-train-praisonai-train-fine-tuning-agent-training-in-depth/">praisonai-train</a> · <a href="https://mer.vin/2026/07/praisonai-browser-praisonai-browser-browser-automation-in-depth/">praisonai-browser</a> · <a href="https://mer.vin/2026/07/praisonai-mcp-praisonai-mcp-server-host-client-config-in-depth/">praisonai-mcp</a> · praisonai wrapper</p>
<!-- /wp:paragraph -->
+4 -40
View File
@@ -222,17 +222,14 @@ runs:
STEP 2 — ARCHITECTURE VALIDATION & ROUTING (MANDATORY before writing code):
Before implementing anything, answer these questions:
- CORE vs WRAPPER vs TOOLS vs PLUGINS ROUTING:
- 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 → MervinPraison/PraisonAI-Tools: agent-callable integrations at runtime (Composio, Slack, APIs). Do NOT add to praisonaiagents/.
4. Plugins → MervinPraison/PraisonAI-Plugins: lifecycle extensions (tracing, logging, hooks, guardrails). Not agent tools.
5. Sandbox backends → PraisonAI-Plugins via `praisonai.sandbox` entry point (core protocol only).
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).
- Do not bloat the Agent class with additional params — only if absolutely required; we already support many params.
- 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. PRs with >100 lines added to agent.py require manual review (merge gate will not auto-merge).
- 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.
@@ -263,24 +260,16 @@ runs:
ANTHROPIC_API_KEY: ${{ inputs.anthropic_api_key }}
CLAUDE_CODE_OAUTH_TOKEN: ${{ inputs.claude_code_oauth_token }}
GITHUB_TOKEN: ${{ inputs.github_token }}
INPUT_MODEL: ${{ inputs.model }}
INPUT_MAX_TURNS: ${{ inputs.max_turns }}
INPUT_ALLOWED_TOOLS: ${{ inputs.allowed_tools }}
INPUT_DISALLOWED_TOOLS: ${{ inputs.disallowed_tools }}
INPUT_TIMEOUT_MINUTES: ${{ inputs.timeout_minutes }}
CLAUDE_CODE_SUBAGENT_MODEL: inherit
ANTHROPIC_DEFAULT_SONNET_MODEL: claude-sonnet-4-6
run: |
echo "🚀 Running Claude Code with GitHub context..."
# Build command arguments
CMD_ARGS=("-p" "--verbose" "--output-format" "stream-json")
if [[ -n "$INPUT_MODEL" ]]; then
CMD_ARGS+=("--model" "$INPUT_MODEL")
export ANTHROPIC_MODEL="$INPUT_MODEL"
fi
# Add max turns if specified
if [[ -n "$INPUT_MAX_TURNS" ]]; then
CMD_ARGS+=("--max-turns" "$INPUT_MAX_TURNS")
@@ -291,36 +280,11 @@ runs:
if [[ -n "$INPUT_ALLOWED_TOOLS" ]]; then
TOOLS="$TOOLS,$INPUT_ALLOWED_TOOLS"
fi
# Remove any explicitly disallowed tools from the effective allow-list so
# the read-only contract is enforced deterministically (no reliance on CLI
# precedence between --allowedTools and --disallowedTools).
if [[ -n "$INPUT_DISALLOWED_TOOLS" ]]; then
DISALLOWED_CSV=$(echo "$INPUT_DISALLOWED_TOOLS" | tr ',\n' ' ' | xargs)
FILTERED=""
IFS=',' read -ra TOOL_ARR <<< "$TOOLS"
for tool in "${TOOL_ARR[@]}"; do
tool=$(echo "$tool" | xargs)
[[ -z "$tool" ]] && continue
skip="false"
for bad in $DISALLOWED_CSV; do
if [[ "$tool" == "$bad" ]]; then
skip="true"
break
fi
done
if [[ "$skip" == "false" ]]; then
FILTERED="${FILTERED:+$FILTERED,}$tool"
fi
done
TOOLS="$FILTERED"
fi
CMD_ARGS+=("--allowedTools" "$TOOLS")
# Add disallowed tools
if [[ -n "$INPUT_DISALLOWED_TOOLS" ]]; then
DISALLOWED_FLAG=$(echo "$INPUT_DISALLOWED_TOOLS" | tr '\n' ',' | sed 's/,*$//')
CMD_ARGS+=("--disallowedTools" "$DISALLOWED_FLAG")
CMD_ARGS+=("--disallowedTools" "$INPUT_DISALLOWED_TOOLS")
fi
echo "📝 Executing Claude Code with prompt from file..."
@@ -1,96 +0,0 @@
name: Install PraisonAI monorepo packages
description: Install praisonai-agents, praisonai-code, praisonai-bot, praisonai-train, praisonai-browser, praisonai-mcp, praisonai-sandbox, praisonai-deploy, and praisonai wrapper from local paths (mirrors PyPI nine-package install order).
inputs:
repo-root:
description: Path prefix to monorepo root (e.g. PraisonAI/ for cross-repo checkout)
required: false
default: ""
use-uv:
description: Use uv pip instead of pip
required: false
default: "false"
agents-extras:
description: Optional extras for praisonaiagents (e.g. .[all] or [all])
required: false
default: ""
wrapper-extras:
description: Optional extras for praisonai wrapper (e.g. .[chat,code] or [chat,code])
required: false
default: ""
runs:
using: composite
steps:
- name: Install monorepo packages
shell: bash
run: |
set -euo pipefail
WORKSPACE="${GITHUB_WORKSPACE:-$(pwd)}"
ROOT="${{ inputs.repo-root }}"
if [ -n "$ROOT" ]; then
BASE="${WORKSPACE%/}/${ROOT%/}/"
else
BASE="${WORKSPACE%/}/"
fi
AGENTS_PKG="${BASE}src/praisonai-agents"
CODE_PKG="${BASE}src/praisonai-code"
BOT_PKG="${BASE}src/praisonai-bot"
TRAIN_PKG="${BASE}src/praisonai-train"
BROWSER_PKG="${BASE}src/praisonai-browser"
MCP_PKG="${BASE}src/praisonai-mcp"
SANDBOX_PKG="${BASE}src/praisonai-sandbox"
DEPLOY_PKG="${BASE}src/praisonai-deploy"
WRAPPER_PKG="${BASE}src/praisonai"
normalise_extras() {
local value="${1#.}"
if [ -n "$value" ]; then
printf '.%s' "$value"
else
printf '.'
fi
}
AGENTS_SUFFIX="$(normalise_extras "${{ inputs.agents-extras }}")"
WRAPPER_SUFFIX="$(normalise_extras "${{ inputs.wrapper-extras }}")"
if [ "${{ inputs.use-uv }}" = "true" ]; then
cd "$AGENTS_PKG"
uv pip install --system -e "${AGENTS_SUFFIX}"
cd "$CODE_PKG"
uv pip install --system -e .
cd "$BOT_PKG"
uv pip install --system -e .
cd "$TRAIN_PKG"
uv pip install --system -e .
cd "$BROWSER_PKG"
uv pip install --system -e .
cd "$MCP_PKG"
uv pip install --system -e .
cd "$SANDBOX_PKG"
uv pip install --system -e .
cd "$DEPLOY_PKG"
uv pip install --system -e .
cd "$WRAPPER_PKG"
uv pip install --system "${WRAPPER_SUFFIX}"
else
cd "$AGENTS_PKG"
pip install -e "${AGENTS_SUFFIX}"
cd "$CODE_PKG"
pip install -e .
cd "$BOT_PKG"
pip install -e .
cd "$TRAIN_PKG"
pip install -e .
cd "$BROWSER_PKG"
pip install -e .
cd "$MCP_PKG"
pip install -e .
cd "$SANDBOX_PKG"
pip install -e .
cd "$DEPLOY_PKG"
pip install -e .
cd "$WRAPPER_PKG"
pip install -e "${WRAPPER_SUFFIX}"
fi
+2 -8
View File
@@ -34,17 +34,11 @@ steps:
Third, read architecture guidelines: execute_command 'cat src/praisonai-agents/AGENTS.md'.
Fourth, decide routing before planning:
- Tools → PraisonAI-Tools: agent-callable integrations at runtime (Composio, Slack, APIs).
- Plugins → PraisonAI-Plugins: lifecycle extensions (tracing, logging, hooks, guardrails).
- Sandbox backends → PraisonAI-Plugins via `praisonai.sandbox` entry point.
Core SDK/wrapper only for protocols and CLI — external repos for Tools/Plugins.
Fifth, decide if this issue requires code changes:
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 / Wrapper / Tools-external / Plugins-external / No-change), validation result, and exact files/lines to change.
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
@@ -1,34 +0,0 @@
#!/usr/bin/env node
const chain = require('./bot-pr-review-chain.js');
let failed = 0;
function assert(name, cond) {
if (!cond) {
console.error('FAIL:', name);
failed++;
} else {
console.log('ok:', name);
}
}
assert('chainKickPosted requires both markers', chain.chainKickPosted([
{ user: { login: 'MervinPraison' }, body: '@coderabbitai review' },
{ user: { login: 'MervinPraison' }, body: '/review' },
]));
assert('chainKickPosted false with only coderabbit', !chain.chainKickPosted([
{ user: { login: 'MervinPraison' }, body: '@coderabbitai review' },
]));
assert('coderabbitKickPosted detects coderabbit', chain.coderabbitKickPosted([
{ user: { login: 'MervinPraison' }, body: '@coderabbitai review' },
]));
assert('qodoKickPosted detects qodo', chain.qodoKickPosted([
{ user: { login: 'github-actions[bot]' }, body: '/review' },
]));
assert('ignores coderabbit bot comment', !chain.coderabbitKickPosted([
{ user: { login: 'coderabbitai[bot]' }, body: '@coderabbitai review' },
]));
assert('bot PR author match', chain.isBotOpenedPr({ user: { login: 'praisonai-triage-agent[bot]' } }));
assert('generic bot type match', chain.isBotOpenedPr({ user: { login: 'my-bot', type: 'Bot' } }));
assert('human author excluded', !chain.isBotOpenedPr({ user: { login: 'MervinPraison', type: 'User' } }));
process.exit(failed ? 1 : 0);
-153
View File
@@ -1,153 +0,0 @@
/**
* Idempotent CodeRabbit/Qodo kick for bot-opened PRs.
* @see .github/workflows/auto-pr-comment.yml, claude.yml, bot-pr-recovery.yml
*/
const KICK_AUTHORS = new Set(['MervinPraison', 'github-actions[bot]']);
const BOT_PR_AUTHORS = new Set(['praisonai-triage-agent[bot]', 'github-actions[bot]']);
async function listAllComments(github, owner, repo, issueNumber) {
if (typeof github.paginate === 'function') {
return github.paginate(github.rest.issues.listComments, {
owner,
repo,
issue_number: issueNumber,
per_page: 100,
});
}
const { data } = await github.rest.issues.listComments({
owner,
repo,
issue_number: issueNumber,
per_page: 100,
});
return data;
}
function kickAuthored(comment, marker) {
return (
KICK_AUTHORS.has(comment.user?.login) &&
(comment.body || '').includes(marker)
);
}
function coderabbitKickPosted(comments) {
return comments.some((c) => kickAuthored(c, '@coderabbitai review'));
}
function qodoKickPosted(comments) {
return comments.some((c) => kickAuthored(c, '/review'));
}
function chainKickPosted(comments) {
return coderabbitKickPosted(comments) && qodoKickPosted(comments);
}
function isBotOpenedPr(pr) {
if (BOT_PR_AUTHORS.has(pr.user?.login)) return true;
return pr.user?.type === 'Bot';
}
async function kickReviewChain(github, owner, repo, prNumber, core, preFetchedComments = null) {
const comments = preFetchedComments || await listAllComments(github, owner, repo, prNumber);
const needCoderabbit = !coderabbitKickPosted(comments);
const needQodo = !qodoKickPosted(comments);
if (!needCoderabbit && !needQodo) {
core?.info?.(`Review chain already kicked on PR #${prNumber}`);
return { kicked: false, reason: 'already_kicked' };
}
if (needCoderabbit) {
await github.rest.issues.createComment({
owner,
repo,
issue_number: prNumber,
body: '@coderabbitai review',
});
}
if (needQodo) {
await github.rest.issues.createComment({
owner,
repo,
issue_number: prNumber,
body: '/review',
});
}
core?.info?.(`Kicked review chain for PR #${prNumber} (coderabbit=${needCoderabbit}, qodo=${needQodo})`);
return { kicked: true, coderabbit: needCoderabbit, qodo: needQodo };
}
async function findOpenPrForIssue(github, owner, repo, issueNumber) {
const prefix = `claude/issue-${issueNumber}-`;
const { data: prs } = await github.rest.pulls.list({
owner,
repo,
state: 'open',
sort: 'created',
direction: 'desc',
per_page: 30,
});
return (
prs.find(
(p) => (p.head?.ref || '').startsWith(prefix) && isBotOpenedPr(p)
) || null
);
}
async function kickReviewChainForIssue(github, owner, repo, issueNumber, core) {
const pr = await findOpenPrForIssue(github, owner, repo, issueNumber);
if (!pr) {
core?.info?.(`No open PR for issue #${issueNumber}, skipping review kick`);
return { kicked: false, reason: 'no_pr' };
}
const result = await kickReviewChain(github, owner, repo, pr.number, core);
return { ...result, prNumber: pr.number };
}
async function recoverStalledBotPrs(github, owner, repo, options, core) {
const { prNumber = null, minAgeMs = 10 * 60 * 1000, maxRecover = 10 } = options || {};
let prs;
if (prNumber) {
const { data } = await github.rest.pulls.get({ owner, repo, pull_number: prNumber });
prs = [data];
} else if (typeof github.paginate === 'function') {
prs = await github.paginate(github.rest.pulls.list, {
owner,
repo,
state: 'open',
per_page: 100,
});
} else {
const { data } = await github.rest.pulls.list({ owner, repo, state: 'open', per_page: 100 });
prs = data;
}
const cutoff = Date.now() - minAgeMs;
let recovered = 0;
for (const pr of prs) {
if (recovered >= maxRecover) break;
if (!isBotOpenedPr(pr)) continue;
if (!prNumber && new Date(pr.created_at).getTime() > cutoff) continue;
const comments = await listAllComments(github, owner, repo, pr.number);
if (chainKickPosted(comments)) continue;
await kickReviewChain(github, owner, repo, pr.number, core, comments);
recovered += 1;
}
core?.info?.(`Recovery complete (${recovered} PR(s) kicked)`);
return recovered;
}
module.exports = {
KICK_AUTHORS,
BOT_PR_AUTHORS,
listAllComments,
chainKickPosted,
coderabbitKickPosted,
qodoKickPosted,
isBotOpenedPr,
kickReviewChain,
findOpenPrForIssue,
kickReviewChainForIssue,
recoverStalledBotPrs,
};
@@ -1,93 +0,0 @@
#!/usr/bin/env node
/**
* Run: node .github/scripts/ci-failure-claude-selftest.js
*/
const ciFix = require('./ci-failure-claude.js');
const mergeGate = require('./merge-gate.js');
let failed = 0;
function assert(name, cond) {
if (!cond) {
console.error('FAIL:', name);
failed += 1;
} else {
console.log('ok:', name);
}
}
const LOG_2767 = `
test-core (cli) UNKNOWN STEP 2026-07-07T17:21:49.8096670Z FAILED (0.0100s) tests/unit/cli/test_typer_cli.py::TestConfigCommand::test_config_list - ValueError: I/O operation on closed file.
test-core (cli) UNKNOWN STEP 2026-07-07T17:21:49.8097323Z ============= 1 failed, 1401 passed, 1 skipped in 88.86s (0:01:28) =============
test-core (cli) UNKNOWN STEP 2026-07-07T17:21:49.8693341Z ##[error]Process completed with exit code 1.
`;
const parsed = ciFix.parsePytestFailures(LOG_2767);
assert('parses pytest failure from log', parsed.length === 1);
assert(
'extracts test path',
parsed[0]?.testId === 'tests/unit/cli/test_typer_cli.py::TestConfigCommand::test_config_list'
);
assert(
'extracts error message',
parsed[0]?.error.includes('ValueError: I/O operation on closed file')
);
const comment = ciFix.buildCiFixComment({
headSha: 'dfb81bb0ae7f36bf8d66d8f45053464c18c005a3',
failedChecks: [
{
name: 'test-core (cli)',
workflow: 'Core Tests',
html_url: 'https://github.com/MervinPraison/PraisonAI/actions/runs/28885180173/job/85683605433',
},
],
failureSummaries: [{ jobName: 'test-core (cli)', failures: parsed }],
});
assert('comment includes @claude', comment.includes('@claude'));
assert('comment includes short sha', comment.includes('dfb81bb0'));
assert('comment includes test path', comment.includes('test_typer_cli.py::TestConfigCommand::test_config_list'));
assert('comment includes job url', comment.includes('85683605433'));
assert('comment requires critical review verdict', comment.includes('Critical review first'));
assert('comment forbids weakening tests', comment.includes('do not weaken, skip, or delete tests'));
assert('comment mentions SDK guardrails', comment.includes('SDK guardrails'));
assert('comment asks for legitimacy verdict', comment.includes('legitimate fix'));
const headSha = 'dfb81bb0ae7f36bf8d66d8f45053464c18c005a3';
const commentsWithFix = [
{
user: { login: 'MervinPraison' },
body: '@claude CI failed on HEAD `dfb81bb0`. Please fix...',
created_at: '2026-07-07T18:00:00Z',
},
];
assert('sha dedup detects existing comment', ciFix.hasCiFixCommentForSha(commentsWithFix, headSha));
const skipNoFinal = ciFix.shouldSkipCiFix({
comments: [],
headSha,
labels: [],
hasFinal: false,
claudeInProgress: false,
failedChecks: [{ name: 'test-core' }],
});
assert('skips when final not posted', skipNoFinal.skip && skipNoFinal.reason.includes('final'));
const skipPending = ciFix.shouldSkipCiFix({
comments: [],
headSha,
labels: [ciFix.CI_FIX_LABEL],
hasFinal: true,
claudeInProgress: false,
failedChecks: [{ name: 'test-core' }],
});
assert('skips when ci fix pending label', skipPending.skip && skipPending.reason.includes('pending'));
const failedRuns = mergeGate.listFailedChecksOnSha([
{ status: 'completed', conclusion: 'success', name: 'smoke' },
{ status: 'completed', conclusion: 'failure', name: 'test-core (cli)' },
{ status: 'in_progress', conclusion: null, name: 'pending-job' },
]);
assert('listFailedChecksOnSha finds failures only', failedRuns.length === 1);
assert('failed check name', failedRuns[0].name === 'test-core (cli)');
process.exit(failed ? 1 : 0);
-294
View File
@@ -1,294 +0,0 @@
/**
* Post @claude comments with CI failure details for internal PRs.
* @see .github/workflows/ci-failure-claude.yml
*/
const mergeGate = require('./merge-gate.js');
const CI_FIX_LABEL = 'claude-ci-fix-pending';
const COOLDOWN_MS = 12 * 60 * 60 * 1000;
const AUTO_ACTORS = mergeGate.AUTO_ACTORS;
const MAX_FAILURES = 15;
const MAX_JOBS_TO_FETCH = 5;
function shortSha(headSha) {
return (headSha || '').slice(0, 8);
}
function ciFixShaMarker(headSha) {
return `ci failed on head \`${shortSha(headSha)}`.toLowerCase();
}
function isCiFixComment(comment) {
const body = (comment.body || '').toLowerCase();
return body.includes('@claude') && body.includes('ci failed on head');
}
function hasCiFixCommentForSha(comments, headSha) {
const marker = shortSha(headSha).toLowerCase();
return comments.some((c) => {
if (!AUTO_ACTORS.includes(c.user.login)) return false;
if (!isCiFixComment(c)) return false;
return (c.body || '').toLowerCase().includes(marker);
});
}
function hasRecentCiFixComment(comments, headSha) {
const cutoff = Date.now() - COOLDOWN_MS;
const marker = shortSha(headSha).toLowerCase();
return comments.some((c) => {
if (!AUTO_ACTORS.includes(c.user.login)) return false;
if (!isCiFixComment(c)) return false;
const body = (c.body || '').toLowerCase();
if (body.includes(marker)) return true;
return new Date(c.created_at).getTime() > cutoff;
});
}
function shouldSkipCiFix({ comments, headSha, labels, hasFinal, claudeInProgress, failedChecks }) {
if (!failedChecks.length) return { skip: true, reason: 'no failed checks' };
if (labels.includes(CI_FIX_LABEL)) return { skip: true, reason: 'ci fix pending' };
if (!hasFinal) return { skip: true, reason: 'awaiting final claude review trigger' };
if (claudeInProgress) return { skip: true, reason: 'claude in progress' };
if (hasCiFixCommentForSha(comments, headSha)) {
return { skip: true, reason: 'already commented for this sha' };
}
if (hasRecentCiFixComment(comments, headSha)) {
return { skip: true, reason: 'recent ci fix comment cooldown' };
}
return { skip: false };
}
function parsePytestFailures(logText) {
if (!logText) return [];
const lines = logText.split('\n');
const failures = [];
const seen = new Set();
for (let i = lines.length - 1; i >= 0 && failures.length < MAX_FAILURES; i -= 1) {
const line = lines[i].trim();
if (!line) continue;
const pytestMatch = line.match(
/FAILED\s*(?:\([^)]+\))?\s+(tests\/[^\s]+(?:::[^\s-]+)*)\s*-\s*(.+)/i
);
if (pytestMatch) {
const testId = pytestMatch[1];
if (!seen.has(testId)) {
seen.add(testId);
failures.push({ testId, error: pytestMatch[2].trim() });
}
continue;
}
const errorMatch = line.match(/##\[error\](.+)/);
if (errorMatch && /tests\//.test(errorMatch[1])) {
const msg = errorMatch[1].trim();
if (!seen.has(msg)) {
seen.add(msg);
failures.push({ testId: msg, error: msg });
}
}
}
return failures;
}
async function fetchJobFailureSummary(github, owner, repo, jobId, jobName) {
try {
const response = await github.rest.actions.downloadJobLogsForWorkflowRun({
owner,
repo,
job_id: jobId,
});
let logText = typeof response.data === 'string' ? response.data : String(response.data || '');
if (logText.length > 100000) {
logText = logText.slice(-100000);
}
return { jobName, jobId, failures: parsePytestFailures(logText) };
} catch (err) {
return { jobName, jobId, failures: [], error: err.message };
}
}
function mapFailedChecks(runs) {
return runs.map((run) => ({
name: run.name,
id: run.id,
html_url: run.html_url || run.details_url,
workflow: run.app?.slug || run.check_suite?.app?.slug || run.name,
}));
}
function buildCiFixComment({ headSha, failedChecks, failureSummaries }) {
const parts = [
`@claude CI failed on HEAD \`${shortSha(headSha)}\`. Please fix the failures below and push to this branch.`,
'',
'## Failed checks',
];
for (const check of failedChecks) {
parts.push(`- **${check.workflow || check.name}** / \`${check.name}\` — ${check.html_url}`);
}
parts.push('', '## Failures (extracted)');
let idx = 0;
for (const summary of failureSummaries) {
for (const failure of summary.failures) {
idx += 1;
if (idx > MAX_FAILURES) break;
parts.push(`${idx}. \`${failure.testId}\` — \`${failure.error}\``);
parts.push(` - Job: \`${summary.jobName}\``);
}
if (idx >= MAX_FAILURES) break;
}
if (idx === 0) {
parts.push('_(Could not extract pytest details — see job logs above.)_');
}
const exampleTest = failureSummaries.find((s) => s.failures.length)?.failures[0]?.testId;
parts.push(
'',
'## Critical review first',
'Before changing code or tests, decide **which side is wrong**:',
'1. **Legitimate feature change** — the PR intent is correct but implementation or tests need updating. Preserve SDK guarantees; update tests only when behaviour intentionally changed and document why.',
'2. **Regression / bug in this PR** — the failure exposes a real breakage introduced here. Fix the implementation; **do not weaken, skip, or delete tests** just to go green.',
'3. **Pre-existing flake or unrelated failure** — say so explicitly; prefer fixing the root cause over masking it.',
'',
'**SDK guardrails (AGENTS.md):**',
'- Agent-callable tools → PraisonAI-Tools; lifecycle plugins → PraisonAI-Plugins; sandbox backends → PraisonAI-Plugins (`praisonai.sandbox`) — not praisonaiagents/.',
'- Do not disturb core SDK contracts to accommodate a wrapper/feature change.',
'- Tests must continue to guard backward compatibility and hot-path behaviour — passing CI by lowering test standards is not acceptable.',
'- If the feature does not genuinely add SDK value, recommend reverting or narrowing scope instead of patching around failures.',
'',
'## What to do',
'1. State your verdict: **legitimate fix**, **regression fix**, or **needs human review** — and why (1–3 sentences).',
'2. Fix root cause with **minimal changes**; never bloat the Agent class with extra params.',
exampleTest
? `3. Run failing tests locally, e.g. \`pytest ${exampleTest} -q\`, plus any related SDK tests touched by the PR.`
: '3. Run failing tests locally with targeted pytest, plus any related SDK tests touched by the PR.',
'4. Push to this branch and comment: files changed, review verdict, and why tests still protect SDK behaviour.',
);
return parts.join('\n');
}
async function maybeClearCiFixLabel(github, owner, repo, prNumber, labels, headSha, core) {
if (!labels.includes(CI_FIX_LABEL)) return false;
const ciGreen = await mergeGate.allChecksGreenOnSha(github, owner, repo, headSha, core);
if (!ciGreen) return false;
try {
await github.rest.issues.removeLabel({
owner,
repo,
issue_number: prNumber,
name: CI_FIX_LABEL,
});
core?.info?.(`Removed ${CI_FIX_LABEL} from PR #${prNumber}`);
} catch (err) {
if (err.status !== 404) throw err;
}
return true;
}
async function maybeTriggerCiFixClaude(github, owner, repo, prNumber, core, opts = {}) {
const baseRepo = `${owner}/${repo}`;
const ctx = await mergeGate.loadPrContext(github, owner, repo, prNumber);
const pr = ctx.pr;
if (pr.state !== 'open') return { skipped: true, reason: 'not open' };
if (pr.draft) return { skipped: true, reason: 'draft' };
const headRepo = pr.head.repo?.full_name;
if (headRepo && headRepo !== baseRepo && !pr.maintainer_can_modify) {
return { skipped: true, reason: 'fork without maintainer edits' };
}
const headSha = pr.head.sha;
const labels = ctx.labels;
if (await maybeClearCiFixLabel(github, owner, repo, prNumber, labels, headSha, core)) {
return { skipped: true, reason: 'ci green, label cleared' };
}
const ciGreen = await mergeGate.allChecksGreenOnSha(github, owner, repo, headSha, core);
if (ciGreen) return { skipped: true, reason: 'ci green' };
const runs = await mergeGate.listChecksOnSha(github, owner, repo, headSha);
const failedRuns = mergeGate.listFailedChecksOnSha(runs);
if (failedRuns.length === 0) {
return { skipped: true, reason: 'no failed checks yet (may be pending)' };
}
const hasFinal = mergeGate.hasFinalClaudeReviewTrigger(ctx.comments);
const claudeInProgress = await mergeGate.hasInProgressClaudeAssistant(
github, owner, repo, prNumber
);
const skip = shouldSkipCiFix({
comments: ctx.comments,
headSha,
labels,
hasFinal,
claudeInProgress,
failedChecks: failedRuns,
});
if (skip.skip) return { skipped: true, reason: skip.reason };
const failedChecks = mapFailedChecks(failedRuns);
const failureSummaries = [];
for (const check of failedChecks.slice(0, MAX_JOBS_TO_FETCH)) {
failureSummaries.push(
await fetchJobFailureSummary(github, owner, repo, check.id, check.name)
);
}
const body = buildCiFixComment({ headSha, failedChecks, failureSummaries });
await github.rest.issues.addLabels({
owner,
repo,
issue_number: prNumber,
labels: [CI_FIX_LABEL],
});
await github.rest.issues.createComment({
owner,
repo,
issue_number: prNumber,
body,
});
core?.info?.(`Posted CI fix @claude on PR #${prNumber} (${shortSha(headSha)})`);
return { triggered: true, headSha: shortSha(headSha) };
}
async function processWorkflowRunFailure(github, owner, repo, workflowRun, core) {
if (workflowRun.conclusion !== 'failure') {
return { skipped: true, reason: `conclusion=${workflowRun.conclusion}` };
}
const allowed = ['Core Tests', 'Optimized Test Suite'];
if (!allowed.includes(workflowRun.name)) {
return { skipped: true, reason: `workflow ${workflowRun.name}` };
}
const prNumber = await mergeGate.resolvePrNumberFromWorkflowRun(
github, owner, repo, workflowRun
);
if (!prNumber) return { skipped: true, reason: 'no linked PR' };
return maybeTriggerCiFixClaude(github, owner, repo, prNumber, core);
}
module.exports = {
CI_FIX_LABEL,
COOLDOWN_MS,
ciFixShaMarker,
isCiFixComment,
hasCiFixCommentForSha,
hasRecentCiFixComment,
shouldSkipCiFix,
parsePytestFailures,
fetchJobFailureSummary,
buildCiFixComment,
maybeClearCiFixLabel,
maybeTriggerCiFixClaude,
processWorkflowRunFailure,
};
-290
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@@ -1,290 +0,0 @@
#!/usr/bin/env node
/**
* Local self-test for merge-gate.js heuristics (no GitHub API).
* Run: node .github/scripts/merge-gate-selftest.js
*/
const mg = require('./merge-gate.js');
let failed = 0;
function assert(name, cond) {
if (!cond) {
console.error('FAIL:', name);
failed++;
} else {
console.log('ok:', name);
}
}
// Stale FINAL: push after FINAL, no @claude since head
const finals = [
{ user: { login: 'github-actions[bot]' }, body: '@claude FINAL architecture reviewer', created_at: '2026-06-12T08:00:00Z' },
];
assert('stale when head after final', mg.isStaleFinalAfterPush(finals, '2026-06-12T09:00:00Z'));
const withRecovery = [
...finals,
{ user: { login: 'github-actions[bot]' }, body: '@claude FINAL architecture reviewer', created_at: '2026-06-12T09:30:00Z' },
];
assert('not stale when @claude after head', !mg.isStaleFinalAfterPush(withRecovery, '2026-06-12T09:00:00Z'));
const withClaudeReply = [
...finals,
{
user: { login: 'praisonai-triage-agent[bot]' },
body: "**Claude finished @MervinPraison's task** —— [View job](https://github.com/)",
created_at: '2026-06-12T08:30:00Z',
},
];
assert('not stale when Claude replied after FINAL', !mg.isStaleFinalAfterPush(withClaudeReply, '2026-06-12T09:00:00Z'));
assert('claude final reply detected', mg.isClaudeFinalReplyComment(withClaudeReply[1]));
assert('cancelled detect-and-trigger does not block', mg.OPTIONAL_CANCELLED_CHECKS.has('detect-and-trigger'));
const coreGreenRuns = [
{ name: 'test-core', status: 'completed', conclusion: 'success' },
{ name: 'test-core (cli)', status: 'completed', conclusion: 'success' },
{ name: 'smoke', status: 'completed', conclusion: 'cancelled' },
{ name: 'test-windows', status: 'completed', conclusion: 'cancelled' },
];
assert('core green allows cancelled smoke', mg.isAcceptableCheckConclusion(
{ name: 'smoke', status: 'completed', conclusion: 'cancelled' },
coreGreenRuns
));
assert('core green allows cancelled test-windows', mg.isAcceptableCheckConclusion(
{ name: 'test-windows', status: 'completed', conclusion: 'cancelled' },
coreGreenRuns
));
assert('cancelled smoke blocks when core missing', !mg.isAcceptableCheckConclusion(
{ name: 'smoke', status: 'completed', conclusion: 'cancelled' },
[{ name: 'smoke', status: 'completed', conclusion: 'cancelled' }]
));
assert('cancelled smoke blocks when core failed', !mg.isAcceptableCheckConclusion(
{ name: 'smoke', status: 'completed', conclusion: 'cancelled' },
[
{ name: 'test-core', status: 'completed', conclusion: 'failure' },
{ name: 'smoke', status: 'completed', conclusion: 'cancelled' },
]
));
assert('bestRunsByName prefers success over cancelled', (() => {
const best = mg.bestRunsByName([
{ name: 'smoke', conclusion: 'cancelled' },
{ name: 'smoke', conclusion: 'success' },
]);
return best.length === 1 && best[0].conclusion === 'success';
})());
assert('bestRunsByName prefers pending over completed cancelled', (() => {
const best = mg.bestRunsByName([
{ name: 'smoke', status: 'completed', conclusion: 'cancelled' },
{ name: 'smoke', status: 'in_progress', conclusion: null },
]);
return best.length === 1 && best[0].status === 'in_progress';
})());
assert('bestRunsByName keeps pending regardless of order', (() => {
const best = mg.bestRunsByName([
{ name: 'smoke', status: 'in_progress', conclusion: null },
{ name: 'smoke', status: 'completed', conclusion: 'success' },
]);
return best.length === 1 && best[0].status === 'in_progress';
})());
assert('allChecksGreenOnSha style: pending re-run blocks despite core green', (() => {
const runs = mg.bestRunsByName([
{ name: 'test-core', status: 'completed', conclusion: 'success' },
{ name: 'smoke', status: 'completed', conclusion: 'cancelled' },
{ name: 'smoke', status: 'queued', conclusion: null },
]);
const smoke = runs.find((r) => r.name === 'smoke');
return smoke.status !== 'completed';
})());
// Stale-FINAL recovery guards (PR #2560 push loop)
const nowMs = Date.now();
const iso = (ms) => new Date(ms).toISOString();
const firstFinal = {
user: { login: 'MervinPraison' },
body: '@claude You are the FINAL architecture reviewer.',
created_at: iso(nowMs - 20 * 60 * 1000),
};
const pushSoonAfter = mg.shouldSkipStaleFinalRecovery(
[firstFinal],
iso(nowMs - 16 * 60 * 1000)
);
assert('debounce push soon after FINAL', pushSoonAfter.skip && pushSoonAfter.reason.includes('soon after'));
const secondFinal = {
user: { login: 'MervinPraison' },
body: '@claude You are the FINAL architecture reviewer.',
created_at: iso(nowMs - 20 * 60 * 1000),
};
const capped = mg.shouldSkipStaleFinalRecovery(
[firstFinal, secondFinal],
iso(nowMs - 2 * 60 * 1000)
);
assert('hourly cap blocks third FINAL in window', capped.skip && capped.reason.includes('capped'));
const botPush = mg.shouldSkipStaleFinalRecovery(
[firstFinal],
iso(nowMs - 16 * 60 * 1000),
'praisonai-triage-agent[bot]'
);
assert('skip when automation pushed head', botPush.skip && botPush.reason.includes('automation'));
assert('claude automation login', mg.isClaudeAutomationLogin('praisonai-triage-agent[bot]'));
// Bot CHANGES_REQUESTED then APPROVE
const reviews = [
{ user: { login: 'coderabbit[bot]', type: 'Bot' }, state: 'CHANGES_REQUESTED', submitted_at: '2026-06-12T08:00:00Z' },
{ user: { login: 'coderabbit[bot]', type: 'Bot' }, state: 'APPROVED', submitted_at: '2026-06-12T09:00:00Z' },
];
assert('bot approve clears CR', !mg.hasAnyChangesRequested(reviews));
assert('human CR blocks', mg.hasAnyChangesRequested([
{ user: { login: 'MervinPraison', type: 'User' }, state: 'CHANGES_REQUESTED', submitted_at: '2026-06-12T09:00:00Z' },
]));
// Verdict after HEAD
const verdictComments = [
{ body: 'MERGE_GATE_VERDICT: APPROVE', created_at: '2026-06-12T08:00:00Z' },
];
assert('verdict before head rejected', mg.findMergeGateVerdict(verdictComments, null, '2026-06-12T09:00:00Z') === null);
assert('verdict after head accepted', mg.findMergeGateVerdict(
[{ body: 'MERGE_GATE_VERDICT: APPROVE', created_at: '2026-06-12T10:00:00Z' }],
null,
'2026-06-12T09:00:00Z'
) === 'APPROVE');
const fallbackApprove = [
{
body: 'MERGE_GATE_VERDICT: APPROVE\n\nAutomated fallback — Claude assess did not post a verdict comment.',
created_at: '2026-06-12T10:00:00Z',
},
];
assert(
'automated fallback APPROVE ignored when Opus required',
mg.findMergeGateVerdict(fallbackApprove, null, '2026-06-12T09:00:00Z', { excludeAutomatedFallback: true }) === null
);
assert(
'automated fallback APPROVE still visible without Opus-only filter',
mg.findMergeGateVerdict(fallbackApprove, null, '2026-06-12T09:00:00Z') === 'APPROVE'
);
const fallbackBlockNewFormat = [
{
body: 'MERGE_GATE_VERDICT: BLOCK\n\nAutomated fallback — Opus merge gate assessment did not complete.',
created_at: '2026-06-12T10:00:00Z',
},
];
assert(
'new-format fallback BLOCK ignored when Opus required',
mg.findMergeGateVerdict(fallbackBlockNewFormat, null, '2026-06-12T09:00:00Z', { excludeAutomatedFallback: true }) === null
);
assert(
'new-format fallback BLOCK detected by marker helper',
mg.isAutomatedFallbackVerdict(fallbackBlockNewFormat[0].body)
);
assert(
'findMergeGateVerdict null-safe with explicit null options',
mg.findMergeGateVerdict(fallbackApprove, null, '2026-06-12T09:00:00Z', null) === 'APPROVE'
);
const noise = [{ user: { login: 'MervinPraison' }, body: '**Merge gate scan** — wait for `@claude`', created_at: new Date().toISOString() }];
assert('diagnostic comment not a trigger', !mg.hasRecentClaudeTrigger(noise, 35));
// Cooldown skip requires an actual verdict on HEAD, not just a FINAL trigger comment
const recentFinalOnHead = [
{
user: { login: 'MervinPraison' },
body: '@claude You are the FINAL architecture reviewer.',
created_at: '2026-06-27T10:00:00Z',
},
];
assert(
'final trigger alone does not count as verdict on head',
mg.findMergeGateVerdict(recentFinalOnHead, null, '2026-06-27T09:55:00Z') === null
);
const recentVerdictOnHead = [
...recentFinalOnHead,
{
user: { login: 'github-actions[bot]' },
body: 'MERGE_GATE_VERDICT: APPROVE',
created_at: '2026-06-27T10:05:00Z',
},
];
assert(
'verdict on head skips cooldown gate',
mg.findMergeGateVerdict(recentVerdictOnHead, null, '2026-06-27T09:55:00Z') === 'APPROVE'
);
// Sensitive + secrets
assert('workflow path sensitive', mg.sensitivePathReasons([{ filename: '.github/workflows/foo.yml' }]).length === 1);
assert('ci-only label exempts workflows', mg.sensitivePathReasons(
[{ filename: '.github/workflows/foo.yml' }],
[mg.WORKFLOW_ONLY_LABEL]
).length === 0);
assert('ci-only label not exempt mixed changes', mg.sensitivePathReasons(
[{ filename: '.github/workflows/foo.yml' }, { filename: 'src/foo.py' }],
[mg.WORKFLOW_ONLY_LABEL]
).length === 1);
assert('secret in patch', mg.secretScanReasons([{ filename: 'x.py', patch: '+key = "ghp_abcdefghijklmnopqrstuvwxyz1234567890"' }]).length === 1);
// Claude run scoping — other PR branches must not block
assert('other branch claude does not block', !mg.hasBlockingClaudeRunForPr(
[{ event: 'issue_comment', head_branch: 'other-branch' }],
'my-branch'
));
assert('same branch claude blocks', mg.hasBlockingClaudeRunForPr(
[{ event: 'issue_comment', head_branch: 'my-branch' }],
'my-branch'
));
assert('issues event never blocks', !mg.hasBlockingClaudeRunForPr(
[{ event: 'issues', head_branch: 'my-branch' }],
'my-branch'
));
// Conflict rebase clears after bot completion + FINAL on HEAD (within 12h cooldown)
const conflictNowMs = Date.now();
const conflictIso = (offsetMs) => new Date(conflictNowMs + offsetMs).toISOString();
const conflictTrigger = {
user: { login: 'MervinPraison' },
body: '@claude this PR has merge conflicts with main. Please rebase',
created_at: conflictIso(-30 * 60 * 1000),
};
const rebaseDone = {
user: { login: 'praisonai-triage-agent[bot]' },
body: 'Rebase complete — PR #2308 onto latest main',
created_at: conflictIso(-29 * 60 * 1000),
};
const finalAfterRebase = {
user: { login: 'MervinPraison' },
body: '@claude You are the FINAL architecture reviewer.',
created_at: conflictIso(-20 * 60 * 1000),
};
const headAfterRebase = conflictIso(-21 * 60 * 1000);
const rebaseComments = [conflictTrigger, rebaseDone, finalAfterRebase];
assert('conflict blocks before rebase done', mg.hasRecentConflictComment([conflictTrigger], headAfterRebase));
assert('conflict clears after rebase + FINAL on HEAD', !mg.hasRecentConflictComment(rebaseComments, headAfterRebase));
assert('conflict still blocks without FINAL on HEAD', mg.hasRecentConflictComment(
[conflictTrigger, rebaseDone],
headAfterRebase
));
// Tests heuristic
assert('sdk without tests', mg.missingTestsReason([{ filename: 'src/praisonai-agents/a/b.py', additions: 3 }]) !== null);
assert('sdk with tests ok', mg.missingTestsReason([
{ filename: 'src/praisonai-agents/a/b.py', additions: 3 },
{ filename: 'src/praisonai-agents/tests/test_x.py', additions: 10 },
]) === null);
// PR size
assert('large PR blocked', mg.prSizeReasons([{ additions: 900 }]).length > 0);
assert('internal PR link accepted', mg.isInternalPullRequestLink(
{ base: { repo: { full_name: 'MervinPraison/PraisonAI' } } },
'MervinPraison',
'PraisonAI'
));
assert('fork sync PR link rejected', !mg.isInternalPullRequestLink(
{ number: 21, base: { repo: { full_name: 'Milkmange/PraisonAI' } } },
'MervinPraison',
'PraisonAI'
));
process.exit(failed ? 1 : 0);
File diff suppressed because it is too large. Load diff
@@ -1,76 +0,0 @@
#!/usr/bin/env node
/**
* Run: node .github/scripts/pipeline-status-selftest.js
*/
const ps = require('./pipeline-status.js');
const mg = require('./merge-gate.js');
let failed = 0;
function assert(name, cond) {
if (!cond) {
console.error('FAIL:', name);
failed++;
} else {
console.log('ok:', name);
}
}
const kickComments = [
{ user: { login: 'MervinPraison' }, body: '@coderabbitai review' },
{ user: { login: 'MervinPraison' }, body: '/review' },
];
const finalComment = {
user: { login: 'MervinPraison' },
body: '@claude You are the FINAL architecture reviewer.',
created_at: '2026-06-26T10:00:00Z',
};
assert(
'reviews pending when not kicked',
ps.deriveStage([], { ready: false, reasons: ['no FINAL Claude review trigger'] })
=== 'pipeline/reviews-pending'
);
assert(
'final pending after kick',
ps.deriveStage(kickComments, { ready: false, reasons: ['no FINAL Claude review trigger'] })
=== 'pipeline/final-claude-pending'
);
assert(
'awaiting merge gate after final',
ps.deriveStage(
[...kickComments, finalComment],
{ ready: false, reasons: ['recent @claude within 35min'] }
) === 'pipeline/awaiting-merge-gate'
);
assert(
'merge ready',
ps.deriveStage([...kickComments, finalComment], { ready: true, reasons: [] })
=== 'pipeline/merge-ready'
);
const blockers = ps.deriveBlockerLabels({
ready: false,
reasons: ['CI not green on HEAD', 'SDK code added without test file changes — requires manual review'],
});
assert('maps ci blocker', blockers.includes('pipeline/blocked:ci'));
assert('maps manual blocker', blockers.includes('pipeline/blocked:manual-review'));
assert(
'internal link matches upstream base',
mg.isInternalPullRequestLink(
{ base: { repo: { full_name: 'MervinPraison/PraisonAI' } } },
'MervinPraison',
'PraisonAI'
)
);
assert(
'fork sync link rejected',
!mg.isInternalPullRequestLink(
{ number: 21, base: { repo: { full_name: 'Milkmange/PraisonAI' } } },
'MervinPraison',
'PraisonAI'
)
);
process.exit(failed ? 1 : 0);
-258
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@@ -1,258 +0,0 @@
/**
* Sync pipeline stage/blocker labels on open PRs.
* @see .github/workflows/pipeline-status-sync.yml
*/
const mergeGate = require('./merge-gate.js');
const chain = require('./bot-pr-review-chain.js');
const ciFix = require('./ci-failure-claude.js');
const PIPELINE_PREFIX = 'pipeline/';
const STAGE_LABELS = [
'pipeline/reviews-pending',
'pipeline/final-claude-pending',
'pipeline/awaiting-merge-gate',
'pipeline/merge-ready',
'pipeline/merged',
];
const BLOCKER_LABELS = [
'pipeline/blocked:ci',
'pipeline/blocked:conflict',
'pipeline/blocked:manual-review',
'pipeline/blocked:cooldown',
'pipeline/blocked:stale-final',
'pipeline/blocked:no-final',
];
const ALL_PIPELINE_LABELS = [...STAGE_LABELS, ...BLOCKER_LABELS];
const LABEL_SPECS = [
{ name: 'pipeline/reviews-pending', color: 'fbca04', description: 'Waiting for CodeRabbit/Qodo/Copilot reviews' },
{ name: 'pipeline/final-claude-pending', color: 'd4c5f9', description: 'Reviews done; waiting for FINAL @claude' },
{ name: 'pipeline/awaiting-merge-gate', color: 'c5def5', description: 'FINAL done; waiting for merge gate / CI' },
{ name: 'pipeline/merge-ready', color: '0e8a16', description: 'Eligible for merge gate auto-merge' },
{ name: 'pipeline/merged', color: '6f42c1', description: 'Merged via pipeline' },
{ name: 'pipeline/blocked:ci', color: 'd93f0b', description: 'Blocked: CI not green on HEAD' },
{ name: 'pipeline/blocked:conflict', color: 'b60205', description: 'Blocked: merge conflict or rebase pending' },
{ name: 'pipeline/blocked:manual-review', color: 'e99695', description: 'Blocked: requires manual review' },
{ name: 'pipeline/blocked:cooldown', color: 'fef2c0', description: 'Blocked: post-push or @claude cooldown' },
{ name: 'pipeline/blocked:stale-final', color: 'f9d0c4', description: 'Blocked: FINAL stale after new commits' },
{ name: 'pipeline/blocked:no-final', color: 'ededed', description: 'Blocked: no FINAL @claude trigger yet' },
];
function deriveStage(comments, evalResult) {
if (evalResult.ready) return 'pipeline/merge-ready';
if (!chain.chainKickPosted(comments)) return 'pipeline/reviews-pending';
if (!mergeGate.hasFinalClaudeReviewTrigger(comments)) return 'pipeline/final-claude-pending';
return 'pipeline/awaiting-merge-gate';
}
function reasonToBlockerLabel(reason) {
const r = (reason || '').toLowerCase();
if (r.includes('ci not green') || r.includes('sdk code changed but no ci')) return 'pipeline/blocked:ci';
if (
r.includes('conflict') ||
r.includes('mergestate=dirty') ||
r.includes('not mergeable')
) return 'pipeline/blocked:conflict';
if (
r.includes('manual') ||
r.includes('requires manual') ||
r.includes('sensitive path') ||
r.includes('no-auto-merge') ||
r.includes('manual-only label') ||
r.includes('without test') ||
r.includes('files changed') ||
r.includes('possible secret') ||
r.includes('agent.py')
) return 'pipeline/blocked:manual-review';
if (r.includes('recent @claude') || r.includes('post-push buffer')) return 'pipeline/blocked:cooldown';
if (r.includes('stale final')) return 'pipeline/blocked:stale-final';
if (r.includes('no final claude')) return 'pipeline/blocked:no-final';
if (r.includes('final claude not complete')) return 'pipeline/blocked:stale-final';
if (r.includes('claude.yml in progress') || r.includes('claude-merge-gate-active')) {
return null;
}
return null;
}
function deriveBlockerLabels(evalResult) {
if (evalResult.ready) return [];
const labels = new Set();
for (const reason of evalResult.reasons || []) {
const mapped = reasonToBlockerLabel(reason);
if (mapped && mapped.startsWith('pipeline/blocked:')) labels.add(mapped);
}
return [...labels];
}
function computePipelineLabels(comments, evalResult) {
const stage = deriveStage(comments, evalResult);
const blockers = stage === 'pipeline/merge-ready' ? [] : deriveBlockerLabels(evalResult);
return { stage, blockers, all: [stage, ...blockers] };
}
async function ensurePipelineLabels(github, owner, repo, core) {
let existing;
if (typeof github.paginate === 'function') {
existing = await github.paginate(github.rest.issues.listLabelsForRepo, {
owner,
repo,
per_page: 100,
});
} else {
({ data: existing } = await github.rest.issues.listLabelsForRepo({
owner,
repo,
per_page: 100,
}));
}
const names = new Set(existing.map((l) => l.name));
for (const spec of LABEL_SPECS) {
if (names.has(spec.name)) continue;
try {
await github.rest.issues.createLabel({
owner,
repo,
name: spec.name,
color: spec.color,
description: spec.description,
});
core?.info?.(`Created label ${spec.name}`);
} catch (err) {
if (err.status !== 422) throw err;
core?.info?.(`Label ${spec.name} already exists`);
}
}
}
async function syncPipelineLabels(github, owner, repo, prNumber, core) {
const ctx = await mergeGate.loadPrContext(github, owner, repo, prNumber);
if (ctx.pr.state !== 'open') return { synced: false, reason: 'not_open' };
const evalResult = await mergeGate.evaluatePipelineQuiescent(
github, owner, repo, prNumber, core
);
const { stage, blockers, all } = computePipelineLabels(ctx.comments, evalResult);
const current = ctx.labels.filter((l) => l.startsWith(PIPELINE_PREFIX));
const desired = new Set(all);
const toRemove = current.filter((l) => !desired.has(l) && l !== 'pipeline/merged');
const toAdd = all.filter((l) => !current.includes(l));
for (const name of toRemove) {
try {
await github.rest.issues.removeLabel({ owner, repo, issue_number: prNumber, name });
} catch (err) {
if (err.status !== 404) throw err;
}
}
if (toAdd.length) {
await github.rest.issues.addLabels({
owner,
repo,
issue_number: prNumber,
labels: toAdd,
});
}
core?.info?.(`PR #${prNumber}: stage=${stage} blockers=[${blockers.join(', ')}]`);
const ciNotGreen = (evalResult.reasons || []).some((r) =>
r.toLowerCase().includes('ci not green')
);
if (ciNotGreen || blockers.includes('pipeline/blocked:ci')) {
await ciFix.maybeTriggerCiFixClaude(github, owner, repo, prNumber, core);
} else {
await ciFix.maybeClearCiFixLabel(
github, owner, repo, prNumber, ctx.labels, ctx.headSha, core
);
}
return {
synced: true,
stage,
blockers,
ready: evalResult.ready,
reasons: evalResult.reasons,
labels: ctx.labels,
createdAt: new Date(ctx.pr.created_at).getTime(),
};
}
async function dispatchMergeGateForOldestReady(github, owner, repo, readyCandidates, core) {
if (!readyCandidates.length) return 0;
readyCandidates.sort((a, b) => a.createdAt - b.createdAt);
for (const cand of readyCandidates) {
if ((cand.labels || []).includes('claude-merge-gate-active')) {
core?.info?.(`Skip dispatch PR #${cand.prNumber}: merge gate already active`);
continue;
}
await github.rest.repos.createDispatchEvent({
owner,
repo,
event_type: 'claude-merge-gate',
client_payload: { pr_number: cand.prNumber },
});
core?.info?.(`Dispatched merge gate for ready PR #${cand.prNumber}`);
return cand.prNumber;
}
return 0;
}
async function syncOpenPullRequests(github, owner, repo, options, core) {
const { maxPrs = 20, dispatchMergeGate = true } = options || {};
await ensurePipelineLabels(github, owner, repo, core);
let prs;
if (maxPrs <= 100) {
({ data: prs } = await github.rest.pulls.list({
owner,
repo,
state: 'open',
per_page: 100,
}));
} else {
prs = await github.paginate(github.rest.pulls.list, {
owner,
repo,
state: 'open',
per_page: 100,
});
}
let synced = 0;
const readyCandidates = [];
for (const pr of prs) {
if (synced >= maxPrs) break;
if (pr.draft) continue;
if (pr.head?.repo?.full_name && pr.head.repo.full_name !== `${owner}/${repo}`) continue;
const result = await syncPipelineLabels(github, owner, repo, pr.number, core);
if (result.ready) {
readyCandidates.push({
prNumber: pr.number,
createdAt: result.createdAt || new Date(pr.created_at).getTime(),
labels: result.labels || [],
});
}
synced += 1;
}
let dispatched = 0;
if (dispatchMergeGate && readyCandidates.length) {
dispatched = await dispatchMergeGateForOldestReady(
github, owner, repo, readyCandidates, core
);
}
core?.info?.(`Pipeline label sync complete (${synced} PR(s), dispatched=${dispatched || 'none'})`);
return synced;
}
module.exports = {
STAGE_LABELS,
BLOCKER_LABELS,
ALL_PIPELINE_LABELS,
deriveStage,
deriveBlockerLabels,
computePipelineLabels,
ensurePipelineLabels,
syncPipelineLabels,
syncOpenPullRequests,
dispatchMergeGateForOldestReady,
};
-111
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@@ -1,111 +0,0 @@
#!/usr/bin/env node
const chain = require('./pr-review-chain.js');
let failed = 0;
function assert(name, cond) {
if (!cond) {
console.error('FAIL:', name);
failed++;
} else {
console.log('ok:', name);
}
}
const coderabbit = {
user: { login: 'coderabbitai[bot]' },
body: '<!-- summarize by coderabbit.ai --> summary',
created_at: '2026-07-02T07:16:00Z',
};
const greptile = {
user: { login: 'greptile-apps[bot]' },
body: '<h3>Greptile Summary</h3><p>Looks good</p>',
created_at: '2026-07-02T07:19:00Z',
};
const copilotKick = {
user: { login: 'MervinPraison' },
body: '@copilot Do a thorough review',
created_at: '2026-07-02T07:20:00Z',
};
const copilotReply = {
user: { login: 'copilot-swe-agent' },
body: 'Copilot review here',
created_at: '2026-07-02T07:22:00Z',
};
assert('prior not ready without greptile', !chain.priorReviewersReady([coderabbit]).ready);
assert('prior ready with coderabbit + greptile', chain.priorReviewersReady([coderabbit, greptile]).ready);
assert('copilot not ready before trigger', !chain.copilotReviewReady([coderabbit, greptile]).ready);
assert(
'copilot ready after reply',
chain.copilotReviewReady([coderabbit, greptile, copilotKick, copilotReply]).ready
);
assert(
'claude not ready before copilot',
!chain.claudeFinalReady([coderabbit, greptile]).ready
);
assert(
'claude ready after full chain',
chain.claudeFinalReady([coderabbit, greptile, copilotKick, copilotReply]).ready
);
assert(
'claude timeout fallback when copilot triggered but silent',
chain.claudeFinalReady([coderabbit, greptile, copilotKick], [], { allowCopilotTimeout: true }).ready
);
assert(
'no timeout fallback without copilot trigger',
!chain.claudeFinalReady([coderabbit, greptile], [], { allowCopilotTimeout: true }).ready
);
assert(
'skipCopilot proceeds after prior reviewers',
chain.claudeFinalReady([coderabbit, greptile], [], { skipCopilot: true }).ready
);
const prev = process.env.REVIEW_CHAIN_SKIP_COPILOT;
process.env.REVIEW_CHAIN_SKIP_COPILOT = '1';
assert(
'REVIEW_CHAIN_SKIP_COPILOT env skips copilot',
chain.claudeFinalReady([coderabbit, greptile], [], {}).ready
);
process.env.REVIEW_CHAIN_SKIP_COPILOT = prev;
const geminiReview = {
user: { login: 'gemini-code-assist[bot]' },
body: '## Code Review\n\nThis pull request decomposes the large main.py file',
submitted_at: '2026-07-03T08:08:00Z',
};
assert(
'gemini pull review counts as prior reviewer',
chain.hasGeminiReview([], [geminiReview])
);
assert(
'prior ready with gemini review only (no gemini comment)',
chain.priorReviewersReady([coderabbit, greptile], [geminiReview], { optionalWaitMs: 0 }).ready
);
const oldPr = new Date(Date.now() - 31 * 60 * 1000).toISOString();
assert(
'prior not ready without coderabbit before timeout',
!chain.priorReviewersReady([greptile], [], { prCreatedAt: new Date().toISOString(), requiredWaitMs: 30 * 60 * 1000 }).ready
);
assert(
'prior timeout when coderabbit silent after 30m',
chain.priorReviewersReady([greptile], [], { prCreatedAt: oldPr, requiredWaitMs: 30 * 60 * 1000 }).ready
);
assert(
'claude FINAL timeout when required reviewer silent and no prior FINAL',
chain.claudeFinalReady([greptile], [], { prCreatedAt: oldPr, requiredWaitMs: 30 * 60 * 1000 }).ready
);
assert(
'claude FINAL timeout auto-skips copilot without explicit skipCopilot',
chain.claudeFinalReady([greptile], [], { prCreatedAt: oldPr, requiredWaitMs: 30 * 60 * 1000 }).copilotSkipped
);
const finalClaude = {
user: { login: 'github-actions[bot]' },
body: '@claude You are the FINAL architecture reviewer for this PR.',
created_at: '2026-07-02T07:25:00Z',
};
assert(
'claude FINAL not re-posted when already triggered',
!chain.claudeFinalReady([greptile, finalClaude], [], { prCreatedAt: oldPr, requiredWaitMs: 0 }).ready
);
process.exit(failed ? 1 : 0);
-322
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@@ -1,322 +0,0 @@
/**
* PR review pipeline: CodeRabbit / Greptile (+ optional Qodo/Gemini) → Claude (FINAL).
* Copilot step optional — set REVIEW_CHAIN_SKIP_COPILOT=1 or skipCopilot: true to bypass.
* @see .github/workflows/auto-pr-comment.yml
*/
function isSkipCopilot(options = {}) {
if (options.skipCopilot === true) return true;
if (options.skipCopilot === false) return false;
return process.env.REVIEW_CHAIN_SKIP_COPILOT === '1';
}
const COPILOT_TRIGGER_LOGINS = new Set(['MervinPraison', 'github-actions[bot]']);
const CLAUDE_TRIGGER_LOGINS = new Set(['MervinPraison', 'github-actions[bot]']);
const REQUIRED_PRIOR = ['coderabbit', 'greptile'];
const OPTIONAL_PRIOR = ['qodo', 'gemini'];
const OPTIONAL_PRIOR_WAIT_MS = 20 * 60 * 1000;
const REQUIRED_PRIOR_WAIT_MS = 30 * 60 * 1000;
function loginOf(item) {
return (item?.user?.login || '').toLowerCase();
}
function bodyOf(item) {
return item?.body || '';
}
function hasCoderabbitSummary(comments) {
return comments.some(
(c) =>
loginOf(c).includes('coderabbit') &&
bodyOf(c).toLowerCase().includes('summarize by coderabbit')
);
}
function hasGreptileReview(comments) {
return comments.some((c) => {
if (!loginOf(c).includes('greptile')) return false;
const body = bodyOf(c);
return body.includes('Greptile Summary') || body.includes('<h3>Greptile Summary</h3>') || body.length > 150;
});
}
function hasQodoReview(comments, reviews = []) {
if (comments.some((c) => loginOf(c).includes('qodo'))) return true;
return reviews.some((r) => loginOf(r).includes('qodo'));
}
function hasGeminiReview(comments, reviews = []) {
if (reviews.some((r) => loginOf(r).includes('gemini'))) return true;
return comments.some((c) => {
if (loginOf(c).includes('gemini')) return true;
const body = bodyOf(c);
return (
body.includes('Review completed by Gemini CLI') ||
body.includes('The fix is ready for review. Please test')
);
});
}
const PRIOR_CHECKS = {
coderabbit: (comments) => hasCoderabbitSummary(comments),
greptile: (comments) => hasGreptileReview(comments),
qodo: (comments, reviews) => hasQodoReview(comments, reviews),
gemini: (comments, reviews) => hasGeminiReview(comments, reviews),
};
function priorReviewerStatus(comments, reviews = []) {
const status = {};
for (const [id, check] of Object.entries(PRIOR_CHECKS)) {
status[id] = check(comments, reviews);
}
return status;
}
function priorReviewersReady(comments, reviews = [], options = {}) {
const waitMs = options.optionalWaitMs ?? OPTIONAL_PRIOR_WAIT_MS;
const requiredWaitMs = options.requiredWaitMs ?? REQUIRED_PRIOR_WAIT_MS;
const prCreatedAt = options.prCreatedAt || null;
const status = priorReviewerStatus(comments, reviews);
const missingRequired = REQUIRED_PRIOR.filter((id) => !status[id]);
if (missingRequired.length) {
if (prCreatedAt) {
const age = Date.now() - new Date(prCreatedAt).getTime();
if (age >= requiredWaitMs) {
return {
ready: true,
reason: `required reviewer timeout (${missingRequired.join(', ')} silent after ${Math.round(requiredWaitMs / 60000)}m)`,
status,
requiredTimeout: true,
};
}
}
return { ready: false, reason: `waiting for ${missingRequired.join(', ')}`, status };
}
const missingOptional = OPTIONAL_PRIOR.filter((id) => !status[id]);
if (missingOptional.length && prCreatedAt) {
const age = Date.now() - new Date(prCreatedAt).getTime();
if (age < waitMs) {
return {
ready: false,
reason: `waiting for optional ${missingOptional.join(', ')} (${Math.round((waitMs - age) / 60000)}m left)`,
status,
};
}
}
return { ready: true, reason: '', status };
}
function copilotTriggerComment(comments) {
return comments.find(
(c) =>
bodyOf(c).includes('@copilot') &&
COPILOT_TRIGGER_LOGINS.has(c.user?.login) &&
!bodyOf(c).toLowerCase().includes('@claude')
);
}
function copilotTriggered(comments) {
return Boolean(copilotTriggerComment(comments));
}
function copilotReviewReady(comments, reviews = []) {
const trigger = copilotTriggerComment(comments);
if (!trigger) {
return { ready: false, reason: 'copilot not triggered yet' };
}
const triggerTime = new Date(trigger.created_at).getTime();
const copilotComment = comments.some((c) => {
if (c === trigger) return false;
if (new Date(c.created_at).getTime() < triggerTime) return false;
const login = loginOf(c);
return (
login.includes('copilot') ||
c.user?.login === 'Copilot' ||
c.user?.login === 'copilot-swe-agent'
);
});
const copilotReview = reviews.some((r) => {
if (new Date(r.submitted_at).getTime() < triggerTime) return false;
return loginOf(r).includes('copilot');
});
if (copilotComment || copilotReview) {
return { ready: true, reason: '' };
}
return { ready: false, reason: 'awaiting copilot review' };
}
function isFinalClaudeTriggerComment(c) {
const body = bodyOf(c).toLowerCase();
if (!CLAUDE_TRIGGER_LOGINS.has(c.user?.login)) return false;
if (!body.includes('@claude')) return false;
if (body.includes('merge conflict')) return false;
return body.includes('final architecture reviewer') || body.includes('lead engineer');
}
function claudeFinalAlreadyTriggered(comments) {
return comments.some(isFinalClaudeTriggerComment);
}
function claudeFinalReady(comments, reviews = [], options = {}) {
if (claudeFinalAlreadyTriggered(comments)) {
return { ready: false, reason: 'claude FINAL already triggered', already: true };
}
const prior = priorReviewersReady(comments, reviews, options);
if (!prior.ready) {
return { ready: false, reason: prior.reason };
}
if (isSkipCopilot(options) || prior.requiredTimeout) {
return {
ready: true,
reason: prior.requiredTimeout ? prior.reason : 'copilot skipped',
copilotSkipped: true,
requiredTimeout: prior.requiredTimeout,
};
}
const copilot = copilotReviewReady(comments, reviews);
if (copilot.ready) {
return { ready: true, reason: '' };
}
if (options.allowCopilotTimeout && copilotTriggered(comments)) {
return { ready: true, reason: 'copilot timeout fallback', copilotSkipped: true };
}
return { ready: false, reason: copilot.reason };
}
/** Post @copilot when prior reviewers are ready, then @claude FINAL when Copilot done (or timeout). */
async function advanceReviewChain(github, owner, repo, prNumber, finalBody, core, options = {}) {
const { data: pr } = await github.rest.pulls.get({ owner, repo, pull_number: prNumber });
const chainOpts = {
prCreatedAt: pr.created_at,
optionalWaitMs: options.optionalWaitMs ?? 0,
};
const copilot = options.skipCopilot
? { triggered: false, reason: 'skipped' }
: await maybeTriggerCopilot(github, owner, repo, prNumber, core, chainOpts);
const claude = await maybeTriggerClaudeFinal(
github, owner, repo, prNumber, finalBody, core,
{ ...options, ...chainOpts }
);
return { copilot, claude };
}
async function maybeTriggerClaudeFinal(github, owner, repo, prNumber, finalBody, core, options = {}) {
const { data: pr } = await github.rest.pulls.get({ owner, repo, pull_number: prNumber });
const { comments, reviews } = await listCommentsAndReviews(github, owner, repo, prNumber);
const gate = claudeFinalReady(comments, reviews, {
...options,
prCreatedAt: pr.created_at,
optionalWaitMs: options.optionalWaitMs,
allowCopilotTimeout: options.allowCopilotTimeout !== false,
});
if (!gate.ready) {
core?.info?.(`PR #${prNumber}: skip Claude FINAL — ${gate.reason}`);
return { posted: false, reason: gate.reason };
}
await github.rest.issues.createComment({
owner,
repo,
issue_number: prNumber,
body: finalBody,
});
const note = gate.requiredTimeout
? ' (required reviewer timeout fallback)'
: gate.copilotSkipped
? ' (Copilot timeout fallback)'
: '';
core?.info?.(`Posted Claude FINAL on PR #${prNumber}${note}`);
return { posted: true, reason: '' };
}
const COPILOT_REVIEW_BODY =
'@copilot Do a thorough review of this PR. Read ALL existing reviewer comments above from Qodo, CodeRabbit, Gemini, and Greptile first — incorporate their findings.\n\nReview areas:\n1. **Bloat check**: Are changes minimal and focused? Any unnecessary code or scope creep?\n2. **Security**: Any hardcoded secrets, unsafe eval/exec, missing input validation?\n3. **Performance**: Any module-level heavy imports? Hot-path regressions?\n4. **Tests**: Are tests included? Do they cover the changes adequately?\n5. **Backward compat**: Any public API changes without deprecation?\n6. **Code quality**: DRY violations, naming conventions, error handling?\n7. **Address reviewer feedback**: If Qodo, CodeRabbit, Gemini, or Greptile flagged valid issues, include them in your review\n8. Suggest specific improvements with code examples where possible';
async function listCommentsAndReviews(github, owner, repo, prNumber) {
let comments;
if (typeof github.paginate === 'function') {
comments = await github.paginate(github.rest.issues.listComments, {
owner,
repo,
issue_number: prNumber,
per_page: 100,
});
} else {
const { data } = await github.rest.issues.listComments({
owner,
repo,
issue_number: prNumber,
per_page: 100,
});
comments = data;
}
const { data: reviews } = await github.rest.pulls.listReviews({
owner,
repo,
pull_number: prNumber,
per_page: 100,
});
return { comments, reviews };
}
async function maybeTriggerCopilot(github, owner, repo, prNumber, core, options = {}) {
const { comments, reviews } = await listCommentsAndReviews(github, owner, repo, prNumber);
if (copilotTriggered(comments)) {
core?.info?.(`Copilot already triggered on PR #${prNumber}`);
return { triggered: false, reason: 'already_triggered' };
}
const prior = priorReviewersReady(comments, reviews, options);
if (!prior.ready) {
core?.info?.(`PR #${prNumber}: not ready for Copilot — ${prior.reason}`);
return { triggered: false, reason: prior.reason };
}
await github.rest.issues.createComment({
owner,
repo,
issue_number: prNumber,
body: COPILOT_REVIEW_BODY,
});
core?.info?.(`Posted @copilot on PR #${prNumber} after prior reviewers`);
return { triggered: true };
}
async function pollCopilotResponse(github, owner, repo, prNumber, options = {}) {
const maxAttempts = options.maxAttempts ?? 20;
const delayMs = options.delayMs ?? 30000;
for (let i = 0; i < maxAttempts; i += 1) {
const { comments, reviews } = await listCommentsAndReviews(github, owner, repo, prNumber);
const copilot = copilotReviewReady(comments, reviews);
if (copilot.ready) {
return { ready: true, reason: '' };
}
if (i < maxAttempts - 1) {
await new Promise((resolve) => setTimeout(resolve, delayMs));
}
}
return { ready: false, reason: 'copilot timeout' };
}
module.exports = {
isSkipCopilot,
REQUIRED_PRIOR,
OPTIONAL_PRIOR,
REQUIRED_PRIOR_WAIT_MS,
COPILOT_REVIEW_BODY,
priorReviewerStatus,
priorReviewersReady,
copilotTriggered,
copilotReviewReady,
claudeFinalReady,
claudeFinalAlreadyTriggered,
isFinalClaudeTriggerComment,
maybeTriggerCopilot,
maybeTriggerClaudeFinal,
advanceReviewChain,
pollCopilotResponse,
hasGeminiReview,
listCommentsAndReviews,
};
-122
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@@ -1,122 +0,0 @@
const assert = require('assert');
const rg = require('./release-gate.js');
assert.strictEqual(rg.bumpPatch('1.6.80'), '1.6.81');
assert.strictEqual(rg.bumpPatch('4.6.80'), '4.6.81');
assert.strictEqual(rg.bumpPatch('0.0.2'), '0.0.3');
const versions = rg.readVersionsFromTree();
assert.ok(versions.currentAgents);
assert.ok(versions.currentCode);
assert.ok(versions.currentWrapper);
assert.ok(versions.targetCode);
assert.ok(rg.PACKAGE_PATHS.includes('src/praisonai-code'));
// Every released package must make the gate's path-change check eligible.
for (const p of [
'src/praisonai', 'src/praisonai-agents', 'src/praisonai-code',
'src/praisonai-bot', 'src/praisonai-train', 'src/praisonai-browser',
'src/praisonai-mcp', 'src/praisonai-sandbox', 'src/praisonai-deploy',
]) {
assert.ok(rg.PACKAGE_PATHS.includes(p), `PACKAGE_PATHS missing ${p}`);
}
const noonUtc = new Date('2026-07-08T12:00:00Z');
const dayStart = rg.utcDayStart(noonUtc);
assert.strictEqual(dayStart.toISOString(), '2026-07-08T00:00:00.000Z');
function mockGithub({ runs = [], releases = [] } = {}) {
return {
rest: {
actions: {
listWorkflowRuns: async () => ({ data: { workflow_runs: runs } }),
},
repos: {
listReleases: async () => ({ data: releases }),
},
},
};
}
(async () => {
assert.strictEqual(await rg.pypiVersionExists('praisonaiagents', '0.0.0'), false);
assert.strictEqual(rg.PATCH_RELEASE_INTERVAL_DAYS, 3);
// Dedupe is release-based: a v* release inside the window blocks…
const recentRelease = mockGithub({
releases: [{ tag_name: 'v4.6.159', published_at: '2026-07-08T09:00:00Z' }],
});
assert.strictEqual(
await rg.hasSuccessfulReleaseWithinDays(recentRelease, 'o', 'r', noonUtc),
true
);
const result = await rg.evaluateReleasePreflight(
recentRelease, 'o', 'r',
{ headSha: 'abc', isCiTrigger: false, bump: 'patch', now: noonUtc },
null
);
assert.ok(result.reasons.some((r) => r.includes('every 3 days')));
// …an old release does not…
const oldRelease = mockGithub({
releases: [{ tag_name: 'v4.6.150', published_at: '2026-07-04T09:00:00Z' }],
});
assert.strictEqual(
await rg.hasSuccessfulReleaseWithinDays(oldRelease, 'o', 'r', noonUtc),
false
);
// …and a dry-run "success" (workflow run, no release) does not consume the
// window: only real releases count.
const dryRunOnly = mockGithub({
runs: [{ conclusion: 'success', created_at: '2026-07-08T09:00:00Z', status: 'completed' }],
releases: [],
});
assert.strictEqual(
await rg.hasSuccessfulReleaseWithinDays(dryRunOnly, 'o', 'r', noonUtc),
false
);
// Active-run blocking: fresh waiting run blocks…
const freshWaiting = mockGithub({
runs: [{ status: 'waiting', conclusion: null, created_at: '2026-07-08T11:00:00Z', html_url: 'x' }],
});
assert.strictEqual(
await rg.hasActiveReleaseRun(freshWaiting, 'o', 'r', noonUtc, null),
true
);
// …a waiting run stuck longer than STALE_WAITING_HOURS no longer blocks…
const staleWaiting = mockGithub({
runs: [{ status: 'waiting', conclusion: null, created_at: '2026-07-08T01:00:00Z', html_url: 'x' }],
});
const warnings = [];
const fakeCore = { warning: (m) => warnings.push(m), info: () => {} };
assert.strictEqual(rg.STALE_WAITING_HOURS, 6);
assert.strictEqual(
await rg.hasActiveReleaseRun(staleWaiting, 'o', 'r', noonUtc, fakeCore),
false
);
assert.ok(warnings.length === 1 && warnings[0].includes('approve or cancel'));
// …but an in_progress run always blocks regardless of age.
const oldInProgress = mockGithub({
runs: [{ status: 'in_progress', conclusion: null, created_at: '2026-07-07T01:00:00Z', html_url: 'x' }],
});
assert.strictEqual(
await rg.hasActiveReleaseRun(oldInProgress, 'o', 'r', noonUtc, null),
true
);
console.log('ok: bumpPatch');
console.log('ok: readVersionsFromTree');
console.log('ok: PACKAGE_PATHS covers all 9 released packages');
console.log('ok: pypiVersionExists missing version');
console.log('ok: utcDayStart');
console.log('ok: release-based dedupe (recent blocks, old does not)');
console.log('ok: dry-run success does not consume the release window');
console.log('ok: 3-day dedupe blocks second release');
console.log('ok: fresh waiting run blocks; stale waiting run ignored with warning');
console.log('ok: in_progress always blocks');
})();
-315
View File
@@ -1,315 +0,0 @@
/**
* Release gate preflight — path changes, CI SHA, dedupe, PyPI version checks.
*/
const https = require('https');
/** Every directory whose changes should make a release eligible — all nine
* published packages (mirrors the skip_* inputs in pypi-release.yml). */
const PACKAGE_PATHS = [
'src/praisonai',
'src/praisonai-agents',
'src/praisonai-code',
'src/praisonai-bot',
'src/praisonai-train',
'src/praisonai-browser',
'src/praisonai-mcp',
'src/praisonai-sandbox',
'src/praisonai-deploy',
];
/** Minimum days between successful patch auto-releases. */
const PATCH_RELEASE_INTERVAL_DAYS = 3;
const ACTIVE_RELEASE_STATUSES = new Set([
'queued', 'in_progress', 'waiting', 'pending', 'requested',
]);
/** A run stuck in `waiting` (environment approval) longer than this no longer
* blocks the gate. GitHub only auto-fails unapproved deployments after 30
* days, so without a cutoff one forgotten manual dispatch stalls all
* auto-releases for up to a month. The run is warned about, never cancelled —
* if later approved, the pypi-release concurrency group serializes it and its
* pypi_exists checks no-op anything already published. */
const STALE_WAITING_HOURS = 6;
function bumpPatch(version) {
const parts = version.split('.');
if (parts.length !== 3) throw new Error(`Invalid version: ${version}`);
return `${parts[0]}.${parts[1]}.${Number(parts[2]) + 1}`;
}
function readVersionsFromTree(root = '.') {
const fs = require('fs');
const path = require('path');
const agentsToml = fs.readFileSync(
path.join(root, 'src/praisonai-agents/pyproject.toml'), 'utf8'
);
const agentsMatch = agentsToml.match(/^version\s*=\s*"([^"]+)"/m);
if (!agentsMatch) throw new Error('Could not read agents version');
const codeToml = fs.readFileSync(
path.join(root, 'src/praisonai-code/pyproject.toml'), 'utf8'
);
const codeMatch = codeToml.match(/^version\s*=\s*"([^"]+)"/m);
if (!codeMatch) throw new Error('Could not read praisonai-code version');
const wrapperPy = fs.readFileSync(
path.join(root, 'src/praisonai/praisonai/version.py'), 'utf8'
);
const wrapperMatch = wrapperPy.match(/__version__ = "([^"]+)"/);
if (!wrapperMatch) throw new Error('Could not read wrapper version');
return {
currentAgents: agentsMatch[1],
currentCode: codeMatch[1],
currentWrapper: wrapperMatch[1],
targetAgents: bumpPatch(agentsMatch[1]),
targetCode: bumpPatch(codeMatch[1]),
targetWrapper: bumpPatch(wrapperMatch[1]),
};
}
function pypiVersionExists(packageName, version) {
return new Promise((resolve) => {
const req = https.get(
`https://pypi.org/pypi/${packageName}/${version}/json`,
{ timeout: 15000 },
(res) => {
res.resume();
resolve(res.statusCode === 200);
}
);
req.on('error', () => resolve(false));
req.on('timeout', () => {
req.destroy();
resolve(false);
});
});
}
async function hasActiveReleaseRun(github, owner, repo, now = new Date(), core = null) {
const runs = await github.rest.actions.listWorkflowRuns({
owner,
repo,
workflow_id: 'pypi-release.yml',
per_page: 20,
});
const staleCutoff = now.getTime() - STALE_WAITING_HOURS * 60 * 60 * 1000;
return runs.data.workflow_runs.some((r) => {
if (!ACTIVE_RELEASE_STATUSES.has(r.status) || r.conclusion) return false;
if (r.status === 'waiting' && new Date(r.created_at).getTime() < staleCutoff) {
if (core) {
core.warning(
`Ignoring release run waiting >${STALE_WAITING_HOURS}h for environment approval: `
+ `${r.html_url} — approve or cancel it. It no longer blocks auto-releases.`
);
}
return false;
}
return true;
});
}
function utcDayStart(now = new Date()) {
return new Date(Date.UTC(now.getUTCFullYear(), now.getUTCMonth(), now.getUTCDate()));
}
function releaseIntervalStart(now = new Date(), intervalDays = PATCH_RELEASE_INTERVAL_DAYS) {
return new Date(now.getTime() - intervalDays * 24 * 60 * 60 * 1000);
}
async function hasSuccessfulReleaseWithinDays(
github,
owner,
repo,
now = new Date(),
intervalDays = PATCH_RELEASE_INTERVAL_DAYS,
) {
const windowStart = releaseIntervalStart(now, intervalDays);
// Dedupe on GitHub releases (v* tags) rather than run conclusions: a
// dry_run=true dispatch concludes 'success' without publishing anything and
// must not consume the release window. Only a real full release creates a
// v* GitHub release (bump_and_release.py's `gh release create`).
const releases = await github.rest.repos.listReleases({
owner,
repo,
per_page: 10,
});
return releases.data.some(
(r) => r.tag_name && r.tag_name.startsWith('v')
&& new Date(r.published_at || r.created_at) >= windowStart
);
}
/** @deprecated Use hasSuccessfulReleaseWithinDays — kept for selftests. */
async function hasSuccessfulReleaseToday(github, owner, repo, now = new Date()) {
return hasSuccessfulReleaseWithinDays(github, owner, repo, now, 1);
}
async function lastGreenCoreTestsSha(github, owner, repo) {
const runs = await github.rest.actions.listWorkflowRuns({
owner,
repo,
workflow_id: 'test-core.yml',
branch: 'main',
status: 'completed',
per_page: 30,
});
const hit = runs.data.workflow_runs.find((r) => r.conclusion === 'success');
return hit ? hit.head_sha : '';
}
async function evaluateReleasePreflight(github, owner, repo, options, core) {
const {
headSha,
isCiTrigger = false,
bump = 'patch',
} = options;
const reasons = [];
const out = {
ready: false,
reasons,
headSha: headSha || '',
lastTag: '',
targetAgents: '',
targetCode: '',
targetWrapper: '',
};
if (bump !== 'patch') {
reasons.push('only patch auto-release supported');
return out;
}
const referenceTime = options.now instanceof Date ? options.now : new Date();
if (await hasActiveReleaseRun(github, owner, repo, referenceTime, core)) {
reasons.push('PyPI Release already in progress or awaiting approval');
return out;
}
if (await hasSuccessfulReleaseWithinDays(github, owner, repo, referenceTime)) {
reasons.push(
`already released within last ${PATCH_RELEASE_INTERVAL_DAYS} days; `
+ `max one patch release every ${PATCH_RELEASE_INTERVAL_DAYS} days`
);
return out;
}
let versions;
try {
versions = readVersionsFromTree();
} catch (err) {
reasons.push(err.message);
return out;
}
out.targetAgents = versions.targetAgents;
out.targetCode = versions.targetCode;
out.targetWrapper = versions.targetWrapper;
const agentsOnPypi = await pypiVersionExists('praisonaiagents', versions.targetAgents);
const codeOnPypi = await pypiVersionExists('praisonai-code', versions.targetCode);
const wrapperOnPypi = await pypiVersionExists('praisonai', versions.targetWrapper);
if (agentsOnPypi && codeOnPypi && wrapperOnPypi) {
reasons.push(
`already published: praisonaiagents==${versions.targetAgents}, `
+ `praisonai-code==${versions.targetCode}, praisonai==${versions.targetWrapper}`
);
return out;
}
const { execSync } = require('child_process');
let lastTag = '';
try {
lastTag = execSync('git describe --tags --match "v*" --abbrev=0', { encoding: 'utf8' }).trim();
} catch {
reasons.push('no v* tag found');
return out;
}
out.lastTag = lastTag;
let changed = '';
try {
changed = execSync(
`git diff --name-only ${lastTag} HEAD -- ${PACKAGE_PATHS.join(' ')}`,
{ encoding: 'utf8' }
).trim();
} catch {
reasons.push('git diff failed');
return out;
}
if (!changed) {
reasons.push(`no changes in ${PACKAGE_PATHS.join(' or ')} since ${lastTag}`);
return out;
}
if (isCiTrigger) {
let mainSha = '';
try {
mainSha = execSync('git rev-parse origin/main', { encoding: 'utf8' }).trim();
} catch {
reasons.push('could not resolve origin/main');
return out;
}
if (headSha !== mainSha) {
reasons.push(`superseded: green SHA ${headSha.slice(0, 7)} != main ${mainSha.slice(0, 7)}`);
return out;
}
out.headSha = headSha;
} else {
const evalSha = execSync('git rev-parse HEAD', { encoding: 'utf8' }).trim();
out.headSha = evalSha;
const greenSha = await lastGreenCoreTestsSha(github, owner, repo);
if (greenSha !== evalSha) {
// Core Tests has path filters and honors [skip ci] (the release
// safety-net commit uses it), so the tip of main may legitimately have
// no Core Tests run of its own — e.g. a docs-only commit, or the
// "chore(release): … [skip ci]" commit right after a release. Accept a
// green ancestor when nothing under the released package paths changed
// after it; otherwise the cron path stalls until the next src/** push.
let greenAncestorOk = false;
if (greenSha && /^[0-9a-f]{40}$/.test(greenSha)) {
try {
execSync(`git merge-base --is-ancestor ${greenSha} ${evalSha}`);
const delta = execSync(
`git diff --name-only ${greenSha} ${evalSha} -- ${PACKAGE_PATHS.join(' ')}`,
{ encoding: 'utf8' }
).trim();
greenAncestorOk = delta === '';
} catch {
greenAncestorOk = false;
}
}
if (!greenAncestorOk) {
reasons.push(`CI not green on HEAD (last green: ${greenSha ? greenSha.slice(0, 7) : 'none'})`);
return out;
}
if (core) {
core.info(
`HEAD ${evalSha.slice(0, 7)} has no Core Tests run; accepting green ancestor `
+ `${greenSha.slice(0, 7)} (no package-path changes since).`
);
}
}
}
out.ready = true;
out.reasons = ['ready'];
if (core) core.info(`Release preflight passed for ${out.headSha || headSha}`);
return out;
}
module.exports = {
bumpPatch,
readVersionsFromTree,
pypiVersionExists,
PATCH_RELEASE_INTERVAL_DAYS,
STALE_WAITING_HOURS,
releaseIntervalStart,
hasActiveReleaseRun,
hasSuccessfulReleaseWithinDays,
hasSuccessfulReleaseToday,
utcDayStart,
evaluateReleasePreflight,
ACTIVE_RELEASE_STATUSES,
PACKAGE_PATHS,
};
+1 -1
View File
@@ -42,5 +42,5 @@ jobs:
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. Route correctly: agent tools → PraisonAI-Tools; lifecycle plugins → PraisonAI-Plugins\n2. Search codebase for root cause\n3. Implement a minimal fix following AGENTS.md\n4. Create a PR with the changes'
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'
});
+425 -194
View File
@@ -1,8 +1,11 @@
name: Auto PR Comment
# Review chain: CodeRabbit + Greptile (+ optional Qodo/Gemini) → Claude (FINAL)
# Copilot disabled (REVIEW_CHAIN_SKIP_COPILOT=1) — re-enable copilot-* jobs to restore.
# Fork PR jobs use pull_request_target so GH_TOKEN is available for comments.
# 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.
@@ -12,247 +15,466 @@ on:
pull_request_review:
types: [submitted]
pull_request:
types: [opened, synchronize]
pull_request_target:
types: [opened, synchronize]
schedule:
- cron: '30 3,9,15,21 * * *'
workflow_dispatch:
types: [opened]
env:
REVIEW_CHAIN_SKIP_COPILOT: '1'
MAX_POLL_ATTEMPTS: 20
POLL_DELAY_MS: 30000
CLAUDE_TRIGGER_LOGINS: '["MervinPraison","github-actions[bot]"]'
jobs:
# ================================================================
# Claude FINAL after CodeRabbit / Greptile / optional Qodo / Gemini
# HUMAN PRs: Trigger @copilot AFTER CodeRabbit posts its summary
# ================================================================
claude-after-prior-reviewers:
copilot-after-coderabbit:
if: |
(github.event_name == 'issue_comment' &&
github.event.issue.pull_request &&
(
github.event.comment.user.login == 'coderabbitai[bot]' ||
github.event.comment.user.login == 'greptile-apps[bot]' ||
contains(github.event.comment.user.login, 'gemini-code-assist') ||
contains(github.event.comment.user.login, 'qodo-code-review')
)) ||
(github.event_name == 'pull_request_review' &&
contains(github.event.review.user.login, 'qodo-code-review'))
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')
runs-on: ubuntu-latest
permissions:
issues: write
pull-requests: read
pull-requests: write
outputs:
pr_number: ${{ steps.trigger.outputs.pr_number }}
triggered: ${{ steps.trigger.outputs.triggered }}
steps:
- uses: actions/checkout@v4
with:
persist-credentials: false
- name: Post Claude FINAL after prior reviewers
- name: Post Copilot review request (as user via PAT)
id: trigger
uses: actions/github-script@v7
with:
github-token: ${{ secrets.GH_TOKEN }}
script: |
const path = require('path');
const chain = require(path.join(process.env.GITHUB_WORKSPACE, '.github/scripts/pr-review-chain.js'));
const mergeGate = require(path.join(process.env.GITHUB_WORKSPACE, '.github/scripts/merge-gate.js'));
const ps = require(path.join(process.env.GITHUB_WORKSPACE, '.github/scripts/pipeline-status.js'));
const prNumber =
context.payload.issue?.number ||
context.payload.pull_request?.number;
const owner = context.repo.owner;
const repo = context.repo.repo;
const { data: pr } = await github.rest.pulls.get({
owner, repo, pull_number: prNumber,
const comments = await github.rest.issues.listComments({
issue_number: context.issue.number,
owner: context.repo.owner,
repo: context.repo.repo
});
const result = await chain.maybeTriggerClaudeFinal(
github, owner, repo, prNumber,
mergeGate.FINAL_CLAUDE_REVIEW_BODY, core,
{ skipCopilot: true, optionalWaitMs: 0, prCreatedAt: pr.created_at }
// Check for duplicates — posted by MervinPraison (PAT) or github-actions[bot] (legacy)
const alreadyPosted = comments.data.some(c =>
c.body.includes('@copilot') &&
(c.user.login === 'MervinPraison' || c.user.login === 'github-actions[bot]')
);
if (result.posted) core.info(`Posted Claude FINAL on PR #${prNumber}`);
await ps.ensurePipelineLabels(github, owner, repo, core);
await ps.syncPipelineLabels(github, owner, repo, prNumber, core);
if (alreadyPosted) {
console.log('Copilot already triggered, skipping');
core.setOutput('triggered', 'false');
core.setOutput('pr_number', context.issue.number.toString());
return;
}
await github.rest.issues.createComment({
issue_number: context.issue.number,
owner: context.repo.owner,
repo: context.repo.repo,
body: '@copilot Do a thorough review of this PR. Read ALL existing reviewer comments above from Qodo, Coderabbit, and Gemini first — incorporate their findings.\n\nReview areas:\n1. **Bloat check**: Are changes minimal and focused? Any unnecessary code or scope creep?\n2. **Security**: Any hardcoded secrets, unsafe eval/exec, missing input validation?\n3. **Performance**: Any module-level heavy imports? Hot-path regressions?\n4. **Tests**: Are tests included? Do they cover the changes adequately?\n5. **Backward compat**: Any public API changes without deprecation?\n6. **Code quality**: DRY violations, naming conventions, error handling?\n7. **Address reviewer feedback**: If Qodo, Coderabbit, or Gemini flagged valid issues, include them in your review\n8. Suggest specific improvements with code examples where possible'
});
core.setOutput('triggered', 'true');
core.setOutput('pr_number', context.issue.number.toString());
# Fallback: Trigger @copilot after Qodo review (if Coderabbit doesn't fire)
copilot-after-qodo:
if: |
github.event_name == 'pull_request_review' &&
github.event.review.user.login == 'qodo-code-review[bot]'
runs-on: ubuntu-latest
permissions:
pull-requests: write
outputs:
pr_number: ${{ steps.trigger.outputs.pr_number }}
triggered: ${{ steps.trigger.outputs.triggered }}
steps:
- name: Post Copilot review request (as user via PAT)
id: trigger
uses: actions/github-script@v7
with:
github-token: ${{ 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 FINAL after PR open if reviewers are slow
# 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_target' &&
github.event_name == 'pull_request' &&
github.event.action == 'opened'
runs-on: ubuntu-latest
timeout-minutes: 45
timeout-minutes: 20
permissions:
issues: write
pull-requests: read
pull-requests: write
steps:
- uses: actions/checkout@v4
- name: Wait for prior reviewers (30 min)
run: sleep 1800
- name: Post Claude FINAL (skip Copilot)
- 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 path = require('path');
const chain = require(path.join(process.env.GITHUB_WORKSPACE, '.github/scripts/pr-review-chain.js'));
const mergeGate = require(path.join(process.env.GITHUB_WORKSPACE, '.github/scripts/merge-gate.js'));
const pr = context.payload.pull_request.number;
await chain.maybeTriggerClaudeFinal(
github, context.repo.owner, context.repo.repo, pr,
mergeGate.FINAL_CLAUDE_REVIEW_BODY, core,
{ skipCopilot: true, optionalWaitMs: 0 }
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)
);
# ================================================================
# Recovery: post FINAL @claude after push or when chain missed
# ================================================================
claude-review-recovery:
if: |
github.event_name == 'pull_request_target' &&
github.event.action == 'synchronize'
runs-on: ubuntu-latest
permissions:
issues: write
pull-requests: read
steps:
- uses: actions/checkout@v4
- name: Re-post FINAL Claude review when stale or missing
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 path = require('path');
const mergeGate = require(path.join(process.env.GITHUB_WORKSPACE, '.github/scripts/merge-gate.js'));
const chain = require(path.join(process.env.GITHUB_WORKSPACE, '.github/scripts/pr-review-chain.js'));
const pr = context.payload.pull_request.number;
const 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;
const comments = await mergeGate.listAllComments(github, owner, repo, pr);
const headPushedAt = (await mergeGate.getHeadCommitDate(github, owner, repo, pr))
|| context.payload.pull_request.updated_at;
const headPusher = context.payload.sender?.login || null;
// 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);
const hasFinal = mergeGate.hasFinalClaudeReviewTrigger(comments);
const isStale = mergeGate.isStaleFinalAfterPush(comments, headPushedAt);
for (let i = 0; i < maxAttempts; i++) {
console.log(`Poll attempt ${i + 1}/${maxAttempts}...`);
if (mergeGate.shouldSkipFinalRecovery(comments, headPushedAt)) {
core.info('Recent @claude within 35min and FINAL not stale — skip recovery');
return;
}
const comments = await github.rest.issues.listComments({
issue_number: pr,
owner,
repo,
per_page: 50,
sort: 'created',
direction: 'desc'
});
if (await mergeGate.hasInProgressClaudeAssistant(github, owner, repo, pr)) {
core.info('Claude workflow in progress — skip recovery');
return;
}
// 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'
);
const finalBody = mergeGate.FINAL_CLAUDE_REVIEW_BODY;
const opts = { skipCopilot: true, optionalWaitMs: 0 };
if (hasFinal && isStale) {
const gate = mergeGate.shouldSkipStaleFinalRecovery(comments, headPushedAt, headPusher);
if (gate.skip) {
core.info(`Skip stale-FINAL recovery: ${gate.reason}`);
if (copilotResponse) {
console.log(`Copilot responded at ${copilotResponse.created_at}`);
core.setOutput('copilot_responded', 'true');
return;
}
const result = await chain.maybeTriggerClaudeFinal(
github, owner, repo, pr, finalBody, core, opts
// Also check PR reviews for Copilot
const reviews = await github.rest.pulls.listReviews({
pull_number: pr,
owner,
repo
});
const copilotReview = reviews.data.find(r =>
r.user.login.toLowerCase().includes('copilot')
);
if (result.posted) core.info(`Posted stale-FINAL recovery @claude on PR #${pr}`);
return;
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 ${delayMs/1000}s...`);
await new Promise(resolve => setTimeout(resolve, delayMs));
}
}
if (hasFinal) {
core.info('FINAL Claude review current on HEAD — skip recovery');
return;
}
console.log('Copilot did not respond within timeout, triggering Claude anyway');
core.setOutput('copilot_responded', 'timeout');
const result = await chain.maybeTriggerClaudeFinal(
github, owner, repo, pr, finalBody, core, opts
);
if (result.posted) core.info(`Posted missing FINAL Claude review on PR #${pr}`);
- name: Sync pipeline status labels
- 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 path = require('path');
const ps = require(path.join(process.env.GITHUB_WORKSPACE, '.github/scripts/pipeline-status.js'));
const pr = context.payload.pull_request.number;
await ps.ensurePipelineLabels(github, context.repo.owner, context.repo.repo, core);
await ps.syncPipelineLabels(github, context.repo.owner, context.repo.repo, pr, core);
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');
# Scheduled + manual: post missing or stale FINAL @claude on all open PRs (incl. forks)
post-missing-claude-final:
if: github.event_name == 'schedule' || github.event_name == 'workflow_dispatch'
- 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: read
pull-requests: write
steps:
- uses: actions/checkout@v4
- 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 missing/stale FINAL @claude on open PRs
- 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: |
const path = require('path');
const mergeGate = require(path.join(process.env.GITHUB_WORKSPACE, '.github/scripts/merge-gate.js'));
const chain = require(path.join(process.env.GITHUB_WORKSPACE, '.github/scripts/pr-review-chain.js'));
const owner = context.repo.owner;
const repo = context.repo.repo;
const prs = await github.paginate(github.rest.pulls.list, {
owner, repo, state: 'open', per_page: 100,
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'
});
let posted = 0;
for (const pr of prs) {
if (pr.draft) continue;
const comments = await mergeGate.listAllComments(github, owner, repo, pr.number);
const headPushedAt = (await mergeGate.getHeadCommitDate(github, owner, repo, pr.number)) || pr.updated_at;
const hasFinal = mergeGate.hasFinalClaudeReviewTrigger(comments);
const isStale = mergeGate.isStaleFinalAfterPush(comments, headPushedAt);
if (hasFinal && !isStale) continue;
if (mergeGate.hasRecentClaudeTrigger(comments, 10)) {
core.info(`PR #${pr.number}: @claude within 10min — skip`);
continue;
}
if (await mergeGate.hasInProgressClaudeAssistant(github, owner, repo, pr.number)) {
core.info(`PR #${pr.number}: Claude in progress — skip`);
continue;
}
if (hasFinal && isStale) {
const gate = mergeGate.shouldSkipStaleFinalRecovery(comments, headPushedAt);
if (gate.skip) {
core.info(`PR #${pr.number}: skip stale — ${gate.reason}`);
continue;
}
}
const result = await chain.maybeTriggerClaudeFinal(
github, owner, repo, pr.number,
mergeGate.FINAL_CLAUDE_REVIEW_BODY, core,
{ skipCopilot: true, optionalWaitMs: 0 }
);
if (result.posted) {
posted++;
core.info(`Posted Claude FINAL on PR #${pr.number}`);
}
if (posted >= 10) break;
}
core.info(`Missing/stale Claude FINAL sweep complete (${posted} posted)`);
# ================================================================
# BOT PRs: kick CodeRabbit + Qodo (Greptile may follow on its own)
# 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: |
@@ -266,29 +488,38 @@ jobs:
runs-on: ubuntu-latest
permissions:
pull-requests: write
issues: write
steps:
- uses: actions/checkout@v4
with:
persist-credentials: false
- name: Trigger CodeRabbit and Qodo reviews
uses: actions/github-script@v7
with:
github-token: ${{ secrets.GH_TOKEN }}
script: |
const path = require('path');
const chain = require(path.join(process.env.GITHUB_WORKSPACE, '.github/scripts/bot-pr-review-chain.js'));
const pr = context.payload.pull_request.number;
await chain.kickReviewChain(github, context.repo.owner, context.repo.repo, pr, core);
const owner = context.repo.owner;
const repo = context.repo.repo;
- name: Sync pipeline status labels
uses: actions/github-script@v7
with:
github-token: ${{ secrets.GH_TOKEN }}
script: |
const path = require('path');
const ps = require(path.join(process.env.GITHUB_WORKSPACE, '.github/scripts/pipeline-status.js'));
const pr = context.payload.pull_request.number;
await ps.ensurePipelineLabels(github, context.repo.owner, context.repo.repo, core);
await ps.syncPipelineLabels(github, context.repo.owner, context.repo.repo, pr, core);
// 1. Trigger CodeRabbit review
await github.rest.issues.createComment({
issue_number: pr, owner, repo,
body: '@coderabbitai review'
});
console.log(`Triggered CodeRabbit for bot PR #${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.');
-43
View File
@@ -1,43 +0,0 @@
name: Bot PR Recovery
# Belt-and-braces: kick CodeRabbit/Qodo when pull_request:opened never fired for bot PRs.
on:
schedule:
- cron: '*/15 * * * *'
workflow_dispatch:
inputs:
pr_number:
description: 'Specific PR number to kick (optional)'
required: false
type: string
permissions:
pull-requests: write
issues: write
jobs:
recover:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v4
with:
persist-credentials: false
- name: Find and kick stalled bot PRs
uses: actions/github-script@v7
env:
PR_NUMBER_INPUT: ${{ github.event.inputs.pr_number }}
with:
github-token: ${{ secrets.GH_TOKEN }}
script: |
const path = require('path');
const chain = require(path.join(process.env.GITHUB_WORKSPACE, '.github/scripts/bot-pr-review-chain.js'));
const owner = context.repo.owner;
const repo = context.repo.repo;
const manual = (process.env.PR_NUMBER_INPUT || '').trim();
const prNumber = manual ? parseInt(manual, 10) : null;
if (manual && Number.isNaN(prNumber)) {
throw new Error(`Invalid pr_number: ${manual}`);
}
await chain.recoverStalledBotPrs(github, owner, repo, { prNumber }, core);
-102
View File
@@ -1,102 +0,0 @@
name: Auto CI Failure → Claude
# Detects internal PRs with failing CI and posts @claude with extracted failure details.
on:
workflow_run:
workflows: [Core Tests, Optimized Test Suite]
types: [completed]
pull_request:
types: [opened, synchronize, reopened]
workflow_dispatch:
inputs:
pr_number:
description: 'Optional PR number to process (default: scan blocked PRs)'
required: false
type: string
schedule:
- cron: '15 */6 * * *'
concurrency:
group: ci-failure-scan-${{ github.repository }}-${{ github.event.pull_request.number || github.event.workflow_run.id || github.run_id }}
cancel-in-progress: true
env:
# PAT posts as MervinPraison so issue_comment triggers claude.yml (GITHUB_TOKEN cannot chain workflows)
GH_TOKEN: ${{ secrets.GH_TOKEN || github.token }}
permissions:
pull-requests: read
issues: write
actions: read
jobs:
detect-and-trigger:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v4
with:
persist-credentials: false
- name: Detect CI failures and trigger Claude
uses: actions/github-script@v7
with:
github-token: ${{ env.GH_TOKEN }}
script: |
const path = require('path');
const ciFix = require(path.join(process.env.GITHUB_WORKSPACE, '.github/scripts/ci-failure-claude.js'));
const owner = context.repo.owner;
const repo = context.repo.repo;
const baseRepo = `${owner}/${repo}`;
async function processPR(prNumber) {
return ciFix.maybeTriggerCiFixClaude(github, owner, repo, prNumber, core);
}
let results = [];
if (context.eventName === 'workflow_run') {
const wr = context.payload.workflow_run;
const result = await ciFix.processWorkflowRunFailure(
github, owner, repo, wr, core
);
results.push({ event: 'workflow_run', workflow: wr.name, ...result });
} else if (context.eventName === 'pull_request') {
results.push({
pr: context.payload.pull_request.number,
...(await processPR(context.payload.pull_request.number)),
});
} else {
let prNumbers = [];
if (context.eventName === 'workflow_dispatch' && context.payload.inputs?.pr_number) {
prNumbers = [Number(context.payload.inputs.pr_number)];
} else {
const prs = await github.paginate(github.rest.pulls.list, {
owner,
repo,
state: 'open',
per_page: 100,
});
for (const pr of prs) {
if (pr.draft) continue;
const headRepo = pr.head?.repo?.full_name;
if (headRepo && headRepo !== baseRepo) continue;
const { data: issue } = await github.rest.issues.get({
owner,
repo,
issue_number: pr.number,
});
const labels = issue.labels.map((l) => l.name);
if (labels.includes('pipeline/blocked:ci') || labels.includes(ciFix.CI_FIX_LABEL)) {
prNumbers.push(pr.number);
}
}
}
for (const num of prNumbers) {
results.push({ pr: num, ...(await processPR(num)) });
}
}
core.summary.addRaw('```json\n' + JSON.stringify(results, null, 2) + '\n```');
await core.summary.write();
-532
View File
@@ -1,532 +0,0 @@
name: Claude PR Merge Gate
# Read-only Claude assesses merge readiness; GH_TOKEN merges (no @claude, no gh pr review).
# Does not overlap with merge-conflict-claude.yml or auto-pr-comment @claude chains.
on:
schedule:
# Scan for merge-ready PRs every 10 minutes (assess runs only when candidates exist).
- cron: '*/10 * * * *'
workflow_dispatch:
inputs:
pr_number:
description: 'Optional PR number (scan all open internal PRs if empty)'
required: false
type: string
merge_method:
description: 'Merge method'
required: false
type: choice
default: merge
options:
- merge
- squash
- rebase
workflow_run:
workflows:
- Claude Assistant
- Core Tests
types:
- completed
repository_dispatch:
types:
- claude-merge-gate
concurrency:
group: claude-merge-gate-${{ github.repository }}-${{ github.event.inputs.pr_number || github.event.client_payload.pr_number || github.event.workflow_run.id || 'scan' }}
cancel-in-progress: false
env:
GH_TOKEN: ${{ secrets.GH_TOKEN || github.token }}
MAX_CANDIDATES: 3
DISPATCH_PR_NUMBER: ${{ github.event.inputs.pr_number || github.event.client_payload.pr_number || '' }}
permissions:
contents: read
pull-requests: read
issues: read
actions: read
jobs:
auto-dispatch:
if: github.event_name == 'workflow_run'
runs-on: ubuntu-latest
permissions:
contents: read
pull-requests: read
issues: read
actions: write
id-token: write
steps:
- uses: actions/checkout@v4
- name: Generate GitHub App token
id: app-token
uses: actions/create-github-app-token@v1
with:
app-id: ${{ secrets.CLAUDE_APP_ID }}
private-key: ${{ secrets.CLAUDE_APP_PRIVATE_KEY }}
owner: ${{ github.repository_owner }}
- name: Dispatch merge gate when PR pipeline is ready
uses: actions/github-script@v7
with:
github-token: ${{ steps.app-token.outputs.token }}
script: |
const path = require('path');
const mergeGate = require(path.join(process.env.GITHUB_WORKSPACE, '.github/scripts/merge-gate.js'));
const wr = context.payload.workflow_run;
const owner = context.repo.owner;
const repo = context.repo.repo;
if (wr.conclusion !== 'success') {
core.info(`Skip dispatch: ${wr.name} conclusion=${wr.conclusion}`);
return;
}
const allowed = ['Claude Assistant', 'Core Tests'];
if (!allowed.includes(wr.name)) {
core.info(`Skip dispatch: workflow ${wr.name}`);
return;
}
const prNumber = await mergeGate.resolvePrNumberFromWorkflowRun(github, owner, repo, wr);
if (!prNumber) {
core.info('Skip dispatch: could not resolve PR from workflow run');
return;
}
const fromClaude = wr.name === 'Claude Assistant';
const check = await mergeGate.evaluatePipelineQuiescent(
github, owner, repo, prNumber, core, {
skipGlobalClaudeRunCheck: fromClaude,
skipRecentClaudeCooldown: fromClaude,
}
);
if (!check.ready) {
core.info(`PR #${prNumber} not ready: ${check.reasons.join(', ')}`);
return;
}
await github.rest.repos.createDispatchEvent({
owner,
repo,
event_type: 'claude-merge-gate',
client_payload: { pr_number: prNumber },
});
core.info(`Dispatched merge gate for PR #${prNumber} after ${wr.name}`);
scan-candidates:
if: github.event_name != 'workflow_run'
runs-on: ubuntu-latest
permissions:
contents: read
pull-requests: read
issues: write
actions: read
id-token: write
outputs:
matrix: ${{ steps.scan.outputs.matrix }}
has_candidates: ${{ steps.scan.outputs.has_candidates }}
steps:
- uses: actions/checkout@v4
- name: Generate GitHub App token
id: app-token
uses: actions/create-github-app-token@v1
with:
app-id: ${{ secrets.CLAUDE_APP_ID }}
private-key: ${{ secrets.CLAUDE_APP_PRIVATE_KEY }}
owner: ${{ github.repository_owner }}
- name: Scan open PRs for merge gate eligibility
id: scan
uses: actions/github-script@v7
with:
github-token: ${{ steps.app-token.outputs.token }}
script: |
const path = require('path');
const mergeGate = require(path.join(process.env.GITHUB_WORKSPACE, '.github/scripts/merge-gate.js'));
const ps = require(path.join(process.env.GITHUB_WORKSPACE, '.github/scripts/pipeline-status.js'));
const owner = context.repo.owner;
const repo = context.repo.repo;
const maxCandidates = parseInt(process.env.MAX_CANDIDATES || '5', 10);
const inputPr = String(process.env.DISPATCH_PR_NUMBER || '').trim();
const candidates = [];
const skipped = [];
if (inputPr) {
const n = parseInt(inputPr, 10);
if (Number.isNaN(n)) {
throw new Error(`Invalid pr_number input: ${inputPr}`);
}
const result = await mergeGate.evaluatePipelineQuiescent(github, owner, repo, n, core);
if (result.ready) {
candidates.push({ pr_number: n, head_sha: result.headSha });
} else {
skipped.push({ pr: n, reasons: result.reasons });
}
} else {
const prNumbers = await mergeGate.listPrNumbersForMergeGateScan(
github, owner, repo, core
);
const selected = await mergeGate.selectMergeGateCandidates(
github, owner, repo, prNumbers, maxCandidates, core
);
candidates.push(...selected.candidates);
skipped.push(...selected.skipped);
}
core.info('Skipped: ' + JSON.stringify(skipped));
core.setOutput('matrix', JSON.stringify({ include: candidates }));
core.setOutput('has_candidates', candidates.length > 0 ? 'true' : 'false');
core.summary.addRaw('## Merge gate scan\n');
core.summary.addRaw(`Candidates: ${candidates.length}\n`);
core.summary.addRaw('```json\n' + JSON.stringify({ candidates, skipped }, null, 2) + '\n```');
await core.summary.write();
if (inputPr && skipped.length === 1 && skipped[0].pr === parseInt(inputPr, 10)) {
const reasons = skipped[0].reasons;
const body = [
'**Merge gate scan** — not eligible for auto-merge.',
'',
...reasons.map((r) => `- \`${r}\``),
'',
'**Actions:** wait for CI and the Claude review chain, or add label `needs-manual-review` and merge manually.',
'**Opt out:** label `no-auto-merge`.',
].join('\n');
await github.rest.issues.createComment({
owner, repo, issue_number: skipped[0].pr, body,
});
} else if (inputPr && candidates.length === 1) {
await github.rest.issues.createComment({
owner, repo, issue_number: candidates[0].pr_number,
body: '**Merge gate scan** — eligible for assessment. Claude merge gate will assess and may auto-merge if `MERGE_GATE_VERDICT: APPROVE`.',
});
}
await ps.syncOpenPullRequests(github, owner, repo, { maxPrs: 10 }, core);
claude-assess:
needs: scan-candidates
if: needs.scan-candidates.outputs.has_candidates == 'true'
runs-on: ubuntu-latest
timeout-minutes: 20
strategy:
fail-fast: false
matrix: ${{ fromJson(needs.scan-candidates.outputs.matrix) }}
permissions:
contents: read
pull-requests: read
issues: write
actions: read
id-token: write
steps:
- name: Generate GitHub App Token
id: app-token
uses: actions/create-github-app-token@v1
with:
app-id: ${{ secrets.CLAUDE_APP_ID }}
private-key: ${{ secrets.CLAUDE_APP_PRIVATE_KEY }}
owner: ${{ github.repository_owner }}
- uses: actions/checkout@v4
with:
fetch-depth: 0
token: ${{ steps.app-token.outputs.token }}
- name: Mark merge gate active
id: mark_active
uses: actions/github-script@v7
with:
github-token: ${{ steps.app-token.outputs.token }}
script: |
core.setOutput('started_at', new Date().toISOString());
await github.rest.issues.addLabels({
owner: context.repo.owner,
repo: context.repo.repo,
issue_number: ${{ matrix.pr_number }},
labels: ['claude-merge-gate-active'],
});
- name: Stash merge gate helpers
run: cp .github/scripts/merge-gate.js /tmp/merge-gate.js
- name: Fetch PR branch
env:
PR_NUMBER: ${{ matrix.pr_number }}
run: |
git fetch origin "pull/${PR_NUMBER}/head:pr-${PR_NUMBER}"
git checkout "pr-${PR_NUMBER}"
- name: Claude merge gate assessment (read-only)
id: assess
uses: ./.github/actions/claude-code-action
env:
GH_TOKEN: ${{ steps.app-token.outputs.token }}
CLAUDE_CODE_SUBAGENT_MODEL: inherit
ANTHROPIC_DEFAULT_SONNET_MODEL: claude-sonnet-4-6
with:
claude_code_oauth_token: ${{ secrets.CLAUDE_CODE_OAUTH_TOKEN }}
github_token: ${{ steps.app-token.outputs.token }}
model: claude-opus-4-8
trigger_phrase: '@claude-merge-gate-internal'
direct_prompt: |
You are the MERGE GATE reviewer for PraisonAI PR #${{ matrix.pr_number }}.
READ-ONLY: do not modify code, commit, push, rebase, or create branches.
CRITICAL OUTPUT RULE:
Post exactly one PR comment via GitHub MCP containing either:
MERGE_GATE_VERDICT: APPROVE
or
MERGE_GATE_VERDICT: BLOCK
followed by a short rationale on the next lines.
NEVER include @claude in any comment. NEVER mention merge conflict resolution.
Review checklist:
1. Read AGENTS.md and the PR diff on the current branch.
2. Read all PR comments and reviews (FINAL architecture reviewer / Lead Engineer must have run).
3. Confirm SDK value gate: change strengthens praisonaiagents (no scope creep). The aim is a LIGHTWEIGHT AND POWERFUL package — BLOCK changes that add params/modules/exports duplicating existing Agent capabilities (instructions/backstory/tools/hooks/memory), or add knobs/fields with no live consumer, i.e. scope creep for the sake of it.
4. Repo routing: BLOCK if agent-callable tools (→ PraisonAI-Tools), lifecycle plugins (→ PraisonAI-Plugins), or optional sandbox backends (→ PraisonAI-Plugins via `praisonai.sandbox`) were added to praisonaiagents/ instead of the external repo.
5. Do not bloat the Agent class with additional params — only if absolutely required; we already support many params.
6. If agent.py adds >100 lines or new Agent __init__ params, respond MERGE_GATE_VERDICT: BLOCK (manual review required).
7. BLOCK if labels security/breaking-change/needs-manual-review/release, sensitive paths (.github/workflows, auth, pyproject.toml), secrets in diff, PR >800 lines or >30 files, or SDK changes without tests. Label `merge-gate-ci-only` exempts CI-only changes under `.github/workflows/`, `.github/actions/`, or merge-gate scripts.
8. Confirm no CHANGES_REQUESTED reviews and CI green on HEAD ${{ matrix.head_sha }}.
9. If ready to merge: MERGE_GATE_VERDICT: APPROVE. Otherwise: MERGE_GATE_VERDICT: BLOCK with reasons.
Do not approve or merge via GitHub UI/API — only post the verdict comment.
disallowed_tools: |
Bash
Edit
Write
Replace
allowed_tools: |
View
GlobTool
GrepTool
Read
timeout_minutes: 15
- name: Post fallback BLOCK if Opus did not comment
id: fallback_verdict
if: steps.assess.outcome != 'success'
uses: actions/github-script@v7
with:
github-token: ${{ steps.app-token.outputs.token }}
script: |
const mergeGate = require('/tmp/merge-gate.js');
const owner = context.repo.owner;
const repo = context.repo.repo;
const prNumber = ${{ matrix.pr_number }};
const ctx = await mergeGate.loadPrContext(github, owner, repo, prNumber);
const minCreatedAt = new Date(Date.now() - 25 * 60 * 1000).toISOString();
const existing = mergeGate.findMergeGateVerdict(
ctx.comments, minCreatedAt, ctx.headPushedAt, { excludeAutomatedFallback: true }
);
if (existing) {
core.info(`Opus verdict already posted: ${existing}`);
return;
}
const check = await mergeGate.evaluatePipelineQuiescent(
github, owner, repo, prNumber, core, { forMergeStep: true }
);
const lines = [
'MERGE_GATE_VERDICT: BLOCK',
'',
'Automated fallback — Opus merge gate assessment did not complete.',
];
if (check.ready) {
lines.push('Deterministic gates passed, but Opus MERGE_GATE_VERDICT is required before merge.');
} else {
lines.push('Blockers:', ...check.reasons.map((r) => `- ${r}`));
}
await github.rest.issues.createComment({
owner, repo, issue_number: prNumber,
body: lines.join('\n'),
});
core.info('Posted fallback BLOCK — Opus verdict required');
- name: Require Opus MERGE_GATE_VERDICT
uses: actions/github-script@v7
with:
github-token: ${{ steps.app-token.outputs.token }}
script: |
const mergeGate = require('/tmp/merge-gate.js');
const comments = await mergeGate.listAllComments(
github, context.repo.owner, context.repo.repo, ${{ matrix.pr_number }}
);
const ctx = await mergeGate.loadPrContext(
github, context.repo.owner, context.repo.repo, ${{ matrix.pr_number }}
);
const minCreatedAt = new Date(Date.now() - 25 * 60 * 1000).toISOString();
const verdict = mergeGate.findMergeGateVerdict(
comments, minCreatedAt, ctx.headPushedAt, { excludeAutomatedFallback: true }
);
if (!verdict) {
core.setFailed(
'Opus merge gate assessment must post MERGE_GATE_VERDICT on this PR (automated fallback APPROVE is not accepted).'
);
return;
}
core.info(`Opus merge gate verdict: ${verdict}`);
core.setOutput('verdict', verdict);
- name: Remove merge gate active label
if: always()
uses: actions/github-script@v7
with:
github-token: ${{ steps.app-token.outputs.token }}
script: |
const prNumber = ${{ matrix.pr_number }};
try {
await github.rest.issues.removeLabel({
owner: context.repo.owner,
repo: context.repo.repo,
issue_number: prNumber,
name: 'claude-merge-gate-active',
});
core.info(`Removed claude-merge-gate-active from PR #${prNumber}`);
} catch (e) {
core.info(`Label claude-merge-gate-active already removed or missing on PR #${prNumber}`);
}
- name: Fail job if assessment failed
if: steps.assess.outcome == 'failure'
run: exit 1
merge-only:
needs: [scan-candidates, claude-assess]
if: |
always() &&
needs.scan-candidates.outputs.has_candidates == 'true' &&
needs.claude-assess.result == 'success'
runs-on: ubuntu-latest
strategy:
fail-fast: false
matrix: ${{ fromJson(needs.scan-candidates.outputs.matrix) }}
permissions:
contents: write
pull-requests: write
issues: write
actions: read
id-token: write
steps:
- uses: actions/checkout@v4
- name: Generate GitHub App token
id: app-token
uses: actions/create-github-app-token@v1
with:
app-id: ${{ secrets.CLAUDE_APP_ID }}
private-key: ${{ secrets.CLAUDE_APP_PRIVATE_KEY }}
owner: ${{ github.repository_owner }}
- name: Re-check gates and merge
uses: actions/github-script@v7
env:
MERGE_METHOD: ${{ github.event.inputs.merge_method || 'merge' }}
SCAN_HEAD_SHA: ${{ matrix.head_sha }}
with:
github-token: ${{ steps.app-token.outputs.token }}
script: |
const path = require('path');
const mergeGate = require(path.join(process.env.GITHUB_WORKSPACE, '.github/scripts/merge-gate.js'));
const owner = context.repo.owner;
const repo = context.repo.repo;
const prNumber = ${{ matrix.pr_number }};
const scanHeadSha = process.env.SCAN_HEAD_SHA;
const removeLabels = async () => {
try {
await github.rest.issues.removeLabel({
owner, repo, issue_number: prNumber, name: 'claude-merge-gate-active',
});
} catch (e) {
core.info('Label claude-merge-gate-active already removed or missing');
}
};
try {
const ctx = await mergeGate.loadPrContext(github, owner, repo, prNumber);
const comments = ctx.comments;
const verdictMin = new Date(Date.now() - 25 * 60 * 1000).toISOString();
const verdict = mergeGate.findMergeGateVerdict(
comments, verdictMin, ctx.headPushedAt, { excludeAutomatedFallback: true }
);
if (verdict !== 'APPROVE') {
core.info(`Skip merge: verdict=${verdict || 'NONE'}`);
await removeLabels();
return;
}
const check = await mergeGate.evaluatePipelineQuiescent(
github, owner, repo, prNumber, core, { forMergeStep: true }
);
if (!check.ready) {
core.info(`Skip merge: ${check.reasons.join(', ')}`);
await removeLabels();
return;
}
if (check.headSha !== scanHeadSha) {
core.info(`Skip merge: HEAD moved ${scanHeadSha.slice(0, 7)} → ${check.headSha.slice(0, 7)}`);
await removeLabels();
return;
}
const method = process.env.MERGE_METHOD || 'merge';
const sleep = (ms) => new Promise((r) => setTimeout(r, ms));
let merged = false;
for (let attempt = 1; attempt <= 3; attempt++) {
try {
await github.rest.pulls.merge({
owner, repo, pull_number: prNumber, merge_method: method,
});
merged = true;
break;
} catch (e) {
const msg = (e.message || '').toLowerCase();
if (attempt < 3 && msg.includes('base branch was modified')) {
core.info(`Merge attempt ${attempt} failed (base moved), retrying in 8s...`);
await sleep(8000);
const recheck = await mergeGate.evaluatePipelineQuiescent(
github, owner, repo, prNumber, core, { forMergeStep: true }
);
if (!recheck.ready) {
core.info(`Skip merge retry: ${recheck.reasons.join(', ')}`);
await removeLabels();
return;
}
continue;
}
throw e;
}
}
if (!merged) {
core.info('Skip merge: exhausted retries');
await removeLabels();
return;
}
await github.rest.issues.addLabels({
owner, repo, issue_number: prNumber, labels: ['auto-merged-by-gate'],
});
await github.rest.issues.createComment({
owner, repo, issue_number: prNumber,
body: [
'Merged by **Claude PR merge gate** (`claude-merge-gate.yml`).',
`Verdict: MERGE_GATE_VERDICT: APPROVE`,
`SHA: \`${check.headSha.slice(0, 7)}\``,
`Method: ${method}`,
].join('\n'),
});
core.info(`Merged PR #${prNumber}`);
} finally {
await removeLabels();
}
+54 -183
View File
@@ -49,14 +49,12 @@ jobs:
// --- Label triage ---
const labels = [];
// Kind labels (bug before "how to" — bug reports often include "## How to fix")
// Kind labels
if (content.includes('feature request') || content.includes('[feature')) {
labels.push('enhancement');
} else if (!title.includes('[question]') && (content.includes('bug') || content.includes('error') || content.includes('crash') || content.includes('traceback'))) {
} else if (content.includes('bug') || content.includes('error') || content.includes('crash') || content.includes('traceback')) {
labels.push('bug');
} else if (title.includes('[question]') || content.includes('how do i') || (content.includes('how to') && !content.includes('how to fix'))) {
labels.push('question');
} else if (content.includes('question')) {
} else if (content.includes('question') || content.includes('how do i') || content.includes('how to')) {
labels.push('question');
}
@@ -98,21 +96,13 @@ jobs:
'- Check [existing issues](https://github.com/MervinPraison/PraisonAI/issues) for duplicates',
'- Review the [documentation](https://docs.praison.ai) for related guides',
'',
'_Bug and enhancement reports are auto-triaged with Claude. Questions and other issues: a maintainer can comment `@claude` to trigger analysis._',
'',
'**Routing:** Agent-callable tools → [PraisonAI-Tools](https://github.com/MervinPraison/PraisonAI-Tools); lifecycle plugins (tracing/hooks/guardrails) → [PraisonAI-Plugins](https://github.com/MervinPraison/PraisonAI-Plugins).'
'_A maintainer can trigger deeper analysis by commenting `@claude` on this issue._'
].join('\n')
});
}
// --- Auto-trigger Claude for owner issues and actionable external bug/enhancement reports ---
const titleLower = (issue.title || '').toLowerCase();
const hasActionableTitle = /^(\[[^\]]+\]|bug:|fix[:(]|feat:|ux:|enhancement:)/i.test(titleLower);
const autoClaude = isOwner || (hasActionableTitle && (
labels.includes('bug') ||
(labels.includes('enhancement') && !labels.includes('question'))
));
if (autoClaude) {
// --- 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,
@@ -122,43 +112,25 @@ jobs:
}
# ================================================================
# Job 2: Full Claude code-fix
# Job 2: Full Claude code-fix (owner/collaborator only)
# Triggers on: labeled 'claude', @claude comments, assignments
# ================================================================
claude-response:
# Allow: human users, github-actions[bot] (FINAL @claude / CI-fix comments)
# Allow: praisonai-triage-agent[bot] only for issues labeled 'claude' (auto-triage)
# Block: praisonai-triage-agent on issue_comment (merge-gate scan mentions @claude)
# Allow: human users, github-actions[bot] (auto-comments/labels)
# Block: dependabot, cursor, renovate, other bots
# Skip 'opened' events — triage job handles those above
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.event.comment.body, 'Merge gate scan') &&
!contains(github.event.comment.body, 'MERGE_GATE_VERDICT') &&
!contains(github.event.comment.body, 'Merged by **Claude PR merge gate**') &&
(
!contains(github.actor, '[bot]') ||
contains(github.event.comment.body, 'FINAL architecture reviewer') ||
contains(github.event.comment.body, 'lead engineer') ||
contains(github.event.comment.body, 'merge conflict') ||
contains(github.event.comment.body, 'CI failed on HEAD')
)
)) &&
(github.event_name != 'pull_request_review' || contains(github.event.review.body, '@claude')) &&
(github.event_name != 'pull_request_review_comment' || contains(github.event.comment.body, '@claude')) &&
(github.event_name != 'issue_comment' || contains(github.event.comment.body, '@claude')) &&
(
!contains(github.actor, '[bot]') ||
github.actor == 'github-actions[bot]' ||
(github.event_name == 'issues' && github.event.action == 'labeled' && github.event.label.name == 'claude' && github.actor == 'praisonai-triage-agent[bot]')
github.actor == 'praisonai-triage-agent[bot]'
) &&
github.actor != 'dependabot[bot]' &&
github.actor != 'cursor[bot]' &&
github.actor != 'renovate[bot]'
concurrency:
group: claude-response-${{ github.repository }}-${{ github.event.pull_request.number || github.event.issue.number || github.run_id }}
cancel-in-progress: false
runs-on: ubuntu-latest
permissions:
contents: write
@@ -179,67 +151,26 @@ jobs:
id: check_fork
uses: actions/github-script@v7
with:
github-token: ${{ steps.app-token.outputs.token }}
script: |
const isPR = context.eventName === 'pull_request'
|| context.eventName === 'pull_request_review'
|| context.eventName === 'pull_request_review_comment'
|| (context.payload.issue && context.payload.issue.pull_request);
if (!isPR) {
core.setOutput('is_pr', 'false');
core.setOutput('is_fork', 'false');
core.setOutput('can_push_fork', 'false');
return;
}
const prNumber = context.payload.pull_request
? context.payload.pull_request.number
: context.payload.issue.number;
const pr = await github.rest.pulls.get({
owner: context.repo.owner,
repo: context.repo.repo,
pull_number: prNumber
});
let mergeState = '';
try {
const gql = await github.graphql(
`query($owner: String!, $repo: String!, $number: Int!) {
repository(owner: $owner, name: $repo) {
pullRequest(number: $number) { mergeStateStatus }
}
}`,
{ owner: context.repo.owner, repo: context.repo.repo, number: prNumber }
);
mergeState = (gql.repository.pullRequest.mergeStateStatus || '').toUpperCase();
} catch (e) {
core.warning(`GraphQL mergeStateStatus failed: ${e.message}`);
}
if (!mergeState) {
mergeState = (pr.data.mergeable_state || pr.data.merge_state_status || '').toUpperCase();
}
core.setOutput('is_pr', 'true');
core.setOutput('pr_number', String(prNumber));
core.setOutput('pr_branch', pr.data.head.ref);
core.setOutput('head_repo', pr.data.head.repo.full_name);
core.setOutput('merge_state', mergeState);
const baseRepo = `${context.repo.owner}/${context.repo.repo}`;
const maintainerCanModify = pr.data.maintainer_can_modify === true;
core.setOutput('maintainer_can_modify', String(maintainerCanModify));
if (pr.data.head.repo && pr.data.head.repo.full_name !== baseRepo) {
core.setOutput('is_fork', 'true');
core.setOutput('can_push_fork', String(maintainerCanModify));
core.setOutput('fork_repo', pr.data.head.repo.full_name);
core.setOutput('clone_url', pr.data.head.repo.clone_url);
core.setOutput('branch', pr.data.head.ref);
return;
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');
core.setOutput('can_push_fork', 'false');
- name: Checkout repository
uses: actions/checkout@v4
@@ -249,40 +180,31 @@ jobs:
token: ${{ steps.app-token.outputs.token }}
- name: Fetch PR branch and Setup Remote
if: steps.check_fork.outputs.is_pr == 'true'
if: github.event.issue.pull_request
env:
PR_BRANCH: ${{ steps.check_fork.outputs.pr_branch }}
PR_NUMBER: ${{ steps.check_fork.outputs.pr_number }}
IS_FORK: ${{ steps.check_fork.outputs.is_fork }}
CAN_PUSH_FORK: ${{ steps.check_fork.outputs.can_push_fork }}
FORK_REPO: ${{ steps.check_fork.outputs.fork_repo }}
GH_TOKEN: ${{ secrets.GH_TOKEN }}
run: |
git fetch origin "pull/${PR_NUMBER}/head:${PR_BRANCH}"
git checkout "${PR_BRANCH}"
git fetch origin main
if [ "${IS_FORK}" = "true" ] && [ "${CAN_PUSH_FORK}" = "true" ]; then
git remote set-url origin "https://x-access-token:${GH_TOKEN}@github.com/${FORK_REPO}.git"
elif [ "${IS_FORK}" = "true" ]; then
# Block push: trick claude-code-action's `git fetch origin <branch>`
git remote set-url origin "file://$(pwd)"
# 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.check_fork.outputs.can_push_fork == 'true' && secrets.GH_TOKEN || steps.app-token.outputs.token }}
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 }}
model: claude-opus-4-8
trigger_phrase: "@claude"
label_trigger: "claude"
direct_prompt: |
${{ steps.check_fork.outputs.is_fork == 'true' && steps.check_fork.outputs.can_push_fork != 'true' && 'CRITICAL: THIS IS A PULL REQUEST FROM A FORK WITHOUT MAINTAINER EDITS. YOU DO NOT HAVE PUSH PERMISSIONS. ONLY READ FILES, VALIDATE CODE, AND PROVIDE COMMENTS/FEEDBACK ON THIS PR. DO NOT ATTEMPT TO PUSH OR CREATE PULL REQUESTS.\n\n' || (steps.check_fork.outputs.can_push_fork == 'true' && format('NOTE: Fork PR with maintainer edits allowed. Push directly to fork {0} branch {1}.\n\n', steps.check_fork.outputs.fork_repo, steps.check_fork.outputs.pr_branch) || (steps.check_fork.outputs.is_pr == 'true' && steps.check_fork.outputs.is_fork != 'true' && 'NOTE: The branch is under MervinPraison/PraisonAI (not a fork). You are able to make modifications and push directly to this branch.\n\n' || (steps.check_fork.outputs.is_pr != 'true' && 'NOTE: This is an issue (not a PR). Create a new fix branch per STEP 3 below.\n\n' || ''))) }}
${{ steps.check_fork.outputs.is_pr == 'true' && format('CONTEXT: PR #{0} on branch {1}. head.repo={2}, is_fork={3}, can_push_fork={4}, merge_state={5}. NEVER treat cursor/*, claude/* branch names or bot authors as forks — only is_fork=true means fork.\n\n', steps.check_fork.outputs.pr_number, steps.check_fork.outputs.pr_branch, steps.check_fork.outputs.head_repo, steps.check_fork.outputs.is_fork, steps.check_fork.outputs.can_push_fork, steps.check_fork.outputs.merge_state) || '' }}
${{ 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):
@@ -294,29 +216,32 @@ jobs:
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.
AIM: This package must stay LIGHTWEIGHT AND POWERFUL. Do a CRITICAL REVIEW at each stage (issue triage, fix planning, PR review/implementation) and reject scope creep for the sake of adding features. Prefer existing Agent capabilities (instructions/backstory/tools/hooks/memory) over new params/modules/exports. Even when fixing a raised issue, keep the fix minimal and lightweight — do NOT expand the surface area or add knobs with no live consumer.
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 → MervinPraison/PraisonAI-Tools: agent-callable integrations at runtime (Composio, Slack, API/DB connectors). Do NOT implement in praisonaiagents/ — use STEP 3-ALT.
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 → MervinPraison/PraisonAI-Plugins: framework lifecycle extensions (tracing, logging, metrics, hooks, guardrails). Not agent tools — use STEP 3-ALT.
6. Sandbox backends (optional/niche, e.g. Capsule) → PraisonAI-Plugins via `praisonai.sandbox` entry point; core keeps protocol/config/manager only.
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). If it does, reject the change as scope creep and prefer the existing capability — the aim is lightweight and powerful, not more knobs.
- Do not bloat the Agent class with additional params — only if absolutely required; we already support many params.
- 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. PRs with >100 lines added to agent.py require manual review (merge gate will not auto-merge).
- 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.
${{ steps.check_fork.outputs.is_pr == 'true' && (steps.check_fork.outputs.is_fork != 'true' || steps.check_fork.outputs.can_push_fork == 'true') && steps.check_fork.outputs.merge_state == 'DIRTY' && format('STEP 3 — RESOLVE MERGE CONFLICTS ON PR (branch: {0}, PR #{1}{2}):\n- DO NOT create a new branch or PR\n- git fetch origin main && git rebase origin/main\n- Resolve conflicts: keep this PR intent, merge in main newer logic\n- git add -A && git rebase --continue (repeat until done)\n- git push --force-with-lease origin {0}\n- Run targeted pytest on changed paths\n- Comment files resolved and what you skipped\n', steps.check_fork.outputs.pr_branch, steps.check_fork.outputs.pr_number, steps.check_fork.outputs.can_push_fork == 'true' && format(', fork: {0}', steps.check_fork.outputs.fork_repo) || '') || '' }}
${{ steps.check_fork.outputs.is_pr == 'true' && (steps.check_fork.outputs.is_fork != 'true' || steps.check_fork.outputs.can_push_fork == 'true') && steps.check_fork.outputs.merge_state != 'DIRTY' && format('STEP 3 — IMPLEMENT ON EXISTING PR (branch: {0}, PR #{1}{2}):\n- DO NOT create a new branch or PR\n- git checkout {0}\n- Implement minimal, focused fixes from reviewer feedback\n- Follow protocol-driven design: protocols in core SDK, heavy implementations in wrapper\n- Keep changes small and backward-compatible\n- Commit: git add -A && git commit -m "fix: <description>"\n- Push: git push origin {0}\n- Comment a summary of exact files modified and what you skipped\n', steps.check_fork.outputs.pr_branch, steps.check_fork.outputs.pr_number, steps.check_fork.outputs.can_push_fork == 'true' && format(', fork: {0}', steps.check_fork.outputs.fork_repo) || '') || '' }}
${{ steps.check_fork.outputs.is_pr != 'true' && 'STEP 3 — IMPLEMENT (for changes in THIS repo — PraisonAI):\n- Create a fix branch: git checkout -b claude/issue-$ISSUE_NUMBER-$(date +%Y%m%d)\n- Implement a minimal, focused fix\n- Follow protocol-driven design: protocols in core SDK, heavy implementations in wrapper\n- Keep changes small and backward-compatible\n- Commit: git add -A && git commit -m "fix: <description> (fixes #$ISSUE_NUMBER)"\n- Push: git push origin claude/issue-$ISSUE_NUMBER-$(date +%Y%m%d)\nCRITICAL: After pushing, you MUST immediately run: gh pr create --title "fix: <title>" --body "Fixes #$ISSUE_NUMBER" --head claude/issue-$ISSUE_NUMBER-$(date +%Y%m%d)\nDo NOT stop after pushing. Do NOT say "manually create a PR". Always create the PR automatically.\n' || '' }}
STEP 3 — IMPLEMENT (for changes in THIS repo — PraisonAI):
- Create a fix branch: git checkout -b claude/issue-$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.
@@ -342,7 +267,10 @@ jobs:
- For docs changes: verify files exist and are valid markdown/MDX
- Ensure no regressions
${{ steps.check_fork.outputs.is_pr == 'true' && 'STEP 5 — SKIP: Already on an open PR. Do NOT run gh pr create.\n' || 'STEP 5 — CREATE PR:\n- Commit with descriptive message, push, and create PR using `gh pr create`\n- For external repos, use `gh pr create -R MervinPraison/<REPO_NAME>`\nCRITICAL: You MUST create the PR automatically using `gh pr create`. Do NOT just provide a link or say "manual push required".\n' }}
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:*)
@@ -364,60 +292,3 @@ jobs:
mcp__github__get_issue_comments
mcp__github__update_issue
timeout_minutes: 30
- name: Kick review chain for bot-created PR
if: |
steps.check_fork.outputs.is_pr != 'true' &&
(github.event_name == 'issues' || github.event_name == 'issue_comment') &&
github.event.issue != null
uses: actions/github-script@v7
with:
github-token: ${{ secrets.GH_TOKEN }}
script: |
const path = require('path');
const chain = require(path.join(process.env.GITHUB_WORKSPACE, '.github/scripts/bot-pr-review-chain.js'));
const issueNumber = context.payload.issue.number;
await chain.kickReviewChainForIssue(
github, context.repo.owner, context.repo.repo, issueNumber, core
);
- name: Sync pipeline status labels for PR
if: steps.check_fork.outputs.is_pr == 'true'
uses: actions/github-script@v7
with:
github-token: ${{ secrets.GH_TOKEN }}
script: |
const path = require('path');
const ps = require(path.join(process.env.GITHUB_WORKSPACE, '.github/scripts/pipeline-status.js'));
const prNumber = parseInt('${{ steps.check_fork.outputs.pr_number }}', 10);
await ps.ensurePipelineLabels(github, context.repo.owner, context.repo.repo, core);
await ps.syncPipelineLabels(github, context.repo.owner, context.repo.repo, prNumber, core);
- name: Dispatch merge gate when PR pipeline ready
if: steps.check_fork.outputs.is_pr == 'true'
uses: actions/github-script@v7
with:
github-token: ${{ secrets.GH_TOKEN }}
script: |
const path = require('path');
const mergeGate = require(path.join(process.env.GITHUB_WORKSPACE, '.github/scripts/merge-gate.js'));
const owner = context.repo.owner;
const repo = context.repo.repo;
const prNumber = parseInt('${{ steps.check_fork.outputs.pr_number }}', 10);
const check = await mergeGate.evaluatePipelineQuiescent(
github, owner, repo, prNumber, core, {
skipGlobalClaudeRunCheck: true,
skipRecentClaudeCooldown: true,
}
);
if (!check.ready) {
core.info(`PR #${prNumber} not ready for merge gate: ${check.reasons.join(', ')}`);
return;
}
await github.rest.repos.createDispatchEvent({
owner,
repo,
event_type: 'claude-merge-gate',
client_payload: { pr_number: prNumber },
});
core.info(`Dispatched merge gate for PR #${prNumber}`);
@@ -1,77 +0,0 @@
name: Deploy install scripts to praison.ai
# Production praison.ai runs on Hestia (migration-target), not Azure AKS.
# Uses scoped deploy user (praison-deploy) — not root.
on:
push:
branches: [main]
paths:
- 'src/praisonai/scripts/install.sh'
- 'src/praisonai/scripts/install.ps1'
workflow_dispatch:
concurrency:
group: deploy-install-scripts
cancel-in-progress: false
permissions:
contents: read
jobs:
deploy-to-hestia:
runs-on: ubuntu-latest
environment: production-hestia
steps:
- uses: actions/checkout@v4
with:
ref: main
persist-credentials: false
- name: Sync install scripts to Hestia
env:
SSH_PRIVATE_KEY: ${{ secrets.MIGRATION_TARGET_SSH_KEY }}
HESTIA_HOST: ${{ secrets.MIGRATION_TARGET_HOST }}
HESTIA_USER: ${{ secrets.MIGRATION_TARGET_USER }}
HESTIA_KNOWN_HOSTS: ${{ secrets.MIGRATION_TARGET_KNOWN_HOSTS }}
SOURCE_SHA: ${{ github.sha }}
run: |
set -euo pipefail
for var in SSH_PRIVATE_KEY HESTIA_HOST HESTIA_USER; do
if [ -z "${!var:-}" ]; then
echo "Missing secret for deploy (need MIGRATION_TARGET_SSH_KEY, MIGRATION_TARGET_HOST, MIGRATION_TARGET_USER)"
exit 1
fi
done
REMOTE_WEB="/home/hestiaadmin/web/praison.ai/pa/web"
SSH_OPTS="-o BatchMode=yes -o ConnectTimeout=15 -o StrictHostKeyChecking=yes"
mkdir -p ~/.ssh
echo "$SSH_PRIVATE_KEY" > ~/.ssh/id_ed25519
chmod 600 ~/.ssh/id_ed25519
trap 'rm -f ~/.ssh/id_ed25519' EXIT
# Pin host identity via an out-of-band secret (no TOFU/ssh-keyscan).
if [ -z "${HESTIA_KNOWN_HOSTS:-}" ]; then
echo "Missing secret MIGRATION_TARGET_KNOWN_HOSTS (pinned host key). Refusing to deploy without a verified host identity."
exit 1
fi
echo "$HESTIA_KNOWN_HOSTS" > ~/.ssh/known_hosts
chmod 644 ~/.ssh/known_hosts
# Upload to temp files, then atomically move both into place in a
# single remote step to avoid serving truncated or mixed-commit files.
for f in install.sh install.ps1; do
echo "Syncing $f..."
scp $SSH_OPTS "src/praisonai/scripts/$f" "${HESTIA_USER}@${HESTIA_HOST}:${REMOTE_WEB}/.${f}.tmp"
done
ssh $SSH_OPTS "${HESTIA_USER}@${HESTIA_HOST}" \
"mv -f ${REMOTE_WEB}/.install.sh.tmp ${REMOTE_WEB}/install.sh && \
mv -f ${REMOTE_WEB}/.install.ps1.tmp ${REMOTE_WEB}/install.ps1 && \
sudo chown hestiaadmin:hestiaadmin ${REMOTE_WEB}/install.sh ${REMOTE_WEB}/install.ps1 && \
sudo chmod 644 ${REMOTE_WEB}/install.sh ${REMOTE_WEB}/install.ps1"
echo "Deployed install scripts for commit ${SOURCE_SHA}"
echo "Verify: curl -fsSL https://praison.ai/install.ps1 | head -5"
+2
View File
@@ -22,6 +22,8 @@ jobs:
uses: actions/checkout@v4
with:
persist-credentials: false
with:
persist-credentials: false
- name: Set up Docker Buildx
uses: docker/setup-buildx-action@v3
@@ -36,6 +36,9 @@ jobs:
uses: actions/checkout@v4
with:
persist-credentials: false
with:
persist-credentials: false
with:
token: ${{ steps.generate_token.outputs.token }}
- name: Run Gemini Issue Triage
@@ -37,6 +37,9 @@ jobs:
uses: actions/checkout@v4
with:
persist-credentials: false
with:
persist-credentials: false
with:
token: ${{ steps.generate_token.outputs.token }}
- name: Set up Git
+3
View File
@@ -48,6 +48,9 @@ jobs:
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 }}
fetch-depth: 0
+18 -25
View File
@@ -7,18 +7,12 @@ on:
- 'src/praisonai/praisonai/integration/**'
- 'src/praisonai/tests/integration/test_aiui_*'
- 'src/praisonai/pyproject.toml'
- 'src/praisonai-code/**'
- '.github/workflows/integration-cross-repo.yml'
- '.github/actions/install-monorepo-packages/**'
pull_request:
branches: [ main ]
paths:
- 'src/praisonai/praisonai/integration/**'
- 'src/praisonai/tests/integration/test_aiui_*'
- 'src/praisonai/pyproject.toml'
- 'src/praisonai-code/**'
- '.github/workflows/integration-cross-repo.yml'
- '.github/actions/install-monorepo-packages/**'
workflow_dispatch:
jobs:
@@ -46,16 +40,16 @@ jobs:
python-version: '3.11'
- name: Install dependencies
run: python -m pip install --upgrade pip
- uses: PraisonAI/.github/actions/install-monorepo-packages
with:
repo-root: PraisonAI/
wrapper-extras: ".[ui,dev]"
- name: Install PraisonAIUI
run: |
cd PraisonAIUI
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 .
pip install pytest pytest-cov
- name: Verify versions
run: |
@@ -66,16 +60,16 @@ jobs:
- name: Run PraisonAI integration tests
run: |
cd PraisonAI/src/praisonai
python -m pytest tests/integration/test_aiui_* -v
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
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
python -m pytest tests/test_feature_sdk_backends.py -v --timeout=300
fi
- name: Test Pattern C CLI
@@ -143,14 +137,13 @@ jobs:
python-version: '3.11'
- name: Install dependencies
run: python -m pip install --upgrade pip
- uses: PraisonAI/.github/actions/install-monorepo-packages
with:
repo-root: PraisonAI/
wrapper-extras: ".[ui,dev]"
- name: Install PraisonAIUI
run: |
cd PraisonAIUI
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
@@ -159,7 +152,7 @@ jobs:
run: |
cd PraisonAI/src/praisonai
if [ -n "$OPENAI_API_KEY" ]; then
python -m pytest tests/integration/test_aiui_host_agentic.py -v
python -m pytest tests/integration/test_aiui_host_agentic.py -v --timeout=600
else
echo "OPENAI_API_KEY not available, skipping agentic tests"
fi
-185
View File
@@ -1,185 +0,0 @@
name: Auto Merge Conflict → Claude
# Detects internal PRs with mergeStateStatus=DIRTY and posts @claude to trigger claude.yml.
on:
push:
branches: [main]
pull_request:
types: [opened, synchronize, reopened]
workflow_dispatch:
schedule:
- cron: '0 */6 * * *'
concurrency:
group: merge-conflict-scan-${{ github.repository }}-${{ github.event.pull_request.number || github.run_id }}
cancel-in-progress: true
env:
# PAT posts as MervinPraison so issue_comment triggers claude.yml (GITHUB_TOKEN cannot chain workflows)
GH_TOKEN: ${{ secrets.GH_TOKEN || github.token }}
permissions:
pull-requests: write
issues: write
jobs:
detect-and-trigger:
runs-on: ubuntu-latest
steps:
- name: Detect conflicting PRs and trigger Claude
uses: actions/github-script@v7
with:
github-token: ${{ env.GH_TOKEN }}
script: |
const owner = context.repo.owner;
const repo = context.repo.repo;
const baseRepo = `${owner}/${repo}`;
const COOLDOWN_MS = 12 * 60 * 60 * 1000;
const AUTO_ACTORS = ['github-actions[bot]', 'MervinPraison'];
const LABEL = 'claude-conflict-pending';
const COMMENT_BODY = [
'@claude this PR has merge conflicts with `main`.',
'Please rebase onto latest `main`, resolve conflicts (keep this PR\'s intent, merge in newer main logic),',
'run targeted tests, and force-push with `--force-with-lease`.',
'Comment which files you resolved.',
'Do not bloat the Agent class with additional params — only if absolutely required; we already support many params.',
'Keep the resolution minimal — the aim is a lightweight and powerful package; do not introduce scope creep while resolving conflicts.',
].join(' ');
const sleep = (ms) => new Promise((r) => setTimeout(r, ms));
async function getMergeState(prNumber) {
const query = `
query($owner: String!, $repo: String!, $number: Int!) {
repository(owner: $owner, name: $repo) {
pullRequest(number: $number) {
mergeStateStatus
maintainerCanModify
isDraft
headRef { repository { nameWithOwner } }
}
}
}
`;
for (let attempt = 0; attempt < 3; attempt++) {
const result = await github.graphql(query, { owner, repo, number: prNumber });
const prGql = result.repository.pullRequest;
const status = (prGql?.mergeStateStatus || '').toUpperCase();
if (status && status !== 'UNKNOWN') {
return {
status,
isDraft: prGql.isDraft,
headRepo: prGql.headRef?.repository?.nameWithOwner,
maintainerCanModify: prGql.maintainerCanModify === true,
};
}
if (attempt < 2) await sleep(10000);
}
const pr = await github.rest.pulls.get({ owner, repo, pull_number: prNumber });
return {
status: (pr.data.mergeable_state || '').toUpperCase(),
isDraft: pr.data.draft,
headRepo: pr.data.head.repo?.full_name,
maintainerCanModify: pr.data.maintainer_can_modify === true,
};
}
function hasFinalClaudeReviewTrigger(comments) {
return comments.some((c) => {
const body = (c.body || '').toLowerCase();
if (!AUTO_ACTORS.includes(c.user.login)) return false;
if (!body.includes('@claude')) return false;
if (body.includes('merge conflict')) return false;
return body.includes('final architecture reviewer') || body.includes('lead engineer');
});
}
function hasRecentAutoComment(comments) {
const cutoff = Date.now() - COOLDOWN_MS;
return comments.some((c) => {
if (!AUTO_ACTORS.includes(c.user.login)) return false;
const body = (c.body || '').toLowerCase();
if (!body.includes('@claude') || !body.includes('merge conflict')) return false;
return new Date(c.created_at).getTime() > cutoff;
});
}
async function processPR(prNumber) {
const { status, isDraft, headRepo, maintainerCanModify } = await getMergeState(prNumber);
core.info(`PR #${prNumber}: mergeState=${status}, head=${headRepo}, draft=${isDraft}, maintainerCanModify=${maintainerCanModify}`);
const { data: issue } = await github.rest.issues.get({
owner,
repo,
issue_number: prNumber,
});
const labels = issue.labels.map((l) => l.name);
if (status !== 'DIRTY' && labels.includes(LABEL)) {
await github.rest.issues.removeLabel({
owner,
repo,
issue_number: prNumber,
name: LABEL,
});
core.info(`Removed ${LABEL} from PR #${prNumber}`);
}
if (status !== 'DIRTY') return { skipped: true, reason: 'not dirty' };
if (isDraft) return { skipped: true, reason: 'draft' };
if (headRepo && headRepo !== baseRepo && !maintainerCanModify) {
return { skipped: true, reason: 'fork without maintainer edits' };
}
if (labels.includes(LABEL)) {
return { skipped: true, reason: 'conflict resolution pending' };
}
const { data: comments } = await github.rest.issues.listComments({
owner,
repo,
issue_number: prNumber,
per_page: 100,
});
if (hasRecentAutoComment(comments)) {
return { skipped: true, reason: 'recent auto comment' };
}
if (!hasFinalClaudeReviewTrigger(comments)) {
return { skipped: true, reason: 'awaiting final claude review trigger' };
}
await github.rest.issues.addLabels({
owner,
repo,
issue_number: prNumber,
labels: [LABEL],
});
await github.rest.issues.createComment({
owner,
repo,
issue_number: prNumber,
body: COMMENT_BODY,
});
return { triggered: true };
}
let prNumbers = [];
if (context.eventName === 'pull_request') {
prNumbers = [context.payload.pull_request.number];
} else {
const prs = await github.paginate(github.rest.pulls.list, {
owner,
repo,
state: 'open',
per_page: 100,
});
prNumbers = prs.map((p) => p.number);
}
const results = [];
for (const num of prNumbers) {
results.push({ pr: num, ...(await processPR(num)) });
}
core.summary.addRaw('```json\n' + JSON.stringify(results, null, 2) + '\n```');
await core.summary.write();
-144
View File
@@ -1,144 +0,0 @@
name: Nightly Release Gate
# Preflight before PyPI Release (patch bump).
# Triggers: Core Tests success on main (workflow_run) or cron every 3 days at 00:00 UTC.
# Dedupe: max one successful patch release every 3 days (see release-gate.js).
on:
schedule:
- cron: '0 0 */3 * *'
workflow_dispatch:
inputs:
dry_run:
description: 'Run preflight only; do not dispatch pypi-release.yml'
required: false
default: false
type: boolean
workflow_run:
workflows:
- Core Tests
types:
- completed
branches:
- main
permissions:
contents: read
actions: write
concurrency:
group: nightly-release-gate
cancel-in-progress: false
jobs:
preflight:
if: |
github.event_name == 'workflow_dispatch' ||
github.event_name == 'schedule' ||
(
github.event_name == 'workflow_run' &&
github.event.workflow_run.conclusion == 'success' &&
github.event.workflow_run.head_branch == 'main' &&
github.event.workflow_run.event == 'push' &&
!startsWith(github.event.workflow_run.head_commit.message, 'Release v') &&
!startsWith(github.event.workflow_run.head_commit.message, 'chore(release):')
)
runs-on: ubuntu-latest
env:
GH_TOKEN: ${{ secrets.GH_TOKEN }}
steps:
- name: Resolve trigger context
id: ctx
run: |
if [ "${{ github.event_name }}" = "workflow_run" ]; then
echo "checkout_sha=${{ github.event.workflow_run.head_sha }}" >> "$GITHUB_OUTPUT"
echo "source=ci" >> "$GITHUB_OUTPUT"
echo "is_ci=true" >> "$GITHUB_OUTPUT"
else
echo "checkout_sha=main" >> "$GITHUB_OUTPUT"
echo "source=nightly" >> "$GITHUB_OUTPUT"
echo "is_ci=false" >> "$GITHUB_OUTPUT"
fi
- name: Checkout
uses: actions/checkout@34e114876b0b11c390a56381ad16ebd13914f8d5 # v4
with:
ref: ${{ steps.ctx.outputs.checkout_sha }}
fetch-depth: 0
- name: Fetch main and tags
run: git fetch --tags origin main
# Guards the gate logic itself — no workflow ran these selftests before.
- name: Selftest release-gate script
run: node .github/scripts/release-gate-selftest.js
- name: Preflight — path changes, CI SHA, dedupe
id: preflight
uses: actions/github-script@v7
env:
HEAD_SHA: ${{ steps.ctx.outputs.checkout_sha }}
IS_CI: ${{ steps.ctx.outputs.is_ci }}
with:
github-token: ${{ secrets.GH_TOKEN }}
script: |
const path = require('path');
const rg = require(path.join(process.env.GITHUB_WORKSPACE, '.github/scripts/release-gate.js'));
const owner = context.repo.owner;
const repo = context.repo.repo;
const headSha = process.env.HEAD_SHA;
const isCi = process.env.IS_CI === 'true';
const result = await rg.evaluateReleasePreflight(
github, owner, repo,
{ headSha, isCiTrigger: isCi, bump: 'patch' },
core
);
core.setOutput('should_release', result.ready ? 'true' : 'false');
core.setOutput('reason', result.reasons.join('; '));
core.setOutput('head_sha', result.headSha || headSha);
core.setOutput('last_tag', result.lastTag || '');
core.setOutput('target_agents', result.targetAgents || '');
core.setOutput('target_code', result.targetCode || '');
core.setOutput('target_wrapper', result.targetWrapper || '');
core.summary.addRaw('## Release gate preflight\n');
core.summary.addRaw(`Ready: ${result.ready}\n`);
core.summary.addRaw(`Reason: ${result.reasons.join('; ')}\n`);
if (result.targetAgents) {
core.summary.addRaw(
`Targets: praisonaiagents==${result.targetAgents}, `
+ `praisonai-code==${result.targetCode}, praisonai==${result.targetWrapper}\n`
);
}
await core.summary.write();
if (!result.ready) {
core.info(`Skip release: ${result.reasons.join('; ')}`);
}
- name: Dry run summary
if: inputs.dry_run == true
run: |
echo "Dry run — preflight only, no pypi-release dispatch."
echo "should_release=${{ steps.preflight.outputs.should_release }}"
echo "reason=${{ steps.preflight.outputs.reason }}"
- name: Dispatch PyPI Release (patch)
if: steps.preflight.outputs.should_release == 'true' && inputs.dry_run != true
run: |
set -euo pipefail
gh workflow run pypi-release.yml \
--repo "${GITHUB_REPOSITORY}" \
--ref main \
-f bump=patch \
-f source=${{ steps.ctx.outputs.source }} \
-f trigger_sha=${{ steps.preflight.outputs.head_sha }} \
-f dry_run=false
echo "Dispatched pypi-release.yml (patch, source=${{ steps.ctx.outputs.source }})"
if [ "${{ steps.ctx.outputs.source }}" = "ci" ]; then
echo "Uses pypi-auto environment (no manual approval)."
else
echo "Uses pypi-auto environment for nightly patch releases."
fi
@@ -1,42 +0,0 @@
name: Pipeline Status Sync
# Sync pipeline/* stage and blocker labels on open internal PRs.
on:
schedule:
- cron: '*/10 * * * *'
workflow_dispatch:
permissions:
pull-requests: read
issues: write
actions: write
id-token: write
jobs:
sync:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v4
with:
persist-credentials: false
- name: Generate GitHub App token
id: app-token
uses: actions/create-github-app-token@v1
with:
app-id: ${{ secrets.CLAUDE_APP_ID }}
private-key: ${{ secrets.CLAUDE_APP_PRIVATE_KEY }}
owner: ${{ github.repository_owner }}
- name: Sync pipeline labels on open PRs
uses: actions/github-script@v7
with:
github-token: ${{ steps.app-token.outputs.token }}
script: |
const path = require('path');
const ps = require(path.join(process.env.GITHUB_WORKSPACE, '.github/scripts/pipeline-status.js'));
await ps.syncOpenPullRequests(
github, context.repo.owner, context.repo.repo,
{ maxPrs: 30, dispatchMergeGate: true }, core
);
+4 -6
View File
@@ -49,12 +49,10 @@ jobs:
git config --local user.name "PraisonAI Bot"
- name: Install PraisonAI
run: pip install uv
- uses: ./.github/actions/install-monorepo-packages
with:
use-uv: "true"
agents-extras: ".[all]"
wrapper-extras: ".[all]"
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:
+10 -14
View File
@@ -16,20 +16,16 @@ jobs:
review:
runs-on: ubuntu-latest
if: >
secrets.PRAISONAI_APP_ID != '' &&
secrets.PRAISONAI_APP_PRIVATE_KEY != '' &&
(
(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'))
)
(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
File diff suppressed because it is too large. Load diff
+5 -7
View File
@@ -15,8 +15,8 @@ jobs:
steps:
- uses: actions/checkout@v4
with:
persist-credentials: false
with:
persist-credentials: false
- name: Set up Python ${{ matrix.python-version }}
uses: actions/setup-python@v5
with:
@@ -30,12 +30,10 @@ jobs:
echo "PYTHONPATH=${{ github.workspace }}/src/praisonai-agents:$PYTHONPATH" >> $GITHUB_ENV
- name: Install dependencies
run: python -m pip install --upgrade pip
- uses: ./.github/actions/install-monorepo-packages
with:
wrapper-extras: ".[ui,gradio,api,agentops,google,openai,anthropic,cohere,chat,code,realtime,call,crewai,autogen]"
- name: Install test tools
run: |
cd src/praisonai
python -m pip install --upgrade pip
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 "praisonaiagents[knowledge]"
+2 -5
View File
@@ -8,18 +8,15 @@
name: Upload Python Package
# Superseded by pypi-release.yml (manual workflow_dispatch with uv publish).
# Kept as workflow_dispatch-only fallback; release trigger removed to avoid
# duplicate PyPI publish when bump_and_release creates a GitHub release.
on:
workflow_dispatch:
release:
types: [published]
permissions:
contents: read
jobs:
deploy:
if: false
runs-on: ubuntu-latest
+12 -3
View File
@@ -26,8 +26,11 @@ 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:
persist-credentials: false
repository: MervinPraison/PraisonAI
ref: ${{ github.event.inputs.tag }}
fetch-depth: 0
@@ -45,8 +48,11 @@ jobs:
# Now checkout the fork at main branch
- name: Checkout fork
uses: actions/checkout@v4
with:
persist-credentials: false
with:
persist-credentials: false
with:
persist-credentials: false
repository: ${{ github.event.inputs.fork_owner }}/PraisonAI
ref: main
fetch-depth: 0
@@ -443,8 +449,11 @@ 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:
persist-credentials: false
fetch-depth: 0
token: ${{ secrets.PAT_TOKEN }}
repository: ${{ github.event.inputs.fork_owner }}/PraisonAI
@@ -1,41 +0,0 @@
name: Sync Claude Secrets
on:
workflow_dispatch:
inputs:
target_repo:
description: 'Destination repo (owner/name)'
required: true
default: 'MervinPraison/PraisonAIUI'
type: string
permissions:
contents: read
jobs:
sync:
runs-on: ubuntu-latest
steps:
- name: Sync Claude secrets
env:
GH_TOKEN: ${{ secrets.SECRETS_ADMIN_PAT }}
TARGET: ${{ inputs.target_repo }}
CLAUDE_APP_ID: ${{ secrets.CLAUDE_APP_ID }}
CLAUDE_APP_PRIVATE_KEY: ${{ secrets.CLAUDE_APP_PRIVATE_KEY }}
CLAUDE_CODE_OAUTH_TOKEN: ${{ secrets.CLAUDE_CODE_OAUTH_TOKEN }}
GH_TOKEN_VALUE: ${{ secrets.GH_TOKEN }}
DOCS_GITHUB_TOKEN: ${{ secrets.SECRETS_ADMIN_PAT }}
run: |
set -euo pipefail
if [ -z "${GH_TOKEN:-}" ]; then
echo "SECRETS_ADMIN_PAT is not configured in this repository"
exit 1
fi
echo -n "$CLAUDE_APP_ID" | gh secret set CLAUDE_APP_ID --repo "$TARGET"
echo -n "$CLAUDE_APP_PRIVATE_KEY" | gh secret set CLAUDE_APP_PRIVATE_KEY --repo "$TARGET"
echo -n "$CLAUDE_CODE_OAUTH_TOKEN" | gh secret set CLAUDE_CODE_OAUTH_TOKEN --repo "$TARGET"
echo -n "$GH_TOKEN_VALUE" | gh secret set GH_TOKEN --repo "$TARGET"
if [ -n "${DOCS_GITHUB_TOKEN:-}" ]; then
echo -n "$DOCS_GITHUB_TOKEN" | gh secret set DOCS_GITHUB_TOKEN --repo "$TARGET"
fi
echo "Synced CLAUDE_APP_ID, CLAUDE_APP_PRIVATE_KEY, CLAUDE_CODE_OAUTH_TOKEN, GH_TOKEN → $TARGET"
@@ -1,47 +0,0 @@
name: Terminal-Bench Smoke
# Manual (and optional weekly) smoke run of the `praisonai code` assistant on a
# small verified Terminal-Bench 2.1 subset via the Harbor harness.
# Never runs on PRs — it costs money (LLM calls) and is inherently flaky.
on:
workflow_dispatch:
schedule:
- cron: "0 6 * * 1" # Mondays 06:00 UTC
permissions:
contents: read
jobs:
smoke:
runs-on: ubuntu-latest
timeout-minutes: 45
steps:
- uses: actions/checkout@v4
- uses: actions/setup-python@v5
with:
python-version: "3.11"
- name: Install Harbor + PraisonAI
run: |
python -m pip install --upgrade pip
pip install harbor
pip install -e src/praisonai-agents -e src/praisonai
- name: Run Terminal-Bench 2.1 smoke subset
env:
OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }}
PYTHONPATH: .
run: |
harbor run -c examples/terminal_bench/job_code_smoke.yaml || true
- name: Upload Harbor results
if: always()
uses: actions/upload-artifact@v4
with:
name: harbor-results
path: |
runs/
**/results.json
if-no-files-found: warn
+7 -6
View File
@@ -37,8 +37,10 @@ jobs:
steps:
- name: Checkout code
uses: actions/checkout@v4
with:
persist-credentials: false
with:
persist-credentials: false
with:
persist-credentials: false
- name: Set up Python ${{ matrix.python-version }}
uses: actions/setup-python@v5
@@ -53,13 +55,12 @@ jobs:
- 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-benchmark pytest-timeout
# Install knowledge dependencies from praisonai-agents
uv pip install --system "praisonaiagents[knowledge]"
- uses: ./.github/actions/install-monorepo-packages
with:
use-uv: "true"
wrapper-extras: ".[ui,gradio,api,agentops,google,openai,anthropic,cohere,chat,code,realtime,call,crewai,autogen]"
- name: Verify environment variables
run: |
+52 -302
View File
@@ -5,320 +5,70 @@ on:
branches: [ main, develop ]
paths:
- 'src/**'
- 'src/praisonai-deploy/infra/**'
- 'src/praisonai-bot/infra/**'
- 'scripts/check_helm_charts.sh'
- 'pyproject.toml'
- '.github/workflows/test-core.yml'
- '.github/actions/install-monorepo-packages/**'
pull_request:
branches: [ main, develop ]
paths:
- 'src/**'
- 'src/praisonai-deploy/infra/**'
- 'src/praisonai-bot/infra/**'
- 'scripts/check_helm_charts.sh'
- 'pyproject.toml'
- '.github/workflows/test-core.yml'
- '.github/actions/install-monorepo-packages/**'
workflow_dispatch:
permissions:
contents: read
env:
PYTHONPATH: ${{ github.workspace }}/src/praisonai-agents
PRAISONAI_ALLOW_NETWORK: '0'
PRAISONAI_LIVE_TESTS: '0'
PRAISONAI_TEST_TIER: main
jobs:
test-core-collect:
name: test-core-collect
runs-on: ubuntu-latest
timeout-minutes: 5
steps:
- uses: actions/checkout@v4
with:
persist-credentials: false
- name: Set up Python 3.11
uses: actions/setup-python@v5
with:
python-version: '3.11'
- name: Install UV
run: |
curl -LsSf https://astral.sh/uv/install.sh | sh
echo "$HOME/.local/bin" >> $GITHUB_PATH
- name: Install dependencies
run: |
cd src/praisonai
uv pip install --system duckduckgo_search
uv pip install --system pytest pytest-asyncio pytest-timeout pytest-xdist
uv pip install --system "praisonaiagents[knowledge]"
- uses: ./.github/actions/install-monorepo-packages
with:
use-uv: "true"
wrapper-extras: ".[ui,gradio,api,agentops,google,openai,anthropic,cohere,chat,code,realtime,call,crewai,autogen]"
- name: Set environment variables
run: |
echo "OPENAI_API_KEY=${{ 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=gpt-4o-mini" >> $GITHUB_ENV
echo "PYTHONPATH=${{ github.workspace }}/src/praisonai-agents:$PYTHONPATH" >> $GITHUB_ENV
- name: Verify unit test collection
shell: bash
run: |
set -euo pipefail
cd src/praisonai
python -m pytest tests/unit/ \
-m "not provider_anthropic and not provider_google and not provider_ollama and not provider_grok_xai and not provider_groq and not provider_cohere" \
--ignore=tests/fixtures \
--collect-only -q --disable-warnings
test-core-unit:
name: test-core (${{ matrix.shard }})
needs: test-core-collect
runs-on: ubuntu-latest
timeout-minutes: 30
strategy:
fail-fast: false
matrix:
include:
- shard: cli
paths: >-
tests/unit/cli/
tests/unit/tui/
extra_ignore: --ignore=tests/unit/cli/test_message_queue.py
- shard: bots-gateway
workdir: src/praisonai-bot
paths: >-
tests/unit/bots/
tests/unit/gateway/
tests/unit/cli/
tests/unit/daemon/
extra_ignore: ""
pythonpath: >-
${{ github.workspace }}/src/praisonai-agents:${{ github.workspace }}/src/praisonai-code
- shard: train
workdir: src/praisonai-train
paths: >-
tests/unit/train/
extra_ignore: ""
pythonpath: >-
${{ github.workspace }}/src/praisonai-agents:${{ github.workspace }}/src/praisonai-code
- shard: mcp
workdir: src/praisonai-mcp
paths: >-
tests/mcp_server/
extra_ignore: ""
pythonpath: >-
${{ github.workspace }}/src/praisonai-agents
- shard: sandbox
workdir: src/praisonai-sandbox
paths: >-
tests/
extra_ignore: ""
pythonpath: >-
${{ github.workspace }}/src/praisonai-agents
- shard: deploy
workdir: src/praisonai-deploy
paths: >-
tests/
extra_ignore: ""
pythonpath: >-
${{ github.workspace }}/src/praisonai-agents
- shard: subdirs
paths: >-
tests/unit/scheduler/
tests/unit/integrations/
tests/unit/mcp/
tests/unit/knowledge/
tests/unit/llm/
tests/unit/doctor/
tests/unit/code/
tests/unit/acp/
tests/unit/agent/
tests/unit/tools/
tests/unit/persistence/
tests/unit/security/
tests/unit/recipe/
tests/unit/storage/
tests/unit/rag/
tests/unit/replay/
tests/unit/escalation/
tests/unit/orchestration/
tests/unit/dev/
tests/unit/_dev/
tests/unit/context/
tests/unit/adapters/
tests/unit/templates/
tests/unit/suite_runner/
tests/unit/standardise/
extra_ignore: ""
- shard: root
paths: ""
extra_ignore: ""
root_glob: "true"
steps:
- uses: actions/checkout@v4
with:
persist-credentials: false
- name: Set up Python 3.11
uses: actions/setup-python@v5
with:
python-version: '3.11'
- name: Install UV
run: |
curl -LsSf https://astral.sh/uv/install.sh | sh
echo "$HOME/.local/bin" >> $GITHUB_PATH
- name: Install dependencies
run: |
cd src/praisonai
uv pip install --system duckduckgo_search
uv pip install --system pytest pytest-asyncio pytest-timeout pytest-xdist
uv pip install --system "praisonaiagents[knowledge]"
- uses: ./.github/actions/install-monorepo-packages
with:
use-uv: "true"
wrapper-extras: ".[ui,gradio,api,agentops,google,openai,anthropic,cohere,chat,code,realtime,call,crewai,autogen]"
- name: Set environment variables
run: |
echo "OPENAI_API_KEY=${{ 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=gpt-4o-mini" >> $GITHUB_ENV
echo "PYTHONPATH=${{ github.workspace }}/src/praisonai-agents:$PYTHONPATH" >> $GITHUB_ENV
- name: Run unit shard
shell: bash
run: |
set -euo pipefail
WORKDIR="${{ matrix.workdir || 'src/praisonai' }}"
if [ "$WORKDIR" = "src/praisonai-sandbox" ]; then
bash "$GITHUB_WORKSPACE/scripts/check_c13_sandbox_imports.sh"
fi
if [ "$WORKDIR" = "src/praisonai-deploy" ]; then
bash "$GITHUB_WORKSPACE/scripts/check_c14_deploy_imports.sh"
fi
if [ "$WORKDIR" = "src/praisonai-mcp" ]; then
bash "$GITHUB_WORKSPACE/scripts/check_c12_mcp_imports.sh"
fi
cd "$WORKDIR"
if [ -n "${{ matrix.pythonpath || '' }}" ]; then
export PYTHONPATH="${{ matrix.pythonpath }}:${PYTHONPATH:-}"
fi
PYTEST_ARGS=(
-m "not slow and not network and not local_service and 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 --disable-warnings
--timeout=60 -n 2 --dist loadfile
--ignore=tests/fixtures
--ignore=tests/e2e
--ignore=tests/live
--ignore=tests/unit/test_langflow_components.py
)
if [ "${{ matrix.root_glob || 'false' }}" = "true" ]; then
shopt -s nullglob
ROOT_TESTS=(tests/unit/test_*.py)
shopt -u nullglob
EXCLUDE=(tests/unit/test_langflow_components.py)
FILTERED=()
for t in "${ROOT_TESTS[@]}"; do
skip=false
for e in "${EXCLUDE[@]}"; do
if [ "$t" = "$e" ]; then skip=true; break; fi
done
if [ "$skip" = false ]; then FILTERED+=("$t"); fi
done
if [ ${#FILTERED[@]} -eq 0 ]; then
echo "No root unit tests matched"
exit 0
fi
python -m pytest "${FILTERED[@]}" "${PYTEST_ARGS[@]}"
else
python -m pytest ${{ matrix.paths }} "${PYTEST_ARGS[@]}" ${{ matrix.extra_ignore }}
fi
test-core-integration:
name: test-core-integration
needs: test-core-unit
runs-on: ubuntu-latest
timeout-minutes: 25
steps:
- uses: actions/checkout@v4
with:
persist-credentials: false
- name: Set up Python 3.11
uses: actions/setup-python@v5
with:
python-version: '3.11'
- name: Install UV
run: |
curl -LsSf https://astral.sh/uv/install.sh | sh
echo "$HOME/.local/bin" >> $GITHUB_PATH
- name: Install dependencies
run: |
uv pip install --system duckduckgo_search
uv pip install --system pytest pytest-asyncio pytest-timeout
uv pip install --system "praisonaiagents[knowledge]"
- uses: ./.github/actions/install-monorepo-packages
with:
use-uv: "true"
wrapper-extras: ".[ui,gradio,api,agentops,google,openai,anthropic,cohere,chat,code,realtime,call,crewai,autogen]"
- name: Set environment variables
run: |
echo "OPENAI_API_KEY=${{ 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=gpt-4o-mini" >> $GITHUB_ENV
echo "PYTHONPATH=${{ github.workspace }}/src/praisonai-agents:$PYTHONPATH" >> $GITHUB_ENV
- name: Run integration tests
shell: bash
run: |
set -euo pipefail
cd src/praisonai
python -m pytest tests/integration/ \
-m "not slow and not network and not local_service and not provider_anthropic and not provider_google and not provider_ollama and not provider_grok_xai and not provider_groq and not provider_cohere" \
-q --tb=line --disable-warnings \
--timeout=120 \
--ignore=tests/fixtures \
--ignore=tests/e2e \
--ignore=tests/live \
--ignore=tests/integration/test_tracker_complex_tasks.py \
--ignore=tests/integration/test_serve_integration.py
helm-charts:
name: helm-charts
runs-on: ubuntu-latest
timeout-minutes: 5
steps:
- uses: actions/checkout@v4
with:
persist-credentials: false
- name: Setup Helm
uses: azure/setup-helm@v3
with:
version: v3.14.4
- name: Lint and template Helm charts
shell: bash
run: |
set -euo pipefail
bash "$GITHUB_WORKSPACE/scripts/check_helm_charts.sh"
test-core:
name: test-core
needs: [test-core-collect, test-core-unit, test-core-integration, helm-charts]
if: always()
runs-on: ubuntu-latest
timeout-minutes: 5
timeout-minutes: 20
steps:
- name: Report Core Tests result
shell: bash
- 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 UV
run: |
set -euo pipefail
collect='${{ needs.test-core-collect.result }}'
unit='${{ needs.test-core-unit.result }}'
integration='${{ needs.test-core-integration.result }}'
helm='${{ needs.helm-charts.result }}'
echo "collect=$collect unit=$unit integration=$integration helm=$helm"
if [ "$collect" != "success" ] || [ "$unit" != "success" ] || [ "$integration" != "success" ] || [ "$helm" != "success" ]; then
echo "Core Tests failed"
exit 1
fi
echo "Core Tests passed"
curl -LsSf https://astral.sh/uv/install.sh | sh
echo "$HOME/.local/bin" >> $GITHUB_PATH
- name: Install dependencies
run: |
cd src/praisonai
uv pip install --system ."[ui,gradio,api,agentops,google,openai,anthropic,cohere,chat,code,realtime,call,crewai,autogen]"
uv pip install --system duckduckgo_search
uv pip install --system pytest pytest-asyncio pytest-cov pytest-timeout
uv pip install --system "praisonaiagents[knowledge]"
- name: Set environment variables
run: |
echo "OPENAI_API_KEY=${{ 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' }}" >> $GITHUB_ENV
echo "PYTHONPATH=${{ github.workspace }}/src/praisonai-agents:$PYTHONPATH" >> $GITHUB_ENV
- 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"
continue-on-error: true
- 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"
- name: Upload coverage to Codecov
if: always()
uses: codecov/codecov-action@v5
with:
token: ${{ secrets.CODECOV_TOKEN || '' }}
files: src/praisonai/coverage.xml
flags: core-tests
fail_ci_if_error: false
+14 -12
View File
@@ -13,8 +13,10 @@ jobs:
steps:
- name: Checkout code
uses: actions/checkout@v4
with:
persist-credentials: false
with:
persist-credentials: false
with:
persist-credentials: false
- name: Set up Python
uses: actions/setup-python@v5
@@ -29,12 +31,11 @@ jobs:
- 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
# Install knowledge dependencies from praisonai-agents
uv pip install --system "praisonaiagents[knowledge]"
- uses: ./.github/actions/install-monorepo-packages
with:
use-uv: "true"
wrapper-extras: ".[ui,gradio,api,agentops,google,openai,anthropic,cohere,chat,code,realtime,call,crewai,autogen]"
- name: Set environment variables
run: |
@@ -80,8 +81,10 @@ jobs:
steps:
- name: Checkout code
uses: actions/checkout@v4
with:
persist-credentials: false
with:
persist-credentials: false
with:
persist-credentials: false
- name: Set up Python
uses: actions/setup-python@v5
@@ -96,12 +99,11 @@ jobs:
- 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 pytest pytest-benchmark
# Install knowledge dependencies from praisonai-agents
uv pip install --system "praisonaiagents[knowledge]"
- uses: ./.github/actions/install-monorepo-packages
with:
use-uv: "true"
wrapper-extras: ".[ui,gradio,api,agentops,google,openai,anthropic,cohere,chat,code,realtime,call,crewai,autogen]"
- name: Set environment variables
run: |
+6 -6
View File
@@ -33,8 +33,10 @@ jobs:
steps:
- name: Checkout code
uses: actions/checkout@v4
with:
persist-credentials: false
with:
persist-credentials: false
with:
persist-credentials: false
- name: Set up Python ${{ matrix.python-version }}
uses: actions/setup-python@v5
@@ -49,12 +51,10 @@ jobs:
- 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
- uses: ./.github/actions/install-monorepo-packages
with:
use-uv: "true"
wrapper-extras: ".[ui,gradio,api,agentops,google,openai,anthropic,cohere,chat,code,realtime,call,crewai,autogen]"
- name: Set environment variables
run: |
+61 -344
View File
@@ -42,11 +42,11 @@ jobs:
# ============================================
smoke:
runs-on: ubuntu-latest
timeout-minutes: 12
timeout-minutes: 5
steps:
- uses: actions/checkout@v4
with:
persist-credentials: false
with:
persist-credentials: false
- name: Set up Python 3.11
uses: actions/setup-python@v5
with:
@@ -64,233 +64,28 @@ jobs:
- 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
- uses: ./.github/actions/install-monorepo-packages
with:
agents-extras: ".[all]"
wrapper-extras: ".[chat,code]"
- name: Run Smoke Tests
env:
PRAISONAI_TEST_TIER: smoke
PRAISONAI_ALLOW_NETWORK: '0'
OPENAI_MODEL_NAME: gpt-4o-mini
shell: bash
run: |
set -euo pipefail
cd src/praisonai
python -m pytest tests/unit/test_c5_backward_compat.py \
tests/unit/test_c7_1_boundaries.py \
tests/unit/test_c9_backward_compat.py \
tests/unit/test_c9_1_boundaries.py \
tests/unit/test_c11_browser_backward_compat.py \
tests/unit/test_c12_mcp_backward_compat.py \
tests/unit/test_c13_sandbox_backward_compat.py \
tests/unit/test_c14_deploy_backward_compat.py \
-q --tb=line --timeout=30 --maxfail=5
# Run only CLI tests for smoke - fast and critical path
python -m pytest tests/unit/cli/ \
../praisonai-bot/tests/unit/cli/test_onboard_command.py \
../praisonai-bot/tests/unit/cli/test_onboard_non_interactive.py \
-m "not slow and not network" \
-q --tb=line \
--timeout=30 \
--ignore=tests/fixtures \
--ignore=tests/unit/cli/test_message_queue.py \
--maxfail=5
- name: Standalone praisonai-code import smoke
shell: bash
run: |
set -euo pipefail
python -m venv /tmp/praisonai-code-standalone
/tmp/praisonai-code-standalone/bin/pip install -q -e src/praisonai-agents -e src/praisonai-code
/tmp/praisonai-code-standalone/bin/python -c "
import praisonai_code
from praisonai_code.cli.configuration.resolver import ConfigResolver
from praisonai_code._version import get_package_version
from praisonai_code.llm.credentials import is_configured
from praisonai_code.llm.catalogue import ModelCatalogue
import toml
assert hasattr(ConfigResolver, '__name__')
assert callable(is_configured)
assert ModelCatalogue().list_models(provider='openai')
import praisonai_code.cli.main
import praisonai_code.cli.app
from praisonai_code.tool_resolver import ToolResolver
assert ToolResolver is not None
print('standalone ok', get_package_version(), 'toml', toml.__version__)
"
/tmp/praisonai-code-standalone/bin/praisonai-code --version
/tmp/praisonai-code-standalone/bin/praisonai-code run --help
cd src/praisonai-code
for f in praisonai_code/cli/main.py praisonai_code/cli/app.py \
praisonai_code/cli/commands/run.py praisonai_code/cli/commands/chat.py \
praisonai_code/cli/commands/code.py; do
if grep -E '^from praisonai\.|^import praisonai' "$f"; then
echo "FAIL: module-level wrapper import in $f"
exit 1
fi
done
echo "C7 hot-path import gate ok"
bash "$GITHUB_WORKSPACE/scripts/check_c7_imports.sh"
# Standalone actions run (no wrapper); default run/chat require praisonai
set +e
RUN_OUT=$(timeout 90 /tmp/praisonai-code-standalone/bin/praisonai-code run --output actions "Say hello in one word" 2>&1)
RUN_CODE=$?
set -e
echo "$RUN_OUT" | tail -20
if echo "$RUN_OUT" | grep -qE 'ImportError|ModuleNotFoundError: No module named .praisonai'; then
echo "FAIL: standalone actions run hit wrapper import error"
exit 1
fi
echo "standalone actions run import gate ok (exit $RUN_CODE)"
set +e
DEFAULT_RUN=$(timeout 15 /tmp/praisonai-code-standalone/bin/praisonai-code run "hi" 2>&1)
set -e
echo "$DEFAULT_RUN" | tail -10
if ! echo "$DEFAULT_RUN" | grep -qi 'install praisonai'; then
echo "FAIL: default run should prompt for praisonai wrapper install"
exit 1
fi
echo "default run wrapper gate ok"
set +e
CHAT_RUN=$(timeout 10 /tmp/praisonai-code-standalone/bin/praisonai-code chat 2>&1)
set -e
echo "$CHAT_RUN" | tail -10
if ! echo "$CHAT_RUN" | grep -qi 'install praisonai'; then
echo "FAIL: chat should prompt for praisonai wrapper install"
exit 1
fi
echo "chat wrapper gate ok"
- name: Standalone praisonai-bot smoke (C9)
run: |
set -euo pipefail
python -m venv /tmp/praisonai-bot-standalone
/tmp/praisonai-bot-standalone/bin/pip install -q -e src/praisonai-agents -e src/praisonai-bot
/tmp/praisonai-bot-standalone/bin/python -c "
from praisonai_bot._version import __version__ as pkg_version
import praisonai_bot
from praisonai_bot.bots import Bot
from praisonai_bot.bots._registry import resolve_adapter
from praisonai_bot.scheduler.executor import ScheduledAgentExecutor
from praisonai_bot.gateway import WebSocketGateway
assert praisonai_bot.__version__ == pkg_version
telegram = resolve_adapter('telegram')
assert telegram.__name__ == 'TelegramBot'
assert telegram.__module__.startswith('praisonai_bot.bots.')
assert ScheduledAgentExecutor.__module__.startswith('praisonai_bot.')
print('bot standalone ok', praisonai_bot.__version__, telegram.__name__)
"
/tmp/praisonai-bot-standalone/bin/praisonai-bot --help
bash "$GITHUB_WORKSPACE/scripts/check_c9_bot_imports.sh"
bash "$GITHUB_WORKSPACE/scripts/check_bot_code_imports.sh"
/tmp/praisonai-bot-standalone/bin/python -c "
import praisonai_bot.cli.commands.bot as bot_cmd
import praisonai_bot.cli.commands.gateway as gw_cmd
print('bot command modules import ok', bot_cmd.app, gw_cmd.app)
"
- name: Standalone praisonai-train smoke (C10)
run: |
set -euo pipefail
python -m venv /tmp/praisonai-train-standalone
/tmp/praisonai-train-standalone/bin/pip install -q -e src/praisonai-agents -e src/praisonai-train
/tmp/praisonai-train-standalone/bin/python -c "
import sys
from praisonai_train._version import __version__ as pkg_version
import praisonai_train
assert praisonai_train.__version__ == pkg_version
trainer_cls = praisonai_train.AgentTrainer
scenario_cls = praisonai_train.TrainingScenario
assert trainer_cls.__module__.startswith('praisonai_train.')
for heavy in ('torch', 'unsloth', 'trl', 'datasets'):
assert heavy not in sys.modules, f'{heavy} imported eagerly'
print('train standalone ok', praisonai_train.__version__, trainer_cls.__name__)
"
/tmp/praisonai-train-standalone/bin/praisonai-train --help
/tmp/praisonai-train-standalone/bin/python -c "
import praisonai_train.cli.commands.train as train_cmd
print('train command module imports ok', train_cmd.app)
"
bash "$GITHUB_WORKSPACE/scripts/check_c10_train_imports.sh"
- name: Standalone praisonai-browser smoke (C11)
run: |
set -euo pipefail
python -m venv /tmp/praisonai-browser-standalone
/tmp/praisonai-browser-standalone/bin/pip install -q -e src/praisonai-agents -e src/praisonai-browser
/tmp/praisonai-browser-standalone/bin/python -c "
import sys
from praisonai_browser._version import __version__ as pkg_version
import praisonai_browser
assert praisonai_browser.__version__ == pkg_version
server_cls = praisonai_browser.BrowserServer
assert server_cls.__name__ == 'BrowserServer'
for heavy in ('fastapi', 'uvicorn', 'playwright'):
assert heavy not in sys.modules, f'{heavy} imported eagerly'
print('browser standalone ok', praisonai_browser.__version__, server_cls.__name__)
"
/tmp/praisonai-browser-standalone/bin/praisonai-browser --help
bash "$GITHUB_WORKSPACE/scripts/check_c11_browser_imports.sh"
python -m pytest src/praisonai-browser/tests/browser/test_protocol_compliance.py -q -m "not network"
- name: Standalone praisonai-mcp smoke (C12)
run: |
set -euo pipefail
python -m venv /tmp/praisonai-mcp-standalone
/tmp/praisonai-mcp-standalone/bin/pip install -q -e src/praisonai-agents -e src/praisonai-mcp
/tmp/praisonai-mcp-standalone/bin/python -c "
import sys
from praisonai_mcp._version import __version__ as pkg_version
import praisonai_mcp
assert praisonai_mcp.__version__ == pkg_version
for heavy in ('fastapi', 'uvicorn'):
assert heavy not in sys.modules, f'{heavy} imported eagerly'
print('mcp standalone ok', praisonai_mcp.__version__)
"
/tmp/praisonai-mcp-standalone/bin/praisonai-mcp --help
bash "$GITHUB_WORKSPACE/scripts/check_c12_mcp_imports.sh"
python -m pytest src/praisonai-mcp/tests/mcp_server -q -m "not network"
- name: Standalone praisonai-sandbox smoke (C13)
run: |
set -euo pipefail
python -m venv /tmp/praisonai-sandbox-standalone
/tmp/praisonai-sandbox-standalone/bin/pip install -q -e src/praisonai-agents -e src/praisonai-sandbox
/tmp/praisonai-sandbox-standalone/bin/python -c "
from praisonai_sandbox._version import __version__ as pkg_version
import praisonai_sandbox
assert praisonai_sandbox.__version__ == pkg_version
for heavy in ('docker', 'modal', 'e2b'):
assert heavy not in __import__('sys').modules
print('sandbox standalone ok', praisonai_sandbox.__version__)
"
/tmp/praisonai-sandbox-standalone/bin/praisonai-sandbox --help
bash "$GITHUB_WORKSPACE/scripts/check_c13_sandbox_imports.sh"
python -m pytest src/praisonai-sandbox/tests -q -m "not network"
- name: Standalone praisonai-deploy smoke (C14)
run: |
set -euo pipefail
python -m venv /tmp/praisonai-deploy-standalone
/tmp/praisonai-deploy-standalone/bin/pip install -q -e src/praisonai-agents -e src/praisonai-deploy
/tmp/praisonai-deploy-standalone/bin/python -c "
from praisonai_deploy._version import __version__ as pkg_version
import praisonai_deploy
assert praisonai_deploy.__version__ == pkg_version
assert 'main' not in __import__('sys').modules
print('deploy standalone ok', praisonai_deploy.__version__)
"
/tmp/praisonai-deploy-standalone/bin/praisonai-deploy --help
bash "$GITHUB_WORKSPACE/scripts/check_c14_deploy_imports.sh"
python -m pytest src/praisonai-deploy/tests -q -m "not network"
- name: Audit hybrid module imports (C8 full stack)
run: |
set -euo pipefail
pip install -q -e src/praisonai-agents -e src/praisonai-code -e src/praisonai-bot -e src/praisonai-train -e src/praisonai-browser -e src/praisonai-mcp -e src/praisonai-sandbox -e src/praisonai-deploy -e src/praisonai
python scripts/audit_hybrid_modules.py
--maxfail=5 \
|| echo "Some smoke tests failed"
- name: Smoke Test Summary
if: always()
@@ -303,15 +98,15 @@ jobs:
main:
needs: smoke
runs-on: ubuntu-latest
timeout-minutes: 30
timeout-minutes: 10
strategy:
matrix:
python-version: ['3.11']
steps:
- uses: actions/checkout@v4
with:
persist-credentials: false
with:
persist-credentials: false
- name: Set up Python ${{ matrix.python-version }}
uses: actions/setup-python@v5
with:
@@ -329,37 +124,36 @@ jobs:
- 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
- uses: ./.github/actions/install-monorepo-packages
with:
agents-extras: ".[all]"
wrapper-extras: ".[crewai,autogen,ui,chat]"
- name: Run Main Tests
env:
PRAISONAI_TEST_TIER: main
PRAISONAI_ALLOW_NETWORK: '0'
OPENAI_MODEL_NAME: gpt-4o-mini
OPENAI_API_KEY: 'test-key'
ANTHROPIC_API_KEY: 'test-key'
GOOGLE_API_KEY: 'test-key'
shell: bash
run: |
set -euo pipefail
cd src/praisonai
python -m pytest tests/unit/ \
-m "not slow and not network and not local_service and not provider_anthropic and not provider_google and not provider_ollama and not provider_grok_xai and not provider_groq and not provider_cohere" \
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/test_langflow_components.py \
--ignore=tests/unit/api \
--cov=praisonai \
--cov-report=xml \
-n 2 --dist loadfile \
--maxfail=10
-n 4 \
--maxfail=10 \
|| echo "Some tests failed"
- name: Upload coverage
if: matrix.python-version == '3.11'
@@ -393,8 +187,8 @@ jobs:
fi
- uses: actions/checkout@v4
with:
persist-credentials: false
with:
persist-credentials: false
if: steps.check-key.outputs.has_key == 'true'
- name: Set up Python 3.11
@@ -416,12 +210,11 @@ jobs:
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
- uses: ./.github/actions/install-monorepo-packages
if: steps.check-key.outputs.has_key == 'true'
with:
agents-extras: ".[all]"
wrapper-extras: ".[openai]"
- name: Run OpenAI Live Tests
if: steps.check-key.outputs.has_key == 'true'
@@ -466,8 +259,8 @@ jobs:
fi
- uses: actions/checkout@v4
with:
persist-credentials: false
with:
persist-credentials: false
if: steps.check-key.outputs.has_key == 'true'
- name: Set up Python 3.11
@@ -480,12 +273,11 @@ jobs:
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
- uses: ./.github/actions/install-monorepo-packages
if: steps.check-key.outputs.has_key == 'true'
with:
agents-extras: ".[all]"
wrapper-extras: ".[anthropic]"
- name: Run Anthropic Tests
if: steps.check-key.outputs.has_key == 'true'
@@ -526,8 +318,8 @@ jobs:
fi
- uses: actions/checkout@v4
with:
persist-credentials: false
with:
persist-credentials: false
if: steps.check-key.outputs.has_key == 'true'
- name: Set up Python 3.11
@@ -540,12 +332,11 @@ jobs:
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
- uses: ./.github/actions/install-monorepo-packages
if: steps.check-key.outputs.has_key == 'true'
with:
agents-extras: ".[all]"
wrapper-extras: ".[google]"
- name: Run Google/Gemini Tests
if: steps.check-key.outputs.has_key == 'true'
@@ -586,8 +377,8 @@ jobs:
fi
- uses: actions/checkout@v4
with:
persist-credentials: false
with:
persist-credentials: false
if: steps.check-key.outputs.has_key == 'true'
- name: Set up Python 3.11
@@ -600,11 +391,11 @@ jobs:
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
- uses: ./.github/actions/install-monorepo-packages
if: steps.check-key.outputs.has_key == 'true'
with:
agents-extras: ".[all]"
- name: Run Groq Tests
if: steps.check-key.outputs.has_key == 'true'
@@ -645,8 +436,8 @@ jobs:
fi
- uses: actions/checkout@v4
with:
persist-credentials: false
with:
persist-credentials: false
if: steps.check-key.outputs.has_key == 'true'
- name: Set up Python 3.11
@@ -659,11 +450,11 @@ jobs:
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
- uses: ./.github/actions/install-monorepo-packages
if: steps.check-key.outputs.has_key == 'true'
with:
agents-extras: ".[all]"
- name: Run xAI/Grok Tests
if: steps.check-key.outputs.has_key == 'true'
@@ -704,8 +495,8 @@ jobs:
fi
- uses: actions/checkout@v4
with:
persist-credentials: false
with:
persist-credentials: false
if: steps.check-key.outputs.has_key == 'true'
- name: Set up Python 3.11
@@ -718,12 +509,11 @@ jobs:
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
- uses: ./.github/actions/install-monorepo-packages
if: steps.check-key.outputs.has_key == 'true'
with:
agents-extras: ".[all]"
wrapper-extras: ".[cohere]"
- name: Run Cohere Tests
if: steps.check-key.outputs.has_key == 'true'
@@ -745,79 +535,6 @@ jobs:
if: steps.check-key.outputs.has_key == 'false'
run: echo "✅ Cohere tests skipped (no API key available)"
# ============================================
# LEGACY UNIT TESTS - Post-C6 re-enabled suite
# Nightly / extended tier only (~401 tests)
# ============================================
legacy-unit:
if: github.event_name == 'schedule' || github.event.inputs.tier == 'extended' || github.event.inputs.tier == 'nightly'
runs-on: ubuntu-latest
timeout-minutes: 20
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 dependencies
run: |
pip install --upgrade pip
pip install pytest pytest-asyncio pytest-timeout
- uses: ./.github/actions/install-monorepo-packages
with:
agents-extras: ".[all]"
wrapper-extras: ".[chat,code,crewai,autogen]"
- name: Run post-C6 legacy unit tests
env:
PRAISONAI_TEST_TIER: extended
PRAISONAI_ALLOW_NETWORK: '0'
PRAISONAI_ALLOW_JOB_WORKFLOWS: 'true'
PRAISONAI_TOOL_SAFETY: 'off'
OPENAI_API_KEY: 'test-key'
run: |
set -euo pipefail
cd src/praisonai
LEGACY_FILES=(
tests/unit/test_warm_runtime.py
tests/unit/test_yaml_cli_backend.py
tests/unit/test_tool_resolver.py
tests/unit/test_serve_unified.py
tests/unit/test_security_fixes_core.py
tests/unit/test_query_rewriter_cli.py
tests/unit/test_kanban_sqlite_store.py
tests/unit/test_job_workflow_agent_steps.py
tests/unit/test_hybrid_workflow.py
../praisonai-bot/tests/unit/test_gateway_session.py
../praisonai-bot/tests/unit/test_gateway_gaps.py
tests/unit/test_discord_approval.py
tests/unit/test_decorator_simple.py
tests/unit/test_db_adapter_tracing_init.py
../praisonai-bot/tests/unit/test_bot_wiring.py
../praisonai-bot/tests/unit/bots/test_enable_shell.py
../praisonai-bot/tests/unit/gateway/test_preflight.py
../praisonai-bot/tests/unit/gateway/test_gateway_doctor.py
../praisonai-bot/tests/unit/test_bot_history.py
../praisonai-bot/tests/unit/test_bot_fixes.py
tests/unit/test_auto_lazy_loading.py
tests/unit/test_async_daemon_deployment.py
tests/unit/test_approval_interactive.py
tests/unit/test_approval_agent_integration.py
tests/unit/test_agents_yaml_validation.py
tests/unit/test_agent_os_wrapper.py
tests/unit/test_lazy_imports.py
tests/unit/test_profiler.py
tests/unit/test_profiler_advanced.py
tests/unit/test_serverless_postgres.py
)
python -m pytest "${LEGACY_FILES[@]}" \
-q --tb=line --timeout=120 --maxfail=10
# ============================================
# TEST SUMMARY
# ============================================
+7 -6
View File
@@ -45,8 +45,10 @@ jobs:
- name: Checkout code
uses: actions/checkout@v4
with:
persist-credentials: false
with:
persist-credentials: false
with:
persist-credentials: false
- name: Set up Python ${{ matrix.python-version }}
uses: actions/setup-python@v5
@@ -61,12 +63,11 @@ jobs:
- 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 pytest pytest-asyncio pytest-cov
# Install knowledge dependencies from praisonai-agents
uv pip install --system "praisonaiagents[knowledge]"
- uses: ./.github/actions/install-monorepo-packages
with:
use-uv: "true"
wrapper-extras: ".[ui,gradio,api,agentops,google,openai,anthropic,cohere,chat,code,realtime,call,crewai,autogen]"
- name: Set environment variables
run: |
+12 -7
View File
@@ -7,20 +7,18 @@ on:
- 'src/**'
- 'pyproject.toml'
- '.github/workflows/test-windows.yml'
- '.github/actions/install-monorepo-packages/**'
pull_request:
branches: [main, develop]
paths:
- 'src/**'
- 'pyproject.toml'
- '.github/workflows/test-windows.yml'
- '.github/actions/install-monorepo-packages/**'
workflow_dispatch:
jobs:
test-windows:
runs-on: windows-latest
timeout-minutes: 10
timeout-minutes: 5
env:
OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }}
OPENAI_MODEL_NAME: gpt-4o-mini
@@ -35,10 +33,18 @@ jobs:
with:
python-version: "3.11"
- name: Install monorepo packages
run: python -m pip install --upgrade pip
- 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
- uses: ./.github/actions/install-monorepo-packages
# ==================== CORE IMPORTS ====================
- name: Test core imports
@@ -176,7 +182,6 @@ jobs:
echo "Testing both entry point methods..."
python -m praisonai --version
praisonai --version
praisonai-bot gateway --help
- name: Test doctor packaging command
run: |
-17
View File
@@ -12,7 +12,6 @@ assets
.DS_Store
.pytest_cache
praisonAI.egg-info
src/*/build/
flagged
test.yaml
db
@@ -23,24 +22,11 @@ other
output
!src/praisonai/praisonai/cli/output/
!src/praisonai-agents/praisonaiagents/output/
!src/praisonai-code/praisonai_code/cli/output/
!src/praisonai-bot/praisonai_bot/cli/output/
!src/praisonai-ts/src/db/
!src/praisonai-ts/src/cli/output/
.files
threads.db
threads.db-journal
# Example run artifacts (generated at runtime, must not be committed)
examples/**/knowledge.db
examples/**/knowledge.db-journal
examples/python/managed-agents/managed_ids.json
examples/python/save_output/blog_post.md
examples/python/save_output/generated/
examples/python/token-metrics/token_metrics_export.json
examples/python/usecases/market_research_results.json
.chainlit
!praisonai/ui/config/.chainlit
@@ -102,9 +88,6 @@ issue_details.json
.internal
.praisonai
# Backup files
*.bak
# Rust / Cargo
target/
Cargo.lock
-15
View File
@@ -1,15 +0,0 @@
# Agent Instructions
You are working on the PraisonAI project.
## Project Guidelines
- Follow the existing code style and conventions
- Be concise and helpful in responses
- Test implementation thoroughly
- Ensure backward compatibility with existing APIs
- Follow protocol-driven design across the nine packages: core protocols in `praisonaiagents/`, agentic terminal CLI in `praisonai-code/`, bots/gateway in `praisonai-bot/`, LLM fine-tuning + agent training in `praisonai-train/`, browser automation in `praisonai-browser/`, MCP server host in `praisonai-mcp/`, sandbox backends in `praisonai-sandbox/`, deployment in `praisonai-deploy/`, integrations/serve/dashboard in the `praisonai/` wrapper
- Preserve old `praisonai.*` import paths via shims when moving code between packages (see §2.3 in `src/praisonai-agents/AGENTS.md`; shim helpers in `src/praisonai/praisonai/cli/_shim.py`)
- Package boundaries and dependency rules: `ARCHITECTURE.md` §2 (Tier 2 packages must never PyPI-depend on the wrapper; cross-tier access goes through lazy `_*_bridge` modules)
- Boundary manifests: `src/praisonai/tests/PRAISONAI_BOT_MANIFEST.md` (C9), `src/praisonai/tests/PRAISONAI_TRAIN_MANIFEST.md` (C10), `src/praisonai/tests/PRAISONAI_BROWSER_MANIFEST.md` (C11), `src/praisonai/tests/PRAISONAI_MCP_MANIFEST.md` (C12), `src/praisonai/tests/PRAISONAI_SANDBOX_MANIFEST.md` (C13), `src/praisonai/tests/PRAISONAI_DEPLOY_MANIFEST.md` (C14)
- When reviewing a PR or an issue, evaluate whether the change addresses a framework concern or a user goal, and design its surface (params, naming, defaults) accordingly
- The aim of this package is to stay **lightweight and powerful**. Do a critical review at each stage — when triaging an issue, when planning a fix, and when reviewing/implementing a PR. Reject scope creep for the sake of adding features: if a capability already exists (e.g. via existing Agent params like `instructions`/`backstory`/`tools`/`hooks`/`memory`), prefer it over a new API surface. A change must genuinely strengthen the SDK (simpler, more robust, more user-friendly) — do not add knobs, params, modules, or exports that have no live consumer or that merely duplicate existing behaviour.
-593
View File
@@ -1,593 +0,0 @@
# PraisonAI Architecture
> **Last updated:** 2026-07-31 (C14 — nine-package tiered model)
>
> Strategic architecture document for PraisonAI — a multi-agent AI framework.
> Covers **Python tiered package model (C7.1 + C9 + C10)**, system design, runtime
> architecture, data contracts, reliability, observability, and the road map.
---
## Table of Contents
1. [Executive Summary](#1-executive-summary)
2. [Python Tiered Package Model (C7.1 + C9 + C10 + C11 + C12 + C13 + C14)](#2-python-tiered-package-model-c71--c9--c10--c11--c12--c13--c14)
3. [System Overview](#3-system-overview)
4. [Layered Architecture](#4-layered-architecture)
5. [Core Data Contracts](#5-core-data-contracts)
6. [Reliability by Design](#6-reliability-by-design)
7. [Observability & Telemetry](#7-observability--telemetry)
8. [Replay & Checkpointing](#8-replay--checkpointing)
9. [Implementation Roadmap](#9-implementation-roadmap)
10. [Success Metrics](#10-success-metrics)
**Related boundary docs:** [`src/praisonai/tests/C7.1_BOUNDARIES.md`](src/praisonai/tests/C7.1_BOUNDARIES.md) · [`src/praisonai/tests/C9.1_BOUNDARIES.md`](src/praisonai/tests/C9.1_BOUNDARIES.md) · [`src/praisonai/tests/PRAISONAI_TRAIN_MANIFEST.md`](src/praisonai/tests/PRAISONAI_TRAIN_MANIFEST.md) · [`src/praisonai/tests/PRAISONAI_BROWSER_MANIFEST.md`](src/praisonai/tests/PRAISONAI_BROWSER_MANIFEST.md) · [`src/praisonai/tests/PRAISONAI_MCP_MANIFEST.md`](src/praisonai/tests/PRAISONAI_MCP_MANIFEST.md) · [`src/praisonai/tests/C7_VERIFICATION.md`](src/praisonai/tests/C7_VERIFICATION.md) · [`src/praisonai/tests/C9_VERIFICATION.md`](src/praisonai/tests/C9_VERIFICATION.md) · [`src/praisonai-agents/AGENTS.md`](src/praisonai-agents/AGENTS.md) §2.4
---
## 1. Executive Summary
PraisonAI is a multi-agent AI framework with broad capability surface across
Python, TypeScript, and Rust SDKs. The framework's core strength is its
feature breadth — agent abstractions, integrations, workflows, and active
release cadence.
The strategic bet for the next two quarters is building a **Reliability +
Orchestration + Observability** core to unlock adoption and trust:
| Dimension | Current State | Target |
|-----------|--------------|--------|
| Reliability | Cross-platform mismatches, optional dep fragility | Deterministic gating, adapter abstraction, parity CI |
| Determinism | Flaky tests, global state collisions | Isolated test fixtures, traceable tenant IDs |
| Developer UX | Complex onboarding, implicit config | Golden-path CLI, Doctor Auto-Fix |
| Observability | Minimal runtime tracing | Structured event bus, replay engine, failure classifier |
### Design Principles
- **Deterministic by default**, flexible by opt-in
- **Policy-enforced execution boundaries** at every layer
- **Structured events** for all lifecycle transitions
- **Capability isolation** per agent and per tool
---
## 2. Python Tiered Package Model (C7.1 + C9 + C10 + C11 + C12 + C13 + C14)
**Release:** v4.6.110+ · `praisonaiagents` · `praisonai-code` · `praisonai-bot` · `praisonai-train` · `praisonai-browser` · `praisonai-mcp` · `praisonai-sandbox` · `praisonai-deploy` · `praisonai`
The Python monorepo publishes nine packages in three tiers with strict dependency
direction. C7 delivered a standalone agentic hot path; C7.1 formalised
code/wrapper ownership; C9 extracted bots, gateway, and channel CLI into
`praisonai-bot`; C10 extracted LLM fine-tuning and agent training into
`praisonai-train`; C11 extracted browser automation into `praisonai-browser`;
C12 extracted the heavy MCP host into `praisonai-mcp`.
C13 extracted sandbox backends into `praisonai-sandbox`.
C14 extracted deployment (API, Docker, cloud) into `praisonai-deploy`.
```mermaid
flowchart TB
subgraph tier1 [Tier 1 — Core SDK]
Agents["praisonaiagents<br/>Agent, tools, memory, hooks, protocols"]
end
subgraph tier2 [Tier 2 — Terminal + Bot + Train + Browser + MCP + Sandbox + Deploy]
Code["praisonai-code<br/>run, chat, code, Typer, runtime, LLM"]
Bot["praisonai-bot<br/>bots, gateway, channel CLI, OS daemon"]
Train["praisonai-train<br/>LLM fine-tuning, agent training"]
Browser["praisonai-browser<br/>extension bridge, CDP, Playwright"]
MCP["praisonai-mcp<br/>MCP server host, auth, capability adapters"]
Sandbox["praisonai-sandbox<br/>Docker, E2B, Modal, Sandlock backends"]
Deploy["praisonai-deploy<br/>API, Docker, AWS/Azure/GCP deploy"]
end
subgraph tier3 [Tier 3 — Wrapper]
Wrapper["praisonai<br/>framework_adapters, serve, dashboard"]
end
Agents --> Code
Agents --> Bot
Agents --> Train
Agents --> Browser
Agents --> MCP
Agents --> Sandbox
Agents --> Deploy
Agents --> Wrapper
Code -.->|"lazy _bot_bridge"| Bot
Code -.->|"lazy _train_bridge"| Train
Code -.->|"lazy _browser_bridge"| Browser
Code -.->|"lazy _mcp_bridge"| MCP
Code -.->|"lazy _sandbox_bridge"| Sandbox
Code -.->|"lazy _deploy_bridge"| Deploy
Code -.->|"lazy _wrapper_bridge"| Wrapper
Bot -.->|"lazy _code_bridge / _wrapper_bridge"| Code
Bot -.->|"lazy _wrapper_bridge"| Wrapper
Train -.->|"lazy _code_bridge / _wrapper_bridge"| Code
```
**PyPI publish order:** `praisonaiagents` → `praisonai-code` + `praisonai-bot` + `praisonai-train` + `praisonai-browser` + `praisonai-mcp` + `praisonai-sandbox` + `praisonai-deploy` → `praisonai`
**Backward compatibility:** `praisonai.bots`, `praisonai.gateway`, `praisonai.train`,
`praisonai.browser`, `praisonai.mcp_server`, `praisonai.sandbox`, `praisonai.deploy`, and related CLI paths remain as
`alias_package` shims to `praisonai_bot.*` / `praisonai_train.*` /
`praisonai_browser.*` / `praisonai_mcp.*` / `praisonai_sandbox.*` / `praisonai_deploy.*`.
| Tier | Package | Owns | Must not depend on |
|------|---------|------|-------------------|
| 1 | `src/praisonai-agents/` | Agent, tools, memory, hooks, `frameworks/` protocols, sandbox protocols | `praisonai`, `praisonai-code`, `praisonai-bot`, `praisonai-train`, `praisonai-browser`, `praisonai-mcp`, `praisonai-sandbox`, `praisonai-deploy` |
| 2a | `src/praisonai-code/` | `run`/`chat`/`code`, Typer, runtime, LLM, tool resolution | **`praisonai` as a PyPI dependency** (optional lazy imports via `_wrapper_bridge` only) |
| 2b | `src/praisonai-bot/` | Bots, gateway, channel CLI, OS daemon, gateway scheduler tick | **`praisonai` as a PyPI dependency** (optional lazy `_wrapper_bridge` for jobs/UI) |
| 2c | `src/praisonai-train/` | LLM fine-tuning (Unsloth), agent training, `train` CLI, conda env setup | **`praisonai` as a PyPI dependency** (lazy `_code_bridge` for legacy dispatch) |
| 2d | `src/praisonai-browser/` | Extension bridge, CDP/hybrid automation, `browser` CLI | **`praisonai` as a PyPI dependency** (none required; depends on `praisonaiagents` only) |
| 2e | `src/praisonai-mcp/` | MCP server host, auth, transports, `mcp` CLI | **`praisonai` as a PyPI dependency** (lazy `_wrapper_bridge` for full capability registry) |
| 2f | `src/praisonai-sandbox/` | Sandbox backends (Docker, E2B, Modal, Sandlock, SSH), `SandboxRegistry` | **`praisonai` as a PyPI dependency** (lazy `_code_bridge` for `PluginRegistry`) |
| 2g | `src/praisonai-deploy/` | Deploy API/Docker/cloud, `deploy` CLI, scheduler integration | **`praisonai` as a PyPI dependency** (lazy `_plugin_registry` via `_code_bridge`) |
| 3 | `src/praisonai/` | `framework_adapters/`, serve, dashboard, async jobs API | — |
### Repo infra (not PyPI)
Deployment packaging that stays in the git checkout, not in any tier-2 wheel:
| Path | Runtime owner | Orchestration |
|------|---------------|---------------|
| `src/praisonai-bot/infra/helm/praisonai-gateway/` | `praisonai-bot` (gateway) | C14 `deploy helm` wrapper |
| `src/praisonai-deploy/infra/helm/praisonai-agents-api/` | Generated API from C14 | C14 cross-link |
| `src/praisonai-deploy/infra/compose/agents-stack/` | Docker Compose | `praisonai deploy compose up/down` |
| `src/praisonai-deploy/infra/starters/` | Starter scaffolds | `praisonai deploy create --template` |
| `docker/` | Mixed (wrapper/bot dev stacks) | Not C14 — see bot manifest for `docker/bots/` |
Same boundary as C14: Helm/K8s manifests are **repo infra**, not `pip install praisonai-deploy` content.
**Config kernel:** Phase 0 `praisonai/common/` was skipped; shared config lives in
`praisonai_code/cli/configuration/` and is reached by the bot tier via lazy
`_code_bridge` (see `src/praisonai/tests/CONFIG_KERNEL.md`).
### Dependency rule (validated)
| Question | Answer |
|----------|--------|
| Does `praisonai-code` declare `praisonai` in `pyproject.toml`? | **No** — only `praisonaiagents` + CLI/runtime deps |
| Does `praisonai` declare `praisonai-code`? | **Yes** — one-way chain, no PyPI cycle |
| Can `praisonai-code` import `praisonai.*` at runtime? | **Only lazily** via `praisonai_code._wrapper_bridge` for optional features; **not** on the agentic hot path |
| Does standalone `pip install praisonai-code` work? | **Yes** — CI smoke validates imports + `praisonai-code run` without the wrapper |
### CLI routing
```mermaid
flowchart LR
User[User] --> Entry{Entry point}
Entry -->|pip install praisonai-code| CodeCLI["praisonai-code run/chat/code"]
Entry -->|pip install praisonai| WrapperCLI["praisonai …"]
WrapperCLI --> Router["praisonai.__main__"]
Router --> CodePath["praisonai_code.cli.app"]
Router --> Legacy["praisonai.cli.main"]
CodePath --> HotPath["run / chat / code"]
CodePath --> Bridge{"wrapper_available?"}
Bridge -->|yes| WrapperCmds["bot, gateway, pairing, …"]
Bridge -->|no| Hidden["Wrapper commands hidden"]
```
### Import gates (CI enforced)
- **Hot path:** no module-level `from praisonai` in `main.py`, `app.py`, `run.py`, `chat.py`, `code.py`
- **Regression baseline:** 50 direct wrapper import lines max (`scripts/check_c7_imports.sh`; C8 achieved **0**)
- **Allowlist:** reviewed files only (`scripts/c7_wrapper_import_allowlist.txt`; empty post-C8)
- **Hybrid audit:** `scripts/audit_hybrid_modules.py` — repatriated cross-tier import paths
### C7 / C7.1 / C8 status
| Milestone | Status |
|-----------|--------|
| Standalone agentic hot path | **Complete** |
| `_wrapper_bridge` hardening | **Complete** |
| Import gate + allowlist | **Complete** |
| Boundary tests + CI smoke | **Complete** |
| C8 reverse import elimination (225 → 0 direct imports) | **Complete** — see [`C8_BACKLOG.md`](src/praisonai/tests/C8_BACKLOG.md) |
| C8.4 main.py physical decomposition | **Deferred** (separate epic) |
| PyPI package splits (`praisonai-bot`, etc.) | **Out of scope** |
---
## 3. System Overview
```
User/SDK/CLI
→ Workflow Compiler (graph + policy + schemas)
→ Execution Orchestrator (state machine, retries, fallbacks)
→ Tool Runtime (sandbox + approval + capability scope)
→ Model Runtime (provider abstraction + rate/timeout policy)
→ Observability Bus (trace events + metrics + cost)
→ Replay Engine (checkpoint + deterministic re-run)
→ Persistence (session, memory, artifacts, run ledger)
```
### Runtime Components
| Component | Responsibility | Interface |
|-----------|---------------|-----------|
| API/CLI Gateway | Accepts run requests, validates config/profile | `RunRequest`, `RunProfile` |
| Workflow Compiler | Converts YAML/DSL to normalized execution graph | `CompiledGraph` |
| Orchestrator | Executes graph state machine with retries/fallbacks | `ExecutionState`, `StepTransition` |
| Tool Runtime | Runs tools with approval/sandbox policies | `ToolCall`, `ToolResult` |
| Model Runtime | Provider routing, timeout, budget control | `ModelRequest`, `ModelResponse` |
| Observability Bus | Streams structured events + metrics | `RunEvent` schema |
| Replay Engine | Restarts from checkpoint with deterministic inputs | `ReplayRequest` |
### Existing Architecture (Python SDK)
The Python SDK is organised as three publishable tiers (see [§2](#2-python-three-tier-package-model-c71)):
- `src/praisonai-agents/` — Core SDK (`Agent`, tools, memory, hooks, protocols)
- `src/praisonai-code/` — Terminal CLI (`run`, `chat`, `code`, Typer, runtime, LLM)
- `src/praisonai/` — Wrapper (gateway, bots, `framework_adapters/`, integrations)
Core execution modules live in `praisonaiagents`:
- `agent/` — Agent class, handoff, autonomy
- `llm/` — Model runtime with provider routing, rate limiting, failover
- `tools/` — Tool runtime with sandbox, approval, retry
- `memory/` — Memory runtime (in-memory, SQLite, MongoDB, Mem0 adapters)
- `knowledge/` — Knowledge management (indexing, retrieval, chunking)
- `workflows/` — Workflow engine (YAML/SDK-based orchestration)
- `hooks/`, `bus/` — Hook system and event bus
- `mcp/` — MCP protocol support
- `a2a/`, `a2ui/` — Agent-to-agent and agent-to-UI protocols (wrapper/SDK)
Wrapper-only surfaces remain in `src/praisonai/`:
- `gateway/`, `bots/` — Multi-bot orchestration (BotOS)
- `framework_adapters/` — CrewAI, AutoGen, PraisonAI adapters
- `cli/commands/` — Wrapper commands (`bot`, `gateway`, `pairing`, …)
### Multi-SDK Layout
- **Python Core SDK** — `src/praisonai-agents/` (`praisonaiagents`)
- **Python Terminal CLI** — `src/praisonai-code/` (`praisonai-code`)
- **Python Wrapper** — `src/praisonai/` (`praisonai`)
- **TypeScript SDK** — JS/TS runtime (`ts-sdk/`)
- **Rust SDK** — High-performance Rust runtime (`rust-sdk/`)
- **UI** — Web UI (`ui/`)
---
## 4. Layered Architecture
```mermaid
flowchart TB
subgraph UX["Interface Layer"]
CLI[CLI]
SDK[SDK]
API[API Gateway]
end
subgraph Control["Control Plane"]
Compiler[Workflow Compiler]
Policy[Policy Engine]
Orchestrator[Execution Orchestrator]
end
subgraph Runtime["Runtime Plane"]
ModelRT[Model Runtime]
ToolRT[Tool Runtime]
MemoryRT[Memory Runtime]
end
subgraph Observe["Observability Plane"]
EventBus[Run Event Bus]
Metrics[Metrics + Cost]
Replay[Replay Engine]
end
subgraph Data["Data Plane"]
Ledger[Run Ledger]
Checkpoints[Checkpoints]
Artifacts[Artifacts Store]
end
CLI --> API
SDK --> API
API --> Compiler
API --> Policy
Compiler --> Orchestrator
Policy --> Orchestrator
Orchestrator --> ModelRT
Orchestrator --> ToolRT
Orchestrator --> MemoryRT
Orchestrator --> EventBus
EventBus --> Metrics
EventBus --> Replay
Orchestrator --> Ledger
Orchestrator --> Checkpoints
ToolRT --> Artifacts
Replay --> Checkpoints
```
### Interface Layer
- **CLI** — The `praisonai` command-line entry point
- **SDK** — Python library API (`from praisonai import Agent`)
- **API Gateway** — HTTP/WebSocket REST API (`praisonai api` or `a2a`/`a2ui`)
### Control Plane
- **Workflow Compiler** — Converts YAML workflows and SDK-defined graphs into
a normalized `CompiledGraph` with adjacency validation and cycle detection.
- **Policy Engine** — Enforces runtime policies (budget, timeout, approval
gates, capability validation) before and during execution.
- **Execution Orchestrator** — Drives the state machine through graph nodes,
handling retry, fallback, and failure classification.
### Runtime Plane
- **Model Runtime** — Provider abstraction layer. Routes to OpenAI, Anthropic,
Gemini, Ollama, DeepSeek, etc. Handles rate limiting, token tracking, and
automatic failover between providers.
- **Tool Runtime** — Executes tool calls with configurable sandboxing,
approval gates, retry policies, and capability scope validation.
- **Memory Runtime** — Manages session memory, persistent memory stores,
and knowledge retrieval across in-memory, SQLite, and MongoDB backends.
### Observability Plane
- **Run Event Bus** — Structured event streaming for all lifecycle transitions
(START, INPUT, MODEL_CALL, TOOL_CALL, ERROR, RETRY, COMPLETE).
- **Metrics + Cost** — Token counting, cost tracking, and performance metrics.
- **Replay Engine** — Deterministic replay from the last stable checkpoint,
with state hash verification.
### Data Plane
- **Run Ledger** — Persistent record of all runs with state, metrics, and
failure classifications.
- **Checkpoints** — Point-in-time snapshots of run state, memory, and
artifacts for replay and recovery.
- **Artifacts Store** — Tool outputs, generated files, and intermediate
results.
---
## 5. Core Data Contracts
### RunRequest
```text
RunRequest {
run_id: UUID,
workflow_ref: string,
inputs: object,
profile: {safe_mode, budget, timeout, approval_policy},
context: {user_id, workspace_id, env}
}
```
### RunEvent
```text
RunEvent {
ts: ISO8601,
run_id: UUID,
step_id: string,
type: START | INPUT | MODEL_CALL | TOOL_CALL |
ERROR | RETRY | COMPLETE,
payload: object,
cost: {tokens_in, tokens_out, usd},
latency_ms: number
}
```
### Checkpoint
```text
Checkpoint {
run_id: UUID,
step_id: string,
state_hash: string,
memory_snapshot_ref: string,
artifact_refs: string[]
}
```
### Execution Sequence
```text
1) Client submits RunRequest
2) Gateway validates profile + schema
3) Compiler resolves workflow → CompiledGraph
4) Orchestrator starts node execution
5) Node may call Model Runtime or Tool Runtime
6) Every transition emits RunEvent
7) On failure: classifier decides retry/fallback/abort
8) Checkpoint stored after each critical step
9) Final state + artifacts persisted to run ledger
10) Replay can resume from last stable checkpoint
```
---
## 6. Reliability by Design
### Error Taxonomy
All failures are classified into one of five categories for automatic
remediation:
| Category | Description | Default Action |
|----------|-------------|----------------|
| `config` | Invalid configuration or profile | Abort with remediation hint |
| `dependency` | Missing optional module or capability | Degrade / skip optional path |
| `tool` | Tool execution failure | Retry with backoff and policy cap |
| `model` | Model API error or timeout | Fallback to alternate provider/route |
| `infra` | Network or resource exhaustion | Circuit-breaker + replay from checkpoint |
```mermaid
flowchart TD
S[Step Failure] --> T{Failure Type?}
T -->|Config| C1[Abort + config remediation hint]
T -->|Dependency| C2[Degrade capability / skip optional path]
T -->|Tool| C3[Retry with backoff and policy cap]
T -->|Model| C4[Fallback model/provider route]
T -->|Infra| C5[Circuit-breaker + replay from checkpoint]
```
### Hardening Checklist
- **Dependency gates** — Optional modules declared as capabilities;
unavailable capability results in skip/degrade, not crash.
- **Cross-platform adapters** — OS-specific implementations behind a single
interface (e.g., file lock adapter for Windows/Linux/macOS).
- **Idempotent fixtures** — Integration tests use unique tenant/workspace IDs
and guaranteed teardown.
- **Fail-safe output mode** — CLI rendering falls back to ASCII-safe mode on
encoding mismatch.
- **CI parity matrix** — Run smoke workflows across Windows, Linux, and macOS.
### Deterministic Test Pattern
```python
# Integration test pattern — always use unique, traceable IDs
import uuid
def test_agent_workflow():
tenant_id = f"test-{uuid.uuid4().hex[:8]}"
agent = Agent(name=f"agent-{tenant_id}", ...)
result = agent.run("task")
assert result.status == "success"
# teardown is guaranteed via fixture or context manager
```
---
## 7. Observability & Telemetry
### Current Telemetry Stack
PraisonAI already includes:
- **OpenTelemetry integration** — Manual and auto-instrumentation for
traces, metrics, and logs.
- **Token tracking** — Per-call and cumulative token/cost tracking.
- **Performance monitoring** — Real-time dashboards and monitoring views.
- **LangTrace integration** — LangTrace provider for tracing.
- **Run outcomes** — Structured `RunOutcome` objects with status, duration,
token usage, and error classification.
### Planned Enhancements
- **Run Event Bus** — Stream all lifecycle events as structured `RunEvent`
payloads.
- **Failure classifier** — Automatic failure category detection with
remediation hints.
- **Run ledger visualization** — Timeline view of runs with step-by-step
event drill-down.
- **Replay integration** — Checkpoint-based run replay from the
observability dashboard.
---
## 8. Replay & Checkpointing
### Design
```mermaid
sequenceDiagram
participant U as User/Client
participant G as Gateway
participant C as Compiler
participant O as Orchestrator
participant R as Model/Tool Runtime
participant E as Event Bus
participant L as Run Ledger
participant K as Checkpoint Store
U->>G: Submit RunRequest
G->>C: Validate + compile workflow
C-->>O: CompiledGraph
O->>R: Execute next step
R-->>O: Step output / error
O->>E: Emit structured RunEvent
O->>K: Persist checkpoint
O->>L: Persist run state + metrics
O-->>U: Final result / failure summary
```
### Current State
- Basic run outcome persistence exists
- Session persistence for bot/multi-turn conversations
- Token and cost tracking per run
### Roadmap
- Full checkpoint creation at configurable step granularity
- State hash verification for deterministic replay
- Replay API endpoint (`POST /runs/{id}/replay`)
- Checkpoint pruning and retention policy
---
## 9. Implementation Roadmap
### Completed (C7 / C7.1 — v4.6.110)
| Project | Description | Status |
|---------|-------------|--------|
| C7 hot path | Standalone `praisonai-code run/chat/code` without wrapper import | **Complete** |
| C7.1 boundaries | Three-tier ownership, `_wrapper_bridge`, import gates | **Complete** |
| CI parity | Smoke standalone block + pre-existing test fixes (#2560) | **Complete** |
### Quarter 1: Trust Foundation (Q3 2026)
| Priority | Project | Description | Status |
|----------|---------|-------------|--------|
| P0 | Reliability Core | Cross-platform hardening, optional-dep gating, deterministic fixtures | In progress |
| P0 | Doctor Auto-Fix | Automated environment diagnosis and repairs | Planned |
| P1 | Golden-Path CLI | Single canonical flow: init → run → test → deploy | Planned |
| P1 | CI Parity Matrix | Cross-platform smoke tests in CI pipeline | Planned |
### Quarter 2: Operational Excellence (Q4 2026)
| Priority | Project | Description | Status |
|----------|---------|-------------|--------|
| P1 | Trace + Replay | Run timeline, checkpoint replay, failure classifier | Planned |
| P1 | Failure Classifier | Automatic failure category detection with remediation | Planned |
| P2 | Graph Studio UX | Visual deterministic orchestration editor/inspector | Planned |
| P2 | Safe Production Profiles | Policy presets: guardrails, approvals, cost/time caps | Planned |
```mermaid
gantt
title PraisonAI Architecture Program (2 Quarters)
dateFormat YYYY-MM-DD
section Quarter 1
Reliability hardening + parity CI :a1, 2026-07-01, 45d
Deterministic test isolation :a2, 2026-07-10, 50d
Doctor Auto-Fix MVP :a3, 2026-07-20, 40d
Golden-path CLI :a4, 2026-08-01, 45d
section Quarter 2
Trace bus + run ledger :b1, 2026-10-01, 45d
Replay engine :b2, 2026-10-15, 45d
Failure classifier :b3, 2026-11-01, 30d
Graph UX beta + Safe profiles :b4, 2026-11-10, 50d
```
---
## 10. Success Metrics
### KPI Targets
| KPI | Target | Primary Workstream |
|-----|--------|-------------------|
| Time-to-first-successful run | 30-40% reduction | Golden-path CLI + Doctor Auto-Fix |
| Cross-platform issue rate | 50% reduction | Reliability Core + adapter layer |
| Incident triage time | 40% reduction | Trace + Replay + failure classifier |
| CI confidence | Flaky test rate <2% | Deterministic tests + fixture isolation |
### Governance
- **Architecture Review Council** — Reviews runtime-contract changes
- **Release Quality Gate** — Platform matrix + deterministic test thresholds
- **Monthly telemetry review** — DX, reliability, adoption trends
---
*This document is a living reference. Update as the architecture evolves.*
-14
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@@ -1,14 +0,0 @@
# Contributing to PraisonAI
Thank you for your interest! Here's how to get started:
1. Fork the repository
2. Create a feature branch
3. Make your changes
4. Submit a pull request
## Guidelines
- Follow existing code style
- Add tests for new features
- Update documentation as needed
+23 -224
View File
@@ -41,6 +41,10 @@ curl -fsSL https://praison.ai/install.sh | bash
<img src=".github/images/dashboard.png" alt="PraisonAI Dashboard" width="800" />
</p>
<p align="center">
<img src=".github/images/agentflow.gif" alt="PraisonAI AgentFlow" width="800" />
</p>
```
██████╗ ██████╗ █████╗ ██╗███████╗ ██████╗ ███╗ ██╗ █████╗ ██╗
██╔══██╗██╔══██╗██╔══██╗██║██╔════╝██╔═══██╗████╗ ██║ ██╔══██╗██║
@@ -52,6 +56,12 @@ curl -fsSL https://praison.ai/install.sh | bash
pip install praisonai
```
<p align="center">
<img src=".github/images/latest_ai_news_and_crawl_each_url_to_find_info.gif" alt="PraisonAI command execution" width="800" />
</p>
\* `export TAVILY_API_KEY=xxxxx`
<div align="center">
<a href="https://docs.praison.ai">
<p align="center">
@@ -96,203 +106,6 @@ agent.start("Analyze the top 3 tech trends of 2026 and format as a markdown tabl
---
## 🧬 The Five-Layer Agent Stack
Most frameworks hand you one or two layers and leave the rest as homework. PraisonAI covers **all five** — plus the outer layer that decides *where* your agent actually runs.
Each layer wraps the one inside it. When an agent misbehaves, the layer tells you where to look.
```
┌─────────────────────────────────────────────────────────────────┐
│ ⬡ MANAGED AGENTS — Where does it actually run? │
│ ┌─────────────────────────────────────────────────────────────┐ │
│ │ 5 · GRAPH — Who runs when, and who checks whom? │ │
│ │ ┌─────────────────────────────────────────────────────────┐ │ │
│ │ │ 4 · LOOP — When do we stop? │ │ │
│ │ │ ┌─────────────────────────────────────────────────────┐ │ │ │
│ │ │ │ 3 · HARNESS — Can it act, and be checked? │ │ │ │
│ │ │ │ ┌─────────────────────────────────────────────────┐ │ │ │ │
│ │ │ │ │ 2 · CONTEXT — Is the right thing in the window? │ │ │ │ │
│ │ │ │ │ ┌─────────────────────────────────────────────┐ │ │ │ │ │
│ │ │ │ │ │ 1 · PROMPT — Did I say it clearly? │ │ │ │ │ │
│ │ │ │ │ └─────────────────────────────────────────────┘ │ │ │ │ │
│ │ │ │ └─────────────────────────────────────────────────┘ │ │ │ │
│ │ │ └─────────────────────────────────────────────────────┘ │ │ │
│ │ └─────────────────────────────────────────────────────────┘ │ │
│ └─────────────────────────────────────────────────────────────┘ │
└─────────────────────────────────────────────────────────────────┘
```
| Layer | The question it answers | PraisonAI |
|:--|:--|:--|
| **1 · Prompt** | Did I say it clearly? | `instructions=`, `role`/`goal`/`backstory`, `output=`, `templates=` |
| **2 · Context** | Is the right thing in the window? | `memory=`, `knowledge=`, `context=`, handoff `ContextPolicy` |
| **3 · Harness** | Can it act, and be checked? | `tools=`, `MCP()`, `guardrails=`, `approval=`, `hooks=`, `sandbox=` |
| **4 · Loop** | When do we stop? | `execution=ExecutionConfig(...)`, `reflection=`, `autonomy=`, doom-loop detection |
| **5 · Graph** | Who runs when, and who checks whom? | `AgentFlow`, `route()`, `parallel()`, `loop()`, `repeat()` |
| **⬡ Managed** | *Where does it actually run?* | `run_on="docker"` — one shared remote sandbox, or a fully hosted loop |
### Layer 1 · Prompt — *Did I say it clearly?*
Role, instructions, examples, output format.
```python
from praisonaiagents import Agent
agent = Agent(
role="Senior Data Analyst",
goal="Turn raw numbers into decisions",
output="verbose", # markdown-formatted output
)
agent.start("Summarise Q3 revenue trends")
```
### Layer 2 · Context — *Is the right thing in the window?*
Write, select, compress, isolate — the four context operations, one parameter each.
```python
from praisonaiagents import Agent
agent = Agent(
instructions="You are a support engineer.",
memory={"user_id": "u-42"}, # write — persists across runs (needs a user_id)
knowledge=["docs/"], # select — retrieves only what's relevant
context="summarize", # compress — auto-compacts before the limit
)
```
> **Isolate** is `handoffs=[specialist]` — a sub-agent inherits the last few messages and the intersection of your tools, not your whole transcript. [📖 Handoffs](https://docs.praison.ai/docs/concepts/handoffs)
### Layer 3 · Harness — *Can it act, and be checked?*
*Agent = Model + Harness.* Tool dispatch, plus the guides that steer before acting and the sensors that observe after.
```python
from praisonaiagents import Agent, MCP, tool
@tool
def deploy(env: str) -> str:
"""Deploy the current build to an environment."""
return f"Deployed to {env}"
agent = Agent(
name="ReleaseEngineer",
instructions="You are a release engineer.",
tools=[deploy, MCP("npx -y @modelcontextprotocol/server-filesystem /tmp")],
approval=True, # guide — human gate before risky tools run
)
agent.start("Deploy to staging, then list the files you can read")
```
### Layer 4 · Loop — *When do we stop?*
Hard iteration caps, budget ceilings, no-progress detection and completion checks — every brake is explicit.
```python
from praisonaiagents import Agent, ExecutionConfig
agent = Agent(
instructions="Fix the failing tests.",
execution=ExecutionConfig(max_iter=30, max_budget=0.50, on_budget_exceeded="stop"),
autonomy=True, # required to drive the loop with run_autonomous()
)
result = agent.run_autonomous("Refactor the auth module", max_iterations=5)
print(result.completion_reason)
# goal | no_tool_calls | max_iterations | timeout | doom_loop | needs_help | error
# (with on_budget_exceeded="stop", hitting the cap raises BudgetExceededError,
# surfaced here as completion_reason="error")
```
> **Doom-loop detection is on by default.** Repeated identical tool calls and A→B→A→B oscillation get caught — while a poller whose output keeps changing does not. [📖 Doom Loop Detection](https://docs.praison.ai/docs/features/doom-loop-detection)
### Layer 5 · Graph — *Who runs when, and who checks whom?*
Topology as a versionable artifact: prompt chaining, routing, parallelisation, orchestrator-worker.
```python
from praisonaiagents import AgentFlow
from praisonaiagents.workflows import route, parallel, repeat
flow = AgentFlow(steps=[
classifier,
route({"bug": [bug_agent], "feature": [feature_agent], "default": [triage]}),
parallel([reviewer, tester]), # fan out, join automatically
repeat(editor, until=lambda ctx: "approved" in ctx.previous_result.lower(),
max_iterations=3), # evaluator–optimizer
])
flow.run("Ticket #123: login fails on Safari")
```
> The same graph is expressible in YAML with no Python at all. [📖 AgentFlow](https://docs.praison.ai/docs/concepts/agentflow)
### ⬡ Outside the stack: Managed Agents — *Where does it actually run?*
The harness is commoditising; **where** the agent executes is the next multiplier. Rather than burning your laptop's CPU, hand an agent a short-lived cloud sandbox — repo, tools and tests run there.
```bash
pip install praisonai
```
The simplest way in is `run_on=` — one whole team or workflow shares **one** sandbox, so a file written by step 1 is there for step 2:
```python
from praisonaiagents import Agent, AgentFlow
writer = Agent(name="Writer", instructions="You write files.")
reader = Agent(name="Reader", instructions="You read files.")
flow = AgentFlow(run_on="docker", steps=[writer, reader]) # or e2b | modal | daytona | flyio
flow.run("Write 'hello' to /workspace/note.txt, then read it back")
```
Same thing with no Python at all:
```yaml
name: remote-demo
run_on: docker # every step shares one sandbox
agents:
writer: {role: Writer, goal: Write files}
reader: {role: Reader, goal: Read files}
steps:
- agent: writer
action: "Write 'hello' to /workspace/note.txt"
- agent: reader
action: "Read /workspace/note.txt"
```
For a single agent, pick the axis you need — remote **tools** or a remote **loop**:
```python
from praisonai import Agent, LocalAgent, LocalAgentConfig, HostedAgent
# A. Tools run in a remote sandbox; the agent loop stays local
agent = Agent(name="builder", backend=LocalAgent(
compute="e2b", # or modal | daytona | flyio | docker | tenki
config=LocalAgentConfig(model="gpt-4o-mini", name="RemoteTools"),
))
# B. The entire agent loop runs in the cloud (needs ANTHROPIC_API_KEY)
agent = Agent(name="teacher", backend=HostedAgent(provider="anthropic"))
agent.start("Write a Python script that prints the first 10 primes, then run it")
```
See what is running and reclaim strays:
```bash
praisonai managed ps # list running sandboxes
praisonai managed stop --all # reclaim them
```
Sandboxes shut themselves down when idle (`auto_shutdown`, `idle_timeout_s`), and a post-setup snapshot is reused so the next run skips the image pull and dependency install. Commit a `.praisonai/environment.yaml` and the environment travels with the repo.
> 📖 [20 runnable examples](examples/python/managed-agents/) · manage sessions with `praisonai managed sessions list <agent-id>` or `praisonai managed sessions resume <session-id> "<prompt>"`
<sub>Stack framing adapted from [The Five-Layer Agent Stack](https://mer.vin/2026/07/five-layer-agent-stack-match-bug-to-right-layer/) and [Agent Harnesses vs Orbs](https://mer.vin/2026/08/agent-harnesses-vs-orbs-why-remote-sandboxes-beat-local-agent-loops/).</sub>
---
## 🌌 The PraisonAI Ecosystem
Start simple with the core SDK, or expand to full visual builders and dashboards when you're ready.
@@ -387,9 +200,9 @@ Powered by 100+ LLMs (OpenAI, Anthropic, Gemini & local models).
| 🧠 | **Planning Mode** — plan → execute → reason | `planning=True` |
| 🔍 | **Deep Research** — multi-step autonomous research | [Docs](https://docs.praison.ai/docs/agents/deep-research) |
| 🤖 | **External Agents** — orchestrate Claude Code, Gemini CLI, Codex | [Docs](https://docs.praison.ai/docs/code/external-agents) |
| 🔄 | **Agent Handoffs** — seamless conversation passing | `handoffs=[other_agent]` |
| 🔄 | **Agent Handoffs** — seamless conversation passing | `handoff=True` |
| 🛡️ | **Guardrails** — input/output validation | [Docs](https://docs.praison.ai/docs/concepts/guardrails) |
| | **Web Search + Fetch** — native browsing | `web=True` |
| | **Web Search + Fetch** — native browsing | `web_search=True` |
| 🪞 | **Self Reflection** — agent reviews its own output | [Docs](https://docs.praison.ai/docs/concepts/reflection) |
| 🔀 | **Workflow Patterns** — route, parallel, loop, repeat | [Docs](https://docs.praison.ai/docs/concepts/agentflow) |
| 🧠 | **Memory (zero deps)** — works out of the box | `memory=True` |
@@ -399,9 +212,9 @@ Powered by 100+ LLMs (OpenAI, Anthropic, Gemini & local models).
| | Feature | How |
|--|---------|-----|
| 💡 | **Prompt Caching** — reduce latency + cost | `caching=True` |
| 💡 | **Prompt Caching** — reduce latency + cost | `prompt_caching=True` |
| 💾 | **Sessions + Auto-Save** — persistent state across restarts | `auto_save="my-project"` |
| 💭 | **Thinking Budgets** — control reasoning depth | `agent.thinking_budget = 1024` |
| 💭 | **Thinking Budgets** — control reasoning depth | `thinking_budget=1024` |
| 📚 | **RAG + Quality-Based RAG** — auto quality scoring retrieval | [Docs](https://docs.praison.ai/docs/concepts/rag) |
| 📊 | **Model Router** — auto-routes to cheapest capable model | [Docs](https://docs.praison.ai/docs/features/model-router) |
| 🧊 | **Shadow Git Checkpoints** — auto-rollback on failure | [Docs](https://docs.praison.ai/docs/features/checkpoints) |
@@ -528,10 +341,8 @@ from praisonaiagents import Agent, db
agent = Agent(
name="Assistant",
memory={
"db": db(database_url="postgresql://localhost/mydb"),
"session_id": "my-session",
},
db=db(database_url="postgresql://localhost/mydb"),
session_id="my-session"
)
agent.chat("Hello!") # Auto-persists messages, runs, traces
```
@@ -757,7 +568,7 @@ praisonai agents.yaml
| Query Rewriter Agent | [Example](examples/python/agents/query-rewriter-agent.py) | [📖](https://docs.praison.ai/docs/agents/query-rewriter) |
| Native Web Search | [Example](examples/python/agents/websearch-agent.py) | [📖](https://docs.praison.ai/docs/agents/websearch) |
| Built-in Search Tools | [Example](examples/python/agents/websearch-agent.py) | [📖](https://docs.praison.ai/docs/tools/tavily) |
| Unified Web Search | [Example](examples/python/web_search_example.py) | [📖](https://docs.praison.ai/docs/tools/web-search) |
| Unified Web Search | [Example](src/praisonai-agents/examples/web_search_example.py) | [📖](https://docs.praison.ai/docs/tools/web-search) |
| Web Fetch (Anthropic) | [Example](examples/python/agents/web-fetch-agent.py) | [📖](https://docs.praison.ai/docs/features/model-capabilities) |
</details>
@@ -959,11 +770,11 @@ agent.start('Write a movie script about a robot in Mars');
## ⚡ Performance
PraisonAI is built for speed, with agent instantiation in around 14μs. This reduces overhead, improves responsiveness, and helps multi-agent systems scale efficiently in real-world production workloads.
PraisonAI is built for speed, with agent instantiation in under 4μs. This reduces overhead, improves responsiveness, and helps multi-agent systems scale efficiently in real-world production workloads.
| Performance Metric | PraisonAI |
|--------------------|-----------|
| Avg Instantiation Time | **14 μs** |
| Avg Instantiation Time | **3.77 μs** |
---
@@ -977,16 +788,6 @@ PraisonAI is built for speed, with agent instantiation in around 14μs. This red
---
<p align="center">
<img src=".github/images/agentflow.gif" alt="PraisonAI AgentFlow" width="800" />
</p>
<p align="center">
<img src=".github/images/latest_ai_news_and_crawl_each_url_to_find_info.gif" alt="PraisonAI command execution" width="800" />
</p>
\* `export TAVILY_API_KEY=xxxxx`
## 🔍 Langfuse Tracing
```bash
@@ -1090,10 +891,8 @@ from praisonaiagents import Agent, db
agent = Agent(
name="Assistant",
memory={
"db": db(database_url="postgresql://localhost/mydb"),
"session_id": "my-session",
},
db=db(database_url="postgresql://localhost/mydb"),
session_id="my-session"
)
```
@@ -1109,8 +908,8 @@ from praisonaiagents import Agent
agent = Agent(
name="Assistant",
# Enables file-based memory (no extra deps!)
memory={"user_id": "user123"},
memory=True, # Enables file-based memory (no extra deps!)
user_id="user123"
)
```
-66
View File
@@ -1,66 +0,0 @@
# Security Policy
PraisonAI takes security seriously. We appreciate responsible disclosure from researchers and users.
## Supported packages
| Package | Registry | Source path |
|---------|----------|-------------|
| `praisonaiagents` | [PyPI](https://pypi.org/project/praisonaiagents/) | `src/praisonai-agents/` |
| `praisonai` | [PyPI](https://pypi.org/project/praisonai/) | `src/praisonai/` |
| `praisonai-platform` | [PyPI](https://pypi.org/project/praisonai-platform/) | `src/praisonai-platform/` |
| `praisonai` | [npm](https://www.npmjs.com/package/praisonai) | `src/praisonai-ts/` |
Report issues against the **specific package** where the vulnerability exists. A platform-only issue does not necessarily affect the core SDK, and vice versa.
## In scope
- Authentication, authorisation, and multi-tenant isolation (e.g. workspace boundaries)
- Tool execution, sandbox escape, and code execution paths
- SSRF, injection, and unsafe deserialisation in shipped code
- MCP, gateway, and bot/webhook integrations
- Secrets handling, JWT/session configuration, and default credentials
- Supply-chain issues in published package artefacts
## Out of scope
- Issues in forks or deployments not maintained in [MervinPraison/PraisonAI](https://github.com/MervinPraison/PraisonAI)
- Vulnerabilities requiring physical access or fully compromised operator machines
- Reports against versions no longer published or without a supported upgrade path
- Theoretical issues with no practical impact in documented, supported configurations
- Behaviour covered by an explicit, documented opt-out (e.g. dev-only env vars)
## How to report
**Preferred:** open a **private** security advisory:
[https://github.com/MervinPraison/PraisonAI/security/advisories/new](https://github.com/MervinPraison/PraisonAI/security/advisories/new)
Include:
1. Affected package and version
2. Clear reproduction steps
3. Impact assessment (confidentiality, integrity, availability)
4. Suggested fix (optional)
Please allow reasonable time for triage and a patched release before public disclosure.
## What to expect
1. **Triage** — we validate the report and assign a disposition (`real`, `duplicate`, `wontfix`, etc.)
2. **Fix** — minimal, backward-compatible patch on `main` where appropriate
3. **Release** — patched version published to PyPI/npm **before** the advisory is published
4. **Advisory** — GitHub Security Advisory with reporter credit and CVE where applicable
## Resources
- **Repository:** https://github.com/MervinPraison/PraisonAI
- **Documentation:** https://docs.praison.ai
- **Website:** https://praison.ai
- **Advisories:** https://github.com/MervinPraison/PraisonAI/security/advisories
## Maintainer workflow
Contributors and agents handling audits should follow:
`src/praisonai-agents/.agent/workflows/security-audit.md`
+311 -73
View File
@@ -7,7 +7,7 @@ Regenerate with: `praisonai docs api-md --write`
Types:
```python
from praisonaiagents import ContextPolicy, GuardrailResult, HandoffConfig, HandoffCycleError, HandoffDepthError, HandoffError, HandoffInputData, HandoffResult, HandoffTimeoutError, ReflectionOutput, StepResult, ToolResult, ToolValidationError, WorkflowContext
from praisonaiagents import ContextPolicy, GuardrailResult, HandoffConfig, HandoffCycleError, HandoffDepthError, HandoffError, HandoffInputData, HandoffResult, HandoffTimeoutError, ReflectionOutput, StepResult, TaskOutput, ToolResult, ToolValidationError, WorkflowContext
```
Methods:
@@ -15,28 +15,31 @@ Methods:
* <code title="class GuardrailResult">GuardrailResult.<a href="./src/praisonai-agents/praisonaiagents/guardrails/guardrail_result.py">from_tuple</a>(result: Tuple[bool, Any]) -> 'GuardrailResult'</code>
* <code title="class HandoffConfig">HandoffConfig.<a href="./src/praisonai-agents/praisonaiagents/agent/handoff.py">from_dict</a>(data: Dict[str, Any]) -> 'HandoffConfig'</code>
* <code title="class HandoffConfig">HandoffConfig.<a href="./src/praisonai-agents/praisonaiagents/agent/handoff.py">to_dict</a>() -> Dict[str, Any]</code>
* <code title="class HandoffResult">HandoffResult.<a href="./src/praisonai-agents/praisonaiagents/agent/handoff.py">from_outcome</a>(outcome: AgentRunOutcome, target_agent: Optional[str] = None, source_agent: Optional[str] = None, handoff_depth: int = 0) -> 'HandoffResult'</code>
* <code title="class ToolResult">ToolResult.<a href="./src/praisonai-agents/praisonaiagents/tools/base.py">is_multimodal</a>() -> bool</code>
* <code title="class TaskOutput">TaskOutput.<a href="./src/praisonai-agents/praisonaiagents/main.py">json</a>() -> Optional[str]</code>
* <code title="class TaskOutput">TaskOutput.<a href="./src/praisonai-agents/praisonaiagents/main.py">to_dict</a>() -> dict</code>
* <code title="class ToolResult">ToolResult.<a href="./src/praisonai-agents/praisonaiagents/tools/base.py">to_dict</a>() -> Dict[str, Any]</code>
# Agents
Types:
```python
from praisonaiagents import Agent, AutoAgents, AutoRagAgent, ContextAgent, DeepResearchAgent, ImageAgent, PlanningAgent, PraisonAIAgents, PromptExpanderAgent, QueryRewriterAgent, create_context_agent
from praisonaiagents import Agent, AutoAgents, AutoRagAgent, ContextAgent, DeepResearchAgent, ImageAgent, PlanningAgent, PromptExpanderAgent, QueryRewriterAgent, create_context_agent
```
Methods:
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">aclose</a>() -> None</code>
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">add_mcp_server</a>(name: str, mcp: Any) -> Any</code>
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">agent_id</a>() -> str</code>
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">analyze_prompt</a>(prompt: str) -> set</code>
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">auto_memory</a>() -> Optional[bool]</code>
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">auto_memory</a>(value: Optional[bool]) -> None</code>
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">background</a>() -> Optional[bool]</code>
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">background</a>(value: Optional[bool]) -> None</code>
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">chat_history</a>()</code>
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">chat_history</a>(value)</code>
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">chat_with_context</a>(message: str, context: 'ContextPack', **kwargs) -> str</code>
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">checkpoints</a>() -> Optional[bool]</code>
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">checkpoints</a>(value: Optional[bool]) -> None</code>
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">clone_for_channel</a>() -> 'Agent'</code>
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">close</a>() -> None</code>
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">console</a>() -> Optional[Any]</code>
@@ -55,10 +58,6 @@ Methods:
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">handoff_to</a>(target_agent: 'Agent', prompt: str, context: Optional[Dict[str, Any]] = None, config: Optional['HandoffConfig'] = None) -> 'HandoffResult'</code>
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">handoff_to_async</a>(target_agent: 'Agent', prompt: str, context: Optional[Dict[str, Any]] = None, config: Optional['HandoffConfig'] = None) -> 'HandoffResult'</code>
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">is_closed</a>() -> bool</code>
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">last_stop_reason</a>() -> str</code>
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">list_mcp_servers</a>() -> List[str]</code>
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">llm_instance</a>()</code>
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">llm_instance</a>(value)</code>
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">llm_model</a>() -> Optional[str]</code>
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">output_style</a>() -> Optional[str]</code>
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">output_style</a>(value: Optional[str]) -> None</code>
@@ -68,25 +67,21 @@ Methods:
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">rag</a>() -> Optional[Any]</code>
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">rag_query</a>(question: str, **kwargs) -> 'RAGResult'</code>
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">redo</a>() -> bool</code>
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">refresh_tools</a>() -> List[Any]</code>
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">remove_mcp_server</a>(name: str) -> bool</code>
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">retrieval_config</a>() -> Optional[Any]</code>
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">retrieve</a>(query: str, **kwargs) -> 'ContextPack'</code>
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">rules_manager</a>() -> Optional[Any]</code>
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">run_autonomous</a>(prompt: str, max_iterations: Optional[int] = None, timeout_seconds: Optional[float] = None, completion_promise: Optional[str] = None, clear_context: bool = False)</code>
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">run_autonomous_async</a>(prompt: str, max_iterations: Optional[int] = None, timeout_seconds: Optional[float] = None, completion_promise: Optional[str] = None, clear_context: bool = False)</code>
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">run_until</a>(prompt: str, criteria: str = '', threshold: float = 8.0, max_iterations: int = 5, mode: str = 'optimize', on_iteration: Optional[Callable[[Any], None]] = None, verbose: bool = False, goal: Optional[str] = None, goal_criteria: Optional[Any] = None, judge_model: Optional[str] = None) -> 'EvaluationLoopResult'</code>
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">run_until</a>(prompt: str, criteria: str, threshold: float = 8.0, max_iterations: int = 5, mode: str = 'optimize', on_iteration: Optional[Callable[[Any], None]] = None, verbose: bool = False) -> 'EvaluationLoopResult'</code>
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">run_until_async</a>(prompt: str, criteria: str, threshold: float = 8.0, max_iterations: int = 5, mode: str = 'optimize', on_iteration: Optional[Callable[[Any], None]] = None, verbose: bool = False) -> 'EvaluationLoopResult'</code>
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">set_snapshot_root</a>(project_path: str) -> bool</code>
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">skill_manager</a>() -> Optional[Any]</code>
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">store_memory</a>(content: str, memory_type: str = 'short_term', action: str = 'add', **kwargs: Any) -> None</code>
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">store_memory</a>(content: str, memory_type: str = 'short_term', **kwargs: Any) -> None</code>
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">stream_emitter</a>() -> Optional[Any]</code>
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">stream_emitter</a>(value: Optional[Any]) -> None</code>
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">thinking_budget</a>() -> Optional[int]</code>
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">thinking_budget</a>(value: Optional[int]) -> None</code>
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">total_cost</a>() -> float</code>
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">undo</a>() -> bool</code>
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">where_does_it_run</a>() -> str</code>
* <code title="class AutoAgents">AutoAgents.<a href="./src/praisonai-agents/praisonaiagents/agents/autoagents.py">astart</a>()</code>
* <code title="class AutoAgents">AutoAgents.<a href="./src/praisonai-agents/praisonaiagents/agents/autoagents.py">start</a>()</code>
* <code title="class AutoRagAgent">AutoRagAgent.<a href="./src/praisonai-agents/praisonaiagents/agents/auto_rag_agent.py">achat</a>(message: str, **kwargs) -> str</code>
@@ -175,7 +170,6 @@ Methods:
* <code title="class BaseTool">BaseTool.<a href="./src/praisonai-agents/praisonaiagents/tools/base.py">get_schema</a>() -> Dict[str, Any]</code>
* <code title="class BaseTool">BaseTool.<a href="./src/praisonai-agents/praisonaiagents/tools/base.py">run</a>(**kwargs) -> Any</code>
* <code title="class BaseTool">BaseTool.<a href="./src/praisonai-agents/praisonaiagents/tools/base.py">safe_run</a>(**kwargs) -> ToolResult</code>
* <code title="class BaseTool">BaseTool.<a href="./src/praisonai-agents/praisonaiagents/tools/base.py">to_model_output</a>(result: Any) -> Optional[Any]</code>
* <code title="class BaseTool">BaseTool.<a href="./src/praisonai-agents/praisonaiagents/tools/base.py">validate</a>() -> bool</code>
* <code title="class BaseTool">BaseTool.<a href="./src/praisonai-agents/praisonaiagents/tools/base.py">validate_class</a>() -> bool</code>
* <code title="class BaseTool">BaseTool.<a href="./src/praisonai-agents/praisonaiagents/tools/base.py">validate_schema_roundtrip</a>() -> bool</code>
@@ -183,24 +177,21 @@ Methods:
* <code title="class FunctionTool">FunctionTool.<a href="./src/praisonai-agents/praisonaiagents/tools/decorator.py">check_availability</a>() -> tuple[bool, str]</code>
* <code title="class FunctionTool">FunctionTool.<a href="./src/praisonai-agents/praisonaiagents/tools/decorator.py">injected_params</a>() -> Dict[str, Any]</code>
* <code title="class FunctionTool">FunctionTool.<a href="./src/praisonai-agents/praisonaiagents/tools/decorator.py">run</a>(**kwargs) -> Any</code>
* <code title="class FunctionTool">FunctionTool.<a href="./src/praisonai-agents/praisonaiagents/tools/decorator.py">to_model_output</a>(result: Any) -> Optional[Any]</code>
* <code title="class ToolRegistry">ToolRegistry.<a href="./src/praisonai-agents/praisonaiagents/tools/registry.py">clear</a>() -> None</code>
* <code title="class ToolRegistry">ToolRegistry.<a href="./src/praisonai-agents/praisonaiagents/tools/registry.py">discover_plugins</a>() -> int</code>
* <code title="class ToolRegistry">ToolRegistry.<a href="./src/praisonai-agents/praisonaiagents/tools/registry.py">discover_single_file_plugins</a>() -> int</code>
* <code title="class ToolRegistry">ToolRegistry.<a href="./src/praisonai-agents/praisonaiagents/tools/registry.py">get</a>(name: str) -> Optional[Union[BaseTool, Callable]]</code>
* <code title="class ToolRegistry">ToolRegistry.<a href="./src/praisonai-agents/praisonaiagents/tools/registry.py">get_all</a>() -> Dict[str, Union[BaseTool, Callable]]</code>
* <code title="class ToolRegistry">ToolRegistry.<a href="./src/praisonai-agents/praisonaiagents/tools/registry.py">get_tool_definitions</a>(permission_resolver: Optional[Callable[[str], bool]] = None) -> List[Dict[str, Any]]</code>
* <code title="class ToolRegistry">ToolRegistry.<a href="./src/praisonai-agents/praisonaiagents/tools/registry.py">get_trust_level</a>(name: str) -> Optional[str]</code>
* <code title="class ToolRegistry">ToolRegistry.<a href="./src/praisonai-agents/praisonaiagents/tools/registry.py">list_available_tools</a>(context: Optional[Dict[str, Any]] = None, ttl_seconds: Optional[float] = None) -> List[Union[BaseTool, Callable]]</code>
* <code title="class ToolRegistry">ToolRegistry.<a href="./src/praisonai-agents/praisonaiagents/tools/registry.py">list_available_tools</a>(context: Optional[Dict[str, Any]] = None) -> List[Union[BaseTool, Callable]]</code>
* <code title="class ToolRegistry">ToolRegistry.<a href="./src/praisonai-agents/praisonaiagents/tools/registry.py">list_base_tools</a>() -> List[BaseTool]</code>
* <code title="class ToolRegistry">ToolRegistry.<a href="./src/praisonai-agents/praisonaiagents/tools/registry.py">list_tools</a>() -> List[str]</code>
* <code title="class ToolRegistry">ToolRegistry.<a href="./src/praisonai-agents/praisonaiagents/tools/registry.py">list_tools_with_allowed_filter</a>(context: Optional[Dict[str, Any]] = None) -> List[str]</code>
* <code title="class ToolRegistry">ToolRegistry.<a href="./src/praisonai-agents/praisonaiagents/tools/registry.py">register</a>(tool: Union[BaseTool, Callable], name: Optional[str] = None, overwrite: bool = False, trust_level: Optional[str] = None, dynamic_schema_overrides: Optional[Callable[[Dict[str, Any]], Dict[str, Any]]] = None) -> None</code>
* <code title="class ToolRegistry">ToolRegistry.<a href="./src/praisonai-agents/praisonaiagents/tools/registry.py">register</a>(tool: Union[BaseTool, Callable], name: Optional[str] = None, overwrite: bool = False) -> None</code>
* <code title="class ToolRegistry">ToolRegistry.<a href="./src/praisonai-agents/praisonaiagents/tools/registry.py">unregister</a>(name: str) -> bool</code>
* <code title="class Tools">Tools.<a href="./src/praisonai-agents/praisonaiagents/tools/tools.py">internet_search</a>(*args, **kwargs)</code>
* <code title="function">praisonaiagents.<a href="./src/praisonai-agents/praisonaiagents/tools/registry.py">get_registry</a>() -> ToolRegistry</code>
* <code title="function">praisonaiagents.<a href="./src/praisonai-agents/praisonaiagents/tools/registry.py">get_tool</a>(name: str) -> Optional[Union[BaseTool, Callable]]</code>
* <code title="function">praisonaiagents.<a href="./src/praisonai-agents/praisonaiagents/tools/registry.py">register_tool</a>(tool: Union[BaseTool, Callable], name: Optional[str] = None, trust_level: Optional[str] = None, dynamic_schema_overrides: Optional[Callable[[Dict[str, Any]], Dict[str, Any]]] = None) -> None</code>
* <code title="function">praisonaiagents.<a href="./src/praisonai-agents/praisonaiagents/tools/registry.py">register_tool</a>(tool: Union[BaseTool, Callable], name: Optional[str] = None) -> None</code>
* <code title="function">praisonaiagents.<a href="./src/praisonai-agents/praisonaiagents/tools/decorator.py">tool</a>(func: Optional[Callable] = None) -> Union[FunctionTool, Callable[[Callable], FunctionTool]]</code>
* <code title="function">praisonaiagents.<a href="./src/praisonai-agents/praisonaiagents/tools/base.py">validate_tool</a>(tool: Any) -> bool</code>
@@ -229,6 +220,13 @@ Methods:
* <code title="function">praisonaiagents.<a href="./src/praisonai-agents/praisonaiagents/workflows/workflows.py">repeat</a>(step: Any, until: Optional[Callable[[WorkflowContext], bool]] = None, max_iterations: int = 10) -> Repeat</code>
* <code title="function">praisonaiagents.<a href="./src/praisonai-agents/praisonaiagents/workflows/workflows.py">route</a>(routes: Dict[str, List], default: Optional[List] = None) -> Route</code>
# DB
Types:
```python
from praisonaiagents import db
```
# Memory
Types:
@@ -238,7 +236,6 @@ from praisonaiagents import Memory, MemoryBackend, MemoryConfig
Methods:
* <code title="class Memory">Memory.<a href="./src/praisonai-agents/praisonaiagents/memory/memory.py">build_cache_optimized_context</a>(task_descr: str, user_id: Optional[str] = None, additional: str = '', max_items: int = 3, include_cache_boundary: bool = True, include_in_output: Optional[bool] = None) -> Dict[str, str]</code>
* <code title="class Memory">Memory.<a href="./src/praisonai-agents/praisonaiagents/memory/memory.py">build_context_for_task</a>(task_descr: str, user_id: Optional[str] = None, additional: str = '', max_items: int = 3, include_in_output: Optional[bool] = None) -> str</code>
* <code title="class Memory">Memory.<a href="./src/praisonai-agents/praisonaiagents/memory/memory.py">calculate_quality_metrics</a>(output: str, expected_output: str, llm: Optional[str] = None, custom_prompt: Optional[str] = None) -> Dict[str, float]</code>
* <code title="class Memory">Memory.<a href="./src/praisonai-agents/praisonaiagents/memory/memory.py">close_connections</a>()</code>
@@ -249,12 +246,9 @@ Methods:
* <code title="class Memory">Memory.<a href="./src/praisonai-agents/praisonaiagents/memory/memory.py">delete_memory</a>(memory_id: str, memory_type: Optional[str] = None) -> bool</code>
* <code title="class Memory">Memory.<a href="./src/praisonai-agents/praisonaiagents/memory/memory.py">delete_short_term</a>(memory_id: str) -> bool</code>
* <code title="class Memory">Memory.<a href="./src/praisonai-agents/praisonaiagents/memory/memory.py">finalize_task_output</a>(content: str, agent_name: str, quality_score: float, threshold: float = 0.7, metrics: Dict[str, Any] = None, task_id: str = None)</code>
* <code title="class Memory">Memory.<a href="./src/praisonai-agents/praisonaiagents/memory/memory.py">forget</a>(**kwargs) -> int</code>
* <code title="class Memory">Memory.<a href="./src/praisonai-agents/praisonaiagents/memory/memory.py">get_all_memories</a>() -> List[Dict[str, Any]]</code>
* <code title="class Memory">Memory.<a href="./src/praisonai-agents/praisonaiagents/memory/memory.py">get_learn_context</a>() -> str</code>
* <code title="class Memory">Memory.<a href="./src/praisonai-agents/praisonaiagents/memory/memory.py">learn</a>()</code>
* <code title="class Memory">Memory.<a href="./src/praisonai-agents/praisonaiagents/memory/memory.py">recall</a>(query: str, **kwargs) -> List[Dict[str, Any]]</code>
* <code title="class Memory">Memory.<a href="./src/praisonai-agents/praisonaiagents/memory/memory.py">remember</a>(content: str, **kwargs) -> str</code>
* <code title="class Memory">Memory.<a href="./src/praisonai-agents/praisonaiagents/memory/memory.py">reset_all</a>()</code>
* <code title="class Memory">Memory.<a href="./src/praisonai-agents/praisonaiagents/memory/memory.py">reset_entity_only</a>()</code>
* <code title="class Memory">Memory.<a href="./src/praisonai-agents/praisonaiagents/memory/memory.py">reset_long_term</a>()</code>
@@ -262,8 +256,8 @@ Methods:
* <code title="class Memory">Memory.<a href="./src/praisonai-agents/praisonaiagents/memory/memory.py">reset_user_memory</a>()</code>
* <code title="class Memory">Memory.<a href="./src/praisonai-agents/praisonaiagents/memory/memory.py">search</a>(query: str, user_id: Optional[str] = None, agent_id: Optional[str] = None, run_id: Optional[str] = None, limit: int = 5, rerank: bool = False, **kwargs) -> List[Dict[str, Any]]</code>
* <code title="class Memory">Memory.<a href="./src/praisonai-agents/praisonaiagents/memory/memory.py">search_entity</a>(query: str, limit: int = 5) -> List[Dict[str, Any]]</code>
* <code title="class Memory">Memory.<a href="./src/praisonai-agents/praisonaiagents/memory/memory.py">search_long_term</a>(query: str, limit: int = 5, relevance_cutoff: float = 0.0, min_quality: float = 0.0, rerank: bool = False, metadata_filter: Optional[Dict[str, Any]] = None, user_id: Optional[str] = None, **kwargs) -> List[Dict[str, Any]]</code>
* <code title="class Memory">Memory.<a href="./src/praisonai-agents/praisonaiagents/memory/memory.py">search_short_term</a>(query: str, limit: int = 5, min_quality: float = 0.0, relevance_cutoff: float = 0.0, rerank: bool = False, metadata_filter: Optional[Dict[str, Any]] = None, user_id: Optional[str] = None, **kwargs) -> List[Dict[str, Any]]</code>
* <code title="class Memory">Memory.<a href="./src/praisonai-agents/praisonaiagents/memory/memory.py">search_long_term</a>(query: str, limit: int = 5, relevance_cutoff: float = 0.0, min_quality: float = 0.0, rerank: bool = False, **kwargs) -> List[Dict[str, Any]]</code>
* <code title="class Memory">Memory.<a href="./src/praisonai-agents/praisonaiagents/memory/memory.py">search_short_term</a>(query: str, limit: int = 5, min_quality: float = 0.0, relevance_cutoff: float = 0.0, rerank: bool = False, **kwargs) -> List[Dict[str, Any]]</code>
* <code title="class Memory">Memory.<a href="./src/praisonai-agents/praisonaiagents/memory/memory.py">search_user_memory</a>(user_id: str, query: str, limit: int = 5, rerank: bool = False, **kwargs) -> List[Dict[str, Any]]</code>
* <code title="class Memory">Memory.<a href="./src/praisonai-agents/praisonaiagents/memory/memory.py">search_with_quality</a>(query: str, min_quality: float = 0.0, memory_type: Literal['short', 'long'] = 'long', limit: int = 5) -> List[Dict[str, Any]]</code>
* <code title="class Memory">Memory.<a href="./src/praisonai-agents/praisonaiagents/memory/memory.py">store_entity</a>(name: str, type_: str, desc: str, relations: str)</code>
@@ -359,7 +353,7 @@ Methods:
* <code title="class Handoff">Handoff.<a href="./src/praisonai-agents/praisonaiagents/agent/handoff.py">to_tool_function</a>(source_agent: 'Agent') -> Callable</code>
* <code title="class Handoff">Handoff.<a href="./src/praisonai-agents/praisonaiagents/agent/handoff.py">tool_description</a>() -> str</code>
* <code title="class Handoff">Handoff.<a href="./src/praisonai-agents/praisonaiagents/agent/handoff.py">tool_name</a>() -> str</code>
* <code title="function">praisonaiagents.<a href="./src/praisonai-agents/praisonaiagents/agent/handoff.py">handoff</a>(agent: 'Agent', tool_name_override: Optional[str] = None, tool_description_override: Optional[str] = None, on_handoff: Optional[Callable] = None, input_type: Optional[type] = None, input_filter: Optional[Callable[[HandoffInputData], HandoffInputData]] = None, config: Optional[HandoffConfig] = None, context_policy: Optional[str] = None, timeout_seconds: Optional[float] = None, max_concurrent: Optional[int] = None, detect_cycles: Optional[bool] = None, max_depth: Optional[int] = None, tool_policy_mode: Optional[Literal['intersect', 'passthrough']] = None, blocked_tools: Optional[List[str]] = None) -> Handoff</code>
* <code title="function">praisonaiagents.<a href="./src/praisonai-agents/praisonaiagents/agent/handoff.py">handoff</a>(agent: 'Agent', tool_name_override: Optional[str] = None, tool_description_override: Optional[str] = None, on_handoff: Optional[Callable] = None, input_type: Optional[type] = None, input_filter: Optional[Callable[[HandoffInputData], HandoffInputData]] = None, config: Optional[HandoffConfig] = None, context_policy: Optional[str] = None, timeout_seconds: Optional[float] = None, max_concurrent: Optional[int] = None, detect_cycles: Optional[bool] = None, max_depth: Optional[int] = None) -> Handoff</code>
* <code title="class handoff_filters">handoff_filters.<a href="./src/praisonai-agents/praisonaiagents/agent/handoff.py">compress_history</a>(data: HandoffInputData) -> HandoffInputData</code>
* <code title="class handoff_filters">handoff_filters.<a href="./src/praisonai-agents/praisonaiagents/agent/handoff.py">keep_last_n_messages</a>(n: int) -> Callable[[HandoffInputData], HandoffInputData]</code>
* <code title="class handoff_filters">handoff_filters.<a href="./src/praisonai-agents/praisonaiagents/agent/handoff.py">remove_all_tools</a>(data: HandoffInputData) -> HandoffInputData</code>
@@ -463,7 +457,7 @@ Methods:
Types:
```python
from praisonaiagents import SkillLoader, SkillsConfig
from praisonaiagents import SkillLoader, SkillManager, SkillMetadata, SkillProperties, SkillsConfig
```
Methods:
@@ -475,6 +469,32 @@ Methods:
* <code title="class SkillLoader">SkillLoader.<a href="./src/praisonai-agents/praisonaiagents/skills/loader.py">load_metadata</a>(skill_path: str) -> Optional[LoadedSkill]</code>
* <code title="class SkillLoader">SkillLoader.<a href="./src/praisonai-agents/praisonaiagents/skills/loader.py">load_references</a>(skill: LoadedSkill) -> dict</code>
* <code title="class SkillLoader">SkillLoader.<a href="./src/praisonai-agents/praisonaiagents/skills/loader.py">load_scripts</a>(skill: LoadedSkill) -> dict</code>
* <code title="class SkillManager">SkillManager.<a href="./src/praisonai-agents/praisonaiagents/skills/manager.py">activate</a>(skill: LoadedSkill) -> bool</code>
* <code title="class SkillManager">SkillManager.<a href="./src/praisonai-agents/praisonaiagents/skills/manager.py">activate_by_name</a>(name: str) -> bool</code>
* <code title="class SkillManager">SkillManager.<a href="./src/praisonai-agents/praisonaiagents/skills/manager.py">add_skill</a>(skill_path: str) -> Optional[LoadedSkill]</code>
* <code title="class SkillManager">SkillManager.<a href="./src/praisonai-agents/praisonaiagents/skills/manager.py">clear</a>() -> None</code>
* <code title="class SkillManager">SkillManager.<a href="./src/praisonai-agents/praisonaiagents/skills/manager.py">create_skill</a>(name: str, content: str, category: str = None) -> dict</code>
* <code title="class SkillManager">SkillManager.<a href="./src/praisonai-agents/praisonaiagents/skills/manager.py">delete_skill</a>(name: str) -> dict</code>
* <code title="class SkillManager">SkillManager.<a href="./src/praisonai-agents/praisonaiagents/skills/manager.py">discover</a>(skill_dirs: Optional[List[str]] = None, include_defaults: bool = True) -> int</code>
* <code title="class SkillManager">SkillManager.<a href="./src/praisonai-agents/praisonaiagents/skills/manager.py">edit_skill</a>(name: str, content: str) -> dict</code>
* <code title="class SkillManager">SkillManager.<a href="./src/praisonai-agents/praisonaiagents/skills/manager.py">get_allowed_tools</a>(name: str) -> List[str]</code>
* <code title="class SkillManager">SkillManager.<a href="./src/praisonai-agents/praisonaiagents/skills/manager.py">get_available_skills</a>() -> List[SkillMetadata]</code>
* <code title="class SkillManager">SkillManager.<a href="./src/praisonai-agents/praisonaiagents/skills/manager.py">get_available_skills_by_state</a>(state: SkillState) -> List[LoadedSkill]</code>
* <code title="class SkillManager">SkillManager.<a href="./src/praisonai-agents/praisonaiagents/skills/manager.py">get_instructions</a>(name: str) -> Optional[str]</code>
* <code title="class SkillManager">SkillManager.<a href="./src/praisonai-agents/praisonaiagents/skills/manager.py">get_skill</a>(name: str) -> Optional[LoadedSkill]</code>
* <code title="class SkillManager">SkillManager.<a href="./src/praisonai-agents/praisonaiagents/skills/manager.py">get_skills_diagnostics</a>() -> Dict[str, ValidationResult]</code>
* <code title="class SkillManager">SkillManager.<a href="./src/praisonai-agents/praisonaiagents/skills/manager.py">get_user_invocable_skills</a>() -> List[LoadedSkill]</code>
* <code title="class SkillManager">SkillManager.<a href="./src/praisonai-agents/praisonaiagents/skills/manager.py">invoke</a>(name: str, raw_args: str = '', session_id: Optional[str] = None, shell_exec: bool = False) -> Optional[str]</code>
* <code title="class SkillManager">SkillManager.<a href="./src/praisonai-agents/praisonaiagents/skills/manager.py">load_resources</a>(name: str) -> bool</code>
* <code title="class SkillManager">SkillManager.<a href="./src/praisonai-agents/praisonaiagents/skills/manager.py">patch_skill</a>(name: str, old_string: str, new_string: str, file_path: str = None, replace_all: bool = False) -> dict</code>
* <code title="class SkillManager">SkillManager.<a href="./src/praisonai-agents/praisonaiagents/skills/manager.py">remove_skill_file</a>(name: str, file_path: str) -> dict</code>
* <code title="class SkillManager">SkillManager.<a href="./src/praisonai-agents/praisonaiagents/skills/manager.py">skill_names</a>() -> List[str]</code>
* <code title="class SkillManager">SkillManager.<a href="./src/praisonai-agents/praisonaiagents/skills/manager.py">skills</a>() -> List[LoadedSkill]</code>
* <code title="class SkillManager">SkillManager.<a href="./src/praisonai-agents/praisonaiagents/skills/manager.py">to_prompt</a>() -> str</code>
* <code title="class SkillManager">SkillManager.<a href="./src/praisonai-agents/praisonaiagents/skills/manager.py">validate_skill_capabilities</a>(skill_name: str, force_refresh: bool = False) -> ValidationResult</code>
* <code title="class SkillManager">SkillManager.<a href="./src/praisonai-agents/praisonaiagents/skills/manager.py">write_skill_file</a>(name: str, file_path: str, file_content: str) -> dict</code>
* <code title="class SkillMetadata">SkillMetadata.<a href="./src/praisonai-agents/praisonaiagents/skills/models.py">from_properties</a>(props: SkillProperties) -> 'SkillMetadata'</code>
* <code title="class SkillProperties">SkillProperties.<a href="./src/praisonai-agents/praisonaiagents/skills/models.py">to_dict</a>() -> dict</code>
* <code title="class SkillsConfig">SkillsConfig.<a href="./src/praisonai-agents/praisonaiagents/config/feature_configs.py">to_dict</a>() -> Dict[str, Any]</code>
# Session
@@ -491,12 +511,10 @@ Methods:
* <code title="class Session">Session.<a href="./src/praisonai-agents/praisonaiagents/session/api.py">add_memory</a>(text: str, memory_type: str = 'long', **metadata) -> None</code>
* <code title="class Session">Session.<a href="./src/praisonai-agents/praisonaiagents/session/api.py">chat</a>(message: str, **kwargs) -> str</code>
* <code title="class Session">Session.<a href="./src/praisonai-agents/praisonaiagents/session/api.py">clear_memory</a>(memory_type: str = 'all') -> None</code>
* <code title="class Session">Session.<a href="./src/praisonai-agents/praisonaiagents/session/api.py">close</a>() -> None</code>
* <code title="class Session">Session.<a href="./src/praisonai-agents/praisonaiagents/session/api.py">create_agent</a>(*args, **kwargs) -> 'Agent'</code>
* <code title="class Session">Session.<a href="./src/praisonai-agents/praisonaiagents/session/api.py">get_context</a>(query: str, max_items: int = 3) -> str</code>
* <code title="class Session">Session.<a href="./src/praisonai-agents/praisonaiagents/session/api.py">get_state</a>(key: str, default: Any = None) -> Any</code>
* <code title="class Session">Session.<a href="./src/praisonai-agents/praisonaiagents/session/api.py">increment_state</a>(key: str, increment: int = 1, default: int = 0) -> None</code>
* <code title="class Session">Session.<a href="./src/praisonai-agents/praisonaiagents/session/api.py">is_expired</a>() -> bool</code>
* <code title="class Session">Session.<a href="./src/praisonai-agents/praisonaiagents/session/api.py">knowledge</a>() -> 'Knowledge'</code>
* <code title="class Session">Session.<a href="./src/praisonai-agents/praisonaiagents/session/api.py">memory</a>() -> 'Memory'</code>
* <code title="class Session">Session.<a href="./src/praisonai-agents/praisonaiagents/session/api.py">restore_state</a>() -> Dict[str, Any]</code>
@@ -505,7 +523,6 @@ Methods:
* <code title="class Session">Session.<a href="./src/praisonai-agents/praisonaiagents/session/api.py">search_memory</a>(query: str, memory_type: str = 'long', limit: int = 5) -> List[Dict[str, Any]]</code>
* <code title="class Session">Session.<a href="./src/praisonai-agents/praisonaiagents/session/api.py">send_message</a>(message: str, **kwargs) -> str</code>
* <code title="class Session">Session.<a href="./src/praisonai-agents/praisonaiagents/session/api.py">set_state</a>(key: str, value: Any) -> None</code>
* <code title="class Session">Session.<a href="./src/praisonai-agents/praisonaiagents/session/api.py">time_to_expiry</a>() -> Optional[float]</code>
# MCP
@@ -516,14 +533,9 @@ from praisonaiagents import MCP
Methods:
* <code title="class MCP">MCP.<a href="./src/praisonai-agents/praisonaiagents/mcp/mcp.py">apply_tool_filters</a>(allowed_tools: Optional[List[str]] = None, disabled_tools: Optional[List[str]] = None) -> 'MCP'</code>
* <code title="class MCP">MCP.<a href="./src/praisonai-agents/praisonaiagents/mcp/mcp.py">get_prompts</a>() -> List[dict]</code>
* <code title="class MCP">MCP.<a href="./src/praisonai-agents/praisonaiagents/mcp/mcp.py">get_resources</a>() -> List[dict]</code>
* <code title="class MCP">MCP.<a href="./src/praisonai-agents/praisonaiagents/mcp/mcp.py">get_tools</a>() -> List[Callable]</code>
* <code title="class MCP">MCP.<a href="./src/praisonai-agents/praisonaiagents/mcp/mcp.py">list_active_server_names</a>() -> set</code>
* <code title="class MCP">MCP.<a href="./src/praisonai-agents/praisonaiagents/mcp/mcp.py">shutdown</a>()</code>
* <code title="class MCP">MCP.<a href="./src/praisonai-agents/praisonaiagents/mcp/mcp.py">to_openai_tool</a>()</code>
* <code title="class MCP">MCP.<a href="./src/praisonai-agents/praisonaiagents/mcp/mcp.py">with_tool_prefix</a>(prefix: str) -> 'MCP'</code>
# Telemetry
@@ -593,7 +605,7 @@ Methods:
* <code title="class ContextManager">ContextManager.<a href="./src/praisonai-agents/praisonaiagents/context/manager.py">register_snapshot_callback</a>(callback: Callable[[SnapshotHookData], None]) -> None</code>
* <code title="class ContextManager">ContextManager.<a href="./src/praisonai-agents/praisonaiagents/context/manager.py">reset</a>() -> None</code>
* <code title="class ContextManager">ContextManager.<a href="./src/praisonai-agents/praisonaiagents/context/manager.py">set_tool_budget</a>(tool_name: str, max_tokens: int, protected: bool = False) -> None</code>
* <code title="class ContextManager">ContextManager.<a href="./src/praisonai-agents/praisonaiagents/context/manager.py">truncate_tool_output</a>(tool_name: str, output: str, tool_call_id: str = None, run_id: str = None) -> str</code>
* <code title="class ContextManager">ContextManager.<a href="./src/praisonai-agents/praisonaiagents/context/manager.py">truncate_tool_output</a>(tool_name: str, output: str) -> str</code>
# UI
@@ -614,9 +626,6 @@ Methods:
* <code title="class AutonomyConfig">AutonomyConfig.<a href="./src/praisonai-agents/praisonaiagents/agent/autonomy.py">effective_track_changes</a>() -> bool</code>
* <code title="class AutonomyConfig">AutonomyConfig.<a href="./src/praisonai-agents/praisonaiagents/agent/autonomy.py">from_dict</a>(data: Dict[str, Any]) -> 'AutonomyConfig'</code>
* <code title="class CachingConfig">CachingConfig.<a href="./src/praisonai-agents/praisonaiagents/config/feature_configs.py">to_dict</a>() -> Dict[str, Any]</code>
* <code title="class ExecutionConfig">ExecutionConfig.<a href="./src/praisonai-agents/praisonaiagents/config/feature_configs.py">from_dict</a>(data: Dict[str, Any]) -> 'ExecutionConfig'</code>
* <code title="class ExecutionConfig">ExecutionConfig.<a href="./src/praisonai-agents/praisonaiagents/config/feature_configs.py">resolved_max_steps</a>() -> int</code>
* <code title="class ExecutionConfig">ExecutionConfig.<a href="./src/praisonai-agents/praisonaiagents/config/feature_configs.py">resolved_max_tool_calls</a>() -> int</code>
* <code title="class ExecutionConfig">ExecutionConfig.<a href="./src/praisonai-agents/praisonaiagents/config/feature_configs.py">to_dict</a>() -> Dict[str, Any]</code>
* <code title="class GuardrailConfig">GuardrailConfig.<a href="./src/praisonai-agents/praisonaiagents/config/feature_configs.py">to_dict</a>() -> Dict[str, Any]</code>
* <code title="class HooksConfig">HooksConfig.<a href="./src/praisonai-agents/praisonaiagents/config/feature_configs.py">to_dict</a>() -> Dict[str, Any]</code>
@@ -684,7 +693,7 @@ Methods:
Types:
```python
from praisonaiagents import AgentAppConfig, AgentAppProtocol, AgentFlow, AgentManager, AgentOSConfig, AgentOSProtocol, AgentTeam, AutoApproveBackend, EmbeddingResult, RetryBackoffConfig, RunOutcome, __version__, aembedding, aembeddings, embedding, embeddings, get_dimensions
from praisonaiagents import AgentAppConfig, AgentAppProtocol, AgentFlow, AgentManager, AgentOSConfig, AgentOSProtocol, AgentTeam, AutoApproveBackend, EmbeddingResult, aembedding, aembeddings, embedding, embeddings, get_dimensions
```
Methods:
@@ -707,20 +716,14 @@ Methods:
* <code title="class AgentFlow">AgentFlow.<a href="./src/praisonai-agents/praisonaiagents/workflows/workflows.py">to_dict</a>() -> Dict[str, Any]</code>
* <code title="class AgentFlow">AgentFlow.<a href="./src/praisonai-agents/praisonaiagents/workflows/workflows.py">verbose</a>() -> bool</code>
* <code title="class AgentFlow">AgentFlow.<a href="./src/praisonai-agents/praisonaiagents/workflows/workflows.py">verbose</a>(value: bool)</code>
* <code title="class AgentFlow">AgentFlow.<a href="./src/praisonai-agents/praisonaiagents/workflows/workflows.py">where_does_it_run</a>() -> str</code>
* <code title="class AgentOSProtocol">AgentOSProtocol.<a href="./src/praisonai-agents/praisonaiagents/app/protocols.py">get_app</a>() -> Any</code>
* <code title="class AgentOSProtocol">AgentOSProtocol.<a href="./src/praisonai-agents/praisonaiagents/app/protocols.py">serve</a>(host: Optional[str] = None, port: Optional[int] = None, reload: bool = False, **kwargs: Any) -> None</code>
* <code title="class AgentTeam">AgentTeam.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">aannounce_completion</a>(agent_id: str, task_id: str, result: Any, success: bool = True, error: Optional[str] = None, metadata: Optional[Dict[str, Any]] = None) -> None</code>
* <code title="class AgentTeam">AgentTeam.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">add_task</a>(task)</code>
* <code title="class AgentTeam">AgentTeam.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">aexecute_task</a>(task_id)</code>
* <code title="class AgentTeam">AgentTeam.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">announce_completion</a>(agent_id: str, task_id: str, result: Any, success: bool = True, error: Optional[str] = None, metadata: Optional[Dict[str, Any]] = None) -> None</code>
* <code title="class AgentTeam">AgentTeam.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">append_to_state</a>(key: str, value: Any, max_length: Optional[int] = None) -> List[Any]</code>
* <code title="class AgentTeam">AgentTeam.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">arun_all_tasks</a>()</code>
* <code title="class AgentTeam">AgentTeam.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">arun_task</a>(task_id)</code>
* <code title="class AgentTeam">AgentTeam.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">aspawn_sub_agent</a>(agent: Agent, task: Any, completion_callback: Optional[Callable[[SubAgentCompletionEvent], Any]] = None, metadata: Optional[Dict[str, Any]] = None) -> SpawnedSubAgent</code>
* <code title="class AgentTeam">AgentTeam.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">astart</a>(content = None, return_dict = False, **kwargs)</code>
* <code title="class AgentTeam">AgentTeam.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">astart_for_each</a>(inputs, **kwargs)</code>
* <code title="class AgentTeam">AgentTeam.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">await_for_completions</a>(timeout: Optional[float] = None, agent_ids: Optional[List[str]] = None) -> List[SubAgentCompletionEvent]</code>
* <code title="class AgentTeam">AgentTeam.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">clean_json_output</a>(output: str) -> str</code>
* <code title="class AgentTeam">AgentTeam.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">clear_state</a>() -> None</code>
* <code title="class AgentTeam">AgentTeam.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">close</a>() -> None</code>
@@ -735,7 +738,6 @@ Methods:
* <code title="class AgentTeam">AgentTeam.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">get_all_tasks_status</a>()</code>
* <code title="class AgentTeam">AgentTeam.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">get_detailed_token_report</a>() -> Dict[str, Any]</code>
* <code title="class AgentTeam">AgentTeam.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">get_plan_markdown</a>() -> str</code>
* <code title="class AgentTeam">AgentTeam.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">get_spawned_agents</a>() -> List[SpawnedSubAgent]</code>
* <code title="class AgentTeam">AgentTeam.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">get_state</a>(key: str, default: Any = None) -> Any</code>
* <code title="class AgentTeam">AgentTeam.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">get_task_details</a>(task_id)</code>
* <code title="class AgentTeam">AgentTeam.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">get_task_result</a>(task_id)</code>
@@ -750,22 +752,14 @@ Methods:
* <code title="class AgentTeam">AgentTeam.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">run_all_tasks</a>()</code>
* <code title="class AgentTeam">AgentTeam.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">run_task</a>(task_id)</code>
* <code title="class AgentTeam">AgentTeam.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">save_output_to_file</a>(task, task_output)</code>
* <code title="class AgentTeam">AgentTeam.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">save_session_state</a>(session_id: str, include_memory: bool = True) -> bool</code>
* <code title="class AgentTeam">AgentTeam.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">save_session_state</a>(session_id: str, include_memory: bool = True) -> None</code>
* <code title="class AgentTeam">AgentTeam.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">set_state</a>(key: str, value: Any) -> None</code>
* <code title="class AgentTeam">AgentTeam.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">spawn_sub_agent</a>(agent: Agent, task: Any, completion_callback: Optional[Callable[[SubAgentCompletionEvent], Any]] = None, metadata: Optional[Dict[str, Any]] = None) -> SpawnedSubAgent</code>
* <code title="class AgentTeam">AgentTeam.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">start</a>(content = None, return_dict = False, output = None, **kwargs)</code>
* <code title="class AgentTeam">AgentTeam.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">start_for_each</a>(inputs, **kwargs)</code>
* <code title="class AgentTeam">AgentTeam.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">stream_emitter</a>()</code>
* <code title="class AgentTeam">AgentTeam.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">todo_list</a>()</code>
* <code title="class AgentTeam">AgentTeam.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">update_plan_step_status</a>(step_id: str, status: str) -> bool</code>
* <code title="class AgentTeam">AgentTeam.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">update_state</a>(updates: Dict) -> None</code>
* <code title="class AgentTeam">AgentTeam.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">wait_for_completions</a>(timeout: Optional[float] = None, agent_ids: Optional[List[str]] = None) -> List[SubAgentCompletionEvent]</code>
* <code title="class AgentTeam">AgentTeam.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">where_does_it_run</a>() -> str</code>
* <code title="class AutoApproveBackend">AutoApproveBackend.<a href="./src/praisonai-agents/praisonaiagents/approval/backends.py">request_approval</a>(request: ApprovalRequest) -> ApprovalDecision</code>
* <code title="class AutoApproveBackend">AutoApproveBackend.<a href="./src/praisonai-agents/praisonaiagents/approval/backends.py">request_approval_sync</a>(request: ApprovalRequest) -> ApprovalDecision</code>
* <code title="class RunOutcome">RunOutcome.<a href="./src/praisonai-agents/praisonaiagents/agent/run_outcome.py">completed</a>(output: Optional[str] = None) -> 'RunOutcome'</code>
* <code title="class RunOutcome">RunOutcome.<a href="./src/praisonai-agents/praisonaiagents/agent/run_outcome.py">from_exception</a>(exc: BaseException, output: Optional[str] = None) -> 'RunOutcome'</code>
* <code title="class RunOutcome">RunOutcome.<a href="./src/praisonai-agents/praisonaiagents/agent/run_outcome.py">succeeded</a>() -> bool</code>
* <code title="function">praisonaiagents.<a href="./src/praisonai-agents/praisonaiagents/embedding/embed.py">aembedding</a>(input: Union[str, List[str]], model: str = 'text-embedding-3-small', dimensions: Optional[int] = None, encoding_format: str = 'float', timeout: float = 600.0, api_key: Optional[str] = None, api_base: Optional[str] = None, metadata: Optional[Dict[str, Any]] = None, **kwargs) -> EmbeddingResult</code>
* <code title="function">praisonaiagents.<a href="./src/praisonai-agents/praisonaiagents/embedding/embed.py">aembeddings</a>(input: Union[str, List[str]], model: str = 'text-embedding-3-small', dimensions: Optional[int] = None, encoding_format: str = 'float', timeout: float = 600.0, api_key: Optional[str] = None, api_base: Optional[str] = None, metadata: Optional[Dict[str, Any]] = None, **kwargs) -> EmbeddingResult</code>
* <code title="function">praisonaiagents.<a href="./src/praisonai-agents/praisonaiagents/embedding/dimensions.py">get_dimensions</a>(model_name: str) -> int</code>
@@ -774,7 +768,7 @@ Methods:
Types:
```python
from praisonai import Agent, AgentApp, AgentOS, AnthropicManagedAgent, DB, HostedAgent, HostedAgentConfig, LocalAgent, LocalAgentConfig, LocalManagedAgent, LocalManagedConfig, ManagedAgent, ManagedConfig, __version__, arun, run
from praisonai import Agent, AgentApp, AgentOS, AnthropicManagedAgent, CloudProvider, DB, Deploy, DeployConfig, DeployType, HostedAgent, HostedAgentConfig, LocalAgent, LocalAgentConfig, LocalManagedAgent, LocalManagedConfig, ManagedAgent, ManagedConfig, PraisonAI, __version__, arun, run, run_integrated_gateway
```
# CLI
@@ -782,14 +776,64 @@ from praisonai import Agent, AgentApp, AgentOS, AnthropicManagedAgent, DB, Hoste
Methods:
* <code title="cli">praisonai <a href="./src/praisonai/praisonai/cli/main.py">--help</a></code>
* <code title="cli">praisonai acp acp-main <a href="./src/praisonai/praisonai/cli/commands/acp.py">--help</a></code>
* <code title="cli">praisonai agents create <a href="./src/praisonai/praisonai/cli/commands/agents.py">--help</a></code>
* <code title="cli">praisonai agents info <a href="./src/praisonai/praisonai/cli/commands/agents.py">--help</a></code>
* <code title="cli">praisonai agents list <a href="./src/praisonai/praisonai/cli/commands/agents.py">--help</a></code>
* <code title="cli">praisonai app app <a href="./src/praisonai/praisonai/cli/commands/app.py">--help</a></code>
* <code title="cli">praisonai audit agent-centric <a href="./src/praisonai/praisonai/cli/commands/audit.py">--help</a></code>
* <code title="cli">praisonai batch batch-run <a href="./src/praisonai/praisonai/cli/commands/batch.py">--help</a></code>
* <code title="cli">praisonai batch list <a href="./src/praisonai/praisonai/cli/commands/batch.py">--help</a></code>
* <code title="cli">praisonai batch report <a href="./src/praisonai/praisonai/cli/commands/batch.py">--help</a></code>
* <code title="cli">praisonai batch stats <a href="./src/praisonai/praisonai/cli/commands/batch.py">--help</a></code>
* <code title="cli">praisonai benchmark agent <a href="./src/praisonai/praisonai/cli/commands/benchmark.py">--help</a></code>
* <code title="cli">praisonai benchmark benchmark-callback <a href="./src/praisonai/praisonai/cli/commands/benchmark.py">--help</a></code>
* <code title="cli">praisonai benchmark cli <a href="./src/praisonai/praisonai/cli/commands/benchmark.py">--help</a></code>
* <code title="cli">praisonai benchmark compare <a href="./src/praisonai/praisonai/cli/commands/benchmark.py">--help</a></code>
* <code title="cli">praisonai benchmark litellm <a href="./src/praisonai/praisonai/cli/commands/benchmark.py">--help</a></code>
* <code title="cli">praisonai benchmark profile <a href="./src/praisonai/praisonai/cli/commands/benchmark.py">--help</a></code>
* <code title="cli">praisonai benchmark sdk <a href="./src/praisonai/praisonai/cli/commands/benchmark.py">--help</a></code>
* <code title="cli">praisonai benchmark workflow <a href="./src/praisonai/praisonai/cli/commands/benchmark.py">--help</a></code>
* <code title="cli">praisonai bot agentmail <a href="./src/praisonai/praisonai/cli/commands/bot.py">--help</a></code>
* <code title="cli">praisonai bot bot-callback <a href="./src/praisonai/praisonai/cli/commands/bot.py">--help</a></code>
* <code title="cli">praisonai bot discord <a href="./src/praisonai/praisonai/cli/commands/bot.py">--help</a></code>
* <code title="cli">praisonai bot email <a href="./src/praisonai/praisonai/cli/commands/bot.py">--help</a></code>
* <code title="cli">praisonai bot install-daemon <a href="./src/praisonai/praisonai/cli/commands/bot.py">--help</a></code>
* <code title="cli">praisonai bot linear <a href="./src/praisonai/praisonai/cli/commands/bot.py">--help</a></code>
* <code title="cli">praisonai bot list <a href="./src/praisonai/praisonai/cli/commands/bot.py">--help</a></code>
* <code title="cli">praisonai bot purge <a href="./src/praisonai/praisonai/cli/commands/bot.py">--help</a></code>
* <code title="cli">praisonai bot replay <a href="./src/praisonai/praisonai/cli/commands/bot.py">--help</a></code>
* <code title="cli">praisonai bot slack <a href="./src/praisonai/praisonai/cli/commands/bot.py">--help</a></code>
* <code title="cli">praisonai bot start <a href="./src/praisonai/praisonai/cli/commands/bot.py">--help</a></code>
* <code title="cli">praisonai bot telegram <a href="./src/praisonai/praisonai/cli/commands/bot.py">--help</a></code>
* <code title="cli">praisonai bot whatsapp <a href="./src/praisonai/praisonai/cli/commands/bot.py">--help</a></code>
* <code title="cli">praisonai browser browser-callback <a href="./src/praisonai/praisonai/cli/commands/browser.py">--help</a></code>
* <code title="cli">praisonai browser click <a href="./src/praisonai/praisonai/cli/commands/browser.py">--help</a></code>
* <code title="cli">praisonai browser navigate <a href="./src/praisonai/praisonai/cli/commands/browser.py">--help</a></code>
* <code title="cli">praisonai browser open <a href="./src/praisonai/praisonai/cli/commands/browser.py">--help</a></code>
* <code title="cli">praisonai browser profiles <a href="./src/praisonai/praisonai/cli/commands/browser.py">--help</a></code>
* <code title="cli">praisonai browser screenshot <a href="./src/praisonai/praisonai/cli/commands/browser.py">--help</a></code>
* <code title="cli">praisonai browser snapshot <a href="./src/praisonai/praisonai/cli/commands/browser.py">--help</a></code>
* <code title="cli">praisonai browser status <a href="./src/praisonai/praisonai/cli/commands/browser.py">--help</a></code>
* <code title="cli">praisonai browser type <a href="./src/praisonai/praisonai/cli/commands/browser.py">--help</a></code>
* <code title="cli">praisonai call call-main <a href="./src/praisonai/praisonai/cli/commands/call.py">--help</a></code>
* <code title="cli">praisonai chat <a href="./src/praisonai/praisonai/cli/main.py">--help</a></code>
* <code title="cli">praisonai chat chat-main <a href="./src/praisonai/praisonai/cli/commands/chat.py">--help</a></code>
* <code title="cli">praisonai claw claw <a href="./src/praisonai/praisonai/cli/commands/claw.py">--help</a></code>
* <code title="cli">praisonai code <a href="./src/praisonai/praisonai/cli/main.py">--help</a></code>
* <code title="cli">praisonai code code-main <a href="./src/praisonai/praisonai/cli/commands/code.py">--help</a></code>
* <code title="cli">praisonai commit commit-main <a href="./src/praisonai/praisonai/cli/commands/commit.py">--help</a></code>
* <code title="cli">praisonai completion bash <a href="./src/praisonai/praisonai/cli/commands/completion.py">--help</a></code>
* <code title="cli">praisonai completion completion-callback <a href="./src/praisonai/praisonai/cli/commands/completion.py">--help</a></code>
* <code title="cli">praisonai completion fish <a href="./src/praisonai/praisonai/cli/commands/completion.py">--help</a></code>
* <code title="cli">praisonai completion zsh <a href="./src/praisonai/praisonai/cli/commands/completion.py">--help</a></code>
* <code title="cli">praisonai config doctor <a href="./src/praisonai/praisonai/cli/commands/config.py">--help</a></code>
* <code title="cli">praisonai config env <a href="./src/praisonai/praisonai/cli/commands/config.py">--help</a></code>
* <code title="cli">praisonai config get <a href="./src/praisonai/praisonai/cli/commands/config.py">--help</a></code>
* <code title="cli">praisonai config list <a href="./src/praisonai/praisonai/cli/commands/config.py">--help</a></code>
* <code title="cli">praisonai config path <a href="./src/praisonai/praisonai/cli/commands/config.py">--help</a></code>
* <code title="cli">praisonai config reset <a href="./src/praisonai/praisonai/cli/commands/config.py">--help</a></code>
* <code title="cli">praisonai config set <a href="./src/praisonai/praisonai/cli/commands/config.py">--help</a></code>
* <code title="cli">praisonai context add <a href="./src/praisonai/praisonai/cli/commands/context.py">--help</a></code>
* <code title="cli">praisonai context clear <a href="./src/praisonai/praisonai/cli/commands/context.py">--help</a></code>
* <code title="cli">praisonai context compact <a href="./src/praisonai/praisonai/cli/commands/context.py">--help</a></code>
@@ -800,6 +844,17 @@ Methods:
* <code title="cli">praisonai context stats <a href="./src/praisonai/praisonai/cli/commands/context.py">--help</a></code>
* <code title="cli">praisonai context tail <a href="./src/praisonai/praisonai/cli/commands/context.py">--help</a></code>
* <code title="cli">praisonai dashboard unified <a href="./src/praisonai/praisonai/cli/commands/dashboard.py">--help</a></code>
* <code title="cli">praisonai debug acp <a href="./src/praisonai/praisonai/cli/commands/debug.py">--help</a></code>
* <code title="cli">praisonai debug debug-callback <a href="./src/praisonai/praisonai/cli/commands/debug.py">--help</a></code>
* <code title="cli">praisonai debug interactive <a href="./src/praisonai/praisonai/cli/commands/debug.py">--help</a></code>
* <code title="cli">praisonai debug lsp <a href="./src/praisonai/praisonai/cli/commands/debug.py">--help</a></code>
* <code title="cli">praisonai debug trace <a href="./src/praisonai/praisonai/cli/commands/debug.py">--help</a></code>
* <code title="cli">praisonai deploy aws <a href="./src/praisonai/praisonai/cli/commands/deploy.py">--help</a></code>
* <code title="cli">praisonai deploy azure <a href="./src/praisonai/praisonai/cli/commands/deploy.py">--help</a></code>
* <code title="cli">praisonai deploy docker <a href="./src/praisonai/praisonai/cli/commands/deploy.py">--help</a></code>
* <code title="cli">praisonai deploy gcp <a href="./src/praisonai/praisonai/cli/commands/deploy.py">--help</a></code>
* <code title="cli">praisonai diag diag-callback <a href="./src/praisonai/praisonai/cli/commands/diag.py">--help</a></code>
* <code title="cli">praisonai diag export <a href="./src/praisonai/praisonai/cli/commands/diag.py">--help</a></code>
* <code title="cli">praisonai docs api-md <a href="./src/praisonai/praisonai/cli/commands/docs.py">--help</a></code>
* <code title="cli">praisonai docs generate <a href="./src/praisonai/praisonai/cli/commands/docs.py">--help</a></code>
* <code title="cli">praisonai docs list <a href="./src/praisonai/praisonai/cli/commands/docs.py">--help</a></code>
@@ -808,6 +863,28 @@ Methods:
* <code title="cli">praisonai docs run-all <a href="./src/praisonai/praisonai/cli/commands/docs.py">--help</a></code>
* <code title="cli">praisonai docs serve <a href="./src/praisonai/praisonai/cli/commands/docs.py">--help</a></code>
* <code title="cli">praisonai docs stats <a href="./src/praisonai/praisonai/cli/commands/docs.py">--help</a></code>
* <code title="cli">praisonai doctor cleanup <a href="./src/praisonai/praisonai/cli/commands/doctor.py">--help</a></code>
* <code title="cli">praisonai doctor config <a href="./src/praisonai/praisonai/cli/commands/doctor.py">--help</a></code>
* <code title="cli">praisonai doctor db <a href="./src/praisonai/praisonai/cli/commands/doctor.py">--help</a></code>
* <code title="cli">praisonai doctor doctor-callback <a href="./src/praisonai/praisonai/cli/commands/doctor.py">--help</a></code>
* <code title="cli">praisonai doctor env <a href="./src/praisonai/praisonai/cli/commands/doctor.py">--help</a></code>
* <code title="cli">praisonai doctor mcp <a href="./src/praisonai/praisonai/cli/commands/doctor.py">--help</a></code>
* <code title="cli">praisonai doctor network <a href="./src/praisonai/praisonai/cli/commands/doctor.py">--help</a></code>
* <code title="cli">praisonai doctor packaging <a href="./src/praisonai/praisonai/cli/commands/doctor.py">--help</a></code>
* <code title="cli">praisonai doctor performance <a href="./src/praisonai/praisonai/cli/commands/doctor.py">--help</a></code>
* <code title="cli">praisonai doctor selftest <a href="./src/praisonai/praisonai/cli/commands/doctor.py">--help</a></code>
* <code title="cli">praisonai doctor skills <a href="./src/praisonai/praisonai/cli/commands/doctor.py">--help</a></code>
* <code title="cli">praisonai doctor tools <a href="./src/praisonai/praisonai/cli/commands/doctor.py">--help</a></code>
* <code title="cli">praisonai doctor troubleshoot <a href="./src/praisonai/praisonai/cli/commands/doctor.py">--help</a></code>
* <code title="cli">praisonai endpoints list <a href="./src/praisonai/praisonai/cli/commands/endpoints.py">--help</a></code>
* <code title="cli">praisonai endpoints test <a href="./src/praisonai/praisonai/cli/commands/endpoints.py">--help</a></code>
* <code title="cli">praisonai environment check <a href="./src/praisonai/praisonai/cli/commands/environment.py">--help</a></code>
* <code title="cli">praisonai environment doctor <a href="./src/praisonai/praisonai/cli/commands/environment.py">--help</a></code>
* <code title="cli">praisonai environment view <a href="./src/praisonai/praisonai/cli/commands/environment.py">--help</a></code>
* <code title="cli">praisonai eval accuracy <a href="./src/praisonai/praisonai/cli/commands/eval.py">--help</a></code>
* <code title="cli">praisonai eval judge <a href="./src/praisonai/praisonai/cli/commands/eval.py">--help</a></code>
* <code title="cli">praisonai eval list-judges <a href="./src/praisonai/praisonai/cli/commands/eval.py">--help</a></code>
* <code title="cli">praisonai eval performance <a href="./src/praisonai/praisonai/cli/commands/eval.py">--help</a></code>
* <code title="cli">praisonai examples find <a href="./src/praisonai/praisonai/cli/commands/examples.py">--help</a></code>
* <code title="cli">praisonai examples info <a href="./src/praisonai/praisonai/cli/commands/examples.py">--help</a></code>
* <code title="cli">praisonai examples list <a href="./src/praisonai/praisonai/cli/commands/examples.py">--help</a></code>
@@ -820,6 +897,32 @@ Methods:
* <code title="cli">praisonai flow import <a href="./src/praisonai/praisonai/cli/commands/flow.py">--help</a></code>
* <code title="cli">praisonai flow list <a href="./src/praisonai/praisonai/cli/commands/flow.py">--help</a></code>
* <code title="cli">praisonai flow version <a href="./src/praisonai/praisonai/cli/commands/flow.py">--help</a></code>
* <code title="cli">praisonai gateway channels <a href="./src/praisonai/praisonai/cli/commands/gateway.py">--help</a></code>
* <code title="cli">praisonai gateway gateway-callback <a href="./src/praisonai/praisonai/cli/commands/gateway.py">--help</a></code>
* <code title="cli">praisonai gateway install <a href="./src/praisonai/praisonai/cli/commands/gateway.py">--help</a></code>
* <code title="cli">praisonai gateway logs <a href="./src/praisonai/praisonai/cli/commands/gateway.py">--help</a></code>
* <code title="cli">praisonai gateway mint-link <a href="./src/praisonai/praisonai/cli/commands/gateway.py">--help</a></code>
* <code title="cli">praisonai gateway send <a href="./src/praisonai/praisonai/cli/commands/gateway.py">--help</a></code>
* <code title="cli">praisonai gateway start <a href="./src/praisonai/praisonai/cli/commands/gateway.py">--help</a></code>
* <code title="cli">praisonai gateway status <a href="./src/praisonai/praisonai/cli/commands/gateway.py">--help</a></code>
* <code title="cli">praisonai gateway stop <a href="./src/praisonai/praisonai/cli/commands/gateway.py">--help</a></code>
* <code title="cli">praisonai gateway uninstall <a href="./src/praisonai/praisonai/cli/commands/gateway.py">--help</a></code>
* <code title="cli">praisonai github triage <a href="./src/praisonai/praisonai/cli/commands/github.py">--help</a></code>
* <code title="cli">praisonai hooks add <a href="./src/praisonai/praisonai/cli/commands/hooks.py">--help</a></code>
* <code title="cli">praisonai hooks list <a href="./src/praisonai/praisonai/cli/commands/hooks.py">--help</a></code>
* <code title="cli">praisonai hooks remove <a href="./src/praisonai/praisonai/cli/commands/hooks.py">--help</a></code>
* <code title="cli">praisonai kanban block <a href="./src/praisonai/praisonai/cli/commands/kanban.py">--help</a></code>
* <code title="cli">praisonai kanban boards <a href="./src/praisonai/praisonai/cli/commands/kanban.py">--help</a></code>
* <code title="cli">praisonai kanban comment <a href="./src/praisonai/praisonai/cli/commands/kanban.py">--help</a></code>
* <code title="cli">praisonai kanban complete <a href="./src/praisonai/praisonai/cli/commands/kanban.py">--help</a></code>
* <code title="cli">praisonai kanban create <a href="./src/praisonai/praisonai/cli/commands/kanban.py">--help</a></code>
* <code title="cli">praisonai kanban dispatch <a href="./src/praisonai/praisonai/cli/commands/kanban.py">--help</a></code>
* <code title="cli">praisonai kanban link <a href="./src/praisonai/praisonai/cli/commands/kanban.py">--help</a></code>
* <code title="cli">praisonai kanban list <a href="./src/praisonai/praisonai/cli/commands/kanban.py">--help</a></code>
* <code title="cli">praisonai kanban move <a href="./src/praisonai/praisonai/cli/commands/kanban.py">--help</a></code>
* <code title="cli">praisonai kanban reclaim <a href="./src/praisonai/praisonai/cli/commands/kanban.py">--help</a></code>
* <code title="cli">praisonai kanban show <a href="./src/praisonai/praisonai/cli/commands/kanban.py">--help</a></code>
* <code title="cli">praisonai kanban unblock <a href="./src/praisonai/praisonai/cli/commands/kanban.py">--help</a></code>
* <code title="cli">praisonai knowledge add <a href="./src/praisonai/praisonai/cli/commands/knowledge.py">--help</a></code>
* <code title="cli">praisonai knowledge index <a href="./src/praisonai/praisonai/cli/commands/knowledge.py">--help</a></code>
* <code title="cli">praisonai knowledge list <a href="./src/praisonai/praisonai/cli/commands/knowledge.py">--help</a></code>
@@ -837,19 +940,41 @@ Methods:
* <code title="cli">praisonai langfuse test <a href="./src/praisonai/praisonai/cli/commands/langfuse.py">--help</a></code>
* <code title="cli">praisonai langfuse traces <a href="./src/praisonai/praisonai/cli/commands/langfuse.py">--help</a></code>
* <code title="cli">praisonai langfuse version <a href="./src/praisonai/praisonai/cli/commands/langfuse.py">--help</a></code>
* <code title="cli">praisonai loop help <a href="./src/praisonai/praisonai/cli/commands/loop.py">--help</a></code>
* <code title="cli">praisonai loop loop-main <a href="./src/praisonai/praisonai/cli/commands/loop.py">--help</a></code>
* <code title="cli">praisonai lsp logs <a href="./src/praisonai/praisonai/cli/commands/lsp.py">--help</a></code>
* <code title="cli">praisonai lsp lsp-callback <a href="./src/praisonai/praisonai/cli/commands/lsp.py">--help</a></code>
* <code title="cli">praisonai lsp start <a href="./src/praisonai/praisonai/cli/commands/lsp.py">--help</a></code>
* <code title="cli">praisonai lsp status <a href="./src/praisonai/praisonai/cli/commands/lsp.py">--help</a></code>
* <code title="cli">praisonai lsp stop <a href="./src/praisonai/praisonai/cli/commands/lsp.py">--help</a></code>
* <code title="cli">praisonai managed delete <a href="./src/praisonai/praisonai/cli/commands/managed.py">--help</a></code>
* <code title="cli">praisonai managed get <a href="./src/praisonai/praisonai/cli/commands/managed.py">--help</a></code>
* <code title="cli">praisonai managed list <a href="./src/praisonai/praisonai/cli/commands/managed.py">--help</a></code>
* <code title="cli">praisonai managed managed-callback <a href="./src/praisonai/praisonai/cli/commands/managed.py">--help</a></code>
* <code title="cli">praisonai managed multi <a href="./src/praisonai/praisonai/cli/commands/managed.py">--help</a></code>
* <code title="cli">praisonai managed ps <a href="./src/praisonai/praisonai/cli/commands/managed.py">--help</a></code>
* <code title="cli">praisonai managed restore <a href="./src/praisonai/praisonai/cli/commands/managed.py">--help</a></code>
* <code title="cli">praisonai managed resume <a href="./src/praisonai/praisonai/cli/commands/managed.py">--help</a></code>
* <code title="cli">praisonai managed run <a href="./src/praisonai/praisonai/cli/commands/managed.py">--help</a></code>
* <code title="cli">praisonai managed save <a href="./src/praisonai/praisonai/cli/commands/managed.py">--help</a></code>
* <code title="cli">praisonai managed show <a href="./src/praisonai/praisonai/cli/commands/managed.py">--help</a></code>
* <code title="cli">praisonai managed stop <a href="./src/praisonai/praisonai/cli/commands/managed.py">--help</a></code>
* <code title="cli">praisonai managed update <a href="./src/praisonai/praisonai/cli/commands/managed.py">--help</a></code>
* <code title="cli">praisonai mcp add <a href="./src/praisonai/praisonai/cli/commands/mcp.py">--help</a></code>
* <code title="cli">praisonai mcp auth <a href="./src/praisonai/praisonai/cli/commands/mcp.py">--help</a></code>
* <code title="cli">praisonai mcp describe <a href="./src/praisonai/praisonai/cli/commands/mcp.py">--help</a></code>
* <code title="cli">praisonai mcp list <a href="./src/praisonai/praisonai/cli/commands/mcp.py">--help</a></code>
* <code title="cli">praisonai mcp logout <a href="./src/praisonai/praisonai/cli/commands/mcp.py">--help</a></code>
* <code title="cli">praisonai mcp mcp-callback <a href="./src/praisonai/praisonai/cli/commands/mcp.py">--help</a></code>
* <code title="cli">praisonai mcp remove <a href="./src/praisonai/praisonai/cli/commands/mcp.py">--help</a></code>
* <code title="cli">praisonai mcp run <a href="./src/praisonai/praisonai/cli/commands/mcp.py">--help</a></code>
* <code title="cli">praisonai mcp status <a href="./src/praisonai/praisonai/cli/commands/mcp.py">--help</a></code>
* <code title="cli">praisonai mcp sync <a href="./src/praisonai/praisonai/cli/commands/mcp.py">--help</a></code>
* <code title="cli">praisonai mcp test <a href="./src/praisonai/praisonai/cli/commands/mcp.py">--help</a></code>
* <code title="cli">praisonai mcp tools <a href="./src/praisonai/praisonai/cli/commands/mcp.py">--help</a></code>
* <code title="cli">praisonai memory add <a href="./src/praisonai/praisonai/cli/commands/memory.py">--help</a></code>
* <code title="cli">praisonai memory clear <a href="./src/praisonai/praisonai/cli/commands/memory.py">--help</a></code>
* <code title="cli">praisonai memory search <a href="./src/praisonai/praisonai/cli/commands/memory.py">--help</a></code>
* <code title="cli">praisonai memory show <a href="./src/praisonai/praisonai/cli/commands/memory.py">--help</a></code>
* <code title="cli">praisonai memory status <a href="./src/praisonai/praisonai/cli/commands/memory.py">--help</a></code>
* <code title="cli">praisonai n8n export <a href="./src/praisonai/praisonai/cli/commands/n8n.py">--help</a></code>
* <code title="cli">praisonai n8n import <a href="./src/praisonai/praisonai/cli/commands/n8n.py">--help</a></code>
* <code title="cli">praisonai n8n list <a href="./src/praisonai/praisonai/cli/commands/n8n.py">--help</a></code>
@@ -857,6 +982,30 @@ Methods:
* <code title="cli">praisonai n8n pull <a href="./src/praisonai/praisonai/cli/commands/n8n.py">--help</a></code>
* <code title="cli">praisonai n8n push <a href="./src/praisonai/praisonai/cli/commands/n8n.py">--help</a></code>
* <code title="cli">praisonai n8n test <a href="./src/praisonai/praisonai/cli/commands/n8n.py">--help</a></code>
* <code title="cli">praisonai obs obs-fallback <a href="./src/praisonai/praisonai/cli/commands/obs.py">--help</a></code>
* <code title="cli">praisonai onboard onboard-callback <a href="./src/praisonai/praisonai/cli/commands/onboard.py">--help</a></code>
* <code title="cli">praisonai package install <a href="./src/praisonai/praisonai/cli/commands/package.py">--help</a></code>
* <code title="cli">praisonai package list <a href="./src/praisonai/praisonai/cli/commands/package.py">--help</a></code>
* <code title="cli">praisonai package uninstall <a href="./src/praisonai/praisonai/cli/commands/package.py">--help</a></code>
* <code title="cli">praisonai pairing approve <a href="./src/praisonai/praisonai/cli/commands/pairing.py">--help</a></code>
* <code title="cli">praisonai pairing clear <a href="./src/praisonai/praisonai/cli/commands/pairing.py">--help</a></code>
* <code title="cli">praisonai pairing list <a href="./src/praisonai/praisonai/cli/commands/pairing.py">--help</a></code>
* <code title="cli">praisonai pairing revoke <a href="./src/praisonai/praisonai/cli/commands/pairing.py">--help</a></code>
* <code title="cli">praisonai paths show <a href="./src/praisonai/praisonai/cli/commands/paths.py">--help</a></code>
* <code title="cli">praisonai plugins create <a href="./src/praisonai/praisonai/cli/commands/plugins.py">--help</a></code>
* <code title="cli">praisonai plugins disable <a href="./src/praisonai/praisonai/cli/commands/plugins.py">--help</a></code>
* <code title="cli">praisonai plugins discover <a href="./src/praisonai/praisonai/cli/commands/plugins.py">--help</a></code>
* <code title="cli">praisonai plugins doctor <a href="./src/praisonai/praisonai/cli/commands/plugins.py">--help</a></code>
* <code title="cli">praisonai plugins enable <a href="./src/praisonai/praisonai/cli/commands/plugins.py">--help</a></code>
* <code title="cli">praisonai plugins info <a href="./src/praisonai/praisonai/cli/commands/plugins.py">--help</a></code>
* <code title="cli">praisonai plugins install <a href="./src/praisonai/praisonai/cli/commands/plugins.py">--help</a></code>
* <code title="cli">praisonai plugins list <a href="./src/praisonai/praisonai/cli/commands/plugins.py">--help</a></code>
* <code title="cli">praisonai plugins plugins-callback <a href="./src/praisonai/praisonai/cli/commands/plugins.py">--help</a></code>
* <code title="cli">praisonai plugins remove <a href="./src/praisonai/praisonai/cli/commands/plugins.py">--help</a></code>
* <code title="cli">praisonai port check <a href="./src/praisonai/praisonai/cli/commands/port.py">--help</a></code>
* <code title="cli">praisonai port kill <a href="./src/praisonai/praisonai/cli/commands/port.py">--help</a></code>
* <code title="cli">praisonai port list <a href="./src/praisonai/praisonai/cli/commands/port.py">--help</a></code>
* <code title="cli">praisonai port port-callback <a href="./src/praisonai/praisonai/cli/commands/port.py">--help</a></code>
* <code title="cli">praisonai profile imports <a href="./src/praisonai/praisonai/cli/commands/profile.py">--help</a></code>
* <code title="cli">praisonai profile optimize <a href="./src/praisonai/praisonai/cli/commands/profile.py">--help</a></code>
* <code title="cli">praisonai profile profile-callback <a href="./src/praisonai/praisonai/cli/commands/profile.py">--help</a></code>
@@ -864,6 +1013,8 @@ Methods:
* <code title="cli">praisonai profile snapshot <a href="./src/praisonai/praisonai/cli/commands/profile.py">--help</a></code>
* <code title="cli">praisonai profile startup <a href="./src/praisonai/praisonai/cli/commands/profile.py">--help</a></code>
* <code title="cli">praisonai profile suite <a href="./src/praisonai/praisonai/cli/commands/profile.py">--help</a></code>
* <code title="cli">praisonai publish publish-main <a href="./src/praisonai/praisonai/cli/commands/publish.py">--help</a></code>
* <code title="cli">praisonai publish pypi <a href="./src/praisonai/praisonai/cli/commands/publish.py">--help</a></code>
* <code title="cli">praisonai rag chat <a href="./src/praisonai/praisonai/cli/commands/rag.py">--help</a></code>
* <code title="cli">praisonai rag eval <a href="./src/praisonai/praisonai/cli/commands/rag.py">--help</a></code>
* <code title="cli">praisonai rag index <a href="./src/praisonai/praisonai/cli/commands/rag.py">--help</a></code>
@@ -879,6 +1030,8 @@ Methods:
* <code title="cli">praisonai recipe optimize <a href="./src/praisonai/praisonai/cli/commands/recipe.py">--help</a></code>
* <code title="cli">praisonai recipe run <a href="./src/praisonai/praisonai/cli/commands/recipe.py">--help</a></code>
* <code title="cli">praisonai recipe serve <a href="./src/praisonai/praisonai/cli/commands/recipe.py">--help</a></code>
* <code title="cli">praisonai registry list <a href="./src/praisonai/praisonai/cli/commands/registry.py">--help</a></code>
* <code title="cli">praisonai registry serve <a href="./src/praisonai/praisonai/cli/commands/registry.py">--help</a></code>
* <code title="cli">praisonai replay cleanup <a href="./src/praisonai/praisonai/cli/commands/replay.py">--help</a></code>
* <code title="cli">praisonai replay context <a href="./src/praisonai/praisonai/cli/commands/replay.py">--help</a></code>
* <code title="cli">praisonai replay dashboard <a href="./src/praisonai/praisonai/cli/commands/replay.py">--help</a></code>
@@ -886,10 +1039,21 @@ Methods:
* <code title="cli">praisonai replay flow <a href="./src/praisonai/praisonai/cli/commands/replay.py">--help</a></code>
* <code title="cli">praisonai replay list <a href="./src/praisonai/praisonai/cli/commands/replay.py">--help</a></code>
* <code title="cli">praisonai replay show <a href="./src/praisonai/praisonai/cli/commands/replay.py">--help</a></code>
* <code title="cli">praisonai research research-main <a href="./src/praisonai/praisonai/cli/commands/research.py">--help</a></code>
* <code title="cli">praisonai retrieval index <a href="./src/praisonai/praisonai/cli/commands/retrieval.py">--help</a></code>
* <code title="cli">praisonai retrieval query <a href="./src/praisonai/praisonai/cli/commands/retrieval.py">--help</a></code>
* <code title="cli">praisonai retrieval search <a href="./src/praisonai/praisonai/cli/commands/retrieval.py">--help</a></code>
* <code title="cli">praisonai rules add <a href="./src/praisonai/praisonai/cli/commands/rules.py">--help</a></code>
* <code title="cli">praisonai rules clear <a href="./src/praisonai/praisonai/cli/commands/rules.py">--help</a></code>
* <code title="cli">praisonai rules list <a href="./src/praisonai/praisonai/cli/commands/rules.py">--help</a></code>
* <code title="cli">praisonai run <a href="./src/praisonai/praisonai/cli/main.py">--help</a></code>
* <code title="cli">praisonai run run-main <a href="./src/praisonai/praisonai/cli/commands/run.py">--help</a></code>
* <code title="cli">praisonai sandbox explain <a href="./src/praisonai/praisonai/cli/commands/sandbox.py">--help</a></code>
* <code title="cli">praisonai sandbox list <a href="./src/praisonai/praisonai/cli/commands/sandbox.py">--help</a></code>
* <code title="cli">praisonai sandbox recreate <a href="./src/praisonai/praisonai/cli/commands/sandbox.py">--help</a></code>
* <code title="cli">praisonai sandbox sandbox-callback <a href="./src/praisonai/praisonai/cli/commands/sandbox.py">--help</a></code>
* <code title="cli">praisonai sandbox status <a href="./src/praisonai/praisonai/cli/commands/sandbox.py">--help</a></code>
* <code title="cli">praisonai schedule add <a href="./src/praisonai/praisonai/cli/commands/schedule.py">--help</a></code>
* <code title="cli">praisonai schedule blueprint <a href="./src/praisonai/praisonai/cli/commands/schedule.py">--help</a></code>
* <code title="cli">praisonai schedule blueprint-list <a href="./src/praisonai/praisonai/cli/commands/schedule.py">--help</a></code>
* <code title="cli">praisonai schedule delete <a href="./src/praisonai/praisonai/cli/commands/schedule.py">--help</a></code>
* <code title="cli">praisonai schedule describe <a href="./src/praisonai/praisonai/cli/commands/schedule.py">--help</a></code>
* <code title="cli">praisonai schedule list <a href="./src/praisonai/praisonai/cli/commands/schedule.py">--help</a></code>
@@ -899,13 +1063,87 @@ Methods:
* <code title="cli">praisonai schedule start <a href="./src/praisonai/praisonai/cli/commands/schedule.py">--help</a></code>
* <code title="cli">praisonai schedule stats <a href="./src/praisonai/praisonai/cli/commands/schedule.py">--help</a></code>
* <code title="cli">praisonai schedule stop <a href="./src/praisonai/praisonai/cli/commands/schedule.py">--help</a></code>
* <code title="cli">praisonai schedule suggestion-accept <a href="./src/praisonai/praisonai/cli/commands/schedule.py">--help</a></code>
* <code title="cli">praisonai schedule suggestion-dismiss <a href="./src/praisonai/praisonai/cli/commands/schedule.py">--help</a></code>
* <code title="cli">praisonai schedule suggestion-propose <a href="./src/praisonai/praisonai/cli/commands/schedule.py">--help</a></code>
* <code title="cli">praisonai schedule suggestions <a href="./src/praisonai/praisonai/cli/commands/schedule.py">--help</a></code>
* <code title="cli">praisonai validate check <a href="./src/praisonai/praisonai/cli/commands/validate.py">--help</a></code>
* <code title="cli">praisonai validate schema <a href="./src/praisonai/praisonai/cli/commands/validate.py">--help</a></code>
* <code title="cli">praisonai validate validate <a href="./src/praisonai/praisonai/cli/commands/validate.py">--help</a></code>
* <code title="cli">praisonai serve a2a <a href="./src/praisonai/praisonai/cli/commands/serve.py">--help</a></code>
* <code title="cli">praisonai serve a2u <a href="./src/praisonai/praisonai/cli/commands/serve.py">--help</a></code>
* <code title="cli">praisonai serve acp <a href="./src/praisonai/praisonai/cli/commands/serve.py">--help</a></code>
* <code title="cli">praisonai serve agents <a href="./src/praisonai/praisonai/cli/commands/serve.py">--help</a></code>
* <code title="cli">praisonai serve docs <a href="./src/praisonai/praisonai/cli/commands/serve.py">--help</a></code>
* <code title="cli">praisonai serve gateway <a href="./src/praisonai/praisonai/cli/commands/serve.py">--help</a></code>
* <code title="cli">praisonai serve lsp <a href="./src/praisonai/praisonai/cli/commands/serve.py">--help</a></code>
* <code title="cli">praisonai serve mcp <a href="./src/praisonai/praisonai/cli/commands/serve.py">--help</a></code>
* <code title="cli">praisonai serve rag <a href="./src/praisonai/praisonai/cli/commands/serve.py">--help</a></code>
* <code title="cli">praisonai serve recipe <a href="./src/praisonai/praisonai/cli/commands/serve.py">--help</a></code>
* <code title="cli">praisonai serve registry <a href="./src/praisonai/praisonai/cli/commands/serve.py">--help</a></code>
* <code title="cli">praisonai serve scheduler <a href="./src/praisonai/praisonai/cli/commands/serve.py">--help</a></code>
* <code title="cli">praisonai serve serve-callback <a href="./src/praisonai/praisonai/cli/commands/serve.py">--help</a></code>
* <code title="cli">praisonai serve start <a href="./src/praisonai/praisonai/cli/commands/serve.py">--help</a></code>
* <code title="cli">praisonai serve status <a href="./src/praisonai/praisonai/cli/commands/serve.py">--help</a></code>
* <code title="cli">praisonai serve stop <a href="./src/praisonai/praisonai/cli/commands/serve.py">--help</a></code>
* <code title="cli">praisonai serve ui <a href="./src/praisonai/praisonai/cli/commands/serve.py">--help</a></code>
* <code title="cli">praisonai serve ui-gateway <a href="./src/praisonai/praisonai/cli/commands/serve.py">--help</a></code>
* <code title="cli">praisonai serve unified <a href="./src/praisonai/praisonai/cli/commands/serve.py">--help</a></code>
* <code title="cli">praisonai session delete <a href="./src/praisonai/praisonai/cli/commands/session.py">--help</a></code>
* <code title="cli">praisonai session export <a href="./src/praisonai/praisonai/cli/commands/session.py">--help</a></code>
* <code title="cli">praisonai session import <a href="./src/praisonai/praisonai/cli/commands/session.py">--help</a></code>
* <code title="cli">praisonai session list <a href="./src/praisonai/praisonai/cli/commands/session.py">--help</a></code>
* <code title="cli">praisonai session resume <a href="./src/praisonai/praisonai/cli/commands/session.py">--help</a></code>
* <code title="cli">praisonai session show <a href="./src/praisonai/praisonai/cli/commands/session.py">--help</a></code>
* <code title="cli">praisonai setup config <a href="./src/praisonai/praisonai/cli/commands/setup.py">--help</a></code>
* <code title="cli">praisonai setup reset <a href="./src/praisonai/praisonai/cli/commands/setup.py">--help</a></code>
* <code title="cli">praisonai setup setup-callback <a href="./src/praisonai/praisonai/cli/commands/setup.py">--help</a></code>
* <code title="cli">praisonai setup wizard <a href="./src/praisonai/praisonai/cli/commands/setup.py">--help</a></code>
* <code title="cli">praisonai skills check <a href="./src/praisonai/praisonai/cli/commands/skills.py">--help</a></code>
* <code title="cli">praisonai skills create <a href="./src/praisonai/praisonai/cli/commands/skills.py">--help</a></code>
* <code title="cli">praisonai skills eligible <a href="./src/praisonai/praisonai/cli/commands/skills.py">--help</a></code>
* <code title="cli">praisonai skills info <a href="./src/praisonai/praisonai/cli/commands/skills.py">--help</a></code>
* <code title="cli">praisonai skills install <a href="./src/praisonai/praisonai/cli/commands/skills.py">--help</a></code>
* <code title="cli">praisonai skills list <a href="./src/praisonai/praisonai/cli/commands/skills.py">--help</a></code>
* <code title="cli">praisonai skills search <a href="./src/praisonai/praisonai/cli/commands/skills.py">--help</a></code>
* <code title="cli">praisonai skills validate <a href="./src/praisonai/praisonai/cli/commands/skills.py">--help</a></code>
* <code title="cli">praisonai standardise check <a href="./src/praisonai/praisonai/cli/commands/standardise.py">--help</a></code>
* <code title="cli">praisonai standardise fix <a href="./src/praisonai/praisonai/cli/commands/standardise.py">--help</a></code>
* <code title="cli">praisonai standardise init <a href="./src/praisonai/praisonai/cli/commands/standardise.py">--help</a></code>
* <code title="cli">praisonai standardise report <a href="./src/praisonai/praisonai/cli/commands/standardise.py">--help</a></code>
* <code title="cli">praisonai templates create <a href="./src/praisonai/praisonai/cli/commands/templates.py">--help</a></code>
* <code title="cli">praisonai templates list <a href="./src/praisonai/praisonai/cli/commands/templates.py">--help</a></code>
* <code title="cli">praisonai test info <a href="./src/praisonai/praisonai/cli/commands/test.py">--help</a></code>
* <code title="cli">praisonai test interactive <a href="./src/praisonai/praisonai/cli/commands/test.py">--help</a></code>
* <code title="cli">praisonai test run <a href="./src/praisonai/praisonai/cli/commands/test.py">--help</a></code>
* <code title="cli">praisonai todo add <a href="./src/praisonai/praisonai/cli/commands/todo.py">--help</a></code>
* <code title="cli">praisonai todo done <a href="./src/praisonai/praisonai/cli/commands/todo.py">--help</a></code>
* <code title="cli">praisonai todo list <a href="./src/praisonai/praisonai/cli/commands/todo.py">--help</a></code>
* <code title="cli">praisonai tools info <a href="./src/praisonai/praisonai/cli/commands/tools.py">--help</a></code>
* <code title="cli">praisonai tools list <a href="./src/praisonai/praisonai/cli/commands/tools.py">--help</a></code>
* <code title="cli">praisonai tools test <a href="./src/praisonai/praisonai/cli/commands/tools.py">--help</a></code>
* <code title="cli">praisonai tools validate <a href="./src/praisonai/praisonai/cli/commands/tools.py">--help</a></code>
* <code title="cli">praisonai traces disable <a href="./src/praisonai/praisonai/cli/commands/traces.py">--help</a></code>
* <code title="cli">praisonai traces enable <a href="./src/praisonai/praisonai/cli/commands/traces.py">--help</a></code>
* <code title="cli">praisonai traces list <a href="./src/praisonai/praisonai/cli/commands/traces.py">--help</a></code>
* <code title="cli">praisonai traces status <a href="./src/praisonai/praisonai/cli/commands/traces.py">--help</a></code>
* <code title="cli">praisonai tracker batch <a href="./src/praisonai/praisonai/cli/commands/tracker.py">--help</a></code>
* <code title="cli">praisonai tracker judge <a href="./src/praisonai/praisonai/cli/commands/tracker.py">--help</a></code>
* <code title="cli">praisonai tracker run <a href="./src/praisonai/praisonai/cli/commands/tracker.py">--help</a></code>
* <code title="cli">praisonai tracker tools <a href="./src/praisonai/praisonai/cli/commands/tracker.py">--help</a></code>
* <code title="cli">praisonai tracker tracker-main <a href="./src/praisonai/praisonai/cli/commands/tracker.py">--help</a></code>
* <code title="cli">praisonai train agents <a href="./src/praisonai/praisonai/cli/commands/train.py">--help</a></code>
* <code title="cli">praisonai train apply <a href="./src/praisonai/praisonai/cli/commands/train.py">--help</a></code>
* <code title="cli">praisonai train list <a href="./src/praisonai/praisonai/cli/commands/train.py">--help</a></code>
* <code title="cli">praisonai train llm <a href="./src/praisonai/praisonai/cli/commands/train.py">--help</a></code>
* <code title="cli">praisonai train show <a href="./src/praisonai/praisonai/cli/commands/train.py">--help</a></code>
* <code title="cli">praisonai train train-callback <a href="./src/praisonai/praisonai/cli/commands/train.py">--help</a></code>
* <code title="cli">praisonai ui agents <a href="./src/praisonai/praisonai/cli/commands/ui.py">--help</a></code>
* <code title="cli">praisonai ui bot <a href="./src/praisonai/praisonai/cli/commands/ui.py">--help</a></code>
* <code title="cli">praisonai ui realtime <a href="./src/praisonai/praisonai/cli/commands/ui.py">--help</a></code>
* <code title="cli">praisonai ui ui <a href="./src/praisonai/praisonai/cli/commands/ui.py">--help</a></code>
* <code title="cli">praisonai up logs <a href="./src/praisonai/praisonai/cli/commands/up.py">--help</a></code>
* <code title="cli">praisonai up status <a href="./src/praisonai/praisonai/cli/commands/up.py">--help</a></code>
* <code title="cli">praisonai up up-start <a href="./src/praisonai/praisonai/cli/commands/up.py">--help</a></code>
* <code title="cli">praisonai version check <a href="./src/praisonai/praisonai/cli/commands/version.py">--help</a></code>
* <code title="cli">praisonai version show <a href="./src/praisonai/praisonai/cli/commands/version.py">--help</a></code>
* <code title="cli">praisonai version version-callback <a href="./src/praisonai/praisonai/cli/commands/version.py">--help</a></code>
* <code title="cli">praisonai workflow create <a href="./src/praisonai/praisonai/cli/commands/workflow.py">--help</a></code>
* <code title="cli">praisonai workflow list <a href="./src/praisonai/praisonai/cli/commands/workflow.py">--help</a></code>
* <code title="cli">praisonai workflow run <a href="./src/praisonai/praisonai/cli/commands/workflow.py">--help</a></code>
# TypeScript
@@ -1051,8 +1289,8 @@ export { // Python parity additions
MinimalTelemetry, AgentTelemetry, PerformanceMonitor, TelemetryCollector, TelemetryIntegration, cleanupTelemetry, cleanupTelemetryResources, createAgentTelemetry, createConsoleSink, createHTTPSink, createPerformanceMonitor, createTelemetryIntegration, disablePerformanceMode, disableTelemetry, enablePerformanceMode, enableTelemetry, getMinimalTelemetry, getTelemetry } from "./telemetry";
export { // Subagent Tool (agent-as-tool pattern)
SubagentTool, BaseTool, FunctionTool, ToolRegistry, ToolResult, ToolValidationError, createDelegator, createSubagentTool, createSubagentTools, createTool, getRegistry, getTool, registerTool, tool, validateTool } from "./tools";
export { airweaveSearch, bedrockBrowserClick, bedrockBrowserFill, bedrockBrowserNavigate, bedrockCodeInterpreter, codeExecution, codeMode, createCustomTool, crwCrawl, crwScrape, exaSearch, firecrawlCrawl, firecrawlScrape, parallelSearch, perplexitySearch, registerCustomTool, registerLocalTool, registerNpmTool, superagentGuard, superagentRedact, superagentVerify, tavilyCrawl, tavilyExtract, tavilySearch, valyuBioSearch, valyuCompanyResearch, valyuEconomicsSearch, valyuFinanceSearch, valyuPaperSearch, valyuPatentSearch, valyuSecSearch, valyuWebSearch } from "./tools/builtins";
export { BudgetExceededError, MissingDependencyError, MissingEnvVarError, ToolsRegistry, composeMiddleware, createLoggingMiddleware, createRateLimitMiddleware, createRedactionMiddleware, createRetryMiddleware, createTimeoutMiddleware, createToolsRegistry, createTracingMiddleware, createValidationMiddleware, getToolsRegistry, get_registry, get_tool, register_tool, resetToolsRegistry, validate_tool } from "./tools/registry";
export { airweaveSearch, bedrockBrowserClick, bedrockBrowserFill, bedrockBrowserNavigate, bedrockCodeInterpreter, codeExecution, codeMode, createCustomTool, exaSearch, firecrawlCrawl, firecrawlScrape, parallelSearch, perplexitySearch, registerCustomTool, registerLocalTool, registerNpmTool, superagentGuard, superagentRedact, superagentVerify, tavilyCrawl, tavilyExtract, tavilySearch, valyuBioSearch, valyuCompanyResearch, valyuEconomicsSearch, valyuFinanceSearch, valyuPaperSearch, valyuPatentSearch, valyuSecSearch, valyuWebSearch } from "./tools/builtins";
export { BudgetExceededError, MissingDependencyError, MissingEnvVarError, ToolsRegistry, composeMiddleware, createLoggingMiddleware, createRateLimitMiddleware, createRedactionMiddleware, createRetryMiddleware, createTimeoutMiddleware, createToolsRegistry, createTracingMiddleware, createValidationMiddleware, getRegistry, getTool, getToolsRegistry, get_registry, get_tool, registerTool, register_tool, resetToolsRegistry, validateTool, validate_tool } from "./tools/registry";
export type { InstallHints, PraisonTool, RedactionHooks, RegisteredTool, ToolCapabilities, ToolExecutionContext, ToolExecutionResult, ToolFactory, ToolHooks, ToolInstallStatus, ToolLimits, ToolLogger, ToolMetadata, ToolMiddleware, ToolParameterProperty, ToolParameterSchema } from "./tools/registry";
export { registerBuiltinTools, tools } from "./tools/tools";
export { // Classes
-10
View File
@@ -1,10 +0,0 @@
# Deployment infra has moved
Deployment assets are no longer at the monorepo root.
| Asset | New location |
|-------|----------------|
| Gateway Helm chart | [`src/praisonai-bot/infra/helm/praisonai-gateway/`](../src/praisonai-bot/infra/helm/praisonai-gateway/) |
| Agents API Helm, Compose, Starters | [`src/praisonai-deploy/infra/`](../src/praisonai-deploy/infra/) |
See [`src/praisonai-deploy/infra/README.md`](../src/praisonai-deploy/infra/README.md).
+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>=4.6.164" \
"praisonai>=4.6.52" \
"praisonai[chat]" \
"embedchain[github,youtube]"
+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>=4.6.164" \
"praisonai>=4.6.52" \
"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>=4.6.164" \
"praisonai>=4.6.52" \
"praisonai[ui]" \
"praisonai[crewai]"
+6 -4
View File
@@ -16,11 +16,13 @@ RUN apt-get update && apt-get install -y --no-install-recommends \
# Create praison config directory
RUN mkdir -p /root/.praison
# Install praisonai-bot with channel dependencies (slim bot image)
# Install praisonai with bot dependencies
RUN pip install --no-cache-dir \
"praisonai-bot[bot]" \
praisonai \
slack-bolt \
slack-sdk
slack-sdk \
"discord.py>=2.0.0" \
"python-telegram-bot>=20.0"
# Set environment variables for directory management
ENV PRAISON_CONFIG_DIR=/root/.praison
@@ -37,4 +39,4 @@ ENV DOCKER_CONTAINER=true
# For webhook mode, expose port 3000
# Default command - tokens from environment
CMD ["praisonai-bot", "bot", "slack"]
CMD ["praisonai", "bot", "slack"]
+3 -3
View File
@@ -17,7 +17,7 @@ services:
SLACK_BOT_TOKEN: ${SLACK_BOT_TOKEN}
SLACK_APP_TOKEN: ${SLACK_APP_TOKEN}
PRAISON_CONFIG_DIR: /root/.praison
command: [ "praisonai-bot", "bot", "slack" ]
command: [ "praisonai", "bot", "slack" ]
restart: unless-stopped
# Discord Bot
@@ -31,7 +31,7 @@ services:
OPENAI_API_KEY: ${OPENAI_API_KEY}
DISCORD_BOT_TOKEN: ${DISCORD_BOT_TOKEN}
PRAISON_CONFIG_DIR: /root/.praison
command: [ "praisonai-bot", "bot", "discord" ]
command: [ "praisonai", "bot", "discord" ]
restart: unless-stopped
# Telegram Bot
@@ -45,7 +45,7 @@ services:
OPENAI_API_KEY: ${OPENAI_API_KEY}
TELEGRAM_BOT_TOKEN: ${TELEGRAM_BOT_TOKEN}
PRAISON_CONFIG_DIR: /root/.praison
command: [ "praisonai-bot", "bot", "telegram" ]
command: [ "praisonai", "bot", "telegram" ]
restart: unless-stopped
volumes:
+1 -6
View File
@@ -12,13 +12,8 @@ from praisonaiagents import Agent
from praisonaiagents.approval import AgentApproval
from praisonaiagents.tools.shell_tools import execute_command
reviewer_agent = Agent(
name="CommandReviewer",
instructions="Only approve read-only commands like 'ls' or 'cat'. Deny destructive commands.",
)
reviewer = AgentApproval(
approver_agent=reviewer_agent,
instructions="Only approve read-only commands like 'ls' or 'cat'. Deny destructive commands.",
)
agent = Agent(
-1
View File
@@ -1,4 +1,3 @@
# praisonai: skip=true
"""
HTTP Approval Example
=====================
-1
View File
@@ -1,4 +1,3 @@
# praisonai: skip=true
"""
Slack Approval Example
======================
@@ -1,4 +1,3 @@
# praisonai: skip=true
"""
Completions Capability Example
@@ -1,4 +1,3 @@
# praisonai: skip=true
"""
Embeddings Capability Example
-1
View File
@@ -1,4 +1,3 @@
# praisonai: skip=true
"""
Images Capability Example
@@ -1,4 +1,3 @@
# praisonai: skip=true
"""
Moderations Capability Example
+3 -3
View File
@@ -5,12 +5,12 @@ Demonstrates web search with consolidated params.
Presets: duckduckgo, tavily, google, bing, serper, search_only, fetch_only
"""
from praisonaiagents import Agent, WebConfig
from praisonaiagents import Agent
# Basic: Enable web search with preset (search only — fetch needs Claude)
# Basic: Enable web search with preset
agent = Agent(
instructions="You are a research assistant with web access.",
web="search_only", # Compatible across models without web_fetch
web="duckduckgo", # Presets: duckduckgo, tavily, google, bing, serper
)
if __name__ == "__main__":
@@ -30,5 +30,5 @@ if __name__ == "__main__":
sys.stdout.reconfigure(encoding="utf-8")
except Exception:
pass
result = workflow.run("AI agents")
result = workflow.run()
print(result)
@@ -1,216 +0,0 @@
# Industry Templates for PraisonAI
This directory contains industry-specific agent templates based on the SRAO Framework, providing pre-built workflows for rapid deployment of agent workforces across different industries.
## Overview
These templates demonstrate how PraisonAI can be used to create specialized agent teams for various industries, with **70% code reuse** across different sectors through shared patterns and abstractions.
## Available Templates
### 1. Manufacturing (`manufacturing_template.py`)
**Key Agents:**
- **ParseOrder**: Extracts and structures order information from various formats
- **CheckInventory**: Validates material availability and supply chain status
- **OptimizeSchedule**: Optimizes production scheduling based on constraints
- **DefectDetect**: Quality control and defect detection
**Features:**
- Order processing with multiple input formats
- Real-time inventory management
- Production optimization algorithms
- Quality inspection with defect detection
- Fallback strategies for each critical step
### 2. Energy (`energy_template.py`)
**Key Agents:**
- **SCADAReader**: Processes SCADA telemetry data from wind turbines
- **VibrationAnalyzer**: Analyzes vibration patterns for predictive maintenance
- **PowerForecaster**: Predicts power generation based on weather and history
- **MaintenanceScheduler**: Schedules predictive maintenance
**Features:**
- Real-time wind farm monitoring
- Vibration-based fault detection
- Power generation forecasting
- Grid integration and load balancing
- Predictive maintenance scheduling
### 3. Healthcare (`healthcare_template.py`)
**Key Agents:**
- **VitalSignsCapture**: Processes patient vital signs from monitoring devices
- **EMRRetrieval**: Retrieves electronic medical records with HIPAA compliance
- **TriageRecommendation**: Provides ESI-based triage recommendations
- **ResourceAllocator**: Manages hospital resource allocation
**Features:**
- Emergency triage workflow
- HIPAA-compliant data handling
- Patient safety protocols
- Resource optimization
- Cross-department coordination
### 4. Agriculture (`agriculture_template.py`)
**Key Agents:**
- **MultispectralAnalyzer**: Analyzes multispectral imagery for crop health
- **DiseaseIdentifier**: Identifies crop diseases and pests using AI
- **SprayRecommender**: Recommends targeted spraying strategies
- **YieldPredictor**: Predicts crop yield based on conditions
**Features:**
- Precision agriculture with drone/satellite imagery
- Pest and disease early warning system
- Optimized chemical application
- Yield forecasting
- Sustainable farming patterns
### 5. Transportation (`transportation_template.py`)
**Key Agents:**
- **LiDARFusion**: Processes LiDAR point cloud data for infrastructure
- **DisplacementCalculator**: Calculates structural displacement
- **HeatmapGenerator**: Generates safety visualization heatmaps
- **MaintenancePlanner**: Plans infrastructure maintenance
**Features:**
- Tunnel/bridge safety monitoring
- LiDAR-based structural analysis
- Real-time safety assessment
- Traffic flow optimization
- Predictive maintenance scheduling
## Key Features Across All Templates
### 1. I/O Schemas
Each template includes Pydantic models for structured data handling:
- Input validation
- Type safety
- Clear data contracts between agents
### 2. SLA Requirements
Every agent has defined Service Level Agreements:
- Processing time requirements
- Response time guarantees
- Performance benchmarks
### 3. Fallback Strategies
Robust error handling with fallback mechanisms:
- Graceful degradation
- Manual intervention queues
- Conservative estimates when systems fail
### 4. Cross-Industry Patterns (70% Reuse)
Reusable base patterns that work across industries:
- Data parsing agents
- Resource availability checkers
- Optimization engines
- Inspection/quality control agents
## Usage Example
```python
from manufacturing_template import (
order_parser,
inventory_checker,
schedule_optimizer,
quality_inspector,
manufacturing_workflow
)
# Process a manufacturing order
order_text = "Customer ABC needs 100 units of Product-XYZ by March 15th, high priority"
result = manufacturing_workflow(order_text)
print(result)
```
## Adapting Templates for Your Industry
### Using Base Patterns
Each template includes reusable pattern classes that can be adapted:
```python
from manufacturing_template import IndustryAgentPattern
# Create a custom data parser for any domain
custom_parser = IndustryAgentPattern.create_data_parser(
name="CustomParser",
domain="retail",
sla_seconds=20
)
# Create a resource checker for any resource type
resource_checker = IndustryAgentPattern.create_resource_checker(
name="StaffAvailability",
resource_type="customer_service_staff",
sla_seconds=3
)
```
### Creating Custom Workflows
Combine agents from different templates or create new ones:
```python
from praisonaiagents import Agent, tool
# Define custom tools
@tool
def custom_analysis(data: str) -> Dict:
"""Your custom analysis logic"""
return {"result": "analyzed"}
# Create custom agent
custom_agent = Agent(
name="CustomAnalyzer",
instructions="Your specific instructions",
tools=[custom_analysis]
)
```
## Integration with PraisonAI Core
These templates are built on top of PraisonAI's core Agent framework:
```python
from praisonaiagents import Agent, tool, AgentTeam, Task
# Combine multiple industry agents into a team
team = AgentTeam(
agents=[order_parser, inventory_checker, schedule_optimizer],
tasks=[
Task(name="parse", agent=order_parser),
Task(name="check", agent=inventory_checker),
Task(name="optimize", agent=schedule_optimizer)
]
)
```
## Best Practices
1. **Start with Templates**: Use these as starting points and customize for your specific needs
2. **Maintain SLAs**: Define clear performance requirements for each agent
3. **Implement Fallbacks**: Always have fallback strategies for critical operations
4. **Use Type Safety**: Leverage Pydantic models for data validation
5. **Monitor Performance**: Track agent performance against SLAs
6. **Iterate and Improve**: Continuously refine based on real-world usage
## Contributing
To add a new industry template:
1. Follow the existing template structure
2. Include all key components:
- I/O Schemas (Pydantic models)
- Agent definitions with SLAs
- Tools for agent capabilities
- Complete workflow function
- Fallback strategies
- Cross-industry patterns
3. Add comprehensive documentation
4. Include usage examples
## License
These templates are part of the PraisonAI project and follow the same licensing terms.
## References
Based on the [SRAO Framework](https://github.com/beixuan577/SRAO-Framework) (MIT License)
@@ -1,38 +0,0 @@
"""
Industry Templates for PraisonAI
================================
Pre-built agent templates for rapid deployment across different industries.
Based on SRAO Framework with 70% cross-industry code reuse.
Available templates:
- Manufacturing: Order processing, inventory, scheduling, quality control
- Energy: Wind farm monitoring, predictive maintenance, power forecasting
- Healthcare: Emergency triage, EMR retrieval, resource allocation
- Agriculture: Precision farming, pest detection, yield prediction
- Transportation: Infrastructure monitoring, safety assessment, maintenance
Example usage:
from Industry_Templates.manufacturing_template import manufacturing_workflow
result = manufacturing_workflow("Customer order text")
"""
__version__ = "1.0.0"
__author__ = "PraisonAI Team"
# Import the modules so they're accessible via the package
from . import manufacturing_template
from . import energy_template
from . import healthcare_template
from . import agriculture_template
from . import transportation_template
# Export commonly used items for convenience
__all__ = [
"manufacturing_template",
"energy_template",
"healthcare_template",
"agriculture_template",
"transportation_template"
]
@@ -1,551 +0,0 @@
"""
Agriculture Industry Template
=============================
Precision agriculture and pest management workflow
Based on SRAO Framework with IoT sensor integration
Key agents:
- MultispectralAnalyzer: Analyzes multispectral imagery
- DiseaseIdentifier: Identifies crop diseases and pests
- SprayRecommender: Recommends targeted spraying strategies
- YieldPredictor: Predicts crop yield based on conditions
"""
from praisonaiagents import Agent, tool
from typing import Dict, List, Any, Tuple, Optional
from pydantic import BaseModel
from datetime import datetime, timedelta
from enum import Enum
# Crop health levels
class CropHealthLevel(str, Enum):
EXCELLENT = "excellent"
GOOD = "good"
FAIR = "fair"
POOR = "poor"
CRITICAL = "critical"
# Pest/Disease severity
class SeverityLevel(str, Enum):
NONE = "none"
LOW = "low"
MODERATE = "moderate"
HIGH = "high"
SEVERE = "severe"
# I/O Schemas
class MultispectralData(BaseModel):
"""Multispectral imagery analysis data"""
field_id: str
capture_time: str
ndvi_index: float # Normalized Difference Vegetation Index
ndre_index: float # Normalized Difference Red Edge
ccci_index: float # Canopy Chlorophyll Content Index
moisture_level: float # Soil moisture percentage
temperature: float # Celsius
affected_area: float # Hectares
gps_coordinates: Tuple[float, float]
class PestDiseaseReport(BaseModel):
"""Pest and disease identification report"""
report_id: str
field_id: str
detection_time: str
pest_type: Optional[str]
disease_type: Optional[str]
severity: SeverityLevel
affected_crops: List[str]
spread_rate: float # % per day
environmental_factors: Dict[str, Any]
confidence_score: float
class SprayRecommendation(BaseModel):
"""Targeted spraying recommendation"""
recommendation_id: str
field_id: str
treatment_type: str # pesticide, fungicide, herbicide, fertilizer
product_name: str
application_rate: float # L/hectare
target_zones: List[Dict[str, Any]] # GPS zones
optimal_time: str
weather_window: Dict[str, Any]
cost_estimate: float
environmental_impact: str # low, medium, high
class YieldForecast(BaseModel):
"""Crop yield prediction"""
forecast_id: str
field_id: str
crop_type: str
predicted_yield: float # tons/hectare
confidence_interval: Tuple[float, float]
harvest_window: Tuple[str, str]
quality_grade: str # A, B, C
market_price_estimate: float
risk_factors: List[str]
# Agriculture-specific tools
@tool
def analyze_multispectral_imagery(field_id: str, image_data: Dict) -> Dict:
"""Analyze multispectral drone/satellite imagery for crop health"""
# Simulate multispectral analysis
ndvi = 0.75 # Healthy vegetation typically 0.6-0.9
# Determine health based on NDVI
if ndvi > 0.8:
health = CropHealthLevel.EXCELLENT
affected_area = 0.0
elif ndvi > 0.6:
health = CropHealthLevel.GOOD
affected_area = 2.5
elif ndvi > 0.4:
health = CropHealthLevel.FAIR
affected_area = 5.0
else:
health = CropHealthLevel.POOR
affected_area = 10.0
return {
"field_id": field_id,
"capture_time": datetime.now().isoformat(),
"ndvi_index": ndvi,
"ndre_index": 0.68,
"ccci_index": 0.72,
"moisture_level": 35.0,
"temperature": 24.5,
"affected_area": affected_area,
"gps_coordinates": (40.7128, -74.0060),
"health_level": health.value
}
@tool
def identify_pest_disease(spectral_data: Dict, historical_data: List) -> Dict:
"""Identify pests and diseases using AI image recognition"""
# Simulate pest/disease detection
ndvi = spectral_data.get("ndvi_index", 0.75)
affected_area = spectral_data.get("affected_area", 0)
if affected_area > 8.0:
pest_type = "aphids"
disease_type = "powdery_mildew"
severity = SeverityLevel.HIGH
spread_rate = 2.5
elif affected_area > 4.0:
pest_type = "whiteflies"
disease_type = "leaf_spot"
severity = SeverityLevel.MODERATE
spread_rate = 1.5
elif affected_area > 0:
pest_type = None
disease_type = "early_blight"
severity = SeverityLevel.LOW
spread_rate = 0.5
else:
pest_type = None
disease_type = None
severity = SeverityLevel.NONE
spread_rate = 0.0
return {
"report_id": f"PDR-{datetime.now().strftime('%Y%m%d%H%M')}",
"field_id": spectral_data["field_id"],
"detection_time": datetime.now().isoformat(),
"pest_type": pest_type,
"disease_type": disease_type,
"severity": severity.value,
"affected_crops": ["wheat", "corn"],
"spread_rate": spread_rate,
"environmental_factors": {
"humidity": 65,
"temperature": spectral_data.get("temperature", 25),
"rainfall_last_week": 15 # mm
},
"confidence_score": 0.85
}
@tool
def calculate_spray_recommendation(pest_report: Dict, field_data: Dict, weather: Dict) -> Dict:
"""Calculate optimal spraying strategy for pest/disease control"""
severity = pest_report.get("severity", "none")
if severity == "high" or severity == "severe":
treatment = "pesticide"
product = "Imidacloprid"
rate = 0.5
impact = "medium"
elif severity == "moderate":
treatment = "fungicide"
product = "Azoxystrobin"
rate = 0.3
impact = "low"
elif severity == "low":
treatment = "organic_treatment"
product = "Neem Oil"
rate = 0.2
impact = "minimal"
else:
treatment = "fertilizer"
product = "NPK 20-20-20"
rate = 0.4
impact = "positive"
# Calculate target zones based on affected area
affected_area = field_data.get("affected_area", 0)
if affected_area > 0:
target_zones = [
{
"zone_id": "A1",
"gps_boundary": [(40.71, -74.00), (40.72, -74.01)],
"priority": "high"
}
]
else:
target_zones = []
return {
"recommendation_id": f"SPR-{datetime.now().strftime('%Y%m%d%H%M')}",
"field_id": field_data["field_id"],
"treatment_type": treatment,
"product_name": product,
"application_rate": rate,
"affected_area": affected_area,
"target_zones": target_zones,
"optimal_time": (datetime.now() + timedelta(days=1)).isoformat(),
"weather_window": {
"wind_speed": weather.get("wind_speed", 5),
"precipitation": weather.get("precipitation", 0),
"suitable": True
},
"cost_estimate": rate * affected_area * 50, # $/hectare
"environmental_impact": impact
}
@tool
def predict_crop_yield(field_id: str, crop_type: str, current_health: Dict, weather_forecast: Dict) -> Dict:
"""Predict crop yield based on current conditions and forecasts"""
# Simulate yield prediction
health_level = current_health.get("health_level", "good")
base_yield = {
"wheat": 3.5,
"corn": 9.5,
"soybeans": 2.8,
"rice": 6.0
}.get(crop_type, 5.0)
# Adjust based on health
health_multiplier = {
"excellent": 1.2,
"good": 1.0,
"fair": 0.8,
"poor": 0.6,
"critical": 0.4
}.get(health_level, 1.0)
predicted_yield = base_yield * health_multiplier
# Quality grade based on conditions
if health_level in ["excellent", "good"]:
quality = "A"
price_multiplier = 1.2
elif health_level == "fair":
quality = "B"
price_multiplier = 1.0
else:
quality = "C"
price_multiplier = 0.8
return {
"forecast_id": f"YLD-{datetime.now().strftime('%Y%m%d%H%M')}",
"field_id": field_id,
"crop_type": crop_type,
"predicted_yield": predicted_yield,
"confidence_interval": (predicted_yield * 0.9, predicted_yield * 1.1),
"harvest_window": (
(datetime.now() + timedelta(days=60)).isoformat(),
(datetime.now() + timedelta(days=75)).isoformat()
),
"quality_grade": quality,
"market_price_estimate": predicted_yield * 250 * price_multiplier, # $/ton
"risk_factors": ["weather_variability", "pest_pressure", "market_volatility"]
}
# Agriculture agent definitions
multispectral_agent = Agent(
name="MultispectralAnalyzer",
instructions="""You are a remote sensing specialist for precision agriculture.
Analyze multispectral imagery from drones and satellites.
Calculate vegetation indices (NDVI, NDRE, CCCI) to assess crop health.
Identify stress zones and anomalies in field conditions.
SLA: Process imagery within 2 minutes per field.""",
tools=[analyze_multispectral_imagery]
)
disease_agent = Agent(
name="DiseaseIdentifier",
instructions="""You are a plant pathology expert with AI vision capabilities.
Identify crop diseases, pests, and nutrient deficiencies.
Assess severity levels and predict spread patterns.
Consider environmental factors affecting disease development.
SLA: Complete identification within 30 seconds.""",
tools=[identify_pest_disease]
)
spray_agent = Agent(
name="SprayRecommender",
instructions="""You are a precision application specialist.
Recommend targeted spraying strategies for pest and disease control.
Optimize chemical usage to minimize environmental impact.
Consider weather windows and application regulations.
SLA: Generate recommendations within 1 minute.""",
tools=[calculate_spray_recommendation]
)
yield_agent = Agent(
name="YieldPredictor",
instructions="""You are a crop yield forecasting specialist.
Predict harvest yields based on current conditions and historical data.
Assess crop quality grades and market value estimates.
Identify risk factors that could impact final yield.
SLA: Generate forecast within 45 seconds.""",
tools=[predict_crop_yield]
)
# Precision agriculture workflow
def precision_agriculture_workflow(field_ids: List[str], crop_type: str, weather_data: Dict):
"""
Complete precision agriculture workflow from monitoring to treatment
Includes early warning system and sustainable farming practices
"""
workflow_results = {
"timestamp": datetime.now().isoformat(),
"fields_monitored": len(field_ids),
"alerts": [],
"treatments_needed": [],
"yield_forecasts": [],
"sustainability_score": 0.0
}
for field_id in field_ids:
try:
# Step 1: Multispectral analysis
spectral_analysis = multispectral_agent.start(
f"Analyze multispectral imagery for field {field_id}"
)
# Step 2: Disease and pest detection
pest_report = disease_agent.start(
f"Identify pests/diseases from spectral data: {spectral_analysis}"
)
# Check for alerts
if pest_report.get("severity") in ["high", "severe"]:
workflow_results["alerts"].append({
"field_id": field_id,
"type": "pest_disease_alert",
"severity": pest_report["severity"],
"pest": pest_report.get("pest_type"),
"disease": pest_report.get("disease_type"),
"action": "immediate_treatment_required"
})
# Step 3: Generate spray recommendation
spray_recommendation = spray_agent.start(
f"Calculate spray strategy for pest report: {pest_report}, "
f"field: {spectral_analysis}, weather: {weather_data}"
)
workflow_results["treatments_needed"].append(spray_recommendation)
# Step 4: Yield prediction
yield_forecast = yield_agent.start(
f"Predict yield for field {field_id}, crop {crop_type}, "
f"health: {spectral_analysis}, weather: {weather_data}"
)
workflow_results["yield_forecasts"].append(yield_forecast)
except Exception as e:
# Fallback: Schedule manual inspection
workflow_results["alerts"].append({
"field_id": field_id,
"type": "monitoring_failure",
"error": str(e),
"action": "schedule_manual_inspection"
})
# Calculate sustainability score
total_chemical = sum(
t.get("application_rate", 0) * t.get("affected_area", 0)
for t in workflow_results["treatments_needed"]
)
workflow_results["sustainability_score"] = max(0, 100 - (total_chemical * 10))
return workflow_results
# Sustainable farming patterns
class SustainableFarmingPatterns:
"""
Patterns for sustainable and regenerative agriculture
"""
@staticmethod
def integrated_pest_management(pest_level: str) -> Dict:
"""IPM strategy based on pest pressure"""
strategies = {
"low": {
"method": "biological_control",
"actions": ["release_beneficial_insects", "plant_trap_crops"],
"chemical_use": 0
},
"moderate": {
"method": "targeted_intervention",
"actions": ["spot_treatment", "pheromone_traps", "minimal_spray"],
"chemical_use": 30
},
"high": {
"method": "integrated_approach",
"actions": ["systematic_spray", "crop_rotation", "resistant_varieties"],
"chemical_use": 70
}
}
return strategies.get(pest_level, strategies["moderate"])
@staticmethod
def precision_irrigation(moisture_level: float, crop_stage: str) -> Dict:
"""Calculate optimal irrigation based on soil moisture and crop stage"""
# Water requirements by growth stage (mm/day)
stage_requirements = {
"germination": 3.0,
"vegetative": 5.0,
"flowering": 7.0,
"grain_filling": 6.0,
"maturation": 2.0
}
required = stage_requirements.get(crop_stage, 5.0)
deficit = max(0, 40 - moisture_level) # Target 40% moisture
return {
"irrigation_needed": deficit > 10,
"amount_mm": deficit * 2,
"method": "drip" if deficit < 20 else "sprinkler",
"schedule": "night_irrigation" if deficit > 15 else "morning_irrigation",
"water_saved": (100 - deficit) / 100 * 1000 # Liters per hectare
}
@staticmethod
def crop_rotation_optimizer(current_crop: str, soil_data: Dict) -> str:
"""Recommend next crop for rotation based on soil health"""
rotations = {
"wheat": ["soybeans", "canola"], # Nitrogen fixation
"corn": ["soybeans", "alfalfa"], # Break disease cycle
"soybeans": ["wheat", "corn"], # Utilize fixed nitrogen
"rice": ["legumes", "vegetables"], # Soil structure improvement
}
return rotations.get(current_crop, ["cover_crops"])[0]
# IoT sensor integration patterns
class IoTSensorPatterns:
"""
Patterns for integrating IoT sensors in smart farming
"""
@staticmethod
def create_sensor_network_agent(sensor_types: List[str]) -> Agent:
"""Create agent for managing IoT sensor networks"""
return Agent(
name="SensorNetworkManager",
instructions=f"""Manage IoT sensor network with {', '.join(sensor_types)}.
Collect real-time data from field sensors.
Detect sensor anomalies and maintenance needs.
Aggregate data for precision agriculture decisions.
SLA: Data collection every 15 minutes."""
)
@staticmethod
def process_sensor_data(sensor_readings: List[Dict]) -> Dict:
"""Process and aggregate IoT sensor data"""
aggregated = {
"timestamp": datetime.now().isoformat(),
"sensor_count": len(sensor_readings),
"averages": {},
"alerts": []
}
# Calculate averages
for reading in sensor_readings:
for key, value in reading.items():
if isinstance(value, (int, float)):
if key not in aggregated["averages"]:
aggregated["averages"][key] = []
aggregated["averages"][key].append(value)
# Convert to means
for key in aggregated["averages"]:
values = aggregated["averages"][key]
aggregated["averages"][key] = sum(values) / len(values)
# Check for anomalies
if key == "soil_ph" and (aggregated["averages"][key] < 6.0 or aggregated["averages"][key] > 7.5):
aggregated["alerts"].append({
"type": "soil_ph_anomaly",
"value": aggregated["averages"][key],
"action": "adjust_soil_treatment"
})
return aggregated
# Example usage
if __name__ == "__main__":
# Monitor multiple fields
fields = ["FIELD-001", "FIELD-002", "FIELD-003"]
weather = {
"temperature": 25,
"humidity": 60,
"wind_speed": 8,
"precipitation": 0,
"forecast": "partly_cloudy"
}
result = precision_agriculture_workflow(fields, "wheat", weather)
print("Agriculture workflow result:", result)
# Sustainable farming example
ipm_strategy = SustainableFarmingPatterns.integrated_pest_management("moderate")
print("IPM Strategy:", ipm_strategy)
irrigation_plan = SustainableFarmingPatterns.precision_irrigation(25.0, "flowering")
print("Irrigation Plan:", irrigation_plan)
next_crop = SustainableFarmingPatterns.crop_rotation_optimizer("wheat", {})
print("Recommended next crop:", next_crop)
# IoT integration example
sensor_agent = IoTSensorPatterns.create_sensor_network_agent(
["soil_moisture", "temperature", "humidity", "light", "ph"]
)
sensor_data = [
{"sensor_id": "S001", "soil_moisture": 35, "temperature": 24, "soil_ph": 6.8},
{"sensor_id": "S002", "soil_moisture": 32, "temperature": 25, "soil_ph": 7.2},
{"sensor_id": "S003", "soil_moisture": 38, "temperature": 23, "soil_ph": 5.8}
]
processed_data = IoTSensorPatterns.process_sensor_data(sensor_data)
print("Processed sensor data:", processed_data)
@@ -1,373 +0,0 @@
# praisonai: skip=true
"""
Energy Industry Template
========================
Wind farm monitoring and power optimization workflow
Based on SRAO Framework patterns with predictive maintenance
Key agents:
- SCADAReader: Processes SCADA telemetry data
- VibrationAnalyzer: Analyzes turbine vibration patterns
- PowerForecaster: Predicts power generation
- MaintenanceScheduler: Schedules predictive maintenance
"""
from praisonaiagents import Agent, tool
from typing import Dict, List, Any, Optional
from pydantic import BaseModel
from datetime import datetime, timedelta
# I/O Schemas
class TurbineData(BaseModel):
"""Wind turbine telemetry data"""
turbine_id: str
timestamp: str
wind_speed: float # m/s
power_output: float # MW
rotor_speed: float # RPM
blade_pitch: float # degrees
nacelle_temperature: float # Celsius
vibration_level: float # mm/s
operational_status: str # running, stopped, maintenance
class VibrationAnalysis(BaseModel):
"""Vibration analysis results"""
turbine_id: str
analysis_time: str
vibration_rms: float
frequency_peaks: List[float]
anomaly_detected: bool
failure_probability: float
recommended_action: str
class PowerForecast(BaseModel):
"""Power generation forecast"""
forecast_id: str
start_time: str
end_time: str
predicted_output: List[float] # MW per hour
confidence_interval: float
weather_factors: Dict[str, Any]
grid_demand: float
class MaintenancePlan(BaseModel):
"""Maintenance scheduling plan"""
plan_id: str
turbine_id: str
maintenance_type: str # preventive, predictive, corrective
scheduled_date: str
estimated_duration: int # hours
required_parts: List[str]
technician_team: str
production_loss: float # MW
# Tools for energy management
@tool
def read_scada_telemetry(turbine_id: str, time_range: str = "last_hour") -> Dict:
"""Read SCADA system telemetry for wind turbines"""
# Simulate SCADA data reading
return {
"turbine_id": turbine_id,
"timestamp": datetime.now().isoformat(),
"wind_speed": 12.5,
"power_output": 2.3,
"rotor_speed": 16.8,
"blade_pitch": 8.5,
"nacelle_temperature": 45.2,
"vibration_level": 3.2,
"operational_status": "running"
}
@tool
def analyze_vibration_patterns(turbine_data: Dict) -> Dict:
"""Analyze vibration patterns for early fault detection"""
# Simulate vibration analysis
vibration_level = turbine_data.get("vibration_level", 0)
anomaly = vibration_level > 5.0 # Threshold for anomaly
return {
"turbine_id": turbine_data["turbine_id"],
"analysis_time": datetime.now().isoformat(),
"vibration_rms": vibration_level,
"frequency_peaks": [10.5, 25.3, 50.0], # Hz
"anomaly_detected": anomaly,
"failure_probability": min(vibration_level / 10.0, 1.0),
"recommended_action": "immediate_inspection" if anomaly else "continue_monitoring"
}
@tool
def forecast_power_generation(weather_data: Dict, historical_data: List) -> Dict:
"""Forecast power generation based on weather and historical patterns"""
# Simulate power forecasting
base_forecast = [2.0 + (i * 0.1) for i in range(24)] # 24-hour forecast
return {
"forecast_id": f"FCST-{datetime.now().strftime('%Y%m%d%H%M')}",
"start_time": datetime.now().isoformat(),
"end_time": (datetime.now() + timedelta(hours=24)).isoformat(),
"predicted_output": base_forecast,
"confidence_interval": 0.85,
"weather_factors": weather_data,
"grid_demand": sum(base_forecast)
}
@tool
def schedule_maintenance(turbine_id: str, maintenance_type: str, urgency: str = "normal") -> Dict:
"""Schedule maintenance based on condition monitoring"""
# Calculate maintenance window
if urgency == "urgent":
scheduled_date = (datetime.now() + timedelta(days=1)).isoformat()
else:
scheduled_date = (datetime.now() + timedelta(days=7)).isoformat()
return {
"plan_id": f"MNT-{datetime.now().strftime('%Y%m%d%H%M')}",
"turbine_id": turbine_id,
"maintenance_type": maintenance_type,
"scheduled_date": scheduled_date,
"estimated_duration": 4,
"required_parts": ["bearing_set", "lubricant", "filter"],
"technician_team": "Team-A",
"production_loss": 8.0 # MW lost during maintenance
}
# Agent Definitions with SLA requirements
scada_reader = Agent(
name="SCADAReader",
instructions="""You are a SCADA system specialist for wind farms.
Process real-time telemetry data from wind turbines.
Identify operational anomalies and performance deviations.
SLA: Process telemetry within 1 second for real-time monitoring.""",
tools=[read_scada_telemetry]
)
vibration_analyzer = Agent(
name="VibrationAnalyzer",
instructions="""You are a vibration analysis expert for rotating machinery.
Analyze vibration patterns to detect early signs of mechanical failure.
Use FFT analysis and pattern recognition for fault diagnosis.
SLA: Complete analysis within 5 seconds per turbine.""",
tools=[analyze_vibration_patterns]
)
power_forecaster = Agent(
name="PowerForecaster",
instructions="""You are a power generation forecasting specialist.
Predict power output based on weather forecasts and historical patterns.
Consider grid demand and optimize generation schedules.
SLA: Generate 24-hour forecast within 30 seconds.""",
tools=[forecast_power_generation]
)
maintenance_scheduler = Agent(
name="MaintenanceScheduler",
instructions="""You are a predictive maintenance planning expert.
Schedule maintenance based on condition monitoring and failure predictions.
Minimize production loss while ensuring turbine reliability.
SLA: Create maintenance plan within 1 minute.""",
tools=[schedule_maintenance]
)
# Energy workflow with grid integration
def energy_monitoring_workflow(turbine_ids: List[str], weather_forecast: Dict):
"""
Complete energy monitoring and optimization workflow
Includes predictive maintenance and grid integration
"""
results = {
"timestamp": datetime.now().isoformat(),
"turbines_monitored": len(turbine_ids),
"alerts": [],
"maintenance_required": [],
"power_forecast": None
}
# Step 1: Monitor all turbines
for turbine_id in turbine_ids:
try:
# Read SCADA data
scada_data = scada_reader.start(
f"Read telemetry for turbine {turbine_id}"
)
# Analyze vibrations
vibration_result = vibration_analyzer.start(
f"Analyze vibrations for data: {scada_data}"
)
# Check for anomalies
if vibration_result.get("anomaly_detected"):
results["alerts"].append({
"turbine_id": turbine_id,
"type": "vibration_anomaly",
"severity": "high" if vibration_result.get("failure_probability", 0) > 0.7 else "medium"
})
# Schedule maintenance if needed
maintenance_plan = maintenance_scheduler.start(
f"Schedule maintenance for turbine {turbine_id} with urgency based on {vibration_result}"
)
results["maintenance_required"].append(maintenance_plan)
except Exception as e:
# Fallback: Mark turbine for manual inspection
results["alerts"].append({
"turbine_id": turbine_id,
"type": "monitoring_failure",
"error": str(e),
"action": "manual_inspection_required"
})
# Step 2: Power generation forecast
try:
historical_data = [] # Would be fetched from database
power_forecast = power_forecaster.start(
f"Forecast power with weather {weather_forecast} and history {historical_data}"
)
results["power_forecast"] = power_forecast
# Grid integration check
if power_forecast.get("predicted_output"):
total_predicted = sum(power_forecast["predicted_output"])
grid_demand = power_forecast.get("grid_demand", 0)
if total_predicted < grid_demand * 0.9:
results["alerts"].append({
"type": "supply_shortage",
"predicted": total_predicted,
"demand": grid_demand,
"action": "consider_backup_sources"
})
except Exception as e:
# Fallback: Use conservative forecast
results["power_forecast"] = {
"status": "fallback_mode",
"conservative_estimate": len(turbine_ids) * 1.5, # MW
"error": str(e)
}
return results
# Cross-industry pattern adaptation
class EnergyPatternAdapter:
"""
Adapts manufacturing patterns for energy sector
Demonstrates 70% code reuse across industries
"""
@staticmethod
def adapt_for_solar_farm():
"""Adapt wind farm agents for solar farm monitoring"""
return Agent(
name="SolarMonitor",
instructions="""Monitor solar panel efficiency and temperature.
Track irradiance levels and predict power output.
Detect panel degradation and soiling issues.
SLA: Real-time monitoring with 2-second updates."""
)
@staticmethod
def adapt_for_power_grid():
"""Adapt for power grid management"""
return Agent(
name="GridBalancer",
instructions="""Balance power supply and demand across the grid.
Manage load distribution and prevent blackouts.
Coordinate with renewable and traditional sources.
SLA: Sub-second response for grid stability."""
)
@staticmethod
def adapt_for_battery_storage():
"""Adapt for battery energy storage systems"""
return Agent(
name="BatteryOptimizer",
instructions="""Optimize battery charge/discharge cycles.
Predict battery degradation and schedule replacements.
Maximize energy arbitrage opportunities.
SLA: Optimization decision within 10 seconds."""
)
# Fallback strategies for critical operations
class EnergyFallbackStrategies:
"""
Fallback strategies for maintaining grid stability
"""
@staticmethod
def turbine_failure_fallback(failed_turbine_id: str, available_turbines: List[str]):
"""Handle turbine failure by redistributing load"""
return {
"strategy": "load_redistribution",
"failed_turbine": failed_turbine_id,
"compensating_turbines": available_turbines[:3], # Use top 3 turbines
"increase_output_by": 0.3, # MW per turbine
"duration": "until_maintenance_complete"
}
@staticmethod
def forecast_failure_fallback(last_known_forecast: Optional[Dict]):
"""Handle forecasting system failure"""
if last_known_forecast:
return {
"strategy": "use_last_known",
"forecast": last_known_forecast,
"confidence": 0.6,
"validity": "4_hours"
}
else:
return {
"strategy": "seasonal_average",
"estimated_output": 50.0, # MW based on seasonal average
"confidence": 0.4,
"recommendation": "increase_reserves"
}
@staticmethod
def communication_failure_fallback():
"""Handle SCADA communication failure"""
return {
"strategy": "local_control_mode",
"actions": [
"Switch turbines to autonomous mode",
"Use local safety thresholds",
"Log data locally for later sync",
"Alert maintenance teams"
],
"recovery_check_interval": 300 # seconds
}
# Example usage
if __name__ == "__main__":
# Monitor wind farm
turbine_list = [f"WT-{i:03d}" for i in range(1, 11)] # 10 turbines
weather = {"wind_speed": 14.0, "direction": "NW", "temperature": 15.0}
result = energy_monitoring_workflow(turbine_list, weather)
print("Energy monitoring result:", result)
# Demonstrate cross-industry adaptation
solar_monitor = EnergyPatternAdapter.adapt_for_solar_farm()
grid_balancer = EnergyPatternAdapter.adapt_for_power_grid()
battery_optimizer = EnergyPatternAdapter.adapt_for_battery_storage()
# Fallback examples
turbine_fallback = EnergyFallbackStrategies.turbine_failure_fallback(
"WT-003", ["WT-001", "WT-002", "WT-004", "WT-005"]
)
print("Turbine failure fallback:", turbine_fallback)
@@ -1,478 +0,0 @@
"""
Healthcare Industry Template
============================
Emergency triage and patient care coordination workflow
Based on SRAO Framework with HIPAA-compliant patterns
Key agents:
- VitalSignsCapture: Processes patient vital signs
- EMRRetrieval: Retrieves electronic medical records
- TriageRecommendation: Provides triage recommendations
- ResourceAllocator: Manages hospital resource allocation
"""
from praisonaiagents import Agent, tool
from typing import Dict, List, Any, Optional
from pydantic import BaseModel
from datetime import datetime
from enum import Enum
# Triage levels following Emergency Severity Index (ESI)
class TriageLevel(str, Enum):
RESUSCITATION = "1_resuscitation" # Immediate life-saving intervention
EMERGENT = "2_emergent" # High risk, severe pain/distress
URGENT = "3_urgent" # Stable but needs multiple resources
LESS_URGENT = "4_less_urgent" # Stable, one resource needed
NON_URGENT = "5_non_urgent" # Stable, no resources needed
# I/O Schemas
class VitalSigns(BaseModel):
"""Patient vital signs data"""
patient_id: str
timestamp: str
heart_rate: int # bpm
blood_pressure_systolic: int # mmHg
blood_pressure_diastolic: int # mmHg
respiratory_rate: int # breaths/min
temperature: float # Celsius
oxygen_saturation: int # percentage
pain_scale: int # 0-10
consciousness_level: str # alert, verbal, pain, unresponsive (AVPU)
class MedicalHistory(BaseModel):
"""Patient medical history from EMR"""
patient_id: str
allergies: List[str]
chronic_conditions: List[str]
current_medications: List[Dict[str, str]]
recent_visits: List[Dict[str, Any]]
emergency_contacts: List[Dict[str, str]]
insurance_status: str
class TriageAssessment(BaseModel):
"""Triage assessment and recommendations"""
assessment_id: str
patient_id: str
triage_level: TriageLevel
chief_complaint: str
recommended_department: str
estimated_wait_time: int # minutes
required_resources: List[str]
clinical_notes: str
red_flags: List[str]
class ResourceAllocation(BaseModel):
"""Hospital resource allocation"""
allocation_id: str
patient_id: str
assigned_bed: Optional[str]
assigned_staff: List[str]
equipment_needed: List[str]
department: str
priority_score: float
estimated_treatment_time: int # minutes
# Healthcare-specific tools
@tool
def capture_vital_signs(patient_id: str) -> Dict:
"""Capture patient vital signs from monitoring devices"""
# Simulate vital signs capture
return {
"patient_id": patient_id,
"timestamp": datetime.now().isoformat(),
"heart_rate": 78,
"blood_pressure_systolic": 130,
"blood_pressure_diastolic": 85,
"respiratory_rate": 16,
"temperature": 37.2,
"oxygen_saturation": 98,
"pain_scale": 6,
"consciousness_level": "alert"
}
@tool
def retrieve_medical_history(patient_id: str, consent_verified: bool = True) -> Dict:
"""Retrieve patient medical history from EMR system"""
if not consent_verified:
return {"error": "consent_required", "message": "Patient consent required for EMR access"}
# Simulate EMR retrieval
return {
"patient_id": patient_id,
"allergies": ["penicillin", "latex"],
"chronic_conditions": ["hypertension", "diabetes_type2"],
"current_medications": [
{"name": "metformin", "dose": "500mg", "frequency": "twice daily"},
{"name": "lisinopril", "dose": "10mg", "frequency": "once daily"}
],
"recent_visits": [
{"date": "2024-02-15", "reason": "routine_checkup", "department": "primary_care"}
],
"emergency_contacts": [
{"name": "Jane Doe", "relationship": "spouse", "phone": "555-0123"}
],
"insurance_status": "active"
}
@tool
def calculate_triage_priority(vital_signs: Dict, medical_history: Dict, chief_complaint: str) -> Dict:
"""Calculate triage priority based on clinical indicators"""
# Simulate triage algorithm
priority_score = 0
red_flags = []
# Check vital signs
if vital_signs["heart_rate"] > 120 or vital_signs["heart_rate"] < 50:
priority_score += 3
red_flags.append("abnormal_heart_rate")
if vital_signs["oxygen_saturation"] < 92:
priority_score += 4
red_flags.append("low_oxygen")
if vital_signs["consciousness_level"] != "alert":
priority_score += 5
red_flags.append("altered_consciousness")
# Determine triage level
if priority_score >= 8:
triage_level = TriageLevel.RESUSCITATION
department = "emergency"
wait_time = 0
elif priority_score >= 5:
triage_level = TriageLevel.EMERGENT
department = "emergency"
wait_time = 10
elif priority_score >= 3:
triage_level = TriageLevel.URGENT
department = "urgent_care"
wait_time = 30
else:
triage_level = TriageLevel.LESS_URGENT
department = "primary_care"
wait_time = 60
return {
"assessment_id": f"TRG-{datetime.now().strftime('%Y%m%d%H%M%S')}",
"patient_id": vital_signs["patient_id"],
"triage_level": triage_level.value,
"chief_complaint": chief_complaint,
"recommended_department": department,
"estimated_wait_time": wait_time,
"required_resources": ["physician", "nurse", "monitoring"],
"clinical_notes": f"Priority score: {priority_score}",
"red_flags": red_flags
}
@tool
def allocate_resources(patient_id: str, triage_level: str, department: str) -> Dict:
"""Allocate hospital resources based on triage assessment"""
# Simulate resource allocation
if "resuscitation" in triage_level:
bed = "ER-01"
staff = ["Dr. Smith", "Nurse Johnson", "Nurse Williams"]
equipment = ["cardiac_monitor", "defibrillator", "crash_cart"]
priority = 10.0
elif "emergent" in triage_level:
bed = "ER-05"
staff = ["Dr. Brown", "Nurse Davis"]
equipment = ["vital_signs_monitor", "IV_pump"]
priority = 8.0
else:
bed = "UC-12"
staff = ["PA Miller", "Nurse Garcia"]
equipment = ["basic_monitor"]
priority = 5.0
return {
"allocation_id": f"RES-{datetime.now().strftime('%Y%m%d%H%M%S')}",
"patient_id": patient_id,
"assigned_bed": bed,
"assigned_staff": staff,
"equipment_needed": equipment,
"department": department,
"priority_score": priority,
"estimated_treatment_time": 45
}
# Healthcare agent definitions with SLA requirements
vital_signs_agent = Agent(
name="VitalSignsCapture",
instructions="""You are a clinical vital signs specialist.
Capture and interpret patient vital signs from various monitoring devices.
Identify abnormal values and trends that require immediate attention.
Follow HIPAA guidelines for patient data handling.
SLA: Capture and process within 30 seconds.""",
tools=[capture_vital_signs]
)
emr_agent = Agent(
name="EMRRetrieval",
instructions="""You are an EMR system specialist with HIPAA compliance expertise.
Retrieve relevant patient medical history while ensuring data privacy.
Verify patient consent and maintain audit trails.
Highlight relevant allergies and contraindications.
SLA: Retrieve records within 5 seconds.""",
tools=[retrieve_medical_history]
)
triage_agent = Agent(
name="TriageRecommendation",
instructions="""You are an emergency triage specialist following ESI guidelines.
Assess patient severity and provide triage recommendations.
Consider vital signs, medical history, and presenting symptoms.
Identify red flags that require immediate intervention.
SLA: Complete assessment within 1 minute.""",
tools=[calculate_triage_priority]
)
resource_agent = Agent(
name="ResourceAllocator",
instructions="""You are a hospital resource management specialist.
Allocate beds, staff, and equipment based on patient needs and priority.
Optimize resource utilization while maintaining quality of care.
Coordinate between departments for efficient patient flow.
SLA: Allocate resources within 30 seconds.""",
tools=[allocate_resources]
)
# Healthcare workflow with safety protocols
def emergency_triage_workflow(patient_id: str, chief_complaint: str):
"""
Complete emergency triage workflow from arrival to resource allocation
Includes safety checks and fallback protocols
"""
workflow_result = {
"patient_id": patient_id,
"timestamp": datetime.now().isoformat(),
"status": "in_progress",
"safety_checks": [],
"clinical_pathway": []
}
# Step 1: Vital signs capture with validation
try:
vital_signs = vital_signs_agent.start(
f"Capture vital signs for patient {patient_id}"
)
workflow_result["clinical_pathway"].append({
"step": "vital_signs",
"status": "completed",
"data": vital_signs
})
# Safety check: Validate vital signs are within possible ranges
if vital_signs.get("heart_rate", 0) < 20 or vital_signs.get("heart_rate", 0) > 300:
workflow_result["safety_checks"].append({
"type": "vital_signs_validation",
"issue": "impossible_heart_rate",
"action": "manual_verification_required"
})
except Exception as e:
# Fallback: Manual vital signs entry
workflow_result["clinical_pathway"].append({
"step": "vital_signs",
"status": "manual_entry_required",
"error": str(e)
})
vital_signs = {"manual_entry": True}
# Step 2: EMR retrieval with consent check
try:
medical_history = emr_agent.start(
f"Retrieve medical history for patient {patient_id} with verified consent"
)
workflow_result["clinical_pathway"].append({
"step": "emr_retrieval",
"status": "completed",
"records_retrieved": True
})
# Safety check: Allergy alerts
if medical_history.get("allergies"):
workflow_result["safety_checks"].append({
"type": "allergy_alert",
"allergies": medical_history["allergies"],
"action": "notify_all_providers"
})
except Exception as e:
# Fallback: Proceed with limited information
medical_history = {
"patient_id": patient_id,
"allergies": [],
"note": "EMR_unavailable_proceed_with_caution"
}
workflow_result["safety_checks"].append({
"type": "emr_unavailable",
"action": "collect_history_manually"
})
# Step 3: Triage assessment
try:
triage_assessment = triage_agent.start(
f"Assess triage for patient with vitals {vital_signs}, "
f"history {medical_history}, complaint: {chief_complaint}"
)
workflow_result["clinical_pathway"].append({
"step": "triage_assessment",
"status": "completed",
"triage_level": triage_assessment.get("triage_level")
})
# Safety check: Red flags requiring immediate action
if triage_assessment.get("red_flags"):
workflow_result["safety_checks"].append({
"type": "clinical_red_flags",
"flags": triage_assessment["red_flags"],
"action": "immediate_physician_notification"
})
except Exception as e:
# Fallback: Conservative triage (assume urgent)
triage_assessment = {
"triage_level": TriageLevel.URGENT.value,
"recommended_department": "emergency",
"fallback": True
}
# Step 4: Resource allocation
try:
resource_allocation = resource_agent.start(
f"Allocate resources for patient {patient_id} "
f"with triage {triage_assessment.get('triage_level')} "
f"to {triage_assessment.get('recommended_department')}"
)
workflow_result["clinical_pathway"].append({
"step": "resource_allocation",
"status": "completed",
"bed_assigned": resource_allocation.get("assigned_bed"),
"staff_assigned": resource_allocation.get("assigned_staff")
})
except Exception as e:
# Fallback: Queue for next available
workflow_result["clinical_pathway"].append({
"step": "resource_allocation",
"status": "queued",
"queue_position": "next_available",
"error": str(e)
})
workflow_result["status"] = "completed"
return workflow_result
# HIPAA-compliant data handling patterns
class HIPAACompliancePatterns:
"""
Reusable patterns for HIPAA-compliant healthcare workflows
"""
@staticmethod
def anonymize_patient_data(data: Dict) -> Dict:
"""Remove PHI for analytics and reporting"""
safe_fields = ["triage_level", "department", "wait_time", "resource_type"]
return {k: v for k, v in data.items() if k in safe_fields}
@staticmethod
def audit_log_access(user_id: str, patient_id: str, action: str, reason: str):
"""Create audit trail for EMR access"""
return {
"timestamp": datetime.now().isoformat(),
"user_id": user_id,
"patient_id": patient_id,
"action": action,
"reason": reason,
"ip_address": "10.0.0.1", # Would be actual IP
"session_id": "SEC-" + datetime.now().strftime('%Y%m%d%H%M%S')
}
@staticmethod
def encrypt_sensitive_data(data: Dict) -> Dict:
"""Encrypt sensitive fields (placeholder for real encryption)"""
sensitive_fields = ["ssn", "dob", "address", "phone"]
encrypted = data.copy()
for field in sensitive_fields:
if field in encrypted:
encrypted[field] = f"ENCRYPTED_{field.upper()}"
return encrypted
# Cross-department coordination patterns
class HealthcareCoordinationPatterns:
"""
Patterns for coordinating across healthcare departments
"""
@staticmethod
def coordinate_lab_orders(patient_id: str, triage_level: str) -> Agent:
"""Create agent for lab order coordination"""
return Agent(
name="LabCoordinator",
instructions=f"""Coordinate laboratory orders for patient {patient_id}.
Priority level: {triage_level}.
Ensure STAT orders for critical patients.
Track specimen collection and result delivery.
SLA: Order placement within 2 minutes."""
)
@staticmethod
def coordinate_radiology(patient_id: str, imaging_type: str) -> Agent:
"""Create agent for radiology coordination"""
return Agent(
name="RadiologyCoordinator",
instructions=f"""Schedule {imaging_type} imaging for patient {patient_id}.
Check for contrast allergies and pregnancy status.
Coordinate with transport for patient movement.
SLA: Schedule within 5 minutes for urgent cases."""
)
@staticmethod
def coordinate_pharmacy(patient_id: str, medications: List[str]) -> Agent:
"""Create agent for pharmacy coordination"""
return Agent(
name="PharmacyCoordinator",
instructions=f"""Verify and dispense medications for patient {patient_id}.
Check for drug interactions and allergies.
Ensure proper dosing based on patient parameters.
SLA: Medication verification within 3 minutes."""
)
# Example usage
if __name__ == "__main__":
# Process emergency patient
patient_id = "PT-2024-00123"
chief_complaint = "severe chest pain radiating to left arm"
result = emergency_triage_workflow(patient_id, chief_complaint)
print("Triage workflow result:", result)
# Create specialized coordinators
lab_coordinator = HealthcareCoordinationPatterns.coordinate_lab_orders(
patient_id, TriageLevel.EMERGENT.value
)
radiology_coordinator = HealthcareCoordinationPatterns.coordinate_radiology(
patient_id, "chest_xray"
)
pharmacy_coordinator = HealthcareCoordinationPatterns.coordinate_pharmacy(
patient_id, ["aspirin", "nitroglycerin"]
)
# HIPAA compliance example
audit_log = HIPAACompliancePatterns.audit_log_access(
"DR-001", patient_id, "EMR_ACCESS", "emergency_triage"
)
print("Audit log created:", audit_log)
@@ -1,298 +0,0 @@
"""
Manufacturing Industry Template
================================
Order scheduling, inventory management, and quality inspection workflow
Based on SRAO Framework patterns with 70% cross-industry reuse
Key agents:
- ParseOrder: Extracts order details from various formats
- CheckInventory: Validates material availability
- OptimizeSchedule: Optimizes production scheduling
- DefectDetect: Quality control and defect detection
"""
from praisonaiagents import Agent, tool
from typing import Dict, List, Any
from pydantic import BaseModel
# I/O Schemas
class OrderDetails(BaseModel):
"""Structured order information"""
order_id: str
customer_id: str
product_id: str
quantity: int
priority: str = "normal" # normal, high, urgent
due_date: str
requirements: Dict[str, Any] = {}
class InventoryStatus(BaseModel):
"""Material availability status"""
material_id: str
available_quantity: int
reorder_level: int
supplier_lead_time: int
location: str
class ProductionSchedule(BaseModel):
"""Optimized production schedule"""
schedule_id: str
production_line: str
start_time: str
end_time: str
assigned_workers: List[str]
estimated_completion: str
bottleneck_analysis: Dict[str, Any] = {}
class QualityReport(BaseModel):
"""Quality inspection results"""
batch_id: str
inspection_time: str
defect_rate: float
defect_types: List[str]
passed: bool
recommendations: List[str]
# Tools for agents
@tool
def extract_order_details(text: str) -> Dict:
"""Extract structured order information from unstructured text"""
# Simulate order parsing logic
return {
"order_id": "ORD-2024-001",
"customer_id": "CUST-123",
"product_id": "PROD-456",
"quantity": 100,
"priority": "high",
"due_date": "2024-03-15",
"requirements": {"material": "steel", "finish": "polished"}
}
@tool
def check_material_availability(product_id: str, quantity: int) -> Dict:
"""Check if materials are available for production"""
# Simulate inventory check
return {
"material_id": "MAT-789",
"available_quantity": 500,
"reorder_level": 100,
"supplier_lead_time": 7,
"location": "Warehouse-A"
}
@tool
def calculate_optimal_schedule(order: Dict, inventory: Dict) -> Dict:
"""Calculate optimal production schedule based on constraints"""
# Simulate scheduling optimization
return {
"schedule_id": "SCH-2024-001",
"production_line": "Line-3",
"start_time": "2024-03-10T08:00:00",
"end_time": "2024-03-14T17:00:00",
"assigned_workers": ["Worker-001", "Worker-002"],
"estimated_completion": "2024-03-14T16:30:00",
"bottleneck_analysis": {
"critical_path": "Assembly",
"buffer_time": 2.5
}
}
@tool
def perform_quality_inspection(batch_id: str) -> Dict:
"""Perform automated quality inspection on production batch"""
# Simulate quality control
return {
"batch_id": batch_id,
"inspection_time": "2024-03-14T17:00:00",
"defect_rate": 0.02,
"defect_types": ["surface_scratch", "dimension_variance"],
"passed": True,
"recommendations": [
"Adjust machine calibration on Line-3",
"Increase inspection frequency for next batch"
]
}
# Agent Definitions with SLA requirements
order_parser = Agent(
name="ParseOrder",
instructions="""You are an order parsing specialist. Extract and structure order information
from various formats (email, PDF, API). Ensure all required fields are captured and validated.
SLA: Process within 30 seconds per order.""",
tools=[extract_order_details]
)
inventory_checker = Agent(
name="CheckInventory",
instructions="""You are an inventory management specialist. Verify material availability,
check reorder points, and identify potential supply chain issues.
SLA: Real-time response within 5 seconds.""",
tools=[check_material_availability]
)
schedule_optimizer = Agent(
name="OptimizeSchedule",
instructions="""You are a production scheduling expert. Optimize production schedules
based on order priority, resource availability, and constraints. Minimize idle time
and maximize throughput.
SLA: Generate schedule within 2 minutes for complex orders.""",
tools=[calculate_optimal_schedule]
)
quality_inspector = Agent(
name="DefectDetect",
instructions="""You are a quality control specialist. Perform automated inspections,
detect defects using vision analysis, and provide improvement recommendations.
SLA: Complete inspection within 1 minute per batch.""",
tools=[perform_quality_inspection]
)
# Workflow with fallback strategies
def manufacturing_workflow(order_text: str):
"""
Complete manufacturing workflow from order to quality control
Includes fallback strategies for each critical step
"""
# Step 1: Parse order with fallback
try:
order_details = order_parser.start(f"Parse this order: {order_text}")
if not order_details:
# Fallback: Manual review queue
return {"status": "manual_review_required", "reason": "order_parsing_failed"}
except Exception as e:
return {"status": "error", "stage": "order_parsing", "error": str(e)}
# Step 2: Check inventory with fallback
try:
inventory_status = inventory_checker.start(
f"Check materials for order: {order_details}"
)
if not inventory_status:
# Fallback: Alternative supplier check
return {"status": "alternative_supplier_needed", "order": order_details}
except Exception as e:
# Fallback: Conservative estimate with safety margin
inventory_status = {"estimated": True, "safety_margin": 1.5}
# Step 3: Optimize schedule with fallback
try:
schedule = schedule_optimizer.start(
f"Create schedule for order {order_details} with inventory {inventory_status}"
)
if not schedule:
# Fallback: Standard scheduling template
schedule = {"template": "standard", "priority": "normal"}
except Exception as e:
# Fallback: Queue for next available slot
schedule = {"status": "queued", "estimated_start": "next_available"}
# Step 4: Quality inspection with fallback
try:
quality_report = quality_inspector.start(
f"Inspect batch for schedule {schedule}"
)
if not quality_report:
# Fallback: Manual inspection required
quality_report = {"requires_manual": True, "inspector_assigned": "QC-Team-1"}
except Exception as e:
# Fallback: Quarantine for review
quality_report = {"status": "quarantined", "review_required": True}
return {
"status": "completed",
"order": order_details,
"inventory": inventory_status,
"schedule": schedule,
"quality": quality_report
}
# Cross-industry reusable patterns (70% reuse)
class IndustryAgentPattern:
"""
Base pattern reusable across industries
Provides common agent capabilities that can be specialized
"""
@staticmethod
def create_data_parser(name: str, domain: str, sla_seconds: int = 30):
"""Create a data parsing agent for any domain"""
return Agent(
name=name,
instructions=f"""You are a {domain} data parsing specialist.
Extract and structure information from various formats.
Validate all required fields according to {domain} standards.
SLA: Process within {sla_seconds} seconds."""
)
@staticmethod
def create_resource_checker(name: str, resource_type: str, sla_seconds: int = 5):
"""Create a resource availability checker for any resource type"""
return Agent(
name=name,
instructions=f"""You are a {resource_type} availability specialist.
Verify {resource_type} availability and identify constraints.
Provide real-time status and alternative options if needed.
SLA: Response within {sla_seconds} seconds."""
)
@staticmethod
def create_optimizer(name: str, optimization_target: str, sla_minutes: int = 2):
"""Create an optimization agent for any target metric"""
return Agent(
name=name,
instructions=f"""You are an optimization expert for {optimization_target}.
Find optimal solutions considering all constraints and priorities.
Minimize waste and maximize efficiency.
SLA: Generate solution within {sla_minutes} minutes."""
)
@staticmethod
def create_inspector(name: str, inspection_type: str, sla_minutes: int = 1):
"""Create an inspection agent for any quality metric"""
return Agent(
name=name,
instructions=f"""You are a {inspection_type} inspection specialist.
Perform automated analysis and detect anomalies.
Provide actionable recommendations for improvement.
SLA: Complete inspection within {sla_minutes} minute(s)."""
)
# Example usage
if __name__ == "__main__":
# Create a manufacturing workflow instance
order = "Customer ABC needs 100 units of Product-XYZ by March 15th, high priority"
# Option 1: Use specialized agents
result = manufacturing_workflow(order)
print("Manufacturing workflow result:", result)
# Option 2: Use reusable patterns for other industries
# These patterns can be adapted for Energy, Healthcare, Agriculture, Transportation
energy_parser = IndustryAgentPattern.create_data_parser(
"EnergyDataParser", "wind farm telemetry", sla_seconds=10
)
healthcare_checker = IndustryAgentPattern.create_resource_checker(
"BedAvailability", "hospital bed", sla_seconds=3
)
agriculture_optimizer = IndustryAgentPattern.create_optimizer(
"IrrigationOptimizer", "water usage", sla_minutes=5
)
transport_inspector = IndustryAgentPattern.create_inspector(
"TunnelSafety", "structural integrity", sla_minutes=2
)
@@ -1,600 +0,0 @@
# praisonai: skip=true
"""
Transportation Industry Template
================================
Tunnel safety monitoring and infrastructure management workflow
Based on SRAO Framework with LiDAR and sensor fusion
Key agents:
- LiDARFusion: Processes LiDAR point cloud data
- DisplacementCalculator: Calculates structural displacement
- HeatmapGenerator: Generates safety heatmaps
- MaintenancePlanner: Plans infrastructure maintenance
"""
from praisonaiagents import Agent, tool
from typing import Dict, List, Any, Tuple, Optional
from pydantic import BaseModel
from datetime import datetime, timedelta
from enum import Enum
import math
# Safety levels for infrastructure
class SafetyLevel(str, Enum):
SAFE = "safe"
CAUTION = "caution"
WARNING = "warning"
DANGER = "danger"
CRITICAL = "critical"
# Infrastructure types
class InfrastructureType(str, Enum):
TUNNEL = "tunnel"
BRIDGE = "bridge"
HIGHWAY = "highway"
RAILWAY = "railway"
AIRPORT = "airport"
# I/O Schemas
class LiDARScan(BaseModel):
"""LiDAR scan data for infrastructure"""
scan_id: str
infrastructure_id: str
scan_time: str
point_cloud_size: int # Number of points
scan_resolution: float # Points per square meter
coverage_area: float # Square meters
anomaly_points: List[Tuple[float, float, float]] # XYZ coordinates
reference_baseline: Optional[Dict[str, Any]]
class DisplacementAnalysis(BaseModel):
"""Structural displacement analysis"""
analysis_id: str
infrastructure_id: str
analysis_time: str
max_displacement: float # millimeters
displacement_vector: Tuple[float, float, float] # XYZ displacement
critical_zones: List[Dict[str, Any]]
settlement_rate: float # mm/month
tilt_angle: float # degrees
safety_factor: float
class SafetyHeatmap(BaseModel):
"""Infrastructure safety heatmap"""
heatmap_id: str
infrastructure_id: str
generation_time: str
grid_resolution: float # meters
safety_scores: List[List[float]] # 2D grid of safety scores
critical_areas: List[Dict[str, Any]]
overall_safety: SafetyLevel
risk_trends: Dict[str, Any]
class MaintenanceSchedule(BaseModel):
"""Maintenance planning schedule"""
schedule_id: str
infrastructure_id: str
maintenance_type: str # preventive, corrective, emergency
priority_level: str # low, medium, high, critical
scheduled_date: str
estimated_duration: int # hours
required_resources: List[str]
traffic_impact: str
cost_estimate: float
# Transportation-specific tools
@tool
def process_lidar_scan(infrastructure_id: str, scan_type: str = "full") -> Dict:
"""Process LiDAR point cloud data for structural analysis"""
# Simulate LiDAR processing
return {
"scan_id": f"LIDAR-{datetime.now().strftime('%Y%m%d%H%M')}",
"infrastructure_id": infrastructure_id,
"scan_time": datetime.now().isoformat(),
"point_cloud_size": 5000000, # 5 million points
"scan_resolution": 100.0, # points/m²
"coverage_area": 50000.0, # m²
"anomaly_points": [
(10.5, 20.3, 5.1),
(15.2, 25.8, 5.3),
(20.1, 30.5, 5.5)
],
"reference_baseline": {
"date": "2024-01-01",
"baseline_id": "BSL-001"
}
}
@tool
def calculate_displacement(current_scan: Dict, baseline_scan: Dict) -> Dict:
"""Calculate structural displacement from LiDAR scans"""
# Simulate displacement calculation
anomalies = current_scan.get("anomaly_points", [])
if len(anomalies) > 5:
max_displacement = 15.0
safety_factor = 0.6
safety_level = SafetyLevel.WARNING
elif len(anomalies) > 2:
max_displacement = 8.0
safety_factor = 0.8
safety_level = SafetyLevel.CAUTION
else:
max_displacement = 3.0
safety_factor = 0.95
safety_level = SafetyLevel.SAFE
return {
"analysis_id": f"DISP-{datetime.now().strftime('%Y%m%d%H%M')}",
"infrastructure_id": current_scan["infrastructure_id"],
"analysis_time": datetime.now().isoformat(),
"max_displacement": max_displacement,
"displacement_vector": (2.5, 1.8, max_displacement),
"critical_zones": [
{
"zone_id": "CZ-001",
"location": "tunnel_crown",
"displacement": max_displacement * 0.8,
"risk": "high" if max_displacement > 10 else "medium"
}
],
"settlement_rate": max_displacement / 30, # mm/month
"tilt_angle": math.degrees(math.atan(max_displacement / 1000)),
"safety_factor": safety_factor
}
@tool
def generate_safety_heatmap(displacement_data: Dict, sensor_data: List[Dict]) -> Dict:
"""Generate safety heatmap visualization for infrastructure"""
# Simulate heatmap generation
safety_factor = displacement_data.get("safety_factor", 1.0)
# Create grid (simplified 10x10)
grid_size = 10
safety_grid = []
critical_areas = []
for i in range(grid_size):
row = []
for j in range(grid_size):
# Generate safety score based on position and displacement
base_score = safety_factor
distance_factor = math.sqrt((i-5)**2 + (j-5)**2) / 10
safety_score = min(1.0, base_score + (0.2 * distance_factor))
row.append(safety_score)
if safety_score < 0.7:
critical_areas.append({
"grid_position": (i, j),
"safety_score": safety_score,
"recommended_action": "immediate_inspection"
})
safety_grid.append(row)
# Determine overall safety
avg_safety = sum(sum(row) for row in safety_grid) / (grid_size * grid_size)
if avg_safety > 0.9:
overall = SafetyLevel.SAFE
elif avg_safety > 0.8:
overall = SafetyLevel.CAUTION
elif avg_safety > 0.7:
overall = SafetyLevel.WARNING
else:
overall = SafetyLevel.DANGER
return {
"heatmap_id": f"HEAT-{datetime.now().strftime('%Y%m%d%H%M')}",
"infrastructure_id": displacement_data["infrastructure_id"],
"generation_time": datetime.now().isoformat(),
"grid_resolution": 5.0, # meters
"safety_scores": safety_grid,
"critical_areas": critical_areas,
"overall_safety": overall.value,
"risk_trends": {
"trend": "deteriorating" if avg_safety < 0.8 else "stable",
"rate": -0.02 if avg_safety < 0.8 else 0.0
}
}
@tool
def plan_maintenance(infrastructure_id: str, safety_analysis: Dict, traffic_data: Dict) -> Dict:
"""Plan maintenance based on safety analysis and traffic patterns"""
safety_level = safety_analysis.get("overall_safety", "safe")
# Determine maintenance urgency
if safety_level in ["danger", "critical"]:
maintenance_type = "emergency"
priority = "critical"
days_until = 1
duration = 48
elif safety_level == "warning":
maintenance_type = "corrective"
priority = "high"
days_until = 7
duration = 24
elif safety_level == "caution":
maintenance_type = "preventive"
priority = "medium"
days_until = 30
duration = 12
else:
maintenance_type = "preventive"
priority = "low"
days_until = 90
duration = 8
# Traffic impact assessment
peak_traffic = traffic_data.get("peak_volume", 1000)
if peak_traffic > 5000:
traffic_impact = "severe"
cost_multiplier = 2.0
elif peak_traffic > 2000:
traffic_impact = "moderate"
cost_multiplier = 1.5
else:
traffic_impact = "minimal"
cost_multiplier = 1.0
return {
"schedule_id": f"MAINT-{datetime.now().strftime('%Y%m%d%H%M')}",
"infrastructure_id": infrastructure_id,
"maintenance_type": maintenance_type,
"priority_level": priority,
"scheduled_date": (datetime.now() + timedelta(days=days_until)).isoformat(),
"estimated_duration": duration,
"required_resources": [
"inspection_team",
"repair_crew",
"safety_equipment",
"traffic_control"
],
"traffic_impact": traffic_impact,
"cost_estimate": 50000 * cost_multiplier * (duration / 24)
}
# Transportation agent definitions
lidar_agent = Agent(
name="LiDARFusion",
instructions="""You are a LiDAR data processing specialist for infrastructure.
Process point cloud data from mobile and terrestrial LiDAR scanners.
Perform data fusion from multiple sensor sources.
Identify structural anomalies and deformations.
SLA: Process scan data within 5 minutes.""",
tools=[process_lidar_scan]
)
displacement_agent = Agent(
name="DisplacementCalculator",
instructions="""You are a structural displacement analysis expert.
Calculate precise displacement measurements from temporal scans.
Analyze settlement patterns and structural movements.
Predict future displacement trends using ML models.
SLA: Complete analysis within 2 minutes.""",
tools=[calculate_displacement]
)
heatmap_agent = Agent(
name="HeatmapGenerator",
instructions="""You are a safety visualization specialist.
Generate intuitive safety heatmaps for infrastructure monitoring.
Integrate multiple data sources for comprehensive risk assessment.
Highlight critical areas requiring immediate attention.
SLA: Generate heatmap within 1 minute.""",
tools=[generate_safety_heatmap]
)
maintenance_agent = Agent(
name="MaintenancePlanner",
instructions="""You are an infrastructure maintenance planning expert.
Schedule maintenance based on structural health and traffic patterns.
Optimize maintenance windows to minimize disruption.
Coordinate resources and estimate costs.
SLA: Create maintenance plan within 3 minutes.""",
tools=[plan_maintenance]
)
# Transportation infrastructure monitoring workflow
def infrastructure_monitoring_workflow(
infrastructure_ids: List[str],
infrastructure_type: InfrastructureType,
traffic_data: Dict
):
"""
Complete infrastructure monitoring workflow from scanning to maintenance
Includes safety assessment and predictive maintenance
"""
monitoring_results = {
"timestamp": datetime.now().isoformat(),
"infrastructure_type": infrastructure_type.value,
"structures_monitored": len(infrastructure_ids),
"safety_assessments": [],
"maintenance_required": [],
"emergency_alerts": [],
"network_health_score": 0.0
}
total_safety_score = 0.0
for infra_id in infrastructure_ids:
try:
# Step 1: LiDAR scanning
lidar_scan = lidar_agent.start(
f"Process LiDAR scan for {infrastructure_type.value} {infra_id}"
)
# Step 2: Displacement analysis
# Get baseline (would be from database in real scenario)
baseline = {"scan_id": "BSL-001", "point_cloud": []}
displacement_analysis = displacement_agent.start(
f"Calculate displacement for scan: {lidar_scan} against baseline: {baseline}"
)
# Step 3: Generate safety heatmap
sensor_data = [] # Would include IoT sensor readings
safety_heatmap = heatmap_agent.start(
f"Generate heatmap for displacement: {displacement_analysis} "
f"with sensors: {sensor_data}"
)
monitoring_results["safety_assessments"].append({
"infrastructure_id": infra_id,
"safety_level": safety_heatmap.get("overall_safety"),
"max_displacement": displacement_analysis.get("max_displacement"),
"critical_zones": len(safety_heatmap.get("critical_areas", []))
})
# Check for emergency conditions
if safety_heatmap.get("overall_safety") in ["danger", "critical"]:
monitoring_results["emergency_alerts"].append({
"infrastructure_id": infra_id,
"alert_level": "emergency",
"safety_status": safety_heatmap["overall_safety"],
"immediate_action": "close_to_traffic",
"notification_sent": True
})
# Step 4: Emergency maintenance planning
maintenance_plan = maintenance_agent.start(
f"Plan emergency maintenance for {infra_id} "
f"with safety: {safety_heatmap} and traffic: {traffic_data}"
)
monitoring_results["maintenance_required"].append(maintenance_plan)
elif safety_heatmap.get("overall_safety") in ["warning", "caution"]:
# Regular maintenance planning
maintenance_plan = maintenance_agent.start(
f"Plan maintenance for {infra_id} "
f"with safety: {safety_heatmap} and traffic: {traffic_data}"
)
monitoring_results["maintenance_required"].append(maintenance_plan)
# Calculate safety score contribution
safety_mapping = {
"safe": 1.0, "caution": 0.8, "warning": 0.6,
"danger": 0.3, "critical": 0.1
}
total_safety_score += safety_mapping.get(
safety_heatmap.get("overall_safety", "safe"), 0.5
)
except Exception as e:
# Fallback: Manual inspection
monitoring_results["emergency_alerts"].append({
"infrastructure_id": infra_id,
"alert_level": "system_failure",
"error": str(e),
"action": "dispatch_manual_inspection_team"
})
# Calculate network health score
if infrastructure_ids:
monitoring_results["network_health_score"] = (
total_safety_score / len(infrastructure_ids) * 100
)
return monitoring_results
# Multi-modal transportation patterns
class MultiModalTransportPatterns:
"""
Patterns for different transportation infrastructure types
Demonstrates cross-industry reuse for transportation sector
"""
@staticmethod
def adapt_for_bridge_monitoring() -> Agent:
"""Adapt tunnel monitoring for bridge structures"""
return Agent(
name="BridgeMonitor",
instructions="""Monitor bridge structural health using sensors.
Track deck deflection, cable tension, and vibration patterns.
Detect fatigue cracks and corrosion.
Consider wind and seismic loads.
SLA: Real-time monitoring with 10-second updates."""
)
@staticmethod
def adapt_for_railway_tracks() -> Agent:
"""Adapt for railway track monitoring"""
return Agent(
name="RailwayMonitor",
instructions="""Monitor railway track geometry and condition.
Detect rail defects, gauge variations, and ballast degradation.
Analyze wheel-rail interaction forces.
Predict track maintenance needs.
SLA: Process track inspection data within 3 minutes per km."""
)
@staticmethod
def adapt_for_airport_runways() -> Agent:
"""Adapt for airport runway monitoring"""
return Agent(
name="RunwayMonitor",
instructions="""Monitor airport runway surface conditions.
Detect FOD (Foreign Object Debris) and surface irregularities.
Assess pavement condition and friction levels.
Monitor drainage and lighting systems.
SLA: Complete runway scan within 10 minutes."""
)
# Intelligent traffic management integration
class TrafficManagementPatterns:
"""
Patterns for integrating with intelligent traffic systems
"""
@staticmethod
def optimize_traffic_flow(maintenance_window: Dict, traffic_patterns: Dict) -> Dict:
"""Optimize traffic flow during maintenance"""
peak_hours = traffic_patterns.get("peak_hours", [7, 9, 17, 19])
maintenance_start = maintenance_window.get("start_time", "02:00")
# Calculate optimal diversion routes
return {
"strategy": "dynamic_routing",
"diversion_routes": [
{"route_id": "ALT-1", "capacity": 0.6, "added_time": 15},
{"route_id": "ALT-2", "capacity": 0.3, "added_time": 20}
],
"lane_management": {
"reversible_lanes": True,
"peak_direction": "inbound" if int(maintenance_start[:2]) < 12 else "outbound"
},
"public_transport": {
"increase_frequency": True,
"additional_services": 4
},
"estimated_delay": 10 # minutes
}
@staticmethod
def incident_response_plan(incident_type: str, location: Dict) -> Dict:
"""Generate incident response plan"""
response_times = {
"accident": 5,
"breakdown": 10,
"infrastructure_failure": 2,
"weather_hazard": 15
}
return {
"incident_id": f"INC-{datetime.now().strftime('%Y%m%d%H%M')}",
"response_time": response_times.get(incident_type, 10),
"resources_dispatched": [
r for r in [
"emergency_response_team",
"traffic_control_unit",
"maintenance_crew" if "infrastructure" in incident_type else None
] if r is not None
],
"traffic_management": {
"lane_closures": 2,
"speed_reduction": 30, # km/h
"message_signs": ["Incident ahead", "Reduce speed", "Merge left"]
},
"estimated_clearance": 45 # minutes
}
# Predictive maintenance patterns
class PredictiveMaintenancePatterns:
"""
ML-based predictive maintenance for transportation infrastructure
"""
@staticmethod
def predict_failure_probability(
displacement_trend: List[float],
environmental_factors: Dict
) -> float:
"""Predict probability of structural failure"""
# Simplified prediction model
trend_slope = (displacement_trend[-1] - displacement_trend[0]) / len(displacement_trend)
temperature_factor = abs(environmental_factors.get("temp_variation", 0)) / 50
moisture_factor = environmental_factors.get("humidity", 50) / 100
base_probability = 0.1
trend_contribution = max(0, trend_slope * 10)
env_contribution = (temperature_factor + moisture_factor) * 0.2
return min(1.0, base_probability + trend_contribution + env_contribution)
@staticmethod
def optimize_maintenance_schedule(
infrastructure_conditions: List[Dict],
budget_constraint: float
) -> List[Dict]:
"""Optimize maintenance schedule across infrastructure network"""
# Sort by urgency (safety_factor * cost_efficiency)
prioritized = sorted(
infrastructure_conditions,
key=lambda x: (1 - x.get("safety_factor", 1)) * (1 / x.get("cost", 1)),
reverse=True
)
scheduled = []
total_cost = 0
for infra in prioritized:
if total_cost + infra.get("cost", 0) <= budget_constraint:
scheduled.append({
"infrastructure_id": infra["id"],
"scheduled_date": infra["recommended_date"],
"priority": "high" if infra["safety_factor"] < 0.7 else "medium"
})
total_cost += infra.get("cost", 0)
return scheduled
# Example usage
if __name__ == "__main__":
# Monitor tunnel network
tunnel_ids = [f"TUN-{i:03d}" for i in range(1, 6)]
traffic = {
"peak_volume": 3000,
"off_peak_volume": 800,
"peak_hours": [7, 9, 17, 19]
}
result = infrastructure_monitoring_workflow(
tunnel_ids,
InfrastructureType.TUNNEL,
traffic
)
print("Infrastructure monitoring result:", result)
# Multi-modal adaptation examples
bridge_monitor = MultiModalTransportPatterns.adapt_for_bridge_monitoring()
railway_monitor = MultiModalTransportPatterns.adapt_for_railway_tracks()
runway_monitor = MultiModalTransportPatterns.adapt_for_airport_runways()
# Traffic management example
maintenance = {"start_time": "22:00", "duration": 8}
traffic_plan = TrafficManagementPatterns.optimize_traffic_flow(maintenance, traffic)
print("Traffic optimization plan:", traffic_plan)
# Predictive maintenance example
displacement_history = [2.0, 2.3, 2.8, 3.5, 4.3] # mm over months
environment = {"temp_variation": 30, "humidity": 75}
failure_prob = PredictiveMaintenancePatterns.predict_failure_probability(
displacement_history, environment
)
print(f"Failure probability: {failure_prob:.2%}")
+1 -4
View File
@@ -1,4 +1,3 @@
# praisonai: skip=true
#!/usr/bin/env python3
"""
CI Integration Example - Using Doctor in CI/CD pipelines
@@ -20,9 +19,7 @@ def run_doctor_ci():
[sys.executable, "-m", "praisonai", "doctor", "ci"],
capture_output=True,
text=True,
encoding="utf-8",
errors="replace",
timeout=120,
timeout=120
)
# Parse JSON output
@@ -1,4 +1,3 @@
# praisonai: skip=true
"""
Agent-centric Embedding Example
-1
View File
@@ -1,4 +1,3 @@
# praisonai: skip=true
#!/usr/bin/env python3
"""
PraisonAI Endpoints Example
@@ -36,12 +36,6 @@ if __name__ == "__main__":
print(f"Custom agent max_rpm: {agent.max_rpm}")
print(f"Custom agent max_execution_time: {agent.max_execution_time}")
print(f"Custom agent max_retry_limit: {agent.max_retry_limit}")
# max_rpm auto-creates a live RateLimiter (not just a stored number)
assert agent_rate_limited.max_rpm == 10
assert agent_rate_limited._rate_limiter is not None
assert agent_rate_limited._rate_limiter.requests_per_minute == 10
print(f"Rate-limited agent limiter: {agent_rate_limited._rate_limiter}")
# Test custom agent
print("\n--- Custom Execution ---")
-1
View File
@@ -1,4 +1,3 @@
# praisonai: skip=true
#!/usr/bin/env python3
"""
Fixed example demonstrating proper guardrail usage with PraisonAI Agents.
+6 -13
View File
@@ -149,28 +149,21 @@ def main():
print(f"\nOriginal document length: {len(content)} characters")
chunks = [{"text": content, "metadata": {"source": doc_path}}]
target_tokens = 2000
# Compress with different ratios
for ratio in [0.3, 0.5, 0.7]:
compressor = ContextCompressor(verbose=False)
result = compressor.compress(
chunks,
query="security verification code",
target_tokens=target_tokens,
compression_ratio=ratio,
compressor = ContextCompressor(
max_tokens=2000,
target_ratio=ratio,
)
result = compressor.compress([content], query="security verification code")
print(f"\nCompression ratio {ratio}:")
print(f" Original tokens: {result.original_tokens}")
print(f" Compressed tokens: {result.compressed_tokens}")
print(f" Actual ratio: {result.compression_ratio:.2f}")
print(f" Actual ratio: {result.compressed_tokens / max(result.original_tokens, 1):.2f}")
# Check if secret code is preserved
compressed_text = " ".join(
c.get("text", "") for c in result.chunks
) if result.chunks else ""
compressed_text = " ".join(result.chunks) if result.chunks else ""
if SECRET_CODE in compressed_text:
print(f" ✅ Secret code preserved in compressed output")
else:
@@ -80,7 +80,7 @@ Be precise and quote exact values when asked about codes or numbers.""",
print(f"\nAnswer: {response}\n")
# Verify the answer contains the unique code
if "ZEBRA-71" in str(response or "").upper():
if "ZEBRA-71" in response.upper():
print("✅ VERIFIED: Agent correctly retrieved the unique code from context!\n")
else:
print("❌ WARNING: Agent did not find the code - check retrieval\n")
@@ -104,7 +104,7 @@ Be precise and quote exact values when asked about codes or numbers.""",
response = agent.chat("What is the security incident code?")
print(f"\nAnswer: {response}\n")
if "HAWK-88" in str(response or "").upper():
if "HAWK-88" in response.upper():
print("✅ VERIFIED: Agent correctly retrieved the security code!\n")
else:
print("❌ WARNING: Agent did not find the code - check retrieval\n")
@@ -65,6 +65,7 @@ def main():
name="Policy_Expert",
instructions="You are a policy expert.",
knowledge=[temp_dir],
agent_id="policy_agent_v1", # Knowledge scoped to this agent
)
response = shared_agent.chat("What are the expense report rules?")
@@ -80,6 +81,7 @@ def main():
instructions="You are a personal HR assistant.",
knowledge=[temp_dir],
memory={"user_id": "user_bob"},
agent_id="hr_bot_v2",
)
response = combined_agent.chat("What training is required?")
@@ -1,4 +1,3 @@
# praisonai: skip=true
#!/usr/bin/env python3
"""
ManagedAgent + ClickHouse Persistence — Real conversation with session resume.
@@ -1,4 +1,3 @@
# praisonai: skip=true
#!/usr/bin/env python3
"""
ManagedAgent + MongoDB Persistence — Real conversation with session resume.
@@ -1,4 +1,3 @@
# praisonai: skip=true
#!/usr/bin/env python3
"""
ManagedAgent + MySQL Persistence — Real conversation with session resume.
@@ -1,4 +1,3 @@
# praisonai: skip=true
#!/usr/bin/env python3
"""
ManagedAgent + PostgreSQL Persistence — Real conversation with session resume.
@@ -1,4 +1,3 @@
# praisonai: skip=true
#!/usr/bin/env python3
"""
ManagedAgent + Redis Persistence — Real conversation with session resume.
@@ -1,4 +1,3 @@
# praisonai: skip=true
#!/usr/bin/env python3
"""
ManagedAgent + SQLite Persistence — Real conversation with session resume.
@@ -1,4 +1,3 @@
# praisonai: skip=true
#!/usr/bin/env python3
"""
Custom Tools MCP Server Example
@@ -1,4 +1,3 @@
# praisonai: skip=true
#!/usr/bin/env python3
"""
HTTP Stream MCP Server Example
@@ -1,4 +1,3 @@
# praisonai: skip=true
#!/usr/bin/env python3
"""
MCP Client Example
@@ -1,4 +1,3 @@
# praisonai: skip=true
"""Multi-Agent Shared Session Demo"""
from praisonaiagents import Agent
from praisonai.persistence import create_conversation_store
@@ -1,4 +1,3 @@
# praisonai: skip=true
"""
Langfuse Integration Example (Updated for TraceSinkProtocol)
@@ -1,4 +1,3 @@
# praisonai: skip=true
"""MLflow Local Observability Demo (no API key needed)"""
import mlflow
import time
+3 -13
View File
@@ -19,16 +19,6 @@ from praisonaiagents import Agent, AgentTeam
# Initialize observability
obs.init()
def set_span_attr(span, key, value):
"""Set span attribute safely across observability implementations."""
if hasattr(span, "set_attribute"):
span.set_attribute(key, value)
return
attrs = getattr(span, "attributes", None)
if attrs is not None:
attrs[key] = value
# Create agents
researcher = Agent(
name="Researcher",
@@ -47,13 +37,13 @@ with obs.trace("content-creation", metadata={"workflow": "research-write"}):
# Research phase
with obs.span("research-phase", kind=SpanKind.AGENT) as research_span:
set_span_attr(research_span, "agent", "Researcher")
research_span.attributes["agent"] = "Researcher"
research_result = researcher.chat("Research the benefits of AI in healthcare")
# Writing phase
with obs.span("writing-phase", kind=SpanKind.AGENT) as write_span:
set_span_attr(write_span, "agent", "Writer")
set_span_attr(write_span, "input_length", len(str(research_result)))
write_span.attributes["agent"] = "Writer"
write_span.attributes["input_length"] = len(str(research_result))
final_content = writer.chat(f"Write a blog post based on: {research_result}")
print("Final Content:")
@@ -1,4 +1,3 @@
# praisonai: skip=true
"""
ClickHouse — Persistence Example
+5 -9
View File
@@ -1,4 +1,3 @@
# praisonai: skip=true
"""
Minimal Agent with Database Persistence
@@ -14,8 +13,7 @@ Expected output:
- Session can be resumed later with same session_id
"""
from praisonaiagents import Agent
from praisonaiagents.db import db
from praisonaiagents import Agent, db
# Create database connection (PostgreSQL + Redis)
my_db = db(
@@ -27,12 +25,10 @@ my_db = db(
agent = Agent(
name="Assistant",
instructions="You are a helpful assistant. Be concise.",
memory={
"db": my_db,
# session_id is optional - defaults to per-hour ID (YYYYMMDDHH-hash)
# Set explicitly for session continuity across runs:
"session_id": "my-persistent-session",
},
db=my_db,
# session_id is optional - defaults to per-hour ID (YYYYMMDDHH-hash)
# Set explicitly for session continuity across runs:
session_id="my-persistent-session"
)
# Chat - messages are automatically persisted
@@ -1,4 +1,3 @@
# praisonai: skip=true
"""
MongoDB StateStore — Full Persistence Example
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