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praisonai-triage-agent[bot]andMervin Praison 7e1ca6b1fa fix: resolve gbr-mcp path to absolute + document GBR_MCP_JS override
Fixes Greptile P1: relative gbr-mcp.js arg resolved from the caller CWD,
causing Node to fail to locate the entrypoint. Now uses os.path.abspath with
a GBR_MCP_JS env override, documented in README.

Co-authored-by: Mervin Praison <[email protected]>
2026-08-23 20:09:40 +00:00
1930 changed files with 18099 additions and 326800 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>
<!-- /wp:table -->
<!-- wp:separator -->
<hr class="wp-block-separator has-alpha-channel-opacity"/>
<!-- /wp:separator -->
<!-- wp:heading -->
<h2 class="wp-block-heading">Section 1 — What wrapper adds (not in Tier-2 alone)</h2>
<!-- /wp:heading -->
<!-- wp:table -->
<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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<!-- wp:heading -->
<h2 class="wp-block-heading">Section 2 — Terminal hot path (via code tier)</h2>
<!-- /wp:heading -->
<!-- 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>
<!-- /wp:code -->
<!-- wp:paragraph -->
<p>Deep dive: <a href="https://mer.vin/2026/07/praisonai-code-praisonai-code-terminal-cli-in-depth/">praisonai-code in-depth</a></p>
<!-- /wp:paragraph -->
<!-- wp:heading -->
<h2 class="wp-block-heading">Section 3 — Train (via praisonai-train tier)</h2>
<!-- /wp:heading -->
<!-- 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>
<!-- /wp:code -->
<!-- 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>
<!-- /wp:paragraph -->
<!-- wp:heading -->
<h2 class="wp-block-heading">Section 4 — Bots &amp; gateway (via bot tier)</h2>
<!-- /wp:heading -->
<!-- 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>
<!-- /wp:code -->
<!-- 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>
<!-- /wp:paragraph -->
<!-- wp:heading -->
<h2 class="wp-block-heading">Section 5 — MCP server host (via mcp tier)</h2>
<!-- /wp:heading -->
<!-- wp:table -->
<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>
<!-- /wp:table -->
<!-- wp:code -->
<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>
<!-- /wp:code -->
<!-- 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>
<!-- /wp:paragraph -->
<!-- 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>
<!-- /wp:code -->
<!-- wp:paragraph -->
<p>Three layers: agents protocols → <code>praisonai browser-tool</code> (praisonai-tools) → <code>praisonai browser</code> (extension bridge, CDP, Playwright).</p>
<!-- /wp:paragraph -->
<!-- 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>
<!-- /wp:heading -->
<!-- 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>
<!-- /wp:table -->
<!-- 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>
<!-- /wp:code -->
<!-- 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>
<!-- /wp:code -->
<!-- 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>
<!-- /wp:table -->
<!-- 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>
<!-- /wp:code -->
<!-- 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>
<!-- /wp:table -->
<!-- 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>
<!-- /wp:table -->
<!-- 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>
<!-- /wp:table -->
<!-- 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>
<!-- /wp:table -->
<!-- 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>
<!-- /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 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 -->
-1
View File
@@ -17,7 +17,6 @@ GROQ_API_KEY=gsk_... # Groq (fast inference)
COHERE_API_KEY=... # Cohere models
AZURE_OPENAI_API_KEY=... # Azure OpenAI
AZURE_OPENAI_ENDPOINT=... # Azure OpenAI endpoint
EVOLINK_API_KEY=... # EvoLink.AI OpenAI-compatible models. Get yours at https://evolink.ai/dashboard/keys
# === Optional: Memory backends ===
MEM0_API_KEY=... # Mem0 memory service
+1 -7
View File
@@ -6,11 +6,6 @@ labels: bug
assignees: ''
---
## SDK / package
- [ ] Python (`pip install praisonai` / `praisonaiagents`)
- [ ] TypeScript / JavaScript (`npm install praisonai`) — fixes in `src/praisonai-ts/`
- [ ] Cross-language / parity (file here on PraisonAI)
## Environment
- Provider (select one):
- [ ] Anthropic
@@ -19,7 +14,6 @@ assignees: ''
- [ ] AWS Bedrock
- [ ] Other: <!-- specify -->
- PraisonAI version: <!-- if known -->
- Node.js version (TS/JS only): <!-- e.g. 20.x -->
- Operating System: <!-- e.g. macOS 14.3, Windows 11, Ubuntu 22.04 -->
## Full Code
@@ -37,4 +31,4 @@ assignees: ''
<!-- What actually happened -->
## Additional Context
<!-- Add any other context about the problem here, such as screenshots, logs, etc. -->
<!-- Add any other context about the problem here, such as screenshots, logs, etc. -->
@@ -228,7 +228,6 @@ runs:
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).
6. TypeScript SDK → src/praisonai-ts/ in this monorepo (read src/praisonai-ts/AGENTS.md for TS rules).
- 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.
@@ -288,7 +287,7 @@ runs:
fi
# Add allowed tools (include GitHub tools by default)
TOOLS="mcp__github__get_issue,mcp__github__get_issue_comments,mcp__github__update_issue,mcp__github__search_issues,mcp__github__list_issues,mcp__github__add_issue_comment,mcp__github__get_pull_request,mcp__github__get_pull_request_files,mcp__github__get_pull_request_reviews,mcp__github__get_pull_request_status,Read,Write,Edit,Bash"
TOOLS="mcp__github__get_issue,mcp__github__get_issue_comments,mcp__github__update_issue,mcp__github__search_issues,mcp__github__list_issues,mcp__github__create_comment,Read,Write,Edit,Bash"
if [[ -n "$INPUT_ALLOWED_TOOLS" ]]; then
TOOLS="$TOOLS,$INPUT_ALLOWED_TOOLS"
fi
@@ -328,7 +327,6 @@ runs:
# Execute Claude Code with timeout, using stdin for the prompt
TIMEOUT_SECONDS=$(($INPUT_TIMEOUT_MINUTES * 60))
timeout $TIMEOUT_SECONDS claude "${CMD_ARGS[@]}" < "$PROMPT_FILE" \
| tee "$GITHUB_WORKSPACE/.claude-assess-output.jsonl"
timeout $TIMEOUT_SECONDS claude "${CMD_ARGS[@]}" < "$PROMPT_FILE"
echo "✅ Claude Code execution completed"
@@ -1,36 +0,0 @@
name: Pick Claude OAuth token
description: Probe primary/secondary Claude OAuth tokens and select a working one (dual OAuth Option B).
inputs:
token_primary:
description: Primary Claude OAuth token (CLAUDE_CODE_OAUTH_TOKEN)
required: false
token_secondary:
description: Secondary Claude OAuth token (CLAUDE_CODE_OAUTH_TOKEN_B)
required: false
active_slot:
description: Preferred slot — primary or secondary (repo variable CLAUDE_OAUTH_ACTIVE)
required: false
default: primary
outputs:
token:
description: Selected OAuth token
value: ${{ steps.pick.outputs.token }}
slot:
description: Slot used (primary, secondary, or *-unprobed fallback)
value: ${{ steps.pick.outputs.slot }}
runs:
using: composite
steps:
- id: pick
shell: bash
env:
CLAUDE_CODE_OAUTH_TOKEN: ${{ inputs.token_primary }}
CLAUDE_CODE_OAUTH_TOKEN_B: ${{ inputs.token_secondary }}
CLAUDE_OAUTH_ACTIVE: ${{ inputs.active_slot }}
run: |
if [[ -n "${HUB_SCRIPTS:-}" && -f "${HUB_SCRIPTS}/oauth-pick-token.sh" ]]; then
SCRIPT="${HUB_SCRIPTS}/oauth-pick-token.sh"
else
SCRIPT="${GITHUB_ACTION_PATH}/../../scripts/oauth-pick-token.sh"
fi
bash "$SCRIPT"
+2 -4
View File
@@ -33,20 +33,18 @@ steps:
Second, read the issue: execute_command 'cat .github/triage-context.md'. Do NOT pass cwd.
Third, read architecture guidelines: execute_command 'cat src/praisonai-agents/AGENTS.md'.
If the issue is TypeScript/JavaScript SDK, also execute_command 'cat src/praisonai-ts/AGENTS.md'.
Fourth, decide routing before planning:
- TypeScript/JavaScript SDK → src/praisonai-ts/ in this monorepo (read src/praisonai-ts/AGENTS.md).
- 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 for Python protocols and CLI; external repos for Tools/Plugins/Docs only.
Core SDK/wrapper only for protocols and CLI — external repos for Tools/Plugins.
Fifth, 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 / TS-monorepo / Tools-external / Plugins-external / No-change), validation result, and exact files/lines to change.
Output: routing decision (Core / Wrapper / Tools-external / Plugins-external / 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 -1
View File
@@ -3,7 +3,7 @@
* @see .github/workflows/auto-pr-comment.yml, claude.yml, bot-pr-recovery.yml
*/
const KICK_AUTHORS = new Set(['MervinPraison', 'github-actions[bot]', 'praisonai-triage-agent[bot]']);
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) {
+2 -114
View File
@@ -213,53 +213,6 @@ assert(
mg.findMergeGateVerdict(recentVerdictOnHead, null, '2026-06-27T09:55:00Z') === 'APPROVE'
);
assert(
'scan kickoff text is not a verdict',
mg.findMergeGateVerdict([
{
body: '**Merge gate scan** — eligible for assessment. Claude merge gate will assess and may auto-merge if `MERGE_GATE_VERDICT: APPROVE`.',
created_at: '2026-06-27T10:05:00Z',
},
], null, '2026-06-27T09:55:00Z') === null
);
// merge-only must not use a short time window — fresh Opus APPROVE after assess wins on HEAD.
assert(
'merge path finds APPROVE on HEAD without minCreatedAt window',
mg.findMergeGateVerdict(
[{ body: 'MERGE_GATE_VERDICT: APPROVE', created_at: '2026-06-12T10:00:00Z' }],
null,
'2026-06-12T09:00:00Z',
{ excludeAutomatedFallback: true }
) === 'APPROVE'
);
assert(
'25min minCreatedAt excludes older APPROVE (scan/dispatch paths only)',
mg.findMergeGateVerdict(
[{ body: 'MERGE_GATE_VERDICT: APPROVE', created_at: '2026-06-12T08:00:00Z' }],
'2026-06-12T09:30:00Z',
'2026-06-12T07:00:00Z',
{ excludeAutomatedFallback: true }
) === null
);
const finalWithFinished = [
{ user: { login: 'MervinPraison' }, body: '@claude You are the FINAL architecture reviewer.', created_at: '2026-06-27T10:00:00Z' },
{ user: { login: 'praisonai-triage-agent[bot]' }, body: 'Claude finished', created_at: '2026-06-27T10:05:00Z' },
];
assert('final complete requires Claude finished reply', mg.finalClaudeCompletedOnSha(finalWithFinished, '2026-06-27T09:55:00Z'));
assert('final trigger alone is incomplete', !mg.finalClaudeCompletedOnSha(
[{ user: { login: 'MervinPraison' }, body: '@claude You are the FINAL architecture reviewer.', created_at: '2026-06-27T10:00:00Z' }],
'2026-06-27T09:55:00Z'
));
assert('recent scan comment detected', mg.hasRecentMergeGateScanComment([
{ body: '**Merge gate scan** — eligible', created_at: new Date().toISOString() },
]));
assert('old scan comment not recent', !mg.hasRecentMergeGateScanComment([
{ body: '**Merge gate scan** — eligible', created_at: '2020-01-01T00:00:00Z' },
]));
// Sensitive + secrets
assert('workflow path sensitive', mg.sensitivePathReasons([{ filename: '.github/workflows/foo.yml' }]).length === 1);
assert('ci-only label exempts workflows', mg.sensitivePathReasons(
@@ -304,13 +257,8 @@ const finalAfterRebase = {
body: '@claude You are the FINAL architecture reviewer.',
created_at: conflictIso(-20 * 60 * 1000),
};
const claudeFinishedAfterRebase = {
user: { login: 'praisonai-triage-agent[bot]' },
body: 'Claude finished',
created_at: conflictIso(-19 * 60 * 1000),
};
const headAfterRebase = conflictIso(-21 * 60 * 1000);
const rebaseComments = [conflictTrigger, rebaseDone, finalAfterRebase, claudeFinishedAfterRebase];
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(
@@ -324,16 +272,6 @@ 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);
assert('ts sdk without tests', mg.missingTestsReason([
{ filename: 'src/praisonai-ts/src/agent/simple.ts', additions: 5 },
]) !== null);
assert('ts sdk with tests ok', mg.missingTestsReason([
{ filename: 'src/praisonai-ts/src/agent/simple.ts', additions: 5 },
{ filename: 'src/praisonai-ts/tests/unit/agent/history-restore.test.ts', additions: 10 },
]) === null);
assert('touches ts sdk', mg.touchesSdk([{ filename: 'src/praisonai-ts/src/agent/simple.ts' }]));
assert('final body requires sdk value table', mg.FINAL_CLAUDE_REVIEW_BODY.includes('| **SDK value** |'));
assert('final body requires ts agents md', mg.FINAL_CLAUDE_REVIEW_BODY.includes('src/praisonai-ts/AGENTS.md'));
// PR size
assert('large PR blocked', mg.prSizeReasons([{ additions: 900 }]).length > 0);
@@ -349,54 +287,4 @@ assert('fork sync PR link rejected', !mg.isInternalPullRequestLink(
'PraisonAI'
));
assert('dispatch blocked when merge gate active', mg.mergeGateDispatchBlockedReason({
labels: ['claude-merge-gate-active'],
pendingRuns: 0,
}) === 'merge gate already active on PR');
assert('dispatch blocked when queue saturated', mg.mergeGateDispatchBlockedReason({
labels: [],
pendingRuns: 3,
})?.includes('already queued or in progress'));
assert('dispatch allowed when queue below cap', mg.mergeGateDispatchBlockedReason({
labels: [],
pendingRuns: 2,
}) == null);
// Pending count excludes workflow_run auto-dispatch probes (PR #4534)
assert('workflow_run probes excluded from pending count', mg.countSubstantiveMergeGateRuns([
{ event: 'workflow_dispatch' },
{ event: 'workflow_run' },
{ event: 'workflow_run' },
]) === 1);
assert('all-probe runs count as zero pending', mg.countSubstantiveMergeGateRuns([
{ event: 'workflow_run' },
{ event: 'workflow_run' },
]) === 0);
assert('substantive dispatches still counted', mg.countSubstantiveMergeGateRuns([
{ event: 'workflow_dispatch' },
{ event: 'schedule' },
]) === 2);
assert('countSubstantiveMergeGateRuns null-safe', mg.countSubstantiveMergeGateRuns(null) === 0);
assert('rate limit threshold is 200', mg.MIN_CORE_RATE_LIMIT_REMAINING === 200);
(async () => {
const skipLow = await mg.shouldSkipMergeGateDispatch(
{
rest: {
rateLimit: {
get: async () => ({ data: { resources: { core: { remaining: 50 } } } }),
},
},
},
'owner',
'repo',
1,
{ info: () => {} }
);
assert('rate limit low skips dispatch', skipLow === true);
process.exit(failed ? 1 : 0);
})().catch((err) => {
console.error(err);
process.exit(1);
});
process.exit(failed ? 1 : 0);
+23 -233
View File
@@ -16,12 +16,8 @@ const PR_MAX_AUTO_ADDITIONS = 800;
const PR_MAX_AUTO_FILES = 30;
const MANUAL_ONLY_LABELS = new Set(['security', 'breaking-change', 'needs-manual-review', 'release']);
const WORKFLOW_ONLY_LABEL = 'merge-gate-ci-only';
const EXTERNAL_EXAMPLE_PATH_PREFIX = 'examples/tools/external/';
const EXTERNAL_EXAMPLE_LABEL = 'pipeline/external-example';
const MAINTAINER_ACCEPT_EXAMPLE_LABEL = 'maintainer-accept-example';
const CI_ONLY_PATH_PREFIXES = ['.github/workflows/', '.github/actions/', '.github/scripts/merge-gate'];
const SDK_PATH_PREFIXES = ['src/praisonai-agents/', 'src/praisonai/', 'src/praisonai-ts/'];
const TS_SDK_SOURCE_PREFIX = 'src/praisonai-ts/src/';
const SDK_PATH_PREFIXES = ['src/praisonai-agents/', 'src/praisonai/'];
const SENSITIVE_PATH_PATTERNS = [
/^\.github\/workflows\//,
/praisonaiagents\/(auth|approval|policy|sandbox)\//,
@@ -30,17 +26,7 @@ const SENSITIVE_PATH_PATTERNS = [
/\.env(\.|$)/,
/credentials\.json$/i,
];
const REQUIRED_SDK_CHECK_PATTERNS = [
/test/i,
/smoke/i,
/core/i,
/python package/i,
/comprehensive/i,
/optimized/i,
/praisonai-ts/i,
/npm/i,
/webview/i,
];
const REQUIRED_SDK_CHECK_PATTERNS = [/test/i, /smoke/i, /core/i, /python package/i, /comprehensive/i, /optimized/i];
const SECRET_PATTERNS = [
/sk-[a-zA-Z0-9]{20,}/,
/AKIA[0-9A-Z]{16}/,
@@ -318,20 +304,11 @@ function shouldSkipStaleFinalRecovery(comments, headPushedAt, headPusherLogin =
function finalClaudeCompletedOnSha(comments, headPushedAt) {
if (!hasFinalClaudeReviewTrigger(comments)) return false;
if (isStaleFinalAfterPush(comments, headPushedAt)) return false;
const finals = comments.filter(isFinalClaudeTriggerComment);
if (finals.length === 0) return false;
const latestFinal = finals.reduce((a, b) =>
new Date(a.created_at) > new Date(b.created_at) ? a : b
);
const finalTime = new Date(latestFinal.created_at).getTime();
return comments.some((c) => {
if (!isClaudeFinalReplyComment(c)) return false;
return new Date(c.created_at).getTime() >= finalTime - 60000;
});
return true;
}
const FINAL_CLAUDE_REVIEW_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: Review changes in this PR. Python SDK: praisonaiagents, praisonai. TypeScript SDK: src/praisonai-ts/. Do NOT modify src/praisonai-rust. Read ALL comments above from Gemini, Qodo, CodeRabbit, and Copilot carefully before responding.\n\n**MANDATORY READ (before reviewing):**\n- Always read src/praisonai-agents/AGENTS.md\n- If this PR touches src/praisonai-ts/, also read src/praisonai-ts/AGENTS.md §2.1.2 (TS triage + PR review checklist)\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\n4. SDK value: review in depth whether the change genuinely adds value to the SDK — never add features for the sake of adding them. It must strengthen the SDK (simpler, more user-friendly, robust, world-class, secure). If it does not clearly add value, request changes or recommend rejecting/closing rather than merging scope creep\n5. Do not bloat the Agent class with additional params — only if absolutely required; we already support many params.\n6. Repo routing: agent-callable tools → PraisonAI-Tools; lifecycle plugins → PraisonAI-Plugins; optional sandbox backends → PraisonAI-Plugins (`praisonai.sandbox` entry point) — request changes if wrongly added to praisonaiagents/\n6b. **External tool examples (`examples/tools/external/**`):** If the diff is confined to that path, mark **SDK value** ❌ for monorepo merge — redirect the contributor to PraisonAI-Tools; do **not** Approve for merge unless the PR has the `maintainer-accept-example` label.\n\n**MANDATORY COMMENT FORMAT — include this Phase 1 table in your review comment:**\n#### Phase 1 — AGENTS.md review\n| Check | Result |\n|---|---|\n| Protocol-driven / no heavy impl in core | ✅ or ❌ + one-line rationale |\n| Backward compatible | ✅ or ❌ + one-line rationale |\n| Performance (hot path) | ✅ or ❌ + one-line rationale |\n| **SDK value** | ✅ or ❌ + one-line rationale (explicitly judge whether the change strengthens the SDK) |\n| No Agent param bloat | ✅ or ❌ + one-line rationale |\n| Repo routing | ✅ or ❌ + one-line rationale |\n\nFor TypeScript PRs (src/praisonai-ts/), also add:\n| TS types / parity / tests | ✅ or ❌ + one-line rationale (npm run build && npm test) |\n\n**Phase 2: FIX Valid Issues**\n7. For any VALID bugs or architectural flaws found by Gemini, CodeRabbit, Qodo, Copilot, or any other reviewer: implement the fix\n8. Also independently identify and fix any gaps or issues you find in the changed code — do not rely only on prior reviewer feedback\n9. Push all code fixes directly to THIS branch (do NOT create a new PR)\n10. Comment a summary of exact files modified and what you skipped\n\n**Phase 3: Final Verdict**\n11. If all issues are resolved, approve the PR / close the Issue\n12. If blocking issues remain, request changes / leave clear action items';
'@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\n4. SDK value: review in depth whether the change genuinely adds value to the SDK — never add features for the sake of adding them. It must strengthen the SDK (simpler, more user-friendly, robust, world-class, secure). If it does not clearly add value, request changes or recommend rejecting/closing rather than merging scope creep\n5. Do not bloat the Agent class with additional params — only if absolutely required; we already support many params.\n6. Repo routing: agent-callable tools → PraisonAI-Tools; lifecycle plugins → PraisonAI-Plugins; optional sandbox backends → PraisonAI-Plugins (`praisonai.sandbox` entry point) — request changes if wrongly added to praisonaiagents/\n\n**Phase 2: FIX Valid Issues**\n7. For any VALID bugs or architectural flaws found by Gemini, CodeRabbit, Qodo, Copilot, or any other reviewer: implement the fix\n8. Also independently identify and fix any gaps or issues you find in the changed code — do not rely only on prior reviewer feedback\n9. Push all code fixes directly to THIS branch (do NOT create a new PR)\n10. Comment a summary of exact files modified and what you skipped\n\n**Phase 3: Final Verdict**\n11. If all issues are resolved, approve the PR / close the Issue\n12. If blocking issues remain, request changes / leave clear action items';
async function getMergeState(github, owner, repo, prNumber) {
const query = `
@@ -487,79 +464,6 @@ function hasBlockingClaudeRunForPr(runs, headRef) {
return (runs || []).some((r) => claudeRunBlocksPr(r, headRef));
}
const MERGE_GATE_WORKFLOW_FILE = 'claude-merge-gate.yml';
const MERGE_GATE_ACTIVE_LABEL = 'claude-merge-gate-active';
const MAX_PENDING_MERGE_GATE_RUNS = 3;
const MIN_CORE_RATE_LIMIT_REMAINING = 200;
function mergeGateDispatchBlockedReason({ labels, pendingRuns, maxPending = MAX_PENDING_MERGE_GATE_RUNS }) {
if ((labels || []).includes(MERGE_GATE_ACTIVE_LABEL)) {
return 'merge gate already active on PR';
}
if (pendingRuns >= maxPending) {
return `${pendingRuns} merge gate run(s) already queued or in progress (max ${maxPending})`;
}
return null;
}
// workflow_run probes (auto-dispatch) share concurrency and must not count
// toward backpressure — they blocked dispatches for merge-ready PRs.
function countSubstantiveMergeGateRuns(runs) {
return (runs || []).filter((r) => r && r.event !== 'workflow_run').length;
}
async function countPendingMergeGateRuns(github, owner, repo) {
let pending = 0;
for (const status of ['queued', 'in_progress']) {
try {
const { data } = await github.rest.actions.listWorkflowRuns({
owner,
repo,
workflow_id: MERGE_GATE_WORKFLOW_FILE,
status,
per_page: 30,
});
pending += countSubstantiveMergeGateRuns(data.workflow_runs);
} catch {
// Best-effort backpressure only.
}
}
return pending;
}
async function getCoreRateLimitRemaining(github) {
try {
const { data } = await github.rest.rateLimit.get();
return data?.resources?.core?.remaining ?? null;
} catch {
return null;
}
}
async function shouldSkipMergeGateDispatch(github, owner, repo, prNumber, core, options = {}) {
const maxPending = options.maxPending ?? MAX_PENDING_MERGE_GATE_RUNS;
const minCoreRemaining = options.minCoreRemaining ?? MIN_CORE_RATE_LIMIT_REMAINING;
const remaining = await getCoreRateLimitRemaining(github);
if (remaining !== null && remaining < minCoreRemaining) {
core?.info?.(
`Skip merge gate dispatch for PR #${prNumber}: rate limit low (${remaining} core remaining)`
);
return true;
}
const ctx = await loadPrContext(github, owner, repo, prNumber);
const pendingRuns = await countPendingMergeGateRuns(github, owner, repo);
const reason = mergeGateDispatchBlockedReason({
labels: ctx.labels,
pendingRuns,
maxPending,
});
if (reason) {
core?.info?.(`Skip merge gate dispatch for PR #${prNumber}: ${reason}`);
return true;
}
return false;
}
async function hasInProgressClaudeAssistant(github, owner, repo, prNumber = null) {
try {
const { data } = await github.rest.actions.listWorkflowRuns({
@@ -586,11 +490,6 @@ function isCiOnlyChange(files) {
return files.every((f) => CI_ONLY_PATH_PREFIXES.some((p) => f.filename.startsWith(p)));
}
function isExternalExampleOnlyChange(files) {
if (!files.length) return false;
return files.every((f) => f.filename.startsWith(EXTERNAL_EXAMPLE_PATH_PREFIX));
}
function isInternalPullRequestLink(link, owner, repo) {
if (link?.base?.repo?.full_name === `${owner}/${repo}`) return true;
const baseUrl = link?.base?.repo?.url || '';
@@ -728,35 +627,18 @@ function prSizeReasons(files) {
}
function missingTestsReason(files) {
const pySdkAdds = files.filter(
const sdkAdds = files.filter(
(f) =>
f.filename.startsWith('src/praisonai-agents/') &&
f.filename.endsWith('.py') &&
!f.filename.endsWith('__init__.py') &&
(f.additions || 0) > 0
);
const tsSdkAdds = files.filter(
(f) =>
f.filename.startsWith(TS_SDK_SOURCE_PREFIX) &&
f.filename.endsWith('.ts') &&
!f.filename.endsWith('.d.ts') &&
(f.additions || 0) > 0
);
if (pySdkAdds.length === 0 && tsSdkAdds.length === 0) return null;
const hasPyTestChange = files.some(
if (sdkAdds.length === 0) return null;
const hasTestChange = files.some(
(f) => /\/tests?\//.test(f.filename) || /test_.*\.py$/.test(f.filename) || /_test\.py$/.test(f.filename)
);
const hasTsTestChange = files.some(
(f) =>
f.filename.startsWith('src/praisonai-ts/tests/') ||
/\.(test|spec)\.ts$/.test(f.filename)
);
if (pySdkAdds.length > 0 && !hasPyTestChange) {
return 'Python SDK code added without test file changes — requires manual review';
}
if (tsSdkAdds.length > 0 && !hasTsTestChange) {
return 'TS SDK code added without test file changes — requires manual review';
}
if (!hasTestChange) return 'SDK code added without test file changes — requires manual review';
return null;
}
@@ -805,67 +687,22 @@ function manualReviewReasonForAgentPy(agentChange) {
return null;
}
async function listAllComments(github, owner, repo, issueNumber, options = {}) {
const { since } = options;
const params = {
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,
};
if (since) params.since = since;
// Always page explicitly — github-script's paginate helper can return only the
// first page on busy PRs, so fresh MERGE_GATE_VERDICT comments on page 2+ are missed.
const all = [];
for (let page = 1; page <= 50; page++) {
const { data } = await github.rest.issues.listComments({ ...params, page });
all.push(...data);
if (data.length < 100) break;
}
return all;
}
/** Poll until Opus posts MERGE_GATE_VERDICT on HEAD (merge-only runs right after assess). */
async function waitForMergeGateVerdict(github, owner, repo, prNumber, options = {}) {
const {
headPushedAt = null,
excludeAutomatedFallback = true,
maxAttempts = 18,
intervalMs = 10000,
since = null,
core: log = null,
} = options;
let resolvedHeadPushedAt = headPushedAt;
const commentSince =
since ||
(resolvedHeadPushedAt
? new Date(new Date(resolvedHeadPushedAt).getTime() - 5 * 60 * 1000).toISOString()
: null);
for (let attempt = 1; attempt <= maxAttempts; attempt++) {
if (!resolvedHeadPushedAt) {
const ctx = await loadPrContext(github, owner, repo, prNumber);
resolvedHeadPushedAt = ctx.headPushedAt;
}
const comments = await listAllComments(github, owner, repo, prNumber, {
since: commentSince || undefined,
});
const verdict = findMergeGateVerdict(comments, null, resolvedHeadPushedAt, {
excludeAutomatedFallback,
});
if (verdict) {
return { verdict, headPushedAt: resolvedHeadPushedAt };
}
if (attempt < maxAttempts) {
log?.info?.(
`Verdict not visible yet (attempt ${attempt}/${maxAttempts}), waiting ${intervalMs / 1000}s...`
);
await new Promise((r) => setTimeout(r, intervalMs));
}
}
return { verdict: null, headPushedAt: resolvedHeadPushedAt };
});
return data;
}
async function getHeadCommitDate(github, owner, repo, prNumber) {
@@ -981,15 +818,6 @@ async function evaluatePipelineQuiescent(github, owner, repo, prNumber, core, op
const pullFiles = await listPullFiles(github, owner, repo, prNumber);
if (
isExternalExampleOnlyChange(pullFiles) &&
!ctx.labels.includes(MAINTAINER_ACCEPT_EXAMPLE_LABEL)
) {
reasons.push(
'external example only — belongs in PraisonAI-Tools (add maintainer-accept-example to opt in)'
);
}
const agentChange = getAgentPyChangeFromFiles(pullFiles);
const agentManual = manualReviewReasonForAgentPy(agentChange);
if (agentManual) reasons.push(agentManual);
@@ -1036,13 +864,6 @@ async function listPrNumbersForMergeGateScan(github, owner, repo, core) {
}
const mergeReady = mergeReadyIssues
.filter((issue) => issue.pull_request)
.filter((issue) => {
const labels = (issue.labels || []).map((l) => (typeof l === 'string' ? l : l.name));
if (labels.includes(EXTERNAL_EXAMPLE_LABEL) && !labels.includes(MAINTAINER_ACCEPT_EXAMPLE_LABEL)) {
return false;
}
return true;
})
.map((issue) => issue.number)
.sort((a, b) => a - b);
@@ -1098,33 +919,18 @@ async function selectMergeGateCandidates(github, owner, repo, prNumbers, maxCand
}
const AUTOMATED_FALLBACK_MARKER = 'Automated fallback —';
const MERGE_GATE_SCAN_MARKER = 'Merge gate scan';
function isAutomatedFallbackVerdict(body) {
return (body || '').includes(AUTOMATED_FALLBACK_MARKER);
}
function isMergeGateVerdictComment(body) {
const text = body || '';
if (text.includes(MERGE_GATE_SCAN_MARKER)) return false;
return /(?:^|\n)\s*MERGE_GATE_VERDICT:\s*(APPROVE|BLOCK)\b/m.test(text);
}
function hasRecentMergeGateScanComment(comments, withinMinutes = 30) {
const cutoff = Date.now() - withinMinutes * 60 * 1000;
return (comments || []).some((c) => {
if (!(c.body || '').includes(MERGE_GATE_SCAN_MARKER)) return false;
return new Date(c.created_at).getTime() > cutoff;
});
}
function findMergeGateVerdict(comments, minCreatedAt = null, headPushedAt = null, options = {}) {
const { excludeAutomatedFallback = false } = options || {};
const minTime = minCreatedAt ? new Date(minCreatedAt).getTime() : 0;
const headTime = headPushedAt ? new Date(headPushedAt).getTime() - 60000 : 0;
const gateComments = comments
.filter((c) => {
if (!isMergeGateVerdictComment(c.body)) return false;
if (!(c.body || '').includes('MERGE_GATE_VERDICT:')) return false;
if (excludeAutomatedFallback && isAutomatedFallbackVerdict(c.body)) return false;
const created = new Date(c.created_at).getTime();
if (minTime && created < minTime) return false;
@@ -1134,8 +940,8 @@ function findMergeGateVerdict(comments, minCreatedAt = null, headPushedAt = null
.sort((a, b) => new Date(b.created_at) - new Date(a.created_at));
if (gateComments.length === 0) return null;
const body = gateComments[0].body || '';
if (/MERGE_GATE_VERDICT:\s*APPROVE\b/.test(body)) return 'APPROVE';
if (/MERGE_GATE_VERDICT:\s*BLOCK\b/.test(body)) return 'BLOCK';
if (body.includes('MERGE_GATE_VERDICT: APPROVE')) return 'APPROVE';
if (body.includes('MERGE_GATE_VERDICT: BLOCK')) return 'BLOCK';
return null;
}
@@ -1170,10 +976,6 @@ module.exports = {
claudeRunBlocksPr,
hasBlockingClaudeRunForPr,
isCiOnlyChange,
isExternalExampleOnlyChange,
EXTERNAL_EXAMPLE_PATH_PREFIX,
EXTERNAL_EXAMPLE_LABEL,
MAINTAINER_ACCEPT_EXAMPLE_LABEL,
isInternalPullRequestLink,
resolvePrNumberFromLinkedPullRequests,
resolvePrNumberFromHeadBranch,
@@ -1192,7 +994,6 @@ module.exports = {
secretScanReasons,
sdkTestChecksReason,
listAllComments,
waitForMergeGateVerdict,
getHeadCommitDate,
isStaleFinalAfterPush,
needsStaleFinalRecovery,
@@ -1211,16 +1012,5 @@ module.exports = {
selectMergeGateCandidates,
isAutomatedFallbackVerdict,
AUTOMATED_FALLBACK_MARKER,
isMergeGateVerdictComment,
hasRecentMergeGateScanComment,
findMergeGateVerdict,
MERGE_GATE_WORKFLOW_FILE,
MERGE_GATE_ACTIVE_LABEL,
MAX_PENDING_MERGE_GATE_RUNS,
MIN_CORE_RATE_LIMIT_REMAINING,
getCoreRateLimitRemaining,
mergeGateDispatchBlockedReason,
countSubstantiveMergeGateRuns,
countPendingMergeGateRuns,
shouldSkipMergeGateDispatch,
};
-101
View File
@@ -1,101 +0,0 @@
#!/usr/bin/env bash
# Pick a working Claude Code OAuth token (primary/secondary with failover).
# Env: CLAUDE_CODE_OAUTH_TOKEN, CLAUDE_CODE_OAUTH_TOKEN_B, CLAUDE_OAUTH_ACTIVE
# Out: GITHUB_OUTPUT token, slot
set -euo pipefail
PRIMARY="${CLAUDE_CODE_OAUTH_TOKEN:-}"
SECONDARY="${CLAUDE_CODE_OAUTH_TOKEN_B:-}"
ACTIVE="${CLAUDE_OAUTH_ACTIVE:-primary}"
ACTIVE_LC=$(echo "$ACTIVE" | tr '[:upper:]' '[:lower:]')
case "$ACTIVE_LC" in
secondary|b|2) PREFERRED=secondary ;;
*) PREFERRED=primary ;;
esac
probe_token() {
local token=$1
[[ -z "$token" ]] && return 1
local body='{"model":"claude-3-5-haiku-latest","max_tokens":1,"messages":[{"role":"user","content":"."}]}'
local tmp http_code body_resp
tmp=$(mktemp)
http_code=$(curl -sS -o "$tmp" -w "%{http_code}" \
-X POST "https://api.anthropic.com/v1/messages" \
-H "Authorization: Bearer ${token}" \
-H "anthropic-version: 2023-06-01" \
-H "content-type: application/json" \
-d "$body" 2>/dev/null || echo "000")
body_resp=$(cat "$tmp")
rm -f "$tmp"
if [[ "$http_code" == "200" ]] || [[ "$http_code" == "400" ]]; then
return 0
fi
if [[ "$http_code" == "401" ]] || [[ "$http_code" == "429" ]]; then
echo "::warning::OAuth probe failed (HTTP ${http_code})"
return 1
fi
if echo "$body_resp" | grep -qiE 'revoked|invalid.*token|authentication|weekly limit|rate_limit|overloaded|billing'; then
echo "::warning::OAuth probe rejected (HTTP ${http_code})"
return 1
fi
return 0
}
try_token() {
local slot=$1 token=$2
[[ -z "$token" ]] && return 1
if probe_token "$token"; then
SELECTED_SLOT=$slot
SELECTED_TOKEN=$token
return 0
fi
return 1
}
SELECTED_SLOT=""
SELECTED_TOKEN=""
if [[ "$PREFERRED" == "primary" ]]; then
try_token primary "$PRIMARY" || try_token secondary "$SECONDARY" || true
else
try_token secondary "$SECONDARY" || try_token primary "$PRIMARY" || true
fi
if [[ -z "$SELECTED_TOKEN" ]]; then
if [[ "$PREFERRED" == "primary" && -n "$PRIMARY" ]]; then
SELECTED_TOKEN="$PRIMARY"
SELECTED_SLOT="primary-unprobed"
elif [[ -n "$SECONDARY" ]]; then
SELECTED_TOKEN="$SECONDARY"
SELECTED_SLOT="secondary-unprobed"
elif [[ -n "$PRIMARY" ]]; then
SELECTED_TOKEN="$PRIMARY"
SELECTED_SLOT="primary-unprobed"
else
echo "::error::No Claude OAuth token configured"
exit 1
fi
echo "::warning::OAuth probe failed for all tokens; using ${SELECTED_SLOT}"
fi
echo "::notice::Claude OAuth slot: ${SELECTED_SLOT}"
if [[ -z "${GITHUB_OUTPUT:-}" ]]; then
echo "slot=${SELECTED_SLOT}"
exit 0
fi
{
echo "token<<EOF"
echo "$SELECTED_TOKEN"
echo "EOF"
echo "slot=${SELECTED_SLOT}"
} >> "$GITHUB_OUTPUT"
@@ -73,33 +73,4 @@ assert(
)
);
assert(
'external example only path',
mg.isExternalExampleOnlyChange([{ filename: 'examples/tools/external/arxiv/tool.py' }])
);
assert(
'mixed paths not external-example only',
!mg.isExternalExampleOnlyChange([
{ filename: 'examples/tools/external/foo.py' },
{ filename: 'src/praisonai-agents/foo.py' },
])
);
assert(
'upstream head repo',
ps.isUpstreamHeadRepo(
{ head: { repo: { full_name: 'MervinPraison/PraisonAI' } } },
'MervinPraison',
'PraisonAI'
)
);
assert(
'fork head repo still synced (not upstream)',
!ps.isUpstreamHeadRepo(
{ head: { repo: { full_name: 'ai-mrscraper/PraisonAI' } } },
'MervinPraison',
'PraisonAI'
)
);
process.exit(failed ? 1 : 0);
+7 -27
View File
@@ -37,17 +37,8 @@ const LABEL_SPECS = [
{ 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' },
{
name: 'pipeline/external-example',
color: 'bfd4f2',
description: 'Diff only under examples/tools/external/ — not merge-ready without maintainer-accept-example',
},
];
// PRs with pipeline/external-example cannot reach pipeline/merge-ready unless
// maintainers add maintainer-accept-example (enforced in merge-gate evaluatePipelineQuiescent,
// same fail-closed pattern as fork PRs).
function deriveStage(comments, evalResult) {
if (evalResult.ready) return 'pipeline/merge-ready';
if (!chain.chainKickPosted(comments)) return 'pipeline/reviews-pending';
@@ -72,8 +63,7 @@ function reasonToBlockerLabel(reason) {
r.includes('without test') ||
r.includes('files changed') ||
r.includes('possible secret') ||
r.includes('agent.py') ||
r.includes('external example only')
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';
@@ -143,16 +133,11 @@ async function syncPipelineLabels(github, owner, repo, prNumber, core) {
github, owner, repo, prNumber, core
);
const { stage, blockers, all } = computePipelineLabels(ctx.comments, evalResult);
const pullFiles = await mergeGate.listPullFiles(github, owner, repo, prNumber);
const auxiliary = mergeGate.isExternalExampleOnlyChange(pullFiles)
? [mergeGate.EXTERNAL_EXAMPLE_LABEL]
: [];
const labelSet = [...all, ...auxiliary];
const current = ctx.labels.filter((l) => l.startsWith(PIPELINE_PREFIX));
const desired = new Set(labelSet);
const desired = new Set(all);
const toRemove = current.filter((l) => !desired.has(l) && l !== 'pipeline/merged');
const toAdd = labelSet.filter((l) => !current.includes(l));
const toAdd = all.filter((l) => !current.includes(l));
for (const name of toRemove) {
try {
@@ -196,10 +181,10 @@ async function syncPipelineLabels(github, owner, repo, prNumber, core) {
async function dispatchMergeGateForOldestReady(github, owner, repo, readyCandidates, core) {
if (!readyCandidates.length) return 0;
const mergeGate = require('./merge-gate.js');
readyCandidates.sort((a, b) => a.createdAt - b.createdAt);
for (const cand of readyCandidates) {
if (await mergeGate.shouldSkipMergeGateDispatch(github, owner, repo, cand.prNumber, core)) {
if ((cand.labels || []).includes('claude-merge-gate-active')) {
core?.info?.(`Skip dispatch PR #${cand.prNumber}: merge gate already active`);
continue;
}
await github.rest.repos.createDispatchEvent({
@@ -214,11 +199,6 @@ async function dispatchMergeGateForOldestReady(github, owner, repo, readyCandida
return 0;
}
function isUpstreamHeadRepo(pr, owner, repo) {
const headFull = pr.head?.repo?.full_name;
return !headFull || headFull === `${owner}/${repo}`;
}
async function syncOpenPullRequests(github, owner, repo, options, core) {
const { maxPrs = 20, dispatchMergeGate = true } = options || {};
await ensurePipelineLabels(github, owner, repo, core);
@@ -243,8 +223,9 @@ async function syncOpenPullRequests(github, owner, repo, options, core) {
for (const pr of prs) {
if (synced >= maxPrs) break;
if (pr.draft) continue;
if (pr.head?.repo?.full_name && pr.head.repo.full_name !== `${owner}/${repo}`) continue;
const result = await syncPipelineLabels(github, owner, repo, pr.number, core);
if (result.ready && isUpstreamHeadRepo(pr, owner, repo)) {
if (result.ready) {
readyCandidates.push({
prNumber: pr.number,
createdAt: result.createdAt || new Date(pr.created_at).getTime(),
@@ -267,7 +248,6 @@ module.exports = {
STAGE_LABELS,
BLOCKER_LABELS,
ALL_PIPELINE_LABELS,
isUpstreamHeadRepo,
deriveStage,
deriveBlockerLabels,
computePipelineLabels,
-142
View File
@@ -1,142 +0,0 @@
# Why this exists
#
# praisonai-agents has ~11,900 tests. Until this gate, CI executed 15 of them:
# one smoke step in test-optimized.yml naming two files. Everything else was
# collected by nobody.
#
# The cost of that showed up as two test modules that could not even be
# IMPORTED -- they referenced symbols moved or replaced months earlier, so 19
# tests silently contributed nothing while still appearing to exist. A failing
# test is loud; a test that never collects is not.
#
# This job started as collection-only, because running the suite would have gone
# red on arrival: 297 pre-existing failures nothing had been enforcing, and a job
# that is red the day it lands teaches people to ignore it. Then a curated
# green-set, ratcheted upward.
#
# Both are gone. The unit suite now runs in full and passes: 9373 tests, 0
# failures. The `collect` job stays because it is the cheaper, stricter signal --
# it cannot pass while a test file is unimportable, and it says so in 40s.
#
name: agents-suite
on:
push:
branches: [ main ]
paths:
- 'src/praisonai-agents/**'
- '.github/workflows/agents-suite.yml'
pull_request:
paths:
- 'src/praisonai-agents/**'
- '.github/workflows/agents-suite.yml'
jobs:
collect:
name: every praisonai-agents test file imports
runs-on: ubuntu-latest
timeout-minutes: 10
steps:
- uses: actions/checkout@v4
- uses: actions/setup-python@v5
with:
python-version: '3.11'
- name: Install
run: |
set -euo pipefail
python -m pip install --upgrade pip
pip install -e src/praisonai-agents
pip install pytest pytest-asyncio pytest-timeout
- name: Collect the whole suite
working-directory: src/praisonai-agents
env:
# A key must be present or some modules bail at import; it is never
# used, because collection does not execute test bodies.
OPENAI_API_KEY: 'sk-collect-only-not-a-real-key'
run: |
set -euo pipefail
# No pipe here: piping pytest into tail discards its exit code, which
# is how a gate silently stops gating.
python -m pytest tests/ --collect-only -q --disable-warnings
unit:
name: praisonai-agents unit tests
runs-on: ubuntu-latest
timeout-minutes: 20
steps:
- uses: actions/checkout@v4
- uses: actions/setup-python@v5
with:
python-version: '3.11'
- name: Install
run: |
set -euo pipefail
python -m pip install --upgrade pip
# Extras, not decoration. Tests across workflows/embedding/eval/context
# patch litellm and construct LLM(...), and the knowledge suite needs
# chonkie for chunking -- without [knowledge] 22 tests fail on
# "chonkie package not found", an install gap that reads as 22 code
# failures.
pip install -e "src/praisonai-agents[llm,knowledge]"
# praisonai-sandbox is a MONOREPO sibling, not a third-party optional.
# Without it 47 tests fail with "No module named
# praisonai_sandbox.compute" -- an install gap reported as 47 code
# failures. Installing it took the suite from 297 failures to 250.
pip install -e src/praisonai-sandbox
# Same story: a stale praisonai-bot in the environment made 22 gateway
# tests fail on a malformed pairing file. The monorepo version already
# handles it; the INSTALLED one did not.
pip install -e src/praisonai-bot
# The wrapper. tests/unit/test_managed_backend.py imports
# praisonai.integrations.managed_agents; without it 47 tests fail with
# "No module named 'praisonai'". Found by running the suite on 3.11 in
# a CI-shaped environment rather than trusting a developer machine
# where every sibling is already installed.
pip install -e src/praisonai
pip install pytest pytest-asyncio pytest-timeout
- name: Run the unit suite
working-directory: src/praisonai-agents
env:
# Never used: PRAISONAI_ALLOW_NETWORK=0 and the live marker keep these
# offline. Present because some modules bail at import without a key.
OPENAI_API_KEY: 'sk-not-a-real-key'
PRAISONAI_ALLOW_NETWORK: '0'
run: |
set -euo pipefail
# The whole suite, not a curated subset. tests/green-set.txt and
# tests/known-failures.txt are gone: 9373 pass, 0 fail.
#
# The 297 failures this job was built around were, in the end:
# 83 environment -- monorepo siblings not installed, dirty HOME
# 19 ONE line -- a module-level os.environ.setdefault in
# tests/unit/tools/test_delegation_tools.py that
# turned auto-approval on for the whole process
# at COLLECTION time
# ~5 deprecation warnings that fire once per process
# ~85 tests asserting contracts the product had deliberately changed
# 5 real product bugs
# the rest: tests built on Mocks whose auto-created attributes
# defeated the very code path under test
#
# Three traps worth knowing before adding a test here, each of which
# cost a full-suite bisect:
# 1. Module-level env mutation persists for the entire process, and
# runs at collection. Use monkeypatch.
# 2. The approval registry is a process-global singleton. Anything
# you add_requirement() stays for every later test.
# 3. `'litellm' in module_name` also matches praisonai's own
# _litellm_loader; evicting it from sys.modules creates a second
# module object with separate globals.
#
# No pipe: piping pytest into anything discards its exit code, which is
# how a gate silently stops gating.
#
# Nothing is excluded. test_prefetch.py used to be, recorded as "passes
# on macOS, fails on Linux" -- wrong variable. It was Python 3.12 vs the
# 3.11 pinned above: isinstance() against a runtime_checkable Protocol
# used hasattr on 3.11 (which any MagicMock satisfies) and
# inspect.getattr_static from 3.12 (which does not see Mock's
# auto-created attributes). The mock now names its methods, so both
# versions take the same branch.
python -m pytest tests/unit/ -q -p no:randomly --timeout=120 \
--disable-warnings
+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: TypeScript → src/praisonai-ts/; 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. 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'
});
+7 -7
View File
@@ -53,7 +53,7 @@ jobs:
- name: Post Claude FINAL after prior reviewers
uses: actions/github-script@v7
with:
github-token: ${{ secrets.GH_TOKEN != '' && secrets.GH_TOKEN || github.token }}
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'));
@@ -97,7 +97,7 @@ jobs:
- name: Post Claude FINAL (skip Copilot)
uses: actions/github-script@v7
with:
github-token: ${{ secrets.GH_TOKEN != '' && secrets.GH_TOKEN || github.token }}
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'));
@@ -126,7 +126,7 @@ jobs:
- name: Re-post FINAL Claude review when stale or missing
uses: actions/github-script@v7
with:
github-token: ${{ secrets.GH_TOKEN != '' && secrets.GH_TOKEN || github.token }}
github-token: ${{ secrets.GH_TOKEN }}
script: |
const path = require('path');
const mergeGate = require(path.join(process.env.GITHUB_WORKSPACE, '.github/scripts/merge-gate.js'));
@@ -182,7 +182,7 @@ jobs:
- name: Sync pipeline status labels
uses: actions/github-script@v7
with:
github-token: ${{ secrets.GH_TOKEN != '' && secrets.GH_TOKEN || github.token }}
github-token: ${{ secrets.GH_TOKEN }}
script: |
const path = require('path');
const ps = require(path.join(process.env.GITHUB_WORKSPACE, '.github/scripts/pipeline-status.js'));
@@ -203,7 +203,7 @@ jobs:
- name: Post missing/stale FINAL @claude on open PRs
uses: actions/github-script@v7
with:
github-token: ${{ secrets.GH_TOKEN != '' && secrets.GH_TOKEN || github.token }}
github-token: ${{ secrets.GH_TOKEN }}
script: |
const path = require('path');
const mergeGate = require(path.join(process.env.GITHUB_WORKSPACE, '.github/scripts/merge-gate.js'));
@@ -275,7 +275,7 @@ jobs:
- name: Trigger CodeRabbit and Qodo reviews
uses: actions/github-script@v7
with:
github-token: ${{ secrets.GH_TOKEN != '' && secrets.GH_TOKEN || github.token }}
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'));
@@ -285,7 +285,7 @@ jobs:
- name: Sync pipeline status labels
uses: actions/github-script@v7
with:
github-token: ${{ secrets.GH_TOKEN != '' && secrets.GH_TOKEN || github.token }}
github-token: ${{ secrets.GH_TOKEN }}
script: |
const path = require('path');
const ps = require(path.join(process.env.GITHUB_WORKSPACE, '.github/scripts/pipeline-status.js'));
+1 -9
View File
@@ -28,16 +28,8 @@ jobs:
with:
token: ${{ steps.app-token.outputs.token }}
- name: Pick Claude OAuth token
id: oauth
uses: MervinPraison/github-automation-template/.github/actions/[email protected]
with:
token_primary: ${{ secrets.CLAUDE_CODE_OAUTH_TOKEN }}
token_secondary: ${{ secrets.CLAUDE_CODE_OAUTH_TOKEN_B }}
active_slot: ${{ vars.CLAUDE_OAUTH_ACTIVE != '' && vars.CLAUDE_OAUTH_ACTIVE || 'primary' }}
- name: Run Claude Issue Triage
uses: ./.github/actions/claude-issue-triage-action
with:
claude_code_oauth_token: ${{ steps.oauth.outputs.token }}
claude_code_oauth_token: ${{ secrets.CLAUDE_CODE_OAUTH_TOKEN }}
github_token: ${{ steps.app-token.outputs.token }}
+35 -140
View File
@@ -33,8 +33,7 @@ on:
- claude-merge-gate
concurrency:
# Serialize workflow_run auto-dispatches (Core Tests / Claude Assistant fan-out).
group: claude-merge-gate-${{ github.repository }}-${{ github.event.inputs.pr_number || github.event.client_payload.pr_number || (github.event_name == 'workflow_run' && 'auto-dispatch') || 'scan' }}
group: claude-merge-gate-${{ github.repository }}-${{ github.event.inputs.pr_number || github.event.client_payload.pr_number || github.event.workflow_run.id || 'scan' }}
cancel-in-progress: false
env:
@@ -108,10 +107,6 @@ jobs:
return;
}
if (await mergeGate.shouldSkipMergeGateDispatch(github, owner, repo, prNumber, core)) {
return;
}
await github.rest.repos.createDispatchEvent({
owner,
repo,
@@ -201,26 +196,17 @@ jobs:
'**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');
const ctx = await mergeGate.loadPrContext(github, owner, repo, skipped[0].pr);
if (!mergeGate.hasRecentMergeGateScanComment(ctx.comments)) {
await github.rest.issues.createComment({
owner, repo, issue_number: skipped[0].pr, body,
});
}
await github.rest.issues.createComment({
owner, repo, issue_number: skipped[0].pr, body,
});
} else if (inputPr && candidates.length === 1) {
const prNum = candidates[0].pr_number;
const ctx = await mergeGate.loadPrContext(github, owner, repo, prNum);
if (!mergeGate.hasRecentMergeGateScanComment(ctx.comments)) {
await github.rest.issues.createComment({
owner, repo, issue_number: prNum,
body: '**Merge gate scan** — eligible for assessment. Claude merge gate will assess and may auto-merge on an APPROVE verdict.',
});
}
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, dispatchMergeGate: false }, core
);
await ps.syncOpenPullRequests(github, owner, repo, { maxPrs: 10 }, core);
claude-assess:
needs: scan-candidates
@@ -267,14 +253,6 @@ jobs:
- name: Stash merge gate helpers
run: cp .github/scripts/merge-gate.js /tmp/merge-gate.js
- name: Pick Claude OAuth token
id: oauth
uses: MervinPraison/github-automation-template/.github/actions/[email protected]
with:
token_primary: ${{ secrets.CLAUDE_CODE_OAUTH_TOKEN }}
token_secondary: ${{ secrets.CLAUDE_CODE_OAUTH_TOKEN_B }}
active_slot: ${{ vars.CLAUDE_OAUTH_ACTIVE != '' && vars.CLAUDE_OAUTH_ACTIVE || 'primary' }}
- name: Fetch PR branch
env:
PR_NUMBER: ${{ matrix.pr_number }}
@@ -284,14 +262,13 @@ jobs:
- name: Claude merge gate assessment (read-only)
id: assess
continue-on-error: true
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: ${{ steps.oauth.outputs.token }}
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'
@@ -311,7 +288,7 @@ jobs:
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 the relevant SDK (Python: praisonaiagents/praisonai; TypeScript: src/praisonai-ts/) — 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. FINAL architecture review must include the Phase 1 table with an explicit **SDK value** row.
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).
@@ -326,97 +303,15 @@ jobs:
Write
Replace
allowed_tools: |
mcp__github__add_issue_comment
mcp__github__get_pull_request
mcp__github__get_pull_request_files
mcp__github__get_pull_request_reviews
mcp__github__get_pull_request_status
mcp__github__get_issue
mcp__github__get_issue_comments
Glob
Grep
View
GlobTool
GrepTool
Read
timeout_minutes: 15
- name: Post Opus verdict from assess output if MCP missed
id: relay_verdict
if: always() && steps.assess.conclusion != 'skipped'
uses: actions/github-script@v7
with:
github-token: ${{ steps.app-token.outputs.token }}
script: |
const fs = require('fs');
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 on PR: ${existing}`);
return;
}
const outPath = `${process.env.GITHUB_WORKSPACE}/.claude-assess-output.jsonl`;
if (!fs.existsSync(outPath)) {
core.info('No assess output file to relay');
return;
}
const lines = fs.readFileSync(outPath, 'utf8').split('\n').filter(Boolean);
let verdict = null;
let rationale = '';
for (let i = lines.length - 1; i >= 0; i--) {
const line = lines[i];
if (line.includes('MERGE_GATE_VERDICT: APPROVE')) {
verdict = 'APPROVE';
rationale = line;
break;
}
if (line.includes('MERGE_GATE_VERDICT: BLOCK')) {
verdict = 'BLOCK';
rationale = line;
break;
}
try {
const evt = JSON.parse(line);
const text = JSON.stringify(evt);
if (text.includes('MERGE_GATE_VERDICT: APPROVE')) {
verdict = 'APPROVE';
rationale = text;
break;
}
if (text.includes('MERGE_GATE_VERDICT: BLOCK')) {
verdict = 'BLOCK';
rationale = text;
break;
}
} catch {
// Not JSON — keep scanning.
}
}
if (!verdict) {
core.info('Assess output had no MERGE_GATE_VERDICT to relay');
return;
}
const body = [
`MERGE_GATE_VERDICT: ${verdict}`,
'',
'Relayed from Opus merge gate assess output (GitHub MCP comment post was unavailable).',
].join('\n');
await github.rest.issues.createComment({
owner, repo, issue_number: prNumber, body,
});
core.info(`Relayed Opus verdict to PR comment: ${verdict}`);
- name: Post fallback verdict if Opus did not comment
- name: Post fallback BLOCK if Opus did not comment
id: fallback_verdict
if: always() && steps.assess.conclusion != 'skipped'
if: steps.assess.outcome != 'success'
uses: actions/github-script@v7
with:
github-token: ${{ steps.app-token.outputs.token }}
@@ -432,21 +327,20 @@ jobs:
ctx.comments, minCreatedAt, ctx.headPushedAt, { excludeAutomatedFallback: true }
);
if (existing) {
core.info(`Verdict already posted: ${existing}`);
core.info(`Opus verdict already posted: ${existing}`);
return;
}
const check = await mergeGate.evaluatePipelineQuiescent(
github, owner, repo, prNumber, core, { forMergeStep: true }
);
const verdict = check.ready ? 'APPROVE' : 'BLOCK';
const lines = [
`MERGE_GATE_VERDICT: ${verdict}`,
'MERGE_GATE_VERDICT: BLOCK',
'',
'Automated fallback — Opus merge gate did not post a PR comment.',
'Automated fallback — Opus merge gate assessment did not complete.',
];
if (check.ready) {
lines.push('All deterministic merge gates passed.');
lines.push('Deterministic gates passed, but Opus MERGE_GATE_VERDICT is required before merge.');
} else {
lines.push('Blockers:', ...check.reasons.map((r) => `- ${r}`));
}
@@ -454,10 +348,9 @@ jobs:
owner, repo, issue_number: prNumber,
body: lines.join('\n'),
});
core.info(`Posted fallback verdict: ${verdict}`);
core.info('Posted fallback BLOCK — Opus verdict required');
- name: Capture Opus MERGE_GATE_VERDICT
id: capture_verdict
- name: Require Opus MERGE_GATE_VERDICT
uses: actions/github-script@v7
with:
github-token: ${{ steps.app-token.outputs.token }}
@@ -473,14 +366,14 @@ jobs:
const verdict = mergeGate.findMergeGateVerdict(
comments, minCreatedAt, ctx.headPushedAt, { excludeAutomatedFallback: true }
);
core.setOutput('verdict', verdict || 'NONE');
if (!verdict) {
core.warning(
'Opus MERGE_GATE_VERDICT not posted on PR (GitHub MCP tools may be blocked). Merge waits for APPROVE.'
core.setFailed(
'Opus merge gate assessment must post MERGE_GATE_VERDICT on this PR (automated fallback APPROVE is not accepted).'
);
} else {
core.info(`Opus merge gate verdict: ${verdict}`);
return;
}
core.info(`Opus merge gate verdict: ${verdict}`);
core.setOutput('verdict', verdict);
- name: Remove merge gate active label
if: always()
@@ -501,6 +394,10 @@ jobs:
core.info(`Label claude-merge-gate-active already removed or missing on PR #${prNumber}`);
}
- name: Fail job if assessment failed
if: steps.assess.outcome == 'failure'
run: exit 1
merge-only:
needs: [scan-candidates, claude-assess]
if: |
@@ -555,12 +452,10 @@ jobs:
try {
const ctx = await mergeGate.loadPrContext(github, owner, repo, prNumber);
const { verdict } = await mergeGate.waitForMergeGateVerdict(
github, owner, repo, prNumber, {
headPushedAt: ctx.headPushedAt,
excludeAutomatedFallback: true,
core,
}
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'}`);
+10 -25
View File
@@ -100,19 +100,18 @@ jobs:
'',
'_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). TypeScript/JavaScript SDK fixes land in `src/praisonai-ts/` in this repo.'
'**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).'
].join('\n')
});
}
// --- Auto-trigger Claude for bug/enhancement reports ---
// --- Auto-trigger Claude for owner issues and actionable external bug/enhancement reports ---
const titleLower = (issue.title || '').toLowerCase();
const bodyRaw = issue.body || '';
const hasBugMarker = /#?\s*\[bug\]/i.test(issue.title || '') || /#?\s*\[bug\]/i.test(bodyRaw);
const hasActionableTitle = /^(\[[^\]]+\]|bug:|fix[:(]|feat:|ux:|enhancement:)/i.test(titleLower);
const isBugReport = labels.includes('bug') || hasBugMarker;
const isEnhancement = labels.includes('enhancement') && !labels.includes('question');
const autoClaude = isOwner || isBugReport || (hasActionableTitle && isEnhancement);
const autoClaude = isOwner || (hasActionableTitle && (
labels.includes('bug') ||
(labels.includes('enhancement') && !labels.includes('question'))
));
if (autoClaude) {
await github.rest.issues.addLabels({
issue_number: issue.number,
@@ -249,14 +248,6 @@ jobs:
fetch-depth: 0
token: ${{ steps.app-token.outputs.token }}
- name: Pick Claude OAuth token
id: oauth
uses: MervinPraison/github-automation-template/.github/actions/[email protected]
with:
token_primary: ${{ secrets.CLAUDE_CODE_OAUTH_TOKEN }}
token_secondary: ${{ secrets.CLAUDE_CODE_OAUTH_TOKEN_B }}
active_slot: ${{ vars.CLAUDE_OAUTH_ACTIVE != '' && vars.CLAUDE_OAUTH_ACTIVE || 'primary' }}
- name: Fetch PR branch and Setup Remote
if: steps.check_fork.outputs.is_pr == 'true'
env:
@@ -283,7 +274,7 @@ jobs:
GH_TOKEN: ${{ steps.check_fork.outputs.can_push_fork == 'true' && secrets.GH_TOKEN || steps.app-token.outputs.token }}
with:
allowed_bots: 'praisonai-triage-agent[bot]'
claude_code_oauth_token: ${{ steps.oauth.outputs.token }}
claude_code_oauth_token: ${{ secrets.CLAUDE_CODE_OAUTH_TOKEN }}
github_token: ${{ steps.app-token.outputs.token }}
model: claude-opus-4-8
trigger_phrase: "@claude"
@@ -302,7 +293,7 @@ jobs:
STEP 1 — READ GUIDELINES:
Read AGENTS.md to understand the architecture rules.
SCOPE: Python SDK (praisonaiagents, praisonai) and TypeScript SDK (src/praisonai-ts/) live in this monorepo. Do NOT modify src/praisonai-rust. For TS issues read src/praisonai-ts/AGENTS.md.
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):
@@ -314,7 +305,6 @@ jobs:
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.
7. TypeScript/JavaScript SDK → src/praisonai-ts/ in this monorepo (not praisonaiagents/).
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.
@@ -346,11 +336,9 @@ jobs:
gh pr create -R MervinPraison/<REPO_NAME> --head claude/issue-$ISSUE_NUMBER-$(date +%Y%m%d) --title "feat: <title>" --body "Fixes MervinPraison/PraisonAI#$ISSUE_NUMBER
<body>"
h) Comment on THIS PraisonAI issue with the external PR URL.
STEP 4 — TEST:
- For Python SDK changes: cd src/praisonai-agents && PYTHONPATH=. python -m pytest tests/ -x -q --timeout=30
- For TypeScript SDK changes: cd src/praisonai-ts && npm install && npm run build && npm test
- For SDK changes: cd src/praisonai-agents && PYTHONPATH=. python -m pytest tests/ -x -q --timeout=30
- For docs changes: verify files exist and are valid markdown/MDX
- Ensure no regressions
@@ -363,8 +351,6 @@ jobs:
Bash(conda:*)
Bash(pytest:*)
Bash(gh:*)
Bash(npm:*)
Bash(node:*)
Bash(python -m pytest:*)
Bash(python -m pip:*)
Bash(poetry:*)
@@ -384,10 +370,9 @@ jobs:
steps.check_fork.outputs.is_pr != 'true' &&
(github.event_name == 'issues' || github.event_name == 'issue_comment') &&
github.event.issue != null
continue-on-error: true
uses: actions/github-script@v7
with:
github-token: ${{ steps.app-token.outputs.token }}
github-token: ${{ secrets.GH_TOKEN }}
script: |
const path = require('path');
const chain = require(path.join(process.env.GITHUB_WORKSPACE, '.github/scripts/bot-pr-review-chain.js'));
-267
View File
@@ -1,267 +0,0 @@
# Build the desktop app for macOS, Windows and Linux, and attach it to the
# release.
#
# Releases carried no assets at all -- v4.7.1 shipped zero -- so there was
# nothing for anyone to download. The macOS half of this shipped first; this
# adds the other two, which were not merely missing from CI but impossible:
# the bundle targets were `["app", "dmg"]`, both macOS-only, so a Windows or
# Linux build produced zero artifacts and still exited zero.
#
# Unsigned, deliberately, on every platform. macOS signing needs a Developer ID
# and Windows signing now needs a hardware-backed certificate or a hosted
# signing service -- neither is in secrets. Shipping builds people can open
# past the warning is better than shipping none, and the release notes say so
# rather than letting Gatekeeper and SmartScreen say it for us.
name: Desktop release
on:
release:
types: [published]
workflow_dispatch:
inputs:
tag:
description: 'Existing release tag to attach the build to'
required: true
permissions:
contents: write
concurrency:
# Queue rather than cancel: a cancelled release build looks identical to a
# release that simply never produced assets, which is the bug being fixed.
group: desktop-release-${{ github.event.release.tag_name || inputs.tag }}
cancel-in-progress: false
jobs:
build:
strategy:
fail-fast: false
matrix:
include:
# macos-15, not macos-14: that image entered deprecation on
# 2026-07-06 and is fully unsupported from 2026-11-02, with brownout
# periods failing jobs before then. This is the only Apple-silicon
# leg, so losing it means no arm64 DMG at all.
- runner: macos-15 # Apple silicon
target: aarch64-apple-darwin
bundles: dmg
ext: dmg
asset: macos-apple-silicon
# macos-15-intel, not macos-13: that image was retired on
# 2025-12-04, so the leg would never schedule and the verify job
# below would correctly report a missing asset on every release,
# forever. macos-15-intel is GitHub's named x86_64 replacement.
- runner: macos-15-intel # Intel
target: x86_64-apple-darwin
bundles: dmg
ext: dmg
asset: macos-intel
- runner: windows-latest
target: x86_64-pc-windows-msvc
bundles: nsis
ext: exe
asset: windows-x64-setup
# ubuntu-22.04 rather than -latest on purpose: glibc is forward
# compatible only, so the build host sets the *oldest* distribution
# the .deb can run on. Building on 24.04 would produce a package that
# refuses to start on 22.04 and Debian 12 with a "GLIBC_2.38 not
# found" that no runtime flag can fix.
#
# This image begins deprecation on 2026-09-17 and is retired on
# 2027-04-17. When it goes, move to `ubuntu-latest` with
# `container: debian:12` rather than bumping the runner -- that keeps
# the glibc floor decided by us instead of by GitHub's image
# lifecycle.
- runner: ubuntu-22.04
target: x86_64-unknown-linux-gnu
bundles: deb
ext: deb
asset: linux-x64
runs-on: ${{ matrix.runner }}
steps:
- uses: actions/checkout@v4
- name: Install the Linux build dependencies
if: runner.os == 'Linux'
run: |
set -euo pipefail
# Retried: a degraded mirror otherwise burns the whole job and
# reports "cancelled", which reads as our failure rather than apt's.
for attempt in 1 2 3; do
sudo apt-get update && break || sleep 15
done
sudo apt-get install -y --no-install-recommends \
libwebkit2gtk-4.1-dev \
libappindicator3-dev \
librsvg2-dev \
libxdo-dev \
libssl-dev \
patchelf \
xdg-utils
# libappindicator3-dev, not the ayatana package: the .deb's generated
# Depends: follows whichever one the binary linked against, so the
# two must not be mixed between builds.
- uses: dtolnay/rust-toolchain@stable
with:
targets: ${{ matrix.target }}
- uses: swatinem/rust-cache@v2
with:
workspaces: src/praisonai-desktop/src-tauri -> target
# Saving the Windows target directory costs more minutes than the
# rebuild it saves.
save-if: ${{ runner.os != 'Windows' }}
- name: Install the Tauri CLI
shell: bash
# `|| true` swallowed a genuine install failure and the next step then
# died with an unrelated "no such command: tauri". It also behaved
# differently per leg, since Windows defaults to pwsh where `true` is
# not a command. Skip the install if it is already there; otherwise
# let a failure be a failure.
run: command -v cargo-tauri >/dev/null || cargo install tauri-cli --version '^2' --locked
- name: Set the desktop version from the release tag
shell: bash
env:
RELEASE_TAG: ${{ github.event.release.tag_name || inputs.tag }}
run: node src/praisonai-desktop/tools/set-release-version.mjs "$RELEASE_TAG"
- name: Build the bundle
working-directory: src/praisonai-desktop/src-tauri
run: cargo tauri build --target ${{ matrix.target }} --bundles ${{ matrix.bundles }}
- name: The Windows binary must carry the release version
if: runner.os == 'Windows'
shell: pwsh
working-directory: src/praisonai-desktop/src-tauri
env:
RELEASE_TAG: ${{ github.event.release.tag_name || inputs.tag }}
run: |
$expected = $env:RELEASE_TAG -replace '^v', ''
$core = ($expected -split '[-+]')[0]
$exe = "target/${{ matrix.target }}/release/praisonai-desktop.exe"
$version = (Get-Item $exe).VersionInfo
Write-Host "ProductVersion=$($version.ProductVersion) FileVersion=$($version.FileVersion)"
if ($version.ProductVersion -ne $expected) {
throw "ProductVersion $($version.ProductVersion) does not match $expected"
}
# Compare the three components that carry meaning, not the string.
#
# This gate blocked the v4.7.4 Windows build with
# FileVersion 4.7.4 does not match 4.7.4.0
# It appended ".0" and compared literally, but Windows reports what
# was stamped -- three parts here. The stamping was correct and the
# check was not, so the release shipped with no Windows installer at
# all: the one platform it was cut to fix.
#
# [version] normalises a missing fourth component to -1, so both
# "4.7.4" and "4.7.4.0" compare equal on major.minor.build.
$got = [version]$version.FileVersion
$want = [version]$core
if ($got.Major -ne $want.Major -or
$got.Minor -ne $want.Minor -or
$got.Build -ne $want.Build) {
throw "FileVersion $($version.FileVersion) does not match $core"
}
- name: The macOS bundle must carry a valid signature
if: runner.os == 'macOS'
working-directory: src/praisonai-desktop/src-tauri
run: |
set -euo pipefail
dmg="$(find "target/${{ matrix.target }}/release/bundle" -name '*.dmg' -print -quit)"
[ -n "$dmg" ] || { echo "no .dmg was produced"; exit 1; }
# Verify inside the DMG, not the .app beside it.
#
# Tauri deletes the app bundle once the DMG is built -- the build log
# says so plainly ("Cleaning .../bundle/macos/PraisonAI.app") -- so a
# gate that looked for the .app found nothing and failed every macOS
# leg. Reading the DMG is also the better check: it is the artifact
# people download, and the one that was broken.
#
# v4.7.2 shipped a DMG that macOS called "damaged and can't be
# opened" on every Mac. The cause was not the missing Developer ID:
# the only signature was the one rustc's linker puts on the bare
# executable, whose CodeDirectory declares a resource seal that an
# unsigned bundle does not have --
#
# Sealed Resources=none
# code has no resources but signature indicates they must be present
#
# That is an *invalid* signature, not an unsigned one, and macOS
# reports invalid as "damaged". Right-click -> Open cannot bypass it,
# so the instructions shipped alongside it could not work either.
mnt="$(mktemp -d)"
hdiutil attach -nobrowse -readonly -quiet -mountpoint "$mnt" "$dmg"
trap 'hdiutil detach "$mnt" -quiet || true' EXIT
app="$(find "$mnt" -maxdepth 1 -name '*.app' -print -quit)"
[ -n "$app" ] || { echo "the DMG contains no .app"; ls -la "$mnt"; exit 1; }
echo "verifying $app"
codesign --verify --deep --strict --verbose=2 "$app"
# Printed, not asserted: --verify already fails on the exact bundle
# that shipped, so a second check for the same thing would only be a
# second way to say it. This is here to make the log readable.
codesign -dv --verbose=2 "$app" 2>&1 | grep -E 'Sealed Resources|flags=' || true
- name: Name the artifact for the platform it runs on
id: artifact
shell: bash
working-directory: src/praisonai-desktop/src-tauri
run: |
set -euo pipefail
tag="${{ github.event.release.tag_name || inputs.tag }}"
root="target/${{ matrix.target }}/release/bundle"
found="$(find "$root" -name "*.${{ matrix.ext }}" -print -quit || true)"
# Fail loudly rather than uploading nothing: an empty release asset
# list is exactly the state this workflow exists to fix, and a bundler
# given a target it does not support exits zero having written none.
if [ -z "$found" ]; then
echo "no .${{ matrix.ext }} was produced under $root"
find "$root" -type f -print || echo "(the bundle directory does not exist)"
exit 1
fi
out="PraisonAI-${tag}-${{ matrix.asset }}.${{ matrix.ext }}"
mv "$found" "../$out"
echo "path=src/praisonai-desktop/$out" >> "$GITHUB_OUTPUT"
- name: Attach it to the release
shell: bash
env:
GH_TOKEN: ${{ github.token }}
run: |
gh release upload \
"${{ github.event.release.tag_name || inputs.tag }}" \
"${{ steps.artifact.outputs.path }}" --clobber
verify:
# A release with a missing platform is worse than an obviously failed
# build, because nobody notices. This says which one is absent.
needs: build
if: always()
runs-on: ubuntu-latest
steps:
- name: Check every platform produced an asset
env:
GH_TOKEN: ${{ github.token }}
TAG: ${{ github.event.release.tag_name || inputs.tag }}
run: |
set -euo pipefail
assets="$(gh release view "$TAG" --repo "$GITHUB_REPOSITORY" \
--json assets -q '.assets[].name')"
echo "$assets"
missing=""
for want in macos-apple-silicon macos-intel windows-x64-setup linux-x64; do
echo "$assets" | grep -q -- "$want" || missing="$missing $want"
done
if [ -n "$missing" ]; then
echo "::error::the release is missing:$missing"
exit 1
fi
echo "all four platform builds are attached"
-115
View File
@@ -1,115 +0,0 @@
# The desktop app's tests.
#
# These existed and ran nowhere: no workflow referenced praisonai-desktop, and
# the frontend suite could not even be installed -- jsdom was undeclared, so it
# ran only on machines that happened to have one further up the tree, at
# whatever version that happened to be.
name: desktop
on:
push:
branches: [main]
paths: ['src/praisonai-desktop/**', '.github/workflows/desktop.yml',
'.github/workflows/desktop-release.yml']
pull_request:
paths: ['src/praisonai-desktop/**', '.github/workflows/desktop.yml',
'.github/workflows/desktop-release.yml']
concurrency:
group: desktop-${{ github.ref }}
cancel-in-progress: true
defaults:
run:
working-directory: src/praisonai-desktop
jobs:
engine:
name: engine (${{ matrix.os }})
# The engine is the part that has to behave the same on all three, which is
# the entire point of the portability suite -- so it is run on all three.
runs-on: ${{ matrix.os }}
strategy:
fail-fast: false
matrix:
os: [ubuntu-22.04, macos-15, windows-latest]
steps:
- uses: actions/checkout@v4
- uses: actions/setup-python@v5
with:
python-version: '3.11'
- name: Run the engine tests
shell: bash
env:
# Never touch a real keychain on a shared runner.
PRAISONAI_KEYCHAIN_SERVICE: ai.praison.desktop.ci
run: |
set -euo pipefail
failed=0
for suite in engine/test_*.py; do
echo "::group::$suite"
python "$suite" -v || failed=1
echo "::endgroup::"
done
exit $failed
frontend:
name: frontend
runs-on: ubuntu-22.04
steps:
- uses: actions/checkout@v4
- uses: actions/setup-node@v4
with:
node-version: '22'
- run: npm ci
# `test:ci` is every suite except lifecycle, which drives real
# conversations against a live engine and a real model -- neither of
# which exists on a runner. It is excluded by name rather than left to
# skip quietly, so that a skipped test here is a genuine problem.
- name: Run the UI tests
# A suite that skips everything still exits 0 -- that is how thirteen
# tests came to look like a pass while proving nothing. So the skip
# count is asserted, not just the exit status.
run: |
set -euo pipefail
set -o pipefail
npm run test:ci 2>&1 | tee "$RUNNER_TEMP/ui.log"
skipped=$(grep -E '^. skipped ' "$RUNNER_TEMP/ui.log" | grep -oE '[0-9]+$' | head -1)
echo "skipped: ${skipped:-unknown}"
test "${skipped:-1}" -eq 0
shell:
name: shell (${{ matrix.os }})
runs-on: ${{ matrix.os }}
strategy:
fail-fast: false
matrix:
os: [ubuntu-22.04, macos-15, windows-latest]
defaults:
run:
working-directory: src/praisonai-desktop/src-tauri
steps:
- uses: actions/checkout@v4
- uses: dtolnay/rust-toolchain@stable
with:
components: clippy
- uses: Swatinem/rust-cache@v2
with:
workspaces: src/praisonai-desktop/src-tauri
# The Windows cache is large and slow enough to cost more than it saves.
save-if: ${{ runner.os != 'Windows' }}
- name: Install the Linux build dependencies
if: runner.os == 'Linux'
working-directory: .
run: |
sudo apt-get update
sudo apt-get install -y --no-install-recommends \
libwebkit2gtk-4.1-dev libappindicator3-dev librsvg2-dev \
libxdo-dev libssl-dev patchelf
- name: Test
# Debug info is the bulk of a Tauri target directory and nothing here
# reads a backtrace, so building without it keeps the runner's disk
# from filling on the Windows leg.
run: cargo test --config 'profile.test.debug=false' --config 'profile.dev.debug=false'
- name: Clippy
run: cargo clippy --all-targets -- -D warnings
+5 -8
View File
@@ -21,9 +21,6 @@ on:
- '.github/actions/install-monorepo-packages/**'
workflow_dispatch:
permissions:
contents: read
jobs:
cross-repo-integration:
runs-on: ubuntu-latest
@@ -44,13 +41,13 @@ jobs:
ref: main
- name: Set up Python
uses: actions/setup-python@v5
uses: actions/setup-python@v4
with:
python-version: '3.11'
- name: Install dependencies
run: python -m pip install --upgrade pip
- uses: ./PraisonAI/.github/actions/install-monorepo-packages
- uses: PraisonAI/.github/actions/install-monorepo-packages
with:
repo-root: PraisonAI/
wrapper-extras: ".[ui,dev]"
@@ -141,13 +138,13 @@ jobs:
ref: main
- name: Set up Python
uses: actions/setup-python@v5
uses: actions/setup-python@v4
with:
python-version: '3.11'
- name: Install dependencies
run: python -m pip install --upgrade pip
- uses: ./PraisonAI/.github/actions/install-monorepo-packages
- uses: PraisonAI/.github/actions/install-monorepo-packages
with:
repo-root: PraisonAI/
wrapper-extras: ".[ui,dev]"
@@ -165,4 +162,4 @@ jobs:
python -m pytest tests/integration/test_aiui_host_agentic.py -v
else
echo "OPENAI_API_KEY not available, skipping agentic tests"
fi
fi
-351
View File
@@ -1,351 +0,0 @@
# The mobile package's PLATFORM builds: a real iOS app and a real Android app.
#
# mobile.yml proves the crate type-checks for a phone (`cargo check` against
# the two mobile targets). This proves the two generated platform projects,
# src-tauri/gen/apple and src-tauri/gen/android, still turn that crate into an
# installable app -- which is a different thing, and the thing that had never
# happened: until #4673 neither project existed.
#
# What each job produces, and why that shape:
#
# ios-simulator -- an UNSIGNED arm64 simulator .app. A device build needs
# an Apple Developer Team and a signing identity, which are
# the maintainer's and not in this repo (bundle.iOS.
# developmentTeam is unset in tauri.conf.json). A simulator
# build needs neither, so it is the build that can run on
# every PR. It is not decoration: it links the Rust
# staticlib into the Xcode target, packages the webview
# into the bundle and exercises Info.plist, i.e. every step
# short of the certificate.
# android-apk -- a debug APK, arm64-v8a. Debug because a release APK
# needs a signing keystore, which is likewise the
# maintainer's; the debug keystore is generated on the
# runner. It installs on any arm64 Android 8.0+ device with
# `adb install`.
#
# Both jobs fail if the thing they exist to produce is missing. The bundler
# exits zero on a target it silently skipped (desktop-release.yml learned this
# the hard way), so "the step passed" is not evidence; "the file exists and
# contains the Rust library" is.
#
# The Xcode project is generated on the macOS runner the first time (this
# laptop has no Xcode, only the Command Line Tools) and then committed, so
# the init step is a no-op once gen/apple is in the tree. The Android project
# was generated locally and is committed; the same guard keeps that job
# honest if someone deletes it.
name: mobile platforms
on:
workflow_dispatch:
pull_request:
paths: &watched
- 'src/praisonai-mobile/**'
- 'src/praisonai-ts/src/**'
- '.github/workflows/mobile-platforms.yml'
# Without this, no platform build had ever run on main -- so a break
# introduced by two PRs that were each green apart could sit on main
# unnoticed. That is exactly what happened: #4737 branched from before
# #4727 added the `file:` dependency, so the two were never installed
# together until they had both landed.
push:
branches: [main]
paths: *watched
concurrency:
# Per-ref on a PR, per-SHA on main. This is the crux of the fix, not
# cancel-in-progress alone: a concurrency group holds at most ONE
# running run and ONE pending run, and a newer arrival always replaces
# the pending one -- cancel-in-progress: false spares only the RUNNING
# run, never the queued one. So with a single mobile-platforms-main
# group, three merges in one ~3-minute window would still drop the
# middle commit's run (it is only ever pending), which is precisely the
# blindness the push trigger was added to remove. Giving each main SHA
# its own group makes every commit a candidate release with its own
# answer, with nothing to contend for and so nothing to cancel.
group: mobile-platforms-${{ github.ref == 'refs/heads/main' && github.sha || github.ref }}
# On a PR, superseding an in-flight build is right: only the tip
# matters and these jobs cost ~3 minutes on two runners. On main each
# group has a single run, so this is a no-op there -- left true because
# the condition that mattered is now expressed in the group name above,
# and this keeps the PR behaviour explicit.
cancel-in-progress: ${{ github.ref != 'refs/heads/main' }}
defaults:
run:
working-directory: src/praisonai-mobile
jobs:
ios-simulator:
name: ios simulator (.app, unsigned)
runs-on: macos-15
steps:
- uses: actions/checkout@v4
- uses: actions/setup-node@v4
with:
node-version: '22.18'
cache: npm
cache-dependency-path: src/praisonai-mobile/package-lock.json
- uses: dtolnay/rust-toolchain@stable
with:
# Both: `tauri ios init` installs whatever it thinks is missing via
# rustup, and having them already present keeps that step quiet and
# deterministic. aarch64-apple-ios-sim is the one the build below
# actually links against.
targets: aarch64-apple-ios,aarch64-apple-ios-sim
- uses: Swatinem/rust-cache@v2
with:
workspaces: src/praisonai-mobile/src-tauri
key: ios-sim
- name: "Build praisonai-ts (the file: dependency)"
# praisonai-mobile depends on praisonai by `file:`, so `npm ci`
# here runs praisonai-ts's own `prepare` -> `rimraf dist`. On a
# fresh runner praisonai-ts has no node_modules, so rimraf is not
# installed and `npm ci` dies with code 127 before a single
# platform step runs. mobile.yml gives all four of its jobs this
# step; these two were written against the tree from before the
# dependency existed and never got it.
working-directory: src/praisonai-ts
run: |
npm install --no-audit --no-fund --legacy-peer-deps
npm run build
- run: npm ci
- name: Generate the Xcode project (only if gen/apple is not committed)
# `tauri ios init` renders the template and then runs `xcodegen`, a
# brew package the CLI would otherwise try to install itself, mid-run,
# with a prompt. Installing it up front is the same outcome without
# the prompt. cocoapods is only invoked when the config declares pods;
# it declares none.
run: |
set -euo pipefail
if [ -d src-tauri/gen/apple ]; then
echo "src-tauri/gen/apple is committed; not regenerating it"
exit 0
fi
brew list xcodegen >/dev/null 2>&1 || brew install xcodegen
npx tauri ios init --ci --skip-targets-install
- name: Put the real AppIcon set into the Xcode project
# `tauri ios init` renders the CLI's OWN placeholder AppIcon PNGs into
# gen/apple/Assets.xcassets, and nothing in the CLI ever replaces them:
# `tauri icon` writes to src-tauri/icons/ios/ and stops there (it wires
# up gen/android, but there is no iOS equivalent). So the copy is done
# here, and every filename matches one-for-one -- both sides are named
# by the same Contents.json.
#
# Idempotent, and it runs whether or not init just ran, so a
# regenerated project cannot silently ship Tauri's icon as ours.
run: |
set -euo pipefail
dest=src-tauri/gen/apple/Assets.xcassets/AppIcon.appiconset
test -d "$dest" || { echo "::error::$dest does not exist"; find src-tauri/gen/apple -maxdepth 3 -print; exit 1; }
cp src-tauri/icons/ios/*.png "$dest/"
ls "$dest" | wc -l
- name: Build the simulator app, unsigned
# --target aarch64-sim: the iphonesimulator SDK, arm64 (the runner is
# Apple silicon, and so is every Mac that will run the simulator).
# --no-sign: xcodebuild with CODE_SIGNING_ALLOWED=NO. For the
# simulator SDK the CLI then lifts PraisonAI.app straight out of the
# xcarchive instead of exporting an IPA (crates/tauri-cli/src/mobile/
# ios/build.rs, the `target.sdk == "iphonesimulator"` branch), which
# is exactly the artifact a simulator installs.
# --debug: the dev profile links in seconds rather than minutes, and a
# simulator build is never the one that ships.
run: npx tauri ios build --debug --target aarch64-sim --no-sign --ci
- name: Is there an app, and is the Rust inside it?
id: app
run: |
set -euo pipefail
root=src-tauri/gen/apple/build
# Printed before anything is asserted, so a failure here is
# diagnosable from the log alone rather than costing another run.
echo "--- what the build left behind"
find "$root" -maxdepth 3 -print 2>/dev/null | head -40 || echo "(no build directory)"
# Prefer the simulator export dir (build/arm64-sim, the `arch` of the
# aarch64-sim target); fall back to any .app so the error message can
# say what WAS built. The name is not hardcoded: it comes from
# productName via the CLI, and guessing it wrong is what failed here
# the first time.
app="$(find "$root" -type d -name '*.app' -path '*arm64-sim*' -print -quit 2>/dev/null || true)"
[ -n "$app" ] || app="$(find "$root" -type d -name '*.app' -print -quit 2>/dev/null || true)"
if [ -z "$app" ]; then
echo "::error::no .app was produced under $root"
exit 1
fi
echo "app: $app"
# The executable's name comes from the bundle itself for the same
# reason.
exe="$app/$(plutil -extract CFBundleExecutable raw "$app/Info.plist")"
test -f "$exe" || { echo "::error::$app has no executable"; ls -la "$app"; exit 1; }
file "$exe"
file "$exe" | grep -q 'arm64' || { echo "::error::the executable is not arm64"; exit 1; }
# iOS links the Rust in as a staticlib, so unlike Android there is no
# .so to look for -- the crate is INSIDE this binary, and its symbols
# are the only real evidence it got there. An .app that built without
# it would be the Swift template alone.
#
# Dumped to files rather than piped into `grep -q`: grep exits on the
# FIRST match, the dumper then dies of SIGPIPE, and `set -o pipefail`
# reports that as a failed pipeline -- so the check failed precisely
# BECAUSE it found what it was looking for. It cost a CI run.
nm -a "$exe" > "$RUNNER_TEMP/symbols.txt" 2>/dev/null || true
strings -a "$exe" > "$RUNNER_TEMP/strings.txt" 2>/dev/null || true
if grep -qi 'praisonai_mobile\|start_app' "$RUNNER_TEMP/symbols.txt" \
|| grep -qi 'praisonai_mobile' "$RUNNER_TEMP/strings.txt"; then
echo "the Rust crate is linked into the executable"
else
echo "::error::the Rust library is not linked into $exe"
exit 1
fi
# The frontend is embedded in that same binary by generate_context!,
# not copied into the bundle as a resource, so it is checked the same
# way rather than by looking for an index.html that is never there.
plutil -p "$app/Info.plist" | grep -E 'CFBundleIdentifier|CFBundleShortVersionString|MinimumOSVersion|UIDeviceFamily'
test -f "$app/Assets.car" || echo "note: no compiled asset catalog in the bundle"
du -sh "$app"
# ditto, not zip: it keeps the bundle's symlinks and modes, which is
# the difference between an .app the simulator installs and one it
# rejects as an invalid bundle.
ditto -c -k --keepParent "$app" "$RUNNER_TEMP/PraisonAI-ios-simulator.app.zip"
ls -la "$RUNNER_TEMP/PraisonAI-ios-simulator.app.zip"
- name: Upload the simulator app
uses: actions/upload-artifact@v4
with:
name: PraisonAI-ios-simulator-app
path: ${{ runner.temp }}/PraisonAI-ios-simulator.app.zip
if-no-files-found: error
retention-days: 30
- name: Package gen/apple for committing
# always(): the project is generated by `init`, so it is worth having
# even on a run whose BUILD failed -- that is exactly the run where
# someone needs to look at it.
if: always()
# Only what `git add src-tauri/gen/apple` would take: the template's
# own .gitignore excludes build/, xcuserdata/ and Externals/, and this
# respects it instead of re-listing them here. Nothing to upload when
# the project was already committed -- the guard above skipped init.
run: |
set -euo pipefail
files="$(git ls-files --others --exclude-standard src-tauri/gen/apple || true)"
if [ -z "$files" ]; then
echo "gen/apple is tracked already; nothing to package"
exit 0
fi
echo "$files" | tar -czf "$RUNNER_TEMP/gen-apple.tgz" -T -
echo "$files" | wc -l
ls -la "$RUNNER_TEMP/gen-apple.tgz"
- name: Upload gen/apple (only on the run that generated it)
if: always()
uses: actions/upload-artifact@v4
with:
name: gen-apple
path: ${{ runner.temp }}/gen-apple.tgz
if-no-files-found: ignore
retention-days: 30
android-apk:
name: android apk (debug, arm64)
runs-on: ubuntu-22.04
steps:
- uses: actions/checkout@v4
- uses: actions/setup-node@v4
with:
node-version: '22.18'
cache: npm
cache-dependency-path: src/praisonai-mobile/package-lock.json
- uses: actions/setup-java@v4
with:
# 17, not the runner's default 21 or a laptop's 25: Gradle 8.14.3's
# Groovy front end rejects class files newer than it knows
# ("Unsupported class file major version 69" on JDK 25), and 17 is
# what AGP 8.11 documents.
distribution: temurin
java-version: '17'
- uses: android-actions/setup-android@v3
with:
# What gen/android/app/build.gradle.kts declares (compileSdk 36),
# plus the build-tools AGP pairs with it. Anything else AGP needs it
# downloads itself; the licences are accepted by this action.
packages: 'platform-tools platforms;android-36 build-tools;36.0.0'
- uses: nttld/setup-ndk@v1
id: ndk
with:
# r28c = 28.2.13676358, the NDK gen/android was generated and first
# built with.
ndk-version: r28c
add-to-path: false
- uses: dtolnay/rust-toolchain@stable
with:
targets: aarch64-linux-android
- uses: Swatinem/rust-cache@v2
with:
workspaces: src/praisonai-mobile/src-tauri
key: android-apk
- name: "Build praisonai-ts (the file: dependency)"
# praisonai-mobile depends on praisonai by `file:`, so `npm ci`
# here runs praisonai-ts's own `prepare` -> `rimraf dist`. On a
# fresh runner praisonai-ts has no node_modules, so rimraf is not
# installed and `npm ci` dies with code 127 before a single
# platform step runs. mobile.yml gives all four of its jobs this
# step; these two were written against the tree from before the
# dependency existed and never got it.
working-directory: src/praisonai-ts
run: |
npm install --no-audit --no-fund --legacy-peer-deps
npm run build
- run: npm ci
- name: Generate the Android project (only if gen/android is not committed)
env:
NDK_HOME: ${{ steps.ndk.outputs.ndk-path }}
run: |
set -euo pipefail
if [ -d src-tauri/gen/android ]; then
echo "src-tauri/gen/android is committed; not regenerating it"
exit 0
fi
npx tauri android init --ci --skip-targets-install
- name: Build the debug APK
env:
NDK_HOME: ${{ steps.ndk.outputs.ndk-path }}
# --target aarch64 only: every phone sold in the last several years is
# arm64-v8a, and one target keeps the Rust build to one link. The
# `universal` in the output path is Gradle's name for "the APK that is
# not split per ABI", not a claim about what is inside it.
run: npx tauri android build --debug --apk --target aarch64 --ci
- name: Is there an APK, and is the Rust inside it?
run: |
set -euo pipefail
root=src-tauri/gen/android/app/build/outputs/apk
apk="$(find "$root" -name '*.apk' -print -quit || true)"
if [ -z "$apk" ]; then
echo "::error::no .apk was produced under $root"
find "$root" -type f -print 2>/dev/null || echo "(the outputs directory does not exist)"
exit 1
fi
echo "apk: $apk"
ls -la "$apk"
unzip -l "$apk" | grep -q 'lib/arm64-v8a/libpraisonai_mobile_lib.so' \
|| { echo "::error::$apk does not contain lib/arm64-v8a/libpraisonai_mobile_lib.so"; unzip -l "$apk" | head -40; exit 1; }
unzip -l "$apk" | grep -E 'lib/|AndroidManifest|classes.dex' | head
cp "$apk" "$RUNNER_TEMP/PraisonAI-android-debug-arm64.apk"
- name: Upload the APK
uses: actions/upload-artifact@v4
with:
name: PraisonAI-android-debug-arm64-apk
path: ${{ runner.temp }}/PraisonAI-android-debug-arm64.apk
if-no-files-found: error
retention-days: 30
-164
View File
@@ -1,164 +0,0 @@
# The mobile package's WEB build: built, booted in a real browser, and
# deployed to GitHub Pages.
#
# mobile.yml proves the package's tests pass. This workflow proves the thing
# that ships to a browser actually ships: dist/ is built, served under the
# repository subpath and driven through first paint, install, and an offline
# reload by tools/web-boot.test.mjs, then published. A PR gets the build and
# the proof; only main deploys.
#
# One setting is outside this file's reach: the repository's Pages source must
# be "GitHub Actions" (Settings -> Pages -> Build and deployment -> Source).
# Until a human turns that on, the deploy job SKIPS with a notice rather than
# failing -- a red main every push because of a setting no workflow can set
# would train people to ignore the mobile checks, which is how the last silent
# breakage in this package survived.
name: mobile web
on:
push:
branches: [main]
paths: &watched
- 'src/praisonai-mobile/**'
- '.github/workflows/mobile-web.yml'
# `praisonai` is a `file:` link to ../praisonai-ts, and the web bundle is
# built FROM it -- so drift on that side changes what ships to a browser
# and must trigger this gate. mobile.yml watches these same paths for the
# same reason; a web gate that watched only praisonai-mobile would go
# quiet exactly when the dependency it bundles moved.
- 'src/praisonai-ts/src/**'
- 'src/praisonai-ts/scripts/**'
- 'src/praisonai-ts/package.json'
pull_request:
paths: *watched
permissions:
contents: read
defaults:
run:
working-directory: src/praisonai-mobile
jobs:
build:
name: build and boot
runs-on: ubuntu-22.04
concurrency:
group: mobile-web-build-${{ github.ref }}
cancel-in-progress: true
steps:
- uses: actions/checkout@v4
- uses: actions/setup-node@v4
with:
node-version: '22.18'
cache: npm
cache-dependency-path: src/praisonai-mobile/package-lock.json
# `praisonai` is a `file:` link to ../praisonai-ts, so its dist/ must
# exist before this package can even INSTALL: npm runs the linked
# package's prepare/prebuild, which fails without its own node_modules.
# `npm install`, not `npm ci`: praisonai-ts gitignores its lockfile.
# `--legacy-peer-deps` for the bedrock-agentcore -> @strands-agents/sdk
# peer conflict, exactly as mobile.yml and praisonai-ts-webview.yml do.
- name: "Build praisonai-ts (the file: dependency)"
working-directory: src/praisonai-ts
run: |
npm install --no-audit --no-fund --legacy-peer-deps
npm run build
- run: npm ci
- name: Cache the Playwright browser
uses: actions/cache@v4
with:
path: ~/.cache/ms-playwright
key: playwright-${{ runner.os }}-${{ hashFiles('src/praisonai-mobile/package-lock.json') }}
- name: Install Chromium for the boot proof
run: npx playwright install --with-deps chromium
- name: Build
run: npm run build
- name: Boot proof
# Serves dist/ under /PraisonAI/ in headless Chromium: composer and
# Send render, manifest served as application/manifest+json, service
# worker activates with the subpath as scope, an offline reload still
# renders, and an injected inline script is blocked by the CSP.
run: npm run test:web
- name: dist contents
run: ls -lR dist
- uses: actions/upload-artifact@v4
with:
name: mobile-web-dist
path: src/praisonai-mobile/dist
if-no-files-found: error
- uses: actions/upload-pages-artifact@v3
if: github.event_name == 'push' && github.ref == 'refs/heads/main'
with:
path: src/praisonai-mobile/dist
# The readiness check is its OWN job, and deliberately declares no
# `environment:`. A job that names `environment: github-pages` cannot START
# until that environment exists, so when Pages is off the runner fails the
# job outright -- zero steps, about one second -- and every carefully
# written skip inside it is unreachable. Measured: run 33730322658 on main,
# "deploy to GitHub Pages" failed with steps: 0.
#
# Splitting the decision out means the check runs with no preconditions and
# the environment-bearing job is never scheduled unless it can succeed.
pages-ready:
name: is GitHub Pages enabled?
if: github.event_name == 'push' && github.ref == 'refs/heads/main'
needs: build
runs-on: ubuntu-22.04
permissions:
contents: read
# `gh api repos/<owner>/<repo>/pages` needs Pages read. Without it the
# request is rejected on a private repo, `2>/dev/null || echo '{}'`
# swallows the error to `{}`, build_type falls to "none", and the deploy
# SKIPS even though Pages is on -- the exact silent skip this file exists
# to prevent. `contents: read` alone leaves this permission at `none`.
pages: read
outputs:
ready: ${{ steps.check.outputs.ready }}
steps:
# Pages cannot be enabled from a workflow, so this reports the setting
# rather than demanding it. `ready` false SKIPS the deploy with a
# notice; it does not fail the run. deploy-pages would otherwise fail
# with a bare 404 that says nothing about which setting is missing.
- name: Is the Pages source "GitHub Actions"?
id: check
env:
GH_TOKEN: ${{ github.token }}
working-directory: .
run: |
site=$(gh api "repos/${{ github.repository }}/pages" 2>/dev/null || echo '{}')
build_type=$(echo "$site" | jq -r '.build_type // "none"')
cname=$(echo "$site" | jq -r '.cname // ""')
echo "build_type=$build_type cname=${cname:-<none>}"
if [ "$build_type" != "workflow" ]; then
echo "::notice::Skipping the Pages deploy: Pages is not set to build from GitHub Actions (build_type=$build_type). A repository admin must set it at https://github.com/${{ github.repository }}/settings/pages -> Build and deployment -> Source: GitHub Actions. The built site is attached to this run as the mobile-web-dist artifact."
echo "ready=false" >> "$GITHUB_OUTPUT"
exit 0
fi
if [ -n "$cname" ]; then
echo "::notice::Skipping the Pages deploy: a custom domain ($cname) is set, so the app would be served there rather than at the github.io URL."
echo "ready=false" >> "$GITHUB_OUTPUT"
exit 0
fi
echo "ready=true" >> "$GITHUB_OUTPUT"
deploy:
name: deploy to GitHub Pages
needs: pages-ready
if: needs.pages-ready.outputs.ready == 'true'
runs-on: ubuntu-22.04
permissions:
pages: write
id-token: write
environment:
name: github-pages
url: ${{ steps.deployment.outputs.page_url }}
concurrency:
# Never cancel a deployment in flight; queue behind it instead.
group: pages
cancel-in-progress: false
steps:
- uses: actions/configure-pages@v5
- uses: actions/deploy-pages@v4
id: deployment
-263
View File
@@ -1,263 +0,0 @@
# The mobile package's tests.
#
# Written at the same time as the package, deliberately. praisonai-desktop's
# suite existed and ran nowhere for months because no workflow referenced it,
# and a package whose tests never run in CI is a package whose tests are
# decoration -- the 523 here would go stale silently.
#
# Four gates, and they catch different things:
#
# typecheck -- the boundary between erasable and non-erasable TypeScript.
# node:test strips types rather than compiling, so an enum or
# a constructor parameter property is a runtime parse error at
# import; `erasableSyntaxOnly` turns that into a typecheck
# failure at the file that caused it.
# boundaries -- the two seams. Only engines/src/praisonai-ts may import
# 'praisonai'; only adapters/src/tauri may import @tauri-apps.
# These are the whole reason the package is swappable, and a
# rule enforced only by review stops being enforced.
# test -- the suite itself.
# bundle gate -- webview compatibility. This is the one a normal test run
# CANNOT do: node:test runs in Node, where a `crypto` import
# and a top-level `process.env` both work fine, and both kill
# a webview bundle at import time.
name: mobile
on:
push:
branches: [main]
paths: &watched
- 'src/praisonai-mobile/**'
- '.github/workflows/mobile.yml'
# The `upstream parity` job below typechecks the REAL praisonai-ts Agent
# against the structural contract in engines/src/praisonai-ts/agent-api.ts.
# Watching only praisonai-mobile made that gate fire when the CONSUMER
# changed and stay silent when the thing it watches did -- so upstream
# drift landed on main unchecked. Verified on 71197fa80, which edited
# src/praisonai-ts/src/agent/simple.ts: no parity check ran on it.
- 'src/praisonai-ts/src/**'
# And the pieces of praisonai-ts that decide what `praisonai/mobile`
# RESOLVES to through the file: link -- the esm shim shapes dist/esm.
- 'src/praisonai-ts/scripts/**'
- 'src/praisonai-ts/package.json'
pull_request:
paths: *watched
concurrency:
group: mobile-${{ github.ref }}
cancel-in-progress: true
defaults:
run:
working-directory: src/praisonai-mobile
jobs:
check:
name: check (node ${{ matrix.node }})
runs-on: ubuntu-22.04
strategy:
fail-fast: false
matrix:
# 22.18 is the floor declared in package.json -- tested because a
# declared floor nobody runs is a guess. 24 is the forward check:
# native type-stripping is the feature this package depends on most,
# and it is exactly the kind of thing a major bump changes.
node: ['22.18', '24']
steps:
- uses: actions/checkout@v4
- uses: actions/setup-node@v4
with:
node-version: ${{ matrix.node }}
cache: npm
cache-dependency-path: src/praisonai-mobile/package-lock.json
# `praisonai` is a `file:` link to ../praisonai-ts (see praisonai-mobile's
# package.json for why), so its dist/ must exist before this package can
# resolve `praisonai/mobile`. `npm install`, not `npm ci`: praisonai-ts
# gitignores its lockfile. `--legacy-peer-deps` for the
# bedrock-agentcore -> @strands-agents/sdk peer conflict, exactly as
# praisonai-ts-webview.yml does.
- name: "Build praisonai-ts (the file: dependency)"
working-directory: src/praisonai-ts
run: |
npm install --no-audit --no-fund --legacy-peer-deps
npm run build
- run: npm ci
- name: Cache the Playwright browser
uses: actions/cache@v4
with:
path: ~/.cache/ms-playwright
key: playwright-${{ runner.os }}-${{ hashFiles('src/praisonai-mobile/package-lock.json') }}
- name: Install Chromium for the boot proof
# `npm test` includes tools/web-boot.test.mjs, which loads the built
# dist/ in a real browser. It fails rather than skips without one.
run: npx playwright install --with-deps chromium
- name: Typecheck
run: npm run typecheck
- name: Layer boundaries
run: npm run boundaries
- name: Tests
run: npm test
- name: Bundle gate fixtures
# Runs the gate's own suite, which proves each check can FAIL -- a
# build check that has only ever seen clean input is a check nobody
# knows the state of.
run: npm run test:bundle
upstream-parity:
name: upstream parity
# Its own job so drift from the real Agent is visible in the checks list
# rather than buried in another job's log.
#
# It needs only THIS package's install. praisonai-ts's own dependencies are
# not needed here (the `check` job installs them, with --legacy-peer-deps,
# to build the file: dependency): every member the check looks at is
# declared locally in simple.ts. That is verified rather than assumed:
# with praisonai-ts's node_modules moved aside, injected drift is still
# caught as TS2741.
runs-on: ubuntu-22.04
steps:
- uses: actions/checkout@v4
- uses: actions/setup-node@v4
with:
node-version: '22.18'
cache: npm
cache-dependency-path: src/praisonai-mobile/package-lock.json
- name: "Build praisonai-ts (the file: dependency)"
working-directory: src/praisonai-ts
run: |
npm install --no-audit --no-fund --legacy-peer-deps
npm run build
- run: npm ci
- name: Does the real Agent still satisfy PraisonAgent?
# Skips loudly if the praisonai-ts checkout is missing, rather than
# passing quietly -- a check that silently stops covering anything is
# worse than no check.
run: npm run check:upstream
shell:
name: rust shell (${{ matrix.os }})
# The Rust crate had 14 tests and no job running them -- the same failure
# this workflow's header says it was created to prevent, one language over.
#
# Both platforms, because the crate is cfg-heavy: the back-gesture fallback
# is #[cfg(target_os = "android")] / ios / not(mobile), and a cfg mistake
# compiles perfectly on whichever host you happened to try.
runs-on: ${{ matrix.os }}
strategy:
fail-fast: false
matrix:
os: [ubuntu-22.04, macos-15]
defaults:
run:
working-directory: src/praisonai-mobile/src-tauri
steps:
- uses: actions/checkout@v4
- uses: actions/setup-node@v4
with:
node-version: '22.18'
cache: npm
cache-dependency-path: src/praisonai-mobile/package-lock.json
- uses: dtolnay/rust-toolchain@stable
with:
components: clippy
- uses: Swatinem/rust-cache@v2
with:
workspaces: src/praisonai-mobile/src-tauri
- name: Install the Linux build dependencies
if: runner.os == 'Linux'
working-directory: .
run: |
sudo apt-get update
sudo apt-get install -y --no-install-recommends \
libwebkit2gtk-4.1-dev librsvg2-dev libxdo-dev libssl-dev patchelf
# generate_context! expands frontendDist (../dist) at COMPILE time, and
# dist/ is gitignored -- absent on a fresh checkout. Without this the
# crate cannot compile and neither test nor clippy below ever runs.
# `praisonai` is a `file:` link to ../praisonai-ts (see praisonai-mobile's
# package.json for why), so its dist/ must exist before this package can
# resolve `praisonai/mobile`. `npm install`, not `npm ci`: praisonai-ts
# gitignores its lockfile. `--legacy-peer-deps` for the
# bedrock-agentcore -> @strands-agents/sdk peer conflict, exactly as
# praisonai-ts-webview.yml does.
- name: "Build praisonai-ts (the file: dependency)"
working-directory: src/praisonai-ts
run: |
npm install --no-audit --no-fund --legacy-peer-deps
npm run build
- name: Build the webview (creates ../dist for generate_context!)
working-directory: src/praisonai-mobile
run: |
npm ci
npm run build
# The pure-logic tests: back-gesture arbitration, the lifecycle mapping,
# and the event-name contract. None of them needs a phone.
- name: Test
run: cargo test
- name: Clippy
run: cargo clippy --all-targets -- -D warnings
# ------------------------------------------------------------------
# The mobile targets, which nothing compiled.
#
# `src/lib.rs` is `#[cfg_attr(mobile, tauri::mobile_entry_point)]`, and
# `tauri_build::build()` emits `cargo:rustc-cfg=mobile` only for android and
# ios targets. Both legs of `rust shell` above are HOST targets, so that
# attribute -- the one that generates the Android JNI symbol and the iOS
# start_app symbol -- expanded exactly zero times in CI, and neither did the
# `#[cfg(target_os = "android")]` / `ios` arms of `commands.rs`. The job
# above says it covers cfg mistakes; it covers the ones in `shell/`, not
# these.
#
# `cargo check`, not `build`: it type-checks and macro-expands under the
# mobile cfg, which is the thing that was never done, and needs no NDK and no
# Xcode project. Verified at 18s for the android target.
# ------------------------------------------------------------------
cross-check:
name: cross-check (${{ matrix.target }})
runs-on: ${{ matrix.os }}
strategy:
fail-fast: false
matrix:
include:
- target: aarch64-linux-android
os: ubuntu-22.04
- target: aarch64-apple-ios
os: macos-15
defaults:
run:
working-directory: src/praisonai-mobile/src-tauri
steps:
- uses: actions/checkout@v4
- uses: actions/setup-node@v4
with:
node-version: '22.18'
cache: npm
cache-dependency-path: src/praisonai-mobile/package-lock.json
- uses: dtolnay/rust-toolchain@stable
with:
targets: ${{ matrix.target }}
- uses: Swatinem/rust-cache@v2
with:
workspaces: src/praisonai-mobile/src-tauri
key: ${{ matrix.target }}
# generate_context! expands frontendDist at COMPILE time and dist/ is
# gitignored, so the crate cannot be checked without this -- the same
# reason the job above needs it.
# `praisonai` is a `file:` link to ../praisonai-ts (see praisonai-mobile's
# package.json for why), so its dist/ must exist before this package can
# resolve `praisonai/mobile`. `npm install`, not `npm ci`: praisonai-ts
# gitignores its lockfile. `--legacy-peer-deps` for the
# bedrock-agentcore -> @strands-agents/sdk peer conflict, exactly as
# praisonai-ts-webview.yml does.
- name: "Build praisonai-ts (the file: dependency)"
working-directory: src/praisonai-ts
run: |
npm install --no-audit --no-fund --legacy-peer-deps
npm run build
- name: Build the webview (creates ../dist for generate_context!)
working-directory: src/praisonai-mobile
run: |
npm ci
npm run build
- name: Does the crate still expand and type-check for a phone?
run: cargo check --lib --target ${{ matrix.target }}
-106
View File
@@ -1,106 +0,0 @@
name: Parity Gate
# Validates Python <-> TypeScript SDK parity on pull requests and FAILS on drift.
#
# Two named checks, so each kind of drift is visible in the checks list:
# names - the exported-name tracker (PARITY.md / FEATURE_PARITY_TRACKER.json)
# must be regenerated in the PR when the public surface changes.
# behaviour - options accepted for parity but not yet acted on; a ratchet,
# so the count may fall and never rise.
# signatures - constructor/method parameters of the curated surfaces in
# src/praisonai/praisonai/_dev/parity/signatures/surface.yaml must
# match (after camelCase/alias/flattening rules) or be waived with a
# reason in waivers.yaml. Stale or expired waivers also fail.
#
# The regenerate-and-commit job stays in update-parity-tracker.yml (push to main).
# This workflow never commits; it only reports.
on:
pull_request:
paths:
- 'src/praisonai-agents/praisonaiagents/**/*.py'
- 'src/praisonai-ts/src/**/*.ts'
- 'src/praisonai-rust/praisonai/src/**/*.rs'
- 'src/praisonai/praisonai/_dev/parity/**'
- 'src/praisonai/praisonai/cli/features/**'
# The generator the `names` job runs. Editing it changed what the gate
# measured without the gate running.
- 'src/praisonai/scripts/**'
- 'src/praisonai-ts/PARITY.md'
- 'src/praisonai-ts/FEATURE_PARITY_TRACKER.json'
- 'src/praisonai-ts/SIGNATURE_PARITY.md'
- 'src/praisonai-ts/signature-parity.json'
# The behaviour baseline itself. These two carry the ratchet floor, so a
# pull request that edited only them raised the floor with no job running.
- 'src/praisonai-ts/BEHAVIOUR_PARITY.md'
- 'src/praisonai-ts/behaviour-parity.json'
- 'src/praisonai-rust/PARITY.md'
- 'src/praisonai-rust/FEATURE_PARITY_TRACKER.json'
- '.github/workflows/parity-gate.yml'
workflow_dispatch:
permissions:
contents: read
jobs:
names:
name: names (exported-symbol tracker up to date)
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v4
- uses: actions/setup-python@v5
with:
python-version: '3.11'
- run: pip install pyyaml
- name: Tracker files match the sources
run: |
if ! python3 src/praisonai/scripts/generate_parity_tracker.py --check; then
echo "::error::Parity tracker is out of date. Run: python3 src/praisonai/scripts/generate_parity_tracker.py and commit src/praisonai-ts/PARITY.md, FEATURE_PARITY_TRACKER.json and the Rust pair."
exit 1
fi
signatures:
name: signatures (constructor and method parameters)
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v4
- uses: actions/setup-python@v5
with:
python-version: '3.11'
- uses: actions/setup-node@v4
with:
node-version: '22'
- run: pip install pyyaml
- name: Install the TypeScript compiler only
# praisonai-ts's full dependency tree is not needed (and does not
# install cleanly); the extractor needs only the `typescript` package.
run: |
mkdir -p "$RUNNER_TEMP/parity-ts"
npm install --prefix "$RUNNER_TEMP/parity-ts" --no-audit --no-fund [email protected]
echo "PARITY_TS_NODE_MODULES=$RUNNER_TEMP/parity-ts/node_modules" >> "$GITHUB_ENV"
- name: Signatures match, or are waived with a reason
env:
PYTHONPATH: src/praisonai
run: |
if ! python3 -m praisonai._dev.parity.signatures --check; then
echo "::error::Signature parity failed. See the output above for the surface and parameter. Fix the TypeScript side, or add a waiver with a reason to src/praisonai/praisonai/_dev/parity/signatures/waivers.yaml, then run: PYTHONPATH=src/praisonai python3 -m praisonai._dev.parity.signatures --write"
exit 1
fi
behaviour:
name: behaviour (options accepted but not acted on)
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v4
- uses: actions/setup-python@v5
with:
python-version: '3.11'
- run: pip install pyyaml
- name: The count of ignored options has not grown
env:
PYTHONPATH: src/praisonai
run: |
if ! python3 -m praisonai._dev.parity.behaviour --check; then
echo "::error::An option accepted for Python parity is not acted on, and the total grew. The name and signature gates cannot see this: they check that a parameter EXISTS. Implement the behaviour and delete its entry from src/praisonai-ts/src/utils/parity-notice.ts, then run: PYTHONPATH=src/praisonai python3 -m praisonai._dev.parity.behaviour --write"
exit 1
fi
+1 -1
View File
@@ -1,6 +1,6 @@
name: Pipeline Status Sync
# Sync pipeline/* stage and blocker labels on open PRs (fork heads included; merge gate only for upstream branches).
# Sync pipeline/* stage and blocker labels on open internal PRs.
on:
schedule:
+2 -26
View File
@@ -16,6 +16,8 @@ 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' ||
@@ -30,28 +32,7 @@ jobs:
)
steps:
- name: Check reviewer configuration
id: config
env:
HAS_APP_CREDENTIALS: ${{ secrets.PRAISONAI_APP_ID != '' && secrets.PRAISONAI_APP_PRIVATE_KEY != '' }}
OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }}
run: |
echo "configured=$HAS_APP_CREDENTIALS" >> "$GITHUB_OUTPUT"
openai_ready=true
if [ -z "$OPENAI_API_KEY" ] || [ "$OPENAI_API_KEY" = "not-needed" ]; then
openai_ready=false
if [ "$HAS_APP_CREDENTIALS" = "true" ]; then
echo "::notice::Skipping PraisonAI PR review: OPENAI_API_KEY is missing or a placeholder."
fi
fi
if [ "$HAS_APP_CREDENTIALS" = "true" ] && [ "$openai_ready" = "true" ]; then
echo "ready=true" >> "$GITHUB_OUTPUT"
else
echo "ready=false" >> "$GITHUB_OUTPUT"
fi
- name: Determine checkout ref
if: steps.config.outputs.ready == 'true'
id: dest
env:
ISSUE_NUMBER: ${{ github.event.issue.number }}
@@ -67,7 +48,6 @@ jobs:
fi
- name: Checkout Repository
if: steps.config.outputs.ready == 'true'
uses: actions/checkout@v4
with:
persist-credentials: false
@@ -75,7 +55,6 @@ jobs:
fetch-depth: 0
- name: Generate GitHub App Token
if: steps.config.outputs.ready == 'true'
id: generate_token
uses: tibdex/github-app-token@v2
with:
@@ -83,17 +62,14 @@ jobs:
private_key: ${{ secrets.PRAISONAI_APP_PRIVATE_KEY }}
- name: Set up Python
if: steps.config.outputs.ready == 'true'
uses: actions/setup-python@v5
with:
python-version: '3.11'
- name: Install PraisonAI
if: steps.config.outputs.ready == 'true'
run: pip install "praisonai[all]"
- name: Run PraisonAI PR Review
if: steps.config.outputs.ready == 'true'
env:
GITHUB_TOKEN: ${{ steps.generate_token.outputs.token }}
OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }}
-70
View File
@@ -1,70 +0,0 @@
# Does praisonai-ts still pass its own tests?
#
# It has a suite -- 2,000+ tests -- and until now nothing ran it. The only
# workflow with `working-directory: src/praisonai-ts` builds the package and
# checks the webview bundle; the two other mentions of `npm test` in this
# directory are a comment and a line of prose telling a reviewer to run it by
# hand. So the suite was green the way an unread report is green.
#
# That mattered the moment the suite grew: PR #4755 added ~880 tests for the
# Python-parity port and not one of them would have run here. A test nobody
# executes is worse than no test, because it is counted as cover.
#
# Deliberately narrow, like its webview sibling: it runs only when
# praisonai-ts changes, installs only what it needs, and asserts two things --
# the package typechecks, and its tests pass.
name: praisonai-ts tests
on:
push:
branches: [main]
paths:
- 'src/praisonai-ts/src/**'
- 'src/praisonai-ts/tests/**'
- 'src/praisonai-ts/package.json'
- 'src/praisonai-ts/jest.config.ts'
- 'src/praisonai-ts/tsconfig*.json'
- '.github/workflows/praisonai-ts-tests.yml'
pull_request:
paths:
- 'src/praisonai-ts/src/**'
- 'src/praisonai-ts/tests/**'
- 'src/praisonai-ts/package.json'
- 'src/praisonai-ts/jest.config.ts'
- 'src/praisonai-ts/tsconfig*.json'
- '.github/workflows/praisonai-ts-tests.yml'
concurrency:
group: praisonai-ts-tests-${{ github.ref }}
cancel-in-progress: true
permissions:
contents: read
jobs:
tests:
name: unit tests
runs-on: ubuntu-22.04
defaults:
run:
working-directory: src/praisonai-ts
steps:
- uses: actions/checkout@v4
- uses: actions/setup-node@v4
with:
node-version: '22.18'
# `npm install --legacy-peer-deps`, matching praisonai-ts-webview.yml:
# the lockfile is gitignored so `npm ci` has nothing to read, and the
# dependency tree does not resolve without the flag (bedrock-agentcore
# wants a peer of @strands-agents/sdk that is not installed).
- name: Install
run: npm install --no-audit --no-fund --legacy-peer-deps
- name: Typecheck
run: npx tsc --noEmit -p .
# PRAISONAI_PARITY_SILENT quiets the one-line notices that options
# accepted for Python parity print when they are not yet honoured; they
# are deliberate output, not failures, and they drown the test log.
- name: Tests
run: npm test
env:
PRAISONAI_PARITY_SILENT: '1'
@@ -1,62 +0,0 @@
# Can praisonai-ts still be loaded in a webview?
#
# Issue #4437 was this failing: `crypto` and `events` were static imports on
# the Agent graph, so a webview bundle died at IMPORT time with no error
# boundary and a blank screen. PR #4438 fixed it, and nothing stopped it
# coming back.
#
# `npm test` cannot catch a regression here, structurally: it runs in Node,
# where every one of these imports works perfectly. One `import { x } from
# "fs"` added to a file the Agent happens to reach would silently un-ship the
# mobile app, and the first signal would be a blank screen on a device.
#
# Deliberately narrow. It runs only when praisonai-ts changes, installs only
# what it needs, and asserts one thing.
name: praisonai-ts webview
on:
push:
branches: [main]
paths:
- 'src/praisonai-ts/src/**'
- 'src/praisonai-ts/package.json'
- 'src/praisonai-ts/scripts/webview-gate.mjs'
- '.github/workflows/praisonai-ts-webview.yml'
pull_request:
paths:
- 'src/praisonai-ts/src/**'
- 'src/praisonai-ts/package.json'
- 'src/praisonai-ts/scripts/webview-gate.mjs'
- '.github/workflows/praisonai-ts-webview.yml'
concurrency:
group: praisonai-ts-webview-${{ github.ref }}
cancel-in-progress: true
jobs:
webview:
name: loadable in a webview
runs-on: ubuntu-22.04
defaults:
run:
working-directory: src/praisonai-ts
steps:
- uses: actions/checkout@v4
- uses: actions/setup-node@v4
with:
node-version: '22.18'
# `npm install`, not `npm ci`: praisonai-ts gitignores its lockfile
# (src/praisonai-ts/.gitignore), so `npm ci` has nothing to install from.
# `--legacy-peer-deps` because the dependency tree does not otherwise
# resolve -- bedrock-agentcore wants a peer of @strands-agents/sdk that
# is not installed. That is pre-existing and out of scope here; without
# the flag this job fails on something unrelated to what it checks.
- name: Install
run: npm install --no-audit --no-fund --legacy-peer-deps
# Build first: the gate must see what actually SHIPS. The esm-shim adds
# a CJS banner that does not exist in the TypeScript sources, and that
# banner is what broke the published entry while the sources passed.
- name: Build
run: npm run build
- name: Check
run: npm run check:webview
+1 -5
View File
@@ -23,7 +23,6 @@ jobs:
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 }}
CLAUDE_CODE_OAUTH_TOKEN_B: ${{ secrets.CLAUDE_CODE_OAUTH_TOKEN_B }}
GH_TOKEN_VALUE: ${{ secrets.GH_TOKEN }}
DOCS_GITHUB_TOKEN: ${{ secrets.SECRETS_ADMIN_PAT }}
run: |
@@ -35,11 +34,8 @@ jobs:
echo -n "$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 "$TARGET"
if [ -n "${CLAUDE_CODE_OAUTH_TOKEN_B:-}" ]; then
echo -n "$CLAUDE_CODE_OAUTH_TOKEN_B" | gh secret set CLAUDE_CODE_OAUTH_TOKEN_B --repo "$TARGET"
fi
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, CLAUDE_CODE_OAUTH_TOKEN_B (if set), GH_TOKEN → $TARGET"
echo "Synced CLAUDE_APP_ID, CLAUDE_APP_PRIVATE_KEY, CLAUDE_CODE_OAUTH_TOKEN, GH_TOKEN → $TARGET"
-106
View File
@@ -1,106 +0,0 @@
name: Sync to praisonai-js
# Canonical TS source: src/praisonai-ts/ in this monorepo.
# This workflow pushes the mirror to MervinPraison/praisonai-js (npm repo).
on:
workflow_dispatch:
inputs:
target_branch:
description: 'Target branch on MervinPraison/praisonai-js'
required: false
default: main
type: string
mode:
description: 'pr = open pull request (default); commit = push directly to target branch'
required: false
default: pr
type: choice
options:
- pr
- commit
permissions:
contents: read
jobs:
sync:
runs-on: ubuntu-latest
env:
GH_TOKEN: ${{ secrets.GH_TOKEN }}
TARGET_REPO: MervinPraison/praisonai-js
SOURCE_PATH: src/praisonai-ts
TARGET_BRANCH: ${{ inputs.target_branch }}
steps:
- name: Validate token
run: |
if [ -z "${GH_TOKEN:-}" ]; then
echo "GH_TOKEN secret is required (PAT with repo write access to praisonai-js)."
exit 1
fi
- name: Checkout PraisonAI monorepo
uses: actions/checkout@v4
- name: Checkout praisonai-js
uses: actions/checkout@v4
with:
repository: ${{ env.TARGET_REPO }}
token: ${{ secrets.GH_TOKEN }}
path: praisonai-js-target
ref: ${{ env.TARGET_BRANCH }}
- name: Sync monorepo path into praisonai-js
run: |
set -euo pipefail
rsync -a --delete \
--exclude '.git/' \
--exclude 'node_modules/' \
--exclude 'dist/' \
--exclude 'coverage/' \
--exclude '.DS_Store' \
--exclude '*.tsbuildinfo' \
"${SOURCE_PATH}/" praisonai-js-target/
- name: Push changes
working-directory: praisonai-js-target
run: |
set -euo pipefail
git config user.name "github-actions[bot]"
git config user.email "41898282+github-actions[bot]@users.noreply.github.com"
# Preserve praisonai-js automation (rsync source has no .github/)
if git diff --quiet; then
echo "No changes — praisonai-js already matches ${SOURCE_PATH} on monorepo main."
exit 0
fi
git add -A
msg="sync: update from monorepo ${SOURCE_PATH}"
if [ "${{ inputs.mode }}" = "commit" ]; then
git commit -m "$msg"
git push origin "HEAD:${TARGET_BRANCH}"
echo "Committed and pushed directly to ${TARGET_BRANCH} on praisonai-js."
exit 0
fi
branch="sync/monorepo-praisonai-ts-$(date -u +%Y%m%d-%H%M%S)"
git checkout -b "$branch"
git commit -m "$msg"
git push origin "$branch"
gh pr create \
--repo "$TARGET_REPO" \
--base "$TARGET_BRANCH" \
--head "$branch" \
--title "$msg" \
--body "$(cat <<EOF
Automated sync from [\`MervinPraison/PraisonAI\`](https://github.com/MervinPraison/PraisonAI) \`${SOURCE_PATH}/\` into the npm mirror repo.
Canonical development is in the monorepo; this PR updates the public \`praisonai-js\` checkout.
Excludes from rsync source: \`node_modules/\`, \`dist/\`, \`coverage/\`. \`.github/\` on praisonai-js is unchanged.
EOF
)"
echo "Opened PR on ${TARGET_REPO} (${branch} → ${TARGET_BRANCH})."
+2 -5
View File
@@ -21,10 +21,7 @@ jobs:
- uses: actions/setup-python@v5
with:
# harbor requires >=3.12; on 3.11 `pip install harbor` resolved to no
# candidate version at all and every scheduled run died in ~15s, so
# this gate has never produced a Terminal-Bench score.
python-version: "3.12"
python-version: "3.11"
- name: Install Harbor + PraisonAI
run: |
@@ -37,7 +34,7 @@ jobs:
OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }}
PYTHONPATH: .
run: |
harbor run -c examples/terminal_bench/job_code_smoke.yaml
harbor run -c examples/terminal_bench/job_code_smoke.yaml || true
- name: Upload Harbor results
if: always()
+1 -68
View File
@@ -31,13 +31,6 @@ env:
PRAISONAI_ALLOW_NETWORK: '0'
PRAISONAI_LIVE_TESTS: '0'
PRAISONAI_TEST_TIER: main
# litellm reads this at import and, without it, downloads its model-price
# table from raw.githubusercontent.com before a single test runs -- which
# made the suite depend on that host being reachable. It has to be set in
# the environment rather than a conftest, because pytest imports plugins
# (and litellm with them) before any conftest is loaded.
LITELLM_LOCAL_MODEL_COST_MAP: 'True'
HF_HUB_OFFLINE: '1'
jobs:
test-core-collect:
@@ -98,78 +91,18 @@ jobs:
extra_ignore: --ignore=tests/unit/cli/test_message_queue.py
- shard: bots-gateway
workdir: src/praisonai-bot
# tests/unit/test_bots_cli.py sat at the top level and was collected
# by no workflow at all, which is why a TypeError that made
# `praisonai bot slack` unstartable shipped unnoticed. Named
# explicitly rather than adding the whole top-level directory, which
# carries suites with pre-existing env-dependent failures.
# tests/unit/kanban/ was likewise collected by no workflow, which
# is how six declared KANBAN_TASK_* hook events shipped with no
# emitter at all.
paths: >-
tests/unit/bots/
tests/unit/gateway/
tests/unit/cli/
tests/unit/daemon/
tests/unit/kanban/
tests/unit/test_bots_cli.py
extra_ignore: ""
pythonpath: >-
${{ github.workspace }}/src/praisonai-agents:${{ github.workspace }}/src/praisonai-code
- shard: agents-core
workdir: src/praisonai-agents
# src/praisonai-agents/tests holds 727 files and 11,437 test
# functions, and until now NO workflow referenced the directory at
# all -- so the LLM layer, the provider adapters, the local-model
# package and the streaming paths were guarded by tests that never
# ran. Nearly every defect found in the recent local-model audits
# had a working test sitting unused beside it.
#
# The ten directories originally left out of this shard (knowledge,
# runtime, session, tools, bus, plugins, skills, agents, rag,
# streaming -- about 52 failures) have since been repaired, so they
# are all listed below: 1,567 tests in the seven added here alone.
# Leaving them out would have meant the repairs were never exercised.
#
# The whole tree in one invocation was hanging. The cause was NOT
# the pytest-rerunfailures run_server thread guessed at here
# earlier: it is test_botos_integration.py, where a supervised
# Bot.start() deliberately never returns and the mock adapter
# reports is_running=True forever (fixed on this branch). Naming
# directories explicitly is still the safer shape for a shard.
paths: >-
tests/unit/agent/ tests/unit/app/ tests/unit/approval/
tests/unit/auth/ tests/unit/background/ tests/unit/checkpoints/
tests/unit/cli/ tests/unit/compaction/ tests/unit/conditions/
tests/unit/config/ tests/unit/context/ tests/unit/embedding/
tests/unit/eval/ tests/unit/gateway/ tests/unit/goal/
tests/unit/hooks/ tests/unit/llm/ tests/unit/lsp/ tests/unit/mcp/
tests/unit/memory/ tests/unit/permissions/ tests/unit/policy/
tests/unit/process/ tests/unit/runs/ tests/unit/sandbox/
tests/unit/security/ tests/unit/server/ tests/unit/snapshot/
tests/unit/storage/ tests/unit/task/ tests/unit/telemetry/
tests/unit/trace/ tests/unit/utils/ tests/unit/workflows/
tests/unit/workspace/ tests/unit/knowledge/ tests/unit/session/
tests/unit/plugins/ tests/unit/runtime/ tests/unit/tools/
tests/unit/bus/ tests/unit/skills/ tests/unit/agents/
tests/unit/rag/ tests/unit/streaming/
tests/unit/test_adapter_registry.py
# Both tests previously deselected here now pass in combination.
# test_lazy_litellm_import was looking the loader module up by
# name and could get a different object than the one get_litellm()
# mutates; it reads the function's own __globals__ now.
# test_skills_discovery_uses_paths_module read the real home
# directory and asserted every discovered dir was named "skills",
# which is false once a remote skill has ever been cached; it runs
# against a temp HOME and asserts the paths module is used.
extra_ignore: ""
pythonpath: >-
${{ github.workspace }}/src/praisonai-agents
- shard: train
workdir: src/praisonai-train
# tests/unit/data/ (96 tests) was collected by no workflow at all.
paths: >-
tests/unit/train/ tests/unit/data/
tests/unit/train/
extra_ignore: ""
pythonpath: >-
${{ github.workspace }}/src/praisonai-agents:${{ github.workspace }}/src/praisonai-code
+1 -123
View File
@@ -759,128 +759,6 @@ jobs:
if: steps.check-key.outputs.has_key == 'false'
run: echo "✅ Cohere tests skipped (no API key available)"
# ============================================
# OLLAMA LIVE TESTS - Real local model, no API key
# Nightly / extended only. Installs Ollama on the runner and pulls a small
# tools-capable model. Unlike the other live jobs this one needs no secret,
# so its required step has no "|| echo" fallback: a failure here is a real
# regression in local-model tool calling, not a missing credential.
# ============================================
extended-ollama:
if: github.event_name == 'schedule' || github.event.inputs.tier == 'extended' || github.event.inputs.tier == 'nightly'
runs-on: ubuntu-latest
timeout-minutes: 15
env:
# Bump deliberately: this is the version everything in this job was
# verified against. Latest at time of writing is v0.33.3.
# No leading "v": install.sh passes ?version=$OLLAMA_VERSION and ollama.com
# redirects to GitHub tag v$version (vv0.33.2 → 404 if set to v0.33.2).
OLLAMA_VERSION: "0.33.2"
# 522 MB, capabilities: completion, tools, thinking.
OLLAMA_TEST_MODEL: qwen3:0.6b
steps:
- uses: actions/checkout@v4
with:
persist-credentials: false
- name: Set up Python 3.11
uses: actions/setup-python@v5
with:
python-version: '3.11'
- name: Cache pip packages
uses: actions/cache@v4
with:
path: ~/.cache/pip
key: ${{ runner.os }}-pip-ollama-${{ hashFiles('**/pyproject.toml') }}
restore-keys: |
${{ runner.os }}-pip-
- name: Cache Ollama model blobs
uses: actions/cache@v4
with:
path: ~/.ollama/models
# No restore-keys on purpose: a partial hit from a different model would
# silently test something other than OLLAMA_TEST_MODEL.
key: ${{ runner.os }}-ollama-models-${{ env.OLLAMA_TEST_MODEL }}
- name: Install Ollama
shell: bash
run: |
set -euo pipefail
# The official installer, but VERSION-PINNED via OLLAMA_VERSION (which it
# honours) so this job cannot silently change what it tests. Fetching the
# release asset directly is not a workable alternative: since v0.33 the
# linux bundle ships as a 1.4 GB .tar.zst with GPU runtimes bundled in,
# and the installer already handles the zst/tgz split across versions.
sudo apt-get update -qq && sudo apt-get install -y -qq zstd
curl -fsSL https://ollama.com/install.sh | sh
ollama --version
- name: Start Ollama and pull model
shell: bash
run: |
set -euo pipefail
ollama serve > /tmp/ollama-serve.log 2>&1 &
for i in $(seq 1 30); do
if curl -sf http://127.0.0.1:11434/api/tags > /dev/null; then
echo "Ollama is up after ${i}s"
break
fi
sleep 1
done
curl -sf http://127.0.0.1:11434/api/tags > /dev/null
ollama pull "$OLLAMA_TEST_MODEL"
ollama list
- 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]"
- name: Run Ollama minimum contract (required)
env:
PRAISONAI_TEST_TIER: extended
PRAISONAI_ALLOW_NETWORK: '1'
PRAISONAI_LIVE_TESTS: '1'
PRAISONAI_TEST_PROVIDERS: 'ollama'
PRAISONAI_TEST_OLLAMA: '1'
PRAISONAI_OLLAMA_TEST_MODEL: ${{ env.OLLAMA_TEST_MODEL }}
shell: bash
run: |
set -euo pipefail
cd src/praisonai
# No "|| echo" here: no secret is involved, so a failure is a real
# regression rather than a missing credential.
python -m pytest tests/integration/test_ollama_tool_calling_live.py::TestOllamaCIMinimum \
-v --tb=short \
--timeout=120
- name: Run remaining Ollama live tests (informational)
if: always()
env:
PRAISONAI_TEST_TIER: extended
PRAISONAI_ALLOW_NETWORK: '1'
PRAISONAI_LIVE_TESTS: '1'
PRAISONAI_TEST_PROVIDERS: 'ollama'
PRAISONAI_TEST_OLLAMA: '1'
PRAISONAI_OLLAMA_TEST_MODEL: ${{ env.OLLAMA_TEST_MODEL }}
run: |
cd src/praisonai
python -m pytest tests/integration/test_ollama_tool_calling_live.py \
--deselect tests/integration/test_ollama_tool_calling_live.py::TestOllamaCIMinimum \
-v --tb=short \
--timeout=180 \
|| echo "Ollama exploratory tests completed (small models are non-deterministic)"
- name: Ollama server log
if: failure()
run: tail -100 /tmp/ollama-serve.log
# ============================================
# LEGACY UNIT TESTS - Post-C6 re-enabled suite
# Nightly / extended tier only (~401 tests)
@@ -958,7 +836,7 @@ jobs:
# TEST SUMMARY
# ============================================
test-summary:
needs: [smoke, main, extended-ollama]
needs: [smoke, main]
if: always()
runs-on: ubuntu-latest
+1 -5
View File
@@ -6,11 +6,7 @@ on:
paths:
- 'src/praisonai-agents/praisonaiagents/**/*.py'
- 'src/praisonai-ts/src/**/*.ts'
# The crate lives at src/praisonai-rust/praisonai/src -- the old
# 'src/praisonai-rust/src/**' path does not exist, so a Rust change
# never triggered either tracker and the Rust numbers only ever
# refreshed incidentally, on an unrelated push.
- 'src/praisonai-rust/praisonai/src/**/*.rs'
- 'src/praisonai-rust/src/**/*.rs'
- 'src/praisonai/praisonai/_dev/parity/**/*.py'
- '.github/workflows/update-docs-parity.yml'
workflow_dispatch: # Allow manual trigger
+7 -50
View File
@@ -1,35 +1,21 @@
name: Update Feature Parity Tracker
# Regenerates the exported-name parity trackers on push to main and commits them.
# Validation on pull requests (fail on drift) lives in parity-gate.yml.
on:
push:
branches: [ "main" ]
paths:
- 'src/praisonai-agents/praisonaiagents/**/*.py'
- 'src/praisonai-ts/src/**/*.ts'
# The crate lives at src/praisonai-rust/praisonai/src -- the old
# 'src/praisonai-rust/src/**' path does not exist, so a Rust change
# never triggered either tracker and the Rust numbers only ever
# refreshed incidentally, on an unrelated push.
- 'src/praisonai-rust/praisonai/src/**/*.rs'
# The generator's own code and the wrapper features it counts. Change
# either and nothing regenerated until an unrelated push landed.
- 'src/praisonai/praisonai/_dev/parity/**/*.py'
- 'src/praisonai/praisonai/cli/features/**/*.py'
- 'src/praisonai-rust/src/**/*.rs'
- '.github/workflows/update-parity-tracker.yml'
permissions:
contents: write
jobs:
update-parity-tracker:
# Push only. On a PR the parity-gate.yml `names` job CHECKS instead --
# committing a regenerated tracker onto a contributor's branch is not this
# workflow's business, and would fail on a fork besides.
if: github.event_name == 'push'
runs-on: ubuntu-latest
steps:
- name: Checkout repository
uses: actions/checkout@v4
@@ -46,45 +32,15 @@ jobs:
- name: Install dependencies
run: pip install pyyaml
- name: Set up Node
uses: actions/setup-node@v4
with:
node-version: '22'
- name: Install the TypeScript compiler only
# The signature extractor needs `typescript` and nothing else;
# praisonai-ts's own dependency tree does not install cleanly.
run: |
mkdir -p "$RUNNER_TEMP/parity-ts"
npm install --prefix "$RUNNER_TEMP/parity-ts" --no-audit --no-fund [email protected]
echo "PARITY_TS_NODE_MODULES=$RUNNER_TEMP/parity-ts/node_modules" >> "$GITHUB_ENV"
- name: Generate parity trackers
run: |
cd $GITHUB_WORKSPACE
python3 src/praisonai/scripts/generate_parity_tracker.py
- name: Regenerate the signature report
# Source locations in the report drift whenever a covered file is edited.
# The pull-request gate ignores line-number-only drift so it never reddens
# a build over it; refreshing here keeps the committed line numbers true.
env:
PYTHONPATH: src/praisonai
run: |
cd $GITHUB_WORKSPACE
python3 -m praisonai._dev.parity.signatures --write
- name: Regenerate the behaviour report
env:
PYTHONPATH: src/praisonai
run: |
cd $GITHUB_WORKSPACE
python3 -m praisonai._dev.parity.behaviour --write
- name: Check for changes
id: check_changes
run: |
if git diff --quiet src/praisonai-ts/FEATURE_PARITY_TRACKER.json src/praisonai-ts/PARITY.md src/praisonai-rust/FEATURE_PARITY_TRACKER.json src/praisonai-rust/PARITY.md src/praisonai-ts/SIGNATURE_PARITY.md src/praisonai-ts/signature-parity.json src/praisonai-ts/BEHAVIOUR_PARITY.md src/praisonai-ts/behaviour-parity.json 2>/dev/null; then
if git diff --quiet src/praisonai-ts/FEATURE_PARITY_TRACKER.json src/praisonai-ts/PARITY.md src/praisonai-rust/FEATURE_PARITY_TRACKER.json src/praisonai-rust/PARITY.md 2>/dev/null; then
echo "changes=false" >> $GITHUB_OUTPUT
echo "No changes to parity trackers"
else
@@ -98,7 +54,8 @@ jobs:
uses: stefanzweifel/git-auto-commit-action@v5
with:
commit_message: "docs: auto-update feature parity trackers [skip ci]"
file_pattern: 'src/praisonai-ts/FEATURE_PARITY_TRACKER.json src/praisonai-ts/PARITY.md src/praisonai-rust/FEATURE_PARITY_TRACKER.json src/praisonai-rust/PARITY.md src/praisonai-ts/SIGNATURE_PARITY.md src/praisonai-ts/signature-parity.json src/praisonai-ts/BEHAVIOUR_PARITY.md src/praisonai-ts/behaviour-parity.json'
file_pattern: 'src/praisonai-ts/FEATURE_PARITY_TRACKER.json src/praisonai-ts/PARITY.md src/praisonai-rust/FEATURE_PARITY_TRACKER.json src/praisonai-rust/PARITY.md'
commit_user_name: "MervinPraison"
commit_user_email: "[email protected]"
commit_author: "MervinPraison <[email protected]>"
+1 -8
View File
@@ -26,9 +26,6 @@ output
!src/praisonai-code/praisonai_code/cli/output/
!src/praisonai-bot/praisonai_bot/cli/output/
!src/praisonai-ts/src/db/
# The bare `db` rule above also swallows the SQLite adapter's test
# directory, so the durability suite would silently never be committed.
!src/praisonai-ts/tests/unit/db/
!src/praisonai-ts/src/cli/output/
.files
@@ -118,8 +115,4 @@ Cargo.lock
src/praisonai/build*.egg-info/
src/praisonai/PraisonAI.egg-info/
jobs/*
*.egg-info
# Local Android SDK/NDK/JDK for building praisonai-mobile on a laptop without
# Android Studio (how: .github/workflows/mobile-platforms.yml). Several GB.
.android-sdk/
.worktrees/
*.egg-info
+2 -15
View File
@@ -7,22 +7,9 @@ You are working on the PraisonAI project.
- Be concise and helpful in responses
- Test implementation thoroughly
- Ensure backward compatibility with existing APIs
- Follow protocol-driven design across the nine Python PyPI packages plus the TypeScript SDK: 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, TypeScript/JavaScript SDK in `src/praisonai-ts/` (`npm: praisonai`)
- **TypeScript review routing:** For TS/JS issues and PRs, read [`src/praisonai-ts/AGENTS.md`](src/praisonai-ts/AGENTS.md) (not just this file). Canonical source is `src/praisonai-ts/` in this monorepo; [MervinPraison/praisonai-js](https://github.com/MervinPraison/praisonai-js) is the npm mirror only (sync: monorepo → praisonai-js via workflow **Sync to praisonai-js**). Do not implement TS fixes in praisonai-js for PraisonAI issues.
- 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.
## Issue and PR routing
| Area | Where to implement | AGENTS.md to read | Tests |
|------|-------------------|-------------------|-------|
| Python core SDK | `src/praisonai-agents/praisonaiagents/` | `src/praisonai-agents/AGENTS.md` | `pytest` in `src/praisonai-agents/tests/` |
| Python wrapper / CLI | `src/praisonai/`, `src/praisonai-code/`, etc. | `src/praisonai-agents/AGENTS.md` | `pytest` under `src/praisonai/tests/` |
| **TypeScript / JavaScript SDK** | **`src/praisonai-ts/`** | **`src/praisonai-ts/AGENTS.md`** | `cd src/praisonai-ts && npm run build && npm test` |
| Agent-callable tools | [PraisonAI-Tools](https://github.com/MervinPraison/PraisonAI-Tools) | — | repo tests |
| Lifecycle plugins | [PraisonAI-Plugins](https://github.com/MervinPraison/PraisonAI-Plugins) | — | repo tests |
| Documentation | [PraisonAIDocs](https://github.com/MervinPraison/PraisonAIDocs) | — | `nav-check` |
| npm mirror (read-only for fixes) | [praisonai-js](https://github.com/MervinPraison/praisonai-js) | mirror of `src/praisonai-ts/AGENTS.md` | CI on praisonai-js |
- 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.
+12 -12
View File
@@ -222,15 +222,15 @@ The Python SDK is organised as three publishable tiers (see [§2](#2-python-thre
Core execution modules live in `praisonaiagents`:
- `src/praisonai-agents/praisonaiagents/agent/` — Agent class, handoff, autonomy
- `src/praisonai-agents/praisonaiagents/llm/` — Model runtime with provider routing, rate limiting, failover
- `src/praisonai-agents/praisonaiagents/tools/` — Tool runtime with sandbox, approval, retry
- `src/praisonai-agents/praisonaiagents/memory/` — Memory runtime (in-memory, SQLite, MongoDB, Mem0 adapters)
- `src/praisonai-agents/praisonaiagents/knowledge/` — Knowledge management (indexing, retrieval, chunking)
- `src/praisonai-agents/praisonaiagents/workflows/` — Workflow engine (YAML/SDK-based orchestration)
- `src/praisonai-agents/praisonaiagents/hooks/`, `src/praisonai-agents/praisonaiagents/bus/` — Hook system and event bus
- `src/praisonai-agents/praisonaiagents/mcp/` — MCP protocol support
- `src/praisonai-agents/praisonaiagents/ui/a2a/`, `src/praisonai-agents/praisonaiagents/ui/a2ui/` — Agent-to-agent and agent-to-UI protocols
- `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/`:
@@ -243,9 +243,9 @@ Wrapper-only surfaces remain in `src/praisonai/`:
- **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 (`src/praisonai-ts/`)
- **Rust SDK** — High-performance Rust runtime (`src/praisonai-rust/`)
- **UI** — Web UI applications (`src/praisonai/praisonai/ui_chat/`, `src/praisonai/praisonai/ui_agents/`, `src/praisonai/praisonai/ui_bot/`, `src/praisonai/praisonai/ui_realtime/`); shared support code lives in `src/praisonai/praisonai/ui/`.
- **TypeScript SDK** — JS/TS runtime (`ts-sdk/`)
- **Rust SDK** — High-performance Rust runtime (`rust-sdk/`)
- **UI** — Web UI (`ui/`)
---
-12
View File
@@ -7,20 +7,8 @@ Thank you for your interest! Here's how to get started:
3. Make your changes
4. Submit a pull request
## Where to report issues
| Topic | Report here | Where fixes land |
|-------|-------------|------------------|
| Python SDK, CLI, wrapper | **This repo** | `src/praisonai-agents/`, `src/praisonai/` |
| TypeScript / JavaScript (`npm install praisonai`) | **This repo** | `src/praisonai-ts/` |
| Cross-language parity | **This repo** | Often both Python and TypeScript paths |
| Agent-callable tools | **This repo** | [PraisonAI-Tools](https://github.com/MervinPraison/PraisonAI-Tools) |
| Lifecycle plugins (tracing, hooks, guardrails) | **This repo** | [PraisonAI-Plugins](https://github.com/MervinPraison/PraisonAI-Plugins) |
## Guidelines
- Follow existing code style
- Add tests for new features
- Update documentation as needed
- TypeScript changes: implement in `src/praisonai-ts/` and run `npm test` there
- After merge, sync the npm mirror: `gh workflow run "Sync to praisonai-js" --repo MervinPraison/PraisonAI`
+5 -43
View File
@@ -12,6 +12,7 @@
<a href="https://github.com/MervinPraison/PraisonAI"><img src="https://static.pepy.tech/badge/PraisonAI" alt="Total Downloads" /></a>
<a href="https://github.com/MervinPraison/PraisonAI"><img src="https://img.shields.io/github/v/release/MervinPraison/PraisonAI" alt="Latest Stable Version" /></a>
<a href="https://github.com/MervinPraison/PraisonAI"><img src="https://img.shields.io/badge/License-MIT-yellow.svg" alt="License" /></a>
<a href="https://registry.modelcontextprotocol.io/servers/io.github.MervinPraison/praisonai"><img src="https://img.shields.io/badge/MCP-Registry-blue" alt="MCP Registry" /></a>
</p>
<div align="center">
@@ -34,19 +35,6 @@ curl -fsSL https://praison.ai/install.sh | bash
<img src="https://img.shields.io/badge/Highlighted_by_Elon_Musk-000000?style=for-the-badge&logo=x&logoColor=white" alt="Highlighted by Elon Musk" />
</a>
<br>
<br>
<a href="https://github.com/MervinPraison/PraisonAI/releases/latest">
<img src="https://img.shields.io/badge/Download_for_macOS-000000?style=for-the-badge&logo=apple&logoColor=white" alt="Download for macOS" />
</a>
&nbsp;&nbsp;
<a href="https://github.com/MervinPraison/PraisonAI/releases/latest">
<img src="https://img.shields.io/badge/Download_for_Windows-0078D6?style=for-the-badge&logo=windows&logoColor=white" alt="Download for Windows" />
</a>
&nbsp;&nbsp;
<a href="https://github.com/MervinPraison/PraisonAI/releases/latest">
<img src="https://img.shields.io/badge/Download_for_Linux-FCC624?style=for-the-badge&logo=linux&logoColor=black" alt="Download for Linux" />
</a>
<br>
</div>
<p align="center">
@@ -1111,39 +1099,13 @@ For other providers, see [Models docs](https://docs.praison.ai/docs/models).
<summary><strong>How do I use a local model (Ollama)?</strong></summary>
```bash
# Start Ollama and pull a model
# Start Ollama server first
ollama serve
ollama pull llama3.2
# Set environment variable
export OPENAI_BASE_URL=http://localhost:11434/v1
```
```python
from praisonaiagents import Agent
agent = Agent(instructions="You are a helpful assistant", llm="ollama/llama3.2")
agent.start("Why is the sky blue?")
```
The `ollama/` prefix is what selects Ollama's handling — tool-call repair,
tool-result formatting and the streaming rules small local models need. Or set
it by environment instead:
```bash
export OPENAI_MODEL_NAME=ollama/llama3.2
```
Setting only `OPENAI_BASE_URL` is not enough: with no model named, the OpenAI
default (`gpt-4o-mini`) is sent to Ollama, which answers
`404 model 'gpt-4o-mini' not found`. Always name the model.
Point at a non-default host with `base_url=` or `OLLAMA_HOST`:
```python
agent = Agent(instructions="...", llm="ollama/llama3.2", base_url="http://192.168.1.10:11434")
```
The same shape works for other local runtimes — `lm_studio/`, `vllm/` and
`hosted_vllm/` with their server's `base_url`.
See [Models docs](https://docs.praison.ai/docs/models) for more details.
</details>
+40 -82
View File
@@ -53,11 +53,9 @@ Methods:
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">get_recommended_stage</a>(prompt: str) -> str</code>
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">get_rules_context</a>(file_path: Optional[str] = None, include_manual: Optional[List[str]] = None) -> str</code>
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">get_skills_prompt</a>() -> str</code>
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">guardrail_retry_count</a>() -> int</code>
* <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_guardrail_error</a>()</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>
@@ -70,8 +68,6 @@ Methods:
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">query</a>(question: str, **kwargs) -> 'RAGResult'</code>
* <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">reasoning_effort</a>() -> Optional[str]</code>
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">reasoning_effort</a>(value: Optional[str]) -> None</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>
@@ -195,7 +191,6 @@ Methods:
* <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_definition</a>(name: str) -> Optional[Dict[str, Any]]</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>
@@ -272,14 +267,14 @@ 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, min_trust = 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, min_trust = 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, 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_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>
* <code title="class Memory">Memory.<a href="./src/praisonai-agents/praisonaiagents/memory/memory.py">store_long_term</a>(text: str, metadata: Dict[str, Any] = None, completeness: float = None, relevance: float = None, clarity: float = None, accuracy: float = None, weights: Dict[str, float] = None, evaluator_quality: float = None, trust = None, origin: Optional[str] = None)</code>
* <code title="class Memory">Memory.<a href="./src/praisonai-agents/praisonaiagents/memory/memory.py">store_long_term</a>(text: str, metadata: Dict[str, Any] = None, completeness: float = None, relevance: float = None, clarity: float = None, accuracy: float = None, weights: Dict[str, float] = None, evaluator_quality: float = None)</code>
* <code title="class Memory">Memory.<a href="./src/praisonai-agents/praisonaiagents/memory/memory.py">store_quality</a>(text: str, quality_score: float, task_id: Optional[str] = None, iteration: Optional[int] = None, metrics: Optional[Dict[str, float]] = None, memory_type: Literal['short', 'long'] = 'long') -> None</code>
* <code title="class Memory">Memory.<a href="./src/praisonai-agents/praisonaiagents/memory/memory.py">store_short_term</a>(text: str, metadata: Dict[str, Any] = None, completeness: float = None, relevance: float = None, clarity: float = None, accuracy: float = None, weights: Dict[str, float] = None, evaluator_quality: float = None, trust = None, origin: Optional[str] = None)</code>
* <code title="class Memory">Memory.<a href="./src/praisonai-agents/praisonaiagents/memory/memory.py">store_short_term</a>(text: str, metadata: Dict[str, Any] = None, completeness: float = None, relevance: float = None, clarity: float = None, accuracy: float = None, weights: Dict[str, float] = None, evaluator_quality: float = None)</code>
* <code title="class Memory">Memory.<a href="./src/praisonai-agents/praisonaiagents/memory/memory.py">store_user_memory</a>(user_id: str, text: str, extra: Dict[str, Any] = None)</code>
* <code title="class MemoryConfig">MemoryConfig.<a href="./src/praisonai-agents/praisonaiagents/config/feature_configs.py">to_dict</a>() -> Dict[str, Any]</code>
@@ -310,9 +305,9 @@ Methods:
* <code title="class Knowledge">Knowledge.<a href="./src/praisonai-agents/praisonaiagents/knowledge/knowledge.py">markdown</a>()</code>
* <code title="class Knowledge">Knowledge.<a href="./src/praisonai-agents/praisonaiagents/knowledge/knowledge.py">memory</a>()</code>
* <code title="class Knowledge">Knowledge.<a href="./src/praisonai-agents/praisonaiagents/knowledge/knowledge.py">normalize_content</a>(content)</code>
* <code title="class Knowledge">Knowledge.<a href="./src/praisonai-agents/praisonaiagents/knowledge/knowledge.py">reset</a>() -> bool</code>
* <code title="class Knowledge">Knowledge.<a href="./src/praisonai-agents/praisonaiagents/knowledge/knowledge.py">reset</a>()</code>
* <code title="class Knowledge">Knowledge.<a href="./src/praisonai-agents/praisonaiagents/knowledge/knowledge.py">search</a>(query, user_id = None, agent_id = None, run_id = None, rerank = None, **kwargs)</code>
* <code title="class Knowledge">Knowledge.<a href="./src/praisonai-agents/praisonaiagents/knowledge/knowledge.py">store</a>(content, user_id = None, agent_id = None, run_id = None, metadata = None, is_content = False)</code>
* <code title="class Knowledge">Knowledge.<a href="./src/praisonai-agents/praisonaiagents/knowledge/knowledge.py">store</a>(content, user_id = None, agent_id = None, run_id = None, metadata = None)</code>
* <code title="class Knowledge">Knowledge.<a href="./src/praisonai-agents/praisonaiagents/knowledge/knowledge.py">update</a>(memory_id, data)</code>
* <code title="class KnowledgeConfig">KnowledgeConfig.<a href="./src/praisonai-agents/praisonaiagents/config/feature_configs.py">to_dict</a>() -> Dict[str, Any]</code>
@@ -390,7 +385,6 @@ Methods:
* <code title="class LLMGuardrail">LLMGuardrail.<a href="./src/praisonai-agents/praisonaiagents/guardrails/llm_guardrail.py">validate_input</a>(content: str, **kwargs) -> Tuple[bool, str]</code>
* <code title="class LLMGuardrail">LLMGuardrail.<a href="./src/praisonai-agents/praisonaiagents/guardrails/llm_guardrail.py">validate_output</a>(content: str, **kwargs) -> Tuple[bool, str]</code>
* <code title="class LLMGuardrail">LLMGuardrail.<a href="./src/praisonai-agents/praisonaiagents/guardrails/llm_guardrail.py">validate_tool_call</a>(tool_name: str, arguments: Dict[str, Any], **kwargs) -> Tuple[bool, Dict[str, Any]]</code>
* <code title="class LLMGuardrail">LLMGuardrail.<a href="./src/praisonai-agents/praisonaiagents/guardrails/llm_guardrail.py">validate_tool_result</a>(tool_name: str, result: Any, **kwargs) -> Tuple[bool, Any]</code>
# Planning
@@ -714,11 +708,8 @@ Methods:
* <code title="class AgentFlow">AgentFlow.<a href="./src/praisonai-agents/praisonaiagents/workflows/workflows.py">reasoning</a>() -> bool</code>
* <code title="class AgentFlow">AgentFlow.<a href="./src/praisonai-agents/praisonaiagents/workflows/workflows.py">run</a>(input: str = '', llm: Optional[str] = None, verbose: bool = False, stream: bool = None) -> Dict[str, Any]</code>
* <code title="class AgentFlow">AgentFlow.<a href="./src/praisonai-agents/praisonaiagents/workflows/workflows.py">start</a>(input: str = '', **kwargs) -> Dict[str, Any]</code>
* <code title="class AgentFlow">AgentFlow.<a href="./src/praisonai-agents/praisonaiagents/workflows/workflows.py">state</a>()</code>
* <code title="class AgentFlow">AgentFlow.<a href="./src/praisonai-agents/praisonaiagents/workflows/workflows.py">stream</a>() -> bool</code>
* <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">to_mermaid</a>() -> str</code>
* <code title="class AgentFlow">AgentFlow.<a href="./src/praisonai-agents/praisonaiagents/workflows/workflows.py">validate_variables</a>() -> None</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>
@@ -752,7 +743,7 @@ Methods:
* <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, tasks = None)</code>
* <code title="class AgentTeam">AgentTeam.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">get_task_result</a>(task_id)</code>
* <code title="class AgentTeam">AgentTeam.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">get_task_status</a>(task_id)</code>
* <code title="class AgentTeam">AgentTeam.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">get_todo_markdown</a>() -> str</code>
* <code title="class AgentTeam">AgentTeam.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">get_token_usage_summary</a>() -> Dict[str, Any]</code>
@@ -776,7 +767,7 @@ Methods:
* <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, timeout: Optional[float] = None) -> 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>
@@ -788,7 +779,7 @@ Methods:
Types:
```python
from praisonai import Agent, AgentApp, AgentOS, AnthropicManagedAgent, HostedAgent, HostedAgentConfig, LocalAgent, LocalAgentConfig, LocalManagedAgent, LocalManagedConfig, ManagedAgent, ManagedConfig, __version__, arun, run
from praisonai import Agent, AgentApp, AgentOS, AnthropicManagedAgent, DB, HostedAgent, HostedAgentConfig, LocalAgent, LocalAgentConfig, LocalManagedAgent, LocalManagedConfig, ManagedAgent, ManagedConfig, __version__, arun, run
```
# CLI
@@ -913,7 +904,6 @@ Methods:
* <code title="cli">praisonai schedule remove <a href="./src/praisonai/praisonai/cli/commands/schedule.py">--help</a></code>
* <code title="cli">praisonai schedule restart <a href="./src/praisonai/praisonai/cli/commands/schedule.py">--help</a></code>
* <code title="cli">praisonai schedule resume <a href="./src/praisonai/praisonai/cli/commands/schedule.py">--help</a></code>
* <code title="cli">praisonai schedule run <a href="./src/praisonai/praisonai/cli/commands/schedule.py">--help</a></code>
* <code title="cli">praisonai schedule runs <a href="./src/praisonai/praisonai/cli/commands/schedule.py">--help</a></code>
* <code title="cli">praisonai schedule schedule-callback <a href="./src/praisonai/praisonai/cli/commands/schedule.py">--help</a></code>
* <code title="cli">praisonai schedule start <a href="./src/praisonai/praisonai/cli/commands/schedule.py">--help</a></code>
@@ -932,24 +922,17 @@ Methods:
Types/Exports:
```ts
export { Agent, AgentTeam, Agents, CodeAgent, EmbeddingAgent, OCRAgent, PraisonAIAgents, RealtimeAgent, Router, TASK_STATUS, VideoAgent, VisionAgent, createCodeAgent, createEmbeddingAgent, createOCRAgent, createRealtimeAgent, createSubprocessExecutor, createVideoAgent, createVisionAgent } from "./agent";
export type { AgentChatCallOptions, AgentChatOptions, AgentEvent, AgentExecuteTask, AgentGuardrailEntry, AgentGuardrailFunction, AgentGuardrailInput, AgentHooksInput, AgentMemoryStore, AgentMessage, AgentRetryConfig, AgentStreamOptions, AgentTaskLike, AgentTeamConfig, AgentTeamProcess, AgentTeamStartDictOptions, AgentTeamStartOptions, AgentTeamStartOptionsInput, AgentWebConfig, PraisonAIAgentsConfig, SimpleAgentConfig, SimpleRouteConfig, SimpleRouterConfig, StopReason, TaskCallback, TaskGuardrail, TaskOnError } from "./agent";
export { Agent, AgentTeam, Agents, PraisonAIAgents, Router } from "./agent";
export type { AgentTeamConfig, PraisonAIAgentsConfig, SimpleAgentConfig, SimpleRouteConfig, SimpleRouterConfig } from "./agent";
export { AudioAgent, createAudioAgent } from "./agent/audio";
export type { AudioAgentConfig, AudioConfig, AudioProvider, AudioSpeakOptions, AudioSpeakResult, AudioTranscribeOptions, AudioTranscribeResult } from "./agent/audio";
export { ContextAgent, createContextAgent, create_context_agent } from "./agent/context";
export { ContextPolicy, DEFAULT_HANDOFF_TOOL_POLICY, Handoff, HandoffCycleError, HandoffDepthError, HandoffError, HandoffTimeoutError, HandoffToolPolicyMode, RECOMMENDED_PROMPT_PREFIX, handoff, handoffFilters, handoffToolName, handoff_filters, listAgentTools, parallelHandoffs, parallel_handoffs, promptWithHandoffInstructions, prompt_with_handoff_instructions, resolveHandoffToolPolicy } from "./agent/handoff";
export { Heartbeat, HeartbeatConfig, parseHeartbeatSchedule } from "./agent/heartbeat";
export type { HeartbeatAgent, HeartbeatOnError, HeartbeatOptions } from "./agent/heartbeat";
export type { AudioAgentConfig, AudioProvider, AudioSpeakOptions, AudioSpeakResult, AudioTranscribeOptions, AudioTranscribeResult } from "./agent/audio";
export { ContextAgent, createContextAgent } from "./agent/context";
export { ContextPolicy, Handoff, HandoffCycleError, HandoffDepthError, HandoffError, HandoffTimeoutError, RECOMMENDED_PROMPT_PREFIX, handoff, handoffFilters, promptWithHandoffInstructions } from "./agent/handoff";
export { ImageAgent, createImageAgent } from "./agent/image";
export { PromptExpanderAgent, createPromptExpanderAgent } from "./agent/prompt-expander";
export { QueryRewriterAgent, createQueryRewriterAgent } from "./agent/query-rewriter";
export { DeepResearchAgent, Provider, createDeepResearchAgent } from "./agent/research";
export { RetryBackoffConfig, interruptibleSleep, jitteredBackoff } from "./agent/retry-utils";
export type { JitteredBackoffOptions, RetryBackoffConfigOptions } from "./agent/retry-utils";
export { DeepResearchAgent, createDeepResearchAgent } from "./agent/research";
export { RouterAgent, createRouter, routeConditions } from "./agent/router";
export { AGENT_RUN_STATUSES, AgentRunOutcome, PROVIDER_BLOCK_REASONS, RunOutcome, TERMINAL_REASON_PRECEDENCE, TERMINATION_TO_RUN_STATUS, TerminationReason, classifyFinishReason, terminationToRunStatus, termination_to_run_status, validateDecisionString, validate_decision_string } from "./agent/run-outcome";
export type { AgentRunOutcomeFailureOptions, AgentRunOutcomeInit, AgentRunOutcomeOptions, AgentRunStatus, RunOutcomeInit, TerminalReason } from "./agent/run-outcome";
export { reviewTaskOutput } from "./agent/task-review";
export { // Agent loop
createAgentLoop, // DevTools
enableDevTools, // MCP
@@ -966,7 +949,6 @@ export { // Agent loop
defineTool, // UI Message (AI SDK v6 parity)
convertToModelMessages, AIAgentStep, AIEmbedManyResult, AIEmbedOptions, AIEmbedResult, AIFilePart, AIGenerateImageOptions, AIGenerateImageResult, AIGenerateObjectOptions, AIGenerateObjectResult, AIGenerateTextOptions, AIGenerateTextResult, AIImagePart, AIMiddleware, AIMiddlewareConfig, AIModelMessage, AISpan, AISpanKind, AISpanOptions, AISpanStatus, AIStreamObjectOptions, AIStreamObjectResult, AIStreamTextOptions, AIStreamTextResult, AITelemetryEvent, AITelemetrySettings, AITextPart, AIToolDefinition, AITracer, AgentLoop, DANGEROUS_PATTERNS, MCPClientType, MODEL_ALIASES, SPEECH_MODELS, TRANSCRIPTION_MODELS, ToolApprovalDeniedError, ToolApprovalTimeoutError, aiEmbed, aiEmbedMany, aiGenerateImage, aiGenerateObject, aiGenerateText, aiStreamObject, aiStreamText, applyMiddleware, autoEnableDevTools, base64ToUint8Array, clearAICache, clearEvents, closeAllMCPClients, closeMCPClient, convertToUIMessages, createAILoggingMiddleware, createAISpan, createApprovalResponse, createDangerousPatternChecker, createDevToolsMiddleware, createExpressHandler, createFastifyHandler, createFilePart, createHonoHandler, createMultimodalMessage, createNestHandler, createPagesHandler, createPdfPart, createSystemMessage, createTelemetryMiddleware, createTelemetrySettings, createTextMessage, createTextPart, createToolSet, disableAITelemetry, disableDevTools, enableAITelemetry, functionToTool, getAICacheStats, getApprovalManager, getDevToolsState, getDevToolsUrl, getEvents, getMCPClient, getModel, getTelemetrySettings, getToolsNeedingApproval, getTracer, hasModelAlias, hasPendingApprovals, initOpenTelemetry, isDangerous, isDataUrl, isDevToolsEnabled, isTelemetryEnabled, isUrl, listModelAliases, mcpToolsToAITools, parseModel, pipeUIMessageStreamToResponse, recordEvent, resolveModelAlias, safeValidateUIMessages, setApprovalManager, stopAfterSteps, stopWhen, stopWhenNoToolCalls, toMessageContent, toUIMessageStreamResponse, transcribe, uint8ArrayToBase64, validateUIMessages, withApproval, withSpan, wrapModel } from "./ai";
export { AutoAgents, AutoTaskConfig, createAutoAgents } from "./auto";
export { BotRunStatus } from "./bots/protocols";
export { BaseCache, FileCache, MemoryCache, createFileCache, createMemoryCache } from "./cache";
export { CLI_SPEC_VERSION, executeCommand, parseArgs } from "./cli";
export { // Autonomy Mode
@@ -985,31 +967,26 @@ export { // Autonomy Mode
SandboxExecutor, // Scheduler
Scheduler, // Slash Commands
SlashCommandHandler, AiderAgent, ClaudeCodeAgent, CodexCliAgent, CommandValidator, CostTokenUsage, DEFAULT_BLOCKED_COMMANDS, DEFAULT_BLOCKED_PATHS, DEFAULT_IGNORE_PATTERNS, DiffViewer, FileCheckpointStorage, FileJobStorage, GeminiCliAgent, GenericExternalAgent, HistoryManager, MODEL_PRICING, MODE_POLICIES, MemoryCheckpointStorage, MemoryJobStorage, StatusDisplay, addLineRangeToFileMatch, cliApprovalPrompt, createAutonomyManager, createCheckpointManager, createCostTracker, createDiffViewer, createExternalAgent, createFastContext, createFileCheckpointStorage, createFileJobStorage, createFileMatch, createFlowDisplay, createGitManager, createHistoryManager, createInteractiveTUI, createJobQueue, createLineRange, createN8NIntegration, createRepoMap, createSandboxExecutor, createScheduler, createSlashCommandHandler, createStatusDisplay, cronExpressions, estimateTokens, executeSlashCommand, externalAgentAsTool, formatCost, getExternalAgentRegistry, getLineCount, getQuickContext, getRepoTree, getTotalLines, isSlashCommand, mergeRanges, parseSlashCommand, rangesOverlap, registerCommand, renderWorkflow, sandboxExec, triggerN8NWebhook } from "./cli/features";
export { ComputeError, DockerCompute, LocalCompute, listComputeProviders, registerComputeProvider, resolveComputeProvider } from "./compute";
export { // Classes
DictCondition, // Functions
evaluateCondition, // Types
type ConditionProtocol, ExpressionCondition, FunctionCondition, andConditions, createCondition, evaluate_condition, notCondition, orConditions } from "./conditions";
type ConditionProtocol, ExpressionCondition, FunctionCondition, andConditions, createCondition, notCondition, orConditions } from "./conditions";
export { // Enums
MemoryBackend, // Errors
ConfigValidationError, // Parse utilities
detect_url_scheme, // Presets
MEMORY_PRESETS, // Resolver functions
resolve, AUTONOMY_PRESETS, ArrayMode, CACHING_PRESETS, CONTEXT_PRESETS, ChunkingStrategy, EXECUTION_PRESETS, ExecutionPreset, FeatureMemoryConfig, GUARDRAIL_PRESETS, GuardrailAction, KNOWLEDGE_PRESETS, LearnBackend, LearnMode, LearnScope, MEMORY_URL_SCHEMES, MULTI_AGENT_EXECUTION_PRESETS, MULTI_AGENT_OUTPUT_PRESETS, OUTPUT_PRESETS, OutputPreset, PLANNING_PRESETS, PreCompactionMemoryFlushConfig, REFLECTION_PRESETS, RulesConfig, ToolSearchConfig, WEB_PRESETS, WebSearchProvider, apply_config_defaults, clean_triple_backticks, get_config, get_config_path, get_default, get_defaults_config, get_plugins_config, is_path_like, is_policy_string, parse_policy_string, resolve_autonomy, resolve_caching, resolve_context, resolve_execution, resolve_guardrails, resolve_hooks, resolve_knowledge, resolve_memory, resolve_output, resolve_planning, resolve_reflection, resolve_routing, resolve_skills, resolve_web, suggest_similar, validate_config } from "./config";
resolve, AUTONOMY_PRESETS, ArrayMode, CACHING_PRESETS, CONTEXT_PRESETS, ChunkingStrategy, EXECUTION_PRESETS, ExecutionPreset, FeatureMemoryConfig, GUARDRAIL_PRESETS, GuardrailAction, KNOWLEDGE_PRESETS, MEMORY_URL_SCHEMES, MULTI_AGENT_EXECUTION_PRESETS, MULTI_AGENT_OUTPUT_PRESETS, OUTPUT_PRESETS, OutputPreset, PLANNING_PRESETS, REFLECTION_PRESETS, WEB_PRESETS, WebSearchProvider, apply_config_defaults, clean_triple_backticks, get_config, get_config_path, get_default, get_defaults_config, get_plugins_config, is_path_like, is_policy_string, parse_policy_string, resolve_autonomy, resolve_caching, resolve_context, resolve_execution, resolve_guardrails, resolve_hooks, resolve_knowledge, resolve_memory, resolve_output, resolve_planning, resolve_reflection, resolve_routing, resolve_skills, resolve_web, suggest_similar, validate_config } from "./config";
export { createDbAdapter, db, getDefaultDbAdapter, setDefaultDbAdapter } from "./db";
export type { DbAdapter, DbConfig, DbMessage, DbRun, DbTrace } from "./db";
export { MemoryPostgresAdapter, NeonPostgresAdapter, PostgresSessionStorage, createMemoryPostgres, createNeonPostgres, createPostgresSessionStorage } from "./db/postgres";
export { MemoryRedisAdapter, UpstashRedisAdapter, createMemoryRedis, createUpstashRedis } from "./db/redis";
export { SQLiteAdapter, createSQLiteAdapter } from "./db/sqlite";
export { // Functions
// NB: the unaliased registerDisplayCallback name belongs to the per-type
// callback registry (callbacks module, // Types
type DisplayCallback, DisplayFlow, DisplayFlowConfig, asyncDisplayCallbacks, async_display_callbacks, clearDisplayCallbacks, clearErrorLogs, displayError, displayGenerating, displayInstruction, displayInteraction, displaySelfReflection, displayToolCall, display_error, display_generating, display_instruction, display_interaction, display_self_reflection, display_tool_call, errorLogs, error_logs, logError, registerDisplay, register_display_callback, syncDisplayCallbacks, sync_display_callbacks } from "./display";
export { // Types
type DisplayCallback, DisplayFlow, DisplayFlowConfig, asyncDisplayCallbacks, clearDisplayCallbacks, clearErrorLogs, displayError, displayGenerating, displayInstruction, displayInteraction, displaySelfReflection, displayToolCall, errorLogs, logError, registerDisplay, syncDisplayCallbacks } from "./display";
export { // Functions
embed, // Types
type EmbeddingResult, aembed, aembedding, aembeddings, cosineSimilarity, embedding, embeddings, euclideanDistance, getDimensions, get_dimensions, normalizeEmbedding, setEmbeddingConfig } from "./embeddings";
export { AGENT_ERROR_KINDS, FailoverDecision, IdleTimeoutBreaker, LEGACY_ERROR_CATEGORY_MAP, LLMError, NetworkError, PraisonAIConfigError, PraisonAIError, ToolExecutionError, ValidationError, isAgentErrorKind, isErrorContext, resolveErrorCategory } from "./errors";
export type { AgentErrorKind, ErrorContextProtocol, FailoverAction, FailoverDecisionOptions, LLMErrorOptions, LegacyErrorCategory, NetworkErrorOptions, PraisonAIConfigErrorOptions, PraisonAIErrorOptions, ToolExecutionErrorOptions, ValidationErrorOptions } from "./errors";
type EmbeddingResult, aembed, aembedding, aembeddings, cosineSimilarity, embedding, embeddings, euclideanDistance, getDimensions, normalizeEmbedding, setEmbeddingConfig } from "./embeddings";
export { // LLM-as-Judge
Judge, AccuracyJudge, CriteriaJudge, EvalResults, EvalSuite, Evaluator, RecipeJudge, accuracyEval, addJudge, addOptimizationRule, containsKeywordsCriterion, createDefaultEvaluator, createEvalResults, createEvaluator, getJudge, getOptimizationRule, lengthCriterion, listJudges, listOptimizationRules, noHarmfulContentCriterion, parseJudgeResponse, performanceEval, relevanceCriterion, reliabilityEval, removeJudge, removeOptimizationRule } from "./eval";
export { AgentEventBus, AgentEvents, EventEmitterPubSub, PubSub, createEventBus, createPubSub } from "./events";
@@ -1018,8 +995,7 @@ export { // Bot types
FailoverManager, // Enums
SandboxStatus, // Gateway types
type GatewayConfig, // Other types
type ProviderStatus, // Session-projection reducer (Issue #5324)
SessionProjection, AutonomyLevel, GatewayEventType, RagRetrievalPolicy } from "./gateway";
type ProviderStatus, AutonomyLevel, RagRetrievalPolicy } from "./gateway";
export { LLMGuardrail, createLLMGuardrail } from "./guardrails/llm-guardrail";
export { DisplayTypes, HooksManager, WorkflowHooksExecutor, clearAllCallbacks, clearApprovalCallback, createHooksManager, createLoggingOperationHooks, createLoggingWorkflowHooks, createTimingWorkflowHooks, createValidationOperationHooks, createWorkflowHooks, executeCallback, executeSyncCallback, getRegisteredDisplayTypes, hasApprovalCallback, registerApprovalCallback, registerDisplayCallback, requestApproval, unregisterDisplayCallback } from "./hooks";
export { // Computer Use
@@ -1031,11 +1007,7 @@ export { // Slack
createSlackBot, SlackBot, parseSlackMessage, verifySlackSignature } from "./integrations/slack";
export { BaseVectorStore, ChromaVectorStore, MemoryVectorStore, PineconeVectorStore, QdrantVectorStore, VectorQueryResult, WeaviateVectorStore, createChromaStore, createMemoryVectorStore, createPineconeStore, createQdrantStore, createWeaviateStore } from "./integrations/vector";
export { BaseVoiceProvider, ElevenLabsVoiceProvider, OpenAIVoiceProvider, createElevenLabsVoice, createOpenAIVoice } from "./integrations/voice";
export type { KnowledgeRecord } from "./knowledge";
export { GraphRAG, GraphStore, createGraphRAG } from "./knowledge/graph-rag";
export { Knowledge } from "./knowledge/knowledge";
export type { KnowledgeIndexOptions, KnowledgeSearchCallOptions, KnowledgeStoreConfig, KnowledgeStoreOptions } from "./knowledge/knowledge";
export { KnowledgeBase, KnowledgeDocument, KnowledgeSearchResult, createKnowledgeBase } from "./knowledge/rag";
export { BaseReranker, CohereReranker, CrossEncoderReranker, LLMReranker, createCohereReranker, createCrossEncoderReranker, createLLMReranker } from "./knowledge/reranker";
export { // Provider classes
OpenAIProvider, // Provider factory and utilities
@@ -1043,22 +1015,14 @@ export { // Provider classes
ProviderRegistry, // Types
type LLMProvider, AnthropicProvider, BaseProvider, GoogleProvider, ProviderMessage, ProviderToolDefinition, createProviderRegistry, getAvailableProviders, getDefaultProvider, getDefaultRegistry, hasProvider, isProviderAvailable, listProviders, parseModelString, registerBuiltinProviders, registerProvider, unregisterProvider } from "./llm/providers";
export { ADAPTERS, AISDK_PROVIDERS, COMMUNITY_PROVIDERS, PROVIDER_ALIASES } from "./llm/providers/ai-sdk/types";
export { AgentMessageEvent, CustomToolUseEvent, ManagedEvent, SessionErrorEvent, SessionIdleEvent, SessionRunningEvent, ToolConfirmationEvent, ToolUseEvent, UsageEvent, isManagedBackend } from "./managed";
export type { AgentMessageEventInit, CustomToolUseEventInit, ManagedBackendKwargs, ManagedBackendProtocol, ManagedContentBlock, ManagedEventInit, ManagedEventType, ManagedStopReason, SessionErrorEventInit, SessionIdleEventInit, ToolConfirmationEventInit, ToolUseEventInit, UsageEventInit } from "./managed";
export { MCPClient, MCPSecurity, MCPServer, MCPSessionManager, createApiKeyPolicy, createMCPClient, createMCPSecurity, createMCPServer, createMCPSession, createRateLimitPolicy, getMCPTools } from "./mcp";
export { ChromaMemory, InMemoryAdapter, MEMORY_PROVIDER_ALIASES, MemoryAdapterRegistry, addMemoryAdapter, addMemoryFactory, add_memory_adapter, add_memory_factory, createChromaMemoryAdapter, createDakeraMemoryAdapter, createMem0MemoryAdapter, createMongodbMemoryAdapter, createSqliteMemoryAdapter, getDefaultMemoryRegistry, getFirstAvailableMemoryAdapter, getMemoryAdapter, get_memory_adapter, hasMemoryAdapter, has_memory_adapter, listMemoryAdapters, list_memory_adapters, registerMemoryAdapter, registerMemoryFactory, register_memory_adapter, register_memory_factory, resetDefaultMemoryRegistry, resolveMemoryAdapterName, sanitizeChromaMetadata } from "./memory/adapters";
export type { ChromaMemoryConfig, MaybePromise, MemoryEmbedder, MemoryProtocol, MemoryRecord } from "./memory/adapters";
export { AutoMemory, AutoMemoryKnowledgeBase, AutoMemoryVectorStore, DEFAULT_POLICIES, createAutoMemory, createLLMSummarizer } from "./memory/auto-memory";
export { DocsManager, createDocsManager } from "./memory/docs-manager";
export { FileMemory, createFileMemory } from "./memory/file-memory";
export { MemoryHooks, createEncryptionHooks, createLoggingHooks, createMemoryHooks, createValidationHooks } from "./memory/hooks";
export { BaseStore, DecisionStore, FeedbackStore, ImprovementStore, InsightStore, LearnBackendNotAvailableError, LearnEntry, LearnError, LearnManager, LearnManagerMode, MongoDBLearnBackend, PatternStore, PersonaStore, RedisLearnBackend, SQLiteLearnBackend, ThreadStore, getDataDir, getLearnDir, resolveLearnConfig, toLearnEntryDict } from "./memory/learn";
export type { AsyncLearnProtocol, BaseStoreOptions, LearnEntryConvertible, LearnEntryData, LearnEntryInit, LearnEntryLike, LearnExtractor, LearnManagerConfig, LearnManagerProtocol, LearnMessage, LearnProtocol, LearnStorageBackend, LearnStore, ProcessConversationResult, ResolvedLearnConfig } from "./memory/learn";
export { Memory, createMemory } from "./memory/memory";
export type { MemoryConfig, MemoryEntry } from "./memory/memory";
export { RulesManager, createRulesManager, createSafetyRules } from "./memory/rules-manager";
export { DEFAULT_PROFILE, HarnessProfile, ModelRequestBlocked, ScriptExhausted, ScriptedModel, allowModelRequests, listHarnessProfiles, modelRequestsAllowed, noModelRequests, registerProfile, register_profile, resetHarnessRegistry, resolveHarness, resolve_harness } from "./model-harness";
export type { HarnessProfileConfig, HarnessRegistryEntry, HarnessResolverProtocol } from "./model-harness";
export { // Adapters
NoopObservabilityAdapter, // Constants
OBSERVABILITY_TOOLS, // Global adapter management
@@ -1066,6 +1030,15 @@ export { // Adapters
type SpanKind, ConsoleObservabilityAdapter, MemoryObservabilityAdapter, clearAdapterCache, createConsoleAdapter, createMemoryAdapter, createObservabilityAdapter, getObservabilityAdapter, getObservabilityToolInfo, hasObservabilityToolEnvVar, listObservabilityTools, noopAdapter, resetObservabilityAdapter, trace } from "./observability";
export { AgentApp, AgentAppConfig, AgentAppProtocol, AgentOS, AgentOSConfig, AgentOSProtocol, DEFAULT_AGENTOS_CONFIG, mergeConfig } from "./os";
export type { AgentAppOptions, AgentOSOptions } from "./os";
export { // P0: Call Types (new)
type MCPCall, // P0: Specialized Agent Configs (new)
type AudioConfig, // P0: Specialized Agents (new)
CodeAgent, // P1: Workflow Patterns (new)
Chunking, // P2: Context Types (new - only items not already exported)
ContextManager, // P3: Display callbacks (snake_case for Python parity)
register_display_callback, // P3: Plugin functions
get_plugin_manager, // P3: Trace & condition functions
evaluate_condition, EmbeddingAgent, If, Knowledge, MCP, OCRAgent, Parallel, RealtimeAgent, Route, Session, VideoAgent, VisionAgent, async_display_callbacks, cleanup_telemetry_resources, create_context_agent, disable_performance_mode, disable_telemetry, discover_and_load_plugins, discover_plugins, display_error, display_generating, display_instruction, display_interaction, display_self_reflection, display_tool_call, enable_performance_mode, enable_telemetry, ensure_plugin_dir, error_logs, get_default_plugin_dirs, get_dimensions, get_plugin_template, get_telemetry, handoff_filters, load_plugin, parse_plugin_header, parse_plugin_header_from_file, prompt_with_handoff_instructions, resolve_guardrail_policies, sync_display_callbacks, trace_context, track_workflow, when } from "./parity";
export { // Core classes
Plan, // Python parity additions
ApprovalCallback, PlanStep, PlanStorage, PlanningAgent, READ_ONLY_TOOLS, RESEARCH_TOOLS, RESTRICTED_TOOLS, TaskAgent, TodoItem, TodoList, createApprovalCallback, createPlan, createPlanStorage, createPlanningAgent, createTaskAgent, createTodoList } from "./planning";
@@ -1073,51 +1046,36 @@ export { // Classes
Plugin, // Enums
PluginHook, // Functions
getPluginManager, // Interfaces
type PluginMetadata, FunctionPlugin, PluginManager, PluginParseError, PluginType, disablePlugins, discoverAndLoadPlugins, discoverPlugins, discover_and_load_plugins, discover_plugins, enablePlugins, ensurePluginDir, ensure_plugin_dir, getDefaultPluginDirs, getPluginTemplate, get_default_plugin_dirs, get_plugin_manager, get_plugin_template, isPluginEnabled, listPlugins, loadPlugin, load_plugin, parsePluginHeader, parsePluginHeaderFromFile, parse_plugin_header, parse_plugin_header_from_file } from "./plugins";
type PluginMetadata, FunctionPlugin, PluginManager, PluginParseError, PluginType, disablePlugins, discoverAndLoadPlugins, discoverPlugins, enablePlugins, ensurePluginDir, getDefaultPluginDirs, getPluginTemplate, isPluginEnabled, listPlugins, loadPlugin, parsePluginHeader, parsePluginHeaderFromFile } from "./plugins";
export { // A2A Protocol
A2ATaskState, // AGUI Protocol
AGUI, // AgentManager alias type
type AgentManager, // Global singletons
config, // Guardrail policies
type GuardrailPolicy, // Tools class
type ToolDefinition, A2A, A2ARole, AutoRagAgent, AutoRetrievalPolicy, DEFAULT_AUTO_KEYWORDS, GUARDRAIL_POLICY_PRESETS, Tools, memory, obs, resolveGuardrailPolicies, resolve_guardrail_policies, workflows } from "./protocols";
type ToolDefinition, A2A, A2ARole, AutoRagAgent, AutoRetrievalPolicy, DEFAULT_AUTO_KEYWORDS, GUARDRAIL_POLICY_PRESETS, Tools, memory, obs, resolveGuardrailPolicies, workflows } from "./protocols";
export { CitationsMode, DEFAULT_RAG_TEMPLATE, RAG, RAGCitation, RAGContextPack, RetrievalPolicy, RetrievalStrategy, createCitation, createContextPack, createRAG, createRAGConfig, createRAGResult, createRetrievalConfig, createSimpleRetrievalConfig, createSmartRetrievalConfig, formatAnswerWithCitations, formatCitation, formatContextPackForPrompt, hasCitations } from "./rag";
export { PraisonAIRuntime, RuntimeRegistry, RuntimeRegistryEntry, RuntimeRegistryError, addRuntimeAlias, getRuntimeRegistry, isAgentRuntime, isRuntimeAvailable, listRuntimes, list_runtimes, registerRuntime, register_runtime, resolveRuntime, resolve_runtime, unregisterRuntime } from "./runtime";
export type { AgentRuntimeProtocol, RunTurnOptions, RuntimeCapabilityMatrix, RuntimeConfig, RuntimeDelta, RuntimeDeltaType, RuntimeFactory, RuntimeMode, RuntimeRegistryEntryInit, RuntimeRegistryProtocol, RuntimeResult, TurnContextBuilderProtocol, TurnRuntimeProtocol } from "./runtime";
export type { RunStatus } from "./session";
export { Session } from "./session/session";
export { // Python parity additions
SkillLoader, EnforcementLevel, SkillManager, SkillParseError, SkillState, createSkillLoader, createSkillManager, createSkillProperties, discoverSkill, discoverSkills, discover_skills, findSkillMd, getDefaultSkillDirs, loadSkill, load_skill, parseFrontmatter, parseSkillFile, validate, validateMetadata, validateSkill, validate_metadata } from "./skills";
export type { RemoteSkillSource } from "./skills";
SkillLoader, SkillManager, createSkillLoader, createSkillManager, createSkillProperties, parseSkillFile } from "./skills";
export { AgentTask, AgentTaskConfig, BaseTask, createTaskOutput } from "./task";
export { // Python parity additions
MinimalTelemetry, AgentTelemetry, PerformanceMonitor, TelemetryCollector, TelemetryIntegration, cleanupTelemetry, cleanupTelemetryResources, cleanup_telemetry_resources, createAgentTelemetry, createConsoleSink, createHTTPSink, createPerformanceMonitor, createTelemetryIntegration, disablePerformanceMode, disableTelemetry, disable_performance_mode, disable_telemetry, enablePerformanceMode, enableTelemetry, enable_performance_mode, enable_telemetry, getMinimalTelemetry, getTelemetry, get_telemetry } from "./telemetry";
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, TOOL_TRUST_LEVELS, ToolRegistry, ToolResult, ToolValidationError, add_tool, createDelegator, createSubagentTool, createSubagentTools, createTool, getRegistry, getTool, getToolDefinitions, get_registry, get_tool, get_tool_definitions, hasTool, has_tool, listTools, list_tools, registerTool, register_tool, removeTool, remove_tool, tool, validateTool, validate_tool } from "./tools";
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 { MCP, MCPToolTransportType } from "./tools/mcp";
export { BudgetExceededError, MissingDependencyError, MissingEnvVarError, ToolConstructionError, ToolNotRegisteredError, ToolsRegistry, composeMiddleware, createLoggingMiddleware, createRateLimitMiddleware, createRedactionMiddleware, createRetryMiddleware, createTimeoutMiddleware, createToolInstance, createToolsRegistry, createTracingMiddleware, createValidationMiddleware, getToolsRegistry, registerToolFactory, resetToolsRegistry, tryCreateToolInstance, validateToolInstall } from "./tools/registry";
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 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 { TOOLSET_TOOL_ID_MAP, ToolsetRegistry, ToolsetSpec, getToolset, getToolsetRegistry, get_toolset, get_toolset_registry, hasToolset, has_toolset, listToolsets, list_toolsets, registerToolset, register_toolset, resolveToolset, resolveToolsetBuiltinIds, resolveToolsets, resolveToolsetsForModel, resolve_toolset, resolve_toolsets, resolve_toolsets_for_model, toolsetToolId, unregisterToolset, unregister_toolset } from "./toolsets";
export type { ToolsetSpecConfig } from "./toolsets";
export { // Classes
TraceSink, // Enums
ContextEventType, // Functions
createContextEvent, // Types
type ContextEvent, ContextListSink, ContextNoOpSink, ContextTraceEmitter, ContextTraceSink, EventType, MessageType, TraceCtx, traceContext, trace_context, trackWorkflow, track_workflow } from "./trace";
export { A2UI, A2UINotInstalledError, A2UI_MIME_TYPE, createA2uiPart, getSchemaManager, isA2uiPart, parseA2uiResponse } from "./ui/a2ui";
export type { A2UIAdapter, A2UISystemPromptOptions, A2UIToolResultProtocol } from "./ui/a2ui";
export { AdapterBackendNotAvailableError, AdapterCreationError, AdapterRegistry, isBackendUnavailableError } from "./utils/adapter-registry";
export type { AdapterClass, AdapterFactory, AdapterKwargs } from "./utils/adapter-registry";
export { Logger, PraisonLogger, ROOT_LOGGER_NAME, StructuredFormatter, configureStructuredLogging, configure_structured_logging, getLogger, get_logger, normalizeLoggerName } from "./utils/logger";
export type { GetLoggerOptions, LogFormatter, LogLevelName, LogRecord, StructuredFormatterOptions } from "./utils/logger";
export { VERSION, __version__, getVersion } from "./version";
type ContextEvent, ContextListSink, ContextNoOpSink, ContextTraceEmitter, ContextTraceSink, EventType, MessageType, TraceCtx, traceContext, trackWorkflow } from "./trace";
export { // New: Python-parity Loop and Repeat classes
Loop, // Task class
Task, AgentFlow, DEFAULT_MAX_PARALLEL_WORKERS, If, Include, MAX_NESTING_DEPTH, NestingDepthError, PARALLEL_ON_FAILURE_MODES, Parallel, Pipeline, Repeat, Route, Workflow, WorkflowStepError, evaluateWorkflowCondition, getRecipeResolver, ifStep, if_, include, isControlFlowPattern, loop, loopPattern, parallel, parallelPattern, repeat, repeatPattern, route, routePattern, setRecipeResolver, substituteWorkflowVariables, when } from "./workflows";
export type { AgentLikeStep, FlowStep, IncludableWorkflow, LoopConfig, LoopResult, ParallelBranchError, ParallelOnFailure, RecipeResolver, RepeatConfig, RepeatContext, RepeatResult, StepContextConfig, StepExecutionConfig, StepOutputConfig, StepResult, StepRoutingConfig, TaskConfig, WorkflowContext } from "./workflows";
export { YAMLWorkflowParser, createWorkflowFromYAML, loadWorkflowFromFile, parseYAMLWorkflow, validateWorkflowDefinition } from "./workflows/yaml-parser";
Task, AgentFlow, Pipeline, Repeat, Workflow, loop, loopPattern, parallel, repeat, repeatPattern, route } from "./workflows";
export type { LoopConfig, LoopResult, RepeatConfig, RepeatContext, RepeatResult, StepContextConfig, StepExecutionConfig, StepOutputConfig, StepResult, StepRoutingConfig, TaskConfig, WorkflowContext } from "./workflows";
export { createWorkflowFromYAML, loadWorkflowFromFile, parseYAMLWorkflow, validateWorkflowDefinition } from "./workflows/yaml-parser";
```
# Optional Plugins
+10
View File
@@ -0,0 +1,10 @@
# 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>=4.7.11" \
"praisonai>=4.7.0" \
"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>=4.7.11" \
"praisonai>=4.7.0" \
"praisonai[ui]" \
"praisonai[chat]" \
"praisonai[realtime]" \
+1 -1
View File
@@ -16,7 +16,7 @@ RUN mkdir -p /root/.praison
# Install Python packages (using latest versions)
RUN pip install --no-cache-dir \
praisonai_tools \
"praisonai>=4.7.11" \
"praisonai>=4.7.0" \
"praisonai[ui]" \
"praisonai[crewai]"
+5 -5
View File
@@ -178,19 +178,19 @@ def example_url_parsing():
print("\n=== Example 9: URL Parsing ===")
# Memory supports URL connection strings
# Supported schemes: sqlite://, mongodb://, mongodb+srv://
# Supported: postgresql://, redis://, sqlite:///, mongodb://
agent = Agent(
instructions="You are a database-backed assistant",
memory="mongodb://user:password@localhost:27017/praisonai",
memory="postgresql://postgres:password@localhost:5432/praisonai",
)
print("Memory URL parsed: memory enabled")
# Also works with presets
agent2 = Agent(
instructions="You are a sqlite-backed assistant",
memory="sqlite", # Preset name
instructions="You are a redis-backed assistant",
memory="redis", # Preset name
)
print("Memory preset 'sqlite': configured")
print("Memory preset 'redis': configured")
def example_knowledge_sources():
+4 -4
View File
@@ -8,15 +8,15 @@ agent = Agent(
)
# With preset
agent_sqlite = Agent(
agent_redis = Agent(
instructions="You are a helpful assistant.",
memory="sqlite", # Uses sqlite preset
memory="redis", # Uses redis preset
)
# With URL
agent_mongo = Agent(
agent_postgres = Agent(
instructions="You are a helpful assistant.",
memory="mongodb://localhost/mydb", # URL auto-detected
memory="postgresql://localhost/mydb", # URL auto-detected
)
if __name__ == "__main__":
+1 -1
View File
@@ -140,4 +140,4 @@ Key fixes applied:
4. String-based LLM guardrails are also supported
The guardrail will automatically retry (up to max_retries times) if validation fails.
""")
""")
+3 -34
View File
@@ -1,32 +1,5 @@
# MCP Server Examples
## Install (SHA-256)
Pin GitHub Release **v0.6.0** and verify `SHA256SUMS`. Website `install.sh` / `install.ps1` abort on mismatch.
https://github.com/LinespottingOrg/GrokBuildRemote-Agents/releases/tag/v0.6.0
https://github.com/LinespottingOrg/GrokBuildRemote-Agents/blob/main/docs/PINNED-INSTALL.md
```
96cef605d3e030ccef99d27ea6240e0d3b668dd045e6b5b9e585c9fd03c6ef23 gbr-agent-darwin-amd64
de7e065ef2cf6877b3b2cd04679a67b627f876337f529247e236204543e4062c gbr-agent-darwin-arm64
a50a5c41993e6531a3b477eb409ccc845212bf541384dc803061c80657f86719 gbr-agent-linux-amd64
5bfd22c7110234942c4c02ff8154b836d0af45a9422c178a4f52010187d40061 gbr-agent-linux-arm64
f773b89fd31310172b756e0593e0f3b2382b0a3440af2a7d0a8b3073b0c23e27 gbr-agent-windows-amd64.exe
8fb9efcbc7e2ac91c11964944bf0f45e31bb23f4356d9dcb4b305d7cb9b0fe8c gbr-agent-windows-arm64.exe
```
```bash
VER=v0.6.0
BASE=https://github.com/LinespottingOrg/GrokBuildRemote-Agents/releases/download/$VER
# swap darwin-arm64 for your OS/arch
curl -fsSL -o gbr-agent-darwin-arm64 "$BASE/gbr-agent-darwin-arm64"
curl -fsSL -o SHA256SUMS "$BASE/SHA256SUMS"
shasum -a 256 -c SHA256SUMS --ignore-missing
gbr-agent pair && gbr-agent run
```
Examples demonstrating the MCP Server v2 features per MCP Protocol Version 2025-11-25.
## Features Demonstrated
@@ -163,13 +136,9 @@ These examples comply with MCP Protocol Version 2025-11-25:
Pair a phone running [Build Remote Agent](https://grokbuildremote.com/) to a PraisonAI agent via MCP stdio `gbr-mcp` (protocol `gbr/1`). Requires `gbr-agent pair && gbr-agent run`. Phone is spectator. Never put mailbox keys in the example.
Clone [`GrokBuildRemote-Agents`](https://github.com/LinespottingOrg/GrokBuildRemote-Agents), run `npm install` in `mcp/gbr-mcp`, then point `GBR_MCP_JS` at the entrypoint (defaults to `GrokBuildRemote-Agents/mcp/gbr-mcp/bin/gbr-mcp.js` relative to the clone; resolved to an absolute path so the example runs from any directory):
```bash
export GBR_MCP_JS=/abs/path/to/GrokBuildRemote-Agents/mcp/gbr-mcp/bin/gbr-mcp.js
python gbr_pair.py
```
## What the phone sees
**Terminal windows** on this PC (machine-wide mailbox). Not headless OpenCode / CodeNomad sidecar / Electron. `:8788` in a sidecar is Bot API JSON, not a transcript.
https://github.com/LinespottingOrg/GrokBuildRemote-Agents/blob/main/docs/WHAT-THE-PHONE-SEES.md
https://grokbuildremote.com/integrations.html
+13 -39
View File
@@ -19,37 +19,21 @@ Independent product by Linespotting AB. Not affiliated with xAI or SpaceX.
https://grokbuildremote.com/
"""
import os
from praisonaiagents import Agent, MCP
# Clone https://github.com/LinespottingOrg/GrokBuildRemote-Agents.git
# Clone https://github.com/LinespottingOrg/GrokBuildRemote-Agents.git then point
# GBR_MCP_JS at mcp/gbr-mcp/bin/gbr-mcp.js (loopback stdio). Resolved to an
# absolute path so the example runs from any working directory. Override with:
# export GBR_MCP_JS=/abs/path/to/GrokBuildRemote-Agents/mcp/gbr-mcp/bin/gbr-mcp.js
GBR_MCP_JS = os.path.abspath(
os.environ.get(
"GBR_MCP_JS",
"GrokBuildRemote-Agents/mcp/gbr-mcp/bin/gbr-mcp.js",
)
)
## Install (SHA-256)
Pin GitHub Release **v0.6.0** and verify `SHA256SUMS`. Website `install.sh` / `install.ps1` abort on mismatch.
https://github.com/LinespottingOrg/GrokBuildRemote-Agents/releases/tag/v0.6.0
https://github.com/LinespottingOrg/GrokBuildRemote-Agents/blob/main/docs/PINNED-INSTALL.md
```
96cef605d3e030ccef99d27ea6240e0d3b668dd045e6b5b9e585c9fd03c6ef23 gbr-agent-darwin-amd64
de7e065ef2cf6877b3b2cd04679a67b627f876337f529247e236204543e4062c gbr-agent-darwin-arm64
a50a5c41993e6531a3b477eb409ccc845212bf541384dc803061c80657f86719 gbr-agent-linux-amd64
5bfd22c7110234942c4c02ff8154b836d0af45a9422c178a4f52010187d40061 gbr-agent-linux-arm64
f773b89fd31310172b756e0593e0f3b2382b0a3440af2a7d0a8b3073b0c23e27 gbr-agent-windows-amd64.exe
8fb9efcbc7e2ac91c11964944bf0f45e31bb23f4356d9dcb4b305d7cb9b0fe8c gbr-agent-windows-arm64.exe
```
```bash
VER=v0.6.0
BASE=https://github.com/LinespottingOrg/GrokBuildRemote-Agents/releases/download/$VER
# swap darwin-arm64 for your OS/arch
curl -fsSL -o gbr-agent-darwin-arm64 "$BASE/gbr-agent-darwin-arm64"
curl -fsSL -o SHA256SUMS "$BASE/SHA256SUMS"
shasum -a 256 -c SHA256SUMS --ignore-missing
gbr-agent pair && gbr-agent run
```
# then point args at mcp/gbr-mcp/bin/gbr-mcp.js (loopback stdio).
gbr = Agent(
instructions=(
"You can attach a phone spectator via Build Remote Agent. "
@@ -57,20 +41,10 @@ gbr = Agent(
"at 127.0.0.1:8788. Do not request mailbox keys."
),
llm="gpt-4o-mini",
tools=MCP(
"node",
args=["GrokBuildRemote-Agents/mcp/gbr-mcp/bin/gbr-mcp.js"],
),
tools=MCP("node", args=[GBR_MCP_JS]),
)
if __name__ == "__main__":
gbr.start(
"Check Build Remote Agent health on 127.0.0.1:8788 and list sessions."
)
## What the phone sees
**Terminal windows** on this PC (machine-wide mailbox). Not headless OpenCode / CodeNomad sidecar / Electron. `:8788` in a sidecar is Bot API JSON, not a transcript.
https://github.com/LinespottingOrg/GrokBuildRemote-Agents/blob/main/docs/WHAT-THE-PHONE-SEES.md
https://grokbuildremote.com/integrations.html
@@ -1,110 +0,0 @@
"""
HOL Guard Tool Policy Example - PraisonAI Agents
Demonstrates using HOL Guard (an optional, external runtime security engine)
at the existing `wrap_tool_call` middleware boundary to inspect command-bearing
tool calls *before* they execute.
HOL Guard is installed and versioned separately. Its side-effect-free CLI can
classify a shell command before execution:
hol-guard command test '<command>' --json
Fail-closed policy: the wrapped tool only runs when Guard returns an explicit
allow/benign classification. Review/block/unknown verdicts, malformed output,
timeouts, or CLI failures all short-circuit the call so the tool never runs.
pip install hol-guard # optional, external dependency
"""
import json
import shutil
import subprocess
from praisonaiagents import Agent, tool
from praisonaiagents.hooks import wrap_tool_call, ToolRequest, ToolResponse
COMMAND_BEARING_TOOLS = {"run_shell"}
GUARD_TIMEOUT_SECONDS = 10
@tool
def run_shell(command: str) -> str:
"""Run a shell command and return its output."""
result = subprocess.run(
command, shell=True, capture_output=True, text=True
)
return result.stdout or result.stderr
def _inspect_with_hol_guard(command: str) -> bool:
"""Return True only if HOL Guard explicitly allows the command.
Fails closed (returns False) on any ambiguity: missing CLI, non-zero exit,
timeout, malformed JSON, or a non-allow verdict.
"""
if not shutil.which("hol-guard"):
return False
try:
completed = subprocess.run(
["hol-guard", "command", "test", command, "--json"],
capture_output=True,
text=True,
timeout=GUARD_TIMEOUT_SECONDS,
)
except (subprocess.TimeoutExpired, OSError):
return False
if completed.returncode != 0:
return False
try:
verdict = json.loads(completed.stdout)
except (json.JSONDecodeError, ValueError):
return False
if not isinstance(verdict, dict):
return False
decision = str(verdict.get("decision", "")).lower()
return decision in ("allow", "benign")
@wrap_tool_call
def hol_guard_tool_policy(request: ToolRequest, call_next):
"""Gate command-bearing tools through HOL Guard before execution."""
if request.tool_name not in COMMAND_BEARING_TOOLS:
return call_next(request)
command = request.arguments.get("command", "")
if _inspect_with_hol_guard(command):
return call_next(request)
blocked_message = "Blocked by HOL Guard: command was not explicitly allowed."
# Surface the denial in `result` too: the agent tool executor returns
# `ToolResponse.result` to the model and discards `error`, so a denial with
# only `error` set would reach the model as a null result. Keeping `error`
# populated preserves the signal for after_tool hooks and logging.
return ToolResponse(
tool_name=request.tool_name,
result=blocked_message,
error=blocked_message,
context=request.context,
)
agent = Agent(
name="GuardedShellBot",
instructions="You run shell commands only when they are safe.",
tools=[run_shell],
hooks=[hol_guard_tool_policy],
)
if __name__ == "__main__":
print("HOL Guard tool policy registered on 'run_shell'.")
print("Commands are only executed when Guard returns an explicit allow.")
print("\n✓ HOL Guard example complete")
@@ -1,18 +1,16 @@
"""
Chroma Knowledge Store - Agent-First Example
Qdrant Knowledge Store - Agent-First Example
Demonstrates using Chroma (a shipped vector store) for knowledge-based RAG
with an Agent.
To use a provider that is not shipped (e.g. Qdrant), register an adapter
first with ``register_knowledge_adapter("qdrant", MyQdrantAdapter)`` and then
pass ``"provider": "qdrant"``.
Demonstrates using Qdrant for knowledge-based RAG with an Agent.
Requirements:
pip install "praisonai[tools]"
Docker Setup:
docker run -d --name praison-qdrant -p 6333:6333 qdrant/qdrant
Run:
python knowledge_chroma.py
python knowledge_qdrant.py
Expected Output:
Agent responds using knowledge from documents
@@ -46,16 +44,17 @@ doc_path = os.path.join(temp_dir, "guide.txt")
with open(doc_path, "w") as f:
f.write(sample_doc)
print("=== Chroma Knowledge Store Demo (Agent-First) ===")
print("=== Qdrant Knowledge Store Demo (Agent-First) ===")
# Agent-first approach: use knowledge parameter with a shipped vector store
# Agent-first approach: use knowledge parameter with Qdrant
agent = Agent(
name="KnowledgeAssistant",
instructions="You are a helpful assistant with access to technical documentation.",
knowledge={
"sources": [doc_path],
"vector_store": {
"provider": "chroma",
"provider": "qdrant",
"url": "http://localhost:6333",
},
}
)
@@ -71,4 +70,4 @@ print("\n=== Demo Complete ===")
# --- Advanced: Direct Store Usage ---
# from praisonai.persistence.factory import create_knowledge_store
# store = create_knowledge_store("chroma")
# store = create_knowledge_store("qdrant", url="http://localhost:6333")
@@ -1,73 +0,0 @@
"""
Meeting Notes Agent
An AI meeting-notes pipeline composed entirely from existing PraisonAI
primitives — no new SDK surface required:
1. AudioAgent.transcribe() -> Whisper speech-to-text
2. Agent (summary) -> structured summary + action items
3. Agent (knowledge=[...]) -> index transcript for cross-meeting Q&A
Usage:
python meeting-notes-agent.py path/to/recording.mp3
Requires: OPENAI_API_KEY (or any LiteLLM-supported STT/LLM provider).
"""
import sys
from praisonaiagents import Agent, AudioAgent
def transcribe_meeting(audio_path: str) -> str:
"""Speech-to-text using the built-in Whisper AudioAgent."""
stt = AudioAgent(llm="openai/whisper-1")
return stt.transcribe(audio_path)
def summarize_meeting(transcript: str) -> str:
"""Summarize decisions, topics, and action items."""
notetaker = Agent(
name="Meeting Notetaker",
instructions=(
"You are an expert meeting notetaker. Given a raw transcript, produce:\n"
"1. A concise summary (3-5 sentences).\n"
"2. Key decisions made.\n"
"3. Action items as a checklist with owners when mentioned.\n"
"Only include action items that were actually spoken."
),
)
return notetaker.start(f"Transcript:\n\n{transcript}")
def build_qa_agent(transcript_path: str) -> Agent:
"""Index the transcript for semantic search and cross-meeting Q&A."""
return Agent(
name="Meeting Q&A",
instructions="Answer questions using only the indexed meeting transcripts. Cite what was said.",
knowledge=[transcript_path],
)
def main() -> None:
if len(sys.argv) < 2:
print("Usage: python meeting-notes-agent.py <audio_file>")
sys.exit(1)
audio_path = sys.argv[1]
transcript = transcribe_meeting(audio_path)
transcript_path = "meeting_transcript.txt"
with open(transcript_path, "w", encoding="utf-8") as f:
f.write(transcript)
notes = summarize_meeting(transcript)
print("\n=== Meeting Notes ===\n")
print(notes)
qa = build_qa_agent(transcript_path)
print("\n=== Q&A ===\n")
print(qa.start("What were the main action items and who owns them?"))
if __name__ == "__main__":
main()
@@ -1,34 +0,0 @@
"""
Basic example of using EvoLink.AI with PraisonAI.
"""
import os
from praisonaiagents import Agent
api_key = os.getenv("EVOLINK_API_KEY")
if not api_key:
raise RuntimeError(
"EVOLINK_API_KEY is not set. Set it before running this example: "
"export EVOLINK_API_KEY=your_api_key"
)
agent = Agent(
instructions="You are a helpful assistant",
llm={
"model": "openai/gpt-5.2",
"api_key": api_key,
"base_url": "https://direct.evolink.ai/v1",
},
)
response = agent.start("Hello! Share one practical AI automation idea.")
print(response)
coding_task = """
Write a Python function that validates whether a string is a palindrome.
Include a short docstring and ignore spaces and capitalization.
"""
response = agent.start(coding_task)
print(response)
-28
View File
@@ -1,28 +0,0 @@
"""OpenRouter video generation via VideoAgent.
Requires OPENROUTER_API_KEY. Optionally set OPENROUTER_REFERER and
OPENROUTER_APP_TITLE for OpenRouter dashboard attribution.
The openrouter/ prefix is required so the request routes to OpenRouter.
Discover exact model ids at https://openrouter.ai/api/v1/videos/models.
"""
from praisonaiagents import VideoAgent
agent = VideoAgent(llm="openrouter/google/veo-3.1")
video = agent.generate(
"A serene mountain landscape at sunset, locked camera",
duration=6,
resolution="720p",
aspect_ratio="16:9",
generate_audio=False,
)
print(f"Video ID: {video.id}")
completed = agent.wait_for_completion(video.id)
if completed.status == "completed":
agent.download(video.id, "openrouter_veo.mp4")
print("Saved openrouter_veo.mp4")
else:
print(f"Generation ended with status: {completed.status}")
+1 -1
View File
@@ -15,4 +15,4 @@ if completed.status == "completed":
# List all videos
videos = agent.list()
# Models: openai/sora-2, gemini/veo-3.1-generate-preview, azure/sora-2
# Models: openai/sora-2, gemini/veo-3.0-generate-preview, azure/sora-2
@@ -16,13 +16,9 @@ Architecture:
Harbor Container → `praisonai code -p --output json "TASK" --dangerously-skip-approval`
Notes:
- `--dangerously-skip-approval` registers an always-approve backend on the
approval registry (plus PRAISON_APPROVAL_MODE=auto /
PRAISONAI_TOOL_SAFETY=off) so the assistant runs fully autonomously in the
container. Before that registry wiring existed the flag left every
critical-tool prompt in place and the non-TTY container auto-denied all of
them, so the agent could not run a single shell command while still
exiting 0 -- one cause of the 0.000 scores in #3932.
- `--dangerously-skip-approval` sets PRAISON_APPROVAL_MODE=auto +
PRAISONAI_TOOL_SAFETY=off so the assistant runs fully autonomously in the
container (no approval hang in a non-TTY session).
- The JSON envelope provides token, cost, session, and status metadata while
the real exit status still surfaces install/auth/startup failures.
- The base `praisonai` package is sufficient; heavy `code` extras are not
+10 -14
View File
@@ -1,25 +1,17 @@
"""Qdrant Vector Store - Agent-First Example
"""Qdrant Vector Store - Agent-First Example (requires Docker)
Qdrant is not a shipped adapter. Register one first, then use it via the
``knowledge`` parameter. If no adapter is registered this example skips
cleanly instead of crashing.
from praisonaiagents.knowledge.adapters import register_knowledge_adapter
register_knowledge_adapter("qdrant", MyQdrantAdapter)
Docker: docker run -d --name qdrant -p 6333:6333 qdrant/qdrant
"""
import sys
import os
from praisonaiagents import Agent
from praisonaiagents.knowledge.adapters import list_knowledge_adapters
if "qdrant" not in list_knowledge_adapters():
print("SKIPPED: Qdrant - no 'qdrant' adapter registered")
sys.exit(0)
# Agent-first approach: use knowledge parameter with Qdrant
url = os.getenv("QDRANT_URL", "http://localhost:6333")
# Agent-first approach: use knowledge parameter with a registered Qdrant adapter
agent = Agent(
name="Assistant",
instructions="You are a helpful assistant with access to documents.",
knowledge={"sources": ["./docs/guide.pdf"], "vector_store": {"provider": "qdrant"}}
knowledge={"sources": ["./docs/guide.pdf"], "vector_store": {"provider": "qdrant", "url": url}}
)
# Chat - agent uses knowledge for RAG
@@ -27,3 +19,7 @@ response = agent.chat("What information do you have?")
print(f"Response: {response}")
print("PASSED: Qdrant with Agent")
# --- Advanced: Direct Store Usage ---
# from praisonai.persistence import create_knowledge_store
# store = create_knowledge_store("qdrant", url=url)
+4 -3
View File
@@ -27,10 +27,11 @@ mcp:
enabled: true
time:
# Time and date utilities (published Python MCP server via uvx)
command: uvx
# Time and date utilities
command: npx
args:
- "mcp-server-time"
- "-y"
- "@modelcontextprotocol/server-time"
env: {}
enabled: true
@@ -0,0 +1,9 @@
{
"short_term_limit": 100,
"long_term_limit": 1000,
"episodic_retention_days": 30,
"enable_summarization": false,
"summarization_threshold": 50,
"importance_threshold": 0.7,
"auto_promote": true
}
@@ -0,0 +1,21 @@
{
"root_path": "/var/folders/0b/t9c4hwvx6lg6jk58gw8w_dp80000gn/T/tmp6_tn0h1t",
"total_files": 0,
"total_tokens": 11,
"levels": 3,
"built_at": "2026-02-02T17:47:19.241146",
"nodes": {
"/var/folders/0b/t9c4hwvx6lg6jk58gw8w_dp80000gn/T/tmp6_tn0h1t": {
"path": "/var/folders/0b/t9c4hwvx6lg6jk58gw8w_dp80000gn/T/tmp6_tn0h1t",
"level": 3,
"summary": "Project with 0 folders and 0 root files: ",
"children": [],
"token_count": 11,
"created_at": "2026-02-02T17:47:19.241224",
"metadata": {
"folder_count": 0,
"root_file_count": 0
}
}
}
}
@@ -0,0 +1,35 @@
{
"root_path": "/var/folders/0b/t9c4hwvx6lg6jk58gw8w_dp80000gn/T/tmp7wxr57wm",
"total_files": 1,
"total_tokens": 16,
"levels": 2,
"built_at": "2026-02-02T17:47:19.243732",
"nodes": {
"/var/folders/0b/t9c4hwvx6lg6jk58gw8w_dp80000gn/T/tmp7wxr57wm/src/app.py": {
"path": "/var/folders/0b/t9c4hwvx6lg6jk58gw8w_dp80000gn/T/tmp7wxr57wm/src/app.py",
"level": 1,
"summary": "# Application code",
"children": [],
"token_count": 5,
"created_at": "2026-02-02T17:47:19.243833",
"metadata": {
"filename": "app.py",
"relative_path": "src/app.py"
}
},
"/var/folders/0b/t9c4hwvx6lg6jk58gw8w_dp80000gn/T/tmp7wxr57wm/src": {
"path": "/var/folders/0b/t9c4hwvx6lg6jk58gw8w_dp80000gn/T/tmp7wxr57wm/src",
"level": 2,
"summary": "Folder contains 1 files: # Application code",
"children": [
"/var/folders/0b/t9c4hwvx6lg6jk58gw8w_dp80000gn/T/tmp7wxr57wm/src/app.py"
],
"token_count": 11,
"created_at": "2026-02-02T17:47:19.243852",
"metadata": {
"folder_name": "src",
"file_count": 1
}
}
}
}
@@ -0,0 +1,21 @@
{
"root_path": "/var/folders/0b/t9c4hwvx6lg6jk58gw8w_dp80000gn/T/tmp8qwfp4zl",
"total_files": 0,
"total_tokens": 11,
"levels": 3,
"built_at": "2026-02-02T17:49:37.074095",
"nodes": {
"/var/folders/0b/t9c4hwvx6lg6jk58gw8w_dp80000gn/T/tmp8qwfp4zl": {
"path": "/var/folders/0b/t9c4hwvx6lg6jk58gw8w_dp80000gn/T/tmp8qwfp4zl",
"level": 3,
"summary": "Project with 0 folders and 0 root files: ",
"children": [],
"token_count": 11,
"created_at": "2026-02-02T17:49:37.074201",
"metadata": {
"folder_count": 0,
"root_file_count": 0
}
}
}
}
@@ -0,0 +1,33 @@
{
"root_path": "/var/folders/0b/t9c4hwvx6lg6jk58gw8w_dp80000gn/T/tmp9nw2kfoj",
"total_files": 2,
"total_tokens": 14,
"levels": 1,
"built_at": "2026-02-02T17:47:19.242486",
"nodes": {
"/var/folders/0b/t9c4hwvx6lg6jk58gw8w_dp80000gn/T/tmp9nw2kfoj/utils.py": {
"path": "/var/folders/0b/t9c4hwvx6lg6jk58gw8w_dp80000gn/T/tmp9nw2kfoj/utils.py",
"level": 1,
"summary": "def helper(): return True",
"children": [],
"token_count": 7,
"created_at": "2026-02-02T17:47:19.242582",
"metadata": {
"filename": "utils.py",
"relative_path": "utils.py"
}
},
"/var/folders/0b/t9c4hwvx6lg6jk58gw8w_dp80000gn/T/tmp9nw2kfoj/main.py": {
"path": "/var/folders/0b/t9c4hwvx6lg6jk58gw8w_dp80000gn/T/tmp9nw2kfoj/main.py",
"level": 1,
"summary": "def main(): print('Hello')",
"children": [],
"token_count": 7,
"created_at": "2026-02-02T17:47:19.242630",
"metadata": {
"filename": "main.py",
"relative_path": "main.py"
}
}
}
}
@@ -0,0 +1,35 @@
{
"root_path": "/var/folders/0b/t9c4hwvx6lg6jk58gw8w_dp80000gn/T/tmp_dbottar",
"total_files": 1,
"total_tokens": 16,
"levels": 2,
"built_at": "2026-02-02T17:49:37.077857",
"nodes": {
"/var/folders/0b/t9c4hwvx6lg6jk58gw8w_dp80000gn/T/tmp_dbottar/src/app.py": {
"path": "/var/folders/0b/t9c4hwvx6lg6jk58gw8w_dp80000gn/T/tmp_dbottar/src/app.py",
"level": 1,
"summary": "# Application code",
"children": [],
"token_count": 5,
"created_at": "2026-02-02T17:49:37.077985",
"metadata": {
"filename": "app.py",
"relative_path": "src/app.py"
}
},
"/var/folders/0b/t9c4hwvx6lg6jk58gw8w_dp80000gn/T/tmp_dbottar/src": {
"path": "/var/folders/0b/t9c4hwvx6lg6jk58gw8w_dp80000gn/T/tmp_dbottar/src",
"level": 2,
"summary": "Folder contains 1 files: # Application code",
"children": [
"/var/folders/0b/t9c4hwvx6lg6jk58gw8w_dp80000gn/T/tmp_dbottar/src/app.py"
],
"token_count": 11,
"created_at": "2026-02-02T17:49:37.078011",
"metadata": {
"folder_name": "src",
"file_count": 1
}
}
}
}
@@ -0,0 +1,33 @@
{
"root_path": "/var/folders/0b/t9c4hwvx6lg6jk58gw8w_dp80000gn/T/tmpp5k48vv4",
"total_files": 2,
"total_tokens": 14,
"levels": 1,
"built_at": "2026-02-02T17:49:37.075925",
"nodes": {
"/var/folders/0b/t9c4hwvx6lg6jk58gw8w_dp80000gn/T/tmpp5k48vv4/utils.py": {
"path": "/var/folders/0b/t9c4hwvx6lg6jk58gw8w_dp80000gn/T/tmpp5k48vv4/utils.py",
"level": 1,
"summary": "def helper(): return True",
"children": [],
"token_count": 7,
"created_at": "2026-02-02T17:49:37.076036",
"metadata": {
"filename": "utils.py",
"relative_path": "utils.py"
}
},
"/var/folders/0b/t9c4hwvx6lg6jk58gw8w_dp80000gn/T/tmpp5k48vv4/main.py": {
"path": "/var/folders/0b/t9c4hwvx6lg6jk58gw8w_dp80000gn/T/tmpp5k48vv4/main.py",
"level": 1,
"summary": "def main(): print('Hello')",
"children": [],
"token_count": 7,
"created_at": "2026-02-02T17:49:37.076227",
"metadata": {
"filename": "main.py",
"relative_path": "main.py"
}
}
}
}
@@ -0,0 +1,33 @@
{
"root_path": "/var/folders/0b/t9c4hwvx6lg6jk58gw8w_dp80000gn/T/tmpwwb01831",
"total_files": 2,
"total_tokens": 16,
"levels": 1,
"built_at": "2026-02-02T17:49:37.079504",
"nodes": {
"/var/folders/0b/t9c4hwvx6lg6jk58gw8w_dp80000gn/T/tmpwwb01831/javascript.js": {
"path": "/var/folders/0b/t9c4hwvx6lg6jk58gw8w_dp80000gn/T/tmpwwb01831/javascript.js",
"level": 1,
"summary": "JavaScript web development",
"children": [],
"token_count": 7,
"created_at": "2026-02-02T17:49:37.079612",
"metadata": {
"filename": "javascript.js",
"relative_path": "javascript.js"
}
},
"/var/folders/0b/t9c4hwvx6lg6jk58gw8w_dp80000gn/T/tmpwwb01831/python.py": {
"path": "/var/folders/0b/t9c4hwvx6lg6jk58gw8w_dp80000gn/T/tmpwwb01831/python.py",
"level": 1,
"summary": "Python programming language code",
"children": [],
"token_count": 9,
"created_at": "2026-02-02T17:49:37.079658",
"metadata": {
"filename": "python.py",
"relative_path": "python.py"
}
}
}
}
@@ -0,0 +1,33 @@
{
"root_path": "/var/folders/0b/t9c4hwvx6lg6jk58gw8w_dp80000gn/T/tmpwzdvf3_7",
"total_files": 2,
"total_tokens": 16,
"levels": 1,
"built_at": "2026-02-02T17:47:19.245229",
"nodes": {
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"path": "/var/folders/0b/t9c4hwvx6lg6jk58gw8w_dp80000gn/T/tmpwzdvf3_7/javascript.js",
"level": 1,
"summary": "JavaScript web development",
"children": [],
"token_count": 7,
"created_at": "2026-02-02T17:47:19.245344",
"metadata": {
"filename": "javascript.js",
"relative_path": "javascript.js"
}
},
"/var/folders/0b/t9c4hwvx6lg6jk58gw8w_dp80000gn/T/tmpwzdvf3_7/python.py": {
"path": "/var/folders/0b/t9c4hwvx6lg6jk58gw8w_dp80000gn/T/tmpwzdvf3_7/python.py",
"level": 1,
"summary": "Python programming language code",
"children": [],
"token_count": 9,
"created_at": "2026-02-02T17:47:19.245395",
"metadata": {
"filename": "python.py",
"relative_path": "python.py"
}
}
}
}
+1 -22
View File
@@ -2,13 +2,6 @@
> **For AI Agents and Developers**: This document provides the complete context needed to work with the PraisonAI ecosystem, including design principles, architecture, repository structure, and implementation guidelines.
> **Active workstream — local model runtimes.** If your task touches local inference
> (Ollama, LM Studio, llama.cpp, vLLM, MLX, `transformers serve`), provider detection,
> `llm/adapters/`, or the `praisonaiagents/local/` package, read
> [`docs/local-model-layer/README.md`](docs/local-model-layer/README.md) **before editing**.
> It carries the measured ground truth, the invariants, and a file-ownership table that
> prevents concurrent work orders from corrupting each other.
---
## 1. What is PraisonAI?
@@ -214,7 +207,6 @@ and features (capabilities, bots, framework adapters) — use
| 2b | `praisonai-bot` | Bots, gateway, channel CLI, OS daemon |
| 2c | `praisonai-train` | LLM fine-tuning (Unsloth), agent training, `train` CLI |
| 3 | `praisonai` | `framework_adapters/`, capabilities, serve orchestration, dashboard |
| 1-TS | `praisonai-ts` | TypeScript/JavaScript SDK (`npm: praisonai`); canonical path `src/praisonai-ts/` |
**Cross-tier rule:** `praisonai-code` must not declare a PyPI dependency on `praisonai`. Use
[`praisonai_code._wrapper_bridge`](../praisonai-code/praisonai_code/_wrapper_bridge.py) for lazy wrapper access.
@@ -230,17 +222,6 @@ from `praisonai_train.cli.commands.*` (`train`, C10); `_WRAPPER_RESIDENT_COMMAND
Full boundary doc: [`src/praisonai/tests/C7.1_BOUNDARIES.md`](../praisonai/tests/C7.1_BOUNDARIES.md).
### 2.5 TypeScript SDK (`praisonai-ts`)
Python guidelines in this file do **not** replace the TypeScript SDK guide. For any issue, PR, or review touching `src/praisonai-ts/`:
1. Read [`src/praisonai-ts/AGENTS.md`](../praisonai-ts/AGENTS.md) — architecture, parity, triage, and PR review rules.
2. Implement fixes in **`src/praisonai-ts/`** in this monorepo (not in `praisonaiagents/`).
3. Verify with `cd src/praisonai-ts && npm install && npm run build && npm test`.
4. After merge, maintainers sync the npm mirror: `gh workflow run "Sync to praisonai-js" --repo MervinPraison/PraisonAI`.
[MervinPraison/praisonai-js](https://github.com/MervinPraison/praisonai-js) is the public npm checkout; direction is **monorepo → praisonai-js** only. Claude merge gate and `@claude` review TS changes under `src/praisonai-ts/` using the TS AGENTS.md criteria (lightweight, type-safe, Python parity where applicable).
---
## 3. Core SDK Architecture (praisonaiagents)
@@ -514,7 +495,7 @@ agent = Agent(
name="assistant",
llm="gpt-4o-mini",
memory=MemoryConfig(provider="chroma", use_long_term=True),
hooks=HooksConfig(on_tool_call=my_tool_logger, middleware=[my_validator]),
hooks=HooksConfig(before_tool=[my_validator]),
guardrail=my_guardrail
)
```
@@ -895,8 +876,6 @@ from praisonaiagents import Workflow, Route, Parallel, Loop
| CLI backends | `praisonai_code/cli_backends/` |
| Back-compat shims | `praisonai/cli/_shim.py`, `praisonai/cli/main.py` |
| C5 regression tests | `praisonai/tests/unit/test_c5_backward_compat.py` |
| TypeScript SDK | `src/praisonai-ts/` — see `src/praisonai-ts/AGENTS.md` |
| npm mirror (sync only) | [MervinPraison/praisonai-js](https://github.com/MervinPraison/praisonai-js) |
---
+56 -57
View File
@@ -17,79 +17,78 @@ This report compares **Python SDK feature categories** against **Python document
| Category | Features | Docs | Lines |
|----------|----------|------|-------|
| ✅ AGUI | 1 | 2 | 511 |
| ✅ Agent | 22 | 59 | 19076 |
| ✅ AGUI | 1 | 2 | 420 |
| ✅ Agent | 22 | 53 | 17053 |
| ✅ Agent-to-Agent (A2A) | 1 | 7 | 2996 |
| ✅ Agent-to-User (A2U) | 1 | 3 | 701 |
| ✅ Approval | 1 | 8 | 3969 |
| ✅ Agent-to-User (A2U) | 1 | 3 | 689 |
| ✅ Approval | 1 | 5 | 2658 |
| ✅ Audio | 2 | 12 | 1000 |
| ✅ Auto Generation | 5 | 12 | 3941 |
| ✅ Autonomy | 3 | 7 | 2805 |
| ✅ Bots | 7 | 38 | 15809 |
| ✅ Auto Generation | 5 | 11 | 3542 |
| ✅ Autonomy | 3 | 7 | 2790 |
| ✅ Bots | 7 | 31 | 13411 |
| ✅ Budget | 1 | 1 | 287 |
| ✅ CLI | 5 | 124 | 39191 |
| ✅ Chunking | 2 | 2 | 435 |
| ✅ CLI | 5 | 122 | 36734 |
| ✅ Chunking | 2 | 2 | 420 |
| ✅ Citations | 2 | 1 | 202 |
| ✅ Code Execution | 2 | 14 | 5022 |
| ✅ Conditions | 1 | 3 | 1386 |
| ✅ Configuration | 3 | 8 | 3341 |
| ✅ Context Management | 16 | 36 | 14384 |
| ✅ Deep Research | 8 | 2 | 591 |
| ✅ Display | 6 | 3 | 844 |
| ✅ Embeddings | 6 | 23 | 2051 |
| ✅ Evaluation | 1 | 9 | 3637 |
| ✅ Events | 1 | 2 | 782 |
| ✅ Execution | 3 | 4 | 1694 |
| ✅ Failover | 2 | 1 | 537 |
| ✅ Files | 2 | 7 | 2376 |
| ✅ Flow | 1 | 3 | 811 |
| ✅ Gateway | 7 | 97 | 37597 |
| ✅ Guardrails | 5 | 4 | 2642 |
| ✅ Handoffs | 11 | 6 | 2748 |
| ✅ Hooks | 2 | 9 | 5230 |
| ✅ Image | 1 | 11 | 1295 |
| ✅ Knowledge | 4 | 20 | 6260 |
| ✅ LLM | 3 | 15 | 5958 |
| ✅ Loops | 4 | 5 | 1478 |
| ✅ MCP | 1 | 64 | 15116 |
| ✅ Memory | 6 | 21 | 8198 |
| ✅ Code Execution | 2 | 14 | 4855 |
| ✅ Conditions | 1 | 3 | 1347 |
| ✅ Configuration | 3 | 8 | 3139 |
| ✅ Context Management | 16 | 36 | 13988 |
| ✅ Deep Research | 8 | 2 | 587 |
| ✅ Display | 6 | 3 | 741 |
| ✅ Embeddings | 6 | 23 | 2049 |
| ✅ Evaluation | 1 | 7 | 2920 |
| ✅ Events | 1 | 2 | 749 |
| ✅ Execution | 3 | 4 | 1606 |
| ✅ Failover | 2 | 1 | 452 |
| ✅ Files | 2 | 7 | 2275 |
| ✅ Flow | 1 | 3 | 788 |
| ✅ Gateway | 7 | 80 | 29490 |
| ✅ Guardrails | 4 | 4 | 2205 |
| ✅ Handoffs | 11 | 6 | 2626 |
| ✅ Hooks | 2 | 9 | 4488 |
| ✅ Image | 1 | 11 | 1255 |
| ✅ Knowledge | 4 | 16 | 4942 |
| ✅ LLM | 3 | 15 | 5372 |
| ✅ Loops | 4 | 5 | 1475 |
| ✅ MCP | 1 | 61 | 14135 |
| ✅ Memory | 6 | 18 | 7187 |
| ✅ OCR | 2 | 1 | 237 |
| ✅ Observability | 2 | 23 | 2859 |
| ✅ Observability | 2 | 23 | 2811 |
| ✅ Optimizer | 1 | 2 | 792 |
| ✅ Output | 3 | 5 | 1289 |
| ✅ Parallel Execution | 3 | 2 | 528 |
| ✅ Planning | 6 | 7 | 1827 |
| ✅ Plugins | 8 | 5 | 4108 |
| ✅ Prompts | 2 | 9 | 2043 |
| ✅ Providers | 1 | 58 | 8751 |
| ✅ Output | 3 | 5 | 1265 |
| ✅ Parallel Execution | 3 | 2 | 497 |
| ✅ Planning | 6 | 6 | 1605 |
| ✅ Plugins | 8 | 5 | 3120 |
| ✅ Prompts | 2 | 9 | 1971 |
| ✅ Providers | 1 | 56 | 7781 |
| ✅ Query | 1 | 2 | 736 |
| ✅ RAG | 5 | 15 | 3152 |
| ✅ RAG | 5 | 15 | 3118 |
| ✅ Realtime | 2 | 5 | 668 |
| ✅ Reflection | 3 | 3 | 732 |
| ✅ Retrieval | 2 | 5 | 1046 |
| ✅ Reflection | 3 | 3 | 730 |
| ✅ Retrieval | 2 | 5 | 1054 |
| ✅ Routing | 1 | 2 | 430 |
| ✅ Sandbox | 5 | 7 | 3720 |
| ✅ Security | 1 | 3 | 3642 |
| ✅ Sessions | 4 | 21 | 8388 |
| ✅ Skills | 6 | 16 | 6045 |
| ✅ Tasks | 2 | 8 | 3266 |
| ✅ Telemetry | 1 | 2 | 660 |
| ✅ Templates | 1 | 9 | 1859 |
| ✅ Tools | 12 | 147 | 45378 |
| ✅ Sandbox | 5 | 7 | 3483 |
| ✅ Security | 1 | 3 | 3482 |
| ✅ Sessions | 4 | 19 | 7576 |
| ✅ Skills | 6 | 15 | 5638 |
| ✅ Tasks | 2 | 6 | 2897 |
| ✅ Telemetry | 1 | 2 | 648 |
| ✅ Templates | 1 | 8 | 1663 |
| ✅ Tools | 12 | 144 | 43102 |
| ✅ Tracing | 3 | 2 | 139 |
| ✅ Vector Store | 1 | 12 | 1219 |
| ✅ Video | 2 | 10 | 1303 |
| ✅ Vector Store | 1 | 12 | 1215 |
| ✅ Video | 2 | 6 | 649 |
| ✅ Vision | 2 | 1 | 329 |
| ✅ Web | 3 | 10 | 2822 |
| ✅ Workflows | 5 | 21 | 8880 |
| ✅ Web | 3 | 9 | 2487 |
| ✅ Workflows | 5 | 18 | 7406 |
## Documentation Without Features
These docs exist but don't match any implemented feature category:
- ℹ️ Database (44 docs, 8206 lines)
- ℹ️ Documents (1 docs, 810 lines)
- ℹ️ Teams (1 docs, 214 lines)
- ℹ️ Database (42 docs, 6959 lines)
- ℹ️ Documents (1 docs, 787 lines)
---
-17
View File
@@ -1,17 +0,0 @@
"""Root conftest: environment that must be set before third-party imports.
pytest loads plugins registered through entry points before it loads
``tests/conftest.py``, and something in that chain imports litellm. litellm
reads LITELLM_LOCAL_MODEL_COST_MAP at *its* import and, without it, fetches
model_prices_and_context_window.json from raw.githubusercontent.com -- so the
suite made an outbound request before a single test ran, and stalled or failed
when offline. A rootdir conftest is loaded early enough to win that race.
Anything that merely needs to be set before the tests themselves belongs in
tests/conftest.py instead.
"""
import os
os.environ.setdefault("LITELLM_LOCAL_MODEL_COST_MAP", "True")
os.environ.setdefault("HF_HUB_OFFLINE", "1")
@@ -1,331 +0,0 @@
# Ground truth
Every claim here was measured, not estimated. Each carries **how** it was obtained so it can
be re-checked cheaply. Measured 2026-09-03 against `origin/main` at `2591aa405`, with a live
Ollama 0.33.2 (`b79067b0`) on `127.0.0.1:11434`.
If a work order contradicts something here, re-measure before acting. Numbers drift.
> **Capabilities are per-model, not per-server.** An early draft of this file attributed the
> 9B model's capability list to `qwen3:0.6b`. Re-verified 2026-09-03: `qwen3:0.6b` is
> `["completion","tools","thinking"]` — **no vision**. Always name the model when quoting a
> capability set.
---
## 1. Runtime facts, verified live
| Fact | Value | How to re-verify |
|---|---|---|
| Ollama liveness probe | `GET /` returns `200` with body `Ollama is running` | `curl -sI 127.0.0.1:11434/` |
| Ollama version probe | `{"version":"0.33.2"}` | `curl -s 127.0.0.1:11434/api/version` |
| Capability probe works | `qwen3:0.6b` → `["completion","tools","thinking"]` (the 9B tamil model, separately, → `[...,"vision"]`) | `curl -s :11434/api/show -d '{"model":"qwen3:0.6b"}' \| jq .capabilities` |
| Unknown `options` keys are silently dropped | `{"totally_bogus_key":123}` → HTTP 200, no warning | send it to `/api/chat`; response is a normal completion |
| Tool-param schema keywords are stripped | `minLength`, `format`, `default`, `additionalProperties` all absent from the rendered prompt | `/api/chat` with `_debug_render_only: true` and those keys set |
| `parameters.type` must be a bare string | `"type": ["object","null"]` → **HTTP 400** `cannot unmarshal array into Go struct field ToolFunctionParameters...type of type string` | send that tool definition to `/api/chat` |
| **`format` + `tools` are mutually destructive** | Tool call silently suppressed; model fabricates. Same request without `format` calls the tool correctly. | see §2 below |
### Installed on this machine
`ollama` (0.33.2), `llama-server` (b7620, Homebrew), `mlx_lm.server`, `hf` CLI.
**Not** installed: `lms` (LM Studio), `vllm`.
Ports open at time of measurement: `11434` only.
---
## 2. The reproduction that matters most
`format` (JSON schema) plus `tools`, sent to Ollama, produces a **confident fabrication** with
an HTTP 200 and no warning. The JSON grammar makes the tool-call tag unemittable, so the
model cannot call the tool and answers from nothing instead.
```
POST /api/chat model=qwen3:0.6b think=false
prompt: "What is the weather in Paris? Use the tool."
tools: [get_weather(city: string)]
WITH format + tools -> HTTP 200
message.tool_calls : null
message.content : {"answer": "The weather in Paris is sunny with a temperature of 15C."}
TOOLS ONLY (format removed) -> HTTP 200
message.tool_calls : [{"function": {"name": "get_weather",
"arguments": {"city": "Paris"}}}]
message.content : ""
```
Consequence for design: this combination must **raise**, not be silently repaired. A
fabricated answer that looks correct is worse than an error.
---
## 3. Codebase measurements
All obtained by script over `praisonaiagents/` at `2591aa405`.
### Scale
| Metric | Value |
|---|---|
| Python files / lines | 595 / 238,936 |
| Files over 2,000 lines | 13 |
| `agent/agent.py` | 7,701 |
| `llm/llm.py` | 7,160 |
| `agent/chat_mixin.py` | 6,151 |
| `llm/openai_client.py` | 2,691 |
| `llm/adapters/__init__.py` | 340 |
### `LLM` class cohesion
95 methods, 6,779 lines. Three largest methods total 3,087 lines — 43% of the file.
| Lines | Location | Method | Branch/loop/try nodes |
|---|---|---|---|
| 1,675 | `llm.py:2557` | `get_response` | **194** |
| 969 | `llm.py:4706` | `get_response_async` | 115 |
| 443 | `llm.py:4233` | `get_response_stream` | 56 |
| 249 | `llm.py:5966` | `_build_completion_params` | 52 |
| 199 | `llm.py:413` | `__init__` | 10 |
### Adapter call sites — the A1 finding
`DefaultAdapter` declares **17 methods** (an earlier draft said 18; the 18th item,
`add_provider_adapter`, is a module-level function). Eleven methods have **zero** call sites
anywhere, and with the three module functions that is 12 dead items. Note also that
`LLMProviderAdapterProtocol` declares only **16** — it omits `get_streaming_adapter`, so that
method is not part of the protocol it claims to implement.
```
supports_streaming 2
format_tool_result_message 1 (llm.py:1712)
get_default_settings 1 (llm.py:690)
should_summarize_tools 1
supports_prompt_caching 1
supports_streaming_with_tools 1
--- zero call sites ---
recover_tool_calls_from_text 0 (inline copy at llm.py:3468-3500)
parse_tool_calls 0
handle_empty_response_with_tools 0
post_tool_iteration 0
format_tools 0
get_streaming_adapter 0
get_max_iteration_threshold 0
should_skip_streaming_with_tools 0
supports_structured_output 0
inject_cache_control 0
extract_reasoning_tokens 0
add_provider_adapter 0 (public registration hook)
```
Ollama references (case-insensitive): `llm/llm.py` **145**, `llm/adapters/__init__.py` 19,
`llm/streaming_protocol.py` 11, `tools/call_executor.py` 6.
### Compensation coverage across the three response paths — the A2 finding
```
get_response _async _stream
1675 L 969 L 443 L
tool_result_mapping (value fix-up) 8 0 0
max_tool_repairs (repair loop) 2 0 0
force_tool_usage (prompt inject) 1 0 0
_validate_and_filter_ollama_arguments 1 1 0
_generate_ollama_tool_summary 1 1 0
_handle_ollama_sequential_logic 1 1 0
_format_ollama_tool_result_message 1 1 1* (indirect)
```
`get_response_stream` has none of the seven — except `_format_ollama_tool_result_message`,
which it reaches indirectly via `_create_tool_message` (`llm.py:6791`), so that row overstated
the gap. A fuller re-measurement found **16** divergent compensations, not 7; three of them run
*against* the sync path. The full matrix is in `06-adapter-revival.md` §2.6. `difflib` similarity of `get_response` against
`get_response_async` is **22.3%**, while the file's other four sync/async pairs are 76–91% —
so those two have diverged, not merely duplicated.
### Import graph — the I6 constraint
65 subpackages, 212 directed edges, **26 mutually-importing pairs**. Heaviest:
```
agent <-> tools 53 + 1 llm/ imports: tools 10, streaming 7,
agent <-> approval 28 + 1 agent 4, telemetry 2,
agent <-> config 25 + 1 auth 2, compaction 2,
agent <-> llm 19 + 4 context 1, thinking 1
llm <-> tools 10 + 1
context <-> llm 2 + 1 15 subpackages import llm/
```
### Reachability — the A3 finding
21 modules call a provider SDK directly, bypassing both clients: 23 `litellm.completion/acompletion`,
7 `litellm.embedding/aembedding`, 16 `chat.completions.create`, 3 bare `OpenAI()`.
These nine contain **zero** occurrences of `api_base` or `base_url`, so there is no parameter
to set — "run everything locally" is currently unachievable, not merely unconfigured:
```
memory/memory.py workflows/workflows.py eval/judge.py
eval/grader.py eval/accuracy.py context/compressor.py
context/optimizer.py lite/__init__.py telemetry/performance_monitor.py
```
Worst single case, `memory/memory.py:2186-2192`:
```python
from openai import OpenAI
client = OpenAI() # no base_url, no api_key
response = client.chat.completions.create(
model=llm or "gpt-4o-mini", ...
```
Hardcoded defaults in code (excluding docstrings): **105** `"gpt-4o-mini"`, **17**
`"text-embedding-3-small"`. Sixteen of the 105 are the identical line
`self.llm if hasattr(self,'llm') else "gpt-4o-mini"` in `agent/context_agent.py`.
### Stringly-typed provider identity — the A6 finding
**77 occurrences of 23 distinct string predicates** across `src/`. The same provider is
tested inconsistently, which is precisely how D3 and D4 arose:
```
9 startswith("anthropic/") gemini tested 3 ways: gpt tested 4 ways:
8 startswith("ollama/") startswith("gemini") startswith('gpt-')
7 "ollama" in startswith("gemini/") startswith("gpt-")
6 startswith("gemini") startswith('gemini-') startswith("gpt")
5 startswith("openai/") "gpt" in
5 startswith("claude")
3 ":11434" in
```
### Accretion history — why boundaries matter here
| File | First | Now | Commits | Ever shrank |
|---|---|---|---|---|
| `llm/llm.py` | 1,212 (Jan 2025) | 7,160 | 251 | never, in 18 sampled months |
| `agent/agent.py` | 1,251 (Jan 2025) | 7,701 | 472 | once — the split below |
| `agent/chat_mixin.py` | created Apr 2026 | 6,151 | 150 | — |
On **2026-04-01** `agent.py` was split 8,915 → 5,030 by extracting `chat_mixin.py`. Five
months later the two halves total **13,852 lines — 55% above the pre-split file**, growing
~33 lines/day. Moving code did not create a boundary. This is the argument for I6 being a
*test* rather than a convention.
---
## 4. Dependency facts
| Package | Version present | Status |
|---|---|---|
| `httpx` | 0.28.1 | **hard transitive dep** of required `openai>=2.0.0` (`httpx<1,>=0.23.0`) |
| `aiohttp` | 3.14.1 | direct required core dep |
| `openai` | 2.44.0 | direct required core dep |
| `litellm` | 1.90.2 | optional (`llm`, `memory` extras) |
`pyproject.toml` declares **17 optional extras** — `a2ui, api, all, auth, autonomy, crawl,
dakera, graph, knowledge, llm, mcp, memory, mongodb, os, sandbox, search, telemetry` — and
**none of them is local**. `import praisonaiagents` measures 0.04 s, so imports are lazy and
cheap; discovery latency is the only startup cost to manage.
**Conclusion (superseded).** This section originally concluded `local/` should use `httpx`.
That was reversed by the normative decision in `07-local-package-spec.md` §3: `httpx` is present
only as an **undeclared transitive** edge (`openai -> httpx`), so building the dependency sink on
it means a future `openai` release dropping `httpx` would silently break `local/`. The client is
therefore stdlib `urllib.request`, and the boundary test forbids `httpx`/`requests`/`aiohttp`.
The measurement above stands; only the recommendation drawn from it was wrong.
---
## 5. litellm prefix resolution vs ours
litellm 1.90.2 resolves all of these; PraisonAI's `_detect_provider` recognises only `ollama/`:
```
ollama/llama3.2 -> ollama OllamaAdapter repairs=2
ollama_chat/llama3.2 -> openai DefaultAdapter repairs=0 <- litellm's RECOMMENDED prefix
lm_studio/qwen -> openai DefaultAdapter repairs=0
vllm/x -> openai DefaultAdapter repairs=0
hosted_vllm/x -> openai DefaultAdapter repairs=0
huggingface/x -> openai DefaultAdapter repairs=0
```
---
## 6. Known-bad environment note
`mervinpraison/praisonai-qwen3.5-9b-tamil-en2ta:latest` does **not load** on Ollama 0.33.2:
`Failed to load CLIP model from ...sha256-11540ddc21b3...`, HTTP 500. The vision projector
blob is the failing piece. Use `qwen3:0.6b` for local verification instead. Unrelated to this
work, but it will waste an agent's time if not known.
---
## 7. The three response paths disagree — measured, not inferred
Live Ollama, `temperature=0`, identical prompt and tool, two trials, reproducible
(script in `06-adapter-revival.md` §2.7):
```
sync calls=2 'Paris: 21C sunny. Paris: 21C sunny.'
async calls=1 'Paris: 21C sunny'
stream calls=10 ''
```
> **Corrected 2026-09-03.** An earlier draft recorded the sync path returning
> `'{\n\n\n}'` with one tool call. That did not reproduce; the figures above did,
> across two trials. The finding is unchanged — the paths disagree and the stream
> path is broken — but the `'{\n\n\n}'` sample should not be cited.
Three facts follow, and they reframe the work:
1. **The best-compensated path produces the worst answer.** `get_response` carries 16 of the 18
compensations and calls the tool twice, returning a doubled answer;
`get_response_async` carries 8 and returns the correct answer once. More compensation is
not the goal — *the same* compensation is.
2. **The stream path is not under-compensated, it is broken.** It burns all 10 iterations of
`max_iter`, invokes the tool **ten times** for a one-tool question, and yields nothing. That
is a cost and side-effect amplifier, not a formatting defect.
3. Leading hypothesis for the sync/async split: `OLLAMA_FINAL_ANSWER_PROMPT` (`llm.py:5302`,
async only). **Still a hypothesis, not a measurement** — it was not settled during order 06,
because the corrected baseline changed what needs explaining.
## 8. Two test-infrastructure traps
- **`src/praisonai-agents/tests/` is almost entirely outside CI.** The only tests any workflow
runs from it are `tests/smoke/test_subscription_auth.py` and
`tests/unit/auth/test_agent_auth_wiring.py`. `tests/unit/test_adapter_registry.py` (38 tests)
and all 13 files in `tests/unit/llm/` run **nowhere**. Put new tests in
`src/praisonai/tests/unit/llm/`, which is run.
- **`test_ollama_tool_reliability.py` tests a copy, not the product.** Its `MockLLM`
re-implements `_is_ollama_provider`, `_apply_ollama_defaults`, `_validate_tool_call`,
`_should_force_tool_usage` and both prompt templates. It cannot fail in response to any change
in `llm.py`. Do not treat it as a safety net.
## 9. Test-gating facts (order 04)
- **`not network`, not `provider_ollama`, is what deselects the mocked base_url suite.** The gating
plugin implies `network` from *any* provider marker (`test_gating.py:235-238`) and every CI
expression contains `not network`. Editing the workflows' `-m` strings accomplishes nothing.
- `tests/unit/**` is **exempt** from provider auto-detection (`test_gating.py:215`,
`test_type != 'unit'`). That is why `tests/unit/llm/test_ollama_tool_reliability.py` runs in CI
while the integration file does not — and why live tests placed under `tests/unit/` need an
**explicit** marker.
- `-m provider_ollama` currently selects **32 tests across 5 files**; only 7 are Ollama tests.
- **4 of the 7 tests in `test_base_url_api_base_fix.py` fail when actually executed** —
`LLMResponseError: 'str' object has no attribute 'choices'`. The mock returns a dict; the
tool-calling loop needs an object with `.choices`.
- **`tests/test_double_api_fix.py` makes a real network call when forced to run.** `llm.py` routes
`gpt-4o-mini` through `litellm.responses` (`llm.py:6434`), not `litellm.completion`, so its patch
no longer intercepts (verified: 401 from `api.openai.com/v1/responses`). It is currently masked
by an unconditional auto-skip — **anyone who "fixes" the skip without fixing the mock gets live
billed calls.**
- **`network_guard.py` disables itself** for anything under `/integration/`, `/e2e/`, `/live/`
(lines 103-105) and for any `provider_*`-marked test (96-100). The suite's network blocker does
not cover the tests most likely to make network calls.
- **A live Ollama suite already exists** and has never run:
`tests/integration/test_ollama_tool_calling_live.py`, 230 lines, 7 tests, gated on
`PRAISONAI_TEST_OLLAMA`. It is broken against `main` — all 7 pass `verbose=True` to `Agent()`,
and two pass `force_tool_usage=` / `max_tool_repairs=`; all three now raise `TypeError`.
- **`qwen3:0.6b` is 522 MB** (not ~400 MB) and reports `completion, tools, thinking` — **no
vision**. Reliability through `Agent`: default 3/4; `force_tool_usage="always"` + `temperature=0`
**6/6**; multi-step arithmetic 0/2 (one hung past 90 s).
@@ -1,372 +0,0 @@
# 04 — D7: provider markers are assigned per file, so mocked tests are gated as if live
**Branch:** `fix/gating-per-test-provider-markers`
**Measured:** clean worktree at `origin/main` (`2591aa405`), working tree clean.
**Owns:** `src/praisonai/tests/_pytest_plugins/test_gating.py`, both `pytest.ini` files,
`src/praisonai/tests/conftest.py`, `tests/integration/test_base_url_api_base_fix.py`,
`tests/unit/cli/test_test_command.py`.
**Must not edit:** any `praisonaiagents/` source; `.github/workflows/**` (order 05).
> **The audit's stated root cause was wrong, and the correction changes the fix.**
> `provider_ollama` is a red herring. **`not network` deselects all 7 tests on its own**, because
> the plugin implies `network` from *any* provider marker and the file also matches
> `provider_openai`. **Removing `not provider_ollama` from the workflows would change nothing.**
> The fix must be marker-side, not workflow-side. This is why order 04 touches no YAML.
---
## 1. Corrections to the audit
| # | Claim | Verdict |
|---|---|---|
| 1 | 4 CI marker expressions carry `not provider_ollama` | **True but incomplete** — there is a 5th, non-CI location: `src/praisonai-code/praisonai_code/cli/commands/test.py:67` (`praisonai test --tier main`). |
| 2 | 7 tests, all deselected | **Exactly true** (`collected 7 items / 7 deselected / 0 selected`). **Stated cause is wrong** — see the callout above. |
| 3 | The file never inspects `litellm.completion` kwargs | **True** (only `mock_completion.assert_called()`). **And worse: 4 of the 7 tests fail outright when executed.** They are not merely toothless, they are broken. |
| 4 | `test_double_api_fix.py`: 0 asserts, 34 prints | **True. And worse:** all 3 tests are auto-`skip`ped in every configuration, and when forced to run its `patch('litellm.completion')` no longer intercepts — `llm.py` routes `gpt-4o-mini` through `litellm.responses`, so it makes a **real network call** (verified: 401 from `api.openai.com/v1/responses`). |
| 5 | `test_ollama_tool_reliability.py` asserts against MockLLM | **True.** 541 lines, MockLLM at 23–197, 28 tests, all pass. **Quantified:** 2 of the 8 re-implemented methods (`_apply_ollama_defaults`, `_try_parse_tool_call_json`) **do not exist on the real `LLM` at all.** |
| 6 | agents-side ollama tests gated only by `OLLAMA_HOST` | **True**, and `test_ollama_fix_openai` is gated only by `OPENAI_API_KEY` — a live **billed** call on a plain `pytest`. Mitigating: no CI workflow runs these two files. |
| 7 | No ollama live job | **True for CI**, but the audit **missed that the suite already exists**: `tests/integration/test_ollama_tool_calling_live.py`, 230 lines, 7 tests, gated on `PRAISONAI_TEST_OLLAMA=1`. It is **broken against current `main`**. See order 05. |
---
## 2. Reproduce before the fix
```bash
cd src/praisonai && export PYTHONPATH=$(cd ../praisonai-agents && pwd)
CI_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"
```
**R1 — 100% deselected:**
```bash
python -m pytest tests/integration/test_base_url_api_base_fix.py -m "$CI_M" --collect-only -q --disable-warnings
# collected 7 items / 7 deselected / 0 selected
```
**R2 — `provider_ollama` is a red herring.** Rerun R1 with `and not provider_ollama` **removed**:
still `7 deselected / 0 selected`. `not network` does it alone.
**R3 — the whole file is tagged.** With a marker-dump plugin, all seven items carry the identical
set `['integration', 'network', 'provider_ollama', 'provider_openai', 'skip']` — including the six
that never mention Ollama.
**R4 — 4 of 7 fail when actually executed:**
```bash
PRAISONAI_ALLOW_NETWORK=1 PRAISONAI_TEST_PROVIDERS=all OPENAI_API_KEY=sk-fake-offline \
python -m pytest tests/integration/test_base_url_api_base_fix.py -o addopts="" -q --tb=no -rA
# 4 failed, 3 passed
```
All four fail with `LLMResponseError: ... 'str' object has no attribute 'choices'`. The three that
pass are the three that never call `get_response()`.
**R5 — `-m provider_ollama` selects 4× more than it should:**
```
7 tests/integration/test_base_url_api_base_fix.py
7 tests/integration/test_ollama_tool_calling_live.py
11 tests/integration/test_rag_integration.py
4 tests/integration/test_setup_integration.py
3 tests/test_double_api_fix.py
```
**32 selected; only 7 are Ollama tests.** This is why order 04 is a hard prerequisite for order 05 —
`-m provider_ollama` is currently not a usable selector.
---
## 3. Root cause
`test_gating.py:153-166` scans the **entire file**:
```python
153 def _detect_providers_in_file(filepath: Path) -> Set[str]:
154 """Detect which providers are referenced in a test file."""
...
161 content = _get_file_content(filepath)
162 detected = set()
163 for marker, pattern in PROVIDER_PATTERNS.items():
164 if pattern.search(content):
165 detected.add(marker)
166 return detected
```
Line 28 is `'provider_ollama': re.compile(r'\b(ollama)\b', re.IGNORECASE)`. One occurrence inside
`test_ollama_environment_variable_compatibility` tags all seven items (applied at lines 213–230).
Note line 215: `if item.fspath and test_type != 'unit'` — **`tests/unit/**` is exempt**, which is
why `tests/unit/llm/test_ollama_tool_reliability.py` runs in CI while the integration file does not.
**The second mechanism, which the audit missed**, is lines 235–238:
```python
235 # 3. Add network marker if any provider marker is present
236 provider_markers = {m for m in existing_markers if m.startswith('provider_')}
237 if provider_markers and 'network' not in existing_markers:
238 item.add_marker(pytest.mark.network)
```
A mocked test that merely *mentions* `openai` gets `network`, and every CI expression contains
`not network`. Lines 262–267 then convert it into a runtime skip.
**Sub-defect 3.** Lines 59, 145, 177, 234 are all bare `mock_completion.assert_called()`. Nothing
reads `call_args`. Measured: `LLM(model='openai/mistral', base_url='http://localhost:4000',
api_key='sk-test').get_response("test", stream=False)` calls `litellm.completion` with
`base_url='http://localhost:4000'` and `api_base=None`. **So the file's title is stale** — the real
invariant is *`base_url` survives into the call*, not "maps to `api_base`".
---
## 4. The change
**Design decision: AST per-test marking, not file splitting.**
- *Split the file* — cost cheap, **benefit zero** (measured, R2): the six non-Ollama tests still
match `provider_openai`, still get `network`, still get deselected. It also leaves `-m
provider_ollama` selecting 32 tests and fixes nothing for the other 14 mixed-provider files.
**Rejected.**
- *AST per-test marking* — one change in one plugin, fixes the class of problem, and is the
prerequisite for order 05's selector to mean anything. **Recommended.**
### Sub-change 1 — per-test provider detection via AST
Keep `_detect_providers_in_file` (it now serves only the `network` marker) and add:
```python
def _detect_providers_in_text(text: str) -> Set[str]:
"""Return every provider marker whose pattern appears in ``text``."""
detected = set()
for marker, pattern in PROVIDER_PATTERNS.items():
if pattern.search(text):
detected.add(marker)
return detected
def _build_per_test_provider_map(filepath: Path) -> Optional[Dict[tuple, Set[str]]]:
"""Map ``(class_name, func_name)`` -> provider markers for one test file.
The text considered for a test is that test's own source segment plus its
decorators -- not the whole file. Returns ``None`` if the file cannot be
parsed, so callers fall back to whole-file rather than under-marking.
"""
key = str(filepath)
if key in _file_provider_cache:
return _file_provider_cache[key]
result: Optional[Dict[tuple, Set[str]]] = None
try:
source = _get_file_content(filepath)
tree = ast.parse(source)
result = {}
def _visit(node, class_name=None):
for child in getattr(node, 'body', ()):
if isinstance(child, ast.ClassDef):
_visit(child, child.name)
elif isinstance(child, (ast.FunctionDef, ast.AsyncFunctionDef)):
segment = ast.get_source_segment(source, child) or ""
for decorator in child.decorator_list:
segment += "\n" + (ast.get_source_segment(source, decorator) or "")
result[(class_name, child.name)] = _detect_providers_in_text(segment)
_visit(tree)
except (SyntaxError, ValueError, RecursionError):
result = None
_file_provider_cache[key] = result
return result
def _detect_providers_for_item(item) -> Set[str]:
"""Provider markers for a single collected item (per test, not per file)."""
filepath = Path(item.fspath)
if _is_excluded_path(str(filepath)):
return set()
per_test = _build_per_test_provider_map(filepath)
if per_test is None:
return _detect_providers_in_file(filepath)
parts = item.nodeid.split("::")[1:]
if not parts:
return _detect_providers_in_file(filepath)
func = parts[-1].split("[")[0]
cls = parts[-2] if len(parts) >= 2 else None
if (cls, func) in per_test:
return set(per_test[(cls, func)])
if (None, func) in per_test:
return set(per_test[(None, func)])
# Dynamically generated item we cannot locate in the AST: stay conservative.
return _detect_providers_in_file(filepath)
```
Add `import ast`, a `_file_provider_cache: Dict[str, Optional[Dict[tuple, Set[str]]]] = {}` next to
`_file_content_cache` (line 46), and clear it in `pytest_configure` (186) and
`pytest_sessionfinish` (294).
### Sub-change 2 — `offline` opt-out, and pin `network` to the file
Replace lines 213–230 with a version that (a) honours an explicit `offline` marker, (b) calls
`_detect_providers_for_item`, and (c) **keeps `network` whole-file derived**:
```python
offline = 'offline' in existing_markers
if not offline:
detected_providers = _detect_providers_for_item(item)
for marker, pattern in PROVIDER_PATTERNS.items():
if pattern.search(item.nodeid):
detected_providers.add(marker)
for provider in detected_providers:
if provider not in existing_markers:
item.add_marker(getattr(pytest.mark, provider))
# The `network` marker stays WHOLE-FILE derived. Narrowing
# the provider markers must not, by itself, un-deselect a
# test that is really live -- only `offline` does that.
if _detect_providers_in_file(filepath) and 'network' not in existing_markers:
item.add_marker(pytest.mark.network)
```
**Why `network` stays file-derived — this is the whole backward-compatibility story and is not
optional.** Measured: if per-test narrowing were also allowed to narrow `network`, **48 currently-
deselected integration tests would newly select, 25 of them with no `skipif` — they would actually
execute**, across nine files including `test_rag_live.py` and `test_model_routing_real.py`, in a
suite where the network guard is disabled for everything under `/integration/`
(`network_guard.py:103-105`). Pinning `network` to the file makes sub-change 1 provably
**selection-neutral** under every existing `-m` expression, while still making `-m provider_ollama`
mean what it says.
Register the marker in both `pytest.ini` files and `tests/conftest.py`:
```
offline: Fully mocked - opt out of provider/network auto-marking
```
### Sub-change 3 — opt the file in, and make it guard its bug
Add `pytestmark = pytest.mark.offline` plus a response factory:
```python
def make_completion_response(text="Test response"):
"""A litellm.completion stand-in the LLM tool-calling loop can consume.
A bare dict is NOT sufficient: the loop reads ``.choices[0].message`` and a
dict raises ``'str' object has no attribute 'choices'``.
"""
resp = MagicMock()
resp.choices = [MagicMock()]
resp.choices[0].message.content = text
resp.choices[0].message.tool_calls = None
resp.choices[0].finish_reason = "stop"
return resp
```
For each of the four broken tests: replace the dict `return_value` with
`make_completion_response(...)`, pass `stream=False` to `get_response`, and replace
`mock_completion.assert_called()` with a real kwarg assertion:
```python
kwargs = mock_completion.call_args.kwargs
assert kwargs['base_url'] == 'http://localhost:4000'
assert kwargs['api_key'] == 'sk-test'
assert kwargs['model'] == 'openai/mistral'
```
- `test_koboldcpp_specific_scenario` → `kwargs['base_url'] == "http://127.0.0.1:5001/v1"`
- `test_litellm_documentation_example_compatibility` → `kwargs['base_url'] == "http://0.0.0.0:4000"`
- `test_ollama_environment_variable_compatibility` → `kwargs['model'] == 'ollama/llama2'` **and**
`'base_url' not in kwargs` (none was configured; the env path must not inject one)
All four were run standalone against `main` and pass. Leave the three currently-passing tests alone.
Update the stale module docstring ("maps base_url to api_base" → "base_url must reach litellm") but
**do not rename the test functions** — the nodeids are referenced in issue discussion, and renaming
would change what the nodeid scan at plugin lines 224–226 sees.
---
## 5. Backward-compatibility contract
Baseline, measured (`tests/integration/`, CI ignores applied): **290 collected, 187 selected,
103 deselected** under the CI marker expression.
> Caveat for the executing agent: a cold first invocation on a fresh interpreter has been observed
> to report `157/260`, apparently an optional-dependency import warming effect. **Run it twice**;
> `187/290/103` is stable from the second run on. Take your own baseline before touching anything.
**Tests whose selection status changes: exactly 7**, all in `test_base_url_api_base_fix.py`, all
deselected → selected. Post-fix expectation: **194/290 (96 deselected)**. Nothing else moves in
either direction — that is what the file-derived `network` guarantees.
Intended change under `-m provider_ollama` (32 → 9):
| file | before | after |
|---|---|---|
| `test_ollama_tool_calling_live.py` | 7 | 7 |
| `test_base_url_api_base_fix.py` | 7 | 0 (`offline`) |
| `test_rag_integration.py` | 11 | 1 |
| `test_setup_integration.py` | 4 | 0 |
| `test_double_api_fix.py` | 3 | 1 |
**The risk, stated plainly.** Un-deselecting tests turns CI red if any fail. **They do: 4 of the 7
fail today** (R4). This is not hypothetical.
**Mitigation — mandatory, not optional: land the gating fix and the four repairs in the same PR.**
Do not merge sub-changes 1+2 with the `pytestmark` but without the repairs. **Quarantining with
`xfail` is explicitly rejected** — the repairs are ~10 lines each, verified working, and an `xfail`
here would recreate the exact defect being fixed (a test that names a bug and does not guard it).
**Escape hatch.** If the 7 prove flaky in CI for a reason not reproducible locally, revert
**sub-change 3 only**. Selection returns to 187/290/103 and the plugin improvements stay.
---
## 6. Tests to add
In `tests/unit/cli/test_test_command.py` (the existing home of gating-plugin tests, and already in
`EXCLUDED_PATHS`, so these cannot be auto-marked by the thing they test), add
`class TestProviderMarkerGranularity` with:
- `test_ollama_does_not_leak_to_sibling_tests` — **THE meta-test.** If this fails, D7 has regressed.
- `test_openai_does_not_leak_to_sibling_tests`
- `test_plain_test_gets_no_provider_markers`
- `test_decorators_are_scanned` — a `@pytest.mark.parametrize("m", ["ollama/llama2"])` must mark it
- `test_unparseable_file_falls_back_to_whole_file` — conservative over-marking on a parse failure
- `test_network_marker_remains_whole_file_derived` — pins the decision that keeps this change
selection-neutral for the 96 still-deselected tests
- `test_offline_marker_is_registered` — both `pytest.ini` files, or every use warns
No new dependency: `ast`, `tmp_path` and `configparser` are stdlib/pytest builtins.
---
## 7. Verification and acceptance
```bash
# 1. The 7 are now selected
python -m pytest tests/integration/test_base_url_api_base_fix.py -m "$CI_M" --collect-only -q
# expect: 7 selected, 0 deselected
# 2. They pass offline, with no keys and no services
env -u OPENAI_API_KEY -u ANTHROPIC_API_KEY -u OLLAMA_HOST \
python -m pytest tests/integration/test_base_url_api_base_fix.py -m "$CI_M" -o addopts="" -q
# expect: 7 passed
# 3. Selection neutral everywhere else
python -m pytest tests/integration/ $IG -o addopts="" -q --collect-only -m "$CI_M" | tail -1
# expect: 194/290 tests collected (96 deselected)
# 4. `-m provider_ollama` now means Ollama -> 7 + 1 + 1, not 32
# 5. Meta-tests pass
# 6. The three CI shards reproduced verbatim do not regress
# 7. The two pytest.ini marker tables stay in sync
```
**Acceptance gate:** `tests/integration/` collects **194/290 (96 deselected)** — exactly seven more
than baseline, all seven from `test_base_url_api_base_fix.py` — **and passes with
`OPENAI_API_KEY`, `ANTHROPIC_API_KEY` and `OLLAMA_HOST` all unset and no Ollama server running.**
**PR title:** `fix(tests): mark provider tests per test function, not per file`
---
## 8. Filed for separate PRs
- **`tests/test_double_api_fix.py`'s mock no longer intercepts.** `llm.py` routes `gpt-4o-mini`
through `litellm.responses` (`llm.py:6434`), not `litellm.completion`. Forced to run, it makes a
**real OpenAI request** (verified: 401 for `https://api.openai.com/v1/responses`). Today it is
masked by an unconditional auto-`skip` — **anyone who "fixes" the skip without fixing the mock
gets live billed calls.**
- **`network_guard.py` disables itself for `/integration/`, `/e2e/`, `/live/`** (lines 103–105) and
for any `provider_*`-marked test (96–100). The suite's network blocker does not cover the tests
most likely to make network calls.
@@ -1,303 +0,0 @@
# 05 — Live local-model CI job
**Branch:** `feat/ci-ollama-live-job`
**Depends on:** order `04` must merge first. Before it, `-m provider_ollama` selects 32 tests
across 5 files (25 of which are not Ollama tests) and this job is unbuildable.
**Owns:** `.github/workflows/test-optimized.yml`,
`src/praisonai/tests/integration/test_ollama_tool_calling_live.py`.
**Must not edit:** `test_gating.py` (order 04); the `smoke` / `main` / `openai-live` jobs; anything
in `test-core.yml`; `src/praisonai-agents/tests/test_ollama_{fix,async_fix}.py`.
---
## 1. The suite already exists — and is broken
The audit concluded "no ollama live job, and no live suite". The first half is right; **the second
is wrong**. `src/praisonai/tests/integration/test_ollama_tool_calling_live.py` is 230 lines,
7 tests, gated at lines 19–22 on `PRAISONAI_TEST_OLLAMA`. It has never run anywhere.
Measured against `main`, **it cannot run** — three `Agent()` kwargs are now rejected:
```
$ python -c "from praisonaiagents import Agent; Agent(name='C', llm='ollama/qwen3:0.6b', verbose=True)"
TypeError: Agent.__init__() got unexpected keyword argument(s): verbose
verbose: verbosity moved into output=; use output='verbose' (or output=OutputConfig(verbose=True)).
$ ... Agent(..., force_tool_usage="always") -> TypeError: unexpected keyword argument(s): force_tool_usage
$ ... Agent(..., max_tool_repairs=3) -> TypeError: unexpected keyword argument(s): max_tool_repairs
```
All 7 tests use `verbose=True`; two also use the other two. **Every test errors on construction.**
The modern form, verified working:
```python
Agent(name="C",
llm={"model": "ollama/qwen3:0.6b", "force_tool_usage": "always", "max_tool_repairs": 3},
tools=[calculator])
# -> llm_instance.force_tool_usage == 'always', llm_instance.max_tool_repairs == 3
```
So this order is **"fix a dead test file and wire it up"**, not "write a live suite".
---
## 2. Model selection
Measured on a real Ollama 0.33.2 host:
```
$ ollama list
qwen3:0.6b 7df6b6e09427 522 MB
$ ollama show qwen3:0.6b
parameters 751.63M quantization Q4_K_M context length 40960
Capabilities: completion, tools, thinking
```
**Two corrections:** the blob is **522 MB**, not ~400 MB; and it is **not vision capable** —
`completion, tools, thinking` only. Tools + thinking is all this job needs.
**Reliability, measured end-to-end through `praisonaiagents.Agent`:**
| configuration | trials | tool invoked + correct answer | latency |
|---|---|---|---|
| default | 4 | **3/4** — one run returned `{}` with no tool call | 0.5–5.4 s |
| `force_tool_usage="always"`, `temperature=0` | 6 | **6/6** | 0.4–4.0 s |
| indirect prompt ("I know it's easy, but use the tool") | 1 | 0/1 — emitted `{"type": "calculator", ...}`, wrong key | 0.6 s |
| multi-step `(17+25)+(8+9)` | 2 | 1 hung past 90 s; 1 answered 42 instead of 59 | — |
**Conclusion: `qwen3:0.6b` is the right model, but only the forced, zero-temperature, single-call
prompt is CI-deterministic.**
Rejected alternatives: `qwen2.5:0.5b` (~400 MB, older tool calling, unmeasured — no reason to
prefer it over a verified model); `llama3.2:1b` (~1.3 GB, 2.5× the cache for no measured gain);
`smollm2:135m` (**no `tools` capability — disqualifying**); `olmo-3` (the file's current default,
~7B, far too large per run). Keep `olmo-3` as the *local* default so developer workflow is
unchanged; let CI override via env var.
**Cache:** `~/.ollama/models`, keyed `${{ runner.os }}-ollama-models-${{ env.OLLAMA_TEST_MODEL }}`.
**No `restore-keys`** — a partial restore of a *different* model's blobs is worse than a clean
pull, and a stale key would silently test the wrong model.
**Install:** pinned release tarball, not `curl https://ollama.com/install.sh | sh`. The install
script tracks latest, so the job would silently change what it tests, and it pulls GPU runtimes a
CPU-only runner never uses. Expect ~20–60 s tarball + ~30–90 s cold model pull, near-zero on a
cache hit — **the executing agent must confirm real timings on the first green run and write them
into a YAML comment.**
**Gating:** `if: github.event_name == 'schedule' || github.event.inputs.tier == 'extended' ||
github.event.inputs.tier == 'nightly'` — byte-identical to `extended-anthropic` (line 467),
`extended-google` (525), `extended-groq` (585), `extended-xai` (644), `extended-cohere` (703).
**It never runs on a pull request.**
---
## 3. One deliberate departure from the sibling jobs
Every existing live job ends `|| echo "... tests completed"`, so **it can never fail**. That is
defensible for key-dependent jobs — a rotated secret should not page anyone — but it is exactly
the "test that cannot fail" pattern this whole effort exists to remove, and **Ollama needs no
secret**: availability is fully under the job's control.
So the job has **two run steps**:
1. a **required** minimum-contract step with **no `|| echo`**;
2. an **informational** step for the measured-flaky remainder, keeping the sibling style.
**Do not merge them.**
---
## 4. Test-file changes
1. After `pytestmark`, add the model indirection:
```python
# CI overrides this with a small, fast model; local runs keep olmo-3.
OLLAMA_MODEL = "ollama/" + os.getenv("PRAISONAI_OLLAMA_TEST_MODEL", "olmo-3")
```
2. Replace all 7 hard-coded `llm="ollama/olmo-3"` with `llm=OLLAMA_MODEL`.
3. Remove `verbose=True` from all 7 `Agent(...)` calls. Where verbosity is wanted: `output="verbose"`.
4. Move `force_tool_usage="always"` and `max_tool_repairs=3` into an `llm` dict.
5. Add the CI-minimum test as a new first class — **the only assertion in the file with a measured
6/6 pass rate**:
```python
class TestOllamaCIMinimum:
"""The minimum contract a local model must satisfy: a tool call round-trips.
Deliberately narrow. Measured on qwen3:0.6b: this exact configuration
(forced tool usage, temperature 0, single arithmetic step) passed 6/6.
The default configuration passed 3/4 and multi-step prompts were worse --
those live in TestOllamaToolCallingLive, which CI runs informationally.
"""
def test_tool_call_round_trips(self, ollama_available):
from praisonaiagents import Agent
invocations = []
def add(a: int, b: int) -> int:
"""Add two integers together.
Args:
a: First number to add
b: Second number to add
"""
invocations.append((a, b))
return a + b
agent = Agent(
name="CI Calculator",
llm={"model": OLLAMA_MODEL, "force_tool_usage": "always", "temperature": 0},
tools=[add],
)
result = agent.chat("Compute 17 + 25. You MUST use the calculator tool.")
# 1. the model actually called our function, with the right arguments
assert invocations == [(17, 25)], f"tool was not invoked: {invocations!r}"
# 2. the tool's return value made it back into the model's answer
assert "42" in str(result), f"tool result did not round-trip: {result!r}"
```
Reuse the existing `ollama_available` fixture (lines 48–53) — it already probes
`http://localhost:11434/api/tags` and skips cleanly. Do not add a second probe.
### Why both assertions are needed
`qwen3:0.6b` answers `17 + 25 = 42` **correctly with no tools at all** (measured, 1.2 s,
`tools=[]`). So a bare `assert "42" in result` is satisfied by a model that ignores tools entirely.
The `invocations == [(17, 25)]` half is what proves the tool call was emitted, parsed and
dispatched with the right arguments; the `"42"` half proves the return value was fed back and
reached the final answer. Anything beyond this — multi-step chains, repair loops, resisting
distraction — is measured-flaky on a 0.6B model and belongs in the informational step.
---
## 5. The YAML
Insert after `extended-cohere`'s `Skip notice` step (ends line 760), before the `legacy-unit`
banner. Key fragments:
```yaml
extended-ollama:
if: github.event_name == 'schedule' || github.event.inputs.tier == 'extended' || github.event.inputs.tier == 'nightly'
runs-on: ubuntu-latest
timeout-minutes: 15
env:
# Bump deliberately; the cache key and what we test both follow this.
# No leading "v": install.sh passes ?version=$OLLAMA_VERSION and ollama.com
# redirects to GitHub tag v$version (vv0.33.2 → 404 if set to v0.33.2).
OLLAMA_VERSION: "0.33.2"
OLLAMA_TEST_MODEL: qwen3:0.6b
steps:
- uses: actions/checkout@v4
with:
persist-credentials: false
- name: Set up Python 3.11
uses: actions/setup-python@v5
with:
python-version: '3.11'
- name: Cache Ollama model blobs
uses: actions/cache@v4
with:
path: ~/.ollama/models
# No restore-keys: a partial hit from a different model would
# silently test something other than OLLAMA_TEST_MODEL.
key: ${{ runner.os }}-ollama-models-${{ env.OLLAMA_TEST_MODEL }}
- name: Install Ollama
shell: bash
run: |
set -euo pipefail
# The official installer, VERSION-PINNED via OLLAMA_VERSION (which it
# honours). Since v0.33 the linux bundle ships as a .tar.zst with GPU
# runtimes bundled in, so a direct release-asset download is not a
# workable alternative; the installer handles the zst/tgz split.
sudo apt-get update -qq && sudo apt-get install -y -qq zstd
curl -fsSL https://ollama.com/install.sh | sh
ollama --version
- name: Start Ollama and pull model
shell: bash
run: |
set -euo pipefail
ollama serve > /tmp/ollama-serve.log 2>&1 &
for i in $(seq 1 30); do
if curl -sf http://127.0.0.1:11434/api/tags > /dev/null; then
echo "Ollama is up after ${i}s"; break
fi
sleep 1
done
curl -sf http://127.0.0.1:11434/api/tags > /dev/null
ollama pull "$OLLAMA_TEST_MODEL"
ollama list
- 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]"
- name: Run Ollama minimum contract (required)
env:
PRAISONAI_TEST_TIER: extended
PRAISONAI_ALLOW_NETWORK: '1'
PRAISONAI_LIVE_TESTS: '1'
PRAISONAI_TEST_PROVIDERS: 'ollama'
PRAISONAI_TEST_OLLAMA: '1'
PRAISONAI_OLLAMA_TEST_MODEL: ${{ env.OLLAMA_TEST_MODEL }}
shell: bash
run: |
set -euo pipefail
cd src/praisonai
# No "|| echo" here on purpose: no secret is involved, so a failure
# here is a real regression in local-model tool calling.
python -m pytest tests/integration/test_ollama_tool_calling_live.py::TestOllamaCIMinimum \
-m "provider_ollama" -v --tb=short --timeout=120
- name: Run remaining Ollama live tests (informational)
if: always()
env: { ...same... }
run: |
cd src/praisonai
python -m pytest tests/integration/test_ollama_tool_calling_live.py \
-m "provider_ollama" \
--deselect tests/integration/test_ollama_tool_calling_live.py::TestOllamaCIMinimum \
-v --tb=short --timeout=180 \
|| echo "Ollama exploratory tests completed (small models are non-deterministic)"
- name: Ollama server log
if: failure()
run: tail -100 /tmp/ollama-serve.log
```
And in `test-summary` (line 838): extend `needs: [smoke, main, extended-ollama]` and add the
summary rows. `test-summary` is already `if: always()`, so a skipped `extended-ollama` on PRs
reports `skipped` rather than blocking.
---
## 6. Verification and acceptance
```bash
ollama pull qwen3:0.6b
cd src/praisonai && export PYTHONPATH=$(cd ../praisonai-agents && pwd)
# Must be 6/6 before this ships.
for i in $(seq 1 6); do
PRAISONAI_TEST_OLLAMA=1 PRAISONAI_ALLOW_NETWORK=1 PRAISONAI_LIVE_TESTS=1 \
PRAISONAI_TEST_PROVIDERS=ollama PRAISONAI_OLLAMA_TEST_MODEL=qwen3:0.6b \
python -m pytest tests/integration/test_ollama_tool_calling_live.py::TestOllamaCIMinimum \
-o addopts="" -q --timeout=120 2>&1 | tail -1
done
# The gate still holds with the env var absent:
python -m pytest tests/integration/test_ollama_tool_calling_live.py -o addopts="" -q --collect-only
# expect: collected, all skipped by the module pytestmark
# Nothing leaked onto the PR path:
grep -n "extended-ollama" -A3 .github/workflows/test-optimized.yml | grep "if:"
python -c "import yaml; yaml.safe_load(open('.github/workflows/test-optimized.yml')); print('yaml ok')"
# Then: gh workflow run "Optimized Test Suite" -f tier=extended
```
**Acceptance gate:** a manual `workflow_dispatch` with `tier=extended` shows `extended-ollama`
**green**, with "Run Ollama minimum contract (required)" reporting `1 passed` — **and** the same
workflow triggered by a pull request shows `extended-ollama` **skipped**.
**PR title:** `ci: add nightly live-Ollama job exercising a real local model`
File diff suppressed because it is too large. Load diff
File diff suppressed because it is too large. Load diff
@@ -1,196 +0,0 @@
# Local Model Layer — implementation ledger
**Status:** every order below has an open PR. See §4.
**Owner workstream:** local model runtimes (Ollama, LM Studio, llama.cpp, vLLM, MLX, `transformers serve`)
**Created:** 2026-09-03
---
## 0. How to use this document
This directory is a **work-order ledger**. It exists so that any agent — including one
with no memory of the conversation that produced it — can pick up exactly one unit of
work and execute it correctly, in isolation, without re-deriving the analysis.
**If you are an agent starting work here, do this in order:**
1. Read [`00-ground-truth.md`](00-ground-truth.md). It records what was measured, how, and
when. Do not trust a claim in any work order that contradicts it; re-measure instead.
2. Read §2 (Invariants) and §3 (File ownership) of this file. §3 is what stops two agents
corrupting each other's work.
3. Open the single work order you were assigned. Execute only that one.
4. Update the status row in §4 of this file in the same commit as your change. That row is
the only shared file content; keep the edit to one line to avoid conflicts.
**Do not** expand scope, batch two work orders into one PR, or "fix while you're in there".
Each order is independently revertible by design and that property is worth more than
convenience.
> **Two corrections this ledger has already had to make.** Both were caught by measuring rather
> than reasoning, and both would have sent an agent down the wrong path.
>
> **The D7 root cause is not `provider_ollama`.** The audit blamed the per-file `provider_ollama`
> tag. Measurement (`04-test-gating.md` §2) shows `not network` deselects all seven tests **on its
> own**, because the plugin implies `network` from *any* provider marker and the file also matches
> `provider_openai`. **Removing `not provider_ollama` from the workflows would change nothing.**
> That is why order `04` touches no YAML at all — the fix is marker-side.
> Its first draft told an agent to "wire
> the twelve dead adapter methods". Measurement (`06-adapter-revival.md` §1) says the opposite:
> **12 of 20 items should be deleted, only 3 wired.** Six of the dead methods have no inline
> equivalent anywhere — they are speculative API, and an agent told to "wire them up" would
> invent an implementation that no test could ever have failed against. Read the decision table
> before touching `llm/adapters/`; do not act on the summary in §1 of this file.
---
## 1. Why this work exists
Every local runtime worth supporting already speaks `POST /v1/chat/completions`, and
`litellm` already handles that transport. So the problem is not calling local models — the
SDK can already do that. The problems are:
- **Discovery.** A user with a running daemon still hand-types a URL, a port and an exact
model tag; getting any one wrong produces `OPENAI_API_KEY environment variable is required`.
- **Capability.** "Does this model support tools?" is answerable by asking the server
(`/api/show`, `/props`, `/server_info`). The SDK asks nothing and guesses from a name prefix.
- **Quirks.** Local stacks fail silently with HTTP 200. The sharpest: sending `format` and
`tools` together to Ollama suppresses the tool call and the model fabricates an answer.
The layer being built is therefore a **resolver, not a transport**: it returns data about
what is running and what it will get wrong. Compensating behaviour stays in
`llm/adapters/`, which already declares methods for exactly this purpose.
---
## 2. Invariants — never break these
These come from `src/praisonai-agents/AGENTS.md` §4.6 plus the structural review in
`00-ground-truth.md`. Every work order inherits them; none may waive them.
| # | Invariant | Why it binds this work specifically |
|---|-----------|--------------------------------------|
| I1 | **Backward compatible.** Public API changes need a deprecation cycle. | Several fixes change which code path a given input takes. Each order carries an explicit list of inputs whose behaviour must not change. |
| I2 | **Lazy imports.** Optional deps never imported at module level. | Discovery must not import `litellm` or any runtime SDK at import time. |
| I3 | **Safe defaults.** New features are opt-in. | Discovery must not fire unless the model spec is `"local"` or unset. Never probe the network on a fully-specified config. |
| I4 | **Deterministic tests.** No dependence on timing or external state. | Every test must pass with **no server running**. Live-server tests go behind an explicit marker and never run in the default suite. |
| I5 | **Protocol-driven core.** No heavy implementations in core. | `local/` returns dataclasses. It performs no chat calls, no retry, no request mutation. |
| I6 | **`local/` is a dependency sink.** | It may import the **standard library only** — nothing from `praisonaiagents`, and no third-party distribution (`httpx`/`requests`/`aiohttp` are forbidden; use `urllib.request`). Enforced by a test. See §5 and `07` §3. |
| I7 | **No second abstraction.** | `llm/adapters/` is the extension point. Do not add a parallel quirk/adapter registry beside it. |
| I8 | **No new public knobs without a live consumer.** | Root `AGENTS.md`: do not add params, modules or exports that merely duplicate existing behaviour. |
### I6 in detail — the import rule
An AST pass over `praisonaiagents/` (595 files, 238,936 lines) found **65 subpackages, 212
directed edges and 26 mutually-importing subpackage pairs**. `llm/` already imports upward
into `agent/`, and 15 subpackages import `llm/` back. Consequently a shared helper placed in
`llm/` **cannot** be adopted by `memory/` or `eval/` without deepening the existing cycles.
`local/` is therefore specified as a leaf. That single property is what allows the 21
modules which currently bypass the LLM layer to adopt it later. Treat any import of
`praisonaiagents.*` from inside `local/` as a build break, not a style issue.
The HTTP client is stdlib `urllib.request`, **not** `httpx`. An earlier draft of this ledger
permitted `httpx` on the grounds that it is a transitive dependency of `openai>=2.0.0`. That
was reversed in `07` §3: the edge is undeclared in `pyproject.toml`, so a future `openai`
release that drops `httpx` would silently break the sink — precisely the class of failure this
package exists to catalogue. The boundary test in §5 hard-forbids `httpx`/`requests`/`aiohttp`
so the decision cannot drift.
---
## 3. File ownership — collision avoidance
Two work orders that touch the same file **must not run concurrently**. This table is the
authority. Before starting, check that no in-flight PR owns your files.
| Work order | Owns (may edit) | Must not edit |
|---|---|---|
| `01-d1-default-model` | `agent/agent.py` (branch chain only) | `llm/llm.py`, `llm/adapters/` |
| `02-d3-provider-detection` | `llm/llm.py` (`_detect_provider`, `_is_ollama_provider` only) | `agent/agent.py`, `llm/adapters/` |
| `03-d2-base-url-routing` | `agent/agent.py` (base_url branch), root `README.md` | `llm/llm.py`, `llm/adapters/` |
| `04-test-gating` | `tests/_pytest_plugins/test_gating.py`, both `pytest.ini`, `tests/conftest.py`, `tests/integration/test_base_url_api_base_fix.py`, `tests/unit/cli/test_test_command.py` | any `praisonaiagents/` source; **`.github/workflows/**` — the `-m` expressions are not the bug** |
| `05-live-ci-job` | `.github/workflows/test-optimized.yml`, `tests/integration/test_ollama_tool_calling_live.py` | any `praisonaiagents/` source; `test_gating.py` |
| `06-adapter-revival` | `llm/adapters/__init__.py`, `llm/llm.py` (3 response paths) | `agent/agent.py` |
| `07-local-package` | `praisonaiagents/local/**` (new), `src/praisonai/tests/unit/llm/local/**` (new), `pyproject.toml` extras | everything else |
| `08-reachability` | `memory/`, `eval/`, `context/`, `lite/`, `telemetry/` | `llm/`, `agent/` |
### Enforced serialisation
- **`01` then `03`** — both edit `agent/agent.py`. Land `01` first.
- **`02` then `06`** — both edit `llm/llm.py`. Land `02` first; it is far smaller.
- **`04` then `05`** — before `04`, `-m provider_ollama` selects 32 tests across 5 files (only 7
are Ollama tests), so `05` has no usable selector and is unbuildable.
- **`04` and `07` are independent** of orders 01/02/03/06 and may run in parallel with them.
- **`08` requires `07`** to have landed, because it consumes `local/`.
---
## 4. Status
Update your row in the same commit as your change. One line only.
Additional PRs not in the original order list, found while executing it:
D4 (local route prefixes) #4798, D5 (local embedding dimensions) #4802,
D6 (registry accepts local providers) #4800.
**Three claims in this ledger were corrected by executing it.** Each is marked
inline where it appears, but they are collected here because a reader who trusts
the summary would otherwise carry the wrong version:
1. *"Wire the twelve dead adapter methods."* Measurement said the opposite:
**12 of 20 items should be deleted, only 3 wired** (`06` §1). Six had no
inline equivalent at all — an agent told to wire them would have invented
behaviour no test could fail against.
2. *"`provider_ollama` deselects the mocked base_url suite."* It does not.
**`not network` deselects it on its own**, because the plugin implies
`network` from any provider marker (`04` §1). Editing the workflow `-m`
strings would have changed nothing.
3. *"Running fully locally is unachievable, not merely unconfigured."* Not so:
litellm and the openai SDK both honour `OPENAI_BASE_URL`, so the bypass sites
**do** reach a local server. The blocker is the hardcoded model name they then
ask for (`00` §5, `08`).
| Order | Title | Branch | PR | Status |
|---|---|---|---|---|
| 01 | D1 — provider-prefixed default model never reaches litellm | `fix/d1-default-provider-model` | #4795 | PR open |
| 02 | D3 — provider over-detection from base_url | `fix/d3-provider-detection` | #4797 | PR open |
| 03 | D2 — README recipe + local-endpoint diagnostic | `fix/d2-base-url-routing` | #4799 | PR open |
| 04 | D7 — per-file provider marker deselects unrelated tests | `fix/d7-per-test-provider-markers` | #4801 | PR open |
| 05 | Live local-model CI job | `feat/ci-ollama-live-job` | #4803 | PR open |
| 06 | A1/A2 — make the provider adapter load-bearing (6 sub-steps) | 6 branches, stacked | #4804 #4806 #4808 #4809 #4810 #4811 | **complete — KNOWN_DEAD empty** |
| 07 | `praisonaiagents/local/` — discovery and capability resolver | `feat/local-model-resolver` | #4807 | PR open |
| 08 | A3 — auxiliary-model fallback configurable everywhere | `fix/reachability-local-endpoint` | #4812 | PR open (model half; parameter half deferred) |
---
## 5. The two tests that keep this work honest
Both are cheap, both are anti-regression, and both should land with their respective orders.
**Import boundary (`07`).** Asserts `local/` imports nothing from `praisonaiagents`. Without
it, I6 decays silently and the leaf property — the whole reason the package can be adopted
by `memory/` and `eval/` — is lost.
**Adapter reachability (`06`).** Asserts every method on `DefaultAdapter` has at least one
call site. This is the test whose absence allowed 11 of 17 adapter methods to become dead code
while `llm.py` grew 145 hand-written Ollama references. Two limits, both real: it cannot detect
an *unreachable* call site (proven by `should_skip_streaming_with_tools`, which a caller would
have satisfied while the branch stayed dead), and **one call site satisfies it — so it does not
detect the three-path divergence at all.** A floor, not a ceiling.
---
## 6. Deliberately out of scope
Named here so that deferring them is a decision rather than an oversight. Do not let a work
order quietly grow into one of these.
| Deferred | Measured size | Why not now |
|---|---|---|
| Consolidating `LLM` and `OpenAIClient` behind one protocol | 7,160 + 2,691 lines, selected by one boolean at 6 sites | Neither is a superset of the other; the merge is larger than every order in this ledger combined. |
| Decomposing `LLM.get_response` | 1,675 lines, 194 branch/loop/try nodes | Highest-risk file in the package. Order `06` must edit it surgically without reflowing it. |
| Removing the sync/async divergence | ~1,628 duplicated lines across 10 pairs; `get_response` vs `_async` only 22.3% similar | Requires the consolidation above to be worth doing. |
The one obligation this ledger accepts toward them: **do not make them worse.** No order may
add a fifth copy of any compensation, and no order may add new logic inside `get_response`
that is not a delegation to an adapter.
@@ -133,23 +133,12 @@ _LAZY_IMPORTS = {
'resolve_harness': ('praisonaiagents.model_harness.profiles', 'resolve_harness'),
'register_profile': ('praisonaiagents.model_harness.profiles', 'register_profile'),
# Test doubles - drive an Agent offline and keep real requests out of a suite
'ScriptedModel': ('praisonaiagents.model_harness.scripted', 'ScriptedModel'),
'ScriptExhausted': ('praisonaiagents.model_harness.scripted', 'ScriptExhausted'),
'allow_model_requests': ('praisonaiagents.model_harness.guard', 'allow_model_requests'),
'no_model_requests': ('praisonaiagents.model_harness.guard', 'no_model_requests'),
'ModelRequestBlocked': ('praisonaiagents.model_harness.guard', 'ModelRequestBlocked'),
# Run outcomes - typed validation and agent execution results
'AgentRunOutcome': ('praisonaiagents.run_outcome', 'AgentRunOutcome'),
'RunStatus': ('praisonaiagents.run_outcome', 'RunStatus'),
'TerminationReason': ('praisonaiagents.run_outcome', 'TerminationReason'),
'termination_to_run_status': ('praisonaiagents.run_outcome', 'termination_to_run_status'),
'validate_decision_string': ('praisonaiagents.run_outcome', 'validate_decision_string'),
'RunTerminal': ('praisonaiagents.run_outcome', 'RunTerminal'),
'merge_run_terminal': ('praisonaiagents.run_outcome', 'merge_run_terminal'),
'is_sticky': ('praisonaiagents.run_outcome', 'is_sticky'),
'collapse': ('praisonaiagents.run_outcome', 'collapse'),
# Main display utilities (imports rich)
'TaskOutput': ('praisonaiagents.main', 'TaskOutput'),
@@ -231,7 +220,6 @@ _LAZY_IMPORTS = {
# Guardrails
'GuardrailResult': ('praisonaiagents.guardrails', 'GuardrailResult'),
'LLMGuardrail': ('praisonaiagents.guardrails', 'LLMGuardrail'),
'GuardrailRetry': ('praisonaiagents.guardrails', 'GuardrailRetry'),
# Approval (agent-centric approval backends)
'AutoApproveBackend': ('praisonaiagents.approval.backends', 'AutoApproveBackend'),
@@ -5,6 +5,7 @@ Provides feature flags and configuration options that can be controlled
via environment variables for performance tuning and behavior control.
Environment Variables:
PRAISONAI_LAZY_IMPORTS: Enable lazy imports (default: true)
PRAISONAI_TELEMETRY_ENABLED: Enable telemetry (default: false, opt-in)
PRAISONAI_TELEMETRY_DISABLED: Disable telemetry (takes precedence)
DO_NOT_TRACK: Standard opt-out flag (takes precedence)
@@ -27,6 +28,13 @@ def _str_to_bool(value: Optional[str], default: bool = False) -> bool:
# Feature Flags
# -------------
# Lazy imports: When True (default), heavy dependencies like litellm are
# only imported when actually needed, reducing import time significantly.
LAZY_IMPORTS = _str_to_bool(
os.environ.get('PRAISONAI_LAZY_IMPORTS'),
default=True
)
# Telemetry: Opt-in by default (False). Users must explicitly enable.
# Precedence (highest to lowest):
# 1. DO_NOT_TRACK=true -> disabled
@@ -99,3 +107,7 @@ def _get_plugins_list() -> list:
return []
# Parse comma-separated list
return [p.strip() for p in env_value.split(',') if p.strip()]
PLUGINS_ENABLED = _get_plugins_enabled()
PLUGINS_LIST = _get_plugins_list()
+3 -35
View File
@@ -37,22 +37,6 @@ _cache_lock = threading.RLock()
# Global module cache
_module_cache: Dict[str, Any] = {}
# Import roots of praisonaiagents' declared *core* runtime dependencies (see
# pyproject.toml ``[project].dependencies``). A lazy import that fails because
# one of these is missing/broken indicates a genuinely broken install, which
# must be surfaced rather than masked as a graceful ``None``. Optional
# integrations whose own optional SDKs are absent are NOT in this set, so they
# keep the documented ``None`` fallback.
_CORE_REQUIRED_DEPENDENCIES = frozenset({
"pydantic",
"rich",
"openai",
"posthog",
"aiohttp",
"yaml", # PyYAML — core dep; import root differs from the package name
"croniter",
})
def lazy_import(
module_path: str,
@@ -236,25 +220,9 @@ def create_lazy_getattr_with_fallback(
_cache[name] = None
return None
except ImportError as exc:
# Distinguish "optional integration not installed" from
# "a required *core* dependency is broken". A missing/broken core
# dependency (e.g. ``pydantic``) must be surfaced loudly instead
# of being masked as ``None`` (which resurfaces later as a
# confusing ``NoneType`` error). But an optional integration whose
# own optional SDK is absent must keep the documented graceful
# ``None`` fallback — the failing module name there belongs to
# that optional SDK, not to us. We therefore only escalate when
# the failing module is one of praisonaiagents' declared *core*
# runtime dependencies; everything else stays a soft None.
failing = getattr(exc, "name", None)
failing_root = failing.split(".")[0] if failing else None
if failing_root in _CORE_REQUIRED_DEPENDENCIES:
raise ImportError(
f"Failed to load {name!r} because importing {module_path!r} "
f"raised: {exc}. This usually means a required core dependency "
f"({failing_root!r}) is missing or broken, not that {name!r} is "
f"an optional feature you chose not to install."
) from exc
# Optional module not available: preserve the graceful None
# fallback, but record why so real import failures remain
# diagnosable instead of surfacing later as NoneType errors.
_logger.debug(
"Lazy import of %r (%s.%s) failed: %s",
name, module_path, attr_name, exc,
@@ -28,10 +28,8 @@ def _configure_environment():
"PYDANTIC_WARNINGS_ENABLED": "False",
}
# Use setdefault so a value the host exported before launch is preserved
# (and not leaked/overwritten into subprocesses spawned afterwards).
for key, value in env_vars.items():
os.environ.setdefault(key, value)
os.environ[key] = value
# ========================================================================
@@ -50,11 +48,7 @@ def _get_all_noisy_loggers() -> List[str]:
# Markdown
"markdown_it", "rich.markdown",
# System
# NOTE: "asyncio" is intentionally NOT suppressed here — it is the host
# application's own logger, not a PraisonAI dependency's. Forcing it to
# CRITICAL hides unrelated host errors (e.g. "Task exception was never
# retrieved").
"selector_events", "pydantic",
"asyncio", "selector_events", "pydantic",
"praisonaiagents.telemetry.telemetry",
]
@@ -215,14 +215,6 @@ def __getattr__(name):
from .memory_mixin import MemoryMixin
_lazy_cache[name] = MemoryMixin
return MemoryMixin
elif name == 'AttachmentError':
from .attachments import AttachmentError
_lazy_cache[name] = AttachmentError
return AttachmentError
elif name == 'build_attachment_parts':
from .attachments import build_attachment_parts
_lazy_cache[name] = build_attachment_parts
return build_attachment_parts
raise AttributeError(f"module {__name__!r} has no attribute {name!r}")
@@ -305,7 +297,4 @@ __all__ = [
'ChatMixin',
'ExecutionMixin',
'MemoryMixin',
# Attachments
'AttachmentError',
'build_attachment_parts',
]
File diff suppressed because it is too large. Load diff
@@ -12,38 +12,6 @@ from contextlib import contextmanager, asynccontextmanager
from weakref import WeakKeyDictionary
def run_async_in_sync_context(coro):
"""
Run an async coroutine to completion from a sync context with proper
event loop handling.
Handles the common cases:
1. No event loop exists - use asyncio.run()
2. Event loop already running - avoid deadlock by running the coroutine
to completion in a dedicated thread with its own event loop.
This is a live production helper on the sync tool-calling path (see
``tool_execution.py``): it bridges ``async def`` tool bodies into the sync
tool loop, otherwise a bare un-awaited coroutine would be handed to the
model as the tool result and the tool body would never run (silent data
loss).
Delegates to the single canonical bridge
(:func:`utils.async_bridge.run_coroutine_from_any_context`) so all sync→async
call sites share one implementation: the caller's ``contextvars`` (trace /
session / approval context) are carried into the coroutine, and the running
loop is handled on a dedicated worker thread rather than raising.
``timeout=None`` is passed deliberately: this helper backs the sync
tool-calling path, where a tool's own timeout policy (or lack of one) already
governs how long a tool may run. Imposing the bridge's default 5-minute
deadline here would silently cancel long-running tools that previously had no
limit — a backward-incompatible regression — so the bridge adds none.
"""
from ..utils.async_bridge import run_coroutine_from_any_context
return run_coroutine_from_any_context(coro, timeout=None)
class DualLock:
"""
A dual-lock abstraction that automatically selects threading.Lock or asyncio.Lock
@@ -69,24 +37,9 @@ class DualLock:
"""
def __init__(self):
"""Initialize with a single underlying mutex shared by both call styles.
A single ``threading.Lock`` backs both ``sync()`` and ``async_lock()``
so that holding one genuinely blocks the other — mutual exclusion is
real across sync and async callers of the same instance. A plain
``Lock`` (not ``RLock``) is used because the async path acquires on a
worker thread but releases on the event-loop thread, which ``RLock``'s
thread-ownership semantics forbid. Same-thread ``sync()`` reentrancy is
preserved explicitly via an owner/depth guard below. The per-event-loop
``asyncio.Lock`` only serialises coroutines on the same loop so they
queue for the underlying mutex cooperatively instead of every coroutine
racing straight into the blocking acquire.
"""
self._thread_lock = threading.Lock() # Shared mutex (cross-thread release ok)
self._owner_lock = threading.Lock() # Guards the reentrancy bookkeeping
self._owner_thread: Any = None # Thread id currently holding for sync reentrancy
self._owner_depth = 0
self._async_locks = WeakKeyDictionary() # Per-event-loop async gate
"""Initialize with separate threading and asyncio locks."""
self._thread_lock = threading.RLock() # Re-entrant lock to handle nested acquisitions
self._async_locks = WeakKeyDictionary() # Per-event-loop async locks
def __deepcopy__(self, memo):
"""Return an unlocked primitive with no event-loop state sharing."""
@@ -96,31 +49,9 @@ class DualLock:
@contextmanager
def sync(self):
"""Acquire lock in synchronous context using the shared mutex.
Re-entrant for the same thread: a nested ``sync()`` on the thread that
already holds the mutex does not re-acquire (and cannot self-deadlock).
"""
me = threading.get_ident()
with self._owner_lock:
reentrant = self._owner_thread == me and self._owner_depth > 0
if reentrant:
self._owner_depth += 1
if not reentrant:
self._thread_lock.acquire()
with self._owner_lock:
self._owner_thread = me
self._owner_depth = 1
try:
"""Acquire lock in synchronous context using threading.Lock."""
with self._thread_lock:
yield
finally:
with self._owner_lock:
self._owner_depth -= 1
released = self._owner_depth == 0
if released:
self._owner_thread = None
if released:
self._thread_lock.release()
def _get_async_lock(self):
"""Get or create an asyncio.Lock for the current event loop."""
@@ -133,64 +64,16 @@ class DualLock:
self._async_locks[loop] = asyncio.Lock()
return self._async_locks[loop]
async def _acquire_shared_mutex(self, loop):
"""Acquire the shared mutex off-loop, releasing it if we are cancelled.
``run_in_executor`` can complete (mutex acquired) after the awaiting
task is cancelled. If we let the ``CancelledError`` propagate without
checking, the worker would strand the mutex forever. We therefore wait
on the acquisition, and on cancellation ensure the mutex is released
once the worker finishes so no caller waits indefinitely.
"""
future = loop.run_in_executor(None, self._thread_lock.acquire)
try:
await asyncio.shield(future)
except asyncio.CancelledError:
# The worker may still be mid-acquire; wait for it to settle, then
# release if it managed to take the mutex so it is never orphaned.
try:
acquired = await future
except asyncio.CancelledError:
acquired = False
if acquired:
self._thread_lock.release()
raise
@asynccontextmanager
async def async_lock(self):
"""Acquire lock in asynchronous context using the shared mutex.
Backs onto the *same* ``threading.Lock`` as ``sync()`` so a concurrent
sync caller is genuinely excluded (and vice-versa). The blocking
``acquire`` is offloaded to a worker thread so the event loop is never
blocked while waiting; the matching ``release`` (allowed cross-thread on
a plain ``Lock``) happens on the loop thread. A per-event-loop
``asyncio.Lock`` serialises coroutines on this loop first so they don't
all spin up executor hops at once.
While the mutex is held, the *event-loop thread* is registered as the
sync owner so a nested ``with lock.sync()`` on that thread (used by the
async handoff seeding path) is treated as re-entrant instead of
self-deadlocking against the mutex we already hold.
"""Acquire lock in asynchronous context using asyncio.Lock.
Uses a per-event-loop asyncio.Lock to ensure proper async coordination
without blocking the event loop or violating thread ownership semantics.
"""
loop = asyncio.get_running_loop()
async_gate = self._get_async_lock()
async with async_gate:
await self._acquire_shared_mutex(loop)
me = threading.get_ident()
with self._owner_lock:
self._owner_thread = me
self._owner_depth = 1
try:
yield
finally:
with self._owner_lock:
self._owner_depth -= 1
released = self._owner_depth == 0
if released:
self._owner_thread = None
if released:
self._thread_lock.release()
async_lock = self._get_async_lock()
async with async_lock:
yield
def is_async_context(self) -> bool:
"""Check if we're currently in an async context."""
@@ -264,11 +147,6 @@ class AsyncSafeState:
@asynccontextmanager
async def async_lock(self):
"""Acquire lock in async context."""
# Fail fast BEFORE blocking on the shared mutex: an in-progress
# synchronous deepcopy holds the mutex for the whole copy, so waiting on
# it here would block until the copy finished instead of surfacing the
# documented RuntimeError (and could stall the loop indefinitely).
self._raise_if_copying()
async with self._lock.async_lock():
self._begin_async_access()
try:
@@ -276,14 +154,6 @@ class AsyncSafeState:
finally:
self._end_async_access()
def _raise_if_copying(self) -> None:
"""Reject entry while a synchronous deepcopy of this state is active."""
with self._activity_lock:
if self._copying:
raise RuntimeError(
"Cannot access AsyncSafeState during synchronous deepcopy"
)
def _begin_async_access(self) -> None:
"""Register async access unless a synchronous copy is in progress."""
with self._activity_lock:
@@ -300,32 +170,20 @@ class AsyncSafeState:
def __enter__(self):
"""Support for synchronous context manager protocol (backward compatibility)."""
self._sync_guard = self._lock.sync()
self._sync_guard.__enter__()
self._lock._thread_lock.acquire()
return self.value
def __exit__(self, exc_type, exc_val, exc_tb):
"""Support for synchronous context manager protocol (backward compatibility)."""
return self._sync_guard.__exit__(exc_type, exc_val, exc_tb)
self._lock._thread_lock.release()
return None
async def __aenter__(self):
"""Support for asynchronous context manager protocol."""
# Fail fast before blocking on the mutex an in-progress deepcopy holds.
self._raise_if_copying()
loop = asyncio.get_running_loop()
async_lock = self._lock._get_async_lock()
await async_lock.acquire()
try:
# Hold the SAME underlying mutex used by the sync path so async and
# sync accessors are mutually exclusive (matches DualLock.async_lock).
# Cancellation-safe acquire so the mutex is never stranded if the
# awaiting task is cancelled mid-acquisition.
await self._lock._acquire_shared_mutex(loop)
try:
self._begin_async_access()
except Exception:
self._lock._thread_lock.release()
raise
self._begin_async_access()
except Exception:
async_lock.release()
raise
@@ -337,10 +195,7 @@ class AsyncSafeState:
try:
self._end_async_access()
finally:
try:
self._lock._thread_lock.release()
finally:
async_lock.release()
async_lock.release()
return None
def get(self) -> Any:
@@ -1,443 +0,0 @@
"""Attachment routing for multimodal prompts.
The one invariant this module exists to enforce: **an attachment is never
dropped silently**. Every input either becomes a model-visible content part, or
produces a loud, actionable signal that names the file and says why.
Two failure classes are treated differently on purpose:
``raise`` -- *addressing* errors: the path does not exist, is a directory, is
unreadable, or the attachment is not a type this API accepts. These are
always caller mistakes (a typo, a wrong working directory, a stale path).
They are fully actionable at the call site, there is no useful degraded
answer, and continuing would produce a confident answer about a file the
model never saw. Raising is the only way the caller can tell.
``warn + visible degrade`` -- *capability* limits: the file is there and
readable, but the target model cannot ingest that media type. The run can
still be useful, so we log a warning **and** put a marker part in the
prompt so the model itself knows a file was withheld or converted and can
say so. This is environmental, not a bug in the caller's code, and hard
failing would make a model swap a breaking change.
Escape hatches (both default to the behaviour described above):
- ``PRAISONAI_ATTACHMENTS_ON_MISSING=warn`` downgrades the missing/unreadable
raise to a warning + visible marker part.
- ``PRAISONAI_ATTACHMENTS_STRICT=1`` escalates capability degrades to raises,
for pipelines that would rather fail than get a partial answer.
Part shapes emitted (OpenAI/LiteLLM chat-completions style):
- image -> ``{"type": "image_url", "image_url": {"url": "data:...;base64,..."}}``
- pdf native -> ``{"type": "file", "file": {"filename": ..., "file_data": "data:application/pdf;base64,..."}}``
- audio -> ``{"type": "input_audio", "input_audio": {"data": "<b64>", "format": "mp3"}}``
- text/degraded/withheld -> ``{"type": "text", "text": "[Attachment: ...] ..."}``
"""
import base64
import logging
import os
from typing import Any, Dict, List, Optional
from ..tools.base import file_part, image_part, text_part
__all__ = [
"AttachmentError",
"build_attachment_parts",
"resolve_attachment_model_name",
"IMAGE_EXTENSIONS",
"PDF_EXTENSIONS",
"AUDIO_EXTENSIONS",
"VIDEO_EXTENSIONS",
"TEXT_EXTENSIONS",
]
class AttachmentError(ValueError):
"""Raised when an attachment cannot be turned into a model content part.
Subclasses ``ValueError`` so existing ``except ValueError`` handlers around
``chat()`` keep working.
"""
# --- Type tables -----------------------------------------------------------
# Unchanged from the original image-only implementation; images must keep
# producing byte-identical parts.
IMAGE_MEDIA_TYPES = {
".jpg": "image/jpeg",
".jpeg": "image/jpeg",
".png": "image/png",
".gif": "image/gif",
".webp": "image/webp",
}
IMAGE_EXTENSIONS = frozenset(IMAGE_MEDIA_TYPES)
PDF_EXTENSIONS = frozenset({".pdf"})
# Extension -> the ``format`` string sent in an ``input_audio`` part.
AUDIO_FORMATS = {
".mp3": "mp3",
".wav": "wav",
".m4a": "m4a",
".ogg": "ogg",
".oga": "ogg",
".opus": "opus",
".flac": "flac",
".aac": "aac",
}
AUDIO_EXTENSIONS = frozenset(AUDIO_FORMATS)
VIDEO_EXTENSIONS = frozenset({".mp4", ".mov", ".avi", ".mkv", ".webm", ".mpeg", ".mpg", ".wmv"})
# Files we can safely inline as UTF-8 text. No model capability needed.
TEXT_EXTENSIONS = frozenset({
".txt", ".md", ".markdown", ".rst", ".log", ".csv", ".tsv", ".json",
".jsonl", ".yaml", ".yml", ".toml", ".ini", ".cfg", ".conf", ".xml",
".html", ".htm", ".sql", ".py", ".js", ".ts", ".tsx", ".jsx", ".java",
".c", ".h", ".cpp", ".hpp", ".cs", ".go", ".rs", ".rb", ".php", ".swift",
".kt", ".sh", ".bash", ".zsh", ".env", ".tex", ".srt", ".vtt",
})
# Inlined text is truncated so one large file cannot blow the context window.
# Truncation is announced in the part itself, never silent.
MAX_INLINE_TEXT_CHARS = 100_000
# --- Helpers ---------------------------------------------------------------
def _on_missing_raises() -> bool:
return os.environ.get("PRAISONAI_ATTACHMENTS_ON_MISSING", "error").strip().lower() not in (
"warn", "warning", "ignore", "0", "false",
)
def _strict_unsupported() -> bool:
return os.environ.get("PRAISONAI_ATTACHMENTS_STRICT", "").strip().lower() in (
"1", "true", "yes", "on", "error", "raise",
)
def _fail(message: str) -> List[Dict[str, Any]]:
"""Addressing error: raise, unless explicitly downgraded to a warning."""
if _on_missing_raises():
raise AttachmentError(message)
logging.warning("Attachment problem: %s", message)
return [text_part(f"[Attachment could not be read: {message}]")]
def _degrade(message: str, marker: str) -> List[Dict[str, Any]]:
"""Capability limit: warn loudly and leave a marker the model can see."""
if _strict_unsupported():
raise AttachmentError(message + " (PRAISONAI_ATTACHMENTS_STRICT is set)")
logging.warning("Attachment degraded: %s", message)
return [text_part(marker)]
def _read_bytes(path: str) -> bytes:
with open(path, "rb") as fh:
return fh.read()
def _b64(data: bytes) -> str:
return base64.b64encode(data).decode("utf-8")
def _extract_pdf_text(path: str) -> Optional[str]:
"""Return a PDF's text, or ``None`` if no extractor is installed/usable."""
try:
from pypdf import PdfReader # type: ignore
except ImportError:
try:
from PyPDF2 import PdfReader # type: ignore
except ImportError:
return None
try:
reader = PdfReader(path)
pages = []
for index, page in enumerate(reader.pages, start=1):
try:
pages.append(f"--- page {index} ---\n{page.extract_text() or ''}")
except Exception as exc: # noqa: BLE001 - one bad page must not kill the rest
logging.debug("PDF page %d of %s failed to extract: %s", index, path, exc)
text = "\n".join(pages).strip()
return text or None
except Exception as exc: # noqa: BLE001
logging.debug("PDF text extraction failed for %s: %s", path, exc)
return None
def _truncate(text: str, label: str) -> str:
if len(text) <= MAX_INLINE_TEXT_CHARS:
return text
logging.warning(
"Attachment %s truncated to %d of %d characters", label, MAX_INLINE_TEXT_CHARS, len(text)
)
return (
text[:MAX_INLINE_TEXT_CHARS]
+ f"\n\n[... truncated: {len(text) - MAX_INLINE_TEXT_CHARS} more characters not shown ...]"
)
def resolve_attachment_model_name(agent: Any) -> str:
"""Best-effort model id for capability routing.
Mirrors the resolution already used by the agent's other capability probes
(``_model_supports_web_search`` and friends).
"""
instance = getattr(agent, "llm_instance", None)
model = getattr(instance, "model", None) if instance else None
if isinstance(model, str) and model:
return model
llm = getattr(agent, "llm", None)
if isinstance(llm, str) and llm:
return llm
if isinstance(llm, dict):
model = llm.get("model")
if isinstance(model, str) and model:
return model
return ""
# --- Per-type builders -----------------------------------------------------
def _image_message_part(path: str, ext: str) -> Dict[str, Any]:
"""Encode an image exactly as the original implementation did."""
media_type = IMAGE_MEDIA_TYPES.get(ext, "image/jpeg")
encoded = _b64(_read_bytes(path))
# Canonical part first (shared vocabulary with tools/base.py), then the
# provider-facing shape, so there is one definition of "an image part".
canonical = image_part(encoded, mime=media_type, name=os.path.basename(path))
logging.debug(
"Successfully encoded image attachment: %s (%d bytes base64)", path, len(encoded)
)
return {
"type": "image_url",
"image_url": {"url": f"data:{canonical['mime']};base64,{canonical['data']}"},
}
def _pdf_parts(path: str, model_name: str) -> List[Dict[str, Any]]:
name = os.path.basename(path)
if _capability("pdf", model_name):
canonical = file_part(
_b64(_read_bytes(path)), mime="application/pdf", name=name
)
return [{
"type": "file",
"file": {
"filename": canonical["name"],
"file_data": f"data:{canonical['mime']};base64,{canonical['data']}",
},
}]
text = _extract_pdf_text(path)
if text:
logging.warning(
"Model %r cannot accept PDF attachments natively; sending locally "
"extracted text of %s instead. Use a PDF-capable model (e.g. an "
"Anthropic Claude or OpenAI gpt-4o/4.1 model) to send the document itself.",
model_name or "<unknown>", path,
)
body = _truncate(text, name)
return [text_part(
f"[Attachment: {name} - PDF text extracted locally because model "
f"{model_name or '<unknown>'!r} cannot accept PDF files directly; "
f"layout, images and tables are lost]\n{body}"
)]
return _degrade(
f"{path}: model {model_name or '<unknown>'!r} cannot accept PDFs natively and the "
f"PDF's text could not be extracted (install 'pypdf', or use a PDF-capable model)",
f"[Attachment omitted: {name} - the PDF could not be sent to model "
f"{model_name or '<unknown>'!r} and its text could not be extracted locally. "
f"Answer without it and say so.]",
)
def _audio_parts(path: str, ext: str, model_name: str) -> List[Dict[str, Any]]:
name = os.path.basename(path)
if _capability("audio", model_name):
canonical = file_part(
_b64(_read_bytes(path)),
mime=f"audio/{AUDIO_FORMATS.get(ext, 'mpeg')}",
name=name,
)
return [{
"type": "input_audio",
"input_audio": {
"data": canonical["data"],
"format": AUDIO_FORMATS.get(ext, "mp3"),
},
}]
return _degrade(
f"{path}: model {model_name or '<unknown>'!r} cannot accept audio input "
f"(use an audio-capable model such as gpt-4o-audio-preview or a Gemini model, "
f"or transcribe the file first)",
f"[Attachment omitted: {name} - audio was not sent because model "
f"{model_name or '<unknown>'!r} cannot accept audio input. Answer without "
f"it and say so.]",
)
def _text_parts(path: str) -> List[Dict[str, Any]]:
name = os.path.basename(path)
try:
with open(path, "r", encoding="utf-8", errors="replace") as fh:
content = fh.read()
except OSError as exc:
return _fail(f"{path}: could not be read ({exc})")
return [text_part(f"[Attachment: {name}]\n{_truncate(content, name)}")]
def _capability(kind: str, model_name: str) -> bool:
"""Capability probe, isolated so a broken/absent litellm never crashes a run."""
try:
from ..llm.model_capabilities import supports_audio_input, supports_pdf_input
except Exception: # noqa: BLE001
return False
try:
if kind == "pdf":
return bool(supports_pdf_input(model_name))
if kind == "audio":
return bool(supports_audio_input(model_name))
except Exception as exc: # noqa: BLE001
logging.debug("Capability probe %s/%s failed: %s", kind, model_name, exc)
return False
# --- Entry point -----------------------------------------------------------
def build_attachment_parts(attachment: Any, model_name: str = "") -> List[Dict[str, Any]]:
"""Turn one attachment into zero-or-more model content parts.
Never returns an empty list for an input it could not handle: it either
raises :class:`AttachmentError` or returns a visible marker part.
"""
# Already-structured content parts pass through untouched.
if isinstance(attachment, dict):
if "type" not in attachment:
logging.warning(
"Attachment dict has no 'type' key and may be ignored by the provider: %r",
attachment,
)
return [attachment]
if isinstance(attachment, os.PathLike):
attachment = os.fspath(attachment)
if not isinstance(attachment, str):
raise AttachmentError(
f"Unsupported attachment type {type(attachment).__name__!r}: expected a file "
f"path, an http(s)/data URL, or a content-part dict, got {attachment!r}"
)
if not attachment.strip():
raise AttachmentError("Empty attachment path")
if attachment.startswith(("http://", "https://", "data:")):
return _remote_parts(attachment, model_name)
if os.path.isdir(attachment):
return _fail(f"{attachment}: is a directory, not a file")
if not os.path.isfile(attachment):
return _fail(
f"{attachment}: no such file (attachment paths are resolved relative to the "
f"current working directory {os.getcwd()!r})"
)
ext = os.path.splitext(attachment)[1].lower()
name = os.path.basename(attachment)
try:
if ext in IMAGE_EXTENSIONS:
return [_image_message_part(attachment, ext)]
if ext in PDF_EXTENSIONS:
return _pdf_parts(attachment, model_name)
if ext in AUDIO_EXTENSIONS:
return _audio_parts(attachment, ext, model_name)
if ext in TEXT_EXTENSIONS:
return _text_parts(attachment)
except AttachmentError:
raise
except OSError as exc:
return _fail(f"{attachment}: could not be read ({exc})")
if ext in VIDEO_EXTENSIONS:
return _degrade(
f"{attachment}: video attachments are not supported on the chat-completions "
f"path (extract frames as images, or a transcript as text, first)",
f"[Attachment omitted: {name} - video attachments are not supported. "
f"Answer without it and say so.]",
)
# Unknown extension. Rather than guess at a binary, try it as text when it
# decodes cleanly as UTF-8; otherwise say plainly that it was not sent.
sample_text = _maybe_text_file(attachment)
if sample_text is not None:
logging.warning(
"Attachment %s has an unrecognised extension %r; inlining it as UTF-8 text.",
attachment, ext or "(none)",
)
return [text_part(f"[Attachment: {name} (unrecognised type, sent as text)]\n"
f"{_truncate(sample_text, name)}")]
return _degrade(
f"{attachment}: unsupported attachment type {ext or '(no extension)'!r}. Supported: "
f"images {sorted(IMAGE_EXTENSIONS)}, PDF, audio {sorted(AUDIO_EXTENSIONS)}, and "
f"text-like files. Convert the file, or pass its text instead.",
f"[Attachment omitted: {name} - unsupported file type "
f"{ext or '(no extension)'!r}. Answer without it and say so.]",
)
def _maybe_text_file(path: str) -> Optional[str]:
"""Return the file's text if it is valid UTF-8 and not obviously binary."""
try:
raw = _read_bytes(path)
except OSError:
return None
if b"\x00" in raw[:8192]:
return None
try:
return raw.decode("utf-8")
except UnicodeDecodeError:
return None
def _remote_parts(url: str, model_name: str) -> List[Dict[str, Any]]:
"""Route an http(s) URL or data URI.
Images (and anything without a recognisable non-image extension) keep the
original behaviour: a straight ``image_url`` part. A URL that plainly names
a non-image document is called out instead of being passed off as an image.
"""
if url.startswith("data:"):
mime = url[5:].split(";", 1)[0].split(",", 1)[0].lower()
if mime and not mime.startswith("image/"):
return _degrade(
f"data URI with media type {mime!r} is not supported as an attachment; "
f"only image data URIs are passed through",
f"[Attachment omitted: a {mime} data URI was not sent to the model. "
f"Answer without it and say so.]",
)
return [{"type": "image_url", "image_url": {"url": url}}]
path = url.split("?", 1)[0].split("#", 1)[0]
ext = os.path.splitext(path)[1].lower()
if ext and ext not in IMAGE_EXTENSIONS and (
ext in PDF_EXTENSIONS or ext in AUDIO_EXTENSIONS
or ext in VIDEO_EXTENSIONS or ext in TEXT_EXTENSIONS
):
return _degrade(
f"{url}: remote {ext} attachments are not fetched (this function performs no "
f"network I/O); download the file and pass the local path instead",
f"[Attachment omitted: {url} - remote {ext} files are not downloaded "
f"automatically. Answer without it and say so.]",
)
return [{"type": "image_url", "image_url": {"url": url}}]
File diff suppressed because it is too large. Load diff
@@ -31,66 +31,17 @@ from praisonaiagents._logging import get_logger
logger = get_logger(__name__)
class _DynamicLimiter:
"""Resizable counting limiter: capacity can change with holders outstanding.
Unlike swapping a fresh threading.Semaphore on every retune (which lets
holders of the old primitive and the release() path operate on different
objects), this keeps one long-lived object per agent name and mutates its
capacity in place. Every acquirer and every release() therefore always
operate on the same shared state, so a retune takes effect immediately and
the configured cap can never be silently exceeded. Loop-neutral: uses a
threading.Condition so it is a true global cap across event loops/threads.
"""
def __init__(self, limit: int):
self._limit = limit
self._held = 0
self._cond = threading.Condition()
def set_limit(self, limit: int) -> None:
with self._cond:
self._limit = limit
self._cond.notify_all()
def acquire(self, blocking: bool = True) -> bool:
with self._cond:
while self._limit > 0 and self._held >= self._limit:
if not blocking:
return False
self._cond.wait(timeout=0.05)
self._held += 1
return True
def release(self) -> None:
with self._cond:
self._held = max(0, self._held - 1)
self._cond.notify_all()
def has_holders(self) -> bool:
with self._cond:
return self._held > 0
class ConcurrencyRegistry:
"""Registry for per-agent concurrency limits.
Thread-safe. Each agent name maps to a loop-neutral, resizable limiter, so
the limit is a true global cap across every event loop and thread and a
retune takes effect immediately for in-flight holders.
Thread-safe. Each agent name maps to an asyncio.Semaphore.
Limit of 0 means unlimited (no throttling).
"""
def __init__(self, default_limit: int = 0):
self._default_limit = default_limit
self._limits: Dict[str, int] = {}
# One long-lived, loop-neutral _DynamicLimiter per agent. Its capacity is
# mutated in place on retune (never swapped for a fresh object), so every
# acquirer and every release() always share the same state and the
# configured cap can never be silently exceeded. Loop-neutral means the
# per-agent limit is a true global cap under multi-loop / multi-thread
# deployments; async callers poll without blocking their loop.
self._limiters: Dict[str, _DynamicLimiter] = {}
self._semaphores: Dict[str, asyncio.Semaphore] = {}
self._lock = threading.Lock()
def set_limit(self, agent_name: str, max_concurrent: int) -> None:
@@ -102,11 +53,8 @@ class ConcurrencyRegistry:
"""
with self._lock:
self._limits[agent_name] = max_concurrent
# Mutate the existing limiter in place so the retune takes effect
# immediately for in-flight holders without ever swapping the object.
limiter = self._limiters.get(agent_name)
if limiter is not None:
limiter.set_limit(max_concurrent)
# Reset semaphore so next acquire creates a fresh one
self._semaphores.pop(agent_name, None)
def get_limit(self, agent_name: str) -> int:
"""Get concurrency limit for an agent."""
@@ -114,78 +62,61 @@ class ConcurrencyRegistry:
return self._limits.get(agent_name, self._default_limit)
def remove_limit(self, agent_name: str) -> None:
"""Remove concurrency limit for an agent (reverts to default).
The limiter object is kept alive while any permit is still held, so
in-flight acquire()/release() pairs keep operating on the same shared
state; dropping it mid-flight would strand those permits and let a
later set_limit() start from a fresh, empty count and admit work beyond
the configured cap. Once no permits are outstanding it is safe to drop.
"""
"""Remove concurrency limit for an agent (reverts to default)."""
with self._lock:
self._limits.pop(agent_name, None)
# Retune the surviving limiter to unlimited so it stops blocking
# while remaining the single accounting object for its holders.
limiter = self._limiters.get(agent_name)
if limiter is None:
return
limiter.set_limit(0)
if not limiter.has_holders():
self._limiters.pop(agent_name, None)
self._semaphores.pop(agent_name, None)
def _get_limiter(self, agent_name: str) -> Optional[_DynamicLimiter]:
"""Get or create the loop-neutral limiter for an agent.
Returns None only when the agent has never been given a limit (pure
unlimited fast path). Once a limiter exists it is always returned — even
while unlimited (limit 0) — so acquire() and release() stay symmetric
across a mid-flight retune to/from unlimited and the count can never be
corrupted. The same _DynamicLimiter is shared across every event loop
and thread, so a configured limit is a true global cap.
"""
def _get_semaphore(self, agent_name: str) -> Optional[asyncio.Semaphore]:
"""Get or create semaphore for agent. Returns None if unlimited."""
with self._lock:
limit = self._limits.get(agent_name, self._default_limit)
limiter = self._limiters.get(agent_name)
if limiter is None:
if limit <= 0:
return None
limiter = _DynamicLimiter(limit)
self._limiters[agent_name] = limiter
return limiter
if limit <= 0:
return None
if agent_name not in self._semaphores:
self._semaphores[agent_name] = asyncio.Semaphore(limit)
return self._semaphores[agent_name]
async def acquire(self, agent_name: str) -> None:
"""Acquire concurrency slot for agent. No-op if unlimited.
Waits on the loop-neutral limiter in short, cancellable polls so the
running event loop is never blocked while other tasks hold permits, and
a cancelled/timed-out await never leaves a thread blocked on acquire().
"""
limiter = self._get_limiter(agent_name)
if limiter is None:
return
while True:
if limiter.acquire(blocking=False):
return
# Yield to the loop; on cancellation this raises and no permit leaks.
await asyncio.sleep(0.005)
"""Acquire concurrency slot for agent. No-op if unlimited."""
sem = self._get_semaphore(agent_name)
if sem is not None:
await sem.acquire()
def acquire_sync(self, agent_name: str) -> None:
"""Synchronous acquire — for non-async code paths.
Prefer async acquire() when possible. Blocks the calling thread until a
permit is available. Safe to call whether or not a loop is running in the
current thread, since the limiter is loop-neutral.
Prefer async acquire() when possible.
If called while an event loop is already running in the current thread,
this method raises RuntimeError to avoid deadlock.
"""
limiter = self._get_limiter(agent_name)
if limiter is not None:
limiter.acquire()
sem = self._get_semaphore(agent_name)
if sem is None:
return
try:
asyncio.get_running_loop()
except RuntimeError:
# No running loop — safe to create one
loop = asyncio.new_event_loop()
try:
loop.run_until_complete(sem.acquire())
finally:
loop.close()
else:
raise RuntimeError(
f"acquire_sync('{agent_name}') cannot be called with a running event loop; "
"use async acquire() in async contexts."
)
def release(self, agent_name: str) -> None:
"""Release concurrency slot for agent. No-op if unlimited."""
with self._lock:
limiter = self._limiters.get(agent_name)
if limiter is not None:
limiter.release()
sem = self._semaphores.get(agent_name)
if sem is not None:
try:
sem.release()
except ValueError:
pass # Already fully released
@asynccontextmanager
async def throttle(self, agent_name: str):
@@ -58,8 +58,8 @@ def save_cost_report(
}
filepath = COST_DIR / f"{safe_name}.json"
from ..utils.atomic_io import atomic_write_json
atomic_write_json(str(filepath), report, indent=2)
with open(filepath, "w") as f:
json.dump(report, f, indent=2)
logger.info(f"[costs] Saved cost report to {filepath}")
return str(filepath)
@@ -898,18 +898,14 @@ You are a professional research analyst. When conducting research:
if grounding_file_prompt:
create_params["grounding_file_prompt"] = grounding_file_prompt
interaction = await asyncio.to_thread(
self.gemini_client.interactions.create, **create_params
)
interaction = self.gemini_client.interactions.create(**create_params)
if self.verbose:
self.logger.debug(f"Gemini research started (async): {interaction.id}")
start_time = time.time()
while True:
interaction = await asyncio.to_thread(
self.gemini_client.interactions.get, interaction.id
)
interaction = self.gemini_client.interactions.get(interaction.id)
if interaction.status == "completed":
if self.verbose:
@@ -22,28 +22,49 @@ logger = logging.getLogger(__name__)
from typing import List, Optional, Any, Dict, Union, Generator, TYPE_CHECKING
# Shared HTTP launch state — the process-wide registry is defined in
# agent/server_registry.py and shared with PraisonAIAgents.launch() so a
# standalone Agent and a team launched on the same port cannot double-bind it or
# hide each other's endpoints.
from .server_registry import _server_registry
# Shared HTTP launch state (Agent.launch() multi-endpoint registration)
_server_lock = threading.Lock()
_server_started: Dict[int, bool] = {}
_registered_agents: Dict[int, Dict[str, str]] = {}
_shared_apps: Dict[int, Any] = {}
def cleanup_launch_registration(agent_id: str) -> None:
"""Remove launch() endpoints registered for ``agent_id`` from the shared
HTTP state that ``Agent.launch()`` actually populates.
``Agent.launch()`` reserves routes on the shared ``_server_registry``. This
tears those routes back down so a closed agent's endpoint stops accepting
requests and the request handler closure no longer keeps the Agent object
graph alive.
The endpoint-registry removal and the matching FastAPI route teardown are
performed together under the registry lock (see
``_AgentServerRegistry.teardown_routes_for``) so cleanup cannot race a
concurrent launch that reserves and registers a route on the same port.
``Agent.launch()`` writes routes into the module-level ``_registered_agents``
and ``_shared_apps`` dicts above. This tears those routes back down so a
closed agent's endpoint stops accepting requests and the request handler
closure no longer keeps the Agent object graph alive.
"""
_server_registry.teardown_routes_for(agent_id)
with _server_lock:
for port, paths in list(_registered_agents.items()):
stale_paths = [p for p, aid in paths.items() if aid == agent_id]
for p in stale_paths:
del paths[p]
app = _shared_apps.get(port)
if app is not None:
try:
# Only drop the agent-owned POST route. launch() always
# registers the handler via ``.post(path)``, so filtering
# on both path AND method preserves unrelated routes that
# share the path with a different verb (e.g. the built-in
# GET /health and GET /).
app.router.routes = [
r for r in app.router.routes
if not (
getattr(r, "path", None) == p
and "POST" in (getattr(r, "methods", None) or set())
)
]
# Invalidate cached OpenAPI schema so removed routes
# disappear from /openapi.json and /docs.
app.openapi_schema = None
except Exception:
pass
if not paths:
_registered_agents.pop(port, None)
if TYPE_CHECKING:
pass
@@ -200,12 +221,8 @@ class ExecutionMixin:
response = await self.achat(prompt, **kwargs)
response_str = str(response) if response else ""
# Auto-save session after chat. Offloaded to a worker thread so
# the synchronous FileLock/JSON read-modify-write never stalls
# the shared event loop (the session store is a process-wide
# singleton, so a blocking write here blocks every concurrent
# async agent task on the same loop).
await asyncio.to_thread(self._auto_save_session)
# Auto-save session after chat
self._auto_save_session()
# Wrap in AutonomyResult for consistent API
from .autonomy import AutonomyResult
@@ -280,33 +297,7 @@ class ExecutionMixin:
raise
except Exception as exc: # noqa: BLE001 - normalised into outcome
return RunOutcome.from_exception(exc)
return self._outcome_for_result(result)
def _outcome_for_result(self, result):
"""Map a normally-returned run result into a canonical RunOutcome.
A run that returned without raising is ``completed`` *unless* the core
recorded a provider block/refusal/truncation on ``last_stop_reason`` from
the LLM ``finish_reason``/refusal signal — in which case the specific,
actionable terminal reason (``content_filtered | refused |
length_truncated``) is surfaced instead of a silent empty ``completed``.
Any other stop reason (``completed``/``max_steps``/unknown) preserves the
existing ``completed`` semantics, so behaviour is unchanged on success.
"""
from .run_outcome import RunOutcome, PROVIDER_BLOCK_REASONS
output = str(result) if result is not None else None
# Read the recorded classification without letting a lookup problem mask a
# provider block as a successful ``completed``. Only an expected
# missing-state lookup (``AttributeError``) is treated as "no reason
# recorded"; anything else propagates rather than silently succeeding.
reason = None
try:
reason = getattr(self, "last_stop_reason", None)
except AttributeError:
reason = None
if reason in PROVIDER_BLOCK_REASONS:
return RunOutcome(reason=reason, output=output)
return RunOutcome.completed(output=output)
return RunOutcome.completed(output=str(result) if result is not None else None)
def run(self, prompt: str, **kwargs: Any) -> Optional[str]:
"""Execute agent silently and return structured result.
@@ -392,7 +383,7 @@ class ExecutionMixin:
result = executor()
except BaseException as exc: # noqa: BLE001 - normalised into outcome
return RunOutcome.from_exception(exc)
return self._outcome_for_result(result)
return RunOutcome.completed(output=str(result) if result is not None else None)
def _delegate_to_backend(self, prompt: str, **kwargs) -> Optional[str]:
"""Delegate execution to external managed backend (e.g., ManagedAgentIntegration).
@@ -476,8 +467,7 @@ class ExecutionMixin:
extra={"session_id": sid, "managed_session_id": msid},
exc_info=True,
)
# Offload the blocking session write off the event loop.
await asyncio.to_thread(self._auto_save_session)
self._auto_save_session()
return result
@@ -502,7 +492,7 @@ class ExecutionMixin:
with concurrent.futures.ThreadPoolExecutor() as executor:
future = executor.submit(run_async)
return future.result()
except RuntimeError:
# No event loop running, safe to use asyncio.run()
return asyncio.run(self.backend.execute(prompt, **kwargs))
@@ -786,32 +776,21 @@ Write the complete compiled report:"""
Args:
new_model: The new model name to switch to (e.g., "gpt-4o", "claude-3-sonnet")
"""
# Serialise against an in-flight sync model fallback (which also swaps
# self.llm / self._unified_dispatcher) so the two can't interleave.
with self._get_model_fallback_lock().sync():
# Store the new model name
self.llm = new_model
# Drop any cached dispatcher bound to the old model so the next
# chat()/achat() rebuilds against new_model. Without this, the
# OpenAI path keeps dispatching on the old model even though
# self.llm now reads the new name (mirrors _apply_default_llm).
if getattr(self, '_unified_dispatcher', None) is not None:
self._unified_dispatcher = None
# Recreate the LLM instance with the new model
try:
from ..llm.llm import LLM
self._llm_instance = LLM(
model=new_model,
base_url=self._openai_base_url,
api_key=self._openai_api_key,
)
self._using_custom_llm = True
self._wire_deferred_history_callback()
except ImportError:
# If LLM class not available, just update the model string
pass
# Store the new model name
self.llm = new_model
# Recreate the LLM instance with the new model
try:
from ..llm.llm import LLM
self._llm_instance = LLM(
model=new_model,
base_url=self._openai_base_url,
api_key=self._openai_api_key,
)
self._using_custom_llm = True
except ImportError:
# If LLM class not available, just update the model string
pass
def start(self, prompt: Optional[str] = None, **kwargs: Any) -> Union[str, Generator[str, None, None], None]:
"""Start the agent interactively with verbose output.
@@ -1405,27 +1384,10 @@ Write the complete compiled report:"""
)
if _verdict.get("stuck"):
if _verdict.get("level") == "critical":
# Async parity with the sync path in tool_execution.py:
# route the critical verdict through the unified approval
# pipeline (human override / per-project policy) instead
# of an unconditional hard stop. Use the native async
# helper so an async-only / event-loop-bound approval
# backend runs on *this* loop via ``approve_async``,
# preserving loop-bound resources — the sync bridge would
# otherwise run the backend on a throwaway worker-thread
# loop and turn its failure into a spurious denial.
_approved = await self._doom_loop_approved_async(
function_name, arguments, _verdict,
)
if _approved:
_loop_detection.reset_matching_history(
_ld_history, function_name, arguments
)
else:
return {
"error": _verdict.get("message", "loop detected"),
"loop_blocked": True,
}
return {
"error": _verdict.get("message", "loop detected"),
"loop_blocked": True,
}
elif not getattr(self, '_loop_warned_this_turn', False):
self._loop_warned_this_turn = True
self._pending_self_correction = (
@@ -1561,46 +1523,14 @@ Write the complete compiled report:"""
),
)
# Bound the worker thread's wait on the async tool by the same per-agent
# tool timeout the direct path applies (ToolConfig.timeout, seconds). The
# inner coroutine already wraps itself in asyncio.wait_for, but the worker
# blocking on future.result() has no bound of its own: if the inner path
# hangs (or no timeout is configured) the middleware worker would block a
# thread-pool worker indefinitely. Give it a slightly larger grace bound so
# the inner wait_for surfaces its structured timeout first when configured.
tool_timeout = getattr(self, '_tool_timeout', None)
worker_timeout = (tool_timeout + 1.0) if tool_timeout and tool_timeout > 0 else None
def _final_handler(req):
import concurrent.futures
future = asyncio.run_coroutine_threadsafe(
self._execute_tool_async_with_retry(
req.tool_name, req.arguments, tool_call_id, tools_override
),
loop,
)
try:
result = future.result(timeout=worker_timeout)
except concurrent.futures.TimeoutError:
# The scheduled coroutine did not finish within the bound. Request
# cancellation on the running loop so it stops rather than leaking,
# and surface the same structured timeout error the direct async
# path returns (retryable=False: an uncancellable side effect must
# not be re-run).
future.cancel()
logger.warning(
"Middleware async tool '%s' timed out after %ss (agent=%s, run_id=%s, tool_call_id=%s)",
req.tool_name,
tool_timeout,
self.name,
getattr(self, '_current_run_id', 'unknown'),
tool_call_id,
)
result = {
"error": f"Tool timed out after {tool_timeout}s",
"timeout": True,
"_praison_retryable": False,
}
result = future.result()
return ToolResponse(tool_name=req.tool_name, result=result)
def _run_chain():
@@ -1638,18 +1568,7 @@ Write the complete compiled report:"""
result.get("_praison_retryable") is False):
result.pop("_praison_retryable", None)
return result
# The body already ran and may have completed its side effect
# before failing. Honour an explicit restart_safe=False /
# idempotent=False declaration, exactly as the sync loops do
# (tool_execution.py:884 and :2115). Without this the async
# path accepts the declaration and silently re-runs the tool
# up to max_attempts times -- charging a card three times for
# a tool the author marked "must never be silently re-executed".
if self._tool_declares_not_idempotent(function_name, tools_override):
result.pop("_praison_retryable", None)
return result
# Determine error type for retry policy
error_type = self._classify_error_type(result, last_exception)
@@ -1738,51 +1657,14 @@ Write the complete compiled report:"""
# Policy/guardrail gate (protocol-driven). Mirrors the sync path in
# _execute_tool_impl so async callers cannot bypass a PolicyEngine
# deny or a tool-call guardrail. A user-supplied guardrail/policy may
# do blocking work (an LLM moderation call, a DB/network lookup), so
# offload to a worker thread rather than run it inline and stall the
# event loop for every other coroutine sharing it.
# deny or a tool-call guardrail. The check is pure/sync (no awaits).
check = getattr(self, "_check_tool_policy_and_guardrails", None)
if check is not None:
# ``tools_override`` is threaded through so a run-scoped tool
# list cannot bypass the per-tool guardrails its tools declare.
policy_result = await asyncio.to_thread(
check, function_name, arguments, tools_override
)
policy_result = check(function_name, arguments)
if isinstance(policy_result, dict):
return policy_result # Error dict
_, arguments = policy_result
# MCP tools first — parity with the sync path (_execute_tool_impl).
# Without this an MCP-backed tool call hard-fails via achat()/astart().
# Only consult MCP when searching the agent's own tools (no override),
# matching the sync path which resolves MCP against self.tools.
if tools_override is None:
resolve_mcp = getattr(self, "_resolve_mcp_tool_result", None)
if resolve_mcp is not None:
found, mcp_result = resolve_mcp(function_name, arguments)
if found:
if inspect.isawaitable(mcp_result):
mcp_result = await mcp_result
# Normalize MCP transport/timeout failures into a native
# error dict — parity with the sync path so an async MCP
# timeout classifies as a retryable failure instead of
# being handed to the model as a bare "Error: ..." string
# that looks like a successful result.
normalize_mcp = getattr(self, "_normalize_mcp_result", None)
if normalize_mcp is not None:
mcp_result = normalize_mcp(mcp_result)
# Tool-result guardrail gate — the native path applies this
# below, but the MCP branch returns early, so gate here too
# or successful MCP output would bypass validation entirely.
# Offloaded to a thread: a user guardrail may block on I/O.
apply_result_guardrails = getattr(self, "_apply_tool_result_guardrails", None)
if apply_result_guardrails is not None:
mcp_result = await asyncio.to_thread(
apply_result_guardrails, function_name, mcp_result
)
return mcp_result
# Try to find the function in the override tools list first, then agent's tools list.
# Resolve by BaseTool/FunctionTool ``.name`` (instances like BrowserBaseTool or
# aliased decorated tools), plain callable ``__name__``, or class name so async
@@ -1790,10 +1672,7 @@ Write the complete compiled report:"""
func = None
tools_to_search = tools_override if tools_override is not None else self.tools
from ..tools.base import BaseTool
plugin_owners = getattr(self, "_plugin_tool_owners", None)
for tool in tools_to_search:
if plugin_owners and not self._is_plugin_tool_active(tool):
continue
if isinstance(tool, BaseTool) and getattr(tool, 'name', None) == function_name:
func = tool
break
@@ -1804,51 +1683,11 @@ Write the complete compiled report:"""
(inspect.isclass(tool) and tool.__name__ == function_name):
func = tool
break
# Name self-repair — parity with the sync path. A slightly hallucinated
# tool name (e.g. 'WebSearch' for 'web_search') is re-matched instead of
# hard-failing. Only over the agent's own active tools (no override).
if func is None and tools_override is None:
repair = getattr(self, "_self_repair_tool_name", None)
if repair is not None:
func = repair(function_name)
if func is None:
# Corrective, model-readable message with the available tools and a
# closest-match hint, mirroring the sync path so the model can retry.
available = None
if hasattr(self, "_available_active_tool_names"):
try:
available = self._available_active_tool_names()
except Exception:
available = None
if available is not None:
suggestion = None
try:
import difflib
near = difflib.get_close_matches(function_name, available, n=1, cutoff=0.5)
suggestion = near[0] if near else None
except Exception:
pass
hint = f" Did you mean '{suggestion}'?" if suggestion else ""
error_msg = f"Tool '{function_name}' not found.{hint} Available tools: {available}"
logging.error(error_msg)
return {"error": error_msg, "available_tools": available}
logging.error(f"Function {function_name} not found in tools")
return {"error": f"Function {function_name} not found in tools"}
# Circuit breaker (pre-execution) — parity with the sync path
# (_execute_tool_with_circuit_breaker_impl). Without this the async
# tool path never engages the per-agent breaker, so a persistently
# failing external tool is hammered indefinitely via achat()/astart()
# and the model never receives the ``circuit_open`` signal the async
# retry loop already checks for. The helpers are pure/sync.
breaker_precheck = getattr(self, '_circuit_breaker_precheck', None)
if breaker_precheck is not None:
open_result = breaker_precheck(function_name)
if open_result is not None:
return open_result
# Loop guard (pre-execution) — parity with the sync path in
# tool_execution.py. The async path previously had no loop-guard or
# doom-loop protection, so a repeatedly-failing tool could be hammered
@@ -1888,21 +1727,6 @@ Write the complete compiled report:"""
from ..streaming.events import tool_progress_channel
# breaker.acall() records the invocation outcome itself. Both record
# sites below then recorded the same failure a SECOND time -- once
# off the returned error dict, once in the raised-exception handler
# -- so every async tool failure counted twice and the breaker
# opened after ceil(threshold/2) calls (3 instead of the configured
# 5), out of parity with the sync path. This flag marks that the
# breaker already owns the outcome; it stays False when
# asyncio.wait_for times out, since the breaker never got a result.
#
# Declared outside the try: the except handler below reads it, and
# roughly seventy lines run between the try and the breaker setup.
# An exception in that window would otherwise raise NameError here
# and mask the original failure.
breaker_saw_outcome = {"done": False}
try:
# BaseTool instances (plugin system, e.g. BrowserBaseTool) are not
# directly callable — dispatch to their .run() method like the sync path.
@@ -1927,134 +1751,22 @@ Write the complete compiled report:"""
call_arguments = dict(arguments)
call_arguments["idempotency_key"] = durable_key
# Establish the injection context (Injected[T] params, including
# the cooperative cancel_event) around dispatch so the async path
# matches the sync execute_tool path. Without this, a long-running
# tool (e.g. shell) executed via achat()/astart() never observes an
# interrupt and runs until its own timeout. Built lazily and reused
# for both the coroutine and executor branches.
from ..tools.injected import with_injection_context
_inject_state = None
if hasattr(self, "_build_agent_state"):
try:
_inject_state = self._build_agent_state()
except Exception:
_inject_state = None
async def _invoke():
# Set the tool-progress channel BEFORE dispatch so the sink
# propagates into the executor thread via contextvars, mirroring
# the sync execute_tool path.
if inspect.iscoroutinefunction(call_target):
logging.debug(f"Executing async function: {function_name}")
if _inject_state is not None:
with with_injection_context(_inject_state), tool_progress_channel(_progress_sink):
return await call_target(**call_arguments)
with tool_progress_channel(_progress_sink):
return await call_target(**call_arguments)
logging.debug(f"Executing sync function in executor: {function_name}")
loop = asyncio.get_running_loop()
from ..trace.context_events import copy_context_to_callable
# copy_context_to_callable snapshots the CURRENT context (incl.
# the injection contextvar) into the executor thread, so setting
# it here propagates cancel_event to the sync tool body too.
if _inject_state is not None:
with with_injection_context(_inject_state), tool_progress_channel(_progress_sink):
return await loop.run_in_executor(
None, copy_context_to_callable(lambda: call_target(**call_arguments))
)
with tool_progress_channel(_progress_sink):
return await loop.run_in_executor(
None, copy_context_to_callable(lambda: call_target(**call_arguments))
)
# Circuit-breaker parity with the sync path (tool_execution.py).
# The async tool path previously had no breaker, so a repeatedly
# failing tool could be hammered every turn via achat()/async
# workflows. Wrap the invocation through the same per-agent/per-tool
# breaker (CircuitBreaker.acall is event-loop safe) so repeated
# failures OPEN the circuit and short-circuit further calls. A
# CircuitBreakerException is surfaced as an error dict carrying
# circuit_open=True, which the retry loop in
# _execute_tool_async_with_retry already treats as terminal.
breaker = None
# Sentinel exception type so the `except` clause below is always a
# valid type even when the circuit_breaker module is unavailable
# (a never-raised local class never matches a real exception).
class _CircuitBreakerException(Exception):
pass
try:
from ..tools.circuit_breaker import (
get_circuit_breaker,
CircuitBreakerConfig,
CircuitBreakerException as _CircuitBreakerException,
)
breaker_name = f"tool_{id(self)}_{function_name}"
breaker = get_circuit_breaker(
breaker_name,
CircuitBreakerConfig(
failure_threshold=5,
recovery_timeout=60.0,
timeout=30.0,
graceful_degradation=True,
),
)
if hasattr(self, "_register_breaker_finalizer"):
self._register_breaker_finalizer(breaker_name)
except ImportError:
# Circuit breaker not available - fall back to direct invocation.
logging.debug("Circuit breaker not available on async path, executing directly")
# Sentinel used to register an error-dict result as a breaker
# failure without losing the dict, mirroring the sync path's
# _ToolFailure wrapper (tool_execution.py). Approval/permission/
# policy/guardrail denials are NOT treated as breaker failures.
class _ToolFailure(Exception):
def __init__(self, error_dict):
self.error_dict = error_dict
super().__init__(error_dict.get("error", "Tool execution failed"))
async def _invoke_for_breaker():
r = await _invoke()
if isinstance(r, dict) and r.get("error") and \
not r.get("approval_denied") and \
not r.get("permission_denied") and \
not r.get("approval_error") and \
not r.get("policy_denied") and \
not r.get("guardrail_denied"):
raise _ToolFailure(r)
return r
async def _invoke_guarded():
if breaker is None:
return await _invoke()
# Set before the await: acall records an outcome however it
# exits (returning, raising _ToolFailure, or letting a raw
# tool exception through). The only exit that records
# nothing is _CircuitBreakerException, and that path returns
# _circuit_open_result() without reaching either record site.
breaker_saw_outcome["done"] = True
try:
return await breaker.acall(_invoke_for_breaker)
except _ToolFailure as tf:
# Failure was counted by the breaker; return the original dict.
return tf.error_dict
def _circuit_open_result():
# Record the rejection as a failure so repeated open-circuit
# rejections still feed the loop guard, then surface an error
# dict carrying circuit_open=True — the retry loop in
# _execute_tool_async_with_retry treats it as terminal.
if loop_guard is not None:
loop_guard.record(function_name, arguments, False, result=None)
return {
"error": f"Tool '{function_name}' circuit breaker open - too many recent failures",
"circuit_open": True,
"agent_name": getattr(self, "name", None),
"session_id": getattr(self, "_session_id", None),
"remediation": "Wait for recovery_timeout (60s) or investigate recent tool failures.",
}
# Apply the per-agent tool timeout (ToolConfig.timeout) so the async
# path matches the sync path in tool_execution.py. asyncio.wait_for
# cannot kill a stuck sync tool running in the executor (same caveat
@@ -2063,10 +1775,7 @@ Write the complete compiled report:"""
tool_timeout = getattr(self, '_tool_timeout', None)
if tool_timeout and tool_timeout > 0:
try:
result = await asyncio.wait_for(_invoke_guarded(), timeout=tool_timeout)
except _CircuitBreakerException as cbe:
logging.warning(f"Tool '{function_name}' circuit breaker open: {cbe}")
return _circuit_open_result()
result = await asyncio.wait_for(_invoke(), timeout=tool_timeout)
except asyncio.TimeoutError:
logging.warning(f"Tool {function_name} timed out after {tool_timeout}s")
# Mark as non-retryable: asyncio.wait_for cannot cancel a sync
@@ -2077,78 +1786,13 @@ Write the complete compiled report:"""
# Fall through (not return) so the loop guard records this
# timeout as a failure — repeated timeouts must accumulate
# toward the BLOCK/HALT thresholds like any other failure.
#
# A timeout cancels the awaited ``_invoke_guarded``; the
# cancellation surfaces inside ``breaker.acall`` as
# ``asyncio.CancelledError`` (a BaseException, not
# Exception), so ``acall`` never ran ``_on_failure`` for
# it. The fall-through breaker-record block below only
# runs when ``breaker is None``, so without recording it
# here a repeatedly timing-out tool would never open the
# circuit. Record the one failure directly on the breaker
# (the block below stays disabled, so it is counted once).
if breaker is not None:
try:
breaker._on_failure()
except Exception:
logging.debug(
"Failed to record tool timeout on circuit breaker",
exc_info=True,
)
result = {
"error": f"Tool timed out after {tool_timeout}s",
"timeout": True,
"_praison_retryable": False,
}
else:
try:
result = await _invoke_guarded()
except _CircuitBreakerException as cbe:
logging.warning(f"Tool '{function_name}' circuit breaker open: {cbe}")
return _circuit_open_result()
# Circuit breaker (post-execution) — record the outcome so
# repeated failures open the breaker, mirroring the sync path's
# breaker.call. Approval/permission/policy/guardrail denials are
# NOT counted as tool failures (same exclusions the sync wrapper
# applies in _execute_tool_with_circuit_breaker_impl), so a gated
# tool never trips the breaker.
#
# Only when the breaker wrapper did not already run. When
# ``breaker`` is set, ``breaker.acall`` above has already called
# _on_success/_on_failure for this invocation, and recording
# again counted every outcome twice -- halving the configured
# failure_threshold (a breaker set to 5 opened after 3) and, on
# the success side, closing a HALF_OPEN circuit in half the
# required successes.
breaker_record = (
getattr(self, '_circuit_breaker_record', None)
if breaker is None else None
)
if breaker_record is not None:
is_breaker_failure = (
isinstance(result, dict)
and result.get("error")
and not result.get("approval_denied")
and not result.get("permission_denied")
and not result.get("approval_error")
and not result.get("policy_denied")
and not result.get("guardrail_denied")
)
breaker_record(function_name, not is_breaker_failure)
# Tool-result guardrail gate (protocol-driven) — parity with the
# sync path in tool_execution.py. Runs on the raw result before it
# re-enters the LLM context so a guardrail can inspect or redact
# unsafe tool output. Fail-closed. Zero overhead when unset.
# Offloaded to a thread: a user guardrail may block on I/O (an LLM
# moderation call, a network lookup), which would otherwise stall
# the event loop for every other coroutine sharing it.
apply_result_guardrails = getattr(self, "_apply_tool_result_guardrails", None)
if apply_result_guardrails is not None:
result = await asyncio.to_thread(
apply_result_guardrails, function_name, result, tools_override
)
result = await _invoke()
# Loop guard (post-execution) — record the outcome and surface a
# block/halt decision back to the model on this same turn, mirroring
@@ -2179,22 +1823,6 @@ Write the complete compiled report:"""
except Exception as e:
logging.error(f"Error executing {function_name}: {str(e)}", exc_info=True)
# Circuit breaker (failure on raised exception) — a raised tool
# exception is a failure just like an error-dict result, and the
# sync path's ``breaker.call`` counts it. Approval/permission/
# policy/guardrail denials surface as error dicts (handled
# above), not raises, so this path only ever sees genuine tool
# failures.
#
# Again only when the breaker wrapper did not run: ``acall``
# records the failure and re-raises, so the exception arriving
# here has already been counted once.
breaker_record = (
getattr(self, '_circuit_breaker_record', None)
if breaker is None else None
)
if breaker_record is not None:
breaker_record(function_name, False)
# Record the failed invocation so repeated identical failures
# accumulate toward the loop-guard BLOCK/HALT thresholds — a raised
# tool exception is a failure just like an error-dict result on the
@@ -2271,13 +1899,18 @@ Write the complete compiled report:"""
NOTE: This implementation will be moved to wrapper layer in future version.
For now, it maintains backward compatibility while following lazy import patterns.
"""
global _server_started, _registered_agents, _shared_apps, _server_lock
from .launch_security import authorise_launch_request, resolve_launch_host
# Try to import FastAPI dependencies - lazy loading
try:
from fastapi import HTTPException, Request
import uvicorn
from fastapi import FastAPI, HTTPException, Request
from fastapi.responses import JSONResponse
from pydantic import BaseModel
import threading
import time
import asyncio
# Define the request model here since we need pydantic
@@ -2303,102 +1936,130 @@ Write the complete compiled report:"""
# process-wide launch token and retroactively 401 a running endpoint.
host = resolve_launch_host(host)
# Get or create the shared FastAPI app for this port (shared with
# PraisonAIAgents.launch via the same _server_registry singleton).
app, is_new_app = _server_registry.get_or_create_app(
port,
title=f"PraisonAI Agents API (Port {port})",
)
should_start = False
with _server_lock:
# Initialize port-specific collections if needed (once per port)
if port not in _registered_agents:
_registered_agents[port] = {}
if is_new_app:
# Add a root endpoint with a welcome message
@app.get("/")
async def root():
return {
"message": f"Welcome to PraisonAI Agents API on port {port}. See /docs for usage.",
"endpoints": _server_registry.list_routes(port)
}
# Add healthcheck endpoint
@app.get("/health")
async def healthcheck():
return {
"status": "ok",
"endpoints": _server_registry.list_routes(port)
}
# Normalize path to ensure it starts with /
if not path.startswith('/'):
path = f'/{path}'
# Atomically reserve the route; on collision the registry returns a
# de-duplicated path so multiple agents can share a single port.
path, original_path = _server_registry.reserve_route(port, path, self.agent_id)
if original_path is not None:
logging.warning(f"Path '{original_path}' is already registered on port {port}.")
print(f"⚠️ Warning: Path '{original_path}' is already registered on port {port}.")
print(f"🔄 Using '{path}' instead")
# Define the endpoint handler
@app.post(path)
async def handle_agent_query(request: Request, query_data: Optional[AgentQuery] = None):
if not authorise_launch_request(request):
raise HTTPException(status_code=401, detail="Unauthorized")
# Handle both direct JSON with query field and form data
if query_data is None:
try:
request_data = await request.json()
if "query" not in request_data:
raise HTTPException(status_code=400, detail="Missing 'query' field in request")
query = request_data["query"]
except Exception:
# Fallback to form data or query params
form_data = await request.form()
if "query" in form_data:
query = form_data["query"]
else:
raise HTTPException(status_code=400, detail="Missing 'query' field in request")
else:
query = query_data.query
try:
# Use async version if available, otherwise use sync version
if asyncio.iscoroutinefunction(self.chat):
response = await self.achat(query, task_name=None, task_description=None, task_id=None)
else:
# Run sync function in a thread to avoid blocking
loop = asyncio.get_running_loop()
response = await loop.run_in_executor(None, lambda p=query: self.chat(p))
return {"response": response}
except Exception as e:
logging.error(f"Error processing query: {str(e)}", exc_info=True)
return JSONResponse(
status_code=500,
content={"error": f"Error processing query: {str(e)}"}
# Initialize shared FastAPI app if not already created for this port
if _shared_apps.get(port) is None:
_shared_apps[port] = FastAPI(
title=f"PraisonAI Agents API (Port {port})",
description="API for interacting with PraisonAI Agents"
)
# Invalidate the cached OpenAPI schema so routes registered by later
# shared-port launch() calls still show up in /openapi.json and /docs.
# FastAPI caches app.openapi_schema on first access and does not
# regenerate it when new routes are added afterwards.
app.openapi_schema = None
# Add a root endpoint with a welcome message
@_shared_apps[port].get("/")
async def root():
return {
"message": f"Welcome to PraisonAI Agents API on port {port}. See /docs for usage.",
"endpoints": list(_registered_agents[port].keys())
}
print(f"🚀 Agent '{self.name}' available at http://{host}:{port}")
# Add healthcheck endpoint
@_shared_apps[port].get("/health")
async def healthcheck():
return {
"status": "ok",
"endpoints": list(_registered_agents[port].keys())
}
# Start the shared server for this port if it is not already running.
# start_server_if_needed atomically checks-and-marks the port and blocks
# on the registry's readiness Event (configurable via
# PRAISONAI_SERVER_READY_TIMEOUT) instead of a heuristic sleep, matching
# PraisonAIAgents.launch().
started = _server_registry.start_server_if_needed(
port, host, log_level="debug" if debug else "info"
)
endpoints = _server_registry.list_routes(port)
if started:
print(f"✅ FastAPI server started at http://{host}:{port}")
print(f"📚 API documentation available at http://{host}:{port}/docs")
print(f"🔌 Available endpoints on port {port}: {', '.join(endpoints)}")
# The path registration below must run on EVERY call, not just when the
# port is new, so multiple agents can share a single port.
# Normalize path to ensure it starts with /
if not path.startswith('/'):
path = f'/{path}'
# Check if path is already registered for this port
if path in _registered_agents[port]:
logging.warning(f"Path '{path}' is already registered on port {port}. Please use a different path.")
print(f"⚠️ Warning: Path '{path}' is already registered on port {port}.")
# Use a modified path to avoid conflicts
original_path = path
path = f"{path}_{self.agent_id[:6]}"
logging.warning(f"Using '{path}' instead of '{original_path}'")
print(f"🔄 Using '{path}' instead")
# Register the agent to this path
_registered_agents[port][path] = self.agent_id
# Define the endpoint handler
@_shared_apps[port].post(path)
async def handle_agent_query(request: Request, query_data: Optional[AgentQuery] = None):
if not authorise_launch_request(request):
raise HTTPException(status_code=401, detail="Unauthorized")
# Handle both direct JSON with query field and form data
if query_data is None:
try:
request_data = await request.json()
if "query" not in request_data:
raise HTTPException(status_code=400, detail="Missing 'query' field in request")
query = request_data["query"]
except Exception:
# Fallback to form data or query params
form_data = await request.form()
if "query" in form_data:
query = form_data["query"]
else:
raise HTTPException(status_code=400, detail="Missing 'query' field in request")
else:
query = query_data.query
try:
# Use async version if available, otherwise use sync version
if asyncio.iscoroutinefunction(self.chat):
response = await self.achat(query, task_name=None, task_description=None, task_id=None)
else:
# Run sync function in a thread to avoid blocking
loop = asyncio.get_running_loop()
response = await loop.run_in_executor(None, lambda p=query: self.chat(p))
return {"response": response}
except Exception as e:
logging.error(f"Error processing query: {str(e)}", exc_info=True)
return JSONResponse(
status_code=500,
content={"error": f"Error processing query: {str(e)}"}
)
# Invalidate the cached OpenAPI schema so routes registered by later
# shared-port launch() calls still show up in /openapi.json and /docs.
# FastAPI caches app.openapi_schema on first access and does not
# regenerate it when new routes are added afterwards.
_shared_apps[port].openapi_schema = None
print(f"🚀 Agent '{self.name}' available at http://{host}:{port}")
# Check and mark server as started atomically to prevent race conditions
should_start = not _server_started.get(port, False)
if should_start:
_server_started[port] = True
# Server start/wait outside the lock to avoid holding it during sleep
if should_start:
# Start the server in a separate thread
def run_server():
try:
print(f"✅ FastAPI server started at http://{host}:{port}")
print(f"📚 API documentation available at http://{host}:{port}/docs")
print(f"🔌 Available endpoints: {', '.join(list(_registered_agents[port].keys()))}")
uvicorn.run(_shared_apps[port], host=host, port=port, log_level="debug" if debug else "info")
except Exception as e:
logging.error(f"Error starting server: {str(e)}", exc_info=True)
print(f"❌ Error starting server: {str(e)}")
# Run server in a background thread
server_thread = threading.Thread(target=run_server, daemon=True)
server_thread.start()
# Wait for a moment to allow the server to start and register endpoints
self._safe_sleep(0.5)
else:
# If server is already running, wait a moment to make sure the endpoint is registered
self._safe_sleep(0.1)
print(f"🔌 Available endpoints on port {port}: {', '.join(list(_registered_agents[port].keys()))}")
# Get the stack frame to check if this is the last launch() call in the script
import inspect
@@ -14,7 +14,7 @@ from typing import Optional, Any, Callable, Dict, List, Union, TYPE_CHECKING, Li
from dataclasses import dataclass, field
from enum import Enum
import inspect
from contextlib import contextmanager, asynccontextmanager
from contextlib import contextmanager
from praisonaiagents._logging import get_logger
import asyncio
import contextvars
@@ -211,44 +211,6 @@ def _clear_handoff_chain() -> None:
"""Clear the handoff chain."""
_handoff_chain_var.set([])
# Serializes lazy creation of each target agent's ``_handoff_seed_lock`` so two
# threads that make the first concurrent handoff to the same target observe the
# same lock object (double-checked locking) instead of each minting — and then
# seeding under — its own, which would defeat the per-target serialization.
_HANDOFF_SEED_LOCK_INIT_GUARD = threading.Lock()
def _get_handoff_seed_lock(agent: 'Agent') -> 'DualLock':
"""Return a per-target-agent lock serializing handoff history seeding.
Concurrent handoffs (e.g. ``parallel_handoffs``) can target the *same*
agent object. ``_seed_target_history`` mutates that shared instance's
``chat_history`` in place, so overlapping seeds would interleave and leak
one caller's prior context into another's. Serializing per target agent
keeps each seeded chat call atomic without changing the public API.
Creation is serialized through a module-level guard (double-checked locking)
so racing first-handoffs to the same target can't each create a distinct
lock and seed concurrently.
"""
from .async_safety import DualLock
lock = getattr(agent, '_handoff_seed_lock', None)
if lock is None:
with _HANDOFF_SEED_LOCK_INIT_GUARD:
lock = getattr(agent, '_handoff_seed_lock', None)
if lock is None:
lock = DualLock()
try:
agent._handoff_seed_lock = lock
except Exception:
# Target can't hold the attribute (e.g. __slots__). Return a
# transient lock; correctness for that exotic case is no
# worse than before, and the common path is fully guarded.
pass
return lock
@dataclass
class HandoffInputData:
"""Data passed to a handoff target agent."""
@@ -508,31 +470,6 @@ class Handoff:
return value
return 'gpt-4o-mini'
def _apply_seed(self, prior_messages: Optional[List[Any]]):
"""Prepend ``prior_messages`` to the target's ``chat_history``.
Returns ``(seeded, original)`` where ``original`` is the list to restore
on exit and ``seeded`` indicates a restore is needed. Callers MUST hold
the per-agent seed lock around this + the chat call + ``_restore_seed``.
"""
existing = getattr(self.agent, 'chat_history', None)
if not prior_messages or not isinstance(existing, list):
return False, None
try:
prior = list(prior_messages)
except TypeError:
return False, None
original = existing
# Avoid re-seeding if the context is already at the head.
if existing[:len(prior)] != prior:
self.agent.chat_history = prior + existing
return True, original
def _restore_seed(self, seeded: bool, original: Optional[List[Any]]) -> None:
"""Restore the target's original ``chat_history`` after a seeded call."""
if seeded:
self.agent.chat_history = original
@contextmanager
def _seed_target_history(self, prior_messages: Optional[List[Any]]):
"""Temporarily seed the filtered handoff context onto the target agent.
@@ -546,45 +483,25 @@ class Handoff:
restored on exit. This keeps handoff context from leaking into later
handoffs or ordinary chats that reuse the same target agent, and stops the
target prompt from growing across sequential handoffs.
Because ``chat_history`` is shared mutable state on the target agent,
concurrent handoffs to the *same* target (e.g. via ``parallel_handoffs``)
would otherwise interleave and corrupt each other's context. The seed +
chat call are serialized per target agent via a ``DualLock`` so each
seeded turn stays atomic. This is the synchronous variant.
No shared mutable state is retained between agents.
"""
lock = _get_handoff_seed_lock(self.agent)
with lock.sync():
seeded, original = self._apply_seed(prior_messages)
try:
yield
finally:
self._restore_seed(seeded, original)
@asynccontextmanager
async def _seed_target_history_async(self, prior_messages: Optional[List[Any]]):
"""Async variant of :meth:`_seed_target_history`.
Uses the per-target-agent lock's async side so overlapping awaited
handoffs to the same agent serialize on the event loop instead of
blocking it, keeping each seeded ``achat`` turn atomic.
``DualLock`` backs ``sync()`` and ``async_lock()`` onto one shared mutex,
so ``async_lock()`` alone already excludes a concurrent *synchronous*
handoff on another thread. We still take the inner ``sync()`` so the
seed/restore reads as one explicit critical section; because
``async_lock()`` registers the event-loop thread as the mutex owner, that
nested ``sync()`` is treated as re-entrant on the same thread instead of
self-deadlocking against the mutex the async side already holds.
"""
lock = _get_handoff_seed_lock(self.agent)
async with lock.async_lock():
with lock.sync():
seeded, original = self._apply_seed(prior_messages)
try:
yield
finally:
self._restore_seed(seeded, original)
existing = getattr(self.agent, 'chat_history', None)
if not prior_messages or not isinstance(existing, list):
yield
return
try:
prior = list(prior_messages)
except TypeError:
yield
return
original = existing
try:
# Avoid re-seeding if the context is already at the head.
if existing[:len(prior)] != prior:
self.agent.chat_history = prior + existing
yield
finally:
self.agent.chat_history = original
def _execute_with_runtime_resolution(
self,
@@ -621,7 +538,7 @@ class Handoff:
target_model_ref,
_get_handoff_depth(),
)
async with self._seed_target_history_async(prior_messages):
with self._seed_target_history(prior_messages):
async_chat = getattr(self.agent, 'achat', None)
if callable(async_chat) and inspect.iscoroutinefunction(async_chat):
return await async_chat(prompt, tools=effective_tools)
@@ -3,7 +3,6 @@ ImageAgent - A specialized agent class for generating images using AI models.
This class extends the base Agent class to provide specific functionality for image generation,
including support for different image models, sizes, and quality settings.
"""
import asyncio
from typing import Optional, Any, Dict, Union, List
from ..agent.agent import Agent
from pydantic import BaseModel, Field
@@ -181,8 +180,8 @@ class ImageAgent(Agent):
logging.error(error_msg)
raise
async def agenerate_image(self, prompt: str, **kwargs) -> Dict[str, Any]:
"""Offload the synchronous generation path to keep the event loop responsive."""
return await asyncio.to_thread(self.generate_image, prompt, **kwargs)
"""Async wrapper for generate_image."""
return self.generate_image(prompt, **kwargs)
# Aliases for consistency with other agents
def generate(self, prompt: str, **kwargs) -> Dict[str, Any]:
@@ -191,7 +190,7 @@ class ImageAgent(Agent):
async def agenerate(self, prompt: str, **kwargs) -> Dict[str, Any]:
"""Async alias for generate_image()."""
return await self.agenerate_image(prompt, **kwargs)
return self.generate_image(prompt, **kwargs)
def chat(self, prompt: str, **kwargs) -> Dict[str, Any]:
"""Generate an image from the prompt."""
@@ -303,8 +302,8 @@ class ImageAgent(Agent):
size: Optional[str] = None,
**kwargs
) -> Dict[str, Any]:
"""Offload the synchronous editing path to keep the event loop responsive."""
return await asyncio.to_thread(self.edit, image, prompt, mask, n, size, **kwargs)
"""Async version of edit()."""
return self.edit(image, prompt, mask, n, size, **kwargs)
def variation(
self,
@@ -373,5 +372,6 @@ class ImageAgent(Agent):
size: Optional[str] = None,
**kwargs
) -> Dict[str, Any]:
"""Offload the synchronous variation path to keep the event loop responsive."""
return await asyncio.to_thread(self.variation, image, n, size, **kwargs)
"""Async version of variation()."""
return self.variation(image, n, size, **kwargs)
@@ -6,26 +6,14 @@ operations. Follows protocol-driven design with zero overhead when not used.
"""
import threading
from typing import Optional, Protocol, Set, runtime_checkable
from typing import Optional, Protocol, Set
from dataclasses import dataclass, field
__all__ = [
"InterruptControllerProtocol",
"CancellableInterruptControllerProtocol",
"InterruptController",
]
__all__ = ["InterruptControllerProtocol", "InterruptController"]
class InterruptControllerProtocol(Protocol):
"""Protocol for interrupt controller extension point.
``event`` is intentionally NOT part of this base contract: exposing the
underlying cancellation Event is an OPTIONAL capability. Existing third-party
controllers that only implement request/clear/is_set/reason/check remain
valid; the runtime probes for ``event`` via ``getattr(..., 'event', None)``.
Controllers that want in-tool cooperative abort can implement
:class:`CancellableInterruptControllerProtocol`.
"""
"""Protocol for interrupt controller extension point."""
def request(self, reason: str = "user") -> None:
"""Request cancellation with optional reason."""
@@ -43,27 +31,12 @@ class InterruptControllerProtocol(Protocol):
def reason(self) -> Optional[str]:
"""Get interrupt reason if set."""
...
def check(self) -> None:
"""Check for interrupt and raise if set."""
...
@runtime_checkable
class CancellableInterruptControllerProtocol(InterruptControllerProtocol, Protocol):
"""Optional extension: controllers that expose the cancellation Event.
A running tool body can wait on / poll this Event to abort promptly instead
of running until its own timeout. Implementing it is entirely optional and
fully backward compatible with :class:`InterruptControllerProtocol`.
"""
@property
def event(self) -> "threading.Event":
"""Get the underlying cancellation Event for in-tool observation."""
...
@dataclass
class InterruptController:
"""Thread-safe cooperative cancellation for agent runs.
@@ -122,19 +95,10 @@ class InterruptController:
return turn_id in self._cancelled_turns
def _end_turn(self, turn_id: int) -> None:
"""Unregister a turn so its request cannot affect a future turn.
Also clears the underlying Event once no turn still needs it (no active
or still-cancelled turns and no pending request). The Event is exposed to
running tool bodies via :attr:`event`; leaving it set after an interrupted
turn would make a reused controller abort tools launched by the NEXT turn.
"""
"""Unregister a turn so its request cannot affect a future turn."""
with self._lock:
self._active_turns.discard(turn_id)
self._cancelled_turns.discard(turn_id)
if not self._active_turns and not self._cancelled_turns and not self._pending_turn_cancel:
self._flag.clear()
self._reason = None
def clear(self) -> None:
"""Clear the cancellation request."""
@@ -162,16 +126,6 @@ class InterruptController:
with self._lock:
return self._reason
@property
def event(self) -> threading.Event:
"""Expose the underlying cancellation Event.
Lets a running tool body observe the interrupt cooperatively (e.g. wait
on it with a timeout, or poll ``is_set()``) so an in-flight subprocess/
request can be aborted rather than left running until its own timeout.
"""
return self._flag
def check(self) -> None:
"""Check for cancellation and raise if requested.
@@ -9,9 +9,8 @@ for maintainability.
import os
import inspect
import logging
import threading
import contextvars
from typing import Optional, Dict
from typing import Optional
# Per-turn ownership of appended chat-history messages. Each chat()/achat() turn
# runs in its own thread (sync) or task (async); both get an isolated copy of
@@ -22,38 +21,6 @@ _active_turn_owned: "contextvars.ContextVar[Optional[list]]" = contextvars.Conte
"praisonai_active_turn_owned", default=None
)
# Registry of the ownership lists of every currently in-flight chat()/achat()
# turn, keyed by id() of the list. A turn registers its list in
# _begin_turn_tracking and removes it in _end_turn_tracking. ephemeral() reads
# this at exit so a message a *concurrent live turn* appended is preserved even
# when that append did not flow through the ephemeral tracker (e.g. the turn
# ran on another thread that never entered this block's context). Guarded by
# _live_turns_lock because turns on different threads mutate it concurrently.
_live_turn_owners: "Dict[int, list]" = {}
_live_turns_lock = threading.Lock()
def _register_live_turn(owned: list) -> None:
with _live_turns_lock:
_live_turn_owners[id(owned)] = owned
def _unregister_live_turn(owned: Optional[list]) -> None:
if owned is None:
return
with _live_turns_lock:
_live_turn_owners.pop(id(owned), None)
def _live_turn_message_ids() -> set:
"""ids of every message any currently in-flight turn has appended so far."""
with _live_turns_lock:
owners = list(_live_turn_owners.values())
ids = set()
for owned in owners:
ids.update(id(m) for m in owned)
return ids
# Shared lazy display helpers (cached, thread-safe; avoid circular imports)
from ._lazy_display import _get_console, _get_live, _get_display_functions
@@ -154,18 +121,11 @@ class MemoryMixin:
runs in its own thread (sync ``chat``) or task (async ``achat``), so the
context var copy is isolated per turn. Safe to call unconditionally; when
a turn opts in, its rollback removes only its own messages by identity.
The list is also registered in the process-wide live-turn registry so a
concurrent ``ephemeral()`` block on another thread can preserve messages
this in-flight turn appends (see ``_live_turn_message_ids``).
"""
owned: list = []
_register_live_turn(owned)
return _active_turn_owned.set(owned)
return _active_turn_owned.set([])
def _end_turn_tracking(self, token):
"""Stop recording for the current turn and drop its ownership list."""
_unregister_live_turn(_active_turn_owned.get())
try:
_active_turn_owned.reset(token)
except (ValueError, LookupError):
@@ -176,10 +136,8 @@ class MemoryMixin:
Used at the start of an async turn (whose control flow has no single
wrapping ``finally``) so a stale list from a completed turn on the same
task cannot accumulate messages from unrelated turns. Also unregisters
that stale list from the live-turn registry so it cannot linger there.
task cannot accumulate messages from unrelated turns.
"""
_unregister_live_turn(_active_turn_owned.get())
_active_turn_owned.set(None)
def _rollback_chat_history_to(self, rollback_length):
@@ -204,7 +162,7 @@ class MemoryMixin:
"""
owned = _active_turn_owned.get()
with self._history_lock:
if owned is not None:
if owned:
owned_ids = {id(m) for m in owned}
self.chat_history[:] = [
m for m in self.chat_history if id(m) not in owned_ids
@@ -242,12 +200,9 @@ class MemoryMixin:
Also resets _auto_save_last_index to prevent silent message loss
when auto_save is enabled.
"""
# Hold the same lock every other history mutator takes so a concurrent
# _add_to_chat_history append can't land on the list object we discard.
with self._history_lock:
self.chat_history = []
# Reset auto-save index to prevent stale index causing message loss
self._auto_save_last_index = 0
self.chat_history = []
# Reset auto-save index to prevent stale index causing message loss
self._auto_save_last_index = 0
def prune_history(self, keep_last: int = 5) -> int:
"""
@@ -341,32 +296,16 @@ class MemoryMixin:
response = agent.chat("[IMAGE] Analyze this")
# After block, history is restored - image NOT persisted
"""
# Restore by identity, not by a blind ``chat_history = saved_history``.
# A message a concurrent chat()/achat() turn on the same shared Agent
# commits during the block must survive; only the ephemeral additions go.
#
# A message is KEPT on exit when it is either:
# * present in the pre-block snapshot (it predates the block), or
# * owned by a chat()/achat() turn that is still in flight (a live
# concurrent turn appended it - preserving it is the fix for the
# history-loss race).
# Everything else that appeared during the block is an ephemeral addition
# and is removed. This also drops direct ``chat_history.append`` writes
# made inside the block, which carry no turn ownership. Nested blocks
# compose: the inner block removes its own additions first, and the outer
# block's snapshot still holds everything that predates it.
# Save current history state
with self._history_lock:
snapshot_ids = {id(m) for m in self.chat_history}
saved_history = self.chat_history.copy()
try:
yield
finally:
live_ids = _live_turn_message_ids()
keep_ids = snapshot_ids | live_ids
# Restore history to pre-block state
with self._history_lock:
self.chat_history[:] = [
m for m in self.chat_history if id(m) in keep_ids
]
self.chat_history = saved_history
def _init_db_session(self):
"""Initialize DB session if db adapter is provided (lazy, first chat only)."""
@@ -408,26 +347,13 @@ class MemoryMixin:
metadata={"role": self.role, "goal": self.goal}
)
# Restore chat history from previous session. Rebuild the full LLM
# message shape so a resumed tool-using session hands the model the
# same transcript it saw before — assistant turns keep their
# ``tool_calls`` and tool-result turns keep their ``tool_call_id``
# (Issue #3089 parity for the DB path). Plain turns stay minimal.
# Restore chat history from previous session
if history:
for msg in history:
entry = {"role": msg.role, "content": msg.content}
tool_calls = getattr(msg, "tool_calls", None)
if tool_calls:
# ``DbMessage.tool_calls`` may arrive as provider-shaped
# dicts (OpenAI format, the way _persist_message stores
# them) or as ``DbToolCall`` dataclasses from an adapter
# that follows the declared field type. Normalise to the
# provider shape so the next model request always gets a
# valid, serialisable tool-call list (Issue #5075).
entry["tool_calls"] = self._normalize_restored_tool_calls(tool_calls)
if getattr(msg, "tool_call_id", None):
entry["tool_call_id"] = msg.tool_call_id
self.chat_history.append(entry)
self.chat_history.append({
"role": msg.role,
"content": msg.content
})
logging.info(f"Resumed session {self._session_id} with {len(history)} messages")
except Exception as e:
logging.warning(f"Failed to initialize DB session: {e}")
@@ -435,37 +361,6 @@ class MemoryMixin:
self._db_initialized = True
self._current_run_id = None # Track current run
@staticmethod
def _normalize_restored_tool_calls(tool_calls):
"""Coerce restored tool calls to provider-shaped (OpenAI) dicts.
Persisted tool calls can come back either already provider-shaped
(dicts with ``id``/``type``/``function``) or as ``DbToolCall``
dataclasses (``tool_name``/``args``/``call_id``) when an adapter follows
the declared ``DbMessage.tool_calls`` field type. Dicts pass through
unchanged; dataclasses are converted so the resumed transcript is always
a valid, serialisable tool-call list (Issue #5075).
"""
normalized = []
for tc in tool_calls:
if isinstance(tc, dict):
normalized.append(tc)
continue
tool_name = getattr(tc, "tool_name", None)
if tool_name is not None:
import json as _json
args = getattr(tc, "args", None)
arguments = args if isinstance(args, str) else _json.dumps(args or {})
normalized.append({
"id": getattr(tc, "call_id", None),
"type": "function",
"function": {"name": tool_name, "arguments": arguments},
})
else:
# Unknown shape — pass through so we never lose data.
normalized.append(tc)
return normalized
def _init_session_store(self):
"""
Initialize session store for JSON-based persistence (lazy, first chat only).
@@ -580,26 +475,7 @@ class MemoryMixin:
if role == "user":
self._db.on_user_message(self._session_id, content)
elif role == "assistant":
# Faithful transcript: carry any tool calls the assistant
# requested so a resumed DB session replays them, matching
# the JSON store fix (Issue #3089). Adapters that predate
# ``on_assistant_message`` fall back to the text-only
# ``on_agent_message`` so behaviour is unchanged for them.
if tool_calls and hasattr(self._db, "on_assistant_message"):
self._db.on_assistant_message(
self._session_id, content, tool_calls=tool_calls
)
else:
self._db.on_agent_message(self._session_id, content)
elif role == "tool":
# Persist the tool-result turn linked to its call id so the
# resumed message list interleaves results in order (#3089).
# Adapters without ``on_tool_message`` keep the prior
# behaviour of dropping the raw tool turn (text-only).
if hasattr(self._db, "on_tool_message"):
self._db.on_tool_message(
self._session_id, content, tool_call_id=tool_call_id
)
self._db.on_agent_message(self._session_id, content)
except Exception as e:
logging.warning(f"Failed to persist message to DB: {e}")
return
@@ -764,50 +640,6 @@ class MemoryMixin:
except Exception as e:
logging.debug(f"Auto-memory extraction failed: {e}")
def _persist_memory_turn(self, user_message: str, assistant_response: str):
"""Persist a raw conversation turn to the memory store.
Called after each response when ``_memory_instance`` is set but
``auto_memory`` extraction is off. Stores the turn to short-term memory
so a later Agent sharing the same store (e.g. ``memory={"user_id": uid}``)
recalls it via ``get_memory_context()``. Best-effort: never raises.
Async-safe: a memory store write is blocking file/DB I/O. When this runs
inside a live event loop (the async ``achat``/``astart`` after-agent path),
the write is offloaded to a worker thread so it never stalls the loop
(AGENTS.md §4.5). On the sync path (no running loop) it writes inline.
"""
memory = getattr(self, "_memory_instance", None)
if memory is None or not assistant_response:
return
store = getattr(memory, "store_short_term", None) or getattr(memory, "add_short_term", None)
if store is None:
return
text = f"User: {user_message}\nAssistant: {assistant_response}"
metadata = {"agent_id": getattr(self, "agent_id", getattr(self, "name", None))}
def _do_store():
try:
store(text, metadata=metadata)
except Exception as e:
logging.debug(f"Memory turn persistence failed: {e}")
try:
import asyncio
asyncio.get_running_loop()
except RuntimeError:
# No running loop (sync chat/run/start path): write inline.
_do_store()
return
# Inside a live loop: offload the blocking write so it cannot stall the
# event loop. Fire-and-forget — persistence is best-effort.
try:
import asyncio
asyncio.get_running_loop().run_in_executor(None, _do_store)
except Exception as e:
logging.debug(f"Memory turn persistence scheduling failed: {e}")
_do_store()
def _process_auto_learning(self):
"""Process auto-learning extraction after agent response.
@@ -898,16 +730,11 @@ class MemoryMixin:
# Reset counter and emit nudge
self._turns_since_nudge = 0
# Optional tool-work floor (Issue #4864): ``nudge_min_tool_iters`` is a
# tunable override, not a hard floor. When it is <= 0 the cadence fires
# on conversational (tool-less) turns too, so a chat-only companion bot
# still learns; a positive value keeps the "only nudge after real tool
# work" behaviour for task-oriented agents.
# Optional: only nudge if agent has done meaningful work
min_iters = getattr(self._learn_config, 'nudge_min_tool_iters', 3)
if min_iters > 0:
tool_calls_count = getattr(self, '_recent_tool_calls_count', 0)
if tool_calls_count < min_iters:
return None
tool_calls_count = getattr(self, '_recent_tool_calls_count', 0)
if tool_calls_count < min_iters:
return None
return (
"\n\n[System nudge] Review the recent conversation. If you discovered a "
@@ -928,56 +755,45 @@ class MemoryMixin:
if not self.auto_save:
return
# Serialize the whole read-modify-write of _auto_save_last_index. This
# method now runs via asyncio.to_thread, so two concurrent async runs
# sharing one Agent can execute it in separate worker threads. Without
# this lock both could read the same last-saved index, then each persist
# the same new turns, duplicating conversation history — the store's
# file lock serializes the writes but does not protect this index.
lock = getattr(self, '_auto_save_lock', None)
if lock is None:
lock = threading.Lock()
self._auto_save_lock = lock
with lock:
try:
# Filter out history markers before saving
clean_history = [
{k: v for k, v in msg.items() if k != "_from_history"}
for msg in self.chat_history
]
# Issue 1 FIX: Only save NEW messages since last save
# Track last saved index to avoid duplicates
last_saved = getattr(self, '_auto_save_last_index', 0)
new_messages = clean_history[last_saved:]
if not new_messages:
return # Nothing new to save
# G-1 FIX: Use SessionStore for conversation history persistence
# This maintains clean separation: Memory = facts, SessionStore = turns
if self._session_store is not None:
# Persist only NEW messages to SessionStore
for msg in new_messages:
self._session_store.add_message(
self.auto_save, # Use auto_save name as session_id
role=msg.get("role", "user"),
content=msg.get("content", ""),
)
# Update last saved index
self._auto_save_last_index = len(clean_history)
logging.debug(f"Auto-saved {len(new_messages)} new messages to SessionStore: {self.auto_save}")
elif self._memory_instance and hasattr(self._memory_instance, 'save_session'):
# Fallback to Memory.save_session() for backward compatibility
# Memory.save_session() replaces entire history, so no duplicate issue
self._memory_instance.save_session(
name=self.auto_save,
conversation_history=clean_history,
metadata={"agent_name": self.name, "user_id": self.user_id}
try:
# Filter out history markers before saving
clean_history = [
{k: v for k, v in msg.items() if k != "_from_history"}
for msg in self.chat_history
]
# Issue 1 FIX: Only save NEW messages since last save
# Track last saved index to avoid duplicates
last_saved = getattr(self, '_auto_save_last_index', 0)
new_messages = clean_history[last_saved:]
if not new_messages:
return # Nothing new to save
# G-1 FIX: Use SessionStore for conversation history persistence
# This maintains clean separation: Memory = facts, SessionStore = turns
if self._session_store is not None:
# Persist only NEW messages to SessionStore
for msg in new_messages:
self._session_store.add_message(
self.auto_save, # Use auto_save name as session_id
role=msg.get("role", "user"),
content=msg.get("content", ""),
)
logging.debug(f"Auto-saved session to Memory: {self.auto_save}")
except Exception as e:
logging.debug(f"Error auto-saving session: {e}")
# Update last saved index
self._auto_save_last_index = len(clean_history)
logging.debug(f"Auto-saved {len(new_messages)} new messages to SessionStore: {self.auto_save}")
elif self._memory_instance and hasattr(self._memory_instance, 'save_session'):
# Fallback to Memory.save_session() for backward compatibility
# Memory.save_session() replaces entire history, so no duplicate issue
self._memory_instance.save_session(
name=self.auto_save,
conversation_history=clean_history,
metadata={"agent_name": self.name, "user_id": self.user_id}
)
logging.debug(f"Auto-saved session to Memory: {self.auto_save}")
except Exception as e:
logging.debug(f"Error auto-saving session: {e}")
def _save_output_to_file(self, content: str) -> bool:
"""Save agent output to file if output_file is configured.
@@ -113,20 +113,11 @@ def resolve_placement(
TypeError: on any combination that names two different places for the
same thing, or a place that cannot do the job asked of it.
"""
managed = managed_runtimes()
places = tool_places()
# ── a place that cannot do the job asked of it ───────────────────────────
run_on_name = _name_of(run_on)
tools_name = _name_of(tools_run_on)
# The two lookups below feed only the branches guarded on run_on_name /
# tools_name being set; the entry-point scan in tool_places() is the
# dominant cost of Agent() construction, so skip both on the default
# (no-placement) path rather than compute results that get discarded.
if run_on_name is not None or tools_name is not None:
managed = managed_runtimes()
places = tool_places()
else:
managed = places = ()
if run_on_name is not None and run_on_name not in managed:
if run_on_name in places:
raise TypeError(
@@ -144,6 +135,7 @@ def resolve_placement(
f"(pass those as tools_run_on=)"
)
tools_name = _name_of(tools_run_on)
if tools_name is not None and tools_name in managed and tools_name not in places:
raise TypeError(
f"{owner}(tools_run_on={tools_run_on!r}) is not valid: {tools_name!r} "
@@ -18,36 +18,18 @@ except ImportError: # pragma: no cover - py<3.8 fallback
if Literal is not None:
TerminalReason = Literal[
"completed",
"hard_timeout",
"cancelled",
"aborted",
"failed",
"content_filtered",
"refused",
"length_truncated",
"completed", "hard_timeout", "cancelled", "aborted", "failed"
]
else: # pragma: no cover
TerminalReason = str # type: ignore
# Provider-side terminal reasons derived from the LLM ``finish_reason``/refusal
# signal. Additive and backward-compatible: absent/unknown finish reasons keep
# the existing ``completed|failed|...`` semantics unchanged.
PROVIDER_BLOCK_REASONS = ("content_filtered", "refused", "length_truncated")
# Precedence: higher wins and is sticky (a hard timeout is not downgraded).
# A specific provider block/refusal/truncation outranks a generic ``failed`` so
# the actionable reason is not masked, but stays below cancellation/timeout,
# which are host-level lifecycle signals.
_REASON_PRECEDENCE = {
"completed": 0,
"failed": 1,
"content_filtered": 2,
"refused": 2,
"length_truncated": 2,
"aborted": 3,
"cancelled": 4,
"hard_timeout": 5,
"aborted": 2,
"cancelled": 3,
"hard_timeout": 4,
}
@@ -111,27 +93,3 @@ class RunOutcome:
def _name_matches(exc: BaseException, needles: tuple) -> bool:
name = type(exc).__name__.lower()
return any(n in name for n in needles)
def classify_finish_reason(finish_reason, refusal=None):
"""Map a provider ``finish_reason``/refusal signal to a terminal reason.
Returns one of ``content_filtered | refused | length_truncated`` when the
provider blocked/refused/truncated the turn, or ``None`` for a normal stop
(``None``/``"stop"``) or any unrecognised value — so unknown finish reasons
behave exactly as today. Additive and zero-cost on the success path.
"""
if refusal:
return "refused"
if not finish_reason:
return None
fr = str(finish_reason).lower()
if fr in ("stop", "tool_calls", "function_call"):
return None
if "content_filter" in fr or fr == "content_filtered":
return "content_filtered"
if "refus" in fr:
return "refused"
if fr == "length" or "max_tokens" in fr or "truncat" in fr:
return "length_truncated"
return None
@@ -1,180 +0,0 @@
"""Export an Agent or AgentTeam back to a config dict.
Config flowed one way. ``workflows/yaml_parser.py`` builds agents FROM YAML, and
nothing exported them back -- so you could not build a team in Python and hand
it to the visual builder, diff two team configs, or check into review what a
programmatically-assembled team actually became. This is the missing half of a
pipeline that already exists.
blob = agent_to_dict(agent) # JSON-safe
same = agent_from_dict(blob) # an equivalent Agent
What is deliberately NOT exported: anything that is a live object rather than
configuration -- an open session, a memory store, a resolved LLM client. A tool
is exported by NAME, because a callable cannot survive a round trip through
JSON and pretending otherwise would produce a config that imports as a
different agent. ``tools_resolvable`` says whether the names could be rebound,
so a caller is told rather than left to discover it.
Scope, stated plainly so a caller is not surprised: this exports the scalar
constructor arguments that are JSON-safe and round-trip cleanly (identity, the
model, and simple flags). It does not yet serialise the grouped feature-config
objects (``output=``, ``reflection=``, ``execution=`` ...) -- those are rich
dataclasses, not scalars, and rebuilding them faithfully is a separate,
larger piece of work. An agent that relies on a customised grouped config will
round-trip to one carrying that config's *defaults*, not the original. That is
a known limit of v1, named here rather than hidden, in the same spirit as
``tools_resolvable``.
"""
from typing import Any, Callable, Dict, List, Optional
__all__ = [
"AGENT_CONFIG_VERSION",
"SerializationError",
"agent_to_dict",
"agent_from_dict",
"team_to_dict",
]
AGENT_CONFIG_VERSION = 1
#: Candidate fields worth carrying. Deliberately a list rather than "everything
#: on the object": an Agent holds runtime state (clients, caches, sessions) that
#: is meaningless -- and sometimes unserialisable -- in a config.
#:
#: Intersected with the CONSTRUCTOR SIGNATURE at export time, so an attribute
#: that still exists on the instance but is no longer a constructor argument
#: (several moved into `output=`) is not exported into a config that cannot be
#: imported. Hardcoding the list alone produced exactly that.
_AGENT_FIELDS = (
"name", "role", "goal", "backstory", "instructions", "llm",
"reasoning_effort",
"self_reflect", "max_reflect", "min_reflect", "respect_context_window",
"max_iter", "reasoning_steps", "markdown", "stream", "verbose",
)
def _constructor_fields(agent_cls: type) -> set:
"""The subset of _AGENT_FIELDS this build's constructor still accepts."""
import inspect
try:
params = inspect.signature(agent_cls.__init__).parameters
except (TypeError, ValueError): # pragma: no cover - exotic callables
return set(_AGENT_FIELDS)
if any(p.kind is inspect.Parameter.VAR_KEYWORD for p in params.values()):
# **kwargs alone is not proof it is accepted: this class validates and
# raises on unknown keys, so trust the named parameters only.
pass
return {f for f in _AGENT_FIELDS if f in params}
class SerializationError(ValueError):
"""Raised when a config cannot be exported or rebuilt."""
def _tool_name(tool: Any) -> Optional[str]:
for attr in ("name", "__name__"):
value = getattr(tool, attr, None)
if isinstance(value, str) and value:
return value
if isinstance(tool, str):
return tool
return None
def agent_to_dict(agent: Any) -> Dict[str, Any]:
"""An Agent as a JSON-safe config dict."""
if agent is None:
raise SerializationError("Cannot export None as an agent config.")
allowed = _constructor_fields(type(agent))
config: Dict[str, Any] = {"version": AGENT_CONFIG_VERSION}
for field in sorted(allowed):
if not hasattr(agent, field):
continue
value = getattr(agent, field)
if value is None:
continue
# An LLM object rather than a model string: keep its identity, not the
# client. A resolved client cannot be rebuilt from JSON anyway.
if field == "llm" and not isinstance(value, str):
value = getattr(value, "model", None) or getattr(value, "name", None) or str(value)
config[field] = value
tools = getattr(agent, "tools", None) or []
names = [_tool_name(t) for t in tools]
config["tools"] = [n for n in names if n]
# Say plainly whether the tools survived as names. A config whose tools
# cannot be rebound imports as an agent that silently cannot act.
config["tools_resolvable"] = all(n is not None for n in names)
return config
def agent_from_dict(
config: Dict[str, Any],
*,
tool_registry: Optional[Dict[str, Callable]] = None,
agent_cls: Optional[type] = None,
) -> Any:
"""Rebuild an Agent from ``agent_to_dict`` output.
``tool_registry`` maps exported tool names back to callables. Without it an
agent is rebuilt WITHOUT tools, and that is reported rather than assumed --
an agent that silently lost its tools looks like an agent that chose not to
use them.
"""
if not isinstance(config, dict):
raise SerializationError(f"Agent config must be a dict; got {type(config).__name__}")
version = config.get("version", AGENT_CONFIG_VERSION)
if version != AGENT_CONFIG_VERSION:
raise SerializationError(
f"Agent config is version {version!r}, this build reads {AGENT_CONFIG_VERSION}."
)
if agent_cls is None:
from .agent import Agent as agent_cls # type: ignore
kwargs = {k: v for k, v in config.items() if k in _constructor_fields(agent_cls)}
wanted: List[str] = list(config.get("tools") or [])
if wanted:
if tool_registry is None:
raise SerializationError(
f"This config declares tools {wanted} but no tool_registry was given, "
f"so they cannot be rebound. Pass tool_registry={{name: callable}}, or "
f"strip 'tools' from the config if a tool-less agent is intended."
)
missing = [n for n in wanted if n not in tool_registry]
if missing:
raise SerializationError(
f"tool_registry is missing {missing}. Rebuilding without them would "
f"produce an agent that silently cannot act."
)
kwargs["tools"] = [tool_registry[n] for n in wanted]
return agent_cls(**kwargs)
def team_to_dict(team: Any) -> Dict[str, Any]:
"""An AgentTeam as a config dict, members included.
A team's *members* export cleanly; its **task graph** does not yet. Tasks
carry agent bindings, ordering, and context wiring whose faithful
serialisation -- and a matching importer -- is a larger piece of work than
this v1. Rather than emit half a task graph that would import wrong, ``tasks``
are omitted and ``tasks_included`` reports whether any were dropped, so the
caller is told rather than handed a team that silently forgot its work.
"""
if team is None:
raise SerializationError("Cannot export None as a team config.")
tasks = getattr(team, "tasks", None)
had_tasks = bool(tasks)
return {
"version": AGENT_CONFIG_VERSION,
"name": getattr(team, "name", None),
"process": getattr(team, "process", None),
"agents": [agent_to_dict(a) for a in (getattr(team, "agents", None) or [])],
"tasks_included": not had_tasks,
}
@@ -1,226 +0,0 @@
"""
Shared HTTP server registry for launch() paths.
Both ``Agent.launch()`` (single-agent) and ``PraisonAIAgents.launch()``
(multi-agent) let multiple ``launch()`` calls share one FastAPI app / uvicorn
server per port. They MUST consult the *same* process-wide registry so a
standalone agent and a team launched on the same port see each other's state:
one "is this port started?" check, one FastAPI app, one set of routes. Keeping
two independent registries caused duplicate binds (``Address already in use``)
and routes registered through one launcher being invisible on the other's app.
"""
import os
import threading
import time
import uuid
from typing import Any, Dict, List, Optional, Tuple
from praisonaiagents._logging import get_logger
logger = get_logger(__name__)
class _AgentServerRegistry:
"""Encapsulates all shared HTTP server state with proper synchronization."""
def __init__(self):
self._lock = threading.Lock()
self._started: Dict[int, bool] = {}
self._endpoints: Dict[int, Dict[str, str]] = {}
self._apps: Dict[int, Any] = {} # FastAPI apps
self._ready_events: Dict[int, threading.Event] = {}
def get_or_create_app(self, port: int, title: str = "AgentTeam API") -> Tuple[Any, bool]:
"""Thread-safe app creation. Returns (app, is_new)."""
with self._lock:
if port not in self._apps:
# Lazy import to avoid optional dependency at module level
from fastapi import FastAPI
self._apps[port] = FastAPI(title=title)
self._endpoints[port] = {}
self._ready_events[port] = threading.Event()
return self._apps[port], True
return self._apps[port], False
def register_route(self, port: int, path: str, endpoint_id: str = "registered") -> None:
"""Thread-safe route registration tracking."""
with self._lock:
if port not in self._endpoints:
self._endpoints[port] = {}
self._endpoints[port][path] = endpoint_id
def reserve_route(self, port: int, path: str, endpoint_id: str) -> Tuple[str, Optional[str]]:
"""Atomically reserve and register a route.
Returns:
tuple[str, Optional[str]]: (final_path, original_path_if_collided).
If there is no collision, final_path equals the requested path and
original_path_if_collided is None.
"""
with self._lock:
if port not in self._endpoints:
self._endpoints[port] = {}
original_path = path
while path in self._endpoints[port]:
path = f"{original_path}_{str(uuid.uuid4())[:6]}"
self._endpoints[port][path] = endpoint_id
return path, (original_path if path != original_path else None)
def list_routes(self, port: int) -> List[str]:
"""Return a snapshot list of registered routes for a port."""
with self._lock:
return list(self._endpoints.get(port, {}).keys())
def unregister_routes_for(self, port: int, endpoint_id: str) -> List[str]:
"""Remove all routes owned by ``endpoint_id`` on ``port``.
Returns the list of removed paths so callers can tear down the matching
FastAPI routes. Thread-safe.
"""
with self._lock:
paths = self._endpoints.get(port, {})
removed = [p for p, owner in paths.items() if owner == endpoint_id]
for p in removed:
del paths[p]
if not paths:
self._endpoints.pop(port, None)
return removed
def teardown_routes_for(self, endpoint_id: str) -> None:
"""Remove every route owned by ``endpoint_id`` across all ports.
Performs BOTH the endpoint-registry removal AND the matching FastAPI
route teardown while holding ``self._lock`` for each port, so it cannot
interleave with a concurrent ``reserve_route`` + ``app.post()`` for the
same path (which would otherwise let this filter delete a freshly
registered live endpoint, or race the ``_apps`` snapshot). Only the
agent-owned POST route at each path is dropped; a co-located GET (e.g.
the built-in ``/`` and ``/health``) is preserved.
"""
for port in list(self._apps.keys()):
with self._lock:
paths = self._endpoints.get(port, {})
removed = [p for p, owner in paths.items() if owner == endpoint_id]
if not removed:
continue
for p in removed:
del paths[p]
if not paths:
self._endpoints.pop(port, None)
app = self._apps.get(port)
if app is None:
continue
removed_set = set(removed)
try:
app.router.routes = [
r for r in app.router.routes
if not (
getattr(r, "path", None) in removed_set
and "POST" in (getattr(r, "methods", None) or set())
)
]
# Invalidate cached OpenAPI schema so removed routes
# disappear from /openapi.json and /docs.
app.openapi_schema = None
except Exception:
logger.debug(
"Failed to tear down routes for %s on port %s",
endpoint_id,
port,
exc_info=True,
)
def start_server_if_needed(self, port: int, host: str = "0.0.0.0", **kwargs) -> bool: # noqa: S104
"""Start server with proper readiness signaling. Returns True if server was started.
Readiness is signalled only *after* uvicorn has actually bound the
socket (``Server.started``), so a caller that observes readiness can
immediately issue a request without a connection-refused race. If the
bind fails (e.g. ``Address already in use``) the port's ``_started``
flag is cleared so a later ``launch()`` can retry the bind instead of
registering routes on an app whose server never came up.
"""
with self._lock:
if self._started.get(port, False):
return False # Already started
self._started[port] = True
app = self._apps.get(port)
if not app:
# Roll back the reservation so a caller that first registers an app
# can start it — we must not leave the port permanently "started".
with self._lock:
self._started[port] = False
raise ValueError(f"No app registered for port {port}")
ready_event = self._ready_events[port]
def run_server():
try:
import uvicorn
# Remove hardcoded log_level to avoid conflict with kwargs
config = uvicorn.Config(app, host=host, port=port, **kwargs)
server = uvicorn.Server(config)
# Signal readiness only once uvicorn reports the socket is bound
# (server.started flips True after startup completes). A watcher
# thread polls that flag and sets the event, so waiters are not
# told "ready" before the port actually accepts connections.
def _signal_when_bound():
while not server.started:
if ready_event.is_set():
return # bind failed / server exited before startup
time.sleep(0.02)
ready_event.set()
watcher = threading.Thread(target=_signal_when_bound, daemon=True)
watcher.start()
server.run()
except Exception:
# Bind/startup failed. Clear the started flag so a subsequent
# launch() can re-attempt binding instead of silently
# registering routes on a dead server, and unblock any waiter.
logger.warning(
"Agent server on port %s failed to start.", port, exc_info=True
)
with self._lock:
self._started[port] = False
finally:
# Always release the waiter: on failure the started flag has been
# cleared above, so the (now-false) readiness is correctly
# observable via the flag rather than a hung wait().
ready_event.set()
thread = threading.Thread(target=run_server, daemon=True)
thread.start()
# Check for configurable timeout via environment variable
try:
timeout = float(os.environ.get("PRAISONAI_SERVER_READY_TIMEOUT", "5.0"))
except ValueError:
logger.warning("Invalid PRAISONAI_SERVER_READY_TIMEOUT value. Using default 5.0s.")
timeout = 5.0
became_ready = ready_event.wait(timeout=timeout)
if not became_ready:
logger.warning(
"Agent server on port %s did not become ready within %.1fs. "
"Proceeding, but some features may not work correctly. "
"Check server logs for startup errors.",
port,
timeout,
)
# Report whether the bind actually succeeded: on failure run_server has
# cleared the flag, so returning it lets callers distinguish a live
# server from a poisoned port.
with self._lock:
return self._started.get(port, False)
# Module level — single registry instance shared by every launch() call site.
_server_registry = _AgentServerRegistry()
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