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praisonai-triage-agent[bot]andMervin Praison 85ba558a3b fix: real MCP readiness check in example + drop unused SseServerTransport
- simple-mcp-server.py: replace blind 2s sleep with TCP readiness poll so
  the smoke test genuinely verifies the server bound and exits non-zero on
  failure (addresses Greptile P1: daemon exited claiming false success)
- execution_mixin.py: remove now-unused SseServerTransport import/instance
  after switching to FastMCP.sse_app() (dead code flagged by Greptile)

Co-authored-by: Mervin Praison <[email protected]>
2026-07-24 08:57:52 +00:00
1787 changed files with 30617 additions and 256154 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"/>
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<h2 class="wp-block-heading">Section 1 — What wrapper adds (not in Tier-2 alone)</h2>
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<figure class="wp-block-table"><table><thead><tr><th>Feature</th><th>Command / path</th><th>Owner</th><th>Extracted?</th></tr></thead><tbody><tr><td>Unified CLI router</td><td><code>praisonai …</code></td><td>code Typer + 6 resident registries</td><td>—</td></tr><tr><td>HTTP serve orchestration</td><td><code>praisonai serve agents|recipe|a2a|…</code></td><td>wrapper <code>cli/features/serve.py</code></td><td>Deferred (C15 epic)</td></tr><tr><td>Dashboard launcher</td><td><code>praisonai dashboard</code></td><td>wrapper</td><td>Stay wrapper</td></tr><tr><td>Framework adapters</td><td><code>praisonai --framework crewai</code></td><td>wrapper <code>framework_adapters/</code></td><td>Stay wrapper (impls in external PraisonAI-Frameworks)</td></tr><tr><td>Jobs API</td><td><code>praisonai.jobs</code> · port 8005</td><td>wrapper</td><td>Deferred (with serve/recipe)</td></tr><tr><td>Recipe NL → YAML</td><td><code>praisonai recipe …</code></td><td>wrapper</td><td>Deferred</td></tr><tr><td>Scheduler CLI</td><td><code>praisonai schedule …</code></td><td>wrapper</td><td>Stay wrapper (3-layer split with bot)</td></tr><tr><td>Sandbox execution</td><td><code>praisonai sandbox …</code></td><td>wrapper <code>sandbox/</code></td><td>C13 candidate</td></tr><tr><td>Cloud deploy</td><td><code>praisonai deploy …</code></td><td>wrapper <code>deploy/</code></td><td>C13 candidate</td></tr><tr><td>Langfuse / Langflow / n8n</td><td><code>langfuse</code>, <code>flow</code>, <code>n8n</code></td><td>wrapper</td><td>Stay wrapper</td></tr><tr><td>Backward-compat shims</td><td><code>praisonai.bots</code> → <code>praisonai_bot</code></td><td>wrapper <code>cli/_shim.py</code></td><td>Permanent</td></tr></tbody></table></figure>
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<p>Tier-2 packages own their domains; the wrapper owns integration surfaces that span multiple tiers.</p>
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<h2 class="wp-block-heading">Section 2 — Terminal hot path (via code tier)</h2>
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<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>
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<pre class="wp-block-code"><code># Python SDK (Tier 1 — same everywhere)
from praisonaiagents import Agent
agent = Agent(instructions="You are a helpful AI assistant")
agent.start("Write a movie script about a robot on Mars")</code></pre>
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<p>Deep dive: <a href="https://mer.vin/2026/07/praisonai-code-praisonai-code-terminal-cli-in-depth/">praisonai-code in-depth</a></p>
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<h2 class="wp-block-heading">Section 3 — Train (via praisonai-train tier)</h2>
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<pre class="wp-block-code"><code># LLM fine-tuning (Unsloth) — lazy ML deps
praisonai train llm dataset.json
praisonai train llm --model llama-3.1 dataset.json
# Agent training — LLM-as-judge
praisonai train agents --input "What is Python?" --iterations 3
# Human feedback loop
praisonai train agents --input "Explain quantum computing" --human
# Session management
praisonai train list
praisonai train apply train-abc123 --run "And Germany?"
# Standalone script (no wrapper prefix)
praisonai-train agents --input "Hello" --iterations 2</code></pre>
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<p>Deep dive: <a href="https://mer.vin/2026/07/praisonai-train-praisonai-train-fine-tuning-agent-training-in-depth/">praisonai-train in-depth</a></p>
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<h2 class="wp-block-heading">Section 4 — Bots &amp; gateway (via bot tier)</h2>
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<pre class="wp-block-code"><code>pip install "praisonai[bot]"
export OPENAI_API_KEY=sk-...
export TELEGRAM_BOT_TOKEN=...
praisonai onboard
praisonai bot start --platform telegram
praisonai gateway start --config ~/.praisonai/bot.yaml
praisonai gateway install --config ~/.praisonai/bot.yaml
praisonai pairing approve telegram ABC12345</code></pre>
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<p>Deep dive: <a href="https://mer.vin/2026/07/praisonai-bot-praisonai-bot-gateway-channels-in-depth/">praisonai-bot in-depth</a></p>
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<h2 class="wp-block-heading">Section 5 — MCP server host (via mcp tier)</h2>
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<figure class="wp-block-table"><table><thead><tr><th>Command</th><th>Layer</th><th>Package</th></tr></thead><tbody><tr><td><code>praisonai serve mcp</code></td><td>Light server</td><td><code>praisonai-code</code> + agents</td></tr><tr><td><code>praisonai mcp serve</code></td><td>Heavy host</td><td><code>praisonai-mcp</code></td></tr><tr><td><code>praisonai-mcp serve</code></td><td>Heavy host (direct)</td><td><code>praisonai-mcp</code></td></tr></tbody></table></figure>
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<pre class="wp-block-code"><code># Heavy MCP host — full tool/resource/prompt registry
praisonai mcp serve --transport stdio
praisonai mcp serve --transport http-stream --port 8080 --api-key secret
# Recipe → scoped MCP server
praisonai mcp serve-recipe support-reply --transport stdio
# Client config management (needs praisonai-code co-installed)
praisonai mcp list
praisonai mcp add filesystem --command npx --args "-y @modelcontextprotocol/server-filesystem ."
# Generate Cursor / Claude Desktop config
praisonai mcp config-generate --client cursor --transport stdio</code></pre>
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<p>Deep dive: <a href="https://mer.vin/2026/07/praisonai-mcp-praisonai-mcp-server-host-client-config-in-depth/">praisonai-mcp in-depth</a></p>
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<h2 class="wp-block-heading">Section 6 — Browser automation (via browser tier)</h2>
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<pre class="wp-block-code"><code>pip install "praisonai[browser]"
# Extension bridge server + LLM browser agent
praisonai browser start
praisonai browser run "Find the latest Python release notes"
# Diagnostics
praisonai browser doctor
# Lightweight tool shim (code tier — no praisonai-browser required)
praisonai browser-tool snapshot https://example.com
# Standalone script
praisonai-browser start
praisonai-browser run "Click the login button"</code></pre>
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<p>Three layers: agents protocols → <code>praisonai browser-tool</code> (praisonai-tools) → <code>praisonai browser</code> (extension bridge, CDP, Playwright).</p>
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<!-- wp:paragraph -->
<p>Deep dive: <a href="https://mer.vin/2026/07/praisonai-browser-praisonai-browser-browser-automation-in-depth/">praisonai-browser in-depth</a></p>
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<h2 class="wp-block-heading">Section 7 — Dashboard stack</h2>
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<pre class="wp-block-code"><code>pip install "praisonai[claw,flow,ui]"
# Individual services
praisonai claw # :8082 — ops dashboard
praisonai flow # :7861 — Langflow
praisonai ui # :8081 — clean chat
# Unified launcher (wrapper-only)
praisonai dashboard # :3000
praisonai dashboard --port 9000 --no-auto-start</code></pre>
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<figure class="wp-block-table"><table><thead><tr><th>Port</th><th>Service</th></tr></thead><tbody><tr><td>3000</td><td>Dashboard hub</td></tr><tr><td>7860/7861</td><td>Langflow</td></tr><tr><td>8081</td><td>UI chat</td></tr><tr><td>8082</td><td>Claw</td></tr><tr><td>8765</td><td>Gateway WebSocket</td></tr><tr><td>8005</td><td>Jobs API</td></tr><tr><td>8080</td><td>MCP HTTP stream (optional)</td></tr></tbody></table></figure>
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<h2 class="wp-block-heading">Section 8 — Multi-framework YAML</h2>
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<pre class="wp-block-code"><code>pip install "praisonai[crewai]"
export OPENAI_API_KEY=sk-...
praisonai --framework crewai --auto "Create a movie script"
praisonai run --file agents.yaml --framework crewai
pip install "praisonai[autogen]"
praisonai --framework autogen agents.yaml</code></pre>
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<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>
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<h2 class="wp-block-heading">Section 9 — Scheduler (24/7 agents)</h2>
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<!-- 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>
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<!-- 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>
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<!-- 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>
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<!-- wp:heading -->
<h2 class="wp-block-heading">Section 10 — Jobs API &amp; wrapper-only surfaces</h2>
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<p>Jobs, recipe, serve, sandbox, and deploy remain wrapper-owned today (deferred or C13 candidates).</p>
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<pre class="wp-block-code"><code># Jobs API (wrapper — port 8005)
python -m uvicorn praisonai.jobs.server:create_app --port 8005 --factory
praisonai run submit "Analyse AI trends"
praisonai run submit "Analyse news" --recipe news-analyzer --wait
export PRAISONAI_JOBS_API_KEY=your-secret
# HTTP serve (wrapper orchestration — Typer shell in code tier)
praisonai serve agents --port 8080
praisonai serve recipe support-reply
# Sandbox / deploy (wrapper today — C13 extraction candidates)
praisonai sandbox run "print hello" --backend docker
praisonai deploy agents.yaml --provider aws</code></pre>
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<h2 class="wp-block-heading">Section 11 — Lazy CLI routing (six resident registries)</h2>
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<figure class="wp-block-table"><table><thead><tr><th>Registry</th><th>Count</th><th>Examples</th><th>Loaded from</th><th>Gate</th></tr></thead><tbody><tr><td>Code-resident</td><td>~40</td><td>run, chat, code, daemon, serve, config</td><td><code>praisonai_code.cli.commands.*</code></td><td>always</td></tr><tr><td>Bot-resident</td><td>8</td><td>bot, gateway, onboard, kanban, claw</td><td><code>praisonai_bot.cli.commands.*</code></td><td><code>bot_package_available()</code></td></tr><tr><td>Train-resident</td><td>1</td><td>train</td><td><code>praisonai_train.cli.commands.*</code></td><td><code>train_package_available()</code></td></tr><tr><td>Browser-resident</td><td>1</td><td>browser</td><td><code>praisonai_browser.cli.commands.*</code></td><td><code>browser_package_available()</code></td></tr><tr><td>MCP-resident</td><td>1</td><td>mcp</td><td><code>praisonai_mcp.cli.commands.*</code></td><td><code>mcp_package_available()</code></td></tr><tr><td>Wrapper-resident</td><td>22</td><td>dashboard, schedule, flow, langfuse, recipe</td><td><code>praisonai.cli.commands.*</code></td><td><code>wrapper_available()</code></td></tr></tbody></table></figure>
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<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>
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<p>Standalone <code>praisonai-code</code> hides bot/train/browser/mcp/wrapper commands from <code>--help</code> when those packages are absent.</p>
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<!-- wp:heading -->
<h2 class="wp-block-heading">Section 12 — Shim map (backward compat)</h2>
<!-- /wp:heading -->
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<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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<pre class="wp-block-code"><code># These must keep working
from praisonai.cli.main import PraisonAI
from praisonai.bots import Bot
from praisonai.gateway import WebSocketGateway
from praisonai.train.agents import AgentTrainer
from praisonai.mcp_server import MCPServer
python -m praisonai run "hello"
python -m praisonai.runtime</code></pre>
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<h2 class="wp-block-heading">Section 13 — Bridges (no PyPI cycles)</h2>
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<figure class="wp-block-table"><table><thead><tr><th>Bridge</th><th>Direction</th><th>Use</th></tr></thead><tbody><tr><td><code>_wrapper_bridge</code></td><td>code → wrapper</td><td>serve handlers, frameworks, jobs</td></tr><tr><td><code>_bot_bridge</code></td><td>code → bot</td><td>bot/gateway CLI routing</td></tr><tr><td><code>_train_bridge</code></td><td>code → train</td><td>train CLI routing</td></tr><tr><td><code>_browser_bridge</code></td><td>code → browser</td><td>browser CLI routing</td></tr><tr><td><code>_mcp_bridge</code></td><td>code → mcp</td><td>mcp CLI routing</td></tr><tr><td><code>_code_bridge</code></td><td>tier-2 → code</td><td>config kernel, legacy dispatch</td></tr><tr><td><code>_wrapper_bridge</code></td><td>tier-2 → wrapper</td><td>capabilities, recipe, jobs/UI</td></tr></tbody></table></figure>
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<!-- wp:heading -->
<h2 class="wp-block-heading">When to use wrapper vs a Tier-2 package alone</h2>
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<!-- wp:table -->
<figure class="wp-block-table"><table><thead><tr><th>Your goal</th><th>Install</th></tr></thead><tbody><tr><td>Only terminal agents</td><td><code>praisonai-code</code> (+ optional <code>praisonaiagents</code>)</td></tr><tr><td>Only bots on Telegram/Slack</td><td><code>praisonai-bot</code></td></tr><tr><td>Only train / fine-tune</td><td><code>praisonai-train</code></td></tr><tr><td>Only automate browser</td><td><code>praisonai-browser</code></td></tr><tr><td>Only MCP server for IDE</td><td><code>praisonai-mcp</code></td></tr><tr><td>Several of the above + serve / dashboard / framework YAML</td><td><code>pip install praisonai</code></td></tr></tbody></table></figure>
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<h2 class="wp-block-heading">What stays in wrapper (not extracted)</h2>
<!-- /wp:heading -->
<!-- wp:table -->
<figure class="wp-block-table"><table><thead><tr><th>Surface</th><th>Why it stays</th></tr></thead><tbody><tr><td><code>dashboard</code> / <code>flow</code> / <code>ui</code></td><td>Langflow extra + launcher glue — not a standalone PyPI product</td></tr><tr><td><code>claw</code></td><td>Default app lives in <code>praisonai-bot</code>; wrapper is a thin shim</td></tr><tr><td><code>framework_adapters/</code></td><td>Thin registry; heavy impls in external PraisonAI-Frameworks</td></tr><tr><td><code>schedule</code> CLI</td><td>Three-layer split: agents store + wrapper CLI + bot executor</td></tr><tr><td><code>serve</code> / <code>recipe</code> / <code>jobs</code></td><td>~14k LOC deferred epic — high coupling (C15)</td></tr><tr><td><code>sandbox</code> / <code>deploy</code></td><td>Still in wrapper today; C13 extraction candidates</td></tr><tr><td><code>standardise</code> / suite runner</td><td>Maintainer/docs tooling — internal only</td></tr><tr><td><code>persist</code> / enterprise adapters</td><td><strong>Rejected</strong> — agents already ship File/SQLite defaults; no crisp standalone story</td></tr></tbody></table></figure>
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<h2 class="wp-block-heading">Roadmap — C13+ candidates</h2>
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<!-- wp:table -->
<figure class="wp-block-table"><table><thead><tr><th>Package</th><th>Status</th><th>Choose when…</th><th>Standalone install (planned)</th></tr></thead><tbody><tr><td><code>praisonai-sandbox</code></td><td><strong>C13 preferred</strong> (execution goal)</td><td>Isolated agent code execution — Docker/E2B/Modal/Daytona/Sandlock</td><td><code>pip install praisonai-sandbox[docker]</code></td></tr><tr><td><code>praisonai-deploy</code></td><td><strong>C13 alt</strong> (deploy goal)</td><td>Ship <code>agents.yaml</code> to Docker/AWS/GCP/Azure</td><td><code>pip install praisonai-deploy</code></td></tr><tr><td><code>praisonai-replay</code></td><td>Conditional C14+</td><td>Deterministic replay from run ledger / traces</td><td>After product sign-off</td></tr><tr><td><code>praisonai-serve</code></td><td>Deferred C15</td><td>HTTP API hosting without full umbrella (~14k LOC)</td><td>With recipe/jobs decision</td></tr><tr><td><code>praisonai-recipe</code></td><td>Deferred</td><td>NL → agent YAML without jobs UI</td><td>Tied to jobs + serve</td></tr><tr><td><code>praisonai-jobs</code></td><td>Deferred</td><td>Async long-running agent jobs API</td><td>Extract with serve or stay wrapper</td></tr></tbody></table></figure>
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<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>
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<!-- 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>
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<!-- wp:heading -->
<h2 class="wp-block-heading">When to use which tier</h2>
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<!-- wp:table -->
<figure class="wp-block-table"><table><thead><tr><th>Scenario</th><th>Install</th></tr></thead><tbody><tr><td>Pure Python agents, minimal deps</td><td><code>pip install praisonaiagents</code></td></tr><tr><td>Terminal coding agent, CI, headless</td><td><code>pip install praisonai-code</code></td></tr><tr><td>Telegram/Discord gateway only</td><td><code>pip install "praisonai-bot[gateway,bot]"</code></td></tr><tr><td>Agent training (no GPU)</td><td><code>pip install praisonai-train</code></td></tr><tr><td>LLM fine-tuning (GPU)</td><td><code>pip install "praisonai-train[llm]"</code></td></tr><tr><td>MCP server for Cursor/Claude</td><td><code>pip install "praisonai-mcp[all]"</code></td></tr><tr><td>Browser automation (extension/CDP)</td><td><code>pip install "praisonai-browser[all]"</code></td></tr><tr><td>CrewAI/AutoGen YAML</td><td><code>pip install "praisonai[crewai]"</code></td></tr><tr><td>Full ops + channels + dashboard</td><td><code>pip install "praisonai[claw]"</code></td></tr><tr><td>Everything in one install</td><td><code>pip install praisonai</code></td></tr><tr><td>Library author / embedding</td><td><code>praisonaiagents</code> only</td></tr></tbody></table></figure>
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<!-- wp:heading -->
<h2 class="wp-block-heading">Seven-package publish order</h2>
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<!-- 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>
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<!-- 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>
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<!-- 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.
@@ -1,5 +1,5 @@
name: Install PraisonAI monorepo packages
description: Install praisonai-agents, praisonai-code, praisonai-bot, praisonai-train, praisonai-browser, praisonai-mcp, praisonai-sandbox, praisonai-deploy, and praisonai wrapper from local paths (mirrors PyPI nine-package install order).
description: Install praisonai-agents, praisonai-code, praisonai-bot, praisonai-train, praisonai-browser, praisonai-mcp, praisonai-sandbox, and praisonai wrapper from local paths (mirrors PyPI eight-package install order).
inputs:
repo-root:
@@ -40,7 +40,6 @@ runs:
BROWSER_PKG="${BASE}src/praisonai-browser"
MCP_PKG="${BASE}src/praisonai-mcp"
SANDBOX_PKG="${BASE}src/praisonai-sandbox"
DEPLOY_PKG="${BASE}src/praisonai-deploy"
WRAPPER_PKG="${BASE}src/praisonai"
normalise_extras() {
@@ -70,8 +69,6 @@ runs:
uv pip install --system -e .
cd "$SANDBOX_PKG"
uv pip install --system -e .
cd "$DEPLOY_PKG"
uv pip install --system -e .
cd "$WRAPPER_PKG"
uv pip install --system "${WRAPPER_SUFFIX}"
else
@@ -89,8 +86,6 @@ runs:
pip install -e .
cd "$SANDBOX_PKG"
pip install -e .
cd "$DEPLOY_PKG"
pip install -e .
cd "$WRAPPER_PKG"
pip install -e "${WRAPPER_SUFFIX}"
fi
+2 -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) {
-39
View File
@@ -272,16 +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);
@@ -297,33 +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);
process.exit(failed ? 1 : 0);
+9 -139
View File
@@ -17,8 +17,7 @@ const PR_MAX_AUTO_FILES = 30;
const MANUAL_ONLY_LABELS = new Set(['security', 'breaking-change', 'needs-manual-review', 'release']);
const WORKFLOW_ONLY_LABEL = 'merge-gate-ci-only';
const CI_ONLY_PATH_PREFIXES = ['.github/workflows/', '.github/actions/', '.github/scripts/merge-gate'];
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)\//,
@@ -27,17 +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}/,
@@ -85,11 +74,7 @@ function isClaudeTriggerNoise(c) {
function isClaudeFinalReplyComment(c) {
const login = (c.user?.login || '').toLowerCase();
const fromAutomation =
login.includes('praisonai-triage') ||
login.includes('github-actions') ||
AUTO_ACTORS.some((a) => a.toLowerCase() === login);
if (!fromAutomation) return false;
if (!login.includes('praisonai-triage')) return false;
return (c.body || '').includes('Claude finished');
}
@@ -111,47 +96,15 @@ function isConflictRebaseTriggerComment(c) {
function isConflictRebaseCompletionComment(c) {
const login = (c.user?.login || '').toLowerCase();
const fromAutomation =
login.includes('praisonai-triage') ||
login.includes('github-actions') ||
AUTO_ACTORS.some((a) => a.toLowerCase() === login);
if (!fromAutomation) return false;
if (!login.includes('praisonai-triage') && !login.includes('github-actions')) return false;
const body = (c.body || '').toLowerCase();
return (
body.includes('rebase complete') ||
body.includes('rebase onto') ||
body.includes('force-pushed') ||
(body.includes('conflict') && body.includes('resolved'))
);
}
/** HEAD landed after conflict rebase but no FINAL @claude since that push. */
function needsFinalReReviewAfterConflictRebase(comments, headPushedAt) {
if (!headPushedAt) return false;
const headTime = new Date(headPushedAt).getTime();
const conflictTriggers = comments.filter(isConflictRebaseTriggerComment);
if (conflictTriggers.length === 0) return false;
const latestConflict = conflictTriggers.reduce((a, b) =>
new Date(a.created_at) > new Date(b.created_at) ? a : b
);
const conflictTime = new Date(latestConflict.created_at).getTime();
if (headTime <= conflictTime) return false;
const rebaseDone = comments.some(
(c) =>
new Date(c.created_at).getTime() > conflictTime && isConflictRebaseCompletionComment(c)
);
if (!rebaseDone) return false;
const finalsAfterHead = comments.filter(
(c) =>
isFinalClaudeTriggerComment(c) &&
new Date(c.created_at).getTime() >= headTime - 60000
);
return finalsAfterHead.length === 0;
}
function conflictRebaseQuiescent(comments, headPushedAt) {
const conflictTriggers = comments.filter(isConflictRebaseTriggerComment);
if (conflictTriggers.length === 0) return true;
@@ -292,9 +245,6 @@ function shouldSkipStaleFinalRecovery(comments, headPushedAt, headPusherLogin =
if (headPusherLogin && isClaudeAutomationLogin(headPusherLogin)) {
return { skip: true, reason: 'head pushed by Claude automation' };
}
if (needsFinalReReviewAfterConflictRebase(comments, headPushedAt)) {
return { skip: false, reason: '' };
}
if (isPushSoonAfterLatestFinal(comments, headPushedAt)) {
return {
skip: true,
@@ -319,7 +269,7 @@ function finalClaudeCompletedOnSha(comments, headPushedAt) {
}
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/\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 = `
@@ -475,61 +425,6 @@ 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;
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 ${maxPending})`;
}
return null;
}
// workflow_run probes (auto-dispatch) share concurrency and must not count
// toward backpressure — they blocked dispatches for merge-ready PRs.
function countSubstantiveMergeGateRuns(runs) {
return (runs || []).filter((r) => r && r.event !== 'workflow_run').length;
}
async function countPendingMergeGateRuns(github, owner, repo) {
let pending = 0;
for (const status of ['queued', 'in_progress']) {
try {
const { data } = await github.rest.actions.listWorkflowRuns({
owner,
repo,
workflow_id: MERGE_GATE_WORKFLOW_FILE,
status,
per_page: 30,
});
pending += countSubstantiveMergeGateRuns(data.workflow_runs);
} catch {
// Best-effort backpressure only.
}
}
return pending;
}
async function shouldSkipMergeGateDispatch(github, owner, repo, prNumber, core, options = {}) {
const maxPending = options.maxPending ?? MAX_PENDING_MERGE_GATE_RUNS;
const ctx = await loadPrContext(github, owner, repo, prNumber);
const pendingRuns = await countPendingMergeGateRuns(github, owner, repo);
const reason = mergeGateDispatchBlockedReason({
labels: ctx.labels,
pendingRuns,
maxPending,
});
if (reason) {
core?.info?.(`Skip merge gate dispatch for PR #${prNumber}: ${reason}`);
return true;
}
return false;
}
async function hasInProgressClaudeAssistant(github, owner, repo, prNumber = null) {
try {
const { data } = await github.rest.actions.listWorkflowRuns({
@@ -693,35 +588,18 @@ function prSizeReasons(files) {
}
function missingTestsReason(files) {
const pySdkAdds = files.filter(
const sdkAdds = files.filter(
(f) =>
f.filename.startsWith('src/praisonai-agents/') &&
f.filename.endsWith('.py') &&
!f.filename.endsWith('__init__.py') &&
(f.additions || 0) > 0
);
const tsSdkAdds = files.filter(
(f) =>
f.filename.startsWith(TS_SDK_SOURCE_PREFIX) &&
f.filename.endsWith('.ts') &&
!f.filename.endsWith('.d.ts') &&
(f.additions || 0) > 0
);
if (pySdkAdds.length === 0 && tsSdkAdds.length === 0) return null;
const hasPyTestChange = files.some(
if (sdkAdds.length === 0) return null;
const hasTestChange = files.some(
(f) => /\/tests?\//.test(f.filename) || /test_.*\.py$/.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;
}
@@ -1038,7 +916,6 @@ module.exports = {
hasRecentConflictComment,
isConflictRebaseTriggerComment,
isConflictRebaseCompletionComment,
needsFinalReReviewAfterConflictRebase,
conflictRebaseQuiescent,
hasHumanChangesRequested,
hasAnyChangesRequested,
@@ -1096,11 +973,4 @@ module.exports = {
isAutomatedFallbackVerdict,
AUTOMATED_FALLBACK_MARKER,
findMergeGateVerdict,
MERGE_GATE_WORKFLOW_FILE,
MERGE_GATE_ACTIVE_LABEL,
MAX_PENDING_MERGE_GATE_RUNS,
mergeGateDispatchBlockedReason,
countSubstantiveMergeGateRuns,
countPendingMergeGateRuns,
shouldSkipMergeGateDispatch,
};
+2 -2
View File
@@ -181,10 +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({
+22 -87
View File
@@ -11,112 +11,47 @@ assert.ok(versions.currentCode);
assert.ok(versions.currentWrapper);
assert.ok(versions.targetCode);
assert.ok(rg.PACKAGE_PATHS.includes('src/praisonai-code'));
// Every released package must make the gate's path-change check eligible.
for (const p of [
'src/praisonai', 'src/praisonai-agents', 'src/praisonai-code',
'src/praisonai-bot', 'src/praisonai-train', 'src/praisonai-browser',
'src/praisonai-mcp', 'src/praisonai-sandbox', 'src/praisonai-deploy',
]) {
assert.ok(rg.PACKAGE_PATHS.includes(p), `PACKAGE_PATHS missing ${p}`);
}
const noonUtc = new Date('2026-07-08T12:00:00Z');
const dayStart = rg.utcDayStart(noonUtc);
assert.strictEqual(dayStart.toISOString(), '2026-07-08T00:00:00.000Z');
function mockGithub({ runs = [], releases = [] } = {}) {
return {
rest: {
actions: {
listWorkflowRuns: async () => ({ data: { workflow_runs: runs } }),
},
repos: {
listReleases: async () => ({ data: releases }),
},
},
};
}
(async () => {
assert.strictEqual(await rg.pypiVersionExists('praisonaiagents', '0.0.0'), false);
assert.strictEqual(rg.PATCH_RELEASE_INTERVAL_DAYS, 3);
// Dedupe is release-based: a v* release inside the window blocks…
const recentRelease = mockGithub({
releases: [{ tag_name: 'v4.6.159', published_at: '2026-07-08T09:00:00Z' }],
});
const mockGithub = {
rest: {
actions: {
listWorkflowRuns: async () => ({
data: {
workflow_runs: [
{
conclusion: 'success',
created_at: '2026-07-08T09:00:00Z',
status: 'completed',
},
],
},
}),
},
},
};
assert.strictEqual(
await rg.hasSuccessfulReleaseWithinDays(recentRelease, 'o', 'r', noonUtc),
await rg.hasSuccessfulReleaseToday(mockGithub, 'o', 'r', noonUtc),
true
);
const result = await rg.evaluateReleasePreflight(
recentRelease, 'o', 'r',
mockGithub, 'o', 'r',
{ headSha: 'abc', isCiTrigger: false, bump: 'patch', now: noonUtc },
null
);
assert.ok(result.reasons.some((r) => r.includes('every 3 days')));
// …an old release does not…
const oldRelease = mockGithub({
releases: [{ tag_name: 'v4.6.150', published_at: '2026-07-04T09:00:00Z' }],
});
assert.strictEqual(
await rg.hasSuccessfulReleaseWithinDays(oldRelease, 'o', 'r', noonUtc),
false
);
// …and a dry-run "success" (workflow run, no release) does not consume the
// window: only real releases count.
const dryRunOnly = mockGithub({
runs: [{ conclusion: 'success', created_at: '2026-07-08T09:00:00Z', status: 'completed' }],
releases: [],
});
assert.strictEqual(
await rg.hasSuccessfulReleaseWithinDays(dryRunOnly, 'o', 'r', noonUtc),
false
);
// Active-run blocking: fresh waiting run blocks…
const freshWaiting = mockGithub({
runs: [{ status: 'waiting', conclusion: null, created_at: '2026-07-08T11:00:00Z', html_url: 'x' }],
});
assert.strictEqual(
await rg.hasActiveReleaseRun(freshWaiting, 'o', 'r', noonUtc, null),
true
);
// …a waiting run stuck longer than STALE_WAITING_HOURS no longer blocks…
const staleWaiting = mockGithub({
runs: [{ status: 'waiting', conclusion: null, created_at: '2026-07-08T01:00:00Z', html_url: 'x' }],
});
const warnings = [];
const fakeCore = { warning: (m) => warnings.push(m), info: () => {} };
assert.strictEqual(rg.STALE_WAITING_HOURS, 6);
assert.strictEqual(
await rg.hasActiveReleaseRun(staleWaiting, 'o', 'r', noonUtc, fakeCore),
false
);
assert.ok(warnings.length === 1 && warnings[0].includes('approve or cancel'));
// …but an in_progress run always blocks regardless of age.
const oldInProgress = mockGithub({
runs: [{ status: 'in_progress', conclusion: null, created_at: '2026-07-07T01:00:00Z', html_url: 'x' }],
});
assert.strictEqual(
await rg.hasActiveReleaseRun(oldInProgress, 'o', 'r', noonUtc, null),
true
);
assert.ok(result.reasons.some((r) => r.includes('already released today')));
console.log('ok: bumpPatch');
console.log('ok: readVersionsFromTree');
console.log('ok: PACKAGE_PATHS covers all 9 released packages');
console.log('ok: pypiVersionExists missing version');
console.log('ok: utcDayStart');
console.log('ok: release-based dedupe (recent blocks, old does not)');
console.log('ok: dry-run success does not consume the release window');
console.log('ok: 3-day dedupe blocks second release');
console.log('ok: fresh waiting run blocks; stale waiting run ignored with warning');
console.log('ok: in_progress always blocks');
console.log('ok: hasSuccessfulReleaseToday');
console.log('ok: daily dedupe blocks second release');
})();
+20 -105
View File
@@ -4,31 +4,10 @@
const https = require('https');
/** Every directory whose changes should make a release eligible — all nine
* published packages (mirrors the skip_* inputs in pypi-release.yml). */
const PACKAGE_PATHS = [
'src/praisonai',
'src/praisonai-agents',
'src/praisonai-code',
'src/praisonai-bot',
'src/praisonai-train',
'src/praisonai-browser',
'src/praisonai-mcp',
'src/praisonai-sandbox',
'src/praisonai-deploy',
];
/** Minimum days between successful patch auto-releases. */
const PATCH_RELEASE_INTERVAL_DAYS = 3;
const PACKAGE_PATHS = ['src/praisonai', 'src/praisonai-agents', 'src/praisonai-code'];
const ACTIVE_RELEASE_STATUSES = new Set([
'queued', 'in_progress', 'waiting', 'pending', 'requested',
]);
/** A run stuck in `waiting` (environment approval) longer than this no longer
* blocks the gate. GitHub only auto-fails unapproved deployments after 30
* days, so without a cutoff one forgotten manual dispatch stalls all
* auto-releases for up to a month. The run is warned about, never cancelled —
* if later approved, the pypi-release concurrency group serializes it and its
* pypi_exists checks no-op anything already published. */
const STALE_WAITING_HOURS = 6;
function bumpPatch(version) {
const parts = version.split('.');
@@ -84,65 +63,36 @@ function pypiVersionExists(packageName, version) {
});
}
async function hasActiveReleaseRun(github, owner, repo, now = new Date(), core = null) {
async function hasActiveReleaseRun(github, owner, repo) {
const runs = await github.rest.actions.listWorkflowRuns({
owner,
repo,
workflow_id: 'pypi-release.yml',
per_page: 20,
});
const staleCutoff = now.getTime() - STALE_WAITING_HOURS * 60 * 60 * 1000;
return runs.data.workflow_runs.some((r) => {
if (!ACTIVE_RELEASE_STATUSES.has(r.status) || r.conclusion) return false;
if (r.status === 'waiting' && new Date(r.created_at).getTime() < staleCutoff) {
if (core) {
core.warning(
`Ignoring release run waiting >${STALE_WAITING_HOURS}h for environment approval: `
+ `${r.html_url} — approve or cancel it. It no longer blocks auto-releases.`
);
}
return false;
}
return true;
});
return runs.data.workflow_runs.some(
(r) => ACTIVE_RELEASE_STATUSES.has(r.status) && !r.conclusion
);
}
function utcDayStart(now = new Date()) {
return new Date(Date.UTC(now.getUTCFullYear(), now.getUTCMonth(), now.getUTCDate()));
}
function releaseIntervalStart(now = new Date(), intervalDays = PATCH_RELEASE_INTERVAL_DAYS) {
return new Date(now.getTime() - intervalDays * 24 * 60 * 60 * 1000);
}
async function hasSuccessfulReleaseWithinDays(
github,
owner,
repo,
now = new Date(),
intervalDays = PATCH_RELEASE_INTERVAL_DAYS,
) {
const windowStart = releaseIntervalStart(now, intervalDays);
// Dedupe on GitHub releases (v* tags) rather than run conclusions: a
// dry_run=true dispatch concludes 'success' without publishing anything and
// must not consume the release window. Only a real full release creates a
// v* GitHub release (bump_and_release.py's `gh release create`).
const releases = await github.rest.repos.listReleases({
async function hasSuccessfulReleaseToday(github, owner, repo, now = new Date()) {
const dayStart = utcDayStart(now);
const runs = await github.rest.actions.listWorkflowRuns({
owner,
repo,
per_page: 10,
workflow_id: 'pypi-release.yml',
status: 'completed',
per_page: 30,
});
return releases.data.some(
(r) => r.tag_name && r.tag_name.startsWith('v')
&& new Date(r.published_at || r.created_at) >= windowStart
return runs.data.workflow_runs.some(
(r) => r.conclusion === 'success' && new Date(r.created_at) >= dayStart
);
}
/** @deprecated Use hasSuccessfulReleaseWithinDays — kept for selftests. */
async function hasSuccessfulReleaseToday(github, owner, repo, now = new Date()) {
return hasSuccessfulReleaseWithinDays(github, owner, repo, now, 1);
}
async function lastGreenCoreTestsSha(github, owner, repo) {
const runs = await github.rest.actions.listWorkflowRuns({
owner,
@@ -179,18 +129,15 @@ async function evaluateReleasePreflight(github, owner, repo, options, core) {
return out;
}
const referenceTime = options.now instanceof Date ? options.now : new Date();
if (await hasActiveReleaseRun(github, owner, repo, referenceTime, core)) {
if (await hasActiveReleaseRun(github, owner, repo)) {
reasons.push('PyPI Release already in progress or awaiting approval');
return out;
}
if (await hasSuccessfulReleaseWithinDays(github, owner, repo, referenceTime)) {
reasons.push(
`already released within last ${PATCH_RELEASE_INTERVAL_DAYS} days; `
+ `max one patch release every ${PATCH_RELEASE_INTERVAL_DAYS} days`
);
const referenceTime = options.now instanceof Date ? options.now : new Date();
if (await hasSuccessfulReleaseToday(github, owner, repo, referenceTime)) {
const day = referenceTime.toISOString().slice(0, 10);
reasons.push(`already released today (UTC ${day}); max one patch release per day`);
return out;
}
@@ -260,35 +207,8 @@ async function evaluateReleasePreflight(github, owner, repo, options, core) {
out.headSha = evalSha;
const greenSha = await lastGreenCoreTestsSha(github, owner, repo);
if (greenSha !== evalSha) {
// Core Tests has path filters and honors [skip ci] (the release
// safety-net commit uses it), so the tip of main may legitimately have
// no Core Tests run of its own — e.g. a docs-only commit, or the
// "chore(release): … [skip ci]" commit right after a release. Accept a
// green ancestor when nothing under the released package paths changed
// after it; otherwise the cron path stalls until the next src/** push.
let greenAncestorOk = false;
if (greenSha && /^[0-9a-f]{40}$/.test(greenSha)) {
try {
execSync(`git merge-base --is-ancestor ${greenSha} ${evalSha}`);
const delta = execSync(
`git diff --name-only ${greenSha} ${evalSha} -- ${PACKAGE_PATHS.join(' ')}`,
{ encoding: 'utf8' }
).trim();
greenAncestorOk = delta === '';
} catch {
greenAncestorOk = false;
}
}
if (!greenAncestorOk) {
reasons.push(`CI not green on HEAD (last green: ${greenSha ? greenSha.slice(0, 7) : 'none'})`);
return out;
}
if (core) {
core.info(
`HEAD ${evalSha.slice(0, 7)} has no Core Tests run; accepting green ancestor `
+ `${greenSha.slice(0, 7)} (no package-path changes since).`
);
}
reasons.push(`CI not green on HEAD (last green: ${greenSha ? greenSha.slice(0, 7) : 'none'})`);
return out;
}
}
@@ -302,11 +222,6 @@ module.exports = {
bumpPatch,
readVersionsFromTree,
pypiVersionExists,
PATCH_RELEASE_INTERVAL_DAYS,
STALE_WAITING_HOURS,
releaseIntervalStart,
hasActiveReleaseRun,
hasSuccessfulReleaseWithinDays,
hasSuccessfulReleaseToday,
utcDayStart,
evaluateReleasePreflight,
+1 -1
View File
@@ -42,5 +42,5 @@ jobs:
issue_number: context.issue.number,
owner: context.repo.owner,
repo: context.repo.repo,
body: '🤖 Auto-triaging with Claude. Analyzing issue and implementing a fix...\n\nClaude will:\n1. Route correctly: TypeScript → src/praisonai-ts/; agent tools → PraisonAI-Tools; lifecycle plugins → PraisonAI-Plugins\n2. Search codebase for root cause\n3. Implement a minimal fix following AGENTS.md\n4. Create a PR with the changes'
body: '🤖 Auto-triaging with Claude. Analyzing issue and implementing a fix...\n\nClaude will:\n1. Route correctly: agent tools → PraisonAI-Tools; lifecycle plugins → PraisonAI-Plugins\n2. Search codebase for root cause\n3. Implement a minimal fix following AGENTS.md\n4. Create a PR with the changes'
});
+2 -7
View File
@@ -33,8 +33,7 @@ on:
- claude-merge-gate
concurrency:
# Serialize workflow_run auto-dispatches (Core Tests / Claude Assistant fan-out).
group: claude-merge-gate-${{ 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,
@@ -293,7 +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).
+9 -16
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,
@@ -294,7 +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):
@@ -306,7 +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.
@@ -338,11 +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
@@ -355,8 +351,6 @@ jobs:
Bash(conda:*)
Bash(pytest:*)
Bash(gh:*)
Bash(npm:*)
Bash(node:*)
Bash(python -m pytest:*)
Bash(python -m pip:*)
Bash(poetry:*)
@@ -376,10 +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
-212
View File
@@ -1,212 +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/**'
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: ${{ matrix.node }}
cache: npm
cache-dependency-path: src/praisonai-mobile/package-lock.json
- run: npm ci
- name: Typecheck
run: npm run typecheck
- name: Layer boundaries
run: npm run boundaries
- name: Tests
run: npm test
- name: Bundle gate fixtures
# Runs the gate's own suite, which proves each check can FAIL -- a
# build check that has only ever seen clean input is a check nobody
# knows the state of.
run: npm run test:bundle
upstream-parity:
name: upstream parity
# Its own job so drift from the real Agent is visible in the checks list
# rather than buried in another job's log.
#
# It needs only THIS package's install. praisonai-ts's own dependencies are
# neither needed nor installable -- `npm install` there fails with an
# ERESOLVE peer conflict (bedrock-agentcore -> @strands-agents/sdk) -- and
# every member the check looks at is declared locally in simple.ts. That is
# verified rather than assumed: with praisonai-ts's node_modules moved
# aside, injected drift is still caught as TS2741.
runs-on: ubuntu-22.04
steps:
- uses: actions/checkout@v4
- uses: actions/setup-node@v4
with:
node-version: '22.18'
cache: npm
cache-dependency-path: src/praisonai-mobile/package-lock.json
- run: npm ci
- name: Does the real Agent still satisfy PraisonAgent?
# Skips loudly if the praisonai-ts checkout is missing, rather than
# passing quietly -- a check that silently stops covering anything is
# worse than no check.
run: npm run check:upstream
shell:
name: rust shell (${{ 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.
- 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.
- 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 }}
+4 -8
View File
@@ -1,12 +1,12 @@
name: Nightly Release Gate
# Preflight before PyPI Release (patch bump).
# Triggers: Core Tests success on main (workflow_run) or cron every 3 days at 00:00 UTC.
# Dedupe: max one successful patch release every 3 days (see release-gate.js).
# Triggers: Core Tests success on main (workflow_run) or nightly cron at 00:00 UTC.
# Dedupe: max one successful patch release per UTC day (see release-gate.js).
on:
schedule:
- cron: '0 0 */3 * *'
- cron: '0 0 * * *'
workflow_dispatch:
inputs:
dry_run:
@@ -41,7 +41,7 @@ jobs:
github.event.workflow_run.head_branch == 'main' &&
github.event.workflow_run.event == 'push' &&
!startsWith(github.event.workflow_run.head_commit.message, 'Release v') &&
!startsWith(github.event.workflow_run.head_commit.message, 'chore(release):')
!startsWith(github.event.workflow_run.head_commit.message, 'Bump praisonai')
)
runs-on: ubuntu-latest
env:
@@ -69,10 +69,6 @@ jobs:
- name: Fetch main and tags
run: git fetch --tags origin main
# Guards the gate logic itself — no workflow ran these selftests before.
- name: Selftest release-gate script
run: node .github/scripts/release-gate-selftest.js
- name: Preflight — path changes, CI SHA, dedupe
id: preflight
uses: actions/github-script@v7
-79
View File
@@ -1,79 +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.
# 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/**'
- 'src/praisonai-ts/PARITY.md'
- 'src/praisonai-ts/FEATURE_PARITY_TRACKER.json'
- 'src/praisonai-ts/SIGNATURE_PARITY.md'
- 'src/praisonai-ts/signature-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" >> "$GITHUB_ENV"
- name: Signatures match, or are waived with a reason
env:
PYTHONPATH: src/praisonai
run: |
if ! python3 -m praisonai._dev.parity.signatures --check; then
echo "::error::Signature parity failed. See the output above for the surface and parameter. Fix the TypeScript side, or add a waiver with a reason to src/praisonai/praisonai/_dev/parity/signatures/waivers.yaml, then run: PYTHONPATH=src/praisonai python3 -m praisonai._dev.parity.signatures --write"
exit 1
fi
@@ -1,62 +0,0 @@
# Can praisonai-ts still be loaded in a webview?
#
# Issue #4437 was this failing: `crypto` and `events` were static imports on
# the Agent graph, so a webview bundle died at IMPORT time with no error
# boundary and a blank screen. PR #4438 fixed it, and nothing stopped it
# coming back.
#
# `npm test` cannot catch a regression here, structurally: it runs in Node,
# where every one of these imports works perfectly. One `import { x } from
# "fs"` added to a file the Agent happens to reach would silently un-ship the
# mobile app, and the first signal would be a blank screen on a device.
#
# Deliberately narrow. It runs only when praisonai-ts changes, installs only
# what it needs, and asserts one thing.
name: praisonai-ts webview
on:
push:
branches: [main]
paths:
- 'src/praisonai-ts/src/**'
- 'src/praisonai-ts/package.json'
- 'src/praisonai-ts/scripts/webview-gate.mjs'
- '.github/workflows/praisonai-ts-webview.yml'
pull_request:
paths:
- 'src/praisonai-ts/src/**'
- 'src/praisonai-ts/package.json'
- 'src/praisonai-ts/scripts/webview-gate.mjs'
- '.github/workflows/praisonai-ts-webview.yml'
concurrency:
group: praisonai-ts-webview-${{ 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
+170 -427
View File
@@ -61,29 +61,6 @@ on:
required: false
default: false
type: boolean
skip_deploy:
description: 'Skip praisonai-deploy publish (recovery if already on PyPI)'
required: false
default: false
type: boolean
# NOTE: GitHub caps workflow_dispatch at 25 top-level inputs; this
# workflow has 23. Adding a 10th package (skip_* + *_version) hits 25.
only:
description: 'Release ONLY this package (forces skip on all others); all = no restriction'
required: false
default: all
type: choice
options:
- all
- agents
- code
- bot
- train
- browser
- mcp
- sandbox
- deploy
- wrapper
agents_version:
description: 'Override agents version (empty = auto bump from pyproject.toml)'
required: false
@@ -124,11 +101,6 @@ on:
required: false
default: ''
type: string
deploy_version:
description: 'Override praisonai-deploy version (empty = auto bump from pyproject.toml)'
required: false
default: ''
type: string
source:
description: 'Trigger source (audit trail)'
required: false
@@ -162,35 +134,15 @@ jobs:
'pypi-auto' || 'pypi'
}}
env:
# PyPI API token auth: username __token__, password = pypi-… token (see pypi.org/help/#invalid-auth)
UV_PUBLISH_USERNAME: __token__
UV_PUBLISH_PASSWORD: ${{ secrets.PYPI_TOKEN || secrets.PYPI_API_TOKEN }}
# GH_TOKEN is NOT set here: it is a GitHub App installation token minted in
# "Generate GitHub App token" and exported via $GITHUB_ENV, so releases are
# authored by praisonai-triage-agent[bot] rather than MervinPraison.
UV_PUBLISH_TOKEN: ${{ secrets.PYPI_TOKEN || secrets.PYPI_API_TOKEN }}
GH_TOKEN: ${{ secrets.GH_TOKEN }}
steps:
- name: Generate GitHub App token
id: app-token
uses: actions/create-github-app-token@v1
with:
app-id: ${{ secrets.CLAUDE_APP_ID }}
private-key: ${{ secrets.CLAUDE_APP_PRIVATE_KEY }}
owner: ${{ github.repository_owner }}
# Scope to this repo only. Without it the token is minted for every
# repository the owner has; this job never leaves PraisonAI (checkout,
# push to origin, and gh release create all target it).
repositories: ${{ github.event.repository.name }}
- name: Checkout main
uses: actions/checkout@34e114876b0b11c390a56381ad16ebd13914f8d5 # v4
with:
ref: main
fetch-depth: 0
token: ${{ steps.app-token.outputs.token }}
# Do not bake the token into .git/config: an http.extraheader would
# outrank the remote URL set in "Configure git" and pin this first
# (1h) token, defeating the refresh before the wrapper release.
persist-credentials: false
token: ${{ secrets.GH_TOKEN }}
- name: Set up Python
uses: actions/setup-python@a26af69be951a213d495a4c3e4e4022e16d87065 # v5
@@ -201,19 +153,10 @@ jobs:
uses: astral-sh/setup-uv@38f3f104447c67c051c4a08e39b64a148898af3a # v4
- name: Configure git
env:
APP_TOKEN: ${{ steps.app-token.outputs.token }}
REPO: ${{ github.repository }}
run: |
set -euo pipefail
git config user.name "praisonai-triage-agent[bot]"
git config user.email "272766704+praisonai-triage-agent[bot]@users.noreply.github.com"
# persist-credentials:false left the remote unauthenticated; push auth
# comes from the app token embedded here (masked in logs, and the
# token dies with the runner).
git remote set-url origin "https://x-access-token:${APP_TOKEN}@github.com/${REPO}.git"
echo "GH_TOKEN=${APP_TOKEN}" >> "$GITHUB_ENV"
GH_TOKEN="${APP_TOKEN}" gh auth setup-git
git config user.name "MervinPraison"
git config user.email "[email protected]"
gh auth setup-git
- name: Release summary
run: |
@@ -223,36 +166,6 @@ jobs:
echo "Dry run: ${{ inputs.dry_run }}"
echo "Environment: ${{ (inputs.source == 'ci' || inputs.source == 'nightly') && inputs.bump == 'patch' && 'pypi-auto' || 'pypi' }}"
# Single source of truth for which packages this run releases. `only`
# inverts into the skip flags here; everything downstream (version
# computation, PyPI detection, publish conditions) consumes these
# outputs, so a dedicated one-package release is one input instead of
# eight skip flags.
- name: Resolve effective skips
id: flags
env:
ONLY: ${{ inputs.only }}
SKIP_AGENTS: ${{ inputs.skip_agents }}
SKIP_CODE: ${{ inputs.skip_code }}
SKIP_BOT: ${{ inputs.skip_bot }}
SKIP_TRAIN: ${{ inputs.skip_train }}
SKIP_BROWSER: ${{ inputs.skip_browser }}
SKIP_MCP: ${{ inputs.skip_mcp }}
SKIP_SANDBOX: ${{ inputs.skip_sandbox }}
SKIP_DEPLOY: ${{ inputs.skip_deploy }}
SKIP_WRAPPER: ${{ inputs.skip_wrapper }}
run: |
set -euo pipefail
for pkg in agents code bot train browser mcp sandbox deploy wrapper; do
var="SKIP_$(echo "$pkg" | tr '[:lower:]' '[:upper:]')"
skip="${!var}"
if [ -n "${ONLY}" ] && [ "${ONLY}" != "all" ] && [ "${ONLY}" != "$pkg" ]; then
skip=true
fi
echo "skip_${pkg}=${skip}" >> "$GITHUB_OUTPUT"
echo "skip_${pkg}=${skip}"
done
- name: Compute release versions
id: versions
env:
@@ -265,15 +178,13 @@ jobs:
BROWSER_OVERRIDE: ${{ inputs.browser_version }}
MCP_OVERRIDE: ${{ inputs.mcp_version }}
SANDBOX_OVERRIDE: ${{ inputs.sandbox_version }}
DEPLOY_OVERRIDE: ${{ inputs.deploy_version }}
SKIP_AGENTS: ${{ steps.flags.outputs.skip_agents }}
SKIP_CODE: ${{ steps.flags.outputs.skip_code }}
SKIP_BOT: ${{ steps.flags.outputs.skip_bot }}
SKIP_TRAIN: ${{ steps.flags.outputs.skip_train }}
SKIP_BROWSER: ${{ steps.flags.outputs.skip_browser }}
SKIP_MCP: ${{ steps.flags.outputs.skip_mcp }}
SKIP_SANDBOX: ${{ steps.flags.outputs.skip_sandbox }}
SKIP_DEPLOY: ${{ steps.flags.outputs.skip_deploy }}
SKIP_AGENTS: ${{ inputs.skip_agents }}
SKIP_CODE: ${{ inputs.skip_code }}
SKIP_BOT: ${{ inputs.skip_bot }}
SKIP_TRAIN: ${{ inputs.skip_train }}
SKIP_BROWSER: ${{ inputs.skip_browser }}
SKIP_MCP: ${{ inputs.skip_mcp }}
SKIP_SANDBOX: ${{ inputs.skip_sandbox }}
run: |
python <<'PY'
import os
@@ -310,7 +221,6 @@ jobs:
browser_override = os.environ.get("BROWSER_OVERRIDE", "").strip()
mcp_override = os.environ.get("MCP_OVERRIDE", "").strip()
sandbox_override = os.environ.get("SANDBOX_OVERRIDE", "").strip()
deploy_override = os.environ.get("DEPLOY_OVERRIDE", "").strip()
validate_version("agents_version", agents_override)
validate_version("wrapper_version", wrapper_override)
validate_version("code_version", code_override)
@@ -319,7 +229,6 @@ jobs:
validate_version("browser_version", browser_override)
validate_version("mcp_version", mcp_override)
validate_version("sandbox_version", sandbox_override)
validate_version("deploy_version", deploy_override)
agents_pyproject = root / "src/praisonai-agents/pyproject.toml"
agents_content = agents_pyproject.read_text()
@@ -377,14 +286,6 @@ jobs:
sys.exit(1)
current_sandbox = sandbox_match.group(1)
deploy_pyproject = root / "src/praisonai-deploy/pyproject.toml"
deploy_content = deploy_pyproject.read_text()
deploy_match = re.search(r'^version\s*=\s*"([^"]+)"', deploy_content, re.MULTILINE)
if not deploy_match:
print("Could not read praisonai-deploy version from pyproject.toml", file=sys.stderr)
sys.exit(1)
current_deploy = deploy_match.group(1)
wrapper_version_py = root / "src/praisonai/praisonai/version.py"
wrapper_content = wrapper_version_py.read_text()
wrapper_match = re.search(r'__version__ = "([^"]+)"', wrapper_content)
@@ -401,7 +302,6 @@ jobs:
("browser", current_browser),
("mcp", current_mcp),
("sandbox", current_sandbox),
("deploy", current_deploy),
("wrapper", current_wrapper),
):
if not SEMVER.match(value):
@@ -415,7 +315,6 @@ jobs:
skip_browser = os.environ.get("SKIP_BROWSER", "false").lower() == "true"
skip_mcp = os.environ.get("SKIP_MCP", "false").lower() == "true"
skip_sandbox = os.environ.get("SKIP_SANDBOX", "false").lower() == "true"
skip_deploy = os.environ.get("SKIP_DEPLOY", "false").lower() == "true"
if agents_override:
agents_version = agents_override
@@ -466,13 +365,6 @@ jobs:
else:
sandbox_version = bump_version(current_sandbox)
if deploy_override:
deploy_version = deploy_override
elif skip_deploy:
deploy_version = current_deploy
else:
deploy_version = bump_version(current_deploy)
if wrapper_override:
wrapper_version = wrapper_override
else:
@@ -487,7 +379,6 @@ jobs:
fh.write(f"browser_version={browser_version}\n")
fh.write(f"mcp_version={mcp_version}\n")
fh.write(f"sandbox_version={sandbox_version}\n")
fh.write(f"deploy_version={deploy_version}\n")
fh.write(f"wrapper_version={wrapper_version}\n")
fh.write(f"current_agents={current_agents}\n")
fh.write(f"current_code={current_code}\n")
@@ -496,7 +387,6 @@ jobs:
fh.write(f"current_browser={current_browser}\n")
fh.write(f"current_mcp={current_mcp}\n")
fh.write(f"current_sandbox={current_sandbox}\n")
fh.write(f"current_deploy={current_deploy}\n")
fh.write(f"current_wrapper={current_wrapper}\n")
print(f"Agents: {current_agents} -> {agents_version}")
@@ -506,7 +396,6 @@ jobs:
print(f"Browser: {current_browser} -> {browser_version}")
print(f"MCP: {current_mcp} -> {mcp_version}")
print(f"Sandbox: {current_sandbox} -> {sandbox_version}")
print(f"Deploy: {current_deploy} -> {deploy_version}")
print(f"Wrapper: {current_wrapper} -> {wrapper_version}")
PY
@@ -521,17 +410,15 @@ jobs:
BROWSER_VERSION: ${{ steps.versions.outputs.browser_version }}
MCP_VERSION: ${{ steps.versions.outputs.mcp_version }}
SANDBOX_VERSION: ${{ steps.versions.outputs.sandbox_version }}
DEPLOY_VERSION: ${{ steps.versions.outputs.deploy_version }}
WRAPPER_VERSION: ${{ steps.versions.outputs.wrapper_version }}
INPUT_SKIP_AGENTS: ${{ steps.flags.outputs.skip_agents }}
INPUT_SKIP_CODE: ${{ steps.flags.outputs.skip_code }}
INPUT_SKIP_BOT: ${{ steps.flags.outputs.skip_bot }}
INPUT_SKIP_TRAIN: ${{ steps.flags.outputs.skip_train }}
INPUT_SKIP_BROWSER: ${{ steps.flags.outputs.skip_browser }}
INPUT_SKIP_MCP: ${{ steps.flags.outputs.skip_mcp }}
INPUT_SKIP_SANDBOX: ${{ steps.flags.outputs.skip_sandbox }}
INPUT_SKIP_DEPLOY: ${{ steps.flags.outputs.skip_deploy }}
INPUT_SKIP_WRAPPER: ${{ steps.flags.outputs.skip_wrapper }}
INPUT_SKIP_AGENTS: ${{ inputs.skip_agents }}
INPUT_SKIP_CODE: ${{ inputs.skip_code }}
INPUT_SKIP_BOT: ${{ inputs.skip_bot }}
INPUT_SKIP_TRAIN: ${{ inputs.skip_train }}
INPUT_SKIP_BROWSER: ${{ inputs.skip_browser }}
INPUT_SKIP_MCP: ${{ inputs.skip_mcp }}
INPUT_SKIP_SANDBOX: ${{ inputs.skip_sandbox }}
INPUT_SKIP_WRAPPER: ${{ inputs.skip_wrapper }}
run: |
set -euo pipefail
skip_agents="${INPUT_SKIP_AGENTS}"
@@ -541,53 +428,30 @@ jobs:
skip_browser="${INPUT_SKIP_BROWSER}"
skip_mcp="${INPUT_SKIP_MCP}"
skip_sandbox="${INPUT_SKIP_SANDBOX}"
skip_deploy="${INPUT_SKIP_DEPLOY}"
skip_wrapper="${INPUT_SKIP_WRAPPER}"
# Returns 0 if published, 1 if definitively absent (404). Any other
# HTTP status (PyPI outage, 5xx, rate limit) FAILS the run: guessing
# "not published" would lead to a duplicate-upload failure midway
# through the release, which is strictly worse than stopping here
# before anything has been published.
pypi_published() { # $1=package $2=version
local code attempt
for attempt in 1 2 3; do
code=$(curl -s -o /dev/null -w '%{http_code}' --max-time 30 \
"https://pypi.org/pypi/$1/$2/json" || echo "000")
case "$code" in
200) return 0 ;;
404) return 1 ;;
*) echo "PyPI check $1==$2 returned HTTP ${code} (attempt ${attempt}/3)"; sleep 5 ;;
esac
done
echo "❌ Cannot determine PyPI state for $1==$2; refusing to guess." >&2
exit 2
}
if [ "$skip_agents" != "true" ]; then
pypi_published praisonaiagents "${AGENTS_VERSION}" && skip_agents=true || true
curl -fsSL "https://pypi.org/pypi/praisonaiagents/${AGENTS_VERSION}/json" >/dev/null && skip_agents=true || true
fi
if [ "$skip_code" != "true" ]; then
pypi_published praisonai-code "${CODE_VERSION}" && skip_code=true || true
curl -fsSL "https://pypi.org/pypi/praisonai-code/${CODE_VERSION}/json" >/dev/null && skip_code=true || true
fi
if [ "$skip_bot" != "true" ]; then
pypi_published praisonai-bot "${BOT_VERSION}" && skip_bot=true || true
curl -fsSL "https://pypi.org/pypi/praisonai-bot/${BOT_VERSION}/json" >/dev/null && skip_bot=true || true
fi
if [ "$skip_train" != "true" ]; then
pypi_published praisonai-train "${TRAIN_VERSION}" && skip_train=true || true
curl -fsSL "https://pypi.org/pypi/praisonai-train/${TRAIN_VERSION}/json" >/dev/null && skip_train=true || true
fi
if [ "$skip_browser" != "true" ]; then
pypi_published praisonai-browser "${BROWSER_VERSION}" && skip_browser=true || true
curl -fsSL "https://pypi.org/pypi/praisonai-browser/${BROWSER_VERSION}/json" >/dev/null && skip_browser=true || true
fi
if [ "$skip_mcp" != "true" ]; then
pypi_published praisonai-mcp "${MCP_VERSION}" && skip_mcp=true || true
curl -fsSL "https://pypi.org/pypi/praisonai-mcp/${MCP_VERSION}/json" >/dev/null && skip_mcp=true || true
fi
if [ "$skip_sandbox" != "true" ]; then
pypi_published praisonai-sandbox "${SANDBOX_VERSION}" && skip_sandbox=true || true
fi
if [ "$skip_deploy" != "true" ]; then
pypi_published praisonai-deploy "${DEPLOY_VERSION}" && skip_deploy=true || true
curl -fsSL "https://pypi.org/pypi/praisonai-sandbox/${SANDBOX_VERSION}/json" >/dev/null && skip_sandbox=true || true
fi
if [ "$skip_wrapper" != "true" ]; then
pypi_published praisonai "${WRAPPER_VERSION}" && skip_wrapper=true || true
curl -fsSL "https://pypi.org/pypi/praisonai/${WRAPPER_VERSION}/json" >/dev/null && skip_wrapper=true || true
fi
echo "skip_agents=${skip_agents}" >> "$GITHUB_OUTPUT"
echo "skip_code=${skip_code}" >> "$GITHUB_OUTPUT"
@@ -596,9 +460,8 @@ jobs:
echo "skip_browser=${skip_browser}" >> "$GITHUB_OUTPUT"
echo "skip_mcp=${skip_mcp}" >> "$GITHUB_OUTPUT"
echo "skip_sandbox=${skip_sandbox}" >> "$GITHUB_OUTPUT"
echo "skip_deploy=${skip_deploy}" >> "$GITHUB_OUTPUT"
echo "skip_wrapper=${skip_wrapper}" >> "$GITHUB_OUTPUT"
if [ "$skip_agents" = "true" ] && [ "$skip_code" = "true" ] && [ "$skip_bot" = "true" ] && [ "$skip_train" = "true" ] && [ "$skip_browser" = "true" ] && [ "$skip_mcp" = "true" ] && [ "$skip_sandbox" = "true" ] && [ "$skip_deploy" = "true" ] && [ "$skip_wrapper" = "true" ]; then
if [ "$skip_agents" = "true" ] && [ "$skip_code" = "true" ] && [ "$skip_bot" = "true" ] && [ "$skip_train" = "true" ] && [ "$skip_browser" = "true" ] && [ "$skip_mcp" = "true" ] && [ "$skip_sandbox" = "true" ] && [ "$skip_wrapper" = "true" ]; then
echo "All target versions already on PyPI — nothing to publish."
fi
@@ -612,7 +475,6 @@ jobs:
steps.pypi_exists.outputs.skip_browser == 'true' &&
steps.pypi_exists.outputs.skip_mcp == 'true' &&
steps.pypi_exists.outputs.skip_sandbox == 'true' &&
steps.pypi_exists.outputs.skip_deploy == 'true' &&
steps.pypi_exists.outputs.skip_wrapper == 'true'
run: echo "Idempotent skip — target versions already on PyPI."
@@ -620,43 +482,34 @@ jobs:
if: inputs.dry_run
run: |
echo "Dry run — no publish, commit, or push."
echo "Only: ${{ inputs.only }}"
echo "Agents version: ${{ steps.versions.outputs.agents_version }}"
echo "Code version: ${{ steps.versions.outputs.code_version }}"
echo "Bot version: ${{ steps.versions.outputs.bot_version }}"
echo "Train version: ${{ steps.versions.outputs.train_version }}"
echo "Browser version: ${{ steps.versions.outputs.browser_version }}"
echo "MCP version: ${{ steps.versions.outputs.mcp_version }}"
echo "Sandbox version: ${{ steps.versions.outputs.sandbox_version }}"
echo "Deploy version: ${{ steps.versions.outputs.deploy_version }}"
echo "Wrapper version: ${{ steps.versions.outputs.wrapper_version }}"
echo ""
if [ "${{ steps.flags.outputs.skip_agents }}" != "true" ]; then
if [ "${{ inputs.skip_agents }}" != "true" ]; then
echo "Would publish praisonaiagents ${{ steps.versions.outputs.agents_version }}"
fi
if [ "${{ steps.flags.outputs.skip_code }}" != "true" ]; then
if [ "${{ inputs.skip_code }}" != "true" ]; then
echo "Would publish praisonai-code ${{ steps.versions.outputs.code_version }}"
fi
if [ "${{ steps.flags.outputs.skip_bot }}" != "true" ]; then
if [ "${{ inputs.skip_bot }}" != "true" ]; then
echo "Would publish praisonai-bot ${{ steps.versions.outputs.bot_version }}"
fi
if [ "${{ steps.flags.outputs.skip_train }}" != "true" ]; then
if [ "${{ inputs.skip_train }}" != "true" ]; then
echo "Would publish praisonai-train ${{ steps.versions.outputs.train_version }}"
fi
if [ "${{ steps.flags.outputs.skip_browser }}" != "true" ]; then
if [ "${{ inputs.skip_browser }}" != "true" ]; then
echo "Would publish praisonai-browser ${{ steps.versions.outputs.browser_version }}"
fi
if [ "${{ steps.flags.outputs.skip_mcp }}" != "true" ]; then
if [ "${{ inputs.skip_mcp }}" != "true" ]; then
echo "Would publish praisonai-mcp ${{ steps.versions.outputs.mcp_version }}"
fi
if [ "${{ steps.flags.outputs.skip_sandbox }}" != "true" ]; then
echo "Would publish praisonai-sandbox ${{ steps.versions.outputs.sandbox_version }}"
fi
if [ "${{ steps.flags.outputs.skip_deploy }}" != "true" ]; then
echo "Would publish praisonai-deploy ${{ steps.versions.outputs.deploy_version }}"
fi
if [ "${{ steps.flags.outputs.skip_wrapper }}" != "true" ]; then
echo "Would run bump_and_release.py ${{ steps.versions.outputs.wrapper_version }} --agents ${{ steps.versions.outputs.agents_version }} --code-pin ${{ steps.versions.outputs.code_version }} --bot-pin ${{ steps.versions.outputs.bot_version }} --train-pin ${{ steps.versions.outputs.train_version }} --browser-pin ${{ steps.versions.outputs.browser_version }} --mcp-pin ${{ steps.versions.outputs.mcp_version }} --sandbox-pin ${{ steps.versions.outputs.sandbox_version }} --deploy-pin ${{ steps.versions.outputs.deploy_version }}"
if [ "${{ inputs.skip_wrapper }}" != "true" ]; then
echo "Would run bump_and_release.py ${{ steps.versions.outputs.wrapper_version }} --agents ${{ steps.versions.outputs.agents_version }} --code-pin ${{ steps.versions.outputs.code_version }} --bot-pin ${{ steps.versions.outputs.bot_version }} --train-pin ${{ steps.versions.outputs.train_version }} --browser-pin ${{ steps.versions.outputs.browser_version }} --mcp-pin ${{ steps.versions.outputs.mcp_version }}"
echo "Would uv publish praisonai ${{ steps.versions.outputs.wrapper_version }}"
fi
@@ -684,9 +537,7 @@ jobs:
rm -rf dist
uv lock
uv build
# --check-url makes re-uploads idempotent: files already on PyPI are
# skipped instead of failing the publish (partial-upload recovery).
uv publish --check-url https://pypi.org/simple/
uv publish
- name: Wait for praisonaiagents on PyPI
if: >-
@@ -715,6 +566,19 @@ jobs:
sleep "$INTERVAL"
done
- name: Commit agents version bump
if: >-
inputs.dry_run != true &&
inputs.skip_agents != true &&
steps.pypi_exists.outputs.skip_agents != 'true'
run: |
set -euo pipefail
git add src/praisonai-agents/pyproject.toml src/praisonai-agents/uv.lock
git diff --cached --quiet && { echo "No agents files to commit"; exit 0; }
git commit -m "Bump praisonaiagents to ${{ steps.versions.outputs.agents_version }}"
git pull --rebase origin main
git push origin main
- name: Publish praisonai-code
if: >-
inputs.dry_run != true &&
@@ -743,9 +607,7 @@ jobs:
rm -rf dist
uv lock
uv build
# --check-url makes re-uploads idempotent: files already on PyPI are
# skipped instead of failing the publish (partial-upload recovery).
uv publish --check-url https://pypi.org/simple/
uv publish
- name: Wait for praisonai-code on PyPI
if: >-
@@ -774,6 +636,19 @@ jobs:
sleep "$INTERVAL"
done
- name: Commit praisonai-code version bump
if: >-
inputs.dry_run != true &&
inputs.skip_code != true &&
steps.pypi_exists.outputs.skip_code != 'true'
run: |
set -euo pipefail
git add src/praisonai-code/pyproject.toml src/praisonai-code/uv.lock src/praisonai-code/praisonai_code/__init__.py
git diff --cached --quiet && { echo "No code files to commit"; exit 0; }
git commit -m "Bump praisonai-code to ${{ steps.versions.outputs.code_version }}"
git pull --rebase origin main
git push origin main
- name: Publish praisonai-bot
if: >-
inputs.dry_run != true &&
@@ -802,9 +677,7 @@ jobs:
rm -rf dist
uv lock
uv build
# --check-url makes re-uploads idempotent: files already on PyPI are
# skipped instead of failing the publish (partial-upload recovery).
uv publish --check-url https://pypi.org/simple/
uv publish
- name: Wait for praisonai-bot on PyPI
if: >-
@@ -833,6 +706,19 @@ jobs:
sleep "$INTERVAL"
done
- name: Commit praisonai-bot version bump
if: >-
inputs.dry_run != true &&
inputs.skip_bot != true &&
steps.pypi_exists.outputs.skip_bot != 'true'
run: |
set -euo pipefail
git add src/praisonai-bot/pyproject.toml src/praisonai-bot/uv.lock src/praisonai-bot/praisonai_bot/_version.py
git diff --cached --quiet && { echo "No bot files to commit"; exit 0; }
git commit -m "Bump praisonai-bot to ${{ steps.versions.outputs.bot_version }}"
git pull --rebase origin main
git push origin main
- name: Publish praisonai-train
if: >-
inputs.dry_run != true &&
@@ -861,9 +747,7 @@ jobs:
rm -rf dist
uv lock
uv build
# --check-url makes re-uploads idempotent: files already on PyPI are
# skipped instead of failing the publish (partial-upload recovery).
uv publish --check-url https://pypi.org/simple/
uv publish
- name: Wait for praisonai-train on PyPI
if: >-
@@ -892,6 +776,19 @@ jobs:
sleep "$INTERVAL"
done
- name: Commit praisonai-train version bump
if: >-
inputs.dry_run != true &&
inputs.skip_train != true &&
steps.pypi_exists.outputs.skip_train != 'true'
run: |
set -euo pipefail
git add src/praisonai-train/pyproject.toml src/praisonai-train/uv.lock src/praisonai-train/praisonai_train/_version.py
git diff --cached --quiet && { echo "No train files to commit"; exit 0; }
git commit -m "Bump praisonai-train to ${{ steps.versions.outputs.train_version }}"
git pull --rebase origin main
git push origin main
- name: Publish praisonai-browser
if: >-
inputs.dry_run != true &&
@@ -920,9 +817,7 @@ jobs:
rm -rf dist
uv lock
uv build
# --check-url makes re-uploads idempotent: files already on PyPI are
# skipped instead of failing the publish (partial-upload recovery).
uv publish --check-url https://pypi.org/simple/
uv publish
- name: Wait for praisonai-browser on PyPI
if: >-
@@ -951,6 +846,19 @@ jobs:
sleep "$INTERVAL"
done
- name: Commit praisonai-browser version bump
if: >-
inputs.dry_run != true &&
inputs.skip_browser != true &&
steps.pypi_exists.outputs.skip_browser != 'true'
run: |
set -euo pipefail
git add src/praisonai-browser/pyproject.toml src/praisonai-browser/uv.lock src/praisonai-browser/praisonai_browser/_version.py
git diff --cached --quiet && { echo "No browser files to commit"; exit 0; }
git commit -m "Bump praisonai-browser to ${{ steps.versions.outputs.browser_version }}"
git pull --rebase origin main
git push origin main
- name: Publish praisonai-mcp
if: >-
inputs.dry_run != true &&
@@ -979,9 +887,7 @@ jobs:
rm -rf dist
uv lock
uv build
# --check-url makes re-uploads idempotent: files already on PyPI are
# skipped instead of failing the publish (partial-upload recovery).
uv publish --check-url https://pypi.org/simple/
uv publish
- name: Wait for praisonai-mcp on PyPI
if: >-
@@ -1010,6 +916,19 @@ jobs:
sleep "$INTERVAL"
done
- name: Commit praisonai-mcp version bump
if: >-
inputs.dry_run != true &&
inputs.skip_mcp != true &&
steps.pypi_exists.outputs.skip_mcp != 'true'
run: |
set -euo pipefail
git add src/praisonai-mcp/pyproject.toml src/praisonai-mcp/uv.lock src/praisonai-mcp/praisonai_mcp/_version.py
git diff --cached --quiet && { echo "No mcp files to commit"; exit 0; }
git commit -m "Bump praisonai-mcp to ${{ steps.versions.outputs.mcp_version }}"
git pull --rebase origin main
git push origin main
- name: Publish praisonai-sandbox
if: >-
inputs.dry_run != true &&
@@ -1038,9 +957,7 @@ jobs:
rm -rf dist
uv lock
uv build
# --check-url makes re-uploads idempotent: files already on PyPI are
# skipped instead of failing the publish (partial-upload recovery).
uv publish --check-url https://pypi.org/simple/
uv publish
- name: Wait for praisonai-sandbox on PyPI
if: >-
@@ -1069,101 +986,20 @@ jobs:
sleep "$INTERVAL"
done
- name: Publish praisonai-deploy
- name: Commit praisonai-sandbox version bump
if: >-
inputs.dry_run != true &&
inputs.skip_deploy != true &&
steps.pypi_exists.outputs.skip_deploy != 'true'
working-directory: src/praisonai-deploy
env:
NEW_VERSION: ${{ steps.versions.outputs.deploy_version }}
CURRENT: ${{ steps.versions.outputs.current_deploy }}
inputs.skip_sandbox != true &&
steps.pypi_exists.outputs.skip_sandbox != 'true'
run: |
set -euo pipefail
python <<'PY'
import os
import re
from pathlib import Path
new = os.environ["NEW_VERSION"]
current = os.environ["CURRENT"]
pyproject = Path("pyproject.toml")
content = pyproject.read_text()
pyproject.write_text(content.replace(f'version = "{current}"', f'version = "{new}"', 1))
version_py = Path("praisonai_deploy/_version.py")
version_content = version_py.read_text()
version_py.write_text(re.sub(r'__version__ = "[^"]+"', f'__version__ = "{new}"', version_content, count=1))
PY
rm -rf dist
uv lock
uv build
# --check-url makes re-uploads idempotent: files already on PyPI are
# skipped instead of failing the publish (partial-upload recovery).
uv publish --check-url https://pypi.org/simple/
- name: Wait for praisonai-deploy on PyPI
if: >-
inputs.dry_run != true &&
inputs.skip_deploy != true &&
steps.pypi_exists.outputs.skip_deploy != 'true'
run: |
set -euo pipefail
PACKAGE="praisonai-deploy"
VERSION="${{ steps.versions.outputs.deploy_version }}"
MAX_WAIT=600
INTERVAL=30
START=$(date +%s)
while true; do
if curl -fsSL "https://pypi.org/pypi/${PACKAGE}/${VERSION}/json" >/dev/null; then
echo "✅ ${PACKAGE}==${VERSION} is available on PyPI"
exit 0
fi
ELAPSED=$(( $(date +%s) - START ))
if [ "$ELAPSED" -ge "$MAX_WAIT" ]; then
echo "❌ Timeout waiting for ${PACKAGE}==${VERSION} on PyPI"
exit 1
fi
echo "⏳ Waiting for ${PACKAGE}==${VERSION} ($(( MAX_WAIT - ELAPSED ))s remaining...)"
sleep "$INTERVAL"
done
# All per-package version bumps are still uncommitted at this point: the
# wrapper release below stages every one of them (bump_and_release.py's
# release_files list) into a SINGLE "Release v…" commit.
# App tokens expire after 1h and this job can exceed that (9 packages ×
# up to a 600s PyPI wait). Re-mint so the final commit/tag/push/release
# never runs on an expired token.
- name: Refresh GitHub App token
id: app-token-final
if: ${{ !cancelled() && inputs.dry_run != true }}
# A failed re-mint must not fail the release: the original token may
# still be valid, and the next step only swaps tokens on success.
continue-on-error: true
uses: actions/create-github-app-token@v1
with:
app-id: ${{ secrets.CLAUDE_APP_ID }}
private-key: ${{ secrets.CLAUDE_APP_PRIVATE_KEY }}
owner: ${{ github.repository_owner }}
repositories: ${{ github.event.repository.name }}
# Guarded on the refresh actually succeeding: if the re-mint failed
# (API blip), the ORIGINAL token — still wired into the remote URL and
# GH_TOKEN — may well be valid, and overwriting it with an empty string
# would turn a recoverable situation into a guaranteed auth failure.
- name: Use refreshed GitHub App token
if: ${{ !cancelled() && inputs.dry_run != true && steps.app-token-final.outcome == 'success' }}
env:
APP_TOKEN: ${{ steps.app-token-final.outputs.token }}
REPO: ${{ github.repository }}
run: |
set -euo pipefail
git remote set-url origin "https://x-access-token:${APP_TOKEN}@github.com/${REPO}.git"
echo "GH_TOKEN=${APP_TOKEN}" >> "$GITHUB_ENV"
git add src/praisonai-sandbox/pyproject.toml src/praisonai-sandbox/uv.lock src/praisonai-sandbox/praisonai_sandbox/_version.py
git diff --cached --quiet && { echo "No sandbox files to commit"; exit 0; }
git commit -m "Bump praisonai-sandbox to ${{ steps.versions.outputs.sandbox_version }}"
git pull --rebase origin main
git push origin main
- name: Bump and release wrapper
id: wrapper
if: >-
inputs.dry_run != true &&
inputs.skip_wrapper != true &&
@@ -1178,8 +1014,7 @@ jobs:
--browser-pin "${{ steps.versions.outputs.browser_version }}" \
--mcp-pin "${{ steps.versions.outputs.mcp_version }}" \
--sandbox-pin "${{ steps.versions.outputs.sandbox_version }}" \
--deploy-pin "${{ steps.versions.outputs.deploy_version }}" \
--wait --max-wait 600 --no-add-all --force
--wait --max-wait 600 --no-add-all
- name: Publish praisonai wrapper to PyPI
if: >-
@@ -1187,7 +1022,7 @@ jobs:
inputs.skip_wrapper != true &&
steps.pypi_exists.outputs.skip_wrapper != 'true'
working-directory: src/praisonai
run: uv publish --check-url https://pypi.org/simple/
run: uv publish
- name: Wait for praisonai on PyPI
if: >-
@@ -1216,139 +1051,47 @@ jobs:
sleep "$INTERVAL"
done
# Actually probes PyPI — previously this step only echoed checkmarks
# from the input flags, so it "verified" publishes that never happened.
- name: Verify PyPI versions
if: inputs.dry_run != true
run: |
set -euo pipefail
verify() { # $1=pypi-name $2=version $3=effective-skip
if [ "$3" = "true" ]; then
echo "⏭️ $1 skipped"
return 0
fi
if curl -fsSL --max-time 30 "https://pypi.org/pypi/$1/$2/json" >/dev/null; then
echo "✅ $1==$2"
else
echo "❌ $1==$2 NOT found on PyPI"
exit 1
fi
}
verify praisonaiagents "${{ steps.versions.outputs.agents_version }}" "${{ steps.flags.outputs.skip_agents }}"
verify praisonai-code "${{ steps.versions.outputs.code_version }}" "${{ steps.flags.outputs.skip_code }}"
verify praisonai-bot "${{ steps.versions.outputs.bot_version }}" "${{ steps.flags.outputs.skip_bot }}"
verify praisonai-train "${{ steps.versions.outputs.train_version }}" "${{ steps.flags.outputs.skip_train }}"
verify praisonai-browser "${{ steps.versions.outputs.browser_version }}" "${{ steps.flags.outputs.skip_browser }}"
verify praisonai-mcp "${{ steps.versions.outputs.mcp_version }}" "${{ steps.flags.outputs.skip_mcp }}"
verify praisonai-sandbox "${{ steps.versions.outputs.sandbox_version }}" "${{ steps.flags.outputs.skip_sandbox }}"
verify praisonai-deploy "${{ steps.versions.outputs.deploy_version }}" "${{ steps.flags.outputs.skip_deploy }}"
verify praisonai "${{ steps.versions.outputs.wrapper_version }}" "${{ steps.flags.outputs.skip_wrapper }}"
AGENTS="${{ steps.versions.outputs.agents_version }}"
CODE="${{ steps.versions.outputs.code_version }}"
BOT="${{ steps.versions.outputs.bot_version }}"
TRAIN="${{ steps.versions.outputs.train_version }}"
BROWSER="${{ steps.versions.outputs.browser_version }}"
MCP="${{ steps.versions.outputs.mcp_version }}"
SANDBOX="${{ steps.versions.outputs.sandbox_version }}"
WRAPPER="${{ steps.versions.outputs.wrapper_version }}"
# Safety net. On a clean run the wrapper's "Release v…" commit already
# carries every bump and this is a no-op. It only fires when the single
# commit could not happen: a package publish failed midway (those versions
# are already live on PyPI, so the bumps must not be lost), skip_wrapper
# was set, or the wrapper itself failed.
- name: Persist any uncommitted version bumps
if: ${{ !cancelled() && inputs.dry_run != true }}
run: |
set -euo pipefail
# If the wrapper release did not complete, drop any uncommitted
# wrapper-side rewrites (version.py, Dockerfiles, pins): committing
# them would put a wrapper version on main that never reached PyPI,
# and the next auto-bump would skip past it forever. Committed
# changes are untouched (checkout only reverts the working tree),
# and if the wrapper was skipped these files were never modified.
if [ "${{ steps.wrapper.outcome }}" != "success" ]; then
git checkout -- \
src/praisonai/praisonai/version.py \
src/praisonai/pyproject.toml \
src/praisonai/uv.lock \
src/praisonai/README.md \
src/praisonai/praisonai.rb \
src/praisonai-deploy/praisonai_deploy/docker.py \
docker/ 2>/dev/null || true
if [ "${{ inputs.skip_agents }}" != "true" ]; then
echo "✅ praisonaiagents==${AGENTS}"
fi
# -u = tracked modifications only; uv build output under dist/ is
# untracked and stays out of the commit.
git add -u
git diff --cached --quiet && { echo "Nothing left to commit"; exit 0; }
# Name the packages actually staged, so a single-package release
# (every other skip_* set) reads "bump praisonai-mcp" rather than a
# generic message. Falls back when nothing under src/ is staged.
PKGS="$(git diff --cached --name-only \
| sed -n 's#^src/\([^/]*\)/.*#\1#p' | sort -u | tr '\n' ' ' | sed 's/ *$//')"
if [ -n "$PKGS" ]; then
MSG="chore(release): bump ${PKGS} [skip ci]"
else
MSG="chore(release): persist version bumps [skip ci]"
fi
echo "Commit message: ${MSG}"
git commit -m "$MSG"
# This step fires exactly when the release went sideways — i.e. when
# main is most likely to have moved — so the rebase+push retries.
# Losing this commit deadlocks future auto-releases: the packages
# are on PyPI at N+1 while the repo says N, so every later run
# detects "already published" and skips both publish and bump.
for attempt in 1 2 3; do
git fetch origin main
if ! git rebase origin/main; then
git rebase --abort || true
# During rebase, "theirs" is the commit being replayed — the
# version bumps — so they win any conflict.
if ! git rebase -X theirs origin/main; then
git rebase --abort || true
echo "Rebase attempt ${attempt}/3 failed"
sleep 5
continue
fi
fi
if git push origin main; then
echo "Pushed version bumps (attempt ${attempt}/3)"
exit 0
fi
echo "Push attempt ${attempt}/3 rejected; retrying..."
sleep 5
done
echo "❌ Could not push version bumps after 3 attempts."
echo " Repo is now BEHIND PyPI; commit the version files on main manually"
echo " or future auto-releases will no-op ('already published')."
exit 1
# Dedicated releases (skip_wrapper) create no "Release v…" tag — the
# wrapper drives that — so tag each published package individually for
# provenance. Full releases keep their single v… tag unchanged.
- name: Tag dedicated package releases
if: >-
${{ !cancelled() && inputs.dry_run != true &&
steps.flags.outputs.skip_wrapper == 'true' &&
steps.versions.outcome == 'success' }}
run: |
set -euo pipefail
tag_pkg() { # $1=effective-skip $2=pypi-name $3=version
if [ "$1" = "true" ]; then
return 0
fi
local tag="$2-v$3"
# Only tag what is confirmed on PyPI — a package whose publish
# failed must not get a tag claiming it shipped.
if ! curl -fsSL --max-time 30 "https://pypi.org/pypi/$2/$3/json" >/dev/null; then
echo "⏭️ $2==$3 not on PyPI; not tagging"
return 0
fi
if git rev-parse -q --verify "refs/tags/${tag}" >/dev/null; then
echo "tag ${tag} already exists"
return 0
fi
git tag "${tag}"
git push origin "refs/tags/${tag}"
echo "🏷️ ${tag}"
}
tag_pkg "${{ steps.flags.outputs.skip_agents }}" praisonaiagents "${{ steps.versions.outputs.agents_version }}"
tag_pkg "${{ steps.flags.outputs.skip_code }}" praisonai-code "${{ steps.versions.outputs.code_version }}"
tag_pkg "${{ steps.flags.outputs.skip_bot }}" praisonai-bot "${{ steps.versions.outputs.bot_version }}"
tag_pkg "${{ steps.flags.outputs.skip_train }}" praisonai-train "${{ steps.versions.outputs.train_version }}"
tag_pkg "${{ steps.flags.outputs.skip_browser }}" praisonai-browser "${{ steps.versions.outputs.browser_version }}"
tag_pkg "${{ steps.flags.outputs.skip_mcp }}" praisonai-mcp "${{ steps.versions.outputs.mcp_version }}"
tag_pkg "${{ steps.flags.outputs.skip_sandbox }}" praisonai-sandbox "${{ steps.versions.outputs.sandbox_version }}"
tag_pkg "${{ steps.flags.outputs.skip_deploy }}" praisonai-deploy "${{ steps.versions.outputs.deploy_version }}"
if [ "${{ inputs.skip_code }}" != "true" ]; then
echo "✅ praisonai-code==${CODE}"
fi
if [ "${{ inputs.skip_bot }}" != "true" ]; then
echo "✅ praisonai-bot==${BOT}"
fi
if [ "${{ inputs.skip_train }}" != "true" ]; then
echo "✅ praisonai-train==${TRAIN}"
fi
if [ "${{ inputs.skip_browser }}" != "true" ]; then
echo "✅ praisonai-browser==${BROWSER}"
fi
if [ "${{ inputs.skip_mcp }}" != "true" ]; then
echo "✅ praisonai-mcp==${MCP}"
fi
if [ "${{ inputs.skip_sandbox }}" != "true" ]; then
echo "✅ praisonai-sandbox==${SANDBOX}"
fi
if [ "${{ inputs.skip_wrapper }}" != "true" ]; then
echo "✅ praisonai==${WRAPPER}"
fi
@@ -24,7 +24,6 @@ jobs:
CLAUDE_APP_PRIVATE_KEY: ${{ secrets.CLAUDE_APP_PRIVATE_KEY }}
CLAUDE_CODE_OAUTH_TOKEN: ${{ secrets.CLAUDE_CODE_OAUTH_TOKEN }}
GH_TOKEN_VALUE: ${{ secrets.GH_TOKEN }}
DOCS_GITHUB_TOKEN: ${{ secrets.SECRETS_ADMIN_PAT }}
run: |
set -euo pipefail
if [ -z "${GH_TOKEN:-}" ]; then
@@ -35,7 +34,4 @@ jobs:
echo -n "$CLAUDE_APP_PRIVATE_KEY" | gh secret set CLAUDE_APP_PRIVATE_KEY --repo "$TARGET"
echo -n "$CLAUDE_CODE_OAUTH_TOKEN" | gh secret set CLAUDE_CODE_OAUTH_TOKEN --repo "$TARGET"
echo -n "$GH_TOKEN_VALUE" | gh secret set GH_TOKEN --repo "$TARGET"
if [ -n "${DOCS_GITHUB_TOKEN:-}" ]; then
echo -n "$DOCS_GITHUB_TOKEN" | gh secret set DOCS_GITHUB_TOKEN --repo "$TARGET"
fi
echo "Synced CLAUDE_APP_ID, CLAUDE_APP_PRIVATE_KEY, CLAUDE_CODE_OAUTH_TOKEN, GH_TOKEN → $TARGET"
-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})."
+5 -40
View File
@@ -5,9 +5,6 @@ on:
branches: [ main, develop ]
paths:
- 'src/**'
- 'src/praisonai-deploy/infra/**'
- 'src/praisonai-bot/infra/**'
- 'scripts/check_helm_charts.sh'
- 'pyproject.toml'
- '.github/workflows/test-core.yml'
- '.github/actions/install-monorepo-packages/**'
@@ -15,9 +12,6 @@ on:
branches: [ main, develop ]
paths:
- 'src/**'
- 'src/praisonai-deploy/infra/**'
- 'src/praisonai-bot/infra/**'
- 'scripts/check_helm_charts.sh'
- 'pyproject.toml'
- '.github/workflows/test-core.yml'
- '.github/actions/install-monorepo-packages/**'
@@ -101,9 +95,8 @@ jobs:
${{ github.workspace }}/src/praisonai-agents:${{ github.workspace }}/src/praisonai-code
- 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
@@ -121,17 +114,11 @@ jobs:
extra_ignore: ""
pythonpath: >-
${{ github.workspace }}/src/praisonai-agents
- shard: deploy
workdir: src/praisonai-deploy
paths: >-
tests/
extra_ignore: ""
pythonpath: >-
${{ github.workspace }}/src/praisonai-agents
- shard: subdirs
paths: >-
tests/unit/scheduler/
tests/unit/integrations/
tests/unit/deploy/
tests/unit/mcp/
tests/unit/knowledge/
tests/unit/llm/
@@ -196,9 +183,6 @@ jobs:
if [ "$WORKDIR" = "src/praisonai-sandbox" ]; then
bash "$GITHUB_WORKSPACE/scripts/check_c13_sandbox_imports.sh"
fi
if [ "$WORKDIR" = "src/praisonai-deploy" ]; then
bash "$GITHUB_WORKSPACE/scripts/check_c14_deploy_imports.sh"
fi
if [ "$WORKDIR" = "src/praisonai-mcp" ]; then
bash "$GITHUB_WORKSPACE/scripts/check_c12_mcp_imports.sh"
fi
@@ -284,27 +268,9 @@ jobs:
--ignore=tests/integration/test_tracker_complex_tasks.py \
--ignore=tests/integration/test_serve_integration.py
helm-charts:
name: helm-charts
runs-on: ubuntu-latest
timeout-minutes: 5
steps:
- uses: actions/checkout@v4
with:
persist-credentials: false
- name: Setup Helm
uses: azure/setup-helm@v3
with:
version: v3.14.4
- name: Lint and template Helm charts
shell: bash
run: |
set -euo pipefail
bash "$GITHUB_WORKSPACE/scripts/check_helm_charts.sh"
test-core:
name: test-core
needs: [test-core-collect, test-core-unit, test-core-integration, helm-charts]
needs: [test-core-collect, test-core-unit, test-core-integration]
if: always()
runs-on: ubuntu-latest
timeout-minutes: 5
@@ -316,9 +282,8 @@ jobs:
collect='${{ needs.test-core-collect.result }}'
unit='${{ needs.test-core-unit.result }}'
integration='${{ needs.test-core-integration.result }}'
helm='${{ needs.helm-charts.result }}'
echo "collect=$collect unit=$unit integration=$integration helm=$helm"
if [ "$collect" != "success" ] || [ "$unit" != "success" ] || [ "$integration" != "success" ] || [ "$helm" != "success" ]; then
echo "collect=$collect unit=$unit integration=$integration"
if [ "$collect" != "success" ] || [ "$unit" != "success" ] || [ "$integration" != "success" ]; then
echo "Core Tests failed"
exit 1
fi
+1 -35
View File
@@ -86,7 +86,6 @@ jobs:
tests/unit/test_c11_browser_backward_compat.py \
tests/unit/test_c12_mcp_backward_compat.py \
tests/unit/test_c13_sandbox_backward_compat.py \
tests/unit/test_c14_deploy_backward_compat.py \
-q --tb=line --timeout=30 --maxfail=5
python -m pytest tests/unit/cli/ \
../praisonai-bot/tests/unit/cli/test_onboard_command.py \
@@ -98,20 +97,6 @@ jobs:
--ignore=tests/unit/cli/test_message_queue.py \
--maxfail=5
- name: Run praisonai-agents subscription-auth smoke tests
env:
PRAISONAI_TEST_TIER: smoke
PRAISONAI_ALLOW_NETWORK: '0'
OPENAI_MODEL_NAME: gpt-4o-mini
OPENAI_API_KEY: 'test-key'
shell: bash
run: |
set -euo pipefail
cd src/praisonai-agents
python -m pytest tests/smoke/test_subscription_auth.py \
tests/unit/auth/test_agent_auth_wiring.py \
-q --tb=line --timeout=60 --maxfail=5
- name: Standalone praisonai-code import smoke
shell: bash
run: |
@@ -284,26 +269,10 @@ jobs:
bash "$GITHUB_WORKSPACE/scripts/check_c13_sandbox_imports.sh"
python -m pytest src/praisonai-sandbox/tests -q -m "not network"
- name: Standalone praisonai-deploy smoke (C14)
run: |
set -euo pipefail
python -m venv /tmp/praisonai-deploy-standalone
/tmp/praisonai-deploy-standalone/bin/pip install -q -e src/praisonai-agents -e src/praisonai-deploy
/tmp/praisonai-deploy-standalone/bin/python -c "
from praisonai_deploy._version import __version__ as pkg_version
import praisonai_deploy
assert praisonai_deploy.__version__ == pkg_version
assert 'main' not in __import__('sys').modules
print('deploy standalone ok', praisonai_deploy.__version__)
"
/tmp/praisonai-deploy-standalone/bin/praisonai-deploy --help
bash "$GITHUB_WORKSPACE/scripts/check_c14_deploy_imports.sh"
python -m pytest src/praisonai-deploy/tests -q -m "not network"
- name: Audit hybrid module imports (C8 full stack)
run: |
set -euo pipefail
pip install -q -e src/praisonai-agents -e src/praisonai-code -e src/praisonai-bot -e src/praisonai-train -e src/praisonai-browser -e src/praisonai-mcp -e src/praisonai-sandbox -e src/praisonai-deploy -e src/praisonai
pip install -q -e src/praisonai-agents -e src/praisonai-code -e src/praisonai-bot -e src/praisonai-train -e src/praisonai-browser -e src/praisonai-mcp -e src/praisonai-sandbox -e src/praisonai
python scripts/audit_hybrid_modules.py
- name: Smoke Test Summary
@@ -813,9 +782,6 @@ jobs:
tests/unit/test_decorator_simple.py
tests/unit/test_db_adapter_tracing_init.py
../praisonai-bot/tests/unit/test_bot_wiring.py
../praisonai-bot/tests/unit/bots/test_enable_shell.py
../praisonai-bot/tests/unit/gateway/test_preflight.py
../praisonai-bot/tests/unit/gateway/test_gateway_doctor.py
../praisonai-bot/tests/unit/test_bot_history.py
../praisonai-bot/tests/unit/test_bot_fixes.py
tests/unit/test_auto_lazy_loading.py
+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
+5 -18
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
@@ -50,7 +36,7 @@ jobs:
run: |
cd $GITHUB_WORKSPACE
python3 src/praisonai/scripts/generate_parity_tracker.py
- name: Check for changes
id: check_changes
run: |
@@ -72,3 +58,4 @@ jobs:
commit_user_name: "MervinPraison"
commit_user_email: "[email protected]"
commit_author: "MervinPraison <[email protected]>"
-3
View File
@@ -12,7 +12,6 @@ assets
.DS_Store
.pytest_cache
praisonAI.egg-info
src/*/build/
flagged
test.yaml
db
@@ -25,8 +24,6 @@ output
!src/praisonai-agents/praisonaiagents/output/
!src/praisonai-code/praisonai_code/cli/output/
!src/praisonai-bot/praisonai_bot/cli/output/
!src/praisonai-ts/src/db/
!src/praisonai-ts/src/cli/output/
.files
threads.db
+3 -16
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@@ -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 eight 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/`, 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)
- 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)
- 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.
+10 -29
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@@ -1,6 +1,6 @@
# PraisonAI Architecture
> **Last updated:** 2026-07-31 (C14 — nine-package tiered model)
> **Last updated:** 2026-07-17 (C13 — eight-package tiered model)
>
> Strategic architecture document for PraisonAI — a multi-agent AI framework.
> Covers **Python tiered package model (C7.1 + C9 + C10)**, system design, runtime
@@ -11,7 +11,7 @@
## Table of Contents
1. [Executive Summary](#1-executive-summary)
2. [Python Tiered Package Model (C7.1 + C9 + C10 + C11 + C12 + C13 + C14)](#2-python-tiered-package-model-c71--c9--c10--c11--c12--c13--c14)
2. [Python Tiered Package Model (C7.1 + C9 + C10 + C11 + C12 + C13)](#2-python-tiered-package-model-c71--c9--c10--c11--c12--c13)
3. [System Overview](#3-system-overview)
4. [Layered Architecture](#4-layered-architecture)
5. [Core Data Contracts](#5-core-data-contracts)
@@ -51,18 +51,17 @@ Orchestration + Observability** core to unlock adoption and trust:
---
## 2. Python Tiered Package Model (C7.1 + C9 + C10 + C11 + C12 + C13 + C14)
## 2. Python Tiered Package Model (C7.1 + C9 + C10 + C11 + C12 + C13)
**Release:** v4.6.110+ · `praisonaiagents` · `praisonai-code` · `praisonai-bot` · `praisonai-train` · `praisonai-browser` · `praisonai-mcp` · `praisonai-sandbox` · `praisonai-deploy` · `praisonai`
**Release:** v4.6.110+ · `praisonaiagents` · `praisonai-code` · `praisonai-bot` · `praisonai-train` · `praisonai-browser` · `praisonai-mcp` · `praisonai-sandbox` · `praisonai`
The Python monorepo publishes nine packages in three tiers with strict dependency
The Python monorepo publishes eight packages in three tiers with strict dependency
direction. C7 delivered a standalone agentic hot path; C7.1 formalised
code/wrapper ownership; C9 extracted bots, gateway, and channel CLI into
`praisonai-bot`; C10 extracted LLM fine-tuning and agent training into
`praisonai-train`; C11 extracted browser automation into `praisonai-browser`;
C12 extracted the heavy MCP host into `praisonai-mcp`.
C13 extracted sandbox backends into `praisonai-sandbox`.
C14 extracted deployment (API, Docker, cloud) into `praisonai-deploy`.
```mermaid
flowchart TB
@@ -70,14 +69,13 @@ flowchart TB
Agents["praisonaiagents<br/>Agent, tools, memory, hooks, protocols"]
end
subgraph tier2 [Tier 2 — Terminal + Bot + Train + Browser + MCP + Sandbox + Deploy]
subgraph tier2 [Tier 2 — Terminal + Bot + Train + Browser + MCP + Sandbox]
Code["praisonai-code<br/>run, chat, code, Typer, runtime, LLM"]
Bot["praisonai-bot<br/>bots, gateway, channel CLI, OS daemon"]
Train["praisonai-train<br/>LLM fine-tuning, agent training"]
Browser["praisonai-browser<br/>extension bridge, CDP, Playwright"]
MCP["praisonai-mcp<br/>MCP server host, auth, capability adapters"]
Sandbox["praisonai-sandbox<br/>Docker, E2B, Modal, Sandlock backends"]
Deploy["praisonai-deploy<br/>API, Docker, AWS/Azure/GCP deploy"]
end
subgraph tier3 [Tier 3 — Wrapper]
@@ -90,53 +88,36 @@ flowchart TB
Agents --> Browser
Agents --> MCP
Agents --> Sandbox
Agents --> Deploy
Agents --> Wrapper
Code -.->|"lazy _bot_bridge"| Bot
Code -.->|"lazy _train_bridge"| Train
Code -.->|"lazy _browser_bridge"| Browser
Code -.->|"lazy _mcp_bridge"| MCP
Code -.->|"lazy _sandbox_bridge"| Sandbox
Code -.->|"lazy _deploy_bridge"| Deploy
Code -.->|"lazy _wrapper_bridge"| Wrapper
Bot -.->|"lazy _code_bridge / _wrapper_bridge"| Code
Bot -.->|"lazy _wrapper_bridge"| Wrapper
Train -.->|"lazy _code_bridge / _wrapper_bridge"| Code
```
**PyPI publish order:** `praisonaiagents` → `praisonai-code` + `praisonai-bot` + `praisonai-train` + `praisonai-browser` + `praisonai-mcp` + `praisonai-sandbox` + `praisonai-deploy` → `praisonai`
**PyPI publish order:** `praisonaiagents` → `praisonai-code` + `praisonai-bot` + `praisonai-train` + `praisonai-browser` + `praisonai-mcp` + `praisonai-sandbox` → `praisonai`
**Backward compatibility:** `praisonai.bots`, `praisonai.gateway`, `praisonai.train`,
`praisonai.browser`, `praisonai.mcp_server`, `praisonai.sandbox`, `praisonai.deploy`, and related CLI paths remain as
`praisonai.browser`, `praisonai.mcp_server`, `praisonai.sandbox`, and related CLI paths remain as
`alias_package` shims to `praisonai_bot.*` / `praisonai_train.*` /
`praisonai_browser.*` / `praisonai_mcp.*` / `praisonai_sandbox.*` / `praisonai_deploy.*`.
`praisonai_browser.*` / `praisonai_mcp.*` / `praisonai_sandbox.*`.
| Tier | Package | Owns | Must not depend on |
|------|---------|------|-------------------|
| 1 | `src/praisonai-agents/` | Agent, tools, memory, hooks, `frameworks/` protocols, sandbox protocols | `praisonai`, `praisonai-code`, `praisonai-bot`, `praisonai-train`, `praisonai-browser`, `praisonai-mcp`, `praisonai-sandbox`, `praisonai-deploy` |
| 1 | `src/praisonai-agents/` | Agent, tools, memory, hooks, `frameworks/` protocols, sandbox protocols | `praisonai`, `praisonai-code`, `praisonai-bot`, `praisonai-train`, `praisonai-browser`, `praisonai-mcp`, `praisonai-sandbox` |
| 2a | `src/praisonai-code/` | `run`/`chat`/`code`, Typer, runtime, LLM, tool resolution | **`praisonai` as a PyPI dependency** (optional lazy imports via `_wrapper_bridge` only) |
| 2b | `src/praisonai-bot/` | Bots, gateway, channel CLI, OS daemon, gateway scheduler tick | **`praisonai` as a PyPI dependency** (optional lazy `_wrapper_bridge` for jobs/UI) |
| 2c | `src/praisonai-train/` | LLM fine-tuning (Unsloth), agent training, `train` CLI, conda env setup | **`praisonai` as a PyPI dependency** (lazy `_code_bridge` for legacy dispatch) |
| 2d | `src/praisonai-browser/` | Extension bridge, CDP/hybrid automation, `browser` CLI | **`praisonai` as a PyPI dependency** (none required; depends on `praisonaiagents` only) |
| 2e | `src/praisonai-mcp/` | MCP server host, auth, transports, `mcp` CLI | **`praisonai` as a PyPI dependency** (lazy `_wrapper_bridge` for full capability registry) |
| 2f | `src/praisonai-sandbox/` | Sandbox backends (Docker, E2B, Modal, Sandlock, SSH), `SandboxRegistry` | **`praisonai` as a PyPI dependency** (lazy `_code_bridge` for `PluginRegistry`) |
| 2g | `src/praisonai-deploy/` | Deploy API/Docker/cloud, `deploy` CLI, scheduler integration | **`praisonai` as a PyPI dependency** (lazy `_plugin_registry` via `_code_bridge`) |
| 3 | `src/praisonai/` | `framework_adapters/`, serve, dashboard, async jobs API | — |
### Repo infra (not PyPI)
Deployment packaging that stays in the git checkout, not in any tier-2 wheel:
| Path | Runtime owner | Orchestration |
|------|---------------|---------------|
| `src/praisonai-bot/infra/helm/praisonai-gateway/` | `praisonai-bot` (gateway) | C14 `deploy helm` wrapper |
| `src/praisonai-deploy/infra/helm/praisonai-agents-api/` | Generated API from C14 | C14 cross-link |
| `src/praisonai-deploy/infra/compose/agents-stack/` | Docker Compose | `praisonai deploy compose up/down` |
| `src/praisonai-deploy/infra/starters/` | Starter scaffolds | `praisonai deploy create --template` |
| `docker/` | Mixed (wrapper/bot dev stacks) | Not C14 — see bot manifest for `docker/bots/` |
Same boundary as C14: Helm/K8s manifests are **repo infra**, not `pip install praisonai-deploy` content.
**Config kernel:** Phase 0 `praisonai/common/` was skipped; shared config lives in
`praisonai_code/cli/configuration/` and is reached by the bot tier via lazy
`_code_bridge` (see `src/praisonai/tests/CONFIG_KERNEL.md`).
-12
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@@ -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`
+20 -250
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@@ -41,6 +41,10 @@ curl -fsSL https://praison.ai/install.sh | bash
<img src=".github/images/dashboard.png" alt="PraisonAI Dashboard" width="800" />
</p>
<p align="center">
<img src=".github/images/agentflow.gif" alt="PraisonAI AgentFlow" width="800" />
</p>
```
██████╗ ██████╗ █████╗ ██╗███████╗ ██████╗ ███╗ ██╗ █████╗ ██╗
██╔══██╗██╔══██╗██╔══██╗██║██╔════╝██╔═══██╗████╗ ██║ ██╔══██╗██║
@@ -52,6 +56,12 @@ curl -fsSL https://praison.ai/install.sh | bash
pip install praisonai
```
<p align="center">
<img src=".github/images/latest_ai_news_and_crawl_each_url_to_find_info.gif" alt="PraisonAI command execution" width="800" />
</p>
\* `export TAVILY_API_KEY=xxxxx`
<div align="center">
<a href="https://docs.praison.ai">
<p align="center">
@@ -96,232 +106,6 @@ agent.start("Analyze the top 3 tech trends of 2026 and format as a markdown tabl
---
## 🧬 The Five-Layer Agent Stack
Most frameworks hand you one or two layers and leave the rest as homework. PraisonAI covers **all five** — plus the outer layer that decides *where* your agent actually runs.
Each layer wraps the one inside it. When an agent misbehaves, the layer tells you where to look.
```
┌─────────────────────────────────────────────────────────────────┐
│ ⬡ MANAGED AGENTS — Where does it actually run? │
│ ┌─────────────────────────────────────────────────────────────┐ │
│ │ 5 · GRAPH — Who runs when, and who checks whom? │ │
│ │ ┌─────────────────────────────────────────────────────────┐ │ │
│ │ │ 4 · LOOP — When do we stop? │ │ │
│ │ │ ┌─────────────────────────────────────────────────────┐ │ │ │
│ │ │ │ 3 · HARNESS — Can it act, and be checked? │ │ │ │
│ │ │ │ ┌─────────────────────────────────────────────────┐ │ │ │ │
│ │ │ │ │ 2 · CONTEXT — Is the right thing in the window? │ │ │ │ │
│ │ │ │ │ ┌─────────────────────────────────────────────┐ │ │ │ │ │
│ │ │ │ │ │ 1 · PROMPT — Did I say it clearly? │ │ │ │ │ │
│ │ │ │ │ └─────────────────────────────────────────────┘ │ │ │ │ │
│ │ │ │ └─────────────────────────────────────────────────┘ │ │ │ │
│ │ │ └─────────────────────────────────────────────────────┘ │ │ │
│ │ └─────────────────────────────────────────────────────────┘ │ │
│ └─────────────────────────────────────────────────────────────┘ │
└─────────────────────────────────────────────────────────────────┘
```
| Layer | The question it answers | PraisonAI |
|:--|:--|:--|
| **1 · Prompt** | Did I say it clearly? | `instructions=`, `role`/`goal`/`backstory`, `output=`, `templates=` |
| **2 · Context** | Is the right thing in the window? | `memory=`, `knowledge=`, `context=`, handoff `ContextPolicy` |
| **3 · Harness** | Can it act, and be checked? | `tools=`, `MCP()`, `guardrails=`, `approval=`, `hooks=`, `sandbox=` |
| **4 · Loop** | When do we stop? | `execution=ExecutionConfig(...)`, `reflection=`, `autonomy=`, doom-loop detection |
| **5 · Graph** | Who runs when, and who checks whom? | `AgentFlow`, `route()`, `parallel()`, `loop()`, `repeat()` |
| **⬡ Managed** | *Where does it actually run?* | `tools_run_on="docker"` — one shared sandbox for the tools, or `run_on="anthropic"` for the whole agent |
### Layer 1 · Prompt — *Did I say it clearly?*
Role, instructions, examples, output format.
```python
from praisonaiagents import Agent
agent = Agent(
role="Senior Data Analyst",
goal="Turn raw numbers into decisions",
output="verbose", # markdown-formatted output
)
agent.start("Summarise Q3 revenue trends")
```
### Layer 2 · Context — *Is the right thing in the window?*
Write, select, compress, isolate — the four context operations, one parameter each.
```python
from praisonaiagents import Agent
agent = Agent(
instructions="You are a support engineer.",
memory={"user_id": "u-42"}, # write — persists across runs (needs a user_id)
knowledge=["docs/"], # select — retrieves only what's relevant
context="summarize", # compress — auto-compacts before the limit
)
```
> **Isolate** is `handoffs=[specialist]` — a sub-agent inherits the last few messages and the intersection of your tools, not your whole transcript. [📖 Handoffs](https://docs.praison.ai/docs/concepts/handoffs)
### Layer 3 · Harness — *Can it act, and be checked?*
*Agent = Model + Harness.* Tool dispatch, plus the guides that steer before acting and the sensors that observe after.
```python
from praisonaiagents import Agent, MCP, tool
@tool
def deploy(env: str) -> str:
"""Deploy the current build to an environment."""
return f"Deployed to {env}"
agent = Agent(
name="ReleaseEngineer",
instructions="You are a release engineer.",
tools=[deploy, MCP("npx -y @modelcontextprotocol/server-filesystem /tmp")],
approval=True, # guide — human gate before risky tools run
)
agent.start("Deploy to staging, then list the files you can read")
```
### Layer 4 · Loop — *When do we stop?*
Hard iteration caps, budget ceilings, no-progress detection and completion checks — every brake is explicit.
```python
from praisonaiagents import Agent, ExecutionConfig
agent = Agent(
instructions="Fix the failing tests.",
execution=ExecutionConfig(max_iter=30, max_budget=0.50, on_budget_exceeded="stop"),
autonomy=True, # required to drive the loop with run_autonomous()
)
result = agent.run_autonomous("Refactor the auth module", max_iterations=5)
print(result.completion_reason)
# goal | no_tool_calls | max_iterations | timeout | doom_loop | needs_help | error
# (with on_budget_exceeded="stop", hitting the cap raises BudgetExceededError,
# surfaced here as completion_reason="error")
```
> **Doom-loop detection is on by default.** Repeated identical tool calls and A→B→A→B oscillation get caught — while a poller whose output keeps changing does not. [📖 Doom Loop Detection](https://docs.praison.ai/docs/features/doom-loop-detection)
### Layer 5 · Graph — *Who runs when, and who checks whom?*
Topology as a versionable artifact: prompt chaining, routing, parallelisation, orchestrator-worker.
```python
from praisonaiagents import AgentFlow
from praisonaiagents.workflows import route, parallel, repeat
flow = AgentFlow(steps=[
classifier,
route({"bug": [bug_agent], "feature": [feature_agent], "default": [triage]}),
parallel([reviewer, tester]), # fan out, join automatically
repeat(editor, until=lambda ctx: "approved" in ctx.previous_result.lower(),
max_iterations=3), # evaluator–optimizer
])
flow.run("Ticket #123: login fails on Safari")
```
> The same graph is expressible in YAML with no Python at all. [📖 AgentFlow](https://docs.praison.ai/docs/concepts/agentflow)
### ⬡ Outside the stack: Managed Agents — *Where does it actually run?*
The harness is commoditising; **where** the agent executes is the next multiplier. Rather than burning your laptop's CPU, hand an agent a short-lived cloud sandbox — repo, tools and tests run there.
```bash
pip install praisonai
```
The simplest way in is `tools_run_on=` — one whole team or workflow shares **one** sandbox, so a file written by step 1 is there for step 2. Thinking stays on your machine:
```python
from praisonaiagents import Agent, AgentFlow
writer = Agent(name="Writer", instructions="You write files.")
reader = Agent(name="Reader", instructions="You read files.")
flow = AgentFlow(tools_run_on="docker", steps=[writer, reader]) # or e2b | modal | daytona | flyio
flow.run("Write 'hello' to /workspace/note.txt, then read it back")
```
Same thing with no Python at all:
```yaml
name: remote-demo
tools_run_on: docker # every step shares one sandbox
agents:
writer: {role: Writer, goal: Write files}
reader: {role: Reader, goal: Read files}
steps:
- agent: writer
action: "Write 'hello' to /workspace/note.txt"
- agent: reader
action: "Read /workspace/note.txt"
```
For a single agent, two words cover it — and they answer different questions:
```python
from praisonaiagents import Agent
# A. Only the TOOLS move. Thinking stays on your machine.
agent = Agent(name="builder", instructions="You build things.",
tools_run_on="docker") # docker | e2b | modal | daytona | flyio
# tenki | sandlock | ssh | novita | subprocess
# B. The WHOLE agent moves — model calls, loop and tools
agent = Agent(name="teacher", instructions="You teach.", run_on="anthropic") # hosted
agent = Agent(name="builder", instructions="You build.", run_on="docker") # self-hosted
agent.start("Write a Python script that prints the first 10 primes, then run it")
```
Ask any object where it runs, and it will tell you:
```python
>>> Agent(name="builder", instructions="x", tools_run_on="docker")
Agent(name='builder', thinks_on='this machine', tools_run_on='a Docker container')
>>> agent.where_does_it_run()
Thinking (the AI model calls) happens on this machine.
Tools run on a Docker container.
Your own tools (check_db) still run on this machine -- only shell, file and
code tools move. They read and write this machine's files.
```
Naming a place that cannot do the job is a typo, not a preference, so it says so:
```python
>>> Agent(name="x", instructions="i", run_on="e2b")
TypeError: Agent(run_on='e2b') is not valid: run_on= places the whole agent
-- model calls, loop and tools -- on a managed runtime, and 'e2b' runs
commands but cannot host an agent loop.
To run only the tools there: Agent(tools_run_on='e2b')
```
To run one block of code somewhere else, name the place on that call:
```python
agent.execute_code_sync("print(6 * 7)", run_in="sandlock") # kernel-enforced
```
See what is running and reclaim strays:
```bash
praisonai managed ps # list running sandboxes
praisonai managed stop --all # reclaim them
```
Sandboxes shut themselves down when idle (`auto_shutdown`, `idle_timeout_s`), and a post-setup snapshot is reused so the next run skips the image pull and dependency install. Commit a `.praisonai/environment.yaml` and the environment travels with the repo.
> 📖 [20 runnable examples](examples/python/managed-agents/) · manage sessions with `praisonai managed sessions list <agent-id>` or `praisonai managed sessions resume <session-id> "<prompt>"`
<sub>Stack framing adapted from [The Five-Layer Agent Stack](https://mer.vin/2026/07/five-layer-agent-stack-match-bug-to-right-layer/) and [Agent Harnesses vs Orbs](https://mer.vin/2026/08/agent-harnesses-vs-orbs-why-remote-sandboxes-beat-local-agent-loops/).</sub>
---
## 🌌 The PraisonAI Ecosystem
Start simple with the core SDK, or expand to full visual builders and dashboards when you're ready.
@@ -416,9 +200,9 @@ Powered by 100+ LLMs (OpenAI, Anthropic, Gemini & local models).
| 🧠 | **Planning Mode** — plan → execute → reason | `planning=True` |
| 🔍 | **Deep Research** — multi-step autonomous research | [Docs](https://docs.praison.ai/docs/agents/deep-research) |
| 🤖 | **External Agents** — orchestrate Claude Code, Gemini CLI, Codex | [Docs](https://docs.praison.ai/docs/code/external-agents) |
| 🔄 | **Agent Handoffs** — seamless conversation passing | `handoffs=[other_agent]` |
| 🔄 | **Agent Handoffs** — seamless conversation passing | `handoff=True` |
| 🛡️ | **Guardrails** — input/output validation | [Docs](https://docs.praison.ai/docs/concepts/guardrails) |
| | **Web Search + Fetch** — native browsing | `web=True` |
| | **Web Search + Fetch** — native browsing | `web_search=True` |
| 🪞 | **Self Reflection** — agent reviews its own output | [Docs](https://docs.praison.ai/docs/concepts/reflection) |
| 🔀 | **Workflow Patterns** — route, parallel, loop, repeat | [Docs](https://docs.praison.ai/docs/concepts/agentflow) |
| 🧠 | **Memory (zero deps)** — works out of the box | `memory=True` |
@@ -428,9 +212,9 @@ Powered by 100+ LLMs (OpenAI, Anthropic, Gemini & local models).
| | Feature | How |
|--|---------|-----|
| 💡 | **Prompt Caching** — reduce latency + cost | `caching=True` |
| 💡 | **Prompt Caching** — reduce latency + cost | `prompt_caching=True` |
| 💾 | **Sessions + Auto-Save** — persistent state across restarts | `auto_save="my-project"` |
| 💭 | **Thinking Budgets** — control reasoning depth | `agent.thinking_budget = 1024` |
| 💭 | **Thinking Budgets** — control reasoning depth | `thinking_budget=1024` |
| 📚 | **RAG + Quality-Based RAG** — auto quality scoring retrieval | [Docs](https://docs.praison.ai/docs/concepts/rag) |
| 📊 | **Model Router** — auto-routes to cheapest capable model | [Docs](https://docs.praison.ai/docs/features/model-router) |
| 🧊 | **Shadow Git Checkpoints** — auto-rollback on failure | [Docs](https://docs.praison.ai/docs/features/checkpoints) |
@@ -557,10 +341,8 @@ from praisonaiagents import Agent, db
agent = Agent(
name="Assistant",
memory={
"db": db(database_url="postgresql://localhost/mydb"),
"session_id": "my-session",
},
db=db(database_url="postgresql://localhost/mydb"),
session_id="my-session"
)
agent.chat("Hello!") # Auto-persists messages, runs, traces
```
@@ -1006,16 +788,6 @@ PraisonAI is built for speed, with agent instantiation in around 14μs. This red
---
<p align="center">
<img src=".github/images/agentflow.gif" alt="PraisonAI AgentFlow" width="800" />
</p>
<p align="center">
<img src=".github/images/latest_ai_news_and_crawl_each_url_to_find_info.gif" alt="PraisonAI command execution" width="800" />
</p>
\* `export TAVILY_API_KEY=xxxxx`
## 🔍 Langfuse Tracing
```bash
@@ -1119,10 +891,8 @@ from praisonaiagents import Agent, db
agent = Agent(
name="Assistant",
memory={
"db": db(database_url="postgresql://localhost/mydb"),
"session_id": "my-session",
},
db=db(database_url="postgresql://localhost/mydb"),
session_id="my-session"
)
```
@@ -1138,8 +908,8 @@ from praisonaiagents import Agent
agent = Agent(
name="Assistant",
# Enables file-based memory (no extra deps!)
memory={"user_id": "user123"},
memory=True, # Enables file-based memory (no extra deps!)
user_id="user123"
)
```
+1 -8
View File
@@ -8,18 +8,11 @@ PraisonAI takes security seriously. We appreciate responsible disclosure from re
|---------|----------|-------------|
| `praisonaiagents` | [PyPI](https://pypi.org/project/praisonaiagents/) | `src/praisonai-agents/` |
| `praisonai` | [PyPI](https://pypi.org/project/praisonai/) | `src/praisonai/` |
| `praisonai-platform` | [PyPI](https://pypi.org/project/praisonai-platform/) | `src/praisonai-platform/` |
| `praisonai` | [npm](https://www.npmjs.com/package/praisonai) | `src/praisonai-ts/` |
Report issues against the **specific package** where the vulnerability exists. A platform-only issue does not necessarily affect the core SDK, and vice versa.
### Packages maintained in their own repositories
`praisonai-platform` now lives at
[MervinPraison/PraisonAI-Platform](https://github.com/MervinPraison/PraisonAI-Platform).
Report platform vulnerabilities through
[that repository's advisories](https://github.com/MervinPraison/PraisonAI-Platform/security/advisories/new),
not here — it is versioned and released independently of the SDK.
## In scope
- Authentication, authorisation, and multi-tenant isolation (e.g. workspace boundaries)
+69 -42
View File
@@ -7,7 +7,7 @@ Regenerate with: `praisonai docs api-md --write`
Types:
```python
from praisonaiagents import ContextPolicy, GuardrailResult, HandoffConfig, HandoffCycleError, HandoffDepthError, HandoffError, HandoffInputData, HandoffResult, HandoffTimeoutError, ReflectionOutput, StepResult, ToolResult, ToolValidationError, WorkflowContext
from praisonaiagents import ContextPolicy, GuardrailResult, HandoffConfig, HandoffCycleError, HandoffDepthError, HandoffError, HandoffInputData, HandoffResult, HandoffTimeoutError, ReflectionOutput, StepResult, TaskOutput, ToolResult, ToolValidationError, WorkflowContext
```
Methods:
@@ -16,6 +16,8 @@ Methods:
* <code title="class HandoffConfig">HandoffConfig.<a href="./src/praisonai-agents/praisonaiagents/agent/handoff.py">from_dict</a>(data: Dict[str, Any]) -> 'HandoffConfig'</code>
* <code title="class HandoffConfig">HandoffConfig.<a href="./src/praisonai-agents/praisonaiagents/agent/handoff.py">to_dict</a>() -> Dict[str, Any]</code>
* <code title="class HandoffResult">HandoffResult.<a href="./src/praisonai-agents/praisonaiagents/agent/handoff.py">from_outcome</a>(outcome: AgentRunOutcome, target_agent: Optional[str] = None, source_agent: Optional[str] = None, handoff_depth: int = 0) -> 'HandoffResult'</code>
* <code title="class TaskOutput">TaskOutput.<a href="./src/praisonai-agents/praisonaiagents/main.py">json</a>() -> Optional[str]</code>
* <code title="class TaskOutput">TaskOutput.<a href="./src/praisonai-agents/praisonaiagents/main.py">to_dict</a>() -> dict</code>
* <code title="class ToolResult">ToolResult.<a href="./src/praisonai-agents/praisonaiagents/tools/base.py">is_multimodal</a>() -> bool</code>
* <code title="class ToolResult">ToolResult.<a href="./src/praisonai-agents/praisonaiagents/tools/base.py">to_dict</a>() -> Dict[str, Any]</code>
@@ -23,21 +25,24 @@ Methods:
Types:
```python
from praisonaiagents import Agent, AutoAgents, AutoRagAgent, ContextAgent, DeepResearchAgent, ImageAgent, PlanningAgent, PraisonAIAgents, PromptExpanderAgent, QueryRewriterAgent, create_context_agent
from praisonaiagents import Agent, AutoAgents, AutoRagAgent, ContextAgent, DeepResearchAgent, ImageAgent, PlanningAgent, PromptExpanderAgent, QueryRewriterAgent, create_context_agent
```
Methods:
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">aclose</a>() -> None</code>
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">add_mcp_server</a>(name: str, mcp: Any) -> Any</code>
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">add_verification</a>(hook: Any) -> None</code>
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">agent_id</a>() -> str</code>
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">analyze_prompt</a>(prompt: str) -> set</code>
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">auto_memory</a>() -> Optional[bool]</code>
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">auto_memory</a>(value: Optional[bool]) -> None</code>
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">background</a>() -> Optional[bool]</code>
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">background</a>(value: Optional[bool]) -> None</code>
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">chat_history</a>()</code>
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">chat_history</a>(value)</code>
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">chat_with_context</a>(message: str, context: 'ContextPack', **kwargs) -> str</code>
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">checkpoints</a>() -> Optional[bool]</code>
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">checkpoints</a>(value: Optional[bool]) -> None</code>
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">clone_for_channel</a>() -> 'Agent'</code>
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">close</a>() -> None</code>
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">console</a>() -> Optional[Any]</code>
@@ -68,12 +73,9 @@ 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>
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">remove_verification</a>(name: str) -> bool</code>
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">retrieval_config</a>() -> Optional[Any]</code>
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">retrieve</a>(query: str, **kwargs) -> 'ContextPack'</code>
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">rules_manager</a>() -> Optional[Any]</code>
@@ -81,7 +83,6 @@ Methods:
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">run_autonomous_async</a>(prompt: str, max_iterations: Optional[int] = None, timeout_seconds: Optional[float] = None, completion_promise: Optional[str] = None, clear_context: bool = False)</code>
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">run_until</a>(prompt: str, criteria: str = '', threshold: float = 8.0, max_iterations: int = 5, mode: str = 'optimize', on_iteration: Optional[Callable[[Any], None]] = None, verbose: bool = False, goal: Optional[str] = None, goal_criteria: Optional[Any] = None, judge_model: Optional[str] = None) -> 'EvaluationLoopResult'</code>
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">run_until_async</a>(prompt: str, criteria: str, threshold: float = 8.0, max_iterations: int = 5, mode: str = 'optimize', on_iteration: Optional[Callable[[Any], None]] = None, verbose: bool = False) -> 'EvaluationLoopResult'</code>
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">set_snapshot_root</a>(project_path: str) -> bool</code>
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">skill_manager</a>() -> Optional[Any]</code>
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">store_memory</a>(content: str, memory_type: str = 'short_term', action: str = 'add', **kwargs: Any) -> None</code>
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">stream_emitter</a>() -> Optional[Any]</code>
@@ -90,7 +91,6 @@ Methods:
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">thinking_budget</a>(value: Optional[int]) -> None</code>
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">total_cost</a>() -> float</code>
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">undo</a>() -> bool</code>
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">where_does_it_run</a>() -> str</code>
* <code title="class AutoAgents">AutoAgents.<a href="./src/praisonai-agents/praisonaiagents/agents/autoagents.py">astart</a>()</code>
* <code title="class AutoAgents">AutoAgents.<a href="./src/praisonai-agents/praisonaiagents/agents/autoagents.py">start</a>()</code>
* <code title="class AutoRagAgent">AutoRagAgent.<a href="./src/praisonai-agents/praisonaiagents/agents/auto_rag_agent.py">achat</a>(message: str, **kwargs) -> str</code>
@@ -179,15 +179,14 @@ Methods:
* <code title="class BaseTool">BaseTool.<a href="./src/praisonai-agents/praisonaiagents/tools/base.py">get_schema</a>() -> Dict[str, Any]</code>
* <code title="class BaseTool">BaseTool.<a href="./src/praisonai-agents/praisonaiagents/tools/base.py">run</a>(**kwargs) -> Any</code>
* <code title="class BaseTool">BaseTool.<a href="./src/praisonai-agents/praisonaiagents/tools/base.py">safe_run</a>(**kwargs) -> ToolResult</code>
* <code title="class BaseTool">BaseTool.<a href="./src/praisonai-agents/praisonaiagents/tools/base.py">to_model_output</a>(result: Any) -> Optional[Any]</code>
* <code title="class BaseTool">BaseTool.<a href="./src/praisonai-agents/praisonaiagents/tools/base.py">validate</a>() -> bool</code>
* <code title="class BaseTool">BaseTool.<a href="./src/praisonai-agents/praisonaiagents/tools/base.py">validate_class</a>() -> bool</code>
* <code title="class BaseTool">BaseTool.<a href="./src/praisonai-agents/praisonaiagents/tools/base.py">validate_schema_roundtrip</a>() -> bool</code>
* <code title="class FunctionTool">FunctionTool.<a href="./src/praisonai-agents/praisonaiagents/tools/decorator.py">__call__</a>(*args, **kwargs) -> Any</code>
* <code title="class FunctionTool">FunctionTool.<a href="./src/praisonai-agents/praisonaiagents/tools/decorator.py">check_availability</a>() -> tuple[bool, str]</code>
* <code title="class FunctionTool">FunctionTool.<a href="./src/praisonai-agents/praisonaiagents/tools/decorator.py">get_schema</a>() -> Dict[str, Any]</code>
* <code title="class FunctionTool">FunctionTool.<a href="./src/praisonai-agents/praisonaiagents/tools/decorator.py">injected_params</a>() -> Dict[str, Any]</code>
* <code title="class FunctionTool">FunctionTool.<a href="./src/praisonai-agents/praisonaiagents/tools/decorator.py">run</a>(**kwargs) -> Any</code>
* <code title="class FunctionTool">FunctionTool.<a href="./src/praisonai-agents/praisonaiagents/tools/decorator.py">to_model_output</a>(result: Any) -> Optional[Any]</code>
* <code title="class ToolRegistry">ToolRegistry.<a href="./src/praisonai-agents/praisonaiagents/tools/registry.py">clear</a>() -> None</code>
* <code title="class ToolRegistry">ToolRegistry.<a href="./src/praisonai-agents/praisonaiagents/tools/registry.py">discover_plugins</a>() -> int</code>
* <code title="class ToolRegistry">ToolRegistry.<a href="./src/praisonai-agents/praisonaiagents/tools/registry.py">discover_single_file_plugins</a>() -> int</code>
@@ -242,12 +241,10 @@ from praisonaiagents import Memory, MemoryBackend, MemoryConfig
Methods:
* <code title="class Memory">Memory.<a href="./src/praisonai-agents/praisonaiagents/memory/memory.py">acommit_memory_batch</a>(writes: List[tuple]) -> None</code>
* <code title="class Memory">Memory.<a href="./src/praisonai-agents/praisonaiagents/memory/memory.py">build_cache_optimized_context</a>(task_descr: str, user_id: Optional[str] = None, additional: str = '', max_items: int = 3, include_cache_boundary: bool = True, include_in_output: Optional[bool] = None) -> Dict[str, str]</code>
* <code title="class Memory">Memory.<a href="./src/praisonai-agents/praisonaiagents/memory/memory.py">build_context_for_task</a>(task_descr: str, user_id: Optional[str] = None, additional: str = '', max_items: int = 3, include_in_output: Optional[bool] = None) -> str</code>
* <code title="class Memory">Memory.<a href="./src/praisonai-agents/praisonaiagents/memory/memory.py">calculate_quality_metrics</a>(output: str, expected_output: str, llm: Optional[str] = None, custom_prompt: Optional[str] = None) -> Dict[str, float]</code>
* <code title="class Memory">Memory.<a href="./src/praisonai-agents/praisonaiagents/memory/memory.py">close_connections</a>()</code>
* <code title="class Memory">Memory.<a href="./src/praisonai-agents/praisonaiagents/memory/memory.py">commit_memory_batch</a>(writes: List[tuple]) -> None</code>
* <code title="class Memory">Memory.<a href="./src/praisonai-agents/praisonaiagents/memory/memory.py">compute_quality_score</a>(completeness: float, relevance: float, clarity: float, accuracy: float, weights: Dict[str, float] = None) -> float</code>
* <code title="class Memory">Memory.<a href="./src/praisonai-agents/praisonaiagents/memory/memory.py">delete_long_term</a>(memory_id: str) -> bool</code>
* <code title="class Memory">Memory.<a href="./src/praisonai-agents/praisonaiagents/memory/memory.py">delete_memories</a>(memory_ids: List[str]) -> int</code>
@@ -255,13 +252,9 @@ Methods:
* <code title="class Memory">Memory.<a href="./src/praisonai-agents/praisonaiagents/memory/memory.py">delete_memory</a>(memory_id: str, memory_type: Optional[str] = None) -> bool</code>
* <code title="class Memory">Memory.<a href="./src/praisonai-agents/praisonaiagents/memory/memory.py">delete_short_term</a>(memory_id: str) -> bool</code>
* <code title="class Memory">Memory.<a href="./src/praisonai-agents/praisonaiagents/memory/memory.py">finalize_task_output</a>(content: str, agent_name: str, quality_score: float, threshold: float = 0.7, metrics: Dict[str, Any] = None, task_id: str = None)</code>
* <code title="class Memory">Memory.<a href="./src/praisonai-agents/praisonaiagents/memory/memory.py">forget</a>(**kwargs) -> int</code>
* <code title="class Memory">Memory.<a href="./src/praisonai-agents/praisonaiagents/memory/memory.py">get_all_memories</a>() -> List[Dict[str, Any]]</code>
* <code title="class Memory">Memory.<a href="./src/praisonai-agents/praisonaiagents/memory/memory.py">get_context</a>(query: Optional[str] = None, **kwargs) -> str</code>
* <code title="class Memory">Memory.<a href="./src/praisonai-agents/praisonaiagents/memory/memory.py">get_learn_context</a>() -> str</code>
* <code title="class Memory">Memory.<a href="./src/praisonai-agents/praisonaiagents/memory/memory.py">learn</a>()</code>
* <code title="class Memory">Memory.<a href="./src/praisonai-agents/praisonaiagents/memory/memory.py">recall</a>(query: str, **kwargs) -> List[Dict[str, Any]]</code>
* <code title="class Memory">Memory.<a href="./src/praisonai-agents/praisonaiagents/memory/memory.py">remember</a>(content: str, **kwargs) -> str</code>
* <code title="class Memory">Memory.<a href="./src/praisonai-agents/praisonaiagents/memory/memory.py">reset_all</a>()</code>
* <code title="class Memory">Memory.<a href="./src/praisonai-agents/praisonaiagents/memory/memory.py">reset_entity_only</a>()</code>
* <code title="class Memory">Memory.<a href="./src/praisonai-agents/praisonaiagents/memory/memory.py">reset_long_term</a>()</code>
@@ -269,8 +262,8 @@ Methods:
* <code title="class Memory">Memory.<a href="./src/praisonai-agents/praisonaiagents/memory/memory.py">reset_user_memory</a>()</code>
* <code title="class Memory">Memory.<a href="./src/praisonai-agents/praisonaiagents/memory/memory.py">search</a>(query: str, user_id: Optional[str] = None, agent_id: Optional[str] = None, run_id: Optional[str] = None, limit: int = 5, rerank: bool = False, **kwargs) -> List[Dict[str, Any]]</code>
* <code title="class Memory">Memory.<a href="./src/praisonai-agents/praisonaiagents/memory/memory.py">search_entity</a>(query: str, limit: int = 5) -> List[Dict[str, Any]]</code>
* <code title="class Memory">Memory.<a href="./src/praisonai-agents/praisonaiagents/memory/memory.py">search_long_term</a>(query: str, limit: int = 5, relevance_cutoff: float = 0.0, min_quality: float = 0.0, rerank: bool = False, metadata_filter: Optional[Dict[str, Any]] = None, user_id: Optional[str] = None, **kwargs) -> List[Dict[str, Any]]</code>
* <code title="class Memory">Memory.<a href="./src/praisonai-agents/praisonaiagents/memory/memory.py">search_short_term</a>(query: str, limit: int = 5, min_quality: float = 0.0, relevance_cutoff: float = 0.0, rerank: bool = False, metadata_filter: Optional[Dict[str, Any]] = None, user_id: Optional[str] = None, **kwargs) -> List[Dict[str, Any]]</code>
* <code title="class Memory">Memory.<a href="./src/praisonai-agents/praisonaiagents/memory/memory.py">search_long_term</a>(query: str, limit: int = 5, relevance_cutoff: float = 0.0, min_quality: float = 0.0, rerank: bool = False, **kwargs) -> List[Dict[str, Any]]</code>
* <code title="class Memory">Memory.<a href="./src/praisonai-agents/praisonaiagents/memory/memory.py">search_short_term</a>(query: str, limit: int = 5, min_quality: float = 0.0, relevance_cutoff: float = 0.0, rerank: bool = False, **kwargs) -> List[Dict[str, Any]]</code>
* <code title="class Memory">Memory.<a href="./src/praisonai-agents/praisonaiagents/memory/memory.py">search_user_memory</a>(user_id: str, query: str, limit: int = 5, rerank: bool = False, **kwargs) -> List[Dict[str, Any]]</code>
* <code title="class Memory">Memory.<a href="./src/praisonai-agents/praisonaiagents/memory/memory.py">search_with_quality</a>(query: str, min_quality: float = 0.0, memory_type: Literal['short', 'long'] = 'long', limit: int = 5) -> List[Dict[str, Any]]</code>
* <code title="class Memory">Memory.<a href="./src/praisonai-agents/praisonaiagents/memory/memory.py">store_entity</a>(name: str, type_: str, desc: str, relations: str)</code>
@@ -470,7 +463,7 @@ Methods:
Types:
```python
from praisonaiagents import SkillLoader, SkillsConfig
from praisonaiagents import SkillLoader, SkillManager, SkillMetadata, SkillProperties, SkillsConfig
```
Methods:
@@ -482,6 +475,54 @@ Methods:
* <code title="class SkillLoader">SkillLoader.<a href="./src/praisonai-agents/praisonaiagents/skills/loader.py">load_metadata</a>(skill_path: str) -> Optional[LoadedSkill]</code>
* <code title="class SkillLoader">SkillLoader.<a href="./src/praisonai-agents/praisonaiagents/skills/loader.py">load_references</a>(skill: LoadedSkill) -> dict</code>
* <code title="class SkillLoader">SkillLoader.<a href="./src/praisonai-agents/praisonaiagents/skills/loader.py">load_scripts</a>(skill: LoadedSkill) -> dict</code>
* <code title="class SkillManager">SkillManager.<a href="./src/praisonai-agents/praisonaiagents/skills/manager.py">activate</a>(skill: LoadedSkill) -> bool</code>
* <code title="class SkillManager">SkillManager.<a href="./src/praisonai-agents/praisonaiagents/skills/manager.py">activate_by_name</a>(name: str) -> bool</code>
* <code title="class SkillManager">SkillManager.<a href="./src/praisonai-agents/praisonaiagents/skills/manager.py">add_bundle</a>(manifest: 'BundleManifest') -> None</code>
* <code title="class SkillManager">SkillManager.<a href="./src/praisonai-agents/praisonaiagents/skills/manager.py">add_skill</a>(skill_path: str) -> Optional[LoadedSkill]</code>
* <code title="class SkillManager">SkillManager.<a href="./src/praisonai-agents/praisonaiagents/skills/manager.py">add_skill_by_name</a>(name: str, skill_dirs: Optional[List[str]] = None, include_defaults: bool = True) -> Optional[LoadedSkill]</code>
* <code title="class SkillManager">SkillManager.<a href="./src/praisonai-agents/praisonaiagents/skills/manager.py">approve</a>(identifier: str) -> dict</code>
* <code title="class SkillManager">SkillManager.<a href="./src/praisonai-agents/praisonaiagents/skills/manager.py">archive_skill</a>(name: str) -> dict</code>
* <code title="class SkillManager">SkillManager.<a href="./src/praisonai-agents/praisonaiagents/skills/manager.py">bundle_names</a>() -> List[str]</code>
* <code title="class SkillManager">SkillManager.<a href="./src/praisonai-agents/praisonaiagents/skills/manager.py">bundles</a>() -> List['BundleManifest']</code>
* <code title="class SkillManager">SkillManager.<a href="./src/praisonai-agents/praisonaiagents/skills/manager.py">clear</a>() -> None</code>
* <code title="class SkillManager">SkillManager.<a href="./src/praisonai-agents/praisonaiagents/skills/manager.py">create</a>(name: str, content: str, category: Optional[str] = None, propose: Optional[bool] = None) -> dict</code>
* <code title="class SkillManager">SkillManager.<a href="./src/praisonai-agents/praisonaiagents/skills/manager.py">create_skill</a>(name: str, content: str, category: str = None, agent_created: bool = True, propose: Optional[bool] = None, base_dir: Optional[str] = None) -> dict</code>
* <code title="class SkillManager">SkillManager.<a href="./src/praisonai-agents/praisonaiagents/skills/manager.py">delete</a>(name: str, propose: Optional[bool] = None) -> dict</code>
* <code title="class SkillManager">SkillManager.<a href="./src/praisonai-agents/praisonaiagents/skills/manager.py">delete_skill</a>(name: str, hard: bool = False, propose: Optional[bool] = None) -> dict</code>
* <code title="class SkillManager">SkillManager.<a href="./src/praisonai-agents/praisonaiagents/skills/manager.py">discover</a>(skill_dirs: Optional[List[str]] = None, include_defaults: bool = True) -> int</code>
* <code title="class SkillManager">SkillManager.<a href="./src/praisonai-agents/praisonaiagents/skills/manager.py">discover_bundles</a>(skill_dirs: Optional[List[str]] = None, include_defaults: bool = True) -> int</code>
* <code title="class SkillManager">SkillManager.<a href="./src/praisonai-agents/praisonaiagents/skills/manager.py">edit</a>(name: str, content: str, propose: Optional[bool] = None) -> dict</code>
* <code title="class SkillManager">SkillManager.<a href="./src/praisonai-agents/praisonaiagents/skills/manager.py">edit_skill</a>(name: str, content: str, propose: Optional[bool] = None) -> dict</code>
* <code title="class SkillManager">SkillManager.<a href="./src/praisonai-agents/praisonaiagents/skills/manager.py">get_allowed_tools</a>(name: str) -> List[str]</code>
* <code title="class SkillManager">SkillManager.<a href="./src/praisonai-agents/praisonaiagents/skills/manager.py">get_available_skills</a>() -> List[SkillMetadata]</code>
* <code title="class SkillManager">SkillManager.<a href="./src/praisonai-agents/praisonaiagents/skills/manager.py">get_available_skills_by_state</a>(state: SkillState) -> List[LoadedSkill]</code>
* <code title="class SkillManager">SkillManager.<a href="./src/praisonai-agents/praisonaiagents/skills/manager.py">get_bundle</a>(name: str) -> Optional['BundleManifest']</code>
* <code title="class SkillManager">SkillManager.<a href="./src/praisonai-agents/praisonaiagents/skills/manager.py">get_bundle_instructions</a>() -> List[str]</code>
* <code title="class SkillManager">SkillManager.<a href="./src/praisonai-agents/praisonaiagents/skills/manager.py">get_instructions</a>(name: str) -> Optional[str]</code>
* <code title="class SkillManager">SkillManager.<a href="./src/praisonai-agents/praisonaiagents/skills/manager.py">get_skill</a>(name: str) -> Optional[LoadedSkill]</code>
* <code title="class SkillManager">SkillManager.<a href="./src/praisonai-agents/praisonaiagents/skills/manager.py">get_skills_diagnostics</a>() -> Dict[str, ValidationResult]</code>
* <code title="class SkillManager">SkillManager.<a href="./src/praisonai-agents/praisonaiagents/skills/manager.py">get_user_invocable_skills</a>() -> List[LoadedSkill]</code>
* <code title="class SkillManager">SkillManager.<a href="./src/praisonai-agents/praisonaiagents/skills/manager.py">invoke</a>(name: str, raw_args: str = '', session_id: Optional[str] = None, shell_exec: bool = False) -> Optional[str]</code>
* <code title="class SkillManager">SkillManager.<a href="./src/praisonai-agents/praisonaiagents/skills/manager.py">list_archived_skills</a>() -> List[str]</code>
* <code title="class SkillManager">SkillManager.<a href="./src/praisonai-agents/praisonaiagents/skills/manager.py">list_pending</a>() -> List[dict]</code>
* <code title="class SkillManager">SkillManager.<a href="./src/praisonai-agents/praisonaiagents/skills/manager.py">load_resources</a>(name: str) -> bool</code>
* <code title="class SkillManager">SkillManager.<a href="./src/praisonai-agents/praisonaiagents/skills/manager.py">patch</a>(name: str, old_string: str, new_string: str, file_path: Optional[str] = None, replace_all: bool = False, propose: Optional[bool] = None) -> dict</code>
* <code title="class SkillManager">SkillManager.<a href="./src/praisonai-agents/praisonaiagents/skills/manager.py">patch_skill</a>(name: str, old_string: str, new_string: str, file_path: str = None, replace_all: bool = False, propose: Optional[bool] = None) -> dict</code>
* <code title="class SkillManager">SkillManager.<a href="./src/praisonai-agents/praisonaiagents/skills/manager.py">reject</a>(identifier: str) -> dict</code>
* <code title="class SkillManager">SkillManager.<a href="./src/praisonai-agents/praisonaiagents/skills/manager.py">remove_file</a>(name: str, file_path: str, propose: Optional[bool] = None) -> dict</code>
* <code title="class SkillManager">SkillManager.<a href="./src/praisonai-agents/praisonaiagents/skills/manager.py">remove_skill_file</a>(name: str, file_path: str, propose: Optional[bool] = None) -> dict</code>
* <code title="class SkillManager">SkillManager.<a href="./src/praisonai-agents/praisonaiagents/skills/manager.py">resolve</a>(selectors: List[str]) -> List[str]</code>
* <code title="class SkillManager">SkillManager.<a href="./src/praisonai-agents/praisonaiagents/skills/manager.py">restore_skill</a>(name: str, skill_dir: Optional[str] = None) -> dict</code>
* <code title="class SkillManager">SkillManager.<a href="./src/praisonai-agents/praisonaiagents/skills/manager.py">rollback_skill</a>(name: str) -> dict</code>
* <code title="class SkillManager">SkillManager.<a href="./src/praisonai-agents/praisonaiagents/skills/manager.py">skill_names</a>() -> List[str]</code>
* <code title="class SkillManager">SkillManager.<a href="./src/praisonai-agents/praisonaiagents/skills/manager.py">skills</a>() -> List[LoadedSkill]</code>
* <code title="class SkillManager">SkillManager.<a href="./src/praisonai-agents/praisonaiagents/skills/manager.py">to_prompt</a>() -> str</code>
* <code title="class SkillManager">SkillManager.<a href="./src/praisonai-agents/praisonaiagents/skills/manager.py">validate_skill_capabilities</a>(skill_name: str, force_refresh: bool = False) -> ValidationResult</code>
* <code title="class SkillManager">SkillManager.<a href="./src/praisonai-agents/praisonaiagents/skills/manager.py">write_file</a>(name: str, file_path: str, file_content: str, propose: Optional[bool] = None) -> dict</code>
* <code title="class SkillManager">SkillManager.<a href="./src/praisonai-agents/praisonaiagents/skills/manager.py">write_skill_file</a>(name: str, file_path: str, file_content: str, propose: Optional[bool] = None) -> dict</code>
* <code title="class SkillMetadata">SkillMetadata.<a href="./src/praisonai-agents/praisonaiagents/skills/models.py">from_properties</a>(props: SkillProperties) -> 'SkillMetadata'</code>
* <code title="class SkillProperties">SkillProperties.<a href="./src/praisonai-agents/praisonaiagents/skills/models.py">idle_days</a>() -> Optional[float]</code>
* <code title="class SkillProperties">SkillProperties.<a href="./src/praisonai-agents/praisonaiagents/skills/models.py">to_dict</a>() -> dict</code>
* <code title="class SkillsConfig">SkillsConfig.<a href="./src/praisonai-agents/praisonaiagents/config/feature_configs.py">to_dict</a>() -> Dict[str, Any]</code>
# Session
@@ -527,7 +568,6 @@ Methods:
* <code title="class MCP">MCP.<a href="./src/praisonai-agents/praisonaiagents/mcp/mcp.py">get_prompts</a>() -> List[dict]</code>
* <code title="class MCP">MCP.<a href="./src/praisonai-agents/praisonaiagents/mcp/mcp.py">get_resources</a>() -> List[dict]</code>
* <code title="class MCP">MCP.<a href="./src/praisonai-agents/praisonaiagents/mcp/mcp.py">get_tools</a>() -> List[Callable]</code>
* <code title="class MCP">MCP.<a href="./src/praisonai-agents/praisonaiagents/mcp/mcp.py">list_active_server_names</a>() -> set</code>
* <code title="class MCP">MCP.<a href="./src/praisonai-agents/praisonaiagents/mcp/mcp.py">shutdown</a>()</code>
* <code title="class MCP">MCP.<a href="./src/praisonai-agents/praisonaiagents/mcp/mcp.py">to_openai_tool</a>()</code>
* <code title="class MCP">MCP.<a href="./src/praisonai-agents/praisonaiagents/mcp/mcp.py">with_tool_prefix</a>(prefix: str) -> 'MCP'</code>
@@ -691,7 +731,7 @@ Methods:
Types:
```python
from praisonaiagents import AgentAppConfig, AgentAppProtocol, AgentFlow, AgentManager, AgentOSConfig, AgentOSProtocol, AgentTeam, AutoApproveBackend, EmbeddingResult, RetryBackoffConfig, RunOutcome, __version__, aembedding, aembeddings, embedding, embeddings, get_dimensions
from praisonaiagents import AgentAppConfig, AgentAppProtocol, AgentFlow, AgentManager, AgentOSConfig, AgentOSProtocol, AgentTeam, AutoApproveBackend, EmbeddingResult, RetryBackoffConfig, __version__, aembedding, aembeddings, embedding, embeddings, get_dimensions
```
Methods:
@@ -714,7 +754,6 @@ Methods:
* <code title="class AgentFlow">AgentFlow.<a href="./src/praisonai-agents/praisonaiagents/workflows/workflows.py">to_dict</a>() -> Dict[str, Any]</code>
* <code title="class AgentFlow">AgentFlow.<a href="./src/praisonai-agents/praisonaiagents/workflows/workflows.py">verbose</a>() -> bool</code>
* <code title="class AgentFlow">AgentFlow.<a href="./src/praisonai-agents/praisonaiagents/workflows/workflows.py">verbose</a>(value: bool)</code>
* <code title="class AgentFlow">AgentFlow.<a href="./src/praisonai-agents/praisonaiagents/workflows/workflows.py">where_does_it_run</a>() -> str</code>
* <code title="class AgentOSProtocol">AgentOSProtocol.<a href="./src/praisonai-agents/praisonaiagents/app/protocols.py">get_app</a>() -> Any</code>
* <code title="class AgentOSProtocol">AgentOSProtocol.<a href="./src/praisonai-agents/praisonaiagents/app/protocols.py">serve</a>(host: Optional[str] = None, port: Optional[int] = None, reload: bool = False, **kwargs: Any) -> None</code>
* <code title="class AgentTeam">AgentTeam.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">aannounce_completion</a>(agent_id: str, task_id: str, result: Any, success: bool = True, error: Optional[str] = None, metadata: Optional[Dict[str, Any]] = None) -> None</code>
@@ -726,7 +765,6 @@ Methods:
* <code title="class AgentTeam">AgentTeam.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">arun_task</a>(task_id)</code>
* <code title="class AgentTeam">AgentTeam.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">aspawn_sub_agent</a>(agent: Agent, task: Any, completion_callback: Optional[Callable[[SubAgentCompletionEvent], Any]] = None, metadata: Optional[Dict[str, Any]] = None) -> SpawnedSubAgent</code>
* <code title="class AgentTeam">AgentTeam.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">astart</a>(content = None, return_dict = False, **kwargs)</code>
* <code title="class AgentTeam">AgentTeam.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">astart_for_each</a>(inputs, **kwargs)</code>
* <code title="class AgentTeam">AgentTeam.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">await_for_completions</a>(timeout: Optional[float] = None, agent_ids: Optional[List[str]] = None) -> List[SubAgentCompletionEvent]</code>
* <code title="class AgentTeam">AgentTeam.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">clean_json_output</a>(output: str) -> str</code>
* <code title="class AgentTeam">AgentTeam.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">clear_state</a>() -> None</code>
@@ -751,28 +789,22 @@ Methods:
* <code title="class AgentTeam">AgentTeam.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">get_token_usage_summary</a>() -> Dict[str, Any]</code>
* <code title="class AgentTeam">AgentTeam.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">has_state</a>(key: str) -> bool</code>
* <code title="class AgentTeam">AgentTeam.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">increment_state</a>(key: str, amount: float = 1, default: float = 0) -> float</code>
* <code title="class AgentTeam">AgentTeam.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">launch</a>(path: str = '/agents', port: int = 8000, host: str = '127.0.0.1', debug: bool = False, protocol: str = 'http')</code>
* <code title="class AgentTeam">AgentTeam.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">launch</a>(path: str = '/agents', port: int = 8000, host: str = '0.0.0.0', debug: bool = False, protocol: str = 'http')</code>
* <code title="class AgentTeam">AgentTeam.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">restore_session_state</a>(session_id: str) -> bool</code>
* <code title="class AgentTeam">AgentTeam.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">run</a>(content = None, return_dict = False, **kwargs)</code>
* <code title="class AgentTeam">AgentTeam.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">run_all_tasks</a>()</code>
* <code title="class AgentTeam">AgentTeam.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">run_task</a>(task_id)</code>
* <code title="class AgentTeam">AgentTeam.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">save_output_to_file</a>(task, task_output)</code>
* <code title="class AgentTeam">AgentTeam.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">save_session_state</a>(session_id: str, include_memory: bool = True) -> bool</code>
* <code title="class AgentTeam">AgentTeam.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">save_session_state</a>(session_id: str, include_memory: bool = True) -> None</code>
* <code title="class AgentTeam">AgentTeam.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">set_state</a>(key: str, value: Any) -> None</code>
* <code title="class AgentTeam">AgentTeam.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">spawn_sub_agent</a>(agent: Agent, task: Any, completion_callback: Optional[Callable[[SubAgentCompletionEvent], Any]] = None, metadata: Optional[Dict[str, Any]] = None) -> SpawnedSubAgent</code>
* <code title="class AgentTeam">AgentTeam.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">start</a>(content = None, return_dict = False, output = None, **kwargs)</code>
* <code title="class AgentTeam">AgentTeam.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">start_for_each</a>(inputs, **kwargs)</code>
* <code title="class AgentTeam">AgentTeam.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">stream_emitter</a>()</code>
* <code title="class AgentTeam">AgentTeam.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">todo_list</a>()</code>
* <code title="class AgentTeam">AgentTeam.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">update_plan_step_status</a>(step_id: str, status: str) -> bool</code>
* <code title="class AgentTeam">AgentTeam.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">update_state</a>(updates: Dict) -> None</code>
* <code title="class AgentTeam">AgentTeam.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">wait_for_completions</a>(timeout: Optional[float] = None, agent_ids: Optional[List[str]] = None) -> List[SubAgentCompletionEvent]</code>
* <code title="class AgentTeam">AgentTeam.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">where_does_it_run</a>() -> str</code>
* <code title="class AutoApproveBackend">AutoApproveBackend.<a href="./src/praisonai-agents/praisonaiagents/approval/backends.py">request_approval</a>(request: ApprovalRequest) -> ApprovalDecision</code>
* <code title="class AutoApproveBackend">AutoApproveBackend.<a href="./src/praisonai-agents/praisonaiagents/approval/backends.py">request_approval_sync</a>(request: ApprovalRequest) -> ApprovalDecision</code>
* <code title="class RunOutcome">RunOutcome.<a href="./src/praisonai-agents/praisonaiagents/agent/run_outcome.py">completed</a>(output: Optional[str] = None) -> 'RunOutcome'</code>
* <code title="class RunOutcome">RunOutcome.<a href="./src/praisonai-agents/praisonaiagents/agent/run_outcome.py">from_exception</a>(exc: BaseException, output: Optional[str] = None) -> 'RunOutcome'</code>
* <code title="class RunOutcome">RunOutcome.<a href="./src/praisonai-agents/praisonaiagents/agent/run_outcome.py">succeeded</a>() -> bool</code>
* <code title="function">praisonaiagents.<a href="./src/praisonai-agents/praisonaiagents/embedding/embed.py">aembedding</a>(input: Union[str, List[str]], model: str = 'text-embedding-3-small', dimensions: Optional[int] = None, encoding_format: str = 'float', timeout: float = 600.0, api_key: Optional[str] = None, api_base: Optional[str] = None, metadata: Optional[Dict[str, Any]] = None, **kwargs) -> EmbeddingResult</code>
* <code title="function">praisonaiagents.<a href="./src/praisonai-agents/praisonaiagents/embedding/embed.py">aembeddings</a>(input: Union[str, List[str]], model: str = 'text-embedding-3-small', dimensions: Optional[int] = None, encoding_format: str = 'float', timeout: float = 600.0, api_key: Optional[str] = None, api_base: Optional[str] = None, metadata: Optional[Dict[str, Any]] = None, **kwargs) -> EmbeddingResult</code>
* <code title="function">praisonaiagents.<a href="./src/praisonai-agents/praisonaiagents/embedding/dimensions.py">get_dimensions</a>(model_name: str) -> int</code>
@@ -781,7 +813,7 @@ 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, CloudProvider, DB, Deploy, DeployConfig, DeployType, HostedAgent, HostedAgentConfig, LocalAgent, LocalAgentConfig, LocalManagedAgent, LocalManagedConfig, ManagedAgent, ManagedConfig, __version__, arun, run
```
# CLI
@@ -849,13 +881,11 @@ Methods:
* <code title="cli">praisonai managed list <a href="./src/praisonai/praisonai/cli/commands/managed.py">--help</a></code>
* <code title="cli">praisonai managed managed-callback <a href="./src/praisonai/praisonai/cli/commands/managed.py">--help</a></code>
* <code title="cli">praisonai managed multi <a href="./src/praisonai/praisonai/cli/commands/managed.py">--help</a></code>
* <code title="cli">praisonai managed ps <a href="./src/praisonai/praisonai/cli/commands/managed.py">--help</a></code>
* <code title="cli">praisonai managed restore <a href="./src/praisonai/praisonai/cli/commands/managed.py">--help</a></code>
* <code title="cli">praisonai managed resume <a href="./src/praisonai/praisonai/cli/commands/managed.py">--help</a></code>
* <code title="cli">praisonai managed run <a href="./src/praisonai/praisonai/cli/commands/managed.py">--help</a></code>
* <code title="cli">praisonai managed save <a href="./src/praisonai/praisonai/cli/commands/managed.py">--help</a></code>
* <code title="cli">praisonai managed show <a href="./src/praisonai/praisonai/cli/commands/managed.py">--help</a></code>
* <code title="cli">praisonai managed stop <a href="./src/praisonai/praisonai/cli/commands/managed.py">--help</a></code>
* <code title="cli">praisonai managed update <a href="./src/praisonai/praisonai/cli/commands/managed.py">--help</a></code>
* <code title="cli">praisonai n8n export <a href="./src/praisonai/praisonai/cli/commands/n8n.py">--help</a></code>
* <code title="cli">praisonai n8n import <a href="./src/praisonai/praisonai/cli/commands/n8n.py">--help</a></code>
@@ -885,7 +915,6 @@ Methods:
* <code title="cli">praisonai recipe list <a href="./src/praisonai/praisonai/cli/commands/recipe.py">--help</a></code>
* <code title="cli">praisonai recipe optimize <a href="./src/praisonai/praisonai/cli/commands/recipe.py">--help</a></code>
* <code title="cli">praisonai recipe run <a href="./src/praisonai/praisonai/cli/commands/recipe.py">--help</a></code>
* <code title="cli">praisonai recipe runs <a href="./src/praisonai/praisonai/cli/commands/recipe.py">--help</a></code>
* <code title="cli">praisonai recipe serve <a href="./src/praisonai/praisonai/cli/commands/recipe.py">--help</a></code>
* <code title="cli">praisonai replay cleanup <a href="./src/praisonai/praisonai/cli/commands/replay.py">--help</a></code>
* <code title="cli">praisonai replay context <a href="./src/praisonai/praisonai/cli/commands/replay.py">--help</a></code>
@@ -902,12 +931,7 @@ Methods:
* <code title="cli">praisonai schedule describe <a href="./src/praisonai/praisonai/cli/commands/schedule.py">--help</a></code>
* <code title="cli">praisonai schedule list <a href="./src/praisonai/praisonai/cli/commands/schedule.py">--help</a></code>
* <code title="cli">praisonai schedule logs <a href="./src/praisonai/praisonai/cli/commands/schedule.py">--help</a></code>
* <code title="cli">praisonai schedule pause <a href="./src/praisonai/praisonai/cli/commands/schedule.py">--help</a></code>
* <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>
* <code title="cli">praisonai schedule stats <a href="./src/praisonai/praisonai/cli/commands/schedule.py">--help</a></code>
@@ -916,7 +940,10 @@ Methods:
* <code title="cli">praisonai schedule suggestion-dismiss <a href="./src/praisonai/praisonai/cli/commands/schedule.py">--help</a></code>
* <code title="cli">praisonai schedule suggestion-propose <a href="./src/praisonai/praisonai/cli/commands/schedule.py">--help</a></code>
* <code title="cli">praisonai schedule suggestions <a href="./src/praisonai/praisonai/cli/commands/schedule.py">--help</a></code>
* <code title="cli">praisonai schedule update <a href="./src/praisonai/praisonai/cli/commands/schedule.py">--help</a></code>
* <code title="cli">praisonai standardise check <a href="./src/praisonai/praisonai/cli/commands/standardise.py">--help</a></code>
* <code title="cli">praisonai standardise fix <a href="./src/praisonai/praisonai/cli/commands/standardise.py">--help</a></code>
* <code title="cli">praisonai standardise init <a href="./src/praisonai/praisonai/cli/commands/standardise.py">--help</a></code>
* <code title="cli">praisonai standardise report <a href="./src/praisonai/praisonai/cli/commands/standardise.py">--help</a></code>
* <code title="cli">praisonai validate check <a href="./src/praisonai/praisonai/cli/commands/validate.py">--help</a></code>
* <code title="cli">praisonai validate schema <a href="./src/praisonai/praisonai/cli/commands/validate.py">--help</a></code>
* <code title="cli">praisonai validate validate <a href="./src/praisonai/praisonai/cli/commands/validate.py">--help</a></code>
@@ -926,7 +953,7 @@ Methods:
Types/Exports:
```ts
export { Agent, AgentTeam, Agents, PraisonAIAgents, Router } from "./agent";
export type { AgentEvent, AgentMessage, AgentStreamOptions, AgentTeamConfig, PraisonAIAgentsConfig, SimpleAgentConfig, SimpleRouteConfig, SimpleRouterConfig, StopReason } from "./agent";
export type { AgentTeamConfig, PraisonAIAgentsConfig, SimpleAgentConfig, SimpleRouteConfig, SimpleRouterConfig } from "./agent";
export { AudioAgent, createAudioAgent } from "./agent/audio";
export type { AudioAgentConfig, AudioProvider, AudioSpeakOptions, AudioSpeakResult, AudioTranscribeOptions, AudioTranscribeResult } from "./agent/audio";
export { ContextAgent, createContextAgent } from "./agent/context";
+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>=4.7.5" \
"praisonai>=4.6.155" \
"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>=4.7.5" \
"praisonai>=4.6.155" \
"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>=4.7.5" \
"praisonai>=4.6.155" \
"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__":
@@ -36,12 +36,6 @@ if __name__ == "__main__":
print(f"Custom agent max_rpm: {agent.max_rpm}")
print(f"Custom agent max_execution_time: {agent.max_execution_time}")
print(f"Custom agent max_retry_limit: {agent.max_retry_limit}")
# max_rpm auto-creates a live RateLimiter (not just a stored number)
assert agent_rate_limited.max_rpm == 10
assert agent_rate_limited._rate_limiter is not None
assert agent_rate_limited._rate_limiter.requests_per_minute == 10
print(f"Rate-limited agent limiter: {agent_rate_limited._rate_limiter}")
# Test custom agent
print("\n--- Custom Execution ---")
-43
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
@@ -157,19 +130,3 @@ These examples comply with MCP Protocol Version 2025-11-25:
- `destructiveHint`: true
- `idempotentHint`: false
- `openWorldHint`: true
## Build Remote Agent (`gbr_pair.py`)
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.
```bash
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
-76
View File
@@ -1,76 +0,0 @@
"""
Build Remote Agent pairing example.
Pair a phone (Build Remote Agent) to this PraisonAI session through the
free MIT gbr-agent. Protocol gbr/1. Phone is spectator + veto.
Requirements:
- gbr-agent v0.6.0+ (`gbr-agent pair && gbr-agent run`)
- GrokBuildRemote-Agents cloned; `npm install` in mcp/gbr-mcp
- pip install praisonaiagents[mcp]
Usage:
python gbr_pair.py
Never put mailbox keys in this file. Phone Settings → Bot API is the
only place the relay key is copied.
Independent product by Linespotting AB. Not affiliated with xAI or SpaceX.
https://grokbuildremote.com/
"""
from praisonaiagents import Agent, MCP
# Clone https://github.com/LinespottingOrg/GrokBuildRemote-Agents.git
## 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. "
"Use GBR tools only to diagnose or attach the local Bot API "
"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"],
),
)
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")
+3 -2
View File
@@ -14,7 +14,7 @@ Expected Output:
Agent responds with state persisted to Redis
"""
from praisonaiagents import Agent, MemoryConfig
from praisonaiagents import Agent
from praisonaiagents.db import db
print("=== Redis State Store (Agent-First) ===")
@@ -28,7 +28,8 @@ my_db = db(
agent = Agent(
name="Assistant",
instructions="You are a helpful assistant.",
memory=MemoryConfig(db=my_db, session_id="redis-state-example"),
memory=my_db,
session_id="redis-state-example"
)
# Chat - state is automatically managed via Redis
@@ -1,111 +0,0 @@
"""
Human Review Between Sequential AgentTeam Tasks
================================================
Demonstrates a human-in-the-loop review gate between sequential tasks using the
existing ``on_task_complete`` hook — no new API required.
IMPORTANT — two different ``on_task_complete`` hooks exist, with DIFFERENT
signatures. Do not confuse them:
AgentTeam(hooks=MultiAgentHooksConfig(on_task_complete=fn))
-> fn(task, task_output) # team-level; gets the Task and its output
Task(on_task_complete=fn)
-> fn(task_output) # 1 param: just the TaskOutput
-> fn(task_output, metadata) # 2+ params: TaskOutput + metadata dict
# NOTE: NOT (task, task_output)
This example uses the TEAM-level hook so we get ``(task, task_output)`` and can
filter which tasks require review by ``task.name``.
Approve / reject / edit:
- approve -> return, workflow continues
- reject -> raise; see "stopping the workflow" note below
- edit -> mutate ``task_output.raw``; downstream tasks that read this task via
``context=[...]`` pick up the edited text
Stopping the workflow on reject
-------------------------------
The TEAM-level hook logs and swallows exceptions, so a bare ``raise`` inside it
does NOT stop the sequential run today. To hard-stop on reject, use the PER-TASK
callback path with the 1-argument signature and ``fail_on_callback_error=True``
(see ``review_output`` / ``t1_strict`` at the bottom of this file).
"""
from praisonaiagents import Agent, Task, AgentTeam
from praisonaiagents.config.feature_configs import MultiAgentHooksConfig
# Only these task names trigger a human review gate.
REVIEW_TASKS = {"research"}
# --- Team-level review gate: signature is (task, task_output) ---------------
def review_gate(task, task_output):
if task.name not in REVIEW_TASKS:
return
print(f"\n--- Review: {task.name} ---\n{task_output.raw}\n")
choice = input("Approve (y), reject (n), edit (e)? ").strip().lower()
if choice == "n":
# NOTE: team-level hook swallows this; see per-task strict path below
# for a version that actually halts the workflow.
raise RuntimeError(f"Human rejected task '{task.name}'")
if choice == "e":
# task.result is the same object as task_output, so mutating .raw here
# propagates to downstream tasks that use context=[this_task].
task_output.raw = input("Edited output: ").strip()
researcher = Agent(name="Researcher", role="Researcher", goal="Research", backstory="Expert")
writer = Agent(name="Writer", role="Writer", goal="Write", backstory="Writer")
t1 = Task(
name="research",
description="List 5 facts about {{topic}}", # {{...}} is the substitution syntax
expected_output="5 bullets",
agent=researcher,
)
t2 = Task(
name="summary",
description="Write 3-sentence summary",
expected_output="3 sentences",
agent=writer,
context=[t1], # reads the (possibly edited) output of t1
)
team = AgentTeam(
agents=[researcher, writer],
tasks=[t1, t2],
process="sequential",
variables={"topic": "REST APIs"}, # substituted into {{topic}} in task descriptions
hooks=MultiAgentHooksConfig(on_task_complete=review_gate),
)
# --- Alternative: per-task strict gate that HALTS on reject -----------------
# Per-task Task.on_task_complete uses the 1-argument signature (task_output).
# With fail_on_callback_error=True a raised exception re-raises and stops the run.
def review_output(task_output):
print(f"\n--- Review output ---\n{task_output.raw}\n")
if input("Approve? (y/n) ").strip().lower() == "n":
raise RuntimeError("Human rejected output")
t1_strict = Task(
name="research",
description="List 5 facts about {{topic}}",
expected_output="5 bullets",
agent=researcher,
variables={"topic": "REST APIs"},
on_task_complete=review_output, # signature: (task_output)
fail_on_callback_error=True, # required so reject halts the workflow
)
if __name__ == "__main__":
# NOTE: template values come from AgentTeam(variables=...), NOT start(inputs=...).
# start() forwards **kwargs but does not consume an ``inputs`` argument.
team.start()
@@ -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()
+22 -3
View File
@@ -1,15 +1,34 @@
import socket
import sys
import threading
import time
from praisonaiagents import Agent
def _wait_until_ready(host: str, port: int, timeout: float = 15.0) -> bool:
"""Poll the MCP server port until it accepts connections or times out."""
deadline = time.time() + timeout
while time.time() < deadline:
with socket.socket(socket.AF_INET, socket.SOCK_STREAM) as sock:
sock.settimeout(1.0)
if sock.connect_ex((host, port)) == 0:
return True
time.sleep(0.25)
return False
if __name__ == "__main__":
host, port = "127.0.0.1", 8080
agent = Agent(name="TweetAgent", instructions="Create a Tweet based on the topic provided")
server = threading.Thread(
target=lambda: agent.launch(port=8080, protocol="mcp", path="/mcp"),
target=lambda: agent.launch(port=port, protocol="mcp", path="/mcp"),
daemon=True,
)
server.start()
time.sleep(2)
print("MCP server started on http://127.0.0.1:8080/mcp")
if _wait_until_ready(host, port):
print(f"MCP server started on http://{host}:{port}/mcp")
else:
print(f"MCP server failed to start on http://{host}:{port}/mcp", file=sys.stderr)
sys.exit(1)
@@ -23,7 +23,6 @@ from praisonaiagents.hooks.verification import (
VerificationResult,
BaseVerificationHook,
CommandVerificationHook,
FileCheckHook,
)
@@ -101,19 +100,7 @@ def main():
print(f" Name: {cmd_hook.name}")
print(f" Command: {cmd_hook.command}")
print(f" Timeout: {cmd_hook.timeout_seconds}s")
# 6. FileCheckHook: declarative, no-shell completion gate
print("\n6. FileCheckHook (declarative completion gate):")
file_hook = FileCheckHook(
name="changelog", path="CHANGELOG.md", non_empty=True
)
file_result = file_hook.run()
print(f" {file_hook.name}: success={file_result.success} — {file_result.output}")
print(
" Gate wiring: when verification_hooks are configured, the autonomous "
"loop cannot finalise with a success outcome while a blocking hook fails."
)
print("\n" + "=" * 60)
print("✓ Verification hooks example completed successfully!")
print("=" * 60)
@@ -86,7 +86,7 @@ def method_1_simple_loop():
agents=[loop_agent],
tasks=[loop_task],
process="workflow",
execution="balanced" # max_iter=10 preset to prevent infinite loops
max_iter=10 # Maximum iterations to prevent infinite loops
)
print(f"🚀 Starting loop processing of {csv_file}")
@@ -64,7 +64,7 @@ def main():
agents=[url_agent],
tasks=[url_task],
process="workflow",
execution="balanced" # max_iter=10 preset; adjust for more URLs
max_iter=10 # Adjust based on how many URLs you have
)
print(f"🚀 Processing URLs from {csv_file}")
+1 -2
View File
@@ -7,8 +7,7 @@ multiple agents and managing real-time communication.
from praisonaiagents import Agent, GatewayConfig, SessionConfig
# Configure the gateway using the typed SDK GatewayConfig.
# In gateway.yaml, the optional ``gateway:`` block is validated at load time (#3050).
# Configure the gateway
gateway_config = GatewayConfig(
host="127.0.0.1",
port=8765,
@@ -141,7 +141,7 @@ class DynamicAgentSystem:
agents=agents,
tasks=tasks,
process=process,
output="verbose" if inputs['depth'] == 'detailed' else "silent"
verbose=inputs['depth'] == 'detailed'
)
result = praison_agents.start()
+2 -2
View File
@@ -7,12 +7,12 @@ allowed_dirs = [
"/path/to/other/allowed/dir"
]
# Pass the executable as the first token and the allowed directories as args
# Use a single string command with allowed directories
filesystem_agent = Agent(
instructions="""You are a helpful assistant that can interact with the filesystem.
Use the available tools when relevant to manage files and directories.""",
llm="gpt-4o-mini",
tools=MCP("npx", args=["-y", "@modelcontextprotocol/server-filesystem", *allowed_dirs])
tools=MCP("npx -y @modelcontextprotocol/server-filesystem", args=allowed_dirs)
)
filesystem_agent.start("List files in the allowed directories")
@@ -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)
@@ -66,7 +66,7 @@ research_task1 = Task(
agents_session1 = AgentTeam(
agents=[research_agent],
tasks=[research_task1],
output="verbose"
session=session1, output="verbose"
)
# Execute first session
@@ -105,7 +105,7 @@ analysis_task = Task(
agents_session2 = AgentTeam(
agents=[analysis_agent],
tasks=[analysis_task],
output="verbose"
session=session2, output="verbose"
)
print("Starting analysis session with previous context...")
@@ -155,7 +155,7 @@ synthesis_task = Task(
agents_recovery = AgentTeam(
agents=[synthesis_agent],
tasks=[synthesis_task],
output="verbose"
session=recovery_session, output="verbose"
)
print("Starting recovery session with full context from previous sessions...")
@@ -205,7 +205,7 @@ review_task = Task(
agents_reviewer = AgentTeam(
agents=[review_agent],
tasks=[review_task],
output="verbose"
session=reviewer_session, output="verbose"
)
print("Starting peer review session by different user...")
@@ -77,35 +77,13 @@ class TrafilaturaTools:
except ValueError:
# Not an IP address, continue with domain validation
pass
# Block common internal domains
if any(hostname.endswith(domain) for domain in ['.local', '.internal', '.localdomain']):
return False
# Block metadata service endpoints
if hostname in ['169.254.169.254', 'metadata.google.internal']:
return False
# Resolve the hostname and reject if any address is internal. The
# checks above only inspect IP *literals*, so a plain domain (or an
# encoded form like a decimal IP or "<internal-ip>.nip.io") still
# passes even though it resolves to an internal address. Resolving
# here closes that SSRF bypass, mirroring the resolve-and-check
# approach already used in praisonaiagents/tools/file_tools.py.
import socket
default_port = 443 if parsed.scheme == 'https' else 80
try:
addrinfos = socket.getaddrinfo(hostname, parsed.port or default_port)
except socket.gaierror:
# Hostname does not resolve; treat it as unsafe.
return False
for addrinfo in addrinfos:
resolved = ipaddress.ip_address(addrinfo[4][0])
if (resolved.is_private or resolved.is_reserved
or resolved.is_loopback or resolved.is_link_local):
return False
return True
return hostname not in ['169.254.169.254', 'metadata.google.internal']
except Exception:
return False
@@ -279,17 +257,7 @@ class TrafilaturaTools:
"newspaper": None,
"spider": None
}
# Validate the URL once before any fetcher runs so the newspaper and
# requests paths below are protected against SSRF, just like the
# trafilatura path (which validates inside extract_content).
if not self._validate_url(url):
error = {"error": f"Invalid or unsafe URL: {url}"}
comparison["trafilatura"] = error
comparison["newspaper"] = error
comparison["spider"] = error
return comparison
# Get Trafilatura extraction
try:
comparison["trafilatura"] = self.extract_content(url)
+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
+1 -1
View File
@@ -24,7 +24,7 @@ Examples for all PraisonAI server types and the unified endpoints CLI.
| `praisonai serve unified --port 8765` | Start unified server |
| `praisonai serve agents --file agents.yaml --port 8000` | Start agents API |
| `praisonai serve recipe --port 8765` | Start recipe server |
| `praisonai mcp serve --transport http-stream --port 8080` | Start MCP server |
| `praisonai serve mcp --transport http --port 8080` | Start MCP server |
| `praisonai serve tools --port 8081` | Start tools MCP server |
| `praisonai serve a2a --port 8082` | Start A2A server |
| `praisonai serve a2u --port 8083` | Start A2U server |
+1 -1
View File
@@ -13,7 +13,7 @@ Usage:
python mcp_http_server.py
# Or use CLI:
praisonai mcp serve --transport http-stream --port 8080
praisonai serve mcp --transport http --port 8080
# Test with curl:
curl http://localhost:8080/mcp/tools
+3 -3
View File
@@ -14,9 +14,9 @@ datasets:
# A small verified subset for a cheap smoke run. Verify against the registry
# with `harbor datasets list` before editing.
task_names:
- terminal-bench/build-pmars
- terminal-bench/bn-fit-modify
- terminal-bench/break-filter-js-from-html
- hello-world
- fix-permissions
- csv-to-parquet
agents:
- import_path: examples.terminal_bench.praisonai_code_agent:PraisonAICodeAgent
+14 -29
View File
@@ -13,14 +13,15 @@ Usage:
-n 4
Architecture:
Harbor Container → `praisonai code -p --output json "TASK" --dangerously-skip-approval`
Harbor Container → `praisonai code "TASK" --dangerously-skip-approval` (headless)
Notes:
- `--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.
- `praisonai code` normally exits 0 and Harbor grades by task verification,
so a benchmark miss does not fail the run — but the real exit status is
propagated so genuine install/auth/startup failures still surface.
- The base `praisonai` package is sufficient; heavy `code` extras are not
required (ACP tools degrade gracefully).
@@ -28,7 +29,6 @@ Dependencies:
pip install harbor praisonai praisonaiagents
"""
import json
import shlex
try:
@@ -81,19 +81,16 @@ class PraisonAICodeAgent(BaseInstalledAgent):
model = self.model_name or "openai/gpt-4o-mini"
command = (
"log_file=$(mktemp /tmp/praisonai_code.XXXXXX); "
"chmod 600 \"$log_file\"; "
f"praisonai code -p --output json {shlex.quote(instruction)} "
f"praisonai code {shlex.quote(instruction)} "
f"--dangerously-skip-approval "
f"--model {shlex.quote(model)} "
"> \"$log_file\" 2>&1; "
"> /tmp/praisonai_code.log 2>&1; "
# Capture the real exit status so install/auth/startup failures still
# surface instead of being silently masked (Harbor otherwise records a
# completed attempt for a crashed agent).
"status=$?; "
# Echo the envelope so Harbor captures it for post-run accounting.
"cat \"$log_file\"; "
"rm -f \"$log_file\"; "
# Tee the log into a stable path so populate_context_post_run can read it.
"cp /tmp/praisonai_code.log /tmp/praisonai_code_run.log 2>/dev/null || true; "
# `praisonai code` normally exits 0 (Harbor grades by task
# verification), so a genuine benchmark miss won't fail here — but a
# nonzero status means the assistant itself failed to run.
@@ -103,35 +100,23 @@ class PraisonAICodeAgent(BaseInstalledAgent):
# `--ae` / job YAML env vars arrive via BaseAgent.extra_env and are wired
# into the container exec context by Harbor Trial, so no per-exec `env=`
# is needed here.
result = await self.exec_as_agent(
await self.exec_as_agent(
environment,
command=command,
)
self._last_stdout = getattr(result, "stdout", "") or ""
def populate_context_post_run(self, context: AgentContext) -> None:
"""Parse the headless JSON envelope into Harbor's accounting fields."""
envelope = None
for line in reversed(getattr(self, "_last_stdout", "").splitlines()):
try:
candidate = json.loads(line)
except (TypeError, ValueError, json.JSONDecodeError):
continue
if isinstance(candidate, dict) and "status" in candidate:
envelope = candidate
break
"""`praisonai code` exposes no machine-readable metrics headlessly.
usage = envelope.get("usage", {}) if envelope else {}
context.n_input_tokens = usage.get("in")
context.n_output_tokens = usage.get("out")
context.cost_usd = usage.get("cost")
Record identifying metadata; token/cost accounting is not available from
the CLI's mixed stdout, so we leave those fields unset rather than guess.
"""
context.metadata = {
"framework": "praisonai",
"agent_type": "code-cli",
"agent_name": self.name(),
"model": self.model_name,
"session_id": envelope.get("session_id") if envelope else None,
"status": envelope.get("status") if envelope else "unknown",
"log_path": "/tmp/praisonai_code.log",
}
@@ -34,7 +34,6 @@ except ImportError as e:
try:
from praisonaiagents import Agent
from praisonaiagents.approval import get_approval_registry, AutoApproveBackend
from praisonaiagents.config.feature_configs import ExecutionConfig
except ImportError as e:
raise ImportError(
f"PraisonAI not installed: {e}\n"
@@ -42,13 +41,6 @@ except ImportError as e:
) from e
TB_EXECUTION = ExecutionConfig(
max_tool_calls_per_turn=80,
max_iter=40,
max_steps=80,
)
class PraisonAIExternalAgent(BaseAgent):
"""External PraisonAI agent that drives a Harbor container environment."""
@@ -150,14 +142,26 @@ class PraisonAIExternalAgent(BaseAgent):
),
tools=[bash_tool],
llm=self.model_name or "openai/gpt-4o-mini",
execution=TB_EXECUTION,
)
# Execute one deliberately long coding turn. Harbor's hidden verifier
# is the only completion authority; model or pytest text is not.
# Execute the agent with outer loop to handle premature stopping
print(f"🚀 PraisonAI Agent starting task: {instruction[:100]}...")
result = await agent.achat(instruction)
print("✅ PraisonAI Agent completed task")
for _iter in range(19):
result_str = str(result)
# Stop if test passed
if any(sig in result_str.lower() for sig in [
" passed", "passed ", "test passed", "all tests pass", "1 passed"
]):
break
result = await agent.achat(
"The task is NOT complete yet — keep working. Run bash_tool commands now. "
"If you haven't already: (1) read all files in /app/, "
"(2) run the test to see the exact failure, "
"(3) implement a fix, (4) run the test again. "
"Repeat until the test passes. What is your next bash_tool command?"
)
print(f"✅ PraisonAI Agent completed task")
# Populate Harbor context with metadata
self._populate_context(agent, context, result)
@@ -199,10 +203,6 @@ class PraisonAIExternalAgent(BaseAgent):
"tools_used": ["bash_tool"],
"framework": "praisonai",
"version": self.version(),
"stop_reason": getattr(agent, "last_stop_reason", None),
"max_tool_calls_per_turn": TB_EXECUTION.max_tool_calls_per_turn,
"max_iter": TB_EXECUTION.max_iter,
"max_steps": TB_EXECUTION.max_steps,
}
except Exception as e:
@@ -218,4 +218,4 @@ if __name__ == "__main__":
print(" --model openai/gpt-4o-mini")
print()
print("Dependencies:")
print(" pip install harbor praisonaiagents")
print(" pip install harbor praisonaiagents")
@@ -1,39 +0,0 @@
"""Static regression checks for the in-tree Harbor adapter configuration."""
from pathlib import Path
import yaml
EXAMPLES = Path(__file__).parent
def test_external_adapter_sets_coding_execution_budget():
source = (EXAMPLES / "praisonai_external_agent.py").read_text(encoding="utf-8")
assert "ExecutionConfig" in source
assert "max_tool_calls_per_turn=80" in source
assert "max_iter=40" in source
assert "max_steps=80" in source
def test_external_adapter_does_not_guess_completion_from_pytest_text():
source = (EXAMPLES / "praisonai_external_agent.py").read_text(encoding="utf-8")
assert '"1 passed"' not in source
assert '"test passed"' not in source
def test_smoke_yaml_uses_terminal_bench_21_registry_ids():
job = yaml.safe_load(
(EXAMPLES / "job_code_smoke.yaml").read_text(encoding="utf-8")
)
names = job["datasets"][0]["task_names"]
assert names
assert all(name.startswith("terminal-bench/") for name in names)
assert names == [
"terminal-bench/build-pmars",
"terminal-bench/bn-fit-modify",
"terminal-bench/break-filter-js-from-html",
]
+18 -18
View File
@@ -14,18 +14,18 @@ def test_imports():
"""Test that all required modules can be imported."""
try:
from praisonaiagents import Agent
print("[OK] Agent imported successfully")
print("✅ Agent imported successfully")
from praisonaiagents.tools import execute_command
print("[OK] execute_command tool imported successfully")
print("✅ execute_command tool imported successfully")
from praisonaiagents.approval import get_approval_registry, AutoApproveBackend
print("[OK] Approval system imported successfully")
print("✅ Approval system imported successfully")
return True
except ImportError as e:
print(f"[FAIL] Import failed: {ascii(e)}")
print(f"❌ Import failed: {e}")
return False
def test_agent_creation():
@@ -40,11 +40,11 @@ def test_agent_creation():
)
assert agent.name == 'test-agent'
print("[OK] Agent creation successful")
print("✅ Agent creation successful")
return True
except Exception as e:
print(f"[FAIL] Agent creation failed: {ascii(e)}")
print(f"❌ Agent creation failed: {e}")
return False
def test_approval_system():
@@ -55,11 +55,11 @@ def test_approval_system():
registry = get_approval_registry()
registry.set_backend(AutoApproveBackend())
print("[OK] Approval system configuration successful")
print("✅ Approval system configuration successful")
return True
except Exception as e:
print(f"[FAIL] Approval system test failed: {ascii(e)}")
print(f"❌ Approval system test failed: {e}")
return False
def test_external_agent_import():
@@ -80,11 +80,11 @@ def test_external_agent_import():
# Now try to import our agent
import praisonai_external_agent
print("[OK] External agent import successful")
print("✅ External agent import successful")
return True
except Exception as e:
print(f"[FAIL] External agent import failed: {ascii(e)}")
print(f"❌ External agent import failed: {e}")
return False
def test_multi_agent_import():
@@ -104,11 +104,11 @@ def test_multi_agent_import():
sys.modules['harbor.models.agent.context'] = MagicMock()
import multi_agent_example
print("[OK] Multi-agent example import successful")
print("✅ Multi-agent example import successful")
return True
except Exception as e:
print(f"[FAIL] Multi-agent example import failed: {ascii(e)}")
print(f"❌ Multi-agent example import failed: {e}")
return False
def test_wrapper_agent_import():
@@ -128,11 +128,11 @@ def test_wrapper_agent_import():
sys.modules['harbor.models.agent.context'] = MagicMock()
import praisonai_wrapper_agent
print("[OK] Wrapper agent import successful (CLI-based approach)")
print("✅ Wrapper agent import successful (CLI-based approach)")
return True
except Exception as e:
print(f"[FAIL] Wrapper agent import failed: {ascii(e)}")
print(f"❌ Wrapper agent import failed: {e}")
return False
if __name__ == "__main__":
@@ -152,19 +152,19 @@ if __name__ == "__main__":
total = len(tests)
for test_name, test_func in tests:
print(f"\n[TEST] {test_name}...")
print(f"\n🧪 Testing {test_name}...")
try:
if test_func():
passed += 1
except Exception as e:
print(f"[FAIL] Test {test_name} crashed: {ascii(e)}")
print(f"❌ Test {test_name} crashed: {e}")
print("\n" + "=" * 55)
print(f"Results: {passed}/{total} tests passed")
if passed == total:
print("[OK] ALL BASIC TESTS PASSED!")
print("🎉 ALL BASIC TESTS PASSED!")
print("The Terminal-Bench integration components are properly structured.")
else:
print("[FAIL] Some tests failed - check output above")
print("❌ Some tests failed - check output above")
sys.exit(1)
+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)
@@ -1,64 +0,0 @@
# Simple Sequential Team (YAML)
A minimal 2-agent sequential team: a **researcher** gathers facts, then a
**writer** summarizes them. This is the copy-paste starting point for the most
common multi-agent pattern (2–5 agents, run in order).
```
research_task -> summary_task
(researcher) (writer)
```
## Files
| File | Purpose |
|------|---------|
| `agents.yaml` | Roles (who) + their tasks (what); tasks run in declaration order |
> **Which loader applies?** This example uses the canonical single-file format
> consumed by `AgentsGenerator.generate_crew_and_kickoff()`
> (`src/praisonai/praisonai/agents_generator.py`). Agents live under `roles:`,
> each with nested `tasks:`. **Tasks run in the order they are declared** — the
> researcher's task first, then the writer's. (An optional top-level
> `dependencies:` block is included to document intent and mirror the canonical
> fixture, but the roles-file loader sequences by declaration order, so keep
> tasks in the order you want them to run.) No new loader module is required —
> this is the existing YAML path.
## Run it
```bash
export OPENAI_API_KEY=sk-...
praisonai examples/yaml/teams/research-writer/agents.yaml
```
This positional-file form is the canonical roles-file entry point. From Python
the equivalent is `praisonai.run("agents.yaml")` (see
`src/praisonai/praisonai/_entrypoint.py`), which dispatches to the same
`AgentsGenerator`.
Change the subject by editing the `topic:` line in `agents.yaml` (interpolated
into every `{topic}` placeholder).
## When to use this vs a workflow YAML
| You need… | Use | Example |
|-----------|-----|---------|
| 2–5 agents, sequential/hierarchical | **This** (`roles:` + `tasks:`) | `agents.yaml` here |
| Routing by classifier output | workflow YAML | `../../workflows/routing_workflow.yaml` |
| Parallel branches | workflow YAML | `../../workflows/parallel_workflow.yaml` |
| Loops / planning / memory | workflow YAML | `../../workflows/complete_workflow.yaml` |
## Python equivalent
```python
from praisonaiagents import Agent, Task, PraisonAIAgents
researcher = Agent(role="Senior Researcher", goal="Find accurate information")
writer = Agent(role="Report Writer", goal="Turn research into summaries")
t1 = Task(description="Research renewable energy and list 5 key facts", agent=researcher)
t2 = Task(description="Write a 3-sentence summary from the research", agent=writer, context=[t1])
PraisonAIAgents(agents=[researcher, writer], tasks=[t1, t2]).start()
```
@@ -1,34 +0,0 @@
# yaml-language-server: $schema=https://docs.praison.ai/schemas/agents.schema.json
# Minimal sequential team: researcher -> writer
# Run: praisonai examples/yaml/teams/research-writer/agents.yaml
framework: "praisonai"
topic: "renewable energy"
roles:
researcher:
role: "Senior Researcher"
goal: "Find accurate information about {topic}"
backstory: "Expert at concise, factual research."
tasks:
research_task:
description: "Research {topic} and list 5 key facts."
expected_output: "A bullet list of 5 facts."
writer:
role: "Report Writer"
goal: "Turn research into readable summaries about {topic}"
backstory: "Clear technical writer."
tasks:
summary_task:
description: "Write a 3-sentence executive summary from the research."
expected_output: "3 sentences, plain text."
# Ordering is by task declaration order above (researcher's task runs first,
# then the writer's), which is how the roles-file loader sequences tasks.
# The optional `dependencies:` block below mirrors the canonical fixture
# (src/praisonai/tests/agents.yaml) and documents intent; the roles-file
# loader does not consume it, so keep tasks in the order you want them run.
dependencies:
- task: summary_task
depends_on: research_task
@@ -1,45 +0,0 @@
# Run a whole workflow's shell/file tools inside ONE shared remote sandbox.
#
# praisonai examples/yaml/workflows/remote_sandbox_workflow.yaml
#
# `tools_run_on:` is the only line that differs from a normal local workflow.
# Every step shares the same sandbox and working directory, so the file the
# writer creates is there for the reader. Thinking and orchestration still run
# on your machine, and the sandbox is torn down when the run finishes.
#
# Places: docker | e2b | modal | daytona | flyio | tenki | local
# subprocess | sandlock | ssh | novita
# - docker needs a local Docker daemon and nothing else
# - e2b / modal / daytona / flyio need that provider's API key
# - sandlock is a kernel-enforced local boundary (Linux 6.12+)
# - subprocess is process separation only, NOT a security boundary
#
# `run_on:` is still accepted here as the old spelling for this key.
#
# See what is still running: praisonai managed ps
# Reclaim strays: praisonai managed stop --all
name: remote-sandbox-demo
tools_run_on: docker
agents:
writer:
role: File Writer
goal: Write files into the shared workspace
instructions: >
You have write_file and execute_command running on a remote Linux
sandbox. Use them; never say you cannot run commands.
reader:
role: File Reader
goal: Read files back out of the shared workspace
instructions: >
You have read_file and execute_command running on the same remote
sandbox the writer used. Use them.
steps:
- agent: writer
action: "Use write_file to put exactly 'hello from step 1' in /workspace/note.txt"
- agent: reader
action: "Use read_file on /workspace/note.txt and report its exact contents"
-55
View File
@@ -1,55 +0,0 @@
#!/usr/bin/env bash
# C14 import-direction gate for praisonai-deploy.
set -euo pipefail
cd "$(cd "$(dirname "${BASH_SOURCE[0]}")/.." && pwd)"
CODE_ROOT="${C14_CODE_ROOT:-src/praisonai-code/praisonai_code}"
DEPLOY_ROOT="${C14_DEPLOY_ROOT:-src/praisonai-deploy/praisonai_deploy}"
ANY_WRAPPER_RE='(^[[:space:]]*from praisonai([[:space:]]|\.)|^[[:space:]]*import praisonai($|\.))'
ANY_CODE_RE='(^from praisonai_code([[:space:]]|\.)|^import praisonai_code($|\.))'
ANY_DEPLOY_RE='(^[[:space:]]*from praisonai_deploy([[:space:]]|\.)|^[[:space:]]*import praisonai_deploy($|\.))'
echo "== C14 praisonai_deploy wrapper import gate (must be zero outside bridges) =="
if command -v rg >/dev/null 2>&1; then
MATCHES="$(rg -n "$ANY_WRAPPER_RE" "$DEPLOY_ROOT" --glob '*.py' 2>/dev/null | grep -v '_wrapper_bridge.py' | grep -v '_bootstrap.py' | grep -v '_code_bridge.py' || true)"
else
MATCHES="$(grep -rEn --include='*.py' "$ANY_WRAPPER_RE" "$DEPLOY_ROOT" 2>/dev/null | grep -v '_wrapper_bridge.py' | grep -v '_bootstrap.py' | grep -v '_code_bridge.py' || true)"
fi
if [ -n "$MATCHES" ]; then
echo "$MATCHES"
echo "FAIL: praisonai_deploy imports the praisonai wrapper"
exit 1
fi
echo "deploy wrapper import gate ok"
echo "== C14 praisonai_deploy module-level praisonai_code import gate =="
if command -v rg >/dev/null 2>&1; then
MATCHES="$(rg -n "$ANY_CODE_RE" "$DEPLOY_ROOT" --glob '*.py' 2>/dev/null | grep -v '_code_bridge.py' | grep -v '_plugin_registry.py' || true)"
else
MATCHES="$(grep -rEn --include='*.py' "$ANY_CODE_RE" "$DEPLOY_ROOT" 2>/dev/null | grep -v '_code_bridge.py' | grep -v '_plugin_registry.py' || true)"
fi
if [ -n "$MATCHES" ]; then
echo "$MATCHES"
echo "FAIL: module-level praisonai_code import in praisonai_deploy"
exit 1
fi
echo "deploy code import gate ok"
echo "== C14 praisonai-code hot-path gate (no praisonai_deploy at module level) =="
for f in \
"$CODE_ROOT/cli/main.py" \
"$CODE_ROOT/cli/app.py" \
"$CODE_ROOT/cli/commands/run.py" \
"$CODE_ROOT/cli/commands/chat.py" \
"$CODE_ROOT/cli/commands/code.py"
do
if [ -f "$f" ] && head -n 80 "$f" | grep -E "$ANY_DEPLOY_RE" 2>/dev/null; then
echo "FAIL: module-level praisonai_deploy import in code hot path $f"
exit 1
fi
done
echo "code hot-path gate ok"
echo "C14 import gates passed"
+1 -3
View File
@@ -18,9 +18,7 @@ for f in \
"$ROOT/cli/app.py" \
"$ROOT/cli/commands/run.py" \
"$ROOT/cli/commands/chat.py" \
"$ROOT/cli/commands/code.py" \
"$ROOT/cli/interactive/async_tui.py" \
"$ROOT/cli/interactive/core.py"
"$ROOT/cli/commands/code.py"
do
if grep -E "$HOT_PATH_RE" "$f" 2>/dev/null; then
echo "FAIL: module-level wrapper import in $f"
-60
View File
@@ -1,60 +0,0 @@
#!/usr/bin/env bash
# Lint and template-render all Helm charts under package infra/ trees.
set -euo pipefail
ROOT="$(cd "$(dirname "${BASH_SOURCE[0]}")/.." && pwd)"
if ! command -v helm >/dev/null 2>&1; then
echo "FAIL: helm CLI not found (install via https://helm.sh/docs/intro/install/)"
exit 1
fi
HELM_ROOTS=(
"$ROOT/src/praisonai-bot/infra/helm"
"$ROOT/src/praisonai-deploy/infra/helm"
)
charts=()
for helm_root in "${HELM_ROOTS[@]}"; do
if [ ! -d "$helm_root" ]; then
continue
fi
shopt -s nullglob
for chart in "$helm_root"/*/; do
if [ -f "${chart}Chart.yaml" ]; then
charts+=("$chart")
fi
done
shopt -u nullglob
done
if [ ${#charts[@]} -eq 0 ]; then
echo "No charts found under package infra/helm trees"
exit 1
fi
for chart in "${charts[@]}"; do
name="$(basename "$chart")"
echo "== helm lint: $name =="
helm lint "$chart"
echo "== helm template: $name =="
case "$name" in
praisonai-gateway)
helm template "ci-smoke-$name" "$chart" \
--set auth.existingSecret=ci-smoke-auth \
>/dev/null
;;
praisonai-agents-api)
helm template "ci-smoke-$name" "$chart" \
--set auth.existingSecret=ci-smoke-auth \
--set postgres.auth.existingSecret=ci-smoke-postgres \
>/dev/null
;;
*)
helm template "ci-smoke-$name" "$chart" >/dev/null
;;
esac
done
echo "Helm chart gates passed (${#charts[@]} chart(s))"
@@ -99,12 +99,13 @@ pip index versions praisonaiagents | head -1
pip index versions praisonai | head -1
```
13. **praisonai-platform** advisories are handled in a different repository:
[MervinPraison/PraisonAI-Platform](https://github.com/MervinPraison/PraisonAI-Platform).
It is not part of this monorepo and is not published from here. Triage, patch,
release and advisory publication all happen in that repo, on its own semver line.
Nothing in this repository imports it, so a platform advisory never requires an
SDK release.
13. Publish **praisonai-platform** (only when the advisory targets platform code):
```bash
cd /Users/praison/praisonai-package/src/praisonai-platform
praisonai publish pypi
# or: uv lock && uv build && uv publish --token $PYPI_TOKEN
```
Platform releases are **independent** of `praisonai` / `praisonaiagents` version numbers. A platform-only fix (e.g. `0.1.8`) does **not** require bumping the main SDK.
14. Publish **praisonai (npm / TypeScript)** (only when the advisory targets `src/praisonai-ts`):
```bash
@@ -112,8 +113,9 @@ cd /Users/praison/praisonai-package/src/praisonai-ts
npm version patch && npm publish
```
15. Verify npm when applicable:
15. Verify platform / npm when applicable:
```bash
pip index versions praisonai-platform | head -1
npm view praisonai version
```
@@ -137,7 +139,7 @@ gh api repos/MervinPraison/PraisonAI/security-advisories/<GHSA_ID> \
}
EOF
```
- `<PACKAGE_NAME>`: `praisonaiagents` (core SDK), `praisonai` (Python wrapper), or `praisonai` (npm ecosystem for TypeScript)
- `<PACKAGE_NAME>`: `praisonaiagents` (core SDK), `praisonai` (Python wrapper), `praisonai-platform` (platform layer), or `praisonai` (npm ecosystem for TypeScript)
- `<LAST_VULNERABLE_VERSION>`: version before the fix
- `<FIRST_PATCHED_VERSION>`: the version just published with the fix
- Always include credits for the reporter
@@ -188,8 +190,8 @@ After validating each advisory in source code, assign **one** label:
| Package | Version line | Notes |
|---|---|---|
| `praisonaiagents` + `praisonai` | Aligned patch (e.g. `1.6.62` / `4.6.62`) | Main SDK + wrapper; bump together via `bump_and_release.py` |
| `praisonai-platform` | Independent semver (e.g. `0.1.8`) | Platform-only fixes; users need **not** upgrade the main SDK |
| `praisonai` (npm) | Independent semver (e.g. `1.7.2`) | TypeScript SDK; publish from `src/praisonai-ts` |
| `praisonai-platform` | Independent semver, **separate repository** | Not released from this repo — see [PraisonAI-Platform](https://github.com/MervinPraison/PraisonAI-Platform) |
Always set the advisory `patched_versions` to the **package that actually contains the fix**. Do not imply users must upgrade all packages when only one changed.
@@ -215,11 +217,9 @@ Close (or publish advisory with no code change only if already mitigated) when:
|---|---|---|---|
| praisonaiagents | pip | src/praisonai-agents/praisonaiagents/ | tools/, mcp/, memory/, agent/, sandbox/ |
| praisonai | pip | src/praisonai/praisonai/ | cli/, capabilities/, mcp_server/, sandbox/, recipe/ |
| praisonai-platform | pip | src/praisonai-platform/praisonai_platform/ | api/routes/, services/, auth |
| praisonai | npm | src/praisonai-ts/src/ | agent/, mcp/, tools/, code-mode/ |
`praisonai-platform` is **not audited from this repository** — it lives in
[MervinPraison/PraisonAI-Platform](https://github.com/MervinPraison/PraisonAI-Platform).
## RESOURCES & DOCUMENTATION
- **Official Repository**: https://github.com/MervinPraison/PraisonAI — Source code, issue tracking, and contribution guidelines
@@ -234,7 +234,7 @@ Close (or publish advisory with no code change only if already mitigated) when:
- ALWAYS set patched_versions before publishing advisory
- ALWAYS publish to PyPI/npm BEFORE publishing advisories (so Dependabot can point users to a fix)
- Python SDK: `praisonai publish pypi` from `src/praisonai-agents`, then `bump_and_release.py` for the wrapper
- Platform-only: released from the separate [PraisonAI-Platform](https://github.com/MervinPraison/PraisonAI-Platform) repo, never from here
- Platform-only: `praisonai publish pypi` from `src/praisonai-platform` — no SDK bump required
- npm: `npm publish` from `src/praisonai-ts` when the TypeScript SDK is affected
- ALWAYS request CVE AFTER publishing advisory
- Use generic commit messages: "refactor: harden X" not "fix: SQL injection in Y"
+2 -16
View File
@@ -140,7 +140,7 @@ The **agentic terminal CLI** (`run`, `chat`, `code`, warm runtime, CLI backends,
**Monorepo bootstrap:** `praisonai._bootstrap.ensure_praisonai_code()` adds sibling `src/praisonai-code` to `sys.path` so `PYTHONPATH=src/praisonai-agents:src/praisonai` works without an explicit code entry.
**Install order (CI and local dev):** `praisonai-agents` → `praisonai-code` → `praisonai-bot` → `praisonai-train` → `praisonai-browser` → `praisonai-mcp` → `praisonai-sandbox` → `praisonai-deploy` → `praisonai` (see `.github/actions/install-monorepo-packages`).
**Install order (CI and local dev):** `praisonai-agents` → `praisonai-code` → `praisonai` (see `.github/actions/install-monorepo-packages`).
**Invocation paths that must remain valid:**
@@ -207,7 +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.
@@ -223,17 +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)
@@ -888,8 +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) |
---
@@ -1088,7 +1074,7 @@ PraisonAI's reliability engineering rests on three pillars — **C**ontext, **H*
> **Evaluator status.** The `ContextEvaluator` / `HarnessEvaluator` / `LoopEvaluator` classes named in the rubric are **planned follow-ups** (PA-CHL-001–004), not yet in the repo. Until they land, the equivalent checks are covered by existing modules:
>
> - **Context** — `context/tokens.py` and `eval/tokens.py` (`estimate_tokens` / `count_tokens`) for budget; `compaction/compactor.py` (`ContextCompactor`) for compaction/retention.
> - **Harness** — `runtime/turn_context.py` for turn-context parity; `examples/runtime/example_harness.py` and `tests/` for harness/artifact checks.
> - **Harness** — `runtime/turn_context.py` for turn-context parity; `runtime/example_harness.py` and `tests/` for harness/artifact checks.
> - **Loop** — `eval/loop.py` (`EvaluationLoop`) and `agent/autonomy.py` for convergence and doom-loop guards.
>
> Keep terminology consistent with the `agent/context_agent.py` (`ContextAgent`) PRP methodology.
+52 -52
View File
@@ -17,78 +17,78 @@ This report compares **Python SDK feature categories** against **Python document
| Category | Features | Docs | Lines |
|----------|----------|------|-------|
| ✅ AGUI | 1 | 2 | 511 |
| ✅ Agent | 22 | 56 | 17728 |
| ✅ Agent-to-Agent (A2A) | 1 | 7 | 2996 |
| ✅ Agent-to-User (A2U) | 1 | 3 | 689 |
| ✅ Approval | 1 | 7 | 3503 |
| ✅ AGUI | 1 | 2 | 420 |
| ✅ Agent | 21 | 45 | 14186 |
| ✅ Agent-to-Agent (A2A) | 1 | 7 | 2965 |
| ✅ Agent-to-User (A2U) | 1 | 3 | 585 |
| ✅ Approval | 1 | 5 | 2286 |
| ✅ Audio | 2 | 12 | 1000 |
| ✅ Auto Generation | 5 | 12 | 3747 |
| ✅ Autonomy | 3 | 7 | 2790 |
| ✅ Bots | 7 | 33 | 13860 |
| ✅ Auto Generation | 5 | 10 | 2868 |
| ✅ Autonomy | 3 | 7 | 2707 |
| ✅ Bots | 7 | 28 | 11301 |
| ✅ Budget | 1 | 1 | 287 |
| ✅ CLI | 5 | 123 | 37946 |
| ✅ Chunking | 2 | 2 | 420 |
| ✅ CLI | 5 | 119 | 33852 |
| ✅ Chunking | 2 | 2 | 385 |
| ✅ Citations | 2 | 1 | 202 |
| ✅ Code Execution | 2 | 14 | 4855 |
| ✅ Conditions | 1 | 3 | 1347 |
| ✅ Configuration | 3 | 8 | 3292 |
| ✅ Context Management | 16 | 36 | 14090 |
| ✅ Code Execution | 2 | 13 | 3970 |
| ✅ Conditions | 1 | 3 | 1179 |
| ✅ Configuration | 3 | 7 | 2772 |
| ✅ Context Management | 16 | 34 | 13204 |
| ✅ Deep Research | 8 | 2 | 587 |
| ✅ Display | 6 | 3 | 741 |
| ✅ Embeddings | 6 | 23 | 2049 |
| ✅ Evaluation | 1 | 8 | 3220 |
| ✅ Events | 1 | 2 | 767 |
| ✅ Execution | 3 | 4 | 1631 |
| ✅ Failover | 2 | 1 | 452 |
| ✅ Files | 2 | 7 | 2376 |
| ✅ Flow | 1 | 3 | 788 |
| ✅ Gateway | 7 | 85 | 31517 |
| ✅ Guardrails | 4 | 4 | 2288 |
| ✅ Handoffs | 11 | 6 | 2626 |
| ✅ Hooks | 2 | 9 | 4690 |
| ✅ Evaluation | 1 | 7 | 2902 |
| ✅ Events | 1 | 2 | 749 |
| ✅ Execution | 3 | 4 | 1528 |
| ✅ Failover | 2 | 1 | 400 |
| ✅ Files | 2 | 6 | 1964 |
| ✅ Flow | 1 | 3 | 777 |
| ✅ Gateway | 7 | 54 | 19347 |
| ✅ Guardrails | 4 | 4 | 1673 |
| ✅ Handoffs | 11 | 6 | 2454 |
| ✅ Hooks | 2 | 9 | 4124 |
| ✅ Image | 1 | 11 | 1255 |
| ✅ Knowledge | 4 | 17 | 5226 |
| ✅ LLM | 3 | 15 | 5395 |
| ✅ Loops | 4 | 5 | 1475 |
| ✅ MCP | 1 | 62 | 14436 |
| ✅ Memory | 6 | 19 | 7512 |
| ✅ Knowledge | 4 | 13 | 4160 |
| ✅ LLM | 3 | 14 | 4830 |
| ✅ Loops | 4 | 4 | 1202 |
| ✅ MCP | 1 | 58 | 13322 |
| ✅ Memory | 6 | 17 | 6635 |
| ✅ OCR | 2 | 1 | 237 |
| ✅ Observability | 2 | 23 | 2811 |
| ✅ Observability | 2 | 23 | 2779 |
| ✅ Optimizer | 1 | 2 | 792 |
| ✅ Output | 3 | 5 | 1273 |
| ✅ Output | 3 | 5 | 1158 |
| ✅ Parallel Execution | 3 | 2 | 497 |
| ✅ Planning | 6 | 7 | 1825 |
| ✅ Plugins | 8 | 5 | 3120 |
| ✅ Prompts | 2 | 9 | 2011 |
| ✅ Providers | 1 | 57 | 8197 |
| ✅ Planning | 6 | 6 | 1545 |
| ✅ Plugins | 8 | 3 | 1900 |
| ✅ Prompts | 2 | 9 | 1910 |
| ✅ Providers | 1 | 55 | 7502 |
| ✅ Query | 1 | 2 | 736 |
| ✅ RAG | 5 | 15 | 3118 |
| ✅ RAG | 5 | 15 | 2936 |
| ✅ Realtime | 2 | 5 | 668 |
| ✅ Reflection | 3 | 3 | 732 |
| ✅ Retrieval | 2 | 5 | 1042 |
| ✅ Reflection | 3 | 3 | 680 |
| ✅ Retrieval | 2 | 5 | 1044 |
| ✅ Routing | 1 | 2 | 430 |
| ✅ Sandbox | 5 | 7 | 3556 |
| ✅ Security | 1 | 3 | 3529 |
| ✅ Sessions | 4 | 19 | 7648 |
| ✅ Skills | 6 | 16 | 5911 |
| ✅ Tasks | 2 | 6 | 2897 |
| ✅ Telemetry | 1 | 2 | 648 |
| ✅ Templates | 1 | 8 | 1667 |
| ✅ Tools | 12 | 145 | 44115 |
| ✅ Sandbox | 5 | 6 | 2700 |
| ✅ Security | 1 | 3 | 2966 |
| ✅ Sessions | 4 | 13 | 5286 |
| ✅ Skills | 6 | 13 | 4946 |
| ✅ Tasks | 2 | 6 | 2743 |
| ✅ Telemetry | 1 | 2 | 604 |
| ✅ Templates | 1 | 8 | 1657 |
| ✅ Tools | 12 | 133 | 37869 |
| ✅ Tracing | 3 | 2 | 139 |
| ✅ Vector Store | 1 | 12 | 1219 |
| ✅ Video | 2 | 6 | 728 |
| ✅ Vector Store | 1 | 12 | 1193 |
| ✅ Video | 2 | 6 | 649 |
| ✅ Vision | 2 | 1 | 329 |
| ✅ Web | 3 | 9 | 2487 |
| ✅ Workflows | 5 | 18 | 7410 |
| ✅ Web | 3 | 8 | 2055 |
| ✅ Workflows | 5 | 16 | 6546 |
## Documentation Without Features
These docs exist but don't match any implemented feature category:
- ℹ️ Database (43 docs, 7293 lines)
- ℹ️ Documents (1 docs, 798 lines)
- ℹ️ Database (40 docs, 6184 lines)
- ℹ️ Documents (1 docs, 787 lines)
---
@@ -92,6 +92,20 @@ from ._lazy import lazy_import, create_lazy_getattr_with_fallback
# Thread-safe cache for lazy-loaded values
_lazy_cache = {}
# Backward compatibility: _get_lazy_cache function for tests
import threading
_lazy_cache_local = threading.local()
def _get_lazy_cache():
"""Get thread-local lazy cache dict. Thread-safe for concurrent access.
Note: This is kept for backward compatibility with tests.
The main lazy loading now uses the centralized _lazy.py utility.
"""
if not hasattr(_lazy_cache_local, 'cache'):
_lazy_cache_local.cache = {}
return _lazy_cache_local.cache
# ============================================================================
# LAZY IMPORT MAPPING
# ============================================================================
@@ -129,9 +143,9 @@ _LAZY_IMPORTS = {
'has_toolset': ('praisonaiagents.toolsets', 'has_toolset'),
# Model-family-aware harness (base prompt + edit-format selection)
'HarnessProfile': ('praisonaiagents.model_harness.profiles', 'HarnessProfile'),
'resolve_harness': ('praisonaiagents.model_harness.profiles', 'resolve_harness'),
'register_profile': ('praisonaiagents.model_harness.profiles', 'register_profile'),
'HarnessProfile': ('praisonaiagents.model_harness', 'HarnessProfile'),
'resolve_harness': ('praisonaiagents.model_harness', 'resolve_harness'),
'register_profile': ('praisonaiagents.model_harness', 'register_profile'),
# Run outcomes - typed validation and agent execution results
'AgentRunOutcome': ('praisonaiagents.run_outcome', 'AgentRunOutcome'),
@@ -244,7 +258,6 @@ _LAZY_IMPORTS = {
# Agent classes
'Agent': ('praisonaiagents.agent.agent', 'Agent'),
'RunOutcome': ('praisonaiagents.agent.run_outcome', 'RunOutcome'),
'RetryBackoffConfig': ('praisonaiagents.agent.retry_utils', 'RetryBackoffConfig'),
'BudgetExceededError': ('praisonaiagents.errors', 'BudgetExceededError'),
@@ -290,10 +303,9 @@ _LAZY_IMPORTS = {
'CodeAgent': ('praisonaiagents.agent.code_agent', 'CodeAgent'),
'CodeConfig': ('praisonaiagents.agent.code_agent', 'CodeConfig'),
# AgentTeam (primary) / AgentManager, PraisonAIAgents (aliases)
# AgentTeam (primary) / AgentManager (alias)
'AgentTeam': ('praisonaiagents.agents.agents', 'AgentTeam'),
'AgentManager': ('praisonaiagents.agents.agents', 'AgentManager'), # Silent alias
'PraisonAIAgents': ('praisonaiagents.agents.agents', 'PraisonAIAgents'), # Silent alias (pre-1.0 name)
# Note: 'Agents' is handled by _custom_handler for deprecation warning
'Task': ('praisonaiagents.task.task', 'Task'),
'AutoAgents': ('praisonaiagents.agents.autoagents', 'AutoAgents'),
@@ -412,7 +424,6 @@ _LAZY_IMPORTS = {
'WebConfig': ('praisonaiagents.config.feature_configs', 'WebConfig'),
'OutputConfig': ('praisonaiagents.config.feature_configs', 'OutputConfig'),
'ExecutionConfig': ('praisonaiagents.config.feature_configs', 'ExecutionConfig'),
'PreCompactionMemoryFlushConfig': ('praisonaiagents.config.feature_configs', 'PreCompactionMemoryFlushConfig'),
'TemplateConfig': ('praisonaiagents.config.feature_configs', 'TemplateConfig'),
'CachingConfig': ('praisonaiagents.config.feature_configs', 'CachingConfig'),
'HooksConfig': ('praisonaiagents.config.feature_configs', 'HooksConfig'),
@@ -827,11 +838,9 @@ __all__ = [
# Core classes - the essentials
'Agent',
'RunOutcome',
'RetryBackoffConfig',
'AgentTeam', # Primary class for multi-agent coordination (v1.0+)
'AgentManager', # Silent alias for AgentTeam
'PraisonAIAgents', # Silent alias for AgentTeam (pre-1.0 name)
'Agents', # Deprecated alias for AgentTeam (emits warning)
'Task',
@@ -28,11 +28,8 @@ from typing import Any, Callable, Dict, Optional, Tuple
_logger = logging.getLogger(__name__)
# Global cache lock for thread-safe access.
# Reentrant so that a lazy import which triggers another lazy import on the
# same thread (e.g. a package attribute that re-exports from a submodule via
# its own __getattr__) degrades to redundant work instead of self-deadlocking.
_cache_lock = threading.RLock()
# Global cache lock for thread-safe access
_cache_lock = threading.Lock()
# Global module cache
_module_cache: Dict[str, Any] = {}
@@ -4,6 +4,7 @@ This module consolidates all logging configuration in one place to avoid duplica
"""
import os
import json
import logging
from typing import Any, Dict, List, Optional, Union
@@ -195,9 +196,6 @@ class StructuredFormatter(logging.Formatter):
extra = {k: v for k, v in record.extra_data.items() if k not in self._STANDARD_FIELDS}
log_data.update(extra)
# Deferred: json is only needed for opt-in structured logging
import json
return json.dumps(log_data)
@@ -27,7 +27,7 @@ SUPPRESSED_PATTERNS = [
"The `dict` method is deprecated; use `model_dump` instead",
"Pydantic serializer warnings",
"PydanticSerializationUnexpectedValue",
"fields but got", # litellm/pydantic "Expected N fields but got M"
"Expected", # Catches all "Expected N fields but got M" patterns
"Expected `StreamingChoices` but got `Choices`",
"serialized value may not be as expected",
"Mixing V1 models and V2 models",
@@ -37,15 +37,6 @@ def __getattr__(name):
from .interrupt import InterruptController
_lazy_cache[name] = InterruptController
return InterruptController
if name in ('RunOutcome', 'TerminalReason'):
from . import run_outcome as _run_outcome_module
value = getattr(_run_outcome_module, name)
_lazy_cache[name] = value
return value
if name == 'prompt_prefix_signature':
from .prompt_cache import prompt_prefix_signature
_lazy_cache[name] = prompt_prefix_signature
return prompt_prefix_signature
# Specialized agents - lazy loaded (import rich)
if name == 'ImageAgent':
@@ -224,9 +215,6 @@ __all__ = [
'Heartbeat',
'HeartbeatConfig',
'InterruptController',
'RunOutcome',
'TerminalReason',
'prompt_prefix_signature',
'ImageAgent',
'VideoAgent',
'VideoConfig',
File diff suppressed because it is too large. Load diff
@@ -7,6 +7,7 @@ async capabilities following the AsyncMemoryProtocol.
"""
import asyncio
import logging
from typing import List, Dict, Any, Optional, Union
from praisonaiagents._logging import get_logger
from ..memory.protocols import AsyncMemoryProtocol
@@ -84,36 +85,21 @@ class AsyncMemoryMixin:
if not hasattr(self, '_memory_instance') or self._memory_instance is None:
logger.debug("No memory configured for async search")
return []
# Shared adapters must receive the configured identity explicitly.
# FileMemory is already bound to a user-specific path and accepts these
# as harmless protocol kwargs.
scoped_kwargs = dict(kwargs)
config = getattr(self, "_memory_config", None)
user_id = getattr(config, "user_id", None)
session_id = getattr(config, "session_id", None)
if user_id:
scoped_kwargs["user_id"] = user_id
if session_id:
scoped_kwargs["session_id"] = session_id
metadata_filter = dict(scoped_kwargs.get("metadata_filter") or {})
metadata_filter["session_id"] = session_id
scoped_kwargs["metadata_filter"] = metadata_filter
# Check if memory adapter supports async operations
if isinstance(self._memory_instance, AsyncMemoryProtocol):
try:
if memory_type == "long_term":
return await self._memory_instance.asearch_long_term(query, limit, **scoped_kwargs)
return await self._memory_instance.asearch_long_term(query, limit, **kwargs)
else:
return await self._memory_instance.asearch_short_term(query, limit, **scoped_kwargs)
return await self._memory_instance.asearch_short_term(query, limit, **kwargs)
except Exception as e:
logger.error(f"Error in async memory search: {e}")
return []
else:
# Fallback: run sync memory operations in thread pool
return await self._run_memory_in_thread(
"search", query, memory_type, limit=limit, **scoped_kwargs
"search", query, memory_type, limit=limit, **kwargs
)
async def _run_memory_in_thread(
@@ -230,4 +216,4 @@ class AsyncMemoryMixin:
)
return False
return True
return False
return False
@@ -5,9 +5,8 @@ This module provides dual-lock abstractions that automatically select
the appropriate lock type based on the execution context (sync vs async).
"""
import asyncio
import copy
import threading
from typing import Any
from typing import Any, Optional, Union
from contextlib import contextmanager, asynccontextmanager
from weakref import WeakKeyDictionary
@@ -40,12 +39,6 @@ class DualLock:
"""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."""
result = type(self)()
memo[id(self)] = result
return result
@contextmanager
def sync(self):
@@ -110,33 +103,6 @@ class AsyncSafeState:
def __init__(self, initial_value: Any = None):
self.value = initial_value
self._lock = DualLock()
self._activity_lock = threading.Lock()
self._async_holders = 0
self._copying = False
def __deepcopy__(self, memo):
"""Copy protected state, rejecting overlap with asynchronous access."""
result = type(self).__new__(type(self))
memo[id(self)] = result
with self._activity_lock:
if self._async_holders:
raise RuntimeError(
"Cannot deepcopy AsyncSafeState during asynchronous access"
)
if self._copying:
raise RuntimeError("AsyncSafeState deepcopy is already in progress")
self._copying = True
try:
with self.lock():
result.value = copy.deepcopy(self.value, memo)
finally:
with self._activity_lock:
self._copying = False
result._lock = DualLock()
result._activity_lock = threading.Lock()
result._async_holders = 0
result._copying = False
return result
@contextmanager
def lock(self):
@@ -148,25 +114,7 @@ class AsyncSafeState:
async def async_lock(self):
"""Acquire lock in async context."""
async with self._lock.async_lock():
self._begin_async_access()
try:
yield self.value
finally:
self._end_async_access()
def _begin_async_access(self) -> None:
"""Register async access unless a synchronous copy is in progress."""
with self._activity_lock:
if self._copying:
raise RuntimeError(
"Cannot access AsyncSafeState during synchronous deepcopy"
)
self._async_holders += 1
def _end_async_access(self) -> None:
"""Unregister one active asynchronous accessor."""
with self._activity_lock:
self._async_holders -= 1
yield self.value
def __enter__(self):
"""Support for synchronous context manager protocol (backward compatibility)."""
@@ -182,20 +130,12 @@ class AsyncSafeState:
"""Support for asynchronous context manager protocol."""
async_lock = self._lock._get_async_lock()
await async_lock.acquire()
try:
self._begin_async_access()
except Exception:
async_lock.release()
raise
return self.value
async def __aexit__(self, exc_type, exc_val, exc_tb):
"""Support for asynchronous context manager protocol."""
async_lock = self._lock._get_async_lock()
try:
self._end_async_access()
finally:
async_lock.release()
async_lock.release()
return None
def get(self) -> Any:
@@ -204,4 +144,4 @@ class AsyncSafeState:
def is_async_context(self) -> bool:
"""Check if we're in an async context."""
return self._lock.is_async_context()
return self._lock.is_async_context()
@@ -136,8 +136,9 @@ class AudioAgent:
- AudioConfig: Full configuration object
verbose: Verbosity level for output
"""
from ..utils.model_alias import resolve_model_name
llm = resolve_model_name(llm, model, "AudioAgent")
# Handle model= alias
if llm is None and model is not None:
llm = model
self.name = name or "AudioAgent"
self.instructions = instructions
@@ -34,6 +34,7 @@ Usage:
from dataclasses import dataclass, field
from typing import Optional, Dict, Any, List, Set
from enum import Enum
import logging
from praisonaiagents._logging import get_logger
logger = get_logger(__name__)
@@ -106,11 +107,8 @@ class AutonomyConfig:
track_changes: Whether to track filesystem changes via shadow git.
Defaults to True when level="full_auto", False otherwise.
When enabled, agent.undo()/redo()/diff() become available.
sandbox: Optional SandboxConfig, carried for forward compatibility.
NOT IMPLEMENTED: nothing currently reads this field, and no sandbox
is auto-enabled at any autonomy level. To isolate execution, set it
on the agent itself -- Agent(sandbox=...) -- or run the whole
workflow remotely with AgentFlow(run_on="docker").
sandbox: Optional SandboxConfig for execution isolation.
When level="full_auto" and sandbox is None, subprocess sandbox is auto-enabled.
snapshot_dir: Directory for snapshot storage. Defaults to ~/.praisonai/snapshots.
Usage::
@@ -217,13 +215,6 @@ class AutonomyConfig:
f"Invalid autonomy level: {level!r}. "
f"Must be one of {sorted(VALID_AUTONOMY_LEVELS)}"
)
verification_hooks = data.get("verification_hooks")
# Config parity: accept declarative `verification:` entries and map
# `command:`/`file:` shapes onto the two hook classes.
declarative = data.get("verification")
if declarative:
built = _build_verification_hooks(declarative)
verification_hooks = (verification_hooks or []) + built
return cls(
enabled=data.get("enabled", True),
level=level,
@@ -234,7 +225,7 @@ class AutonomyConfig:
observe=data.get("observe", False),
completion_promise=data.get("completion_promise"),
clear_context=data.get("clear_context", False),
verification_hooks=verification_hooks,
verification_hooks=data.get("verification_hooks"),
track_changes=data.get("track_changes"),
sandbox=data.get("sandbox"),
snapshot_dir=data.get("snapshot_dir"),
@@ -244,49 +235,6 @@ class AutonomyConfig:
budget_action=data.get("budget_action", "pause"),
)
def _build_verification_hooks(entries: List[Any]) -> List[Any]:
"""Map declarative ``verification:`` config entries onto hook instances.
Each entry is a dict with either a ``command`` key (→
:class:`CommandVerificationHook`) or a ``file`` key (→
:class:`FileCheckHook`). Unknown shapes are skipped.
Example::
verification:
- {name: tests, command: "python -m pytest -q"}
- {name: changelog, file: CHANGELOG.md, non_empty: true}
"""
from ..hooks.verification import CommandVerificationHook, FileCheckHook
hooks: List[Any] = []
for entry in entries or []:
if not isinstance(entry, dict):
continue
blocking = entry.get("blocking", True)
if "command" in entry:
hooks.append(CommandVerificationHook(
name=entry.get("name", "command"),
command=entry["command"],
cwd=entry.get("cwd"),
timeout=entry.get("timeout", 60.0),
blocking=blocking,
))
elif "file" in entry:
hooks.append(FileCheckHook(
name=entry.get("name", "file"),
path=entry["file"],
exists=entry.get("exists", True),
non_empty=entry.get("non_empty", False),
contains=entry.get("contains"),
json_field=entry.get("json_field"),
equals=entry.get("equals"),
blocking=blocking,
))
return hooks
class AutonomySignal(str, Enum):
"""Signals detected from prompts for autonomy decisions.
@@ -315,6 +263,17 @@ class AutonomySignal(str, Enum):
)
super().__init_subclass__(**kwargs)
def _warn_autonomy_signal():
"""Emit deprecation warning when AutonomySignal is accessed."""
from ..utils.deprecation import warn_deprecated_param
warn_deprecated_param(
"AutonomySignal",
since="1.0.0",
removal="2.0.0",
alternative="use EscalationSignal from praisonaiagents.escalation.types instead",
stacklevel=4
)
class AutonomyTrigger:
"""Detects signals from prompts for autonomy decisions.
File diff suppressed because it is too large. Load diff
@@ -59,8 +59,7 @@ class CodeAgent:
def __init__(
self,
name: str = "CodeAgent",
llm: Optional[str] = None, # Deprecated alias for model=
model: Optional[str] = None,
llm: Optional[str] = None,
code: Optional[Union[bool, Dict, CodeConfig]] = None,
instructions: Optional[str] = None,
verbose: bool = True,
@@ -70,16 +69,14 @@ class CodeAgent:
Args:
name: Agent name
llm: Deprecated alias for model=. Passing both raises TypeError.
model: Model to use (default: gpt-4o-mini)
llm: LLM model (default: gpt-4o-mini)
code: Code configuration (bool, dict, or CodeConfig)
instructions: System instructions
verbose: Enable verbose output
**kwargs: Additional arguments
"""
from ..utils.model_alias import resolve_model_name
self.name = name
self.llm = resolve_model_name(llm, model, "CodeAgent") or "gpt-4o-mini"
self.llm = llm or "gpt-4o-mini"
self.instructions = instructions
self.verbose = verbose
@@ -22,6 +22,7 @@ from typing import Optional, Any, Dict, Union, List, TYPE_CHECKING
# Lazy imports for performance - these are only loaded when needed
_subprocess = None
_glob = None
_ast = None
_asyncio = None
def _get_subprocess():
@@ -40,6 +41,14 @@ def _get_glob():
_glob = glob
return _glob
def _get_ast():
"""Lazy import ast to avoid import-time overhead."""
global _ast
if _ast is None:
import ast
_ast = ast
return _ast
def _get_asyncio():
"""Lazy import asyncio to avoid import-time overhead."""
global _asyncio
@@ -12,6 +12,7 @@ Usage::
"""
import json
import logging
from praisonaiagents._logging import get_logger
import os
import time
@@ -34,6 +34,7 @@ Example:
"""
import os
import logging
from praisonaiagents._logging import get_logger
import time
import asyncio
@@ -1,614 +0,0 @@
"""Opt-in durable tool-loop context backed by :class:`RunJournal`."""
from __future__ import annotations
import asyncio
import contextvars
import inspect
import json
import threading
from typing import Any, Callable, Dict, List, Optional, Tuple
from uuid import uuid4
from ..errors import ToolExecutionError
from ..runtime.journal import (
JournalEvent,
KIND_ITERATION,
KIND_MODEL_DECISION,
KIND_TOOL_CALL,
KIND_TOOL_RESULT,
KIND_VERIFICATION,
RunJournal,
)
_active_durable_run: contextvars.ContextVar[Optional["DurableRunContext"]] = (
contextvars.ContextVar("praisonai_active_durable_run", default=None)
)
_active_idempotency_key: contextvars.ContextVar[Optional[str]] = (
contextvars.ContextVar("praisonai_idempotency_key", default=None)
)
def _json_safe(value: Any) -> Any:
try:
return json.loads(json.dumps(value))
except (TypeError, ValueError):
return json.loads(json.dumps(value, default=str))
def _tool_result_content(result: Any) -> str:
if result is None:
return "Function returned an empty output"
try:
return json.dumps(result)
except (TypeError, ValueError):
return json.dumps({"result": str(result)})
def _accepts_idempotency_key(execute_tool_fn: Callable) -> bool:
"""Return whether an executor accepts the optional durable key contract."""
try:
parameters = inspect.signature(execute_tool_fn).parameters.values()
except (TypeError, ValueError):
return False
return any(
parameter.name == "idempotency_key"
or parameter.kind == inspect.Parameter.VAR_KEYWORD
for parameter in parameters
)
def _normalize_restart_safe(value: Any) -> Optional[bool]:
"""Accept only genuine booleans as a restart-safety declaration.
``None`` means undeclared. Any other type (e.g. the string ``"False"``) is a
malformed declaration and is treated as unsafe so we fail closed rather than
coercing a truthy value into an unintended replay.
"""
if value is None:
return None
if isinstance(value, bool):
return value
return False
def _canonical_tool_name(name: Any) -> str:
"""Normalise a tool name for tolerant comparison across repair variants.
``execute_tool`` may repair case/separator variants (e.g. ``Send-Email`` →
``send_email``); the declaration lookup mirrors that so an explicit
``restart_safe`` declaration is not missed for a repaired name.
"""
return "".join(ch for ch in str(name).lower() if ch.isalnum())
def _declared_restart_safe(
function_name: str, executor: Optional[Callable]
) -> Optional[bool]:
"""Return an explicit ``restart_safe`` declaration for ``function_name``.
Resolves the tool object first from the executor's owning agent (its live
``tools``), then from the global tool registry, and reads its
``restart_safe`` attribute. Returns ``None`` when the tool is undeclared or
cannot be resolved.
"""
if not function_name:
return False
target = _canonical_tool_name(function_name)
agent = getattr(executor, "__self__", None)
tools = getattr(agent, "tools", None)
if isinstance(tools, (list, tuple)):
for tool in tools:
name = getattr(tool, "name", None) or getattr(tool, "__name__", None)
if (
name is not None
and _canonical_tool_name(name) == target
and getattr(tool, "restart_safe", None) is not None
):
return _normalize_restart_safe(tool.restart_safe)
try:
from ..tools import get_registry as _get_tool_registry
tool = _get_tool_registry().get(function_name)
except Exception: # pragma: no cover - registry lookup is best-effort
tool = None
declared = getattr(tool, "restart_safe", None) if tool is not None else None
return _normalize_restart_safe(declared)
def _is_restart_safe(function_name: str, executor: Optional[Callable] = None) -> bool:
"""Resolve whether a tool is safe to re-run for an in-flight durable resume.
An explicit ``restart_safe`` declaration on the tool contract wins. When the
tool is undeclared (or cannot be resolved), fall back to the read-only name
heuristic and, ultimately, fail closed — an effectful/unknown tool is *not*
replayed so a missing declaration never causes a duplicated side effect.
"""
if not function_name:
return False
declared = _declared_restart_safe(function_name, executor)
if declared is not None:
return declared
try:
from .tool_execution import ToolExecutionMixin
return bool(ToolExecutionMixin._is_read_only_tool(function_name))
except Exception: # pragma: no cover - heuristic import is best-effort
return False
class DurableRunContext:
"""Per-turn journal state; safe for parallel tool-call wrappers."""
def __init__(
self,
journal: RunJournal,
run_id: str,
*,
replaying: bool,
) -> None:
self.journal = journal
self.run_id = run_id
self.replaying = replaying
self._lock = threading.RLock()
self._replay = journal.replay_index(run_id)
events = journal.events(run_id)
self._next_seq = max((event.seq for event in events), default=-1) + 1
self._restored = False
self._closed = False
self._results_by_tool_call_id: Dict[str, Any] = {}
self._pending_by_call_id: Dict[str, Tuple[int, str, Dict[str, Any], str]] = {}
self._pending_by_fingerprint: Dict[str, Tuple[int, str, Dict[str, Any], str]] = {}
# Names of in-flight tool calls (journalled tool_call with no tool_result
# at the crash). Used only when replaying to gate replay by restart-safety.
self._inflight_names_by_call_id: Dict[str, str] = {}
self._inflight_names_by_fingerprint: Dict[str, str] = {}
self._recorded_iterations = set()
for event in events:
if event.kind == KIND_TOOL_RESULT:
tool_call_id = event.payload.get("tool_call_id")
if tool_call_id:
self._results_by_tool_call_id[str(tool_call_id)] = event.payload.get(
"result"
)
elif event.kind == KIND_ITERATION:
self._recorded_iterations.add(
int(event.payload.get("index", event.seq))
)
for event in events:
if event.kind != KIND_TOOL_CALL:
continue
call_id = str(event.payload.get("tool_call_id") or "")
if not call_id or call_id in self._results_by_tool_call_id:
continue
name = str(event.payload.get("name") or "")
args = event.payload.get("args") or {}
key = str(
event.payload.get("idempotency_key")
or f"{self.run_id}:{event.seq}:{name}"
)
pending = (event.seq, call_id, args, key)
fingerprint = self._fingerprint(name, args)
self._pending_by_call_id[call_id] = pending
self._pending_by_fingerprint[fingerprint] = pending
self._inflight_names_by_call_id[call_id] = name
self._inflight_names_by_fingerprint[fingerprint] = name
self._resume_completed_steps = len(self._recorded_iterations)
@property
def completed_steps(self) -> int:
return len(self._recorded_iterations)
@staticmethod
def _fingerprint(function_name: str, arguments: Dict[str, Any]) -> str:
return f"{function_name}:{json.dumps(_json_safe(arguments), sort_keys=True)}"
def _is_inflight_call(
self,
function_name: str,
arguments: Dict[str, Any],
tool_call_id: Optional[str],
) -> bool:
"""Whether this call was in-flight (journalled, no result) at the crash.
Only meaningful while replaying: such calls have a recorded ``tool_call``
but no ``tool_result``, so re-driving the loop would re-execute their
side effect. Completed calls (already have a result) are replayed
upstream and never reach this check.
"""
if not self.replaying:
return False
call_id = str(tool_call_id) if tool_call_id is not None else None
if call_id and call_id in self._inflight_names_by_call_id:
return True
return self._fingerprint(function_name, arguments) in (
self._inflight_names_by_fingerprint
)
@staticmethod
def _not_safely_resumable_result(function_name: str) -> Dict[str, Any]:
"""Typed, operator-visible outcome for a gated in-flight effectful tool."""
return {
"error": (
f"Tool '{function_name}' was in-flight when the durable run "
"crashed and is not declared restart_safe; its outcome could not "
"be confirmed. It was not re-executed on resume to avoid a "
"duplicate side effect. Reconcile the external action manually "
"or mark the tool @tool(restart_safe=True) if it is idempotent."
),
"error_type": "NotSafelyResumable",
"not_safely_resumable": True,
"restart_safe": False,
}
def restore_messages(self, messages: List[Dict[str, Any]]) -> List[Dict[str, Any]]:
"""Append completed decision/result pairs once, before the next model call."""
if not self.replaying or self._restored:
return messages
existing_ids = set()
for message in messages:
for tool_call in message.get("tool_calls") or []:
if isinstance(tool_call, dict) and tool_call.get("id"):
existing_ids.add(str(tool_call["id"]))
for seq in sorted({key[0] for key in self._replay}):
decision = self._replay.get((seq, KIND_MODEL_DECISION))
result = self._replay.get((seq, KIND_TOOL_RESULT))
if not decision or result is None:
continue
message = decision.get("message")
tool_call_id = result.get("tool_call_id")
if not isinstance(message, dict) or not tool_call_id:
continue
if str(tool_call_id) in existing_ids:
continue
messages.append(_json_safe(message))
messages.append(
{
"role": "tool",
"tool_call_id": str(tool_call_id),
"content": _tool_result_content(result.get("result")),
}
)
existing_ids.add(str(tool_call_id))
self._restored = True
return messages
def _allocate_step(
self,
function_name: str,
arguments: Dict[str, Any],
tool_call_id: Optional[str],
) -> Tuple[int, str, str]:
with self._lock:
requested_call_id = str(tool_call_id) if tool_call_id is not None else None
pending = (
self._pending_by_call_id.pop(requested_call_id, None)
if requested_call_id
else None
)
fingerprint = self._fingerprint(function_name, arguments)
if pending is None and self.replaying:
pending = self._pending_by_fingerprint.pop(fingerprint, None)
if pending is not None:
seq, call_id, _args, idempotency_key = pending
self._pending_by_call_id.pop(call_id, None)
self._pending_by_fingerprint.pop(fingerprint, None)
return seq, call_id, idempotency_key
seq = self._next_seq
self._next_seq += 1
call_id = str(tool_call_id or f"{self.run_id}-tool-{seq}")
idempotency_key = f"{self.run_id}:{seq}:{function_name}"
safe_arguments = _json_safe(arguments)
message = {
"role": "assistant",
"content": "",
"tool_calls": [
{
"id": call_id,
"type": "function",
"function": {
"name": function_name,
"arguments": json.dumps(safe_arguments),
},
}
],
}
self.journal.append(
JournalEvent(
self.run_id,
seq,
KIND_MODEL_DECISION,
{"message": message},
)
)
self.journal.append(
JournalEvent(
self.run_id,
seq,
KIND_TOOL_CALL,
{
"name": function_name,
"args": safe_arguments,
"tool_call_id": call_id,
"idempotency_key": idempotency_key,
},
)
)
return seq, call_id, idempotency_key
def _record_result(
self,
seq: int,
tool_call_id: str,
result: Any,
iteration_index: Optional[int],
) -> Any:
safe_result = _json_safe(result)
with self._lock:
self.journal.append(
JournalEvent(
self.run_id,
seq,
KIND_TOOL_RESULT,
{"tool_call_id": tool_call_id, "result": safe_result},
)
)
if iteration_index is None:
global_iteration = max(self._recorded_iterations, default=-1) + 1
else:
global_iteration = self._resume_completed_steps + int(iteration_index)
if global_iteration not in self._recorded_iterations:
self.journal.append(
JournalEvent(
self.run_id,
global_iteration,
KIND_ITERATION,
{"index": global_iteration},
)
)
self._recorded_iterations.add(global_iteration)
self._results_by_tool_call_id[tool_call_id] = safe_result
self._replay[(seq, KIND_TOOL_RESULT)] = {
"tool_call_id": tool_call_id,
"result": safe_result,
}
return safe_result
def _record_terminal_failure(
self,
seq: int,
tool_call_id: str,
error: ToolExecutionError,
iteration_index: Optional[int],
) -> None:
"""Persist a fatal tool outcome and make the run non-resumable."""
self._record_result(
seq,
tool_call_id,
{
"error": str(error),
"error_type": type(error).__name__,
"is_retryable": bool(error.is_retryable),
"terminal": True,
},
iteration_index,
)
self.finalize("failed")
def record_verification(self, payloads: List[Dict[str, Any]]) -> None:
"""Append verification-gate results as durable ``verification`` events.
Each payload gets its own fresh ``seq`` so the events append cleanly
alongside the tool-call cursor without colliding on ``(run_id, seq,
kind)``. Best-effort: journalling never raises into the gate.
"""
if self._closed:
return
with self._lock:
for payload in payloads:
seq = self._next_seq
self._next_seq += 1
try:
self.journal.append(
JournalEvent(self.run_id, seq, KIND_VERIFICATION, payload)
)
except Exception: # pragma: no cover - journalling is best-effort
pass
def wrap_sync(self, execute_tool_fn: Optional[Callable]) -> Optional[Callable]:
if execute_tool_fn is None:
return None
def execute(function_name, arguments, tool_call_id=None, **kwargs):
iteration_index = kwargs.pop("_durable_iteration_index", None)
call_id = str(tool_call_id) if tool_call_id is not None else None
if call_id and call_id in self._results_by_tool_call_id:
return self._results_by_tool_call_id[call_id]
gate_inflight = self._is_inflight_call(
function_name, arguments, tool_call_id
) and not _is_restart_safe(function_name, execute_tool_fn)
seq, call_id, idempotency_key = self._allocate_step(
function_name, arguments, tool_call_id
)
if gate_inflight:
return self._record_result(
seq,
call_id,
self._not_safely_resumable_result(function_name),
iteration_index,
)
token = _active_idempotency_key.set(idempotency_key)
try:
call_kwargs = dict(kwargs)
call_kwargs["tool_call_id"] = tool_call_id
if _accepts_idempotency_key(execute_tool_fn):
call_kwargs["idempotency_key"] = idempotency_key
result = execute_tool_fn(function_name, arguments, **call_kwargs)
except ToolExecutionError as exc:
if not exc.is_retryable:
self._record_terminal_failure(
seq, call_id, exc, iteration_index
)
raise
except Exception as exc:
result = {"error": str(exc)}
finally:
_active_idempotency_key.reset(token)
return self._record_result(seq, call_id, result, iteration_index)
return execute
def wrap_async(self, execute_tool_fn: Optional[Callable]) -> Optional[Callable]:
if execute_tool_fn is None:
return None
async def execute(function_name, arguments, tool_call_id=None, **kwargs):
iteration_index = kwargs.pop("_durable_iteration_index", None)
call_id = str(tool_call_id) if tool_call_id is not None else None
if call_id and call_id in self._results_by_tool_call_id:
return self._results_by_tool_call_id[call_id]
gate_inflight = self._is_inflight_call(
function_name, arguments, tool_call_id
) and not _is_restart_safe(function_name, execute_tool_fn)
seq, call_id, idempotency_key = await asyncio.to_thread(
self._allocate_step, function_name, arguments, tool_call_id
)
if gate_inflight:
return await asyncio.to_thread(
self._record_result,
seq,
call_id,
self._not_safely_resumable_result(function_name),
iteration_index,
)
token = _active_idempotency_key.set(idempotency_key)
try:
call_kwargs = dict(kwargs)
call_kwargs["tool_call_id"] = tool_call_id
if _accepts_idempotency_key(execute_tool_fn):
call_kwargs["idempotency_key"] = idempotency_key
result = execute_tool_fn(function_name, arguments, **call_kwargs)
if inspect.isawaitable(result):
result = await result
except ToolExecutionError as exc:
if not exc.is_retryable:
await asyncio.to_thread(
self._record_terminal_failure,
seq,
call_id,
exc,
iteration_index,
)
raise
except Exception as exc:
result = {"error": str(exc)}
finally:
_active_idempotency_key.reset(token)
return await asyncio.to_thread(
self._record_result, seq, call_id, result, iteration_index
)
return execute
def finalize(self, outcome: str = "succeeded") -> None:
if not self._closed:
self.journal.close_run(self.run_id, outcome)
self._closed = True
def close(self) -> None:
self.journal.close()
async def arestore_messages(
self, messages: List[Dict[str, Any]]
) -> List[Dict[str, Any]]:
return await asyncio.to_thread(self.restore_messages, messages)
async def afinalize(self, outcome: str = "succeeded") -> None:
await asyncio.to_thread(self.finalize, outcome)
async def aclose(self) -> None:
await asyncio.to_thread(self.close)
def begin_durable_run(agent: Any, prompt: str):
"""Create and activate a context, or return ``(None, None)`` when disabled."""
execution = getattr(agent, "execution", None)
if execution is None or not getattr(execution, "durable", False):
return None, None
if _active_durable_run.get() is not None:
return None, None
context = _open_durable_run(agent, prompt)
token = _active_durable_run.set(context)
return context, token
def _open_durable_run(agent: Any, prompt: str) -> DurableRunContext:
"""Open journal state without mutating the caller's ContextVar."""
execution = agent.execution
journal = RunJournal(getattr(execution, "journal_path", None))
resume_run_id = getattr(execution, "resume_run_id", None)
replaying = bool(resume_run_id)
run_id = str(resume_run_id or uuid4())
if replaying:
metadata = journal.run_meta(run_id)
if metadata is None:
journal.close()
raise ValueError(f"Cannot resume unknown durable run {run_id!r}")
if metadata.status != "running":
journal.close()
raise ValueError(
f"Cannot resume terminal durable run {run_id!r} "
f"(status={metadata.status!r})"
)
if metadata.task and metadata.task != prompt:
journal.close()
raise ValueError(
"Resume prompt does not match the prompt recorded for durable "
f"run {run_id!r}"
)
journal.open_run(
run_id,
agent=getattr(agent, "name", ""),
task=prompt,
metadata={"version": 1, "explicit_resume": replaying},
)
context = DurableRunContext(journal, run_id, replaying=replaying)
agent._last_durable_run_id = run_id
return context
async def abegin_durable_run(agent: Any, prompt: str):
"""Async durable-run creation with all SQLite I/O off the event loop."""
execution = getattr(agent, "execution", None)
if execution is None or not getattr(execution, "durable", False):
return None, None
if _active_durable_run.get() is not None:
return None, None
context = await asyncio.to_thread(_open_durable_run, agent, prompt)
token = _active_durable_run.set(context)
return context, token
def end_durable_run(token) -> None:
if token is not None:
_active_durable_run.reset(token)
def get_durable_run() -> Optional[DurableRunContext]:
return _active_durable_run.get()
def get_durable_idempotency_key() -> Optional[str]:
"""Return the stable key for the currently executing durable tool call."""
return _active_idempotency_key.get()
@@ -110,8 +110,8 @@ class EmbeddingAgent:
- EmbeddingConfig: Full configuration object
verbose: Verbosity level for output
"""
from ..utils.model_alias import resolve_model_name
llm = resolve_model_name(llm, model, "EmbeddingAgent")
if llm is None and model is not None:
llm = model
self.name = name or "EmbeddingAgent"
self.instructions = instructions
@@ -1,276 +0,0 @@
"""Describe, in plain English, where an agent's work actually happens.
PraisonAI can run the thinking (LLM calls) and the tools in different places:
this machine, a container, or a provider's cloud. Which one you get depends on
``run_on=``, ``backend=`` and ``sandbox=``, and until now none of that was
visible from the object -- ``repr(agent)`` was the bare default.
This module is the single source of that answer, shared by ``Agent``,
``AgentTeam`` and ``AgentFlow`` so all three describe themselves identically.
Vocabulary note: the fields are ``thinks_on`` / ``tools_run_on``, never
``loop``. "Loop" is already a public workflow primitive here
(``praisonaiagents.workflows.loop()``), asyncio's event loop, and agent-loop
jargon a beginner would not know -- three meanings for one word is exactly the
problem this module exists to fix.
"""
from __future__ import annotations
from typing import Any, Dict, Optional
# Provider name -> how a human would say it out loud.
_PLACE_WORDS = {
"local": "this machine",
"subprocess": "a separate process on this machine",
"sandlock": "a locked-down process on this machine",
"docker": "a Docker container",
"e2b": "an E2B cloud sandbox",
"modal": "a Modal cloud sandbox",
"daytona": "a Daytona cloud sandbox",
"flyio": "a Fly.io machine",
"tenki": "a Tenki cloud sandbox",
"novita": "a Novita cloud sandbox",
"ssh": "a remote machine over SSH",
"anthropic": "Anthropic's cloud",
}
HERE = "this machine"
# Public sandbox aliases the SandboxManager collapses before it picks a backend
# (see praisonaiagents/sandbox/manager.py). We must describe the backend that
# actually runs, not the alias the user typed, or "native"/"local" would report
# a place that never executes.
_ALIASES = {"native": "sandlock", "local": "subprocess"}
# ...but only for the SANDBOX registry. "local" resolves to two different
# backends depending on which parameter carried it:
# run_in="local" -> SandboxManager collapses it to subprocess:
# scrubbed environment, blocked commands and paths
# tools_run_on="local" -> the wrapper's LocalCompute: a plain shell in the
# current directory, full environment inherited,
# no security policy at all
# Describing the second in the first's words overstates it, which is the exact
# failure this module exists to prevent. One word, two backends -- so the
# phrase has to depend on where the word came from.
_COMPUTE_ONLY_WORDS = {"local": "a plain shell on this machine (no policy applied)"}
# Tiers that separate a process but do NOT contain it. Verified: under the
# subprocess backend, outbound network still works and ~/.ssh is readable even
# though SecurityPolicy declares them blocked.
# `native` is deliberately absent: it aliases sandlock, which applies Landlock,
# seccomp, a scrubbed environment and deny-all networking. Listing it here made
# tools_run_on="native" and tools_run_on="sandlock" -- the same backend --
# disagree about whether they contain anything.
_NOT_A_BOUNDARY = {"subprocess", "local"}
def say_place(name: Any, *, via: str = "sandbox") -> str:
"""Turn a place name into a phrase a non-developer can read.
``via`` says which registry resolved the name -- ``"compute"`` for
``tools_run_on=``, ``"sandbox"`` for ``run_in=``. It only matters for names
that mean different backends in each (see ``_COMPUTE_ONLY_WORDS``).
"""
if name is None:
return HERE
if name is True:
return _PLACE_WORDS["subprocess"]
if not isinstance(name, str):
# A configured provider instance: use its own declared name if it has
# one. Normalise BEFORE the compute-only check, or a backend holding a
# LocalCompute object (provider_name="local") skips the branch and gets
# described in the subprocess backend's stronger words -- the exact
# overstatement this module exists to prevent.
name = getattr(name, "provider_name", None) or type(name).__name__
if via == "compute" and name.lower() in _COMPUTE_ONLY_WORDS:
return _COMPUTE_ONLY_WORDS[name.lower()]
key = str(name).lower()
key = _ALIASES.get(key, key)
known = _PLACE_WORDS.get(key)
if known:
return known
# A place contributed by another package can name itself; the bare name is
# the last resort rather than the only option, because the phrase table is
# a literal that cannot know about packages installed later.
try:
from ..managed._compute_bridge import contributed_display_name
declared = contributed_display_name(key)
if declared:
return declared
except Exception:
pass
return str(name)
def _backend_places(backend: Any) -> Optional[Dict[str, str]]:
"""Where does a managed ``backend=`` put the thinking and the tools?"""
if backend is None:
return None
# Ask the backend what it is, rather than guessing from its class name.
# Name-matching missed any backend that did not happen to contain "Hosted"
# or "Anthropic" -- a self-hosted docker backend reported that it was
# thinking on this machine while the whole loop ran in a container.
declared = getattr(backend, "provider_name", None)
if isinstance(declared, str):
try:
from .placement import managed_runtimes
if declared.lower() in managed_runtimes():
where = say_place(declared)
return {"thinks_on": where, "tools_run_on": where}
except Exception:
pass
cls = type(backend).__name__
# Hosted runtimes move the entire turn off this machine.
if "Hosted" in cls or "Anthropic" in cls:
provider = getattr(backend, "provider", None) or "anthropic"
where = say_place(provider)
return {"thinks_on": where, "tools_run_on": where}
# Local/sandboxed agents keep the loop here and may push tools out. A
# backend's compute object is a COMPUTE-registry provider, so it is read
# with the compute vocabulary: a LocalCompute here is the unrestricted
# shell, not the subprocess backend "local" collapses to under run_in=.
compute = getattr(backend, "_compute", None) or getattr(backend, "compute", None)
if compute is not None:
return {"thinks_on": HERE, "tools_run_on": say_place(compute, via="compute")}
return {"thinks_on": HERE, "tools_run_on": HERE}
def describe(obj: Any, *, shared: bool = False) -> Dict[str, str]:
"""Return ``{thinks_on, tools_run_on, code_runs_on?}`` for an object.
Never raises: a description of where things run must not be able to break
the thing it describes.
"""
places: Dict[str, str] = {"thinks_on": HERE, "tools_run_on": HERE}
try:
from_backend = _backend_places(getattr(obj, "backend", None))
if from_backend:
places.update(from_backend)
where_tools = getattr(obj, "tools_run_on", None)
if where_tools is not None:
where = say_place(where_tools, via="compute")
places["tools_run_on"] = f"{where} (shared)" if shared else where
# run_on= puts the WHOLE agent on a managed runtime, so it moves the
# thinking as well. _backend_places() already reports that (run_on= is
# turned into a backend at construction); this only covers an object
# that carries the name without a built backend.
whole = getattr(obj, "run_on", None)
if whole is not None and not from_backend:
everywhere = say_place(whole)
places["thinks_on"] = everywhere
places["tools_run_on"] = everywhere
sandbox_config = getattr(obj, "sandbox_config", None)
if sandbox_config is not None:
places["code_runs_on"] = say_place(
getattr(sandbox_config, "sandbox_type", None)
)
except Exception: # pragma: no cover - description must never break callers
pass
return places
def _tools_staying_here(obj: Any) -> list:
"""Names of the object's own tools, which do NOT move to the sandbox.
Only four tool names are bridged (``execute_command``, ``read_file``,
``write_file``, ``list_files``); everything else the user passed keeps
running in this process, against this filesystem. The capability prompt
tells the model the sandbox is where things happen, so anything staying
behind has to be said out loud.
Reads the pre-attach tool list when a sandbox is already attached: by then
``agent.tools`` has been rewritten and the originals live in the sandbox's
restore record.
"""
try:
from ..managed.shared_compute import BRIDGED_TOOL_NAMES
except Exception:
BRIDGED_TOOL_NAMES = ("execute_command", "read_file", "write_file", "list_files")
tools = None
shared = getattr(obj, "_tools_sandbox", None)
if shared is not None:
for patched, original_tools, _ in getattr(shared, "_patched", []):
if patched is obj:
tools = original_tools
break
if tools is None:
tools = getattr(obj, "tools", None) or []
names = []
for tool in tools:
name = getattr(tool, "__name__", None) or getattr(tool, "name", None)
if isinstance(name, str) and name not in BRIDGED_TOOL_NAMES:
names.append(name)
return names
def repr_fields(obj: Any, *, shared: bool = False) -> str:
"""Render the places as ``key='value'`` pairs for a ``__repr__``."""
return ", ".join(f"{k}={v!r}" for k, v in describe(obj, shared=shared).items())
def explain(obj: Any, *, shared: bool = False) -> str:
"""Plain-sentence answer to "where does this actually run?".
Deliberately uses only words a non-engineer already knows -- no "loop",
"harness", "provision" or "runtime".
"""
places = describe(obj, shared=shared)
lines = [
f"Thinking (the AI model calls) happens on {places['thinks_on']}.",
f"Tools run on {places['tools_run_on']}.",
]
if shared and getattr(obj, "tools_run_on", None) is not None:
lines.append(
"Every step shares that same sandbox, so a file written by one step "
"is visible to the next."
)
staying = _tools_staying_here(obj)
if staying and places["tools_run_on"] != places["thinks_on"]:
listed = ", ".join(staying[:6]) + ("..." if len(staying) > 6 else "")
lines.append(
f"Your own tools ({listed}) still run on {HERE} -- only shell, file "
f"and code tools move. They read and write this machine's files."
)
if "code_runs_on" in places:
lines.append(
f"Code you run yourself with execute_code() runs on {places['code_runs_on']}."
)
# Say plainly when the chosen tier is not a security boundary.
raw = [
getattr(obj, "tools_run_on", None),
getattr(obj, "run_on", None),
getattr(getattr(obj, "sandbox_config", None), "sandbox_type", None),
]
if any(isinstance(v, str) and v.lower() in _NOT_A_BOUNDARY for v in raw) or any(
v is True for v in raw
):
lines.append(
"Note: a separate process is not a security boundary -- it can still "
"reach the network and read your files, and its blocked-command "
"list can be worked around by ordinary shell syntax. Use docker or a cloud "
"provider for untrusted code."
)
if places["thinks_on"] == HERE and places["tools_run_on"] == HERE:
lines.append(
"Nothing is isolated: tools you pass run in this program, with your "
"permissions."
)
return "\n".join(lines)
File diff suppressed because it is too large. Load diff
@@ -14,10 +14,9 @@ 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
import logging
from praisonaiagents._logging import get_logger
import asyncio
import contextvars
import threading
import time
import json
@@ -164,52 +163,33 @@ from ..errors import (
HandoffValidationError
)
# Per-task/per-thread storage for tracking handoff chains.
#
# ``contextvars.ContextVar`` isolates the chain per :class:`asyncio.Task`
# (and per OS thread), unlike ``threading.local()`` which shares one list
# across every coroutine running on the same event-loop thread. Concurrent
# async handoffs (``asyncio.gather``, a server handling parallel requests, or
# any ``max_concurrent`` workflow) would otherwise push/pop into the same list
# and corrupt each other's cycle/depth state. Combined with the copy-on-write
# push/pop below, this fully isolates sibling handoff tasks (e.g. those spawned
# by ``parallel_handoffs`` via ``asyncio.gather``).
_handoff_chain_var: "contextvars.ContextVar[Optional[List[str]]]" = contextvars.ContextVar(
"handoff_chain", default=None
)
# Thread-local storage for tracking handoff chains
_handoff_context = threading.local()
def _get_handoff_chain() -> List[str]:
"""Get current handoff chain for this task/thread."""
chain = _handoff_chain_var.get()
if chain is None:
chain = []
_handoff_chain_var.set(chain)
return chain
"""Get current handoff chain from thread-local storage."""
if not hasattr(_handoff_context, 'chain'):
_handoff_context.chain = []
return _handoff_context.chain
def _get_handoff_depth() -> int:
"""Get current handoff depth."""
return len(_get_handoff_chain())
def _push_handoff(agent_name: str) -> None:
"""Push agent to handoff chain.
Uses copy-on-write so a push made inside a child task does not leak back
into the parent task's chain once the child completes.
"""
chain = list(_get_handoff_chain())
"""Push agent to handoff chain."""
chain = _get_handoff_chain()
chain.append(agent_name)
_handoff_chain_var.set(chain)
def _pop_handoff() -> Optional[str]:
"""Pop agent from handoff chain."""
chain = list(_get_handoff_chain())
popped = chain.pop() if chain else None
_handoff_chain_var.set(chain)
return popped
chain = _get_handoff_chain()
return chain.pop() if chain else None
def _clear_handoff_chain() -> None:
"""Clear the handoff chain."""
_handoff_chain_var.set([])
if hasattr(_handoff_context, 'chain'):
_handoff_context.chain = []
@dataclass
class HandoffInputData:
@@ -309,14 +289,12 @@ class Handoff:
- Cycle detection and depth limiting
- Configurable context policies
"""
# Class-level lock guarding lazy creation of each instance's async
# semaphore. The semaphore itself is per-instance (so every Handoff
# enforces its own max_concurrent), but the brief init critical section is
# only ever touched under this shared threading.Lock, which keeps
# double-checked lazy creation thread-safe without a per-instance lock.
_semaphore_lock: threading.Lock = threading.Lock()
# Class-level semaphore for concurrency control
_semaphore: Optional[asyncio.Semaphore] = None
_sync_semaphore: Optional[threading.Semaphore] = None
_semaphore_lock: threading.Lock = threading.Lock() # Lock for semaphore initialization
def __init__(
self,
agent: 'Agent',
@@ -347,40 +325,10 @@ class Handoff:
self.input_type = input_type
self.input_filter = input_filter
self.config = config or HandoffConfig()
# Instance-level concurrency control. Each Handoff enforces its own
# max_concurrent instead of sharing one process-wide semaphore, so
# different handoffs don't silently override each other's limits based
# on execution order. The async semaphore is created lazily (and
# recreated if bound to a stale event loop) since it binds to the
# running loop on first use.
self._semaphore: Optional[asyncio.Semaphore] = None
self._semaphore_loop: Optional[asyncio.AbstractEventLoop] = None
# Override config callback if on_handoff provided directly
if on_handoff and not self.config.on_handoff:
self.config.on_handoff = on_handoff
def _get_semaphore(self) -> Optional[asyncio.Semaphore]:
"""Return this handoff's async semaphore, bound to the current loop.
Returns None when concurrency limiting is disabled (max_concurrent <= 0).
The semaphore is created lazily and recreated if the running event loop
differs from the one it was originally bound to, so a process that calls
asyncio.run(...) more than once doesn't crash with a "bound to a
different event loop" RuntimeError.
"""
if self.config.max_concurrent <= 0:
return None
try:
current_loop = asyncio.get_event_loop()
except RuntimeError:
current_loop = None
with self._semaphore_lock:
if self._semaphore is None or self._semaphore_loop is not current_loop:
self._semaphore = asyncio.Semaphore(self.config.max_concurrent)
self._semaphore_loop = current_loop
return self._semaphore
@property
def tool_name(self) -> str:
@@ -470,46 +418,12 @@ class Handoff:
return value
return 'gpt-4o-mini'
@contextmanager
def _seed_target_history(self, prior_messages: Optional[List[Any]]):
"""Temporarily seed the filtered handoff context onto the target agent.
The configured ``context_policy``/``input_filter`` produce the messages the
target should see; without seeding them the target only ever received the
literal handoff prompt string and the configured policy had no effect.
The seeding is *invocation-scoped*: the prior messages are prepended for the
duration of this handoff and the target's original ``chat_history`` is
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.
No shared mutable state is retained between agents.
"""
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,
source_agent: 'Agent',
prompt: str,
effective_tools: Optional[List[Any]],
context: Dict[str, Any],
prior_messages: Optional[List[Any]] = None,
context: Dict[str, Any]
) -> str:
"""Execute handoff through the target agent's full chat pipeline."""
target_model_ref = self._extract_model_ref(self.agent)
@@ -519,16 +433,14 @@ class Handoff:
target_model_ref,
_get_handoff_depth(),
)
with self._seed_target_history(prior_messages):
return self.agent.chat(prompt, tools=effective_tools)
return self.agent.chat(prompt, tools=effective_tools)
async def _execute_with_runtime_resolution_async(
self,
source_agent: 'Agent',
prompt: str,
effective_tools: Optional[List[Any]],
context: Dict[str, Any],
prior_messages: Optional[List[Any]] = None,
context: Dict[str, Any]
) -> str:
"""Execute handoff through the target agent's full async chat pipeline."""
target_model_ref = self._extract_model_ref(self.agent)
@@ -538,14 +450,13 @@ class Handoff:
target_model_ref,
_get_handoff_depth(),
)
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)
loop = asyncio.get_running_loop()
return await loop.run_in_executor(
None, lambda: self.agent.chat(prompt, tools=effective_tools)
)
async_chat = getattr(self.agent, 'achat', None)
if callable(async_chat) and inspect.iscoroutinefunction(async_chat):
return await async_chat(prompt, tools=effective_tools)
loop = asyncio.get_running_loop()
return await loop.run_in_executor(
None, lambda: self.agent.chat(prompt, tools=effective_tools)
)
def _check_safety(self, source_agent: 'Agent') -> None:
"""
@@ -686,22 +597,19 @@ class Handoff:
"""
start_time = time.time()
kwargs = context or {}
pushed = False
try:
# Safety checks (may raise before anything is pushed for this call)
# Safety checks
self._check_safety(source_agent)
# Track handoff chain
_push_handoff(source_agent.name)
pushed = True
# Execute on_handoff callback
self._execute_callback(self.config.on_handoff or self.on_handoff, source_agent, kwargs)
# Prepare context per the configured context_policy/input_filter and
# thread the filtered history through to the target agent.
handoff_data = self._prepare_context(source_agent, kwargs)
# Prepare context (for future extensibility - context data available for hooks)
_ = self._prepare_context(source_agent, kwargs)
# Build prompt with context
context_prefix = f"[Handoff from {source_agent.name}] "
@@ -716,8 +624,7 @@ class Handoff:
# Resolve runtime at turn-time instead of using construction-time pin
response = self._execute_with_runtime_resolution(
source_agent, full_prompt, effective_tools, kwargs,
prior_messages=handoff_data.messages,
source_agent, full_prompt, effective_tools, kwargs
)
result = HandoffResult(
@@ -772,8 +679,7 @@ class Handoff:
logger.error(f"Handoff error: {e}")
return result
finally:
if pushed:
_pop_handoff()
_pop_handoff()
async def execute_async(
self,
@@ -792,26 +698,26 @@ class Handoff:
Returns:
HandoffResult with response or error
"""
# Per-instance semaphore, bound to the current event loop
semaphore = self._get_semaphore()
# Initialize semaphore if needed (thread-safe)
if self.config.max_concurrent > 0 and Handoff._semaphore is None:
with Handoff._semaphore_lock: # Thread-safe initialization
if Handoff._semaphore is None: # Double-check after acquiring lock
Handoff._semaphore = asyncio.Semaphore(self.config.max_concurrent)
start_time = time.time()
kwargs = context or {}
async def _execute():
pushed = False
try:
# Safety checks (may raise before anything is pushed for this call)
# Safety checks
self._check_safety(source_agent)
_push_handoff(source_agent.name)
pushed = True
# Execute callback
self._execute_callback(self.config.on_handoff or self.on_handoff, source_agent, kwargs)
# Prepare context per the configured context_policy/input_filter
# and thread the filtered history through to the target agent.
handoff_data = self._prepare_context(source_agent, kwargs)
# Prepare context (for future extensibility)
_ = self._prepare_context(source_agent, kwargs)
# Build prompt
context_prefix = f"[Handoff from {source_agent.name}] "
@@ -826,8 +732,7 @@ class Handoff:
# Resolve runtime at turn-time for async execution
response = await self._execute_with_runtime_resolution_async(
source_agent, full_prompt, effective_tools, kwargs,
prior_messages=handoff_data.messages,
source_agent, full_prompt, effective_tools, kwargs
)
result = HandoffResult(
@@ -855,12 +760,11 @@ class Handoff:
return result
finally:
if pushed:
_pop_handoff()
_pop_handoff()
try:
if semaphore is not None:
async with semaphore:
if self.config.max_concurrent > 0 and Handoff._semaphore:
async with Handoff._semaphore:
if self.config.timeout_seconds > 0:
result = await asyncio.wait_for(
_execute(),
@@ -924,15 +828,13 @@ class Handoff:
def handoff_tool(**kwargs):
"""Execute the handoff to the target agent."""
start_time = time.time()
pushed = False
try:
# Safety checks (may raise before anything is pushed for this call)
# Safety checks
self._check_safety(source_agent)
# Track handoff chain
_push_handoff(source_agent.name)
pushed = True
# Execute on_handoff callback
self._execute_callback(self.config.on_handoff or self.on_handoff, source_agent, kwargs)
@@ -940,39 +842,20 @@ class Handoff:
# Prepare handoff data with context policy
handoff_data = self._prepare_context(source_agent, kwargs)
# Get the last user message or context to pass to target agent.
# Track the index of the message chosen for ``prompt`` so exactly
# that item is excluded from the seeded history (it may not be the
# final list item if an assistant/tool message follows it).
# Get the last user message or context to pass to target agent
last_message = None
selected_index = None
for i in range(len(handoff_data.messages) - 1, -1, -1):
msg = handoff_data.messages[i]
for msg in reversed(handoff_data.messages):
if isinstance(msg, dict) and msg.get('role') == 'user':
last_message = msg.get('content', '')
selected_index = i
break
if not last_message and handoff_data.messages:
selected_index = len(handoff_data.messages) - 1
last_msg = handoff_data.messages[selected_index]
last_msg = handoff_data.messages[-1]
if isinstance(last_msg, dict):
last_message = last_msg.get('content', '')
else:
last_message = str(last_msg)
# Tool-style handoff (as_tool): ContextPolicy.NONE discards the
# history, so the prompt must come from the generated ``task``/
# ``prompt`` argument instead. Without this the sub-agent would
# never run and the tool would report a hollow "completed". The
# task is the sub-agent's whole instruction, so it is passed
# verbatim rather than wrapped in a ``[Handoff from …]`` prefix.
task_prompt = None
if not last_message and not self.input_type:
task_prompt = kwargs.get('task') or kwargs.get('prompt')
if task_prompt:
last_message = str(task_prompt)
# Prepare context information
context_info = f"[Handoff from {source_agent.name}] "
if kwargs and self.input_type:
@@ -980,26 +863,15 @@ class Handoff:
# Execute the target agent with tool boundary enforcement
if last_message:
prompt = last_message if task_prompt else context_info + last_message
prompt = context_info + last_message
logger.info(f"Handing off to {self.agent.name} with prompt: {prompt}")
# Compute effective tools based on tool policy
effective_tools = self._compute_effective_tools(source_agent)
# Resolve runtime at turn-time for tool function execution.
# The selected message is already folded into ``prompt`` above,
# so exclude exactly that item from the seeded history to avoid
# duplicating it while preserving any messages that follow it.
if selected_index is None:
prior_messages = list(handoff_data.messages)
else:
prior_messages = (
handoff_data.messages[:selected_index]
+ handoff_data.messages[selected_index + 1:]
)
# Resolve runtime at turn-time for tool function execution
response = self._execute_with_runtime_resolution(
source_agent, prompt, effective_tools, kwargs,
prior_messages=prior_messages,
source_agent, prompt, effective_tools, kwargs
)
result = HandoffResult(
@@ -1048,8 +920,7 @@ class Handoff:
self._execute_callback(self.config.on_error, source_agent, kwargs, result)
return f"Error during handoff to {self.agent.name}: {str(e)}"
finally:
if pushed:
_pop_handoff()
_pop_handoff()
# Set function metadata for tool definition generation
handoff_tool.__name__ = self.tool_name
@@ -1067,17 +938,6 @@ class Handoff:
)
)
handoff_tool.__signature__ = inspect.Signature(sig_params)
elif self.config.context_policy == ContextPolicy.NONE:
# Tool-style handoff (as_tool): no conversation context is passed, so
# advertise an explicit ``task`` parameter the caller must fill. This
# is what ``handoff_tool`` reads as the sub-agent's prompt above.
handoff_tool.__signature__ = inspect.Signature([
inspect.Parameter(
'task',
inspect.Parameter.KEYWORD_ONLY,
annotation=str,
)
])
return handoff_tool
@@ -1311,13 +1171,6 @@ async def parallel_handoffs(
semaphore = asyncio.Semaphore(effective_max_concurrent) if effective_max_concurrent > 0 else None
async def _run_one(agent, prompt):
# Each gathered task shares a copied context, but a copied ContextVar
# binding still points at the *same* parent list object. Rebind to a
# fresh, per-task copy so sibling handoffs cannot corrupt each other's
# cycle/depth tracking when parallel_handoffs runs inside a non-empty
# parent handoff chain.
_handoff_chain_var.set(list(_handoff_chain_var.get() or []))
async def _do_handoff():
try:
return await source.handoff_to_async(agent, prompt, config=config)
@@ -1538,22 +1391,19 @@ class TypedHandoff(Handoff, Generic[T]):
start_time = time.time()
kwargs = context or {}
pushed = False
try:
# Safety checks (may raise before anything is pushed for this call)
# Safety checks
self._check_safety(source_agent)
# Track handoff chain
_push_handoff(source_agent.name)
pushed = True
# Execute on_handoff callback
self._execute_callback(self.config.on_handoff or self.on_handoff, source_agent, kwargs)
# Apply context policy / input filter; the resulting messages are
# seeded onto the target only for the duration of its chat below.
handoff_data = self._prepare_context(source_agent, kwargs)
# Apply input filter if provided (fixes Greptile P1 issue)
_ = self._prepare_context(source_agent, kwargs)
# Validate payload against schema
try:
@@ -1580,8 +1430,7 @@ class TypedHandoff(Handoff, Generic[T]):
logger.info(f"Typed handoff to {self.agent.name} with validated payload")
# Execute with timeout if sync
with self._seed_target_history(handoff_data.messages):
response = self.agent.chat(full_prompt)
response = self.agent.chat(full_prompt)
result = HandoffResult(
success=True,
@@ -1621,8 +1470,7 @@ class TypedHandoff(Handoff, Generic[T]):
logger.error(f"Typed handoff error: {e}")
return result
finally:
if pushed:
_pop_handoff()
_pop_handoff()
async def execute_async(
self,
@@ -1649,26 +1497,26 @@ class TypedHandoff(Handoff, Generic[T]):
if isinstance(payload, str):
return await super().execute_async(source_agent, payload, context)
# Per-instance semaphore, bound to the current event loop
semaphore = self._get_semaphore()
# Initialize semaphore if needed (thread-safe)
if self.config.max_concurrent > 0 and Handoff._semaphore is None:
with Handoff._semaphore_lock:
if Handoff._semaphore is None:
Handoff._semaphore = asyncio.Semaphore(self.config.max_concurrent)
start_time = time.time()
kwargs = context or {}
async def _execute():
pushed = False
try:
# Safety checks (may raise before anything is pushed for this call)
# Safety checks
self._check_safety(source_agent)
_push_handoff(source_agent.name)
pushed = True
# Execute callback
self._execute_callback(self.config.on_handoff or self.on_handoff, source_agent, kwargs)
# Apply context policy / input filter; the resulting messages are
# seeded onto the target only for the duration of its chat below.
handoff_data = self._prepare_context(source_agent, kwargs)
# Apply input filter if provided (fixes Greptile P1 issue)
_ = self._prepare_context(source_agent, kwargs)
# Validate payload against schema
try:
@@ -1694,13 +1542,12 @@ class TypedHandoff(Handoff, Generic[T]):
logger.info(f"Async typed handoff to {self.agent.name}")
# Execute - check for async chat method
with self._seed_target_history(handoff_data.messages):
if hasattr(self.agent, 'achat'):
response = await self.agent.achat(full_prompt)
else:
# Run sync chat in executor
loop = asyncio.get_event_loop()
response = await loop.run_in_executor(None, self.agent.chat, full_prompt)
if hasattr(self.agent, 'achat'):
response = await self.agent.achat(full_prompt)
else:
# Run sync chat in executor
loop = asyncio.get_event_loop()
response = await loop.run_in_executor(None, self.agent.chat, full_prompt)
return HandoffResult(
success=True,
@@ -1711,12 +1558,11 @@ class TypedHandoff(Handoff, Generic[T]):
handoff_depth=_get_handoff_depth(),
)
finally:
if pushed:
_pop_handoff()
_pop_handoff()
try:
if semaphore is not None:
async with semaphore:
if self.config.max_concurrent > 0 and Handoff._semaphore:
async with Handoff._semaphore:
if self.config.timeout_seconds > 0:
result = await asyncio.wait_for(
_execute(),
@@ -13,6 +13,7 @@ Usage::
"""
import asyncio
import logging
from praisonaiagents._logging import get_logger
import threading
import time
@@ -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
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.
@@ -84,10 +57,6 @@ class InterruptController:
_flag: threading.Event = field(default_factory=threading.Event, init=False, repr=False)
_reason: Optional[str] = field(default=None, init=False)
_active_turns: Set[int] = field(default_factory=set, init=False, repr=False)
_cancelled_turns: Set[int] = field(default_factory=set, init=False, repr=False)
_next_turn_id: int = field(default=0, init=False, repr=False)
_pending_turn_cancel: bool = field(default=False, init=False, repr=False)
_lock: threading.Lock = field(default_factory=threading.Lock, init=False, repr=False)
def request(self, reason: str = "user") -> None:
@@ -100,49 +69,12 @@ class InterruptController:
if not self._flag.is_set():
self._reason = reason
self._flag.set()
if self._active_turns:
self._cancelled_turns.update(self._active_turns)
else:
self._pending_turn_cancel = True
def _begin_turn(self) -> int:
"""Register an Agent turn and consume any request made while idle."""
with self._lock:
self._next_turn_id += 1
turn_id = self._next_turn_id
self._active_turns.add(turn_id)
if self._pending_turn_cancel:
self._cancelled_turns.add(turn_id)
self._pending_turn_cancel = False
return turn_id
def _turn_is_cancelled(self, turn_id: int) -> bool:
"""Return whether a registered turn was targeted by a request."""
with self._lock:
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.
"""
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."""
with self._lock:
self._reason = None
self._flag.clear()
self._pending_turn_cancel = False
self._cancelled_turns.clear()
def is_set(self) -> bool:
"""Check if cancellation has been requested.
@@ -162,16 +94,6 @@ 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.
@@ -1,88 +0,0 @@
"""Shared authorisation + bind guard for the ``launch()`` serving paths.
Both ``Agent.launch()`` (``agent/execution_mixin.py``) and
``PraisonAIAgents.launch()`` (``agents/agents.py``) expose a prompt-execution
HTTP endpoint. They must enforce identical request authorisation and must not
silently bind all interfaces without a token. Factoring the two helpers here
keeps that policy in one place so the two launch paths cannot drift apart.
Stdlib only — no heavy imports, no new public params.
"""
from __future__ import annotations
import os
import secrets as _secrets
from typing import Optional
__all__ = [
"launch_auth_token",
"authorise_launch_request",
"resolve_launch_host",
]
# Hosts that are safe to serve keyless on: loopback only.
_LOOPBACK_HOSTS = frozenset({"127.0.0.1", "::1", "localhost"})
# One auto-generated token per process, reused across launches so a later
# non-loopback launch cannot mint a fresh token and lock out an endpoint that
# is already serving with the previously generated one.
_GENERATED_TOKEN: Optional[str] = None
def launch_auth_token() -> Optional[str]:
"""Return the configured launch bearer token, if any."""
return os.environ.get("PRAISONAI_LAUNCH_AUTH_TOKEN")
def authorise_launch_request(request) -> bool:
"""Return True if the request carries the configured bearer token.
When no token is configured this returns True (local-dev flow preserved).
Accepts either ``Authorization: Bearer <token>`` or ``X-Auth-Token``.
"""
token = launch_auth_token()
if not token:
return True
auth = request.headers.get("Authorization", "")
if auth.startswith("Bearer ") and _secrets.compare_digest(auth[7:], token):
return True
supplied = request.headers.get("X-Auth-Token", "")
return bool(supplied) and _secrets.compare_digest(supplied, token)
def _is_loopback(host: str) -> bool:
return host in _LOOPBACK_HOSTS
def resolve_launch_host(host: str) -> str:
"""Fail-closed bind guard, mirroring the ``serve``/jobs precedent.
* Token set → bind ``host`` unchanged (auth protects the endpoint).
* Token unset + loopback host → bind unchanged (local dev unchanged).
* Token unset + non-loopback host → auto-generate a token, export it via
``PRAISONAI_LAUNCH_AUTH_TOKEN`` so every route enforces it, and print it
once. This closes the unauthenticated-exposure hole without refusing to
start.
Returns the host to bind (unchanged; the guard acts on the token, not the
host, so an explicit ``0.0.0.0`` is still honoured — just never keyless).
A generated token is reused for the lifetime of the process: repeated
non-loopback launches share the one token rather than each minting a fresh
one, so a later launch cannot invalidate an already-running endpoint's
clients.
"""
if launch_auth_token() or _is_loopback(host):
return host
global _GENERATED_TOKEN
if _GENERATED_TOKEN is None:
_GENERATED_TOKEN = _secrets.token_urlsafe(32)
print(
f"🔐 launch() bound to non-loopback host {host!r} without "
f"PRAISONAI_LAUNCH_AUTH_TOKEN set. Generated a one-time bearer token "
f"(set PRAISONAI_LAUNCH_AUTH_TOKEN to override): {_GENERATED_TOKEN}"
)
os.environ["PRAISONAI_LAUNCH_AUTH_TOKEN"] = _GENERATED_TOKEN
return host
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