Metadata-Version: 2.4
Name: pooolify
Version: 0.1.0
Summary: pooolify: Code-centric Python framework for multi-agent LLM orchestration with FastAPI + SSE and PostgreSQL persistence
Project-URL: Homepage, https://github.com/Pooolingforest/pooolifyAI
Author: pooolify maintainers
License: MIT
Requires-Python: >=3.10
Requires-Dist: fastapi>=0.110
Requires-Dist: httpx>=0.27
Requires-Dist: openai>=1.40.0
Requires-Dist: psycopg[binary]>=3.2
Requires-Dist: pydantic>=2.6
Requires-Dist: python-dotenv>=1.0
Requires-Dist: uvicorn>=0.30
Description-Content-Type: text/markdown

pooolify — Code‑Centric Multi‑Agent AI Framework (Python)

Overview

- Purpose: Orchestrate multiple LLM‑powered agents to collaboratively solve complex tasks.
- Focus: Developer Experience (DX), extensibility, and installable Python package.
- Core: FastAPI + SSE, PostgreSQL persistence, code‑declared agents and tools, provider‑agnostic LLM layer with cost tracking.

Key Features

- Manager‑Agent driven orchestration with DAG planning and parallel execution (asyncio).
- Code‑declared Agents (`pydantic`) and Tools (Python classes) with a simple runtime.
- FastAPI endpoints with Server‑Sent Events for plan/route/thought summaries/tool traces.
- PostgreSQL persistence for sessions, messages, costs, plans, tool calls, and feedback.
- Limits per request (steps, depth, duration) configured in code.

Repository Layout

pooolify-project/
├─ pyproject.toml
├─ README.md
├─ pooolify/ # Framework core
│ ├─ **init**.py
│ ├─ config.py
│ ├─ api/
│ ├─ core/
│ ├─ agents/
│ ├─ tools/
│ ├─ llm/
│ └─ persistence/
├─ examples/
│ └─ 01_basic_chatbot/
│ ├─ main.py
│ ├─ my_agents.py
│ ├─ my_tools.py
│ ├─ .env
│ └─ prompts/
│ └─ my_agent.prompt
│ └─ 02_multi_agent/
│ ├─ main.py
│ ├─ agents.py
│ ├─ tools.py
│ ├─ data/kb.json
│ └─ prompts/
│ ├─ researcher.prompt
│ ├─ calculator.prompt
│ └─ writer.prompt
└─ tests/

Install (dev)

- Editable install to dogfood the framework while building examples.

  pip install -e .

Env setup

- Copy and adjust the environment file:

  cp .env.example .env

  # then edit .env as needed (API_TOKEN, DATABASE_URL, etc.)

Environment

- Use uv (recommended) or regular venv. Configure env via .env or real env vars:
  - APP_ENV=dev|staging|prod
  - DATABASE_URL=postgresql+psycopg://user:pass@host:5432/db
  - API_TOKEN=your_api_token
  - LLM_OPENAI_API_KEY=sk-...

Run the example

- Start example 01 (basic):

  uvicorn examples.01_basic_chatbot.main:app --reload

- Test health:

  curl http://localhost:8000/v1/healthz

- Stream chat (SSE):

  curl -H "Accept: text/event-stream" -H "Authorization: Bearer $API_TOKEN" \
   -N http://localhost:8000/v1/chat/stream -d '{"session_id":"demo","query":"안녕?"}'

- Start example 02 (multi-agent):

  uvicorn examples.02_multi_agent.main:app --reload

- Stream multi-agent (SSE):

  curl -H "Accept: text/event-stream" \
   -N http://localhost:8000/v1/chat/stream -d '{"session_id":"demo2","query":"SSE가 뭐야? 2+2는?"}'

Manager limits in code

- Set request limits when instantiating the core app:

  from pooolify.core import PooolifyApp
  from pooolify.core import ManagerLimits

  core = PooolifyApp(limits=ManagerLimits(max_steps=20, max_depth=4, max_duration_s=120))

  # register agents ...

FastAPI Endpoints

- POST /v1/chat/stream (SSE): main streaming interface.
- POST /v1/chat: non‑streaming response.
- POST /v1/sessions: create a session id.
- GET /v1/sessions/{id}/messages: public conversation messages.
- GET /v1/healthz, GET /v1/readyz: health endpoints.

Security

- Simple bearer token via `Authorization: Bearer <token>`; wire to `API_TOKEN`.

Persistence

- Tables are created on startup if missing (see pooolify/persistence/schema.py for DDL).

Notes

- Supported models are 'gpt-5' and 'gpt-5-high'. Gemini is temporarily unsupported.
- SSE Thought summaries are structured; raw chain‑of‑thought is never emitted.
