797f02c74d
Sets up the full backend foundation for CouncilOS:
- CouncilState TypedDict with all required fields and LangGraph reducers
- Three agent nodes: master_agent (drafts), critic_agent (scores + routes),
writer_agent (final polish)
- LangGraph graph with cyclic rework loop: Master → Critic → (score < 8:
back to Master | score ≥ 8: Writer → END)
- Safety valve: MAX_ITERATIONS=5 prevents infinite loops
- FastAPI app with REST endpoints (POST /api/councils/run, GET /api/councils/run/{id})
and WebSocket endpoint (/ws/council/{run_id}) for real-time agent status events
- In-memory RunStore for Phase 1 (PostgreSQL-backed in Phase 3)
- pytest test suite: state, routing logic, critic parser, agent nodes, API endpoints
- .env.example, .gitignore, docker-compose.yml, Dockerfile
https://claude.ai/code/session_01RfMpt3TbMjZEtK3CAyP5iQ
63 lines
1.9 KiB
Python
63 lines
1.9 KiB
Python
"""
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Writer Agent Node — final polishing of an approved draft.
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This agent receives a critic-approved draft and produces the final,
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publication-ready version with polished formatting and language.
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"""
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import os
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from langchain_anthropic import ChatAnthropic
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from langchain_core.messages import HumanMessage, SystemMessage
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from state import CouncilState
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_SYSTEM_PROMPT = """You are the Writer AI in a council of expert AIs.
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You receive a draft that has already been approved for quality by the Critic AI.
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Your job is to give it a final professional polish:
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- Improve sentence flow and readability
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- Ensure consistent formatting (headers, bullet points, paragraphs)
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- Fix any grammatical or stylistic issues
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- Do NOT change the factual content or overall structure
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- Preserve all key information from the draft
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Return only the polished document — no meta-commentary."""
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def writer_agent_node(state: CouncilState) -> dict:
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"""
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LangGraph node function for the Writer Agent.
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Receives the approved current_draft and returns a polished final version.
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Args:
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state: The current CouncilState.
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Returns:
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A dict with the final polished current_draft and updated messages.
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"""
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llm = ChatAnthropic(
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model="claude-3-5-sonnet-20241022",
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api_key=os.environ.get("ANTHROPIC_API_KEY"),
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temperature=0.4,
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max_tokens=4096,
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)
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system_msg = SystemMessage(content=_SYSTEM_PROMPT)
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user_msg = HumanMessage(
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content=(
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f"Please give a final professional polish to this approved document "
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f"on the topic '{state['input_topic']}':\n\n"
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f"{state['current_draft']}"
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)
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)
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response = llm.invoke([system_msg, user_msg])
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return {
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"current_draft": response.content,
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"messages": [system_msg, user_msg, response],
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"active_node": "writer_agent",
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"route_decision": "done",
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}
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