87 lines
2.1 KiB
Python
87 lines
2.1 KiB
Python
# router.py
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from unittest import result
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from fastapi import APIRouter, HTTPException
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from pydantic import BaseModel
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from reasoning.reasoning import reason_check
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from reasoning.reflection import reflect_notes
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from reasoning.refine import refine_answer
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from persona.speak import speak
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from ingest.intake_client import IntakeClient
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# -----------------------------
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# Router (NOT FastAPI app)
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# -----------------------------
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cortex_router = APIRouter()
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# Initialize Intake client once
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intake_client = IntakeClient()
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# -----------------------------
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# Pydantic models
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# -----------------------------
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class ReasonRequest(BaseModel):
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session_id: str
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user_prompt: str
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temperature: float | None = None
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# -----------------------------
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# /reason endpoint
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# -----------------------------
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@cortex_router.post("/reason")
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async def run_reason(req: ReasonRequest):
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# 1. Pull context from Intake
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try:
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intake_summary = await intake_client.get_context(req.session_id)
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except Exception:
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intake_summary = "(no context available)"
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# 2. Reflection
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try:
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reflection = await reflect_notes(intake_summary, identity_block=None)
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reflection_notes = reflection.get("notes", [])
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except Exception:
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reflection_notes = []
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# 3. First-pass reasoning draft
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draft = await reason_check(
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req.user_prompt,
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identity_block=None,
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rag_block=None,
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reflection_notes=reflection_notes
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)
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# 4. Refinement
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result = await refine_answer(
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draft_output=draft,
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reflection_notes=reflection_notes,
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identity_block=None,
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rag_block=None,
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)
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final_neutral = result["final_output"]
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# 5. Persona layer
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persona_answer = await speak(final_neutral)
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# 6. Return full bundle
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return {
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"draft": draft,
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"neutral": final_neutral,
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"persona": persona_answer,
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"reflection": reflection_notes,
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"session_id": req.session_id,
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}
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# -----------------------------
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# Intake ingest passthrough
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# -----------------------------
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@cortex_router.post("/ingest")
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async def ingest_stub():
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return {"status": "ok"}
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