200 lines
6.5 KiB
Python
200 lines
6.5 KiB
Python
# router.py
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import os
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import logging
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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 persona.identity import load_identity
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from ingest.intake_client import IntakeClient
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from context import collect_context, update_last_assistant_message
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# -----------------------------
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# Debug configuration
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# -----------------------------
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VERBOSE_DEBUG = os.getenv("VERBOSE_DEBUG", "false").lower() == "true"
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logger = logging.getLogger(__name__)
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if VERBOSE_DEBUG:
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logger.setLevel(logging.DEBUG)
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# Console handler
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console_handler = logging.StreamHandler()
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console_handler.setFormatter(logging.Formatter(
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'%(asctime)s [ROUTER] %(levelname)s: %(message)s',
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datefmt='%H:%M:%S'
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))
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logger.addHandler(console_handler)
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# File handler
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try:
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os.makedirs('/app/logs', exist_ok=True)
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file_handler = logging.FileHandler('/app/logs/cortex_verbose_debug.log', mode='a')
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file_handler.setFormatter(logging.Formatter(
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'%(asctime)s [ROUTER] %(levelname)s: %(message)s',
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datefmt='%Y-%m-%d %H:%M:%S'
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))
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logger.addHandler(file_handler)
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logger.debug("VERBOSE_DEBUG mode enabled for router.py - logging to file")
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except Exception as e:
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logger.debug(f"VERBOSE_DEBUG mode enabled for router.py - file logging failed: {e}")
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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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if VERBOSE_DEBUG:
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logger.debug(f"\n{'='*80}")
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logger.debug(f"[PIPELINE START] Session: {req.session_id}")
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logger.debug(f"[PIPELINE START] User prompt: {req.user_prompt[:200]}...")
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logger.debug(f"{'='*80}\n")
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# 0. Collect unified context from all sources
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if VERBOSE_DEBUG:
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logger.debug("[STAGE 0] Collecting unified context...")
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context_state = await collect_context(req.session_id, req.user_prompt)
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if VERBOSE_DEBUG:
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logger.debug(f"[STAGE 0] Context collected - {len(context_state.get('rag', []))} RAG results")
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# 0.5. Load identity block
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if VERBOSE_DEBUG:
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logger.debug("[STAGE 0.5] Loading identity block...")
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identity_block = load_identity(req.session_id)
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if VERBOSE_DEBUG:
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logger.debug(f"[STAGE 0.5] Identity loaded: {identity_block.get('name', 'Unknown')}")
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# 1. Extract Intake summary for reflection
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# Use L20 (Session Overview) as primary summary for reflection
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intake_summary = "(no context available)"
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if context_state.get("intake"):
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l20_summary = context_state["intake"].get("L20")
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if l20_summary and isinstance(l20_summary, dict):
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intake_summary = l20_summary.get("summary", "(no context available)")
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elif isinstance(l20_summary, str):
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intake_summary = l20_summary
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if VERBOSE_DEBUG:
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logger.debug(f"[STAGE 1] Intake summary extracted (L20): {intake_summary[:150]}...")
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# 2. Reflection
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if VERBOSE_DEBUG:
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logger.debug("[STAGE 2] Running reflection...")
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try:
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reflection = await reflect_notes(intake_summary, identity_block=identity_block)
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reflection_notes = reflection.get("notes", [])
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if VERBOSE_DEBUG:
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logger.debug(f"[STAGE 2] Reflection complete - {len(reflection_notes)} notes generated")
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for idx, note in enumerate(reflection_notes, 1):
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logger.debug(f" Note {idx}: {note}")
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except Exception as e:
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reflection_notes = []
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if VERBOSE_DEBUG:
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logger.debug(f"[STAGE 2] Reflection failed: {e}")
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# 3. First-pass reasoning draft
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if VERBOSE_DEBUG:
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logger.debug("[STAGE 3] Running reasoning (draft)...")
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draft = await reason_check(
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req.user_prompt,
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identity_block=identity_block,
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rag_block=context_state.get("rag", []),
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reflection_notes=reflection_notes,
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context=context_state
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)
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if VERBOSE_DEBUG:
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logger.debug(f"[STAGE 3] Draft answer ({len(draft)} chars):")
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logger.debug(f"--- DRAFT START ---\n{draft}\n--- DRAFT END ---")
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# 4. Refinement
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if VERBOSE_DEBUG:
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logger.debug("[STAGE 4] Running 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=identity_block,
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rag_block=context_state.get("rag", []),
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)
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final_neutral = result["final_output"]
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if VERBOSE_DEBUG:
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logger.debug(f"[STAGE 4] Refined answer ({len(final_neutral)} chars):")
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logger.debug(f"--- REFINED START ---\n{final_neutral}\n--- REFINED END ---")
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# 5. Persona layer
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if VERBOSE_DEBUG:
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logger.debug("[STAGE 5] Applying persona layer...")
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persona_answer = await speak(final_neutral)
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if VERBOSE_DEBUG:
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logger.debug(f"[STAGE 5] Persona answer ({len(persona_answer)} chars):")
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logger.debug(f"--- PERSONA START ---\n{persona_answer}\n--- PERSONA END ---")
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# 6. Update session state with assistant's response
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if VERBOSE_DEBUG:
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logger.debug("[STAGE 6] Updating session state...")
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update_last_assistant_message(req.session_id, persona_answer)
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if VERBOSE_DEBUG:
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logger.debug(f"\n{'='*80}")
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logger.debug(f"[PIPELINE COMPLETE] Session: {req.session_id}")
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logger.debug(f"[PIPELINE COMPLETE] Final answer length: {len(persona_answer)} chars")
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logger.debug(f"{'='*80}\n")
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# 7. 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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"context_summary": {
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"rag_results": len(context_state.get("rag", [])),
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"minutes_since_last": context_state.get("minutes_since_last_msg"),
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"message_count": context_state.get("message_count"),
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"mode": context_state.get("mode"),
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}
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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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