Cortex-Inara/cortex/routers/orchestrator.py

"""
Orchestrator router — POST /orchestrate, GET /orchestrate/{job_id}

Accepts a task description, runs it through the orchestrator engine
(Gemini tool loop → Claude response), and returns the result.

Designed to be triggered from:
  - The Cortex web UI (future "Agent mode" toggle)
  - Cron jobs:  curl -X POST http://localhost:8000/orchestrate -d '{"task":"..."}'
  - Webhooks:   Gitea, Aether events, etc.
"""

import asyncio
import logging
import uuid
from datetime import datetime, timezone

from fastapi import APIRouter
from pydantic import BaseModel

from auth_utils import get_user_gemini_key, get_user_role
from config import settings
from context_loader import load_context
from persona import set_context, validate as validate_persona
import model_registry
import orchestrator_engine
import openai_orchestrator

logger = logging.getLogger(__name__)
router = APIRouter(prefix="/orchestrate", tags=["orchestrator"])

# ---------------------------------------------------------------------------
# In-memory job store
# Jobs are keyed by UUID. For this phase, memory is fine — jobs are short-lived.
# ---------------------------------------------------------------------------

_jobs: dict[str, dict] = {}
_jobs_lock = asyncio.Lock()


# ---------------------------------------------------------------------------
# Request / response models
# ---------------------------------------------------------------------------

class OrchestrateRequest(BaseModel):
    task: str
    session_id: str | None = None       # include session history in context
    tier: int | None = None             # Inara context tier (default from settings)
    respond_with_claude: bool = True    # False = return Gemini summary only (faster, for cron)
    include_long: bool = True
    include_mid: bool = True
    include_short: bool = True
    user: str = "scott"
    persona: str = "inara"
    chat_role: str = "chat"             # role used for the final response (decoupled from tool-loop model)


class OrchestrateResponse(BaseModel):
    job_id: str
    status: str     # "queued" | "running" | "complete" | "error"


class JobStatusResponse(BaseModel):
    job_id: str
    status: str
    task: str
    created_at: str
    completed_at: str | None = None
    session_id: str | None = None
    response: str | None = None
    tool_calls: list[dict] | None = None
    backend: str | None = None
    gemini_summary: str | None = None
    error: str | None = None


# ---------------------------------------------------------------------------
# Endpoints
# ---------------------------------------------------------------------------

@router.post("", response_model=OrchestrateResponse)
async def orchestrate(req: OrchestrateRequest) -> OrchestrateResponse:
    """Submit a task to the orchestrator. Returns a job_id to poll."""
    try:
        user, persona = validate_persona(req.user, req.persona)
        set_context(user, persona)
    except ValueError as e:
        from fastapi import HTTPException
        raise HTTPException(status_code=400, detail=str(e))

    job_id = str(uuid.uuid4())
    now = datetime.now(timezone.utc).isoformat()

    job: dict = {
        "job_id": job_id,
        "status": "queued",
        "task": req.task,
        "created_at": now,
        "completed_at": None,
        "response": None,
        "tool_calls": None,
        "backend": None,
        "gemini_summary": None,
        "error": None,
    }

    async with _jobs_lock:
        _jobs[job_id] = job

    # Run in background — caller polls GET /orchestrate/{job_id}
    asyncio.create_task(_run_job(job_id, req, user))
    logger.info("Orchestrator job queued: %s — %.80s", job_id, req.task)
    return OrchestrateResponse(job_id=job_id, status="queued")


@router.get("/{job_id}", response_model=JobStatusResponse)
async def job_status(job_id: str) -> JobStatusResponse:
    """Poll the status of an orchestrator job."""
    async with _jobs_lock:
        job = _jobs.get(job_id)

    if job is None:
        from fastapi import HTTPException
        raise HTTPException(status_code=404, detail=f"Job {job_id} not found")

    return JobStatusResponse(**job)


@router.get("", response_model=list[JobStatusResponse])
async def list_jobs() -> list[JobStatusResponse]:
    """List all jobs (most recent first). Useful for debugging."""
    async with _jobs_lock:
        jobs = sorted(_jobs.values(), key=lambda j: j["created_at"], reverse=True)
    return [JobStatusResponse(**j) for j in jobs]


# ---------------------------------------------------------------------------
# Background runner
# ---------------------------------------------------------------------------

async def _run_job(job_id: str, req: OrchestrateRequest, user: str) -> None:
    """Execute the orchestration job and update the job store."""
    async with _jobs_lock:
        _jobs[job_id]["status"] = "running"

    try:
        from session_store import load as load_session, save as save_session, generate_session_id

        # Load Inara's system prompt (same as the chat router does)
        tier = req.tier or settings.default_tier
        system_prompt = load_context(
            tier,
            include_long=req.include_long,
            include_mid=req.include_mid,
            include_short=req.include_short,
        )

        # Load session history if a session_id was provided
        session_id = req.session_id or generate_session_id()
        history = load_session(session_id)
        session_messages = history or None

        # Choose engine based on the orchestrator role in the model registry
        orch_model = model_registry.get_model_for_role(user, "orchestrator")

        user_role = get_user_role(user)

        if orch_model and orch_model.get("type") == "local_openai":
            result = await openai_orchestrator.run(
                task=req.task,
                system_prompt=system_prompt,
                session_messages=session_messages,
                model_cfg=orch_model,
                respond_with_final=req.respond_with_claude,
                user_role=user_role,
            )
        else:
            # Use the API key embedded in the resolved model config (V2 registry with
            # account_id), then fall back to the per-user key from auth.json, then .env.
            gemini_key = (
                (orch_model.get("api_key") if orch_model else None)
                or get_user_gemini_key(user)
            )
            result = await orchestrator_engine.run(
                task=req.task,
                system_prompt=system_prompt,
                session_messages=session_messages,
                respond_with_claude=req.respond_with_claude,
                gemini_api_key=gemini_key,
                model_name=orch_model.get("model_name") if orch_model else None,
                response_role=req.chat_role,
                user_role=user_role,
            )

        # Save the turn to the session store so it survives a page refresh
        history.append({"role": "user", "content": req.task})
        history.append({"role": "assistant", "content": result.response})
        save_session(session_id, history)

        from session_logger import log_turn
        log_turn(session_id, req.task, result.response)

        now = datetime.now(timezone.utc).isoformat()
        async with _jobs_lock:
            _jobs[job_id].update({
                "status": "complete",
                "completed_at": now,
                "session_id": session_id,
                "response": result.response,
                "tool_calls": result.tool_calls,
                "backend": result.backend,
                "gemini_summary": result.gemini_summary,
            })
        logger.info("Orchestrator job complete: %s (%d tool calls)", job_id, len(result.tool_calls))

    except Exception as e:
        logger.exception("Orchestrator job failed: %s", job_id)
        now = datetime.now(timezone.utc).isoformat()
        async with _jobs_lock:
            _jobs[job_id].update({
                "status": "error",
                "completed_at": now,
                "error": str(e),
            })