app/api/agentic.py

"""Agentic RICS inspection endpoints."""

from __future__ import annotations

import logging
from datetime import UTC, datetime

from fastapi import APIRouter, Depends, HTTPException, Request
from sqlalchemy import update
from sqlalchemy.ext.asyncio import AsyncSession

from app.api import rate_limit
from app.db.database import get_db
from app.db.models import Report, ReportStatus
from app.jobs.models import GenerationJob, JobType
from app.jobs.queue import dispatch_or_enqueue
from app.services.generation import mark_report_generation_failed, run_agentic_full_report_job

from app.agentic.runtime_status import is_openai_inspector_live
from app.agentic.tools import list_tool_specs

logger = logging.getLogger(__name__)
router = APIRouter()


@router.post(
    "/reports/{report_id}/agentic/generate",
    summary="Generate a full RICS-style report using an agentic pipeline",
)
async def agentic_generate_report(
    report_id: str,
    request: Request,
    body: dict,
    db: AsyncSession = Depends(get_db),
    _rl: None = Depends(rate_limit.check_generate),
) -> dict:
    tenant_id: str = request.state.tenant_id
    report = await db.get(Report, report_id)
    if report is None or report.tenant_id != tenant_id:
        raise HTTPException(status_code=404, detail="Report not found")

    bullets_by_section = body.get("bullets_by_section") or {}
    if not isinstance(bullets_by_section, dict) or not bullets_by_section:
        raise HTTPException(status_code=422, detail="bullets_by_section must be a non-empty object")

    ai_percent = body.get("ai_percent", 50)
    retrieval_level = body.get("retrieval_level", "paragraph")
    reference_document_ids = body.get("reference_document_ids") or []
    similarity_scan = bool(body.get("similarity_scan", False))
    peer_sections = body.get("peer_sections") if isinstance(body.get("peer_sections"), dict) else {}
    sim_excl = body.get("similarity_exclude_document_ids")
    similarity_exclude_document_ids = (
        [str(x) for x in sim_excl] if isinstance(sim_excl, list) else []
    )
    interference_level = body.get("interference_level")
    il_arg = str(interference_level).strip() if interference_level is not None else None

    try:
        ai_percent_i = int(ai_percent)
    except Exception:  # noqa: BLE001
        ai_percent_i = 50
    ai_percent_i = max(0, min(100, ai_percent_i))

    bullets_map = {
        str(k): list(v) for k, v in bullets_by_section.items() if isinstance(v, list)
    }

    cas_result = await db.execute(
        update(Report)
        .where(
            Report.id == report_id,
            Report.tenant_id == tenant_id,
            Report.status != ReportStatus.generating,
        )
        .values(
            status=ReportStatus.generating,
            generation_started_at=datetime.now(UTC),
            generation_section_total=len(bullets_map) if bullets_map else None,
        )
    )
    if cas_result.rowcount == 0:
        raise HTTPException(
            status_code=409,
            detail="A generation task is already running for this report.",
        )
    await db.commit()
    ref_ids = (
        [str(x) for x in reference_document_ids]
        if isinstance(reference_document_ids, list)
        else None
    )
    peer_map = {str(k): str(v) for k, v in (peer_sections or {}).items()}

    agentic_job = GenerationJob(
        job_type=JobType.agentic_full,
        report_id=report_id,
        tenant_id=tenant_id,
        payload={
            "bullets_by_section": bullets_map,
            "ai_percent": ai_percent_i,
            "retrieval_level": str(retrieval_level),
            "reference_document_ids": ref_ids,
            "similarity_scan": similarity_scan,
            "peer_sections": peer_map,
            "similarity_exclude_document_ids": similarity_exclude_document_ids or None,
            "interference_level": il_arg,
        },
    )

    async def _run_agentic_task() -> None:
        try:
            await run_agentic_full_report_job(
                report_id,
                tenant_id,
                bullets_by_section=bullets_map,
                ai_percent=ai_percent_i,
                retrieval_level=str(retrieval_level),
                reference_document_ids=ref_ids,
                similarity_scan=similarity_scan,
                peer_sections=peer_map,
                similarity_exclude_document_ids=similarity_exclude_document_ids or None,
                interference_level=il_arg,
            )
        except Exception as exc:  # noqa: BLE001
            logger.exception("Agentic background task failed report=%s", report_id)
            await mark_report_generation_failed(report_id, tenant_id, str(exc))

    queue_mode = await dispatch_or_enqueue(job=agentic_job, inline_factory=_run_agentic_task)

    inspector_mode = "openai_tool_agent" if is_openai_inspector_live() else "legacy_pipeline"
    queue_hint = " (Redis worker)" if queue_mode == "redis" else ""
    return {
        "report_id": report_id,
        "status": "generating",
        "message": (
            f"Agentic generation queued{queue_hint}. "
            f"Poll GET /reports/{report_id}/status or "
            f"GET /reports/{report_id}/sections for results."
        ),
        "inspector_mode": inspector_mode,
        "ai_percent": ai_percent_i,
        "retrieval_level": str(retrieval_level),
        "agent_tools": [s.name for s in list_tool_specs()],
    }