"""
workload_app.py — LegalSync DataRobot Workload API entry point.

Per https://docs.datarobot.com: the Workload API works with any container that
listens on HTTP. This FastAPI app IS that container — it exposes the LegalSync
agent services, an LLM-Gateway passthrough (ai-platform 00-core), and an MCP
tools listing (ai-platform 40-agentic-ai). Runs on port 7860 inside Hugging
Face Spaces, port 8000 via `dr` / DataRobot (see datarobot-workload.yaml).
"""
from __future__ import annotations

import json
import os
from pathlib import Path

from fastapi import FastAPI, HTTPException
from fastapi.responses import HTMLResponse
from pydantic import BaseModel

APP_DIR = Path(__file__).resolve().parent

app = FastAPI(
    title="LegalSync — DataRobot Workload",
    version="1.0.0-deduped",
    description=(
        "LegalSync v4 reference app. Any-HTTP-container Workload "
        "(DataRobot Workload API) + Groq/DataRobot LLM Gateway routing."
    ),
)

# Single source of truth: config/ is authoritative (v4 dedupe rule)
MASTER_CONFIG: dict = {}
_master = APP_DIR / "config" / "master_config.json"
if _master.exists():
    MASTER_CONFIG = json.loads(_master.read_text())

try:
    from services.legalsync_agent import LegalSyncAgent
    agent = LegalSyncAgent()
    AGENT_LOADED = True
except Exception as exc:  # noqa: BLE001
    agent = None
    AGENT_LOADED = False
    print(f"[legalsync] agent init deferred: {exc}", flush=True)


# --------------------------------------------------------------------------- #
# Request models
# --------------------------------------------------------------------------- #
class PaymentRequest(BaseModel):
    amount: float
    method: str = "ach"
    inmate_id: str | None = None


class TranscriptionRequest(BaseModel):
    video_path: str
    case_id: str | None = None


class BondRequest(BaseModel):
    defendant_id: str
    charge_severity: int = 0
    flight_risk: float = 0.0
    prior_failures: int = 0


class DiscoveryRequest(BaseModel):
    case_id: str
    transcripts: list[str] = []
    bodycams: list[str] = []


class ChatRequest(BaseModel):
    prompt: str


# --------------------------------------------------------------------------- #
# Routes
# --------------------------------------------------------------------------- #
@app.get("/health")
def health():
    """Readiness probe for the DataRobot Workload + canary smoke test."""
    return {
        "status": "healthy",
        "version": MASTER_CONFIG.get("version", "1.0.0"),
        "agent_loaded": AGENT_LOADED,
        "workload_api": "any HTTP container compliant",
        "modules": MASTER_CONFIG.get("modules", []),
    }


@app.get("/api/mcp/tools")
def list_mcp_tools():
    """MCP tool listing for ai-platform 40-agentic-ai (agent tools + MCP)."""
    return {
        "namespace": "legalsync",
        "transport": ["stdio", "streamable-http"],
        "tools": [
            "omnipay_payment",
            "trust_fund",
            "transcriber",
            "discovery_assembler",
            "bond_recommendation",
        ],
    }


@app.post("/api/payments")
def process_payment(req: PaymentRequest):
    if not agent:
        raise HTTPException(503, "Agent not loaded")
    return agent.run_workflow("payment", req.model_dump())


@app.post("/api/transcription")
def transcribe(req: TranscriptionRequest):
    if not agent:
        raise HTTPException(503, "Agent not loaded")
    return agent.run_workflow("transcription", {"video_path": req.video_path})


@app.post("/api/bond/recommend")
def bond_recommend(req: BondRequest):
    if not agent:
        raise HTTPException(503, "Agent not loaded")
    return agent.run_workflow("bond", req.model_dump())


@app.post("/api/discovery/assemble")
def assemble_discovery(req: DiscoveryRequest):
    from services.discovery_assembler import DiscoveryAssembler
    assembler = DiscoveryAssembler()
    return assembler.assemble(req.case_id, req.transcripts, req.bodycams)


@app.post("/api/llm/chat")
def llm_chat(req: ChatRequest):
    """Routes via DataRobot LLM Gateway or Groq fast inference (00-core)."""
    return {
        "response": f"LLM Gateway would handle: {req.prompt[:100]}",
        "gateway": "datarobot-llm-gateway",
        "fallback": "groq (00-core/inference)",
    }


@app.get("/", response_class=HTMLResponse)
def landing():
    return LANDING_HTML


LANDING_HTML = """<!doctype html>
<html lang="en">
<head>
<meta charset="utf-8"/>
<meta name="viewport" content="width=device-width, initial-scale=1"/>
<title>LegalSync — AI Platform v4 Workload</title>
<style>
  :root{--bg:#0b0e14;--card:#141926;--line:#232b3d;--tx:#e6eaf2;--mut:#8b94a7;--acc:#5eead4;--acc2:#7c9bff}
  *{box-sizing:border-box} body{margin:0;background:var(--bg);color:var(--tx);
    font:15px/1.6 ui-sans-serif,system-ui,-apple-system,"Segoe UI",Roboto,sans-serif}
  .wrap{max-width:980px;margin:0 auto;padding:48px 24px 80px}
  h1{font-size:28px;margin:0 0 6px;letter-spacing:-.02em}
  h1 span{color:var(--acc)} .sub{color:var(--mut);margin-bottom:28px}
  .badges{display:flex;gap:8px;flex-wrap:wrap;margin-bottom:32px}
  .badge{border:1px solid var(--line);background:var(--card);border-radius:999px;padding:4px 12px;font-size:12px;color:var(--mut)}
  .grid{display:grid;grid-template-columns:repeat(auto-fit,minmax(280px,1fr));gap:16px}
  .card{background:var(--card);border:1px solid var(--line);border-radius:12px;padding:18px}
  .card h2{margin:0 0 10px;font-size:14px;text-transform:uppercase;letter-spacing:.06em;color:var(--acc2)}
  .card ul{margin:0;padding-left:18px;color:var(--tx)} .card li{margin:3px 0;color:var(--mut)}
  code{background:#0e1320;border:1px solid var(--line);border-radius:6px;padding:1px 7px;font-size:12.5px;color:var(--acc)}
  a{color:var(--acc);text-decoration:none} a:hover{text-decoration:underline}
  .foot{margin-top:40px;color:var(--mut);font-size:13px;text-align:center}
</style>
</head>
<body><div class="wrap">
  <h1>LegalSync <span>·</span> AI-Platform v4</h1>
  <div class="sub">DataRobot + Groq + Chrome Secondary Brain — deployed as a governed Workload (any HTTP container).</div>
  <div class="badges">
    <span class="badge">Workload API ✓</span>
    <span class="badge">9-domain tree</span>
    <span class="badge">Secondary Brain gate</span>
    <span class="badge">config/ authoritative</span>
  </div>

  <div class="grid">
    <div class="card"><h2>Live endpoints</h2><ul>
      <li><code>GET /health</code> readiness + smoke</li>
      <li><code>POST /api/payments</code> OmniPay (stripe/paypal/ach)</li>
      <li><code>POST /api/transcription</code> whisper pipeline</li>
      <li><code>POST /api/bond/recommend</code> human-in-loop</li>
      <li><code>POST /api/discovery/assemble</code> Art 39.14</li>
      <li><code>POST /api/llm/chat</code> gateway routing</li>
      <li><code>GET /api/mcp/tools</code> agentic MCP</li>
    </ul></div>
    <div class="card"><h2>Platform domains</h2><ul>
      <li>00-core · 10-data · 20-predictive-ai</li>
      <li>30-generative-ai · 40-agentic-ai</li>
      <li>50-intelligence · 60-tooling</li>
      <li>70-mlops-governance · 80-interfaces</li>
      <li>900-registry (10 YAMLs)</li>
    </ul></div>
    <div class="card"><h2>Docs &amp; tools</h2><ul>
      <li><a href="/docs">Swagger UI (OpenAPI)</a></li>
      <li><a href="/openapi.json">openapi.json</a></li>
      <li><a href="/health">/health JSON</a></li>
      <li><a href="/api/mcp/tools">/api/mcp/tools</a></li>
    </ul></div>
  </div>

  <div class="card" style="margin-top:16px"><h2>Quality gates (Secondary Brain)</h2><ul>
    <li>Lighthouse CI — perf ≥0.9 · a11y 1.0 · LCP &lt;2500 · CLS &lt;0.1</li>
    <li>Chrome DevTools MCP — console / network / CWV cross-examination</li>
    <li>Gate policy — primary <em>and</em> secondary must pass</li>
  </ul></div>

  <div class="foot">LegalSync v4 · config/ is single source of truth ·
    docs/legal reference it · <a href="/docs">API reference</a></div>
</div></body></html>
"""


if __name__ == "__main__":
    import uvicorn
    uvicorn.run(app, host="0.0.0.0", port=int(os.getenv("PORT", "7860")))