"""HearthNet — Hugging Face Space entry point.

This Space runs a **real** HearthNet node using HuggingFace Transformers as the
LLM backend. All 8 tabs are live:

  Ask        — LLM + RAG queries routed via capability bus
  Chat       — Event-sourced direct messages between nodes
  Mesh       — Live topology graph of discovered peers
  Marketplace — Community offers / requests / emergency posts
  Files      — BLAKE3 content-addressed blob store
  Emergency  — Offline-mode probe and connectivity status
  Settings   — Node identity, peer list, QR invite, RAG ingest

Difference between this Space and a local install
──────────────────────────────────────────────────
  HF Space     → single node, no real peer mesh, SmolLM2-135M for LLM
  Local node   → full peer mesh, any LLM backend (Ollama / llama.cpp / HF),
                 file sharing, multi-node chat, hardware acceleration

Quick start (local, full features):
  git clone https://huggingface.co/spaces/build-small-hackathon/HearthNet
  cd HearthNet
  pip install -e .
  python -m hearthnet.cli run
  # Open http://localhost:7860 in your browser

See docs/HOWTO.md for Raspberry Pi, Docker, and multi-node mesh setup.
"""

from __future__ import annotations

import contextlib
import os

# ─────────────────────────────────────────────────────────────────────────────
# Optional HF Spaces GPU decorator
# ─────────────────────────────────────────────────────────────────────────────
try:
    import spaces as _spaces  # type: ignore[import]

    HF_SPACES = True
except ImportError:
    HF_SPACES = False

# ─────────────────────────────────────────────────────────────────────────────
# Bootstrap a real HearthNet node
# ─────────────────────────────────────────────────────────────────────────────

MODEL_ID = os.getenv("MODEL_ID", "HuggingFaceTB/SmolLM2-135M-Instruct")
MODEL_REVISION = os.getenv("MODEL_REVISION", "12fd25f77366fa6b3b4b768ec3050bf629380bac")

SEED_CORPUS = [
    {
        "id": "water.001",
        "title": "Water Safety",
        "text": (
            "If the mains supply is disrupted, use stored clean water first. "
            "Rainwater should be filtered through clean cloth, brought to a rolling "
            "boil for at least one minute, and stored in a clean covered container. "
            "Adult daily minimum: 3 litres for drinking and sanitation."
        ),
    },
    {
        "id": "power.001",
        "title": "Power Outage",
        "text": (
            "Keep refrigerators closed to preserve food up to 4 hours. "
            "Disconnect sensitive electronics. Reserve battery banks for communication. "
            "Share verified charging points through the local marketplace. "
            "Candles are a fire risk — use battery or wind-up torches."
        ),
    },
    {
        "id": "mesh.001",
        "title": "HearthNet Routing",
        "text": (
            "A HearthNet UI sends requests to a capability bus. The bus scores local "
            "capabilities higher than remote ones and routes to the best available "
            "provider. If a node is quarantined the bus fails over automatically. "
            "RAG corpus routing uses the 'corpus' parameter to match the right node."
        ),
    },
    {
        "id": "firstaid.001",
        "title": "First Aid — Bleeding",
        "text": (
            "Apply direct firm pressure to the wound with a clean cloth. "
            "Maintain pressure for at least 10 minutes. Do not remove the cloth — "
            "add more on top if it soaks through. Elevate the limb above heart level "
            "if possible. Seek emergency care if bleeding is severe or arterial."
        ),
    },
    {
        "id": "firstaid.002",
        "title": "CPR Basics",
        "text": (
            "If a person is unresponsive and not breathing normally: call emergency services, "
            "then give 30 chest compressions (hard, fast, centre of chest) followed by "
            "2 rescue breaths. Continue the 30:2 cycle until help arrives or the person "
            "recovers. Hands-only CPR (compressions without rescue breaths) is acceptable "
            "for untrained bystanders."
        ),
    },
    {
        "id": "setup.001",
        "title": "Node Setup — Quick Start",
        "text": (
            "Install HearthNet with: pip install hearthnet. "
            "Run: python -m hearthnet.cli run "
            "to start a node. Open http://localhost:7860 in your browser. "
            "Other devices on the same LAN discover your node automatically via mDNS. "
            "Use the Settings tab to generate an invite QR for devices on other networks."
        ),
    },
    {
        "id": "setup.002",
        "title": "Node Setup — Specialized Nodes",
        "text": (
            "Register only the capabilities your hardware supports. "
            "An OCR Raspberry Pi: register OcrService. "
            "A medical knowledge node: register RagService with a medical corpus. "
            "A thin client (phone): register no services — all bus calls route to peers. "
            "The bus auto-discovers and routes to the best provider in the mesh."
        ),
    },
    {
        "id": "emergency.001",
        "title": "Emergency Communication Plan",
        "text": (
            "Before a disaster: exchange node IDs with neighbours. "
            "During internet outage: HearthNet switches to offline mode automatically. "
            "All routing stays local. Use the mesh to share offers and requests. "
            "For emergency alerts, post to the Marketplace with category=emergency. "
            "Battery-powered device with HearthNet can serve the whole neighbourhood."
        ),
    },
    {
        "id": "food.001",
        "title": "Emergency Food Safety",
        "text": (
            "In a power outage, refrigerated food is safe for up to 4 hours. "
            "Frozen food stays safe for 24-48 hours if the freezer stays closed. "
            "Discard meat, poultry, seafood, dairy, or cooked food left above 4°C "
            "for more than 2 hours. When in doubt, throw it out."
        ),
    },
    {
        "id": "shelter.001",
        "title": "Shelter in Place",
        "text": (
            "During chemical or biological hazards, stay indoors. "
            "Close all windows and doors. Turn off HVAC. "
            "Seal gaps with wet towels or tape. "
            "Monitor emergency broadcasts on battery radio. "
            "Do not leave until authorities give the all-clear."
        ),
    },
]


def _build_node():
    """Bootstrap the HearthNet node for this Space.

    Uses HfLocalBackend (SmolLM2-135M) so inference works without Ollama.
    Falls back to _UnavailableBackend if transformers is not installed.
    """
    import hashlib
    import os
    import socket

    from hearthnet.node import HearthNode
    from hearthnet.services.chat.service import ChatService
    from hearthnet.services.files.service import FileService
    from hearthnet.services.llm.backends.hf_local import HfLocalBackend
    from hearthnet.services.llm.service import LlmService
    from hearthnet.services.marketplace.service import MarketplaceService

    # Generate a stable node_id from the HF Space hostname (so it doesn't change on restart).
    # Use SPACE_HOST env var (set only on HF Spaces) to differentiate: local nodes get
    # "local-*" prefix so they never collide with live "hf-space-*" peers in the relay.
    _space_host = os.getenv("SPACE_HOST", "")
    _host = _space_host or socket.gethostname()
    _suffix = hashlib.sha256(_host.encode()).hexdigest()[:8]
    if _space_host:
        _node_id = f"hf-space-{_suffix}"
        _display = os.getenv("SPACE_TITLE", f"HearthNet Space ({_suffix})")
    else:
        _node_id = f"local-{_suffix}"
        _display = os.getenv("SPACE_TITLE", f"HearthNet Local ({_suffix})")

    node = HearthNode(
        node_id=_node_id,
        display_name=_display,
        community_id="ed25519:hf-space-community",
    )

    # LLM — HF Transformers backend (SmolLM2 by default)
    try:
        backend = HfLocalBackend(model=MODEL_ID)
        # On ZeroGPU Spaces, patch the backend to use the @spaces.GPU wrapper so
        # GPU memory is properly allocated per inference call.
        if HF_SPACES:
            import asyncio
            import time as _time

            from hearthnet.services.llm.backends.base import ChatResult
            from hearthnet.services.llm.backends.hf_local import _trim_generated

            @_spaces.GPU(duration=120)
            def _gpu_pipeline_call(
                pipeline, prompt: str, max_new_tokens: int, temperature: float
            ) -> list:
                """GPU-wrapped pipeline call. ZeroGPU allocates GPU for this function."""
                return pipeline(
                    prompt,
                    max_new_tokens=max_new_tokens,
                    temperature=temperature,
                    do_sample=True,
                    return_full_text=False,
                )

            # Store the GPU wrapper on the backend so it can be replaced without
            # changing the public API.
            backend._gpu_pipeline_call = _gpu_pipeline_call  # type: ignore[attr-defined]

            async def _patched_chat(
                self,
                messages: list[dict],
                *,
                model: str = "",
                stream: bool = False,
                temperature: float = 0.7,
                max_tokens: int = 256,
                **kwargs,
            ):
                if self._pipeline is None:
                    await self.warm()
                if self._pipeline is None:
                    raise RuntimeError("HF model not loaded")
                t0 = _time.monotonic()
                prompt = self._build_prompt(messages)
                loop = asyncio.get_running_loop()
                result = await loop.run_in_executor(
                    None,
                    lambda: self._gpu_pipeline_call(
                        self._pipeline, prompt, max_tokens, temperature
                    ),
                )
                raw = result[0]["generated_text"] if result else ""
                text = _trim_generated(raw)
                ms = int((_time.monotonic() - t0) * 1000)
                return ChatResult(
                    text=text,
                    tokens_in=len(prompt.split()),
                    tokens_out=len(text.split()),
                    model=self._model_name,
                    ms=ms,
                )

            HfLocalBackend.chat = _patched_chat  # type: ignore[method-assign]

        backends: list = [backend]
        # ── Sponsor cloud backends (opt-in via env) ───────────────────────
        # NVIDIA Nemotron (prize track) — cloud NIM, no local availability check.
        if os.getenv("NVIDIA_API_KEY"):
            try:
                from hearthnet.services.llm.backends.nemotron import NemotronBackend

                backends.append(NemotronBackend(api_key_env="NVIDIA_API_KEY"))
            except Exception:
                pass
        # Modal serverless GPU (prize track).
        if os.getenv("MODAL_ENDPOINT"):
            try:
                from hearthnet.services.llm.backends.modal_backend import ModalBackend

                modal_b = ModalBackend()
                if modal_b.is_available():
                    backends.append(modal_b)
            except Exception:
                pass
        # MiniCPM local server (OpenBMB prize track).
        # MINICPM_URL          → OpenAI-compatible vLLM/SGLang/llama.cpp endpoint
        # MINICPM_MODELS       → comma-separated model ids to advertise (multi-model
        #                        serving from one server). Omit → full MiniCPM catalogue.
        # MINICPM_LIGHTWEIGHT  → "1" to also advertise Pi-friendly small models.
        _minicpm_url = os.getenv("MINICPM_URL")
        if _minicpm_url:
            try:
                from hearthnet.services.llm.backends.openbmb import OpenBmbBackend

                _models_env = os.getenv("MINICPM_MODELS", "")
                _models = [m.strip() for m in _models_env.split(",") if m.strip()] or None
                _lightweight = os.getenv("MINICPM_LIGHTWEIGHT", "") in ("1", "true", "yes")
                minicpm = OpenBmbBackend(
                    base_url=_minicpm_url,
                    models=_models,
                    include_lightweight=_lightweight,
                )
                if minicpm.is_available():
                    backends.append(minicpm)
            except Exception:
                pass

        llm = LlmService(backends=backends)
    except Exception:
        llm = LlmService()  # _UnavailableBackend — shows clear error

    node.bus.register_service(llm)

    # ── Durable event log (ZeroGPU-safe; no mDNS/transport on a single Space) ──
    event_log = None
    try:
        import tempfile
        from pathlib import Path

        from hearthnet.events import EventLog

        _data_dir = Path(os.getenv("HEARTHNET_DATA_DIR", tempfile.gettempdir())) / "hearthnet-space"
        _data_dir.mkdir(parents=True, exist_ok=True)
        event_log = EventLog(_data_dir / "events.db", node.community_id, node.node_id)
        node._event_log = event_log
    except Exception:
        event_log = None

    # ── Blob store for content-addressed RAG documents ────────────────────
    blob_store = None
    try:
        import tempfile
        from pathlib import Path

        from hearthnet.blobs.store import BlobStore

        blob_store = BlobStore(
            Path(os.getenv("HEARTHNET_DATA_DIR", tempfile.gettempdir()))
            / "hearthnet-space"
            / "blobs"
        )
    except Exception:
        blob_store = None

    # ── Real semantic RAG (replaces the in-memory demo corpus) ────────────
    from hearthnet.bus.capability import RouteRequest
    from hearthnet.services.rag.federated import FederatedRagService
    from hearthnet.services.rag.service import RagService

    # Register the embedding backend first so rag.query routes through embed.text.
    node.install_extended_services(research=True)

    import tempfile

    _corpora_dir = (
        Path(os.getenv("HEARTHNET_DATA_DIR", tempfile.gettempdir()))
        / "hearthnet-space"
        / "corpora"
    )
    rag = RagService(
        corpus="community",
        corpora_dir=_corpora_dir,
        bus=node.bus,
        event_log=event_log,
        blob_store=blob_store,
    )
    node.bus.register_service(rag)
    node.bus.register_service(FederatedRagService(node.bus, corpus="community"))

    # Seed the corpus through the real ingest path (content-addressed + logged).
    async def _seed_corpus() -> None:
        import pathlib

        # 1. Fixed emergency seed documents (water, first aid, CPR, etc.)
        for doc in SEED_CORPUS:
            with contextlib.suppress(Exception):
                await rag.handle_ingest(
                    RouteRequest(
                        capability="rag.ingest",
                        version_req=(1, 0),
                        body={
                            "input": {
                                "corpus": "community",
                                "documents": [
                                    {
                                        "id": doc["id"],
                                        "title": doc["title"],
                                        "text": doc["text"],
                                    }
                                ],
                            }
                        },
                        caller=node.node_id,
                        trace_id="seed",
                        deadline_ms=0,
                    )
                )

        # 2. Ingest all .md / .txt files from docs/ (main), docs/guides/, assets/initial_docs/.
        # Files are content-addressed (BLAKE3), so re-ingesting the same file is a no-op.
        _app_root = pathlib.Path(__file__).parent
        _doc_dirs = [
            _app_root / "docs",  # Main docs: CAPABILITY_CONTRACT, GLOSSARY, M01-M13, X01-X04, etc.
            _app_root / "docs" / "guides",
            _app_root / "assets" / "initial_docs",
        ]
        _text_suffixes = {".md", ".txt", ".rst"}
        for _doc_dir in _doc_dirs:
            if not _doc_dir.exists():
                continue
            for _doc_file in sorted(_doc_dir.rglob("*")):
                if _doc_file.suffix.lower() not in _text_suffixes:
                    continue
                with contextlib.suppress(Exception):
                    _text = _doc_file.read_text(encoding="utf-8", errors="replace")
                    if len(_text.strip()) < 80:
                        continue  # skip near-empty or placeholder files
                    _title = _doc_file.stem.replace("-", " ").replace("_", " ").title()
                    _doc_id = f"file:{_doc_file.relative_to(_app_root).as_posix()}"
                    await rag.handle_ingest(
                        RouteRequest(
                            capability="rag.ingest",
                            version_req=(1, 0),
                            body={
                                "input": {
                                    "text": _text,
                                    "title": _title,
                                    "doc_cid": _doc_id,
                                }
                            },
                            caller=node.node_id,
                            trace_id="seed-docs",
                            deadline_ms=0,
                        )
                    )

    # Run seed corpus in a dedicated thread with its own event loop to avoid
    # conflicts with any loop already running (e.g. Gradio's internal loop).
    import asyncio
    import threading

    def _seed_in_thread() -> None:
        loop = asyncio.new_event_loop()
        asyncio.set_event_loop(loop)
        try:
            loop.run_until_complete(_seed_corpus())
        except Exception:
            pass
        finally:
            loop.close()

    _seed_thread = threading.Thread(target=_seed_in_thread, daemon=True, name="hearthnet-seed")
    _seed_thread.start()
    _seed_thread.join(timeout=60)  # wait up to 60 s; don't block Space startup indefinitely

    # Register this node's LLM model as an expert in the MoE registry so
    # route_expert tool calls return meaningful results instead of an empty list.
    try:
        _moe_tags = list({
            doc.get("id", "").split(".")[0]
            for doc in SEED_CORPUS
            if doc.get("id")
        } | {"emergency", "mesh", "community"})
        loop_moe = asyncio.new_event_loop()
        loop_moe.run_until_complete(
            node.bus.call(
                "moe.register",
                (1, 0),
                {
                    "input": {
                        "expert_id": f"model:{MODEL_ID}",
                        "expert_type": "model",
                        "topic_tags": _moe_tags,
                        "confidence_score": 0.6,
                        "community_id": node.community_id,
                        "name": MODEL_ID.split("/")[-1],
                        "ttl_seconds": 0,
                    }
                },
            )
        )
        loop_moe.close()
    except Exception:
        pass

    # Marketplace, Chat, Files — now durably event-sourced where supported.
    node.bus.register_service(MarketplaceService(event_log=event_log, node_id=node.node_id))
    node.bus.register_service(ChatService(node.node_id, event_log=event_log, bus=node.bus))
    node.bus.register_service(FileService())

    return node


# Build node and Gradio app at import time (HF Spaces requires module-level `demo`)
_node = _build_node()

# ── Local-only: start mDNS peer discovery + HTTP bus transport ────────────────
# On HF Space (SPACE_HOST set): port 7080 is not exposed to the internet and mDNS
# doesn't cross network boundaries — the relay hub handles internet peering instead.
# Locally: node.start() activates zero-config LAN discovery and makes this node's
# bus callable by other nodes over HTTP so RAG, chat, and LLM route across devices.
if not os.getenv("SPACE_HOST"):
    import asyncio as _asyncio
    import threading as _threading

    def _run_local_networking() -> None:
        _loop = _asyncio.new_event_loop()
        _asyncio.set_event_loop(_loop)
        try:
            # node._event_log is already set by _build_node(); start() reuses it
            # (see the "already set" guard added to node.start()).
            _loop.run_until_complete(_node.start(port=7080))
            _loop.run_forever()
        except Exception as _exc:
            print(f"[hearthnet] local networking start failed: {_exc}")

    _threading.Thread(
        target=_run_local_networking, daemon=True, name="hearthnet-local-node"
    ).start()

# Relay hub: pull-based mailbox router so NAT-bound nodes mesh all-to-all through
# this public Space (see hearthnet/transport/relay_hub.py). Members poll their
# mailbox over HTTPS; the Space never needs to reach back into a home network.
from hearthnet.transport.relay_hub import RelayHub as _RelayHub  # noqa: E402
from hearthnet.transport.relay_hub import mount_relay_endpoints as _mount_relay_endpoints  # noqa: E402

import tempfile as _tempfile
from pathlib import Path as _Path2

_relay_db_path = (
    _Path2(os.getenv("HEARTHNET_DATA_DIR", _tempfile.gettempdir()))
    / "hearthnet-space"
    / "relay.db"
)
_relay_db_path.parent.mkdir(parents=True, exist_ok=True)
_relay_hub = _RelayHub(db_path=_relay_db_path)

from hearthnet.ui.app import build_ui as _build_ui  # noqa: E402

_ui = _build_ui(
    bus=_node.bus,
    state_bus=_node.state_bus,
    node=_node,
    display_name=_node.display_name,
    node_id=_node.node_id,
    community_id=_node.community_id,
)

demo = _ui.build()

# ── Serve webagent at /webagent/ ──────────────────────────────────────────────
# HF Space enables Gradio SSR mode (GRADIO_SSR_MODE=true), where a Node.js layer
# intercepts ALL requests before Python/FastAPI sees them, making StaticFiles
# mounts invisible. Fix: force SSR off so Python handles all requests directly.
from pathlib import Path as _Path

import gradio as _gr

_webagent_dir = _Path(__file__).parent / "webagent"

# 1) Override the env var that launch() reads when ssr_mode param is None
os.environ["GRADIO_SSR_MODE"] = "false"

# 2) Also patch _resolve_ssr_mode in case HF passes ssr_mode=True explicitly
_gr.Blocks._resolve_ssr_mode = lambda self, ssr_mode=None, **kw: False


def _mount_bus_endpoints(app) -> None:
    """Expose the node's capability bus on the Space's public port.

    On HF Spaces only the Gradio port is reachable from the internet — the
    node's internal HttpServer (port 7080) is not. Mounting the bus RPC
    endpoints directly into the Gradio FastAPI app lets a remote/local node
    peer with this Space via ``discovery.peer.add`` and route real
    ``llm.chat`` / ``rag.query`` / ``moe.*`` calls to it over HTTPS.
    """
    try:
        from fastapi import Body
        from fastapi.responses import JSONResponse
    except Exception as exc:  # pragma: no cover
        print(f"[hearthnet] bus endpoint mount skipped: {exc}")
        return

    if any(getattr(r, "path", "") == "/bus/v1/call" for r in app.routes):
        return

    def _parse_version(v) -> tuple[int, int]:
        parts = str(v).split(".")
        if len(parts) < 2:
            parts.append("0")
        return (int(parts[0]), int(parts[1]))

    @app.get("/manifest")
    async def _hn_manifest():
        return JSONResponse(_node.manifest().as_dict())

    @app.get("/health")
    async def _hn_health():
        return JSONResponse({"status": "ok", "node_id": _node.node_id})

    @app.get("/bus/v1/capabilities")
    async def _hn_capabilities():
        return JSONResponse([e.descriptor.name for e in _node.bus.registry.all_local()])

    @app.post("/bus/v1/call")
    async def _hn_bus_call(payload: dict = Body(...)):
        capability = payload.get("capability")
        if not capability:
            return JSONResponse(
                {"error": "bad_request", "message": "capability required"}, status_code=400
            )
        version = _parse_version(payload.get("version", "1.0"))
        call_body = {
            "params": payload.get("params", {}),
            "input": payload.get("input", {}),
        }
        try:
            result = await _node.bus.call(capability, version, call_body)
            return JSONResponse(result)
        except Exception as exc:
            code = getattr(exc, "code", "call_error")
            return JSONResponse({"error": code, "message": str(exc)}, status_code=500)

    # New routes are appended last; move them ahead of Gradio's SPA catch-all.
    for _path in ("/bus/v1/call", "/bus/v1/capabilities", "/manifest", "/health"):
        for _i in range(len(app.routes) - 1, -1, -1):
            if getattr(app.routes[_i], "path", "") == _path:
                app.routes.insert(0, app.routes.pop(_i))
                break


# 3) Patch App.create_app to inject the StaticFiles mount after Gradio routes
if _webagent_dir.exists():
    try:
        import gradio.routes as _gr_routes
        from fastapi.staticfiles import StaticFiles as _SF

        _orig_create_app = _gr_routes.App.__dict__["create_app"].__func__

        def _patched_create_app(blocks, app=None, **kwargs):
            result = _orig_create_app(blocks, app=app, **kwargs)
            try:
                if not any(getattr(r, "name", "") == "webagent" for r in result.routes):
                    result.mount("/webagent", _SF(directory=str(_webagent_dir)), name="webagent")
                    _wrt = result.routes.pop()
                    result.routes.insert(0, _wrt)
            except Exception as _me:
                print(f"[hearthnet] webagent mount: {_me}")
            _mount_bus_endpoints(result)
            _mount_relay_endpoints(result, _relay_hub)

            # Auto-join: the Space node registers itself in its own relay hub
            # so remote nodes that connect see it in the roster immediately.
            try:
                _caps = [
                    f"{e.descriptor.name}@{e.descriptor.version[0]}.{e.descriptor.version[1]}"
                    for e in _node.bus.registry.all_local()
                ]
                _nid = getattr(_node, "node_id_full", _node.node_id)
                _relay_hub.join(
                    _nid,
                    display_name=_node.display_name,
                    community_id=_node.community_id,
                    capabilities=_caps,
                    endpoint="",
                )
                _relay_hub.set_local_handler(_nid, _node.bus)
                print(f"[hearthnet] Space node '{_node.display_name}' joined local relay hub")
            except Exception as _je:
                print(f"[hearthnet] self-join relay failed: {_je}")
            return result

        _gr_routes.App.create_app = staticmethod(_patched_create_app)
    except Exception as _pe:
        print(f"[hearthnet] create_app patch failed: {_pe}")

if __name__ == "__main__":
    demo.launch()