"""
OpenAI-compatible /v1 API Gateway
Proxies to NVIDIA NIM API with streaming always enabled,
function calling support, and per-model system prompts.

Deploy on Hugging Face Spaces (Docker).
Authorization: Bearer connect
"""

import json
import time
import uuid
import asyncio
from typing import Any, AsyncGenerator

import httpx
from fastapi import FastAPI, HTTPException, Request
from fastapi.middleware.cors import CORSMiddleware
from fastapi.responses import StreamingResponse, JSONResponse
from pydantic import BaseModel, Field

from system_prompts import SYSTEM_PROMPTS, MODEL_MAP, REVERSE_MODEL_MAP, EXTRA_BODY_MODELS

# ---------------------------------------------------------------------------
# Config
# ---------------------------------------------------------------------------

NVIDIA_BASE_URL = "https://integrate.api.nvidia.com/v1"
NVIDIA_API_KEY  = "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"
GATEWAY_API_KEY = "connect"

# ---------------------------------------------------------------------------
# App
# ---------------------------------------------------------------------------

app = FastAPI(
    title="AI Gateway",
    description="OpenAI-compatible gateway to NVIDIA NIM models",
    version="1.0.0",
)

app.add_middleware(
    CORSMiddleware,
    allow_origins=["*"],
    allow_credentials=True,
    allow_methods=["*"],
    allow_headers=["*"],
)

# ---------------------------------------------------------------------------
# Auth
# ---------------------------------------------------------------------------

def verify_api_key(request: Request) -> None:
    auth = request.headers.get("Authorization", "")
    if not auth.startswith("Bearer "):
        raise HTTPException(status_code=401, detail="Missing Bearer token")
    token = auth.removeprefix("Bearer ").strip()
    if token != GATEWAY_API_KEY:
        raise HTTPException(status_code=401, detail="Invalid API key")

# ---------------------------------------------------------------------------
# Pydantic models (OpenAI-compatible)
# ---------------------------------------------------------------------------

class FunctionParameters(BaseModel):
    type: str = "object"
    properties: dict[str, Any] = {}
    required: list[str] = []

class FunctionDef(BaseModel):
    name: str
    description: str | None = None
    parameters: FunctionParameters | None = None

class Tool(BaseModel):
    type: str = "function"
    function: FunctionDef

class ToolChoice(BaseModel):
    type: str = "function"
    function: dict[str, str] | None = None

class Message(BaseModel):
    role: str
    content: str | list[Any] | None = None
    name: str | None = None
    tool_calls: list[Any] | None = None
    tool_call_id: str | None = None

class ChatCompletionRequest(BaseModel):
    model: str
    messages: list[Message]
    temperature: float | None = None
    top_p: float | None = None
    max_tokens: int | None = None
    tools: list[Tool] | None = None
    tool_choice: str | ToolChoice | None = None
    # stream is ALWAYS True – ignored if provided, always forced to True
    stream: bool = True
    stop: list[str] | str | None = None
    presence_penalty: float | None = None
    frequency_penalty: float | None = None
    seed: int | None = None
    n: int | None = None
    logprobs: bool | None = None
    top_logprobs: int | None = None
    user: str | None = None

# ---------------------------------------------------------------------------
# Helpers
# ---------------------------------------------------------------------------

def resolve_model(requested: str) -> str:
    """Map display name or raw NVIDIA model ID to NVIDIA model ID."""
    if requested in MODEL_MAP:
        return MODEL_MAP[requested]
    if requested in REVERSE_MODEL_MAP:
        return requested  # already a raw ID
    raise HTTPException(
        status_code=400,
        detail=f"Unknown model '{requested}'. Available: {list(MODEL_MAP.keys())}",
    )

def get_display_name(nvidia_id: str) -> str:
    return REVERSE_MODEL_MAP.get(nvidia_id, nvidia_id)

def inject_system_prompt(messages: list[Message], display_name: str) -> list[dict]:
    """Inject per-model system prompt if not already present."""
    prompt = SYSTEM_PROMPTS.get(display_name)
    serialized = [m.model_dump(exclude_none=True) for m in messages]

    if prompt:
        has_system = any(m["role"] == "system" for m in serialized)
        if not has_system:
            serialized = [{"role": "system", "content": prompt}] + serialized

    return serialized

def build_nvidia_payload(req: ChatCompletionRequest, nvidia_model: str) -> dict:
    display = get_display_name(nvidia_model)
    messages = inject_system_prompt(req.messages, display)

    payload: dict[str, Any] = {
        "model": nvidia_model,
        "messages": messages,
        "stream": True,  # ALWAYS TRUE
    }

    # Optional params
    if req.temperature is not None:
        payload["temperature"] = req.temperature
    if req.top_p is not None:
        payload["top_p"] = req.top_p
    if req.max_tokens is not None:
        payload["max_tokens"] = req.max_tokens
    if req.stop is not None:
        payload["stop"] = req.stop
    if req.presence_penalty is not None:
        payload["presence_penalty"] = req.presence_penalty
    if req.frequency_penalty is not None:
        payload["frequency_penalty"] = req.frequency_penalty
    if req.seed is not None:
        payload["seed"] = req.seed
    if req.n is not None:
        payload["n"] = req.n
    if req.user is not None:
        payload["user"] = req.user

    # Function calling / tools
    if req.tools:
        payload["tools"] = [t.model_dump(exclude_none=True) for t in req.tools]
    if req.tool_choice is not None:
        if isinstance(req.tool_choice, str):
            payload["tool_choice"] = req.tool_choice
        else:
            payload["tool_choice"] = req.tool_choice.model_dump(exclude_none=True)

    # Extra body for specific models (e.g. GLM-4.7 thinking params)
    extra = EXTRA_BODY_MODELS.get(nvidia_model, {})
    payload.update(extra)

    return payload

# ---------------------------------------------------------------------------
# SSE streaming proxy
# ---------------------------------------------------------------------------

async def stream_nvidia(payload: dict) -> AsyncGenerator[bytes, None]:
    headers = {
        "Authorization": f"Bearer {NVIDIA_API_KEY}",
        "Content-Type": "application/json",
        "Accept": "text/event-stream",
    }

    async with httpx.AsyncClient(timeout=300) as client:
        async with client.stream(
            "POST",
            f"{NVIDIA_BASE_URL}/chat/completions",
            headers=headers,
            json=payload,
        ) as response:
            if response.status_code != 200:
                body = await response.aread()
                error_detail = body.decode(errors="replace")
                error_chunk = {
                    "error": {
                        "message": f"Upstream error {response.status_code}: {error_detail}",
                        "type": "upstream_error",
                        "code": response.status_code,
                    }
                }
                yield f"data: {json.dumps(error_chunk)}\n\n".encode()
                yield b"data: [DONE]\n\n"
                return

            async for line in response.aiter_lines():
                if line.startswith("data: "):
                    yield f"{line}\n\n".encode()
                    if line == "data: [DONE]":
                        return
                elif line.strip():
                    # Pass through any unexpected lines
                    yield f"data: {line}\n\n".encode()

# ---------------------------------------------------------------------------
# Routes
# ---------------------------------------------------------------------------

@app.get("/")
async def root():
    return {"status": "ok", "service": "AI Gateway", "version": "1.0.0"}

@app.get("/v1/models")
async def list_models(request: Request):
    verify_api_key(request)
    now = int(time.time())
    models = []
    for display_name in MODEL_MAP:
        models.append({
            "id": display_name,
            "object": "model",
            "created": now,
            "owned_by": "ai-gateway",
        })
    return {"object": "list", "data": models}

@app.post("/v1/chat/completions")
async def chat_completions(request: Request, req: ChatCompletionRequest):
    verify_api_key(request)

    nvidia_model = resolve_model(req.model)
    payload = build_nvidia_payload(req, nvidia_model)

    return StreamingResponse(
        stream_nvidia(payload),
        media_type="text/event-stream",
        headers={
            "Cache-Control": "no-cache",
            "Connection": "keep-alive",
            "X-Accel-Buffering": "no",
        },
    )

# Passthrough completions (legacy)
@app.post("/v1/completions")
async def completions(request: Request):
    verify_api_key(request)
    body = await request.json()

    model_req = body.get("model", "")
    try:
        nvidia_model = resolve_model(model_req)
    except HTTPException:
        nvidia_model = model_req

    body["model"] = nvidia_model
    body["stream"] = True

    return StreamingResponse(
        stream_nvidia(body),
        media_type="text/event-stream",
        headers={
            "Cache-Control": "no-cache",
            "Connection": "keep-alive",
            "X-Accel-Buffering": "no",
        },
    )

@app.get("/health")
async def health():
    return {"status": "healthy"}