import json
import logging
import os
import uuid
from datetime import datetime
from typing import Any, Dict, List, Optional

import httpx
import uvicorn
from dotenv import load_dotenv
from fastapi import FastAPI, HTTPException, Depends
from fastapi.security import HTTPBearer, HTTPAuthorizationCredentials
from pydantic import BaseModel
from starlette.middleware.cors import CORSMiddleware
from starlette.responses import StreamingResponse, Response

# ==============================
# Configuration and Setup
# ==============================

# Configure logging
logging.basicConfig(
    level=logging.DEBUG,  # Set to DEBUG for detailed logs
    format="%(asctime)s - %(name)s - %(levelname)s - %(message)s"
)
logger = logging.getLogger(__name__)

# Load environment variables from .env file
load_dotenv()

# Initialize FastAPI app
app = FastAPI()

# Constants and configurations
BASE_URL = "https://aichatonlineorg.erweima.ai/aichatonline"
APP_SECRET = os.getenv("APP_SECRET", "666")
ACCESS_TOKEN = os.getenv("SD_ACCESS_TOKEN", "")
headers = {    
    'accept': '*/*',
    'accept-language': 'en-US,en;q=0.9',
    'authorization': f'Bearer {ACCESS_TOKEN}',
    'cache-control': 'no-cache',
    'origin': 'chrome-extension://difoiogjjojoaoomphldepapgpbgkhkb',
    'pragma': 'no-cache',
    'priority': 'u=1, i',
    'sec-fetch-dest': 'empty',
    'sec-fetch-mode': 'cors',
    'sec-fetch-site': 'none',
    'user-agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/130.0.0.0 Safari/537.36', 
}

# Define allowed models
ALLOWED_MODELS = [
    {"id": "claude-3.5-sonnet", "name": "claude-3.5-sonnet"},
    {"id": "claude-3-opus", "name": "claude-3-opus"},
    {"id": "gemini-1.5-pro", "name": "gemini-1.5-pro"},
    {"id": "gpt-4o", "name": "gpt-4o"},
    {"id": "o1-preview", "name": "o1-preview"},
    {"id": "o1-mini", "name": "o1-mini"},
    {"id": "gpt-4o-mini", "name": "gpt-4o-mini"},
]

# Configure CORS middleware
app.add_middleware(
    CORSMiddleware,
    allow_origins=["*"],  # Allow all origins; restrict if necessary
    allow_credentials=True,
    allow_methods=["*"],  # Allow all HTTP methods
    allow_headers=["*"],  # Allow all headers
)

# Security configuration
security = HTTPBearer()

# ==============================
# Pydantic Models
# ==============================

class Message(BaseModel):
    role: str
    content: str

class ChatRequest(BaseModel):
    model: str
    messages: List[Message]
    stream: Optional[bool] = False

# ==============================
# Helper Functions
# ==============================

def simulate_data(content: str, model: str) -> Dict[str, Any]:
    """Simulate chunked response data."""
    return {
        "id": f"chatcmpl-{uuid.uuid4()}",
        "object": "chat.completion.chunk",
        "created": int(datetime.now().timestamp()),
        "model": model,
        "choices": [
            {
                "index": 0,
                "delta": {"content": content, "role": "assistant"},
                "finish_reason": None,
            }
        ],
        "usage": None,
    }

def stop_data(content: str, model: str) -> Dict[str, Any]:
    """Simulate the final chunk indicating the end of the response."""
    return {
        "id": f"chatcmpl-{uuid.uuid4()}",
        "object": "chat.completion.chunk",
        "created": int(datetime.now().timestamp()),
        "model": model,
        "choices": [
            {
                "index": 0,
                "delta": {"content": content, "role": "assistant"},
                "finish_reason": "stop",
            }
        ],
        "usage": None,
    }

def create_chat_completion_data(content: str, model: str, finish_reason: Optional[str] = None) -> Dict[str, Any]:
    """Create a structured chat completion data chunk."""
    return {
        "id": f"chatcmpl-{uuid.uuid4()}",
        "object": "chat.completion.chunk",
        "created": int(datetime.now().timestamp()),
        "model": model,
        "choices": [
            {
                "index": 0,
                "delta": {"content": content, "role": "assistant"},
                "finish_reason": finish_reason,
            }
        ],
        "usage": None,
    }

def verify_app_secret(credentials: HTTPAuthorizationCredentials = Depends(security)) -> str:
    """Verify the provided APP_SECRET."""
    if credentials.credentials != APP_SECRET:
        raise HTTPException(status_code=403, detail="Invalid APP_SECRET")
    return credentials.credentials

def replace_escaped_newlines(input_string: str) -> str:
    """Replace escaped newline characters with actual newlines."""
    return input_string.replace("\\n", "\n")

# ==============================
# API Endpoints
# ==============================

@app.options("/hf/v1/chat/completions")
async def chat_completions_options():
    """Handle CORS preflight requests."""
    return Response(
        status_code=200,
        headers={
            "Access-Control-Allow-Origin": "*",
            "Access-Control-Allow-Methods": "POST, OPTIONS",
            "Access-Control-Allow-Headers": "Content-Type, Authorization",
        },
    )

@app.get("/hf/v1/models")
async def list_models():
    """List all allowed models."""
    return {"object": "list", "data": ALLOWED_MODELS}

@app.post("/hf/v1/chat/completions")
async def chat_completions(
    request: ChatRequest, app_secret: str = Depends(verify_app_secret)
):
    """Handle chat completion requests."""
    logger.info(f"Received chat completion request for model: {request.model}")

    # Validate model
    allowed_model_ids = [model['id'] for model in ALLOWED_MODELS]
    if request.model not in allowed_model_ids:
        raise HTTPException(
            status_code=400,
            detail=f"Model {request.model} is not allowed. Allowed models are: {', '.join(allowed_model_ids)}",
        )

    # Generate a UUID
    original_uuid = uuid.uuid4()
    uuid_str = str(original_uuid).replace("-", "")

    # Construct the payload to send to the external API
    json_data = {
        'prompt': "\n".join(
            [
                f"{'User' if msg.role == 'user' else 'Assistant'}: {msg.content}"
                for msg in request.messages
            ]
        ),
        'stream': True,
        'app_name': 'ChitChat_Edge_Ext',
        'app_version': '4.28.0',
        'tz_name': 'Asia/Karachi',
        'cid': 'C092SEMXM9BJ',
        'model': request.model,
        'search': False,  # Disable search
        'auto_search': False,  # Disable auto_search
        'filter_search_history': False,
        'from': 'chat',
        'group_id': 'default',
        'chat_models': [],
        'files': [],
        'prompt_template': {
            'key': '',
            'attributes': {
                'lang': 'original',
            },
        },
        'tools': {
            'auto': [
                'search',  # Re-add search to maintain API expectations
                'text_to_image',
                'data_analysis',
            ],
        },
        'extra_info': {
            'origin_url': '',
            'origin_title': '',
        },
    }

    # Define the asynchronous generator for streaming responses
    async def generate():
        async with httpx.AsyncClient() as client:
            try:
                async with client.stream('POST', 'https://sider.ai/api/v3/completion/text', headers=headers, json=json_data, timeout=120.0) as response:
                    response.raise_for_status()
                    async for line in response.aiter_lines():
                        if line:
                            logger.debug(f"Raw line received: {line}")  # Log raw line
                        if line and ("[DONE]" not in line):
                            try:
                                # Remove 'data: ' prefix if present
                                if line.startswith("data: "):
                                    line_content = line[6:]
                                else:
                                    line_content = line
                                
                                # Log the content before parsing
                                logger.debug(f"Line content to parse: {line_content}")
                                
                                # Check if the line is not empty after stripping
                                if not line_content.strip():
                                    logger.warning("Received an empty line, skipping.")
                                    continue
                                
                                # Attempt to parse JSON
                                parsed_json = json.loads(line_content)
                                
                                # Ensure 'data' key exists
                                if "data" not in parsed_json:
                                    logger.error(f"'data' key not found in the response: {parsed_json}")
                                    continue
                                
                                content_data = parsed_json["data"]
                                
                                # Extract text content if available
                                text_content = content_data.get("text", "")
                                
                                # Yield the formatted data
                                yield f"data: {json.dumps(create_chat_completion_data(text_content, request.model))}\n\n"
                            except json.JSONDecodeError as e:
                                logger.error(f"JSON decode error: {e} | Line: {line_content}")
                                continue
                        else:
                            if line and "[DONE]" in line:
                                yield f"data: {json.dumps(create_chat_completion_data('', request.model, 'stop'))}\n\n"
                                yield "data: [DONE]\n\n"
            except httpx.HTTPStatusError as e:
                logger.error(f"HTTP error occurred: {e}")
                raise HTTPException(status_code=e.response.status_code, detail=str(e))
            except httpx.RequestError as e:
                logger.error(f"An error occurred while requesting: {e}")
                raise HTTPException(status_code=500, detail=str(e))

    if request.stream:
        logger.info("Streaming response")
        return StreamingResponse(generate(), media_type="text/event-stream")
    else:
        logger.info("Non-streaming response")
        full_response = ""
        async for chunk in generate():
            if chunk.startswith("data: ") and not chunk[6:].startswith("[DONE]"):
                try:
                    data = json.loads(chunk[6:])
                    if data["choices"][0]["delta"].get("content"):
                        full_response += data["choices"][0]["delta"]["content"]
                except json.JSONDecodeError as e:
                    logger.error(f"JSON decode error in non-streaming response: {e}")
                    continue

        return {
            "id": f"chatcmpl-{uuid.uuid4()}",
            "object": "chat.completion",
            "created": int(datetime.now().timestamp()),
            "model": request.model,
            "choices": [
                {
                    "index": 0,
                    "message": {"role": "assistant", "content": full_response},
                    "finish_reason": "stop",
                }
            ],
            "usage": None,
        }

# ==============================
# Entry Point
# ==============================

if __name__ == "__main__":
    uvicorn.run(app, host="0.0.0.0", port=7860)