import os
from typing import Optional
from fastapi import FastAPI, HTTPException, Security, Depends
from fastapi.security import APIKeyHeader
from fastapi.middleware.cors import CORSMiddleware
from dotenv import load_dotenv
import json
from pydantic import BaseModel
from fastapi import HTTPException
import os
from scripts.transcriber import transcribe_media, group_words_into_sentences
from scripts.generate_summary import general_summary, custom_summary
from src.models import PlanTier, PlanLimits
# Load environment variables
load_dotenv()
API_KEY = os.getenv("API_KEY_ACCESS")

# Initialize FastAPI app
app = FastAPI(
    title="Microdot AI API",
    description="API For fire fighter",
    version="1.0.0"
)

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

# Setup API key authentication
api_key_header = APIKeyHeader(name="Authorization", auto_error=False)


async def get_api_key(api_key_header: str = Security(api_key_header)) -> str:
    """Validate API key from header"""
    if not api_key_header or not api_key_header.startswith('Bearer '):
        raise HTTPException(
            status_code=401,
            detail={"error": "Unauthorized", "message": "API key is missing or invalid."}
        )

    token = api_key_header.split(' ')[1]
    if token != API_KEY:
        raise HTTPException(
            status_code=401,
            detail={"error": "Unauthorized", "message": "API key does not match."}
        )

    return token

class TranscribeRequest(BaseModel):
    media_url: Optional[str] = None
    media_type: Optional[str]  # Corrected type hint for media_type

class ChatResp(BaseModel):  # Added BaseModel inheritance
    error: Optional[str] = None
class TranscriptResponse(BaseModel):
    transcript: dict  # Changed type hint for transcript to a dictionary



class GeneralSummaryRequest(BaseModel):
    transcript: Optional[str] = None
    plan_tier: Optional[str] = "pro"  # Default to pro plan if not specified

class TemplateSummaryRequest(BaseModel):
    transcript: Optional[str] = None
    template: Optional[str] = None


@app.post("/microdot-ai/transcribe")
async def chat_endpoint(
    request: TranscribeRequest,
    api_key: str = Depends(get_api_key)
):
    try:

        # Use the transcribe_media function to transcribe the media
        if request.media_url:
            transcription_response = transcribe_media(request.media_url, media_type=request.media_type)
            if transcription_response is None:
                raise HTTPException(status_code=500, detail="Transcription failed.")
            print(f"Transcription response: {transcription_response}")  # Debugging print

        # Parse response
        words = transcription_response["results"]["channels"][0]["alternatives"][0]["words"]
        transcript = group_words_into_sentences(words=words)
        return TranscriptResponse(
            transcript=transcript,  # Corrected to return the transcript
            error=None
        )

    except Exception as e:
        print(f"Error processing chat request: {str(e)}")  # Print statement added
        raise HTTPException(
            status_code=500,
            detail=f"Error processing chat request: {str(e)}"
        )


@app.post("/microdot-ai/general-summary")
async def general_summary_endpoint(
    request: GeneralSummaryRequest,
    api_key: str = Depends(get_api_key)
):
    try:
        if not request.transcript:
            raise HTTPException(status_code=400, detail="Transcript is required.")

        # Get the plan tier from the request or default to pro
        plan_tier = request.plan_tier.lower() if request.plan_tier else "pro"

        # Validate plan tier using our PlanTier enum
        valid_tiers = [t.value for t in PlanTier]
        if plan_tier not in valid_tiers:
            plan_tier = PlanTier.PRO.value  # Default to pro if invalid tier

        # Get the appropriate summary type for this plan tier
        summary_type = PlanLimits.get_limit(plan_tier, "summary_type")

        # Generate the summary based on the plan tier
        response = general_summary(json.loads(request.transcript), plan_tier=plan_tier)

        return TranscriptResponse(
            transcript=response
        )

    except Exception as e:
        print(f"Error processing general summary request: {str(e)}")
        raise HTTPException(
            status_code=500,
            detail=f"Error processing general summary request: {str(e)}"
        )


@app.post("/microdot-ai/template-summary")
async def template_summary_endpoint(  # Corrected function name to avoid conflict
    request: TemplateSummaryRequest,
    api_key: str = Depends(get_api_key)
):
    try:
        if not request.transcript:
            raise HTTPException(status_code=400, detail="Transcript is required.")

        if not request.template:
            raise HTTPException(status_code=400, detail="Template is required.")

        transcript = json.loads(request.transcript)
        template = json.loads(request.template)  # Removed the check for missing template as it's now required
        response = custom_summary(template, transcript)

        return TranscriptResponse(
            transcript=response
        )

    except Exception as e:
        print(f"Error processing template summary request: {str(e)}")  # Updated print statement for clarity
        raise HTTPException(
            status_code=500,
            detail=f"Error processing template summary request: {str(e)}"
        )


@app.on_event("startup")
async def startup_event():
    """Initialize required components on startup"""
    pass

if __name__ == "__main__":
    import uvicorn
    uvicorn.run("app:app", host="0.0.0.0", port=5056, reload=True)