from fastapi import FastAPI, WebSocket, WebSocketDisconnect
from routes.index import router
import websockets
from ai.emotion import emotion_model

app = FastAPI()


@app.get("/")
def read_root():
    return {"message": "Hello, FastAPI!"}


# To run: uvicorn main:app --reload


# pymongo

from pymongo.mongo_client import MongoClient

uri = "mongodb+srv://gowdaman:gowdaman@cluster0.z5dooqf.mongodb.net/?retryWrites=true&w=majority&appName=Cluster0"
client = MongoClient(uri)
db = client["ai-saas"]
emotion = db["emotion"]
sentiment = db["sentiments"]


# emotion detection
import base64
import json
from bson.objectid import ObjectId
from bson import ObjectId


@app.websocket("/emotion")
async def websocket_emotion(websocket: WebSocket):
    await websocket.accept()
    course_id = None
    try:
        while True:
            data = await websocket.receive_text()
            msg = json.loads(data)
            image_b64 = msg.get("image")
            course_id = msg.get("course_id")  # Get the courseId from the message
            if not image_b64:
                await websocket.send_text("No image data received")
                continue
            image_bytes = base64.b64decode(image_b64)
            label, face = emotion_model.predict_from_frame_bytes(image_bytes)
            await websocket.send_text(str(label))
    except WebSocketDisconnect:
        # Do not call await websocket.close() here
        pass
    finally:
        print(f"WebSocket connection closed for user with course ID {course_id}")
        # Convert course_id to ObjectId if it's a string
        try:
            course_obj_id = ObjectId(course_id)
            # course_obj_id = course_id  # fallback if already ObjectId or invalid
            emotion_data = emotion.find_one({"course_id": course_obj_id})
            total_len = len(emotion_data['emotion'])
            print(emotion_data['emotion'].count(0)) # negetive
            print(emotion_data['emotion'].count(1)) # positive
            #positive percentage
            positive_percentage = round((emotion_data['emotion'].count(1)/total_len)*100,2)
            negative_percentage = round((emotion_data['emotion'].count(0)/total_len)*100,2)
            print(positive_percentage)
            print(negative_percentage)
            sentiment.update_one(
                {"course_id": course_obj_id},
                {
                    "$set": {
                        "expression_positive_score": positive_percentage,
                        "expression_negetive_score": negative_percentage,
                    }
                },
            )
        except Exception:
            pass


app.include_router(router)

# if __name__ == "__main__":
#     import uvicorn

#     uvicorn.run("main:app", host="0.0.0.0", port=7000, reload=True)