main.py

from fastapi import FastAPI, UploadFile, File, Form, HTTPException
from fastapi.middleware.cors import CORSMiddleware
from fastapi.staticfiles import StaticFiles
from pydantic import BaseModel
import uuid
import os
from datetime import datetime
from config import config
from database import db
from ai_model import ai_models
import uvicorn
import json

app = FastAPI(
    title="MobileDoc API",
    description="Mobile Doctor Backend MVP",
    version="1.0.0"
)

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

# ---------------- File Handling ----------------
os.makedirs(config.UPLOAD_DIR, exist_ok=True)
app.mount("/uploads", StaticFiles(directory=config.UPLOAD_DIR), name="uploads")

# ---------------- Pydantic Models ----------------
class UserProfile(BaseModel):
    username: str
    email: str
    age: int
    gender: str
    allergies: str = ""
    conditions: str = ""

class LoginRequest(BaseModel):
    username: str

class SymptomsRequest(BaseModel):
    user_id: str
    symptoms: str

class AnalysisResponse(BaseModel):
    success: bool
    data: dict
    message: str = ""

# ---------------- Routes ----------------
@app.get("/")
async def root():
    return {"status": "AI Health Diagnostics API Running", "timestamp": datetime.now().isoformat()}


# ---------- Create User Profile ----------
@app.post("/create-profile", response_model=AnalysisResponse)
async def create_profile(profile: UserProfile):
    try:
        user_id = str(uuid.uuid4())
        user_data = {
            "id": user_id,
            "username": profile.username.strip(),
            "email": profile.email.strip(),
            "age": profile.age,
            "gender": profile.gender,
            "allergies": profile.allergies,
            "conditions": profile.conditions
        }

        db.create_user(user_data)

        return AnalysisResponse(
            success=True,
            data={"user_id": user_id},
            message="Profile created successfully"
        )
    except Exception as e:
        raise HTTPException(status_code=500, detail=str(e))


# ---------- Check User Profile ----------
@app.post("/check-profile", response_model=AnalysisResponse)
async def check_profile(request: LoginRequest):
    username = request.username.strip()
    try:
        response = db.client.table("users").select("*").eq("username", username).execute()

        users = response.data or []
        if not users:
            raise HTTPException(status_code=404, detail="User not found")

        user = users[0]
        return AnalysisResponse(
            success=True,
            data={"user_id": user["id"], "username": user["username"]},
            message="Profile found"
        )
    except Exception as e:
        raise HTTPException(status_code=500, detail=str(e))


# ---------- Symptom Check ----------
@app.post("/symptom-check", response_model=AnalysisResponse)
async def symptom_check(request: SymptomsRequest):
    try:
        # Fetch user from Supabase
        user_response = db.client.table("users").select("*").eq("id", request.user_id).execute()
        users = user_response.data or []
        if not users:
            raise HTTPException(status_code=404, detail="User not found")

        user_profile = users[0]

        # Run AI analysis
        analysis_result = ai_models.analyze_symptoms(request.symptoms, user_profile)

        # Log analysis
        db.log_symptom_analysis({
            "id": str(uuid.uuid4()),
            "user_id": request.user_id,
            "symptoms": request.symptoms,
            "result": json.dumps(analysis_result)
        })

        return AnalysisResponse(
            success=True,
            data=analysis_result,
            message="Symptoms analyzed successfully"
        )
    except Exception as e:
        raise HTTPException(status_code=500, detail=str(e))


# ---------- Image Analysis ----------
@app.post("/analyze-image", response_model=AnalysisResponse)
async def analyze_image(
    user_id: str = Form(...),
    image_type: str = Form("skin"),
    file: UploadFile = File(...)
):
    try:
        allowed_types = ["image/jpeg", "image/png", "image/jpg"]
        if file.content_type not in allowed_types:
            raise HTTPException(status_code=400, detail="Invalid image format")

        image_data = await file.read()
        if len(image_data) > config.MAX_IMAGE_SIZE:
            raise HTTPException(status_code=400, detail="Image too large")

        analysis_result = ai_models.analyze_image(image_data, image_type)

        filename = f"{uuid.uuid4()}_{file.filename}"
        file_path = os.path.join(config.UPLOAD_DIR, filename)
        with open(file_path, "wb") as f:
            f.write(image_data)

        db.log_image_analysis({
            "id": str(uuid.uuid4()),
            "user_id": user_id,
            "filename": filename,
            "result": json.dumps(analysis_result),
            "confidence": analysis_result.get("confidence", 0.0)
        })

        return AnalysisResponse(
            success=True,
            data=analysis_result,
            message="Image analyzed successfully"
        )
    except Exception as e:
        print("🔥 SERVER ERROR:", repr(e))
        raise HTTPException(status_code=500, detail=str(e))


# ---------- User History ----------
@app.get("/user-history/{user_id}", response_model=AnalysisResponse)
async def get_user_history(user_id: str):
    try:
        symptoms = db.client.table("symptoms_history").select("*").eq("user_id", user_id).order("created_at", desc=True).limit(10).execute()
        images = db.client.table("image_analysis").select("*").eq("user_id", user_id).order("created_at", desc=True).limit(10).execute()

        return AnalysisResponse(
            success=True,
            data={
                "symptom_checks": symptoms.data or [],
                "image_analyses": images.data or []
            },
            message="History retrieved successfully"
        )
    except Exception as e:
        raise HTTPException(status_code=500, detail=str(e))


# ---------- Run Server ----------
if __name__ == "__main__":
    uvicorn.run(app, host="0.0.0.0", port=8000)