from fastapi import FastAPI, File, UploadFile, HTTPException
from fastapi.responses import JSONResponse
from pydantic import BaseModel
import uvicorn
import os
import json
import tempfile
from typing import List

app = FastAPI(title="Voice API", version="1.0.0")

class VoiceModel:
    def __init__(self):
        self.models_dir = "./voice_models"
        os.makedirs(self.models_dir, exist_ok=True)
        self.voice_models = self._load_voice_models()
    
    def _load_voice_models(self) -> dict:
        """Load available voice models from disk"""
        models = {}
        for filename in os.listdir(self.models_dir):
            if filename.endswith('.json'):
                model_name = filename.replace('.json', '')
                try:
                    with open(os.path.join(self.models_dir, filename), 'r') as f:
                        model_data = json.load(f)
                        models[model_name] = model_data
                except Exception as e:
                    print(f"Error loading model {model_name}: {e}")
        return models
    
    def clone_voice(self, audio_file: UploadFile, voice_name: str) -> dict:
        """Clone voice from audio sample"""
        try:
            # Save audio file temporarily
            temp_path = os.path.join(tempfile.gettempdir(), audio_file.filename)
            with open(temp_path, 'wb') as f:
                f.write(audio_file.file.read())
            
            # TODO: Implement actual voice cloning using Coqui TTS or similar
            # For now, create a placeholder model
            model_path = os.path.join(self.models_dir, f"{voice_name}.json")
            model_data = {
                "name": voice_name,
                "status": "created",
                "sample_file": audio_file.filename,
                "sample_duration": 30,  # Placeholder
                "created_at": "2026-04-01T14:10:00Z"
            }
            
            with open(model_path, 'w') as f:
                json.dump(model_data, f, indent=2)
            
            # Update in-memory models
            self.voice_models[voice_name] = model_data
            
            return {
                "success": True,
                "voice_name": voice_name,
                "message": f"Voice model '{voice_name}' created successfully"
            }
            
        except Exception as e:
            raise HTTPException(status_code=500, detail=f"Voice cloning failed: {str(e)}")
    
    def synthesize(self, text: str, voice_name: str) -> bytes:
        """Generate speech with cloned voice"""
        if voice_name not in self.voice_models:
            raise HTTPException(status_code=404, detail=f"Voice model '{voice_name}' not found")
        
        try:
            # TODO: Implement actual TTS synthesis using Coqui TTS or similar
            # For now, return a placeholder audio file
            return b"placeholder_audio_data"
            
        except Exception as e:
            raise HTTPException(status_code=500, detail=f"Text-to-speech failed: {str(e)}")

class VoiceModelResponse(BaseModel):
    success: bool
    voice_name: str
    message: str

class SynthesizeRequest(BaseModel):
    text: str
    voice_name: str

class CloneRequest(BaseModel):
    voice_name: str

voice_model = VoiceModel()

@app.get("/")
async def root():
    return {"message": "Voice API - Stack 2.9 Integration"}

@app.get("/voices")
async def list_voices():
    """List available voice models"""
    return {
        "voices": list(voice_model.voice_models.keys()),
        "count": len(voice_model.voice_models)
    }

@app.post("/clone", response_model=VoiceModelResponse)
async def clone_voice(file: UploadFile = File(...), request: CloneRequest = None):
    """Clone voice from audio sample"""
    if not request:
        request = CloneRequest(voice_name="default")
    
    result = voice_model.clone_voice(file, request.voice_name)
    return result

@app.post("/synthesize")
async def synthesize_speech(request: SynthesizeRequest):
    """Generate speech with cloned voice"""
    audio_data = voice_model.synthesize(request.text, request.voice_name)
    
    return Response(content=audio_data, media_type="audio/wav")

@app.post("/synthesize_stream")
async def synthesize_stream(request: SynthesizeRequest):
    """Stream speech synthesis (placeholder)"""
    # TODO: Implement streaming TTS
    audio_data = voice_model.synthesize(request.text, request.voice_name)
    return Response(content=audio_data, media_type="audio/wav")

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