Create app.py

app.py

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+from fastapi import FastAPI, HTTPException
+from pydantic import BaseModel
+import torch
+import torchaudio
+import ChatTTS
+
+# Configure Torch
+torch._dynamo.config.cache_size_limit = 64
+torch._dynamo.config.suppress_errors = True
+torch.set_float32_matmul_precision('high')
+
+# Initialize FastAPI app and ChatTTS model
+app = FastAPI()
+chat = ChatTTS.Chat()
+chat.load_models(compile=False)
+
+# Define the request model
+class TextRequest(BaseModel):
+    text: str
+
+@app.post("/synthesize/")
+async def synthesize_speech(request: TextRequest):
+    try:
+        # Perform inference
+        wavs = chat.infer([request.text])
+        
+        # Save the generated audio
+        output_file = "output.wav"
+        torchaudio.save(output_file, torch.from_numpy(wavs[0]), 24000)
+
+        return {"message": "Speech synthesized successfully", "audio_file": output_file}
+    except Exception as e:
+        raise HTTPException(status_code=500, detail=str(e))
+
+# Root endpoint
+@app.get("/")
+def read_root():
+    return {"message": "Welcome to the ChatTTS API. Use the /synthesize/ endpoint to generate speech."}