Create main.py

main.py

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+from fastapi import FastAPI, WebSocket
+from transformers import pipeline
+from kokoro import KPipeline
+import asyncio
+
+app = FastAPI()
+
+# Initialize models
+llm = pipeline("text-generation", model="HuggingFaceTB/SmolLM2-360M-Instruct")
+tts = KPipeline(lang_code='a', model='shahid202/Kokoro-82M-TTS')
+
+def get_llm_response(text):
+    # Very short, witty generation
+    prompt = f"User: {text}\nBella:"
+    return llm(prompt, max_new_tokens=30)[0]['generated_text'].split("Bella:")[-1].strip()
+
+@app.websocket("/ws/chat")
+async def websocket_endpoint(websocket: WebSocket):
+    await websocket.accept()
+    while True:
+        user_msg = await websocket.receive_text()
+        
+        # 1. Get response from LLM
+        full_text = get_llm_response(user_msg)
+        
+        # 2. Simple split by punctuation to trigger TTS immediately
+        sentences = [s.strip() + "." for s in full_text.split('.') if s]
+        
+        for sentence in sentences:
+            # 3. Generate audio for the sentence
+            generator = tts(sentence, voice="af_heart", speed=1.0)
+            for _, _, audio in generator:
+                # 4. Send audio bytes over WebSocket
+                await websocket.send_bytes(audio.tobytes())
+                # Small pause to mimic natural speech flow
+                await asyncio.sleep(0.1) 
+