Create app.py

app.py

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+from flask import Flask, request, jsonify, send_file
+from flask_cors import CORS
+from faster_whisper import WhisperModel
+from transformers import pipeline
+from TTS.api import TTS
+import tempfile
+import os
+
+app = Flask(__name__)
+CORS(app)
+
+# Load models
+whisper_model = WhisperModel("small", device="cpu", compute_type="int8")
+llm = pipeline("text-generation", model="tiiuae/falcon-rw-1b", max_new_tokens=100)
+tts = TTS(model_name="tts_models/en/ljspeech/tacotron2-DDC", progress_bar=False, gpu=False)
+
+@app.route("/talk", methods=["POST"])
+def talk():
+    if "audio" not in request.files:
+        return jsonify({"error": "No audio file"}), 400
+
+    # Save audio
+    audio_file = request.files["audio"]
+    with tempfile.NamedTemporaryFile(delete=False, suffix=".wav") as tmp:
+        audio_path = tmp.name
+        audio_file.save(audio_path)
+
+    # Transcribe
+    segments, _ = whisper_model.transcribe(audio_path)
+    transcription = "".join([seg.text for seg in segments])
+
+    # Generate response
+    response = llm(transcription)[0]["generated_text"]
+
+    # Synthesize speech
+    tts_audio_path = audio_path.replace(".wav", "_reply.wav")
+    tts.tts_to_file(text=response, file_path=tts_audio_path)
+
+    return send_file(tts_audio_path, mimetype="audio/wav")
+
+@app.route("/")
+def index():
+    return "Metaverse AI Character API running."
+
+if __name__ == "__main__":
+    app.run(host="0.0.0.0", port=7860)