Upload folder using huggingface_hub

.github/workflows/update_space.yml

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+name: Run Python script
+
+on:
+  push:
+    branches:
+      - main
+
+jobs:
+  build:
+    runs-on: ubuntu-latest
+
+    steps:
+    - name: Checkout
+      uses: actions/checkout@v2
+
+    - name: Set up Python
+      uses: actions/setup-python@v2
+      with:
+        python-version: '3.9'
+
+    - name: Install Gradio
+      run: python -m pip install gradio
+
+    - name: Log in to Hugging Face
+      run: python -c 'import huggingface_hub; huggingface_hub.login(token="${{ secrets.hf_token }}")'
+
+    - name: Deploy to Spaces
+      run: gradio deploy

LLM voice chat.py

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+
+# pip install fastrtc[stt] kokoro_onnx
+
+import os
+import gradio as gr
+
+from fastrtc import (ReplyOnPause, Stream, get_stt_model, get_tts_model)
+from openai import OpenAI
+
+llm_client = OpenAI(
+    #api_key=os.getenv("SAMBANOVA_API_KEY"), base_url="https://api.sambanova.ai/v1"
+)
+stt_model = get_stt_model()
+tts_model = get_tts_model()
+print(type(llm_client), type(stt_model), type(tts_model) )
+      
+def echo(audio):
+    prompt = stt_model.stt(audio)
+    print(prompt)
+    response = llm_client.chat.completions.create(
+        #model="Meta-Llama-3.2-3B-Instruct",
+        model='gpt-4o-mini',
+        messages=[{"role": "user", "content": prompt}],
+        max_tokens=200,
+    )
+    prompt = response.choices[0].message.content
+    print(prompt)
+    for audio_chunk in tts_model.stream_tts_sync(prompt):
+        yield audio_chunk
+
+stream = Stream(ReplyOnPause(echo), modality="audio", mode="send-receive")
+
+stream.ui.launch()

README.md

@@ -1,12 +1,6 @@
 ---
-title: LLM Voice Chat
-emoji: 📊
-colorFrom: blue
-colorTo: gray
+title: LLM_voice_chat
+app_file: LLM voice chat.py
 sdk: gradio
-sdk_version: 5.29.0
-app_file: app.py
-pinned: false
+sdk_version: 5.27.0
 ---
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

requirements.txt

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+fastrtc[vad, stt, tts]
+openai