Create app.py

app.py

@@ -0,0 +1,91 @@
+import gradio as gr
+from huggingface_hub import InferenceClient
+import os
+from gtts import gTTS
+import speech_recognition as sr
+import pyaudio
+import io
+from tempfile import NamedTemporaryFile
+
+api = os.getenv("HF_API_TOKEN")
+client = InferenceClient("meta-llama/Meta-Llama-3.1-70B-Instruct", token=f"{api}")
+
+def respond(
+    message,
+    history: list[tuple[str, str]],
+    system_message,
+    max_tokens,
+    temperature,
+    top_p,
+):
+    messages = [{"role": "system", "content": system_message}]
+
+    for val in history:
+        if val[0]:
+            messages.append({"role": "user", "content": val[0]})
+        if val[1]:
+            messages.append({"role": "assistant", "content": val[1]})
+
+    messages.append({"role": "user", "content": message})
+
+    response = ""
+
+    for message in client.chat_completion(
+        messages,
+        max_tokens=max_tokens,
+        stream=True,
+        temperature=temperature,
+        top_p=top_p,
+    ):
+        token = message.choices[0].delta.content
+
+        response += token
+        yield response
+
+def text_to_speech(text):
+    tts = gTTS(text=text, lang='en')
+    with NamedTemporaryFile(delete=True) as tmpfile:
+        tts.save(tmpfile.name)
+        with open(tmpfile.name, "rb") as f:
+            return f.read()
+
+def speech_to_text(audio):
+    recognizer = sr.Recognizer()
+    with sr.AudioFile(io.BytesIO(audio)) as source:
+        audio_data = recognizer.record(source)
+        return recognizer.recognize_google(audio_data)
+
+def process_audio(audio, system_message, max_tokens, temperature, top_p):
+    text = speech_to_text(audio)
+    response_gen = respond(
+        message=text,
+        history=[],
+        system_message=system_message,
+        max_tokens=max_tokens,
+        temperature=temperature,
+        top_p=top_p,
+    )
+    response_text = next(response_gen)
+    audio_response = text_to_speech(response_text)
+    return audio_response
+
+demo = gr.Interface(
+    fn=process_audio,
+    inputs=[
+        gr.Audio(source="microphone", type="bytes"),
+        gr.Textbox(value="You are a friendly Chatbot.", label="System message"),
+        gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max new tokens"),
+        gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature"),
+        gr.Slider(
+            minimum=0.1,
+            maximum=1.0,
+            value=0.95,
+            step=0.05,
+            label="Top-p (nucleus sampling)",
+        ),
+    ],
+    outputs=gr.Audio(type="bytes"),
+)
+
+if __name__ == "__main__":
+    demo.launch()