Create app.py

app.py

@@ -0,0 +1,40 @@
+import streamlit as st
+from huggingface_hub import InferenceClient
+from gtts import gTTS
+import os
+
+client = InferenceClient("HuggingFaceH4/zephyr-7b-beta")
+
+def generate_response(message, system_message, max_tokens, temperature, top_p):
+    messages = [{"role": "system", "content": system_message}]
+    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
+
+    # Generate speech from the response text using gTTS
+    tts = gTTS(text=response, lang='en')
+    audio_file = "response.mp3"
+    tts.save(audio_file)
+    return response, audio_file
+
+st.title("Hugging Face Chatbot with Voice Response")
+
+message = st.text_input("Enter your message:")
+system_message = st.text_input("System message:", value="You are a friendly Chatbot.")
+max_tokens = st.slider("Max new tokens", 1, 2048, 512)
+temperature = st.slider("Temperature", 0.1, 4.0, 0.7, step=0.1)
+top_p = st.slider("Top-p (nucleus sampling)", 0.1, 1.0, 0.95, step=0.05)
+
+if st.button("Generate Response"):
+    response, audio_file = generate_response(message, system_message, max_tokens, temperature, top_p)
+    st.write(response)
+    st.audio(audio_file)