Update app.py

app.py

@@ -46,50 +46,38 @@ import gradio as gr
 from huggingface_hub import InferenceClient
 import os
 
+# Initialize Hugging Face Inference Client
 hf_token = os.getenv("HF_TOKEN")
 client = InferenceClient(api_key=hf_token)
 
-def chatbot(input_text, history):
-    # Prepare the conversation messages
+# Function to handle user inputs and fetch model responses
+def chatbot(input_text, history=[]):
     messages = [{"role": "user", "content": input_text}]
+    for user_input, bot_response in history:
+        messages.append({"role": "user", "content": user_input})
+        messages.append({"role": "assistant", "content": bot_response})
 
-    # Add conversation history (if exists)
-    if history:
-        for user_input, bot_response in history:
-            messages.append({"role": "user", "content": user_input})
-            messages.append({"role": "assistant", "content": bot_response})
-
-    # Generate model response
     stream = client.chat.completions.create(
         model="google/gemma-2-2b-it", 
         messages=messages, 
-        temperature=0.5,
-        max_tokens=2048,
-        top_p=0.7,
+        #temperature=0.5,
+        #max_tokens=2048,
+        #top_p=0.7,
         stream=True
     )
 
-    # Collect response from the model
-    bot_response = ""
-    for chunk in stream:
-        bot_response += chunk.choices[0].delta.content
-
-    # Update the conversation history
+    # Concatenate streamed response
+    bot_response = "".join(chunk.choices[0].delta.content for chunk in stream)
     history.append((input_text, bot_response))
     return bot_response, history
 
-# Create Gradio Interface
-with gr.Blocks() as demo:
-    chatbot_ui = gr.Chatbot(label="Gemma Chatbot").style(height=400)
-    text_input = gr.Textbox(show_label=False, placeholder="Type your message here...")
-    state = gr.State([])  # Keeps track of conversation history
-
-    def user_input_handler(user_input, chatbot_ui, state):
-        bot_response, state = chatbot(user_input, state)
-        chatbot_ui.append((user_input, bot_response))
-        return chatbot_ui, state
-
-    text_input.submit(user_input_handler, [text_input, chatbot_ui, state], [chatbot_ui, state])
+# Gradio Interface
+demo = gr.Interface(
+    fn=chatbot, 
+    inputs=["text", "state"], 
+    outputs=["text", "state"], 
+    title="Gemma Chatbot"
+)
 
-# Run the application
+# Launch Gradio App
 demo.launch()