Update app.py

app.py

@@ -111,18 +111,19 @@ chunk_embeddings = create_embeddings(cleaned_chunks)
 client= InferenceClient("Qwen/Qwen2.5-7B-Instruct-1M")
 
 #defining role of AI and user
-def respond(message,history):
+# i moved it to the bottom
+#def respond(message,history):
 
-    messages = [{"role": "assistant", "content": "You are a friendly chatbot."}]
+ #   messages = [{"role": "assistant", "content": "You are a friendly chatbot."}]
 
-    if history:
-        messages.extend(history) #keep adding history 
+  #  if history:
+   #     messages.extend(history) #keep adding history 
 
-    messages.append({"role":"user", "content": message})
+    #messages.append({"role":"user", "content": message})
 
-    response=client.chat_completion(messages, max_tokens=100) #capping how many words the LLM is allowed to generate as a respond (100 words)
+    #response=client.chat_completion(messages, max_tokens=100) #capping how many words the LLM is allowed to generate as a respond (100 words)
 
-    return response['choices'][0]['message']['content'].strip() #storing value of response in a readable format to display
+#    return response['choices'][0]['message']['content'].strip() #storing value of response in a readable format to display
 
 ### STEP 6
 # Call the preprocess_text function and store the result in a cleaned_chunks variable
@@ -170,12 +171,21 @@ custom_css = """
 """
 
 def respond(message, history):
+    # Prepare messages for the API
     messages = [{"role": "assistant", "content": "You are a friendly chatbot."}]
     if history:
-        messages.extend(history)
+        # Convert Gradio history into API format
+        for user_msg, bot_msg in history:
+            messages.append({"role": "user", "content": user_msg})
+            messages.append({"role": "assistant", "content": bot_msg})
     messages.append({"role": "user", "content": message})
+    
+    # Call the API
     response = client.chat_completion(messages, max_tokens=100)
-    return history + [(message, response['choices'][0]['message']['content'].strip())], ""
+    assistant_reply = response['choices'][0]['message']['content'].strip()
+    
+    # Return for Gradio
+    return history + [(message, assistant_reply)], ""
 
 with gr.Blocks(css=custom_css) as demo:
     gr.HTML("<div id='header'>DivaBot</div>")