Update app.py

app.py

@@ -9,25 +9,31 @@ with open("BACKGROUND.md", "r", encoding="utf-8") as f:
 client = InferenceClient("HuggingFaceH4/zephyr-7b-beta")
 
 def respond(
-    message,
-    history: list[tuple[str, str]],
-    system_message,
-    max_tokens,
-    temperature,
-    top_p,
+    message: str,
+    history: list[dict],
+    system_message: str,
+    max_tokens: int,
+    temperature: float,
+    top_p: float,
 ):
+    if history is None:
+        history = []
+
+    # Include system message
     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]})
 
+    # Append history in the required format
+    for interaction in history:
+        if "user" in interaction:
+            messages.append({"role": "user", "content": interaction["user"]})
+        if "assistant" in interaction:
+            messages.append({"role": "assistant", "content": interaction["assistant"]})
+
+    # Append the current user message
     messages.append({"role": "user", "content": message})
 
+    # Generate response from the model
     response = ""
-
     for msg in client.chat_completion(
         messages,
         max_tokens=max_tokens,
@@ -37,26 +43,26 @@ def respond(
     ):
         token = msg.choices[0].delta.content
         response += token
-        # 'yield' returns partial responses for streaming
         yield response
 
-# Step 3: Build a Gradio Blocks interface with two Tabs
+# Step 3: Build a Gradio Blocks interface with Tabs
 with gr.Blocks() as demo:
-    # (A) First Tab: Chat Interface
+    # Tab 1: GPT Chat Agent
     with gr.Tab("GPT Chat Agent"):
         gr.Markdown("## Welcome to Varun's GPT Agent")
         gr.Markdown("Feel free to ask questions about Varun’s journey, skills, and more!")
         chat = gr.ChatInterface(
-            respond,
+            fn=respond,
             additional_inputs=[
                 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)"),
             ],
+            type="messages",  # Use 'messages' type for Gradio's ChatInterface
         )
 
-    # (B) Second Tab: Background Document
+    # Tab 2: Background Document
     with gr.Tab("Varun's Background"):
         gr.Markdown("# About Varun")
         gr.Markdown(background_text)