Update app.py

app.py

@@ -1,33 +1,65 @@
 import gradio as gr
-from transformers import pipeline
-
-# Load the text generation pipeline
-print("Loading model pipeline...")
-pipe = pipeline("text-generation", model="esha111/id2223_lab2_correct")
-print("Pipeline loaded.")
-
-# Function to handle user input
-def generate_response(user_input):
-    try:
-        # Prepare input message
-        messages = [{"role": "user", "content": user_input}]
-        
-        # Generate response using the pipeline
-        response = pipe(messages)
-        return response[1]["content"]
-    except Exception as e:
-        return f"Error: {e}"
-
-# Create a Gradio interface
-demo = gr.Interface(
-    fn=generate_response,  # Function to call
-    inputs="text",         # Input type: single text field
-    outputs="text",        # Output type: single text field
-    title="Chat with Model",
-    description="Type a message to interact with the model.",
+from huggingface_hub import InferenceClient
+
+"""
+Cloned from https://huggingface.co/spaces/gradio-templates/chatbot - and added the history toggle to the interface
+For more information on `huggingface_hub` Inference API support, please check the docs: https://huggingface.co/docs/huggingface_hub/v0.22.2/en/guides/inference
+"""
+
+client = InferenceClient("esha111/id2223_lab2_correct")
+
+
+def respond(
+    message,
+    history: list[tuple[str, str]],
+    system_message,
+    use_history,
+    max_tokens,
+    temperature,
+    top_p,
+):
+    messages = [{"role": "system", "content": system_message}]
+
+    # Only use history if the toggle is on 
+    if use_history == "Yes":
+        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
+    
+    # Then add to history (even if the toggle is of)
+    history.append((message, response))
+
+
+demo = gr.ChatInterface(
+    respond,
+    additional_inputs=[
+        gr.Textbox(value="You are a friendly Chatbot.", label="System message"),
+        gr.Radio(["Yes", "No"], value="Yes", label="Use chat history"),
+        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)", ),
+    ],
 )
 
-# Launch the Gradio app
+
 if __name__ == "__main__":
-    print("Launching Gradio app...")
     demo.launch()