Update app.py

app.py

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+from huggingface_hub import InferenceClient
+import gradio as gr
+import base64
+import datetime
+
+client = InferenceClient("meta-llama/Meta-Llama-3-8B-Instruct")
+
+# Debate response function
+def debate_respond(message, history: list[tuple[str, str]],
+                   max_tokens=1024, temperature=0.4, top_p=0.95):
+    # System message defining assistant behavior in a debate
+    system_message = {
+        "role": "system",
+        "content": f"Act as a debate participant taking the position '{position}' on the topic '{topic}'. Respond professionally, thoughtfully, and convincingly, staying within the specified role."
+                   f"If the user's point challenges your position, provide a counterargument. Maintain a respectful tone throughout the discussion."
+        }
+
+    messages = [system_message]
+
+    # Adding conversation history
+    for val in history:
+        if val[0]:
+            messages.append({"role": "user", "content": val[0]})
+        if val[1]:
+            messages.append({"role": "assistant", "content": val[1]})
+
+    # Adding the current user input
+    messages.append({"role": "user", "content": message})
+
+    # Generating the response
+    response = ""
+    for message in client.chat_completion(
+            messages,
+            max_tokens=max_tokens,
+            stream=True,
+            temperature=temperature,
+            top_p=top_p,
+    ):
+        response += message.choices[0].delta.content
+    yield  response
+    print(f"{datetime.datetime.now()}::{messages[-1]['content']}->{response}\n")
+
+# Encode image function for logos (optional, kept for design)
+def encode_image(image_path):
+    with open(image_path, "rb") as image_file:
+        return base64.b64encode(image_file.read()).decode('utf-8')
+
+# Gradio interface
+global topic, position
+with gr.Blocks(theme=gr.themes.Ocean(font=[gr.themes.GoogleFont("Roboto Mono")]),
+               css='footer {visibility: hidden}') as demo:
+    gr.Markdown("# LLM Debate Participant")
+    with gr.Tabs():
+        with gr.TabItem("Debate Interface"):
+            with gr.Row():
+                topic = gr.Textbox(label="Debate Topic", placeholder="Enter the topic of the debate")
+                position = gr.Radio(["For", "Against"], label="Position", info="LLM's debate stance")
+            chatbot = gr.Chatbot(height=500)
+            debate_interface = gr.ChatInterface(debate_respond,
+                chatbot=chatbot,
+                examples=[
+                    "Why do you support this stance?",
+                    "Can you refute the opposing view on this topic?",
+                    "What evidence supports your position?"
+                ]
+            )
+    gr.HTML("<footer><p>LLM Debate Participant © 2024</p></footer>")
+
+if __name__ == "__main__":
+    demo.launch(share=True)