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import gradio as gr
from huggingface_hub import InferenceClient
# Initialize the InferenceClient with the model hosted on Hugging Face Hub
client = InferenceClient("deepseek-ai/DeepSeek-R1")
def respond(message, history: list[tuple[str, str]]):
# System message and generation parameters
system_message = "You are a friendly Chatbot."
max_tokens = 2048
temperature = 0.7
top_p = 0.95
# Prepare the conversation history
messages = [{"role": "system", "content": system_message}]
for user_msg, assistant_msg in history:
if user_msg:
messages.append({"role": "user", "content": user_msg})
if assistant_msg:
messages.append({"role": "assistant", "content": assistant_msg})
# Add the current user message
messages.append({"role": "user", "content": message})
# Stream the response from the model
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
# Custom button actions
def retry_last_message(history):
if history:
return history[:-1] # Remove the last assistant response
return history
def undo_last_interaction(history):
if history:
return history[:-1] # Remove the last user-assistant interaction
return history
def clear_chat(history):
return [] # Clear the entire chat history
# Create the Gradio ChatInterface with custom buttons
with gr.Blocks() as demo:
chatbot = gr.Chatbot(label="Chat with DeepSeek-R1")
msg = gr.Textbox(label="Your Message")
clear = gr.Button("Clear")
undo = gr.Button("Undo")
retry = gr.Button("Retry")
# Define button actions
clear.click(clear_chat, chatbot, chatbot)
undo.click(undo_last_interaction, chatbot, chatbot)
retry.click(retry_last_message, chatbot, chatbot)
# Handle user input and chatbot responses
msg.submit(respond, [msg, chatbot], chatbot)
# Launch the Gradio app
if __name__ == "__main__":
demo.launch() |