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import gradio as gr |
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from huggingface_hub import InferenceClient |
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client = InferenceClient("Pinkstack/Superthoughts-lite-v1") |
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def respond( |
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message, |
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history: list[tuple[str, str]], |
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system_message, |
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max_tokens, |
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temperature, |
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top_p, |
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): |
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messages = [{"role": "system", "content": system_message}] |
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for val in history: |
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if val[0]: |
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messages.append({"role": "user", "content": val[0]}) |
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if val[1]: |
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messages.append({"role": "assistant", "content": val[1]}) |
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messages.append({"role": "user", "content": message}) |
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response = "" |
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for message in client.chat_completion( |
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messages, |
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max_tokens=max_tokens, |
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stream=True, |
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temperature=temperature, |
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top_p=top_p, |
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): |
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token = message.choices[0].delta.content |
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response += token |
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yield response |
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def format_response(response): |
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response = response.replace("<think>", '<details><summary>Show thoughts</summary><div class="thoughts">') |
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response = response.replace("</think>", "</div></details>") |
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return response |
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css = """ |
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.thoughts { |
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border: 1px solid #ccc; |
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padding: 10px; |
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background-color: #f9f9f9; |
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border-radius: 5px; |
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} |
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details summary { |
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cursor: pointer; |
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padding: 5px; |
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background-color: #e0e0e0; |
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border-radius: 5px; |
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font-weight: bold; |
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} |
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details summary::-webkit-details-marker { |
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display: none; |
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} |
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details summary:after { |
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content: " ▶"; |
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} |
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details[open] summary:after { |
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content: " ▼"; |
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} |
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""" |
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with gr.Blocks(css=css) as demo: |
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gr.Markdown("## Chat with Superthoughts") |
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gr.Markdown("**Warning:** The first output from the AI may take a few moments. After the first message, it should work quickly.") |
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chatbot = gr.Chatbot() |
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msg = gr.Textbox() |
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system_message = gr.Textbox(value="You must always include <think> ... </think> <output> </output> tokens.", label="System message") |
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max_tokens = gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max new tokens") |
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temperature = gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature") |
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top_p = gr.Slider(minimum=0.1, maximum=1.0, value=0.95, step=0.05, label="Top-p (nucleus sampling)") |
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def user(user_message, history): |
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return "", history + [[user_message, None]] |
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def bot(history, system_message, max_tokens, temperature, top_p): |
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user_message, _ = history[-1] |
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response = "" |
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for partial_response in respond(user_message, history[:-1], system_message, max_tokens, temperature, top_p): |
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response = partial_response |
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formatted_response = format_response(response) |
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history[-1][1] = formatted_response |
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return history |
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msg.submit(user, [msg, chatbot], [msg, chatbot], queue=False).then( |
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bot, [chatbot, system_message, max_tokens, temperature, top_p], chatbot |
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) |
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demo.launch() |
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