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Sleeping
| # app.py | |
| # GPT Chatbot with thinking mode | |
| # Users enter their HF_API_TOKEN in the UI | |
| # Ready for Hugging Face Spaces | |
| import time | |
| import gradio as gr | |
| from huggingface_hub import InferenceClient | |
| # ----------------------- | |
| # Configuration | |
| # ----------------------- | |
| GPT_MODEL_ID = "HuggingFaceH4/zephyr-7b-beta" # default model, can change | |
| # ----------------------- | |
| # Chatbot Core | |
| # ----------------------- | |
| def gpt_chat(prompt, history, thinking, thinking_time, hf_token): | |
| """ | |
| Generate a chat response using Hugging Face Inference API. | |
| Users provide their own HF_API_TOKEN. | |
| """ | |
| if not hf_token or hf_token.strip() == "": | |
| return history, "❌ Please enter your Hugging Face API Token." | |
| if not prompt.strip(): | |
| return history, "Please write a message." | |
| # Initialize client | |
| try: | |
| client = InferenceClient(model=GPT_MODEL_ID, token=hf_token) | |
| except Exception as e: | |
| return history, f"Error creating HF client: {str(e)}" | |
| # Append user message to history | |
| history = history + [(prompt, None)] | |
| # Simulate thinking | |
| if thinking: | |
| time.sleep(max(0.0, thinking_time)) | |
| try: | |
| # Build conversation prompt | |
| conversation_text = "" | |
| for user_msg, bot_msg in history: | |
| if bot_msg is not None: | |
| conversation_text += f"User: {user_msg}\nAssistant: {bot_msg}\n" | |
| conversation_text += f"User: {prompt}\nAssistant:" | |
| # Generate response | |
| response = client.text_generation( | |
| prompt=conversation_text, | |
| max_new_tokens=200, | |
| temperature=0.7, | |
| do_sample=True | |
| ) | |
| answer = response.replace(conversation_text, "").strip() | |
| if "Assistant:" in answer: | |
| answer = answer.split("Assistant:")[-1].strip() | |
| # Update last entry in history | |
| history = history[:-1] + [(prompt, answer)] | |
| return history, "OK" | |
| except Exception as e: | |
| history = history[:-1] + [(prompt, "⚠ Error generating response.")] | |
| return history, str(e) | |
| # ----------------------- | |
| # Gradio UI | |
| # ----------------------- | |
| with gr.Blocks(title="ThinkPad - Chatbot") as demo: | |
| gr.Markdown(""" | |
| # 🤖 ThinkPad Chatbot | |
| Enter your Hugging Face API Token below to start chatting. | |
| Built with ❤️ by [JumpLander](https://jumplander.org) | |
| """) | |
| with gr.Row(): | |
| with gr.Column(scale=2): | |
| chatbot = gr.Chatbot(label="Chat") | |
| user_input = gr.Textbox(show_label=False, placeholder="Write a message and press Send") | |
| hf_token_input = gr.Textbox( | |
| label="Hugging Face API Token", | |
| placeholder="Paste your HF_API_TOKEN here", | |
| type="password" | |
| ) | |
| thinking_mode = gr.Checkbox(label="Thinking mode", value=True) | |
| thinking_time = gr.Slider(0, 5, value=2.0, step=0.5, label="Thinking time (seconds)") | |
| status_box = gr.Textbox(label="Status") | |
| send_btn = gr.Button("Send") | |
| # handle send | |
| def respond(history, msg, thinking, thinking_t, hf_token): | |
| return gpt_chat(msg, history or [], thinking, thinking_t, hf_token) | |
| send_btn.click(respond, inputs=[chatbot, user_input, thinking_mode, thinking_time, hf_token_input], outputs=[chatbot, status_box]) | |
| user_input.submit(respond, inputs=[chatbot, user_input, thinking_mode, thinking_time, hf_token_input], outputs=[chatbot, status_box]) | |
| if __name__ == "__main__": | |
| demo.launch() | |