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| import gradio as gr | |
| from huggingface_hub import InferenceClient | |
| """ | |
| 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("R3troR0b/What-If-Explorer") | |
| def respond( | |
| message, | |
| history: list[tuple[str, str]], | |
| system_message, | |
| max_tokens, | |
| temperature, | |
| top_p, | |
| ): | |
| # Prepare the prompt based on the message and history | |
| prompt = system_message + "\n" | |
| for val in history: | |
| if val[0]: | |
| prompt += "User: " + val[0] + "\n" | |
| if val[1]: | |
| prompt += "Assistant: " + val[1] + "\n" | |
| prompt += "User: " + message + "\nAssistant:" | |
| response = "" | |
| # Prevent infinite loops by limiting history and avoiding repeated responses | |
| if len(history) > 5: # Limit history to the last 5 exchanges | |
| history = history[-5:] | |
| # Detect if responses are getting repetitive and stop the loop | |
| if len(set([h[1] for h in history])) == 1: # All assistant's responses are the same | |
| yield "It seems we're repeating ourselves. Let's move to a new topic." | |
| return | |
| # Use text-generation instead of chat-completion | |
| for message in client.text_generation( | |
| prompt=prompt, | |
| max_new_tokens=max_tokens, | |
| temperature=temperature, | |
| top_p=top_p, | |
| stream=True, | |
| ): | |
| # Since the message is a string, no need for indexing | |
| token = message.replace(prompt, '') | |
| response += token | |
| yield response | |
| """ | |
| For information on how to customize the ChatInterface, peruse the gradio docs: https://www.gradio.app/docs/chatinterface | |
| """ | |
| demo = gr.ChatInterface( | |
| respond, | |
| additional_inputs=[ | |
| gr.Textbox(value="You are a friendly Chatbot.", label="System message"), | |
| 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)", | |
| ), | |
| ], | |
| ) | |
| if __name__ == "__main__": | |
| demo.launch() | |