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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("HuggingFaceH4/zephyr-7b-beta") | |
| #client = InferenceClient("meta-llama/Llama-3.2-1B-Instruct") | |
| #client = InferenceClient("microsoft/Phi-3.5-mini-instruct") | |
| client = InferenceClient("unsloth/Llama-3.2-1B-Instruct") | |
| def respond( | |
| message, | |
| history: list[tuple[str, str]], | |
| system_message, | |
| max_tokens, | |
| temperature, | |
| top_p, | |
| ): | |
| messages = [{"role": "system", "content": system_message}] | |
| for val in history: | |
| if val[0]: | |
| messages.append({"role": "user", "content": val[0]}) | |
| if val[1]: | |
| messages.append({"role": "assistant", "content": val[1]}) | |
| messages.append({"role": "user", "content": message}) | |
| response = "" | |
| try: | |
| for message in client.chat_completion( | |
| messages, | |
| max_tokens=max_tokens, | |
| stream=True, | |
| temperature=temperature, | |
| top_p=top_p, | |
| ): | |
| # Ensure the message has a valid structure | |
| if not message or not isinstance(message, dict): | |
| continue | |
| try: | |
| # Extract content and finish reason | |
| content = message.choices[0].delta.content | |
| finish_reason = message.choices[0].finish_reason | |
| # Check if the content is empty | |
| if content.strip() == "": | |
| # If the finish reason is 'stop', it's expected and we can break the loop | |
| if finish_reason == "stop": | |
| print("Stream ended normally.") | |
| break | |
| else: | |
| print("Received unexpected empty content, skipping...") | |
| continue | |
| response += content | |
| yield response | |
| except (AttributeError, IndexError, KeyError) as e: | |
| print(f"Error processing message: {e}") | |
| continue | |
| except Exception as e: | |
| print(f"Unexpected error: {e}") | |
| yield "An error occurred while generating the response." | |
| # Final check if the response is empty | |
| if response.strip() == "": | |
| yield "No response generated. Please try again or adjust the settings." | |
| """ | |
| 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. Your name is Juninho.", 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() | |