| import gradio as gr |
| from huggingface_hub import InferenceClient |
| from transformers import pipeline |
|
|
|
|
| """ |
| 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 |
| """ |
| print("starting") |
| |
| model_name = "microsoft/Phi-3.5-mini-instruct" |
| chat_model = pipeline("text-generation", model=model_name) |
| print("Defining function") |
| def respond( |
| message, |
| history: list[tuple[str, str]], |
| system_message, |
| max_tokens, |
| ): |
| print("Enter respond") |
| messages = [{"role": "system", "content": system_message}] |
|
|
| messages.append({"role": "user", "content": message}) |
| print("getting response", messages) |
| response = chat_model(messages) |
| print("got response",response) |
| return response[-1]['generated_text'][-1]['content'] |
|
|
| """ |
| 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"), |
|
|
| ], |
| ) |
|
|
|
|
| if __name__ == "__main__": |
| demo.launch() |
|
|
