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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("AuriLab/gpt-bi-instruct-cesar") | |
def respond( | |
message, | |
history: list[tuple[str, str]], | |
): | |
messages = [{"role": "system", "content": "Gpt-Bi zara, AuriLabsek sortutako assitente digitala."}] | |
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 = "" | |
for message in client.chat_completion( | |
messages, | |
max_tokens=60, | |
stream=True, | |
temperature=0.7, | |
top_p=0.85, | |
): | |
token = message.choices[0].delta.content | |
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, | |
title="GPT-BI Instruct", | |
) | |
if __name__ == "__main__": | |
demo.launch() | |