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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("gpt-omni/mini-omni2") | |
#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() |