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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("unsloth/Llama-3.2-1B-Instruct")
#client = InferenceClient(model="https://aq0teqpujnx3bv68.us-east-1.aws.endpoints.huggingface.cloud/")
import requests
API_URL = "https://aq0teqpujnx3bv68.us-east-1.aws.endpoints.huggingface.cloud"
headers = {
"Accept" : "application/json",
"Content-Type": "application/json"
}
def query(payload):
response = requests.post(API_URL, headers=headers, json=payload)
return response.json()
def respond(
message,
history: list[tuple[str, str]],
# system_message,
# max_tokens,
# temperature,
# top_p,
):
system_message = "You are a Dietician Assistant specializing in providing general guidance on diet, "
"nutrition, and healthy eating habits. Answer questions thoroughly with scientifically "
"backed advice, practical tips, and easy-to-understand explanations. Keep in mind that "
"your role is to assist, not replace a registered dietitian, so kindly remind users to "
"consult a professional for personalized advice when necessary."
max_tokens = 512
temperature = 0.7
top_p = 0.95
for message in query({
"inputs":system_message + "\n\n" + message,
"parameters": {
"max_new_tokens": 150
}
}):
print(message)
token = message
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(
fn=respond,
#title="Hi there! I'm your Dietician Assistant, here to help you with general advice on diet, nutrition, and healthy eating habits. Let's explore your questions.",
title="Your Personal Dietician Assistant: Expert Guidance on Healthy Eating and Nutrition",
examples=["What are some healthy snacks I can eat if I feel hungry between meals?",
"How can I improve my gut health through diet?",
"Can you recommend some high-protein vegetarian meals?"]
# 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() |