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import gradio as gr | |
from huggingface_hub import InferenceClient | |
import google.generativeai as genai | |
from pathlib import Path | |
# Set up the model | |
generation_config = { | |
"temperature": 0, | |
"top_p": 1, | |
"top_k": 32, | |
"max_output_tokens": 4096, | |
} | |
safety_settings = [ | |
{ | |
"category": "HARM_CATEGORY_HARASSMENT", | |
"threshold": "BLOCK_MEDIUM_AND_ABOVE" | |
}, | |
{ | |
"category": "HARM_CATEGORY_HATE_SPEECH", | |
"threshold": "BLOCK_MEDIUM_AND_ABOVE" | |
}, | |
{ | |
"category": "HARM_CATEGORY_SEXUALLY_EXPLICIT", | |
"threshold": "BLOCK_MEDIUM_AND_ABOVE" | |
}, | |
{ | |
"category": "HARM_CATEGORY_DANGEROUS_CONTENT", | |
"threshold": "BLOCK_MEDIUM_AND_ABOVE" | |
} | |
] | |
genai.configure(api_key = "AIzaSyCi0mbXfp0uEBZpK7n-YnqR9tXT0tyXSM0") | |
model = genai.GenerativeModel(model_name = "gemini-pro-vision", | |
generation_config = generation_config, | |
safety_settings = safety_settings) | |
input_prompt = """ You are a highly renowned health and nutrition expert FitnessGPT. Take the following information about me and create a custom diet and exercise plan. I am #Age years old, #gender gender, #height inches tall. My current weight is #currentweight weight in pounds. My current medical conditions are #medicalconditions. I have food allergies to #foodallergies. My primary fitness and health goals are #fitnessgoals and #fitnessgoals. I can commit to working out #daysperweek days per week. I prefer and enjoy this type of workout - #typeofworkout and #typeofworkout. I have a diet preference of #dietpreference. I want to have #numbersofmeals Meals and #numbersofmeals Snacks per day. I dislike and cannot eat #foodyoudislike. Create a summary of my diet and exercise plan. Create a detailed workout program for my exercise plan. Create a detailed Meal Plan for my diet. Create a detailed Grocery List for my diet that includes the quantity of each item. Avoid any superfluous pre and post-descriptive text. Don't break character under any circumstance. """ | |
client = InferenceClient("HuggingFaceH4/zephyr-7b-beta") | |
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 = "" | |
for message in client.chat_completion( | |
messages, | |
max_tokens=max_tokens, | |
stream=True, | |
temperature=temperature, | |
top_p=top_p, | |
): | |
token = message.choices[0].delta.content | |
response += token | |
yield response | |
demo = gr.ChatInterface( | |
respond, | |
additional_inputs=[ | |
gr.Textbox(value="You are a FitnessGPT.", 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() |