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import os
from dotenv import load_dotenv
import json
import streamlit as st
from huggingface_hub import InferenceApi, login, InferenceClient
# Get the Hugging Face token from environment variables
load_dotenv()
hf_token = os.getenv("HF_TOKEN")
if hf_token is None:
raise ValueError("Hugging Face token not found. Please set the HF_TOKEN environment variable.")
# Authenticate with Hugging Face
login(hf_token)
# Model information and links
model_links = {
"Zephyr-7B": "HuggingFaceH4/zephyr-7b-beta"
}
model_info = {
"Zephyr-7B": {
'description': """Zephyr 7B is a Huggingface model, fine-tuned for helpful and instructive interactions.""",
'logo': 'https://huggingface.co/HuggingFaceH4/zephyr-7b-alpha/resolve/main/thumbnail.png'
}
}
# Inference API Initialization
client = InferenceClient('HuggingFaceH4/zephyr-7b-beta')
# Reset conversation button
def reset_conversation():
return [
{"role": "system", "content": "You are a knowledgeable and empathetic ornithologist assistant providing accurate and relevant information based on user input."}
]
# Initialize conversation and chat history
messages = reset_conversation()
# Display chat history
for message in messages:
with st.chat_message(message["role"]):
st.markdown(message["content"])
def respond(message, history, max_tokens, temperature, top_p):
# Prepare the list of messages for the chat completion
messages = [{"role": "system", "content": history[0]["content"]}]
for val in history:
if val["role"] == "user":
messages.append({"role": "user", "content": val["content"]})
elif val["role"] == "assistant":
messages.append({"role": "assistant", "content": val["content"]})
messages.append({"role": "user", "content": message})
# Generate response
response = ""
response_container = st.empty() # Placeholder to update the response text dynamically
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
# response_container.text(response) # Stream the response
return response
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