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import streamlit as st
from gradio_client import Client
# Constants
TITLE = "Llama2 70B Chatbot"
DESCRIPTION = """
This Space demonstrates model [Llama-2-70b-chat-hf](https://huggingface.co/meta-llama/Llama-2-70b-chat-hf) by Meta,
a Llama 2 model with 70B parameters fine-tuned for chat instructions.
"""
# Initialize client
client = Client("https://ysharma-explore-llamav2-with-tgi.hf.space/")
# Prediction function
def predict(message, system_prompt="", temperature=0.9, max_new_tokens=4096):
return client.predict(
message=message,
system_prompt=system_prompt,
temperature=temperature,
max_new_tokens=max_new_tokens,
api_name="/chat"
)
# Streamlit UI
st.title(TITLE)
st.write(DESCRIPTION)
# Input fields
message = st.text_area("Enter your message:", "")
system_prompt = st.text_area("Optional system prompt:", "")
temperature = st.slider("Temperature", min_value=0.0, max_value=1.0, value=0.9, step=0.05)
max_new_tokens = st.slider("Max new tokens", min_value=0, max_value=4096, value=4096, step=64)
if st.button("Predict"):
response = predict(message, system_prompt, temperature, max_new_tokens)
st.write("Response:", response)
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