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import streamlit as st
import time
import requests
import os
from huggingface_hub import InferenceClient
# Hugging Face API Setup
API_TOKEN = os.environ.get("HUGGINGFACE_API_TOKEN")
GPT2XL_API_URL = "https://api-inference.huggingface.co/models/openai-community/gpt2-xl"
MISTRAL_MODEL_NAME = "mistralai/Mistral-7B-Instruct-v0.3"
client = InferenceClient(api_key=API_TOKEN)
# Query GPT-2 XL
def query_from_gpt2xl(text: str):
headers = {"Authorization": f"Bearer {API_TOKEN}"}
while True:
response = requests.post(GPT2XL_API_URL, headers=headers, json={"inputs": text})
response_data = response.json()
if "error" in response_data and "loading" in response_data["error"]:
wait_time = response_data.get("estimated_time", 10)
st.info(f"Model is loading. Waiting for {wait_time:.2f} seconds...")
time.sleep(wait_time)
else:
return response_data[0]["generated_text"]
# Query Mistral
def query_from_mistral(text: str):
messages = [{"role": "user", "content": text}]
completion = client.chat.completions.create(
model=MISTRAL_MODEL_NAME,
messages=messages,
max_tokens=500,
)
return completion.choices[0].message["content"]
def main():
st.set_page_config(page_title="Multi-Model Chat", layout="centered")
st.title("πŸ€– Multi-Model Chat")
st.markdown("Chat with either **GPT-2 XL** or **Mistral-7B-Instruct** via Hugging Face API.")
if "messages" not in st.session_state:
st.session_state.messages = []
model_choice = st.selectbox("Select a model:", ["GPT-2 XL", "Mistral-7B-Instruct"])
with st.form(key="chat_form", clear_on_submit=True):
user_input = st.text_input("You:", "")
submit = st.form_submit_button("Send")
if submit and user_input:
st.session_state.messages.append({"role": "user", "content": user_input})
with st.spinner("Fetching response..."):
try:
if model_choice == "GPT-2 XL":
response = query_from_gpt2xl(user_input)
elif model_choice == "Mistral-7B-Instruct":
response = query_from_mistral(user_input)
st.session_state.messages.append({"role": "bot", "content": response})
except Exception as e:
st.error(f"Error: {e}")
for message in st.session_state.messages:
if message["role"] == "user":
st.markdown(f"**You:** {message['content']}")
elif message["role"] == "bot":
st.markdown(f"**Bot:** {message['content']}")
if __name__ == "__main__":
main()