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import os
import streamlit as st
import requests
# Retrieve Hugging Face API token from environment variable
API_TOKEN = os.environ.get("HUGGING_FACE_API_TOKEN")
# Define the Hugging Face API URL
API_URL = "https://api-inference.huggingface.co/models/meta-llama/Meta-Llama-3-8B"
headers = {"Authorization": f"Bearer {API_TOKEN}"}
# Function to query the Hugging Face API
def query(payload):
response = requests.post(API_URL, headers=headers, json=payload)
return response.json()
# Streamlit app
def main():
st.title("SQL Query Generator")
# User prompt input
prompt = st.text_input("Enter your prompt:")
# Button to generate SQL query
if st.button("Generate SQL Query"):
# Generate payload for Hugging Face API
payload = {"inputs": prompt}
# Query the Hugging Face API
with st.spinner('Generating SQL query...'):
output = query(payload)
# Display the SQL query response
if "generated_text" in output:
st.write("Generated SQL Query:")
st.code(output["generated_text"])
else:
st.error("Failed to generate SQL query. Please try again.")
if __name__ == "__main__":
main()
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