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import streamlit as st | |
import requests | |
# Function to query the Hugging Face model | |
def query(data): | |
headers = { | |
"Content-Type": "application/json", | |
"Authorization": "Bearer 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" | |
} | |
response = requests.post( | |
"https://api-inference.huggingface.co/models/h2oai/h2ogpt-gm-oasst1-en-1024-12b", | |
headers=headers, | |
json={"inputs": data} | |
) | |
result = response.json() | |
return result.get("generated_text", "No response") | |
# Streamlit app | |
def main(): | |
st.title("Hugging Face Chatbot") | |
st.write("Enter a message to chat with the model:") | |
# Input text box | |
user_input = st.text_area("Your Message", "") | |
if st.button("Submit"): | |
if user_input: | |
st.write("User: ", user_input) | |
try: | |
response = query(user_input) | |
st.write("Chatbot: ", response) | |
except Exception as e: | |
st.error(f"An error occurred: {str(e)}") | |
if __name__ == "__main__": | |
main() | |