File size: 939 Bytes
a666253
03b119a
dab1ed6
b7d7bd0
a666253
03b119a
eaaef65
 
 
a0e69d5
a666253
03b119a
 
 
a8841fa
 
 
 
03b119a
 
 
a8841fa
03b119a
 
 
 
 
 
 
 
 
 
a0e69d5
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
import os
import streamlit as st
import requests


# Set up Hugging Face API details
#token=os.getenv("HF_TOKEN", None)
st.write("Hello")
#st.write(token)
'''
headers = {"Authorization": f"Bearer {token}"}
API_URL = "https://api-inference.huggingface.co/models/facebook/bart-large-cnn"

# Function to query the Hugging Face model
def query(payload):
    response = requests.post(API_URL, headers=headers, json=payload)
    return response.json()

# Streamlit UI
st.title("Chat App with Hugging Face")
user_input = st.text_input("You:", "")

if st.button("Send"):
    if user_input.strip() != "":
        # Query Hugging Face model
        data = query({"inputs": user_input, "parameters": {"do_sample": False}})
        
        # Display response
        if data and "summary_text" in data[0]:
            st.text_area("Bot:", value=data[0]["summary_text"], height=150)
        else:
            st.error("No response from the model")
'''