Create app.py
Browse files
app.py
ADDED
@@ -0,0 +1,33 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
import streamlit as st
|
2 |
+
import requests
|
3 |
+
|
4 |
+
API_URL = "https://api-inference.huggingface.co/models/TaylorAI/gte-tiny"
|
5 |
+
headers = {"Authorization": "Bearer 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"}
|
6 |
+
|
7 |
+
def query(payload):
|
8 |
+
response = requests.post(API_URL, headers=headers, json=payload)
|
9 |
+
return response.json()
|
10 |
+
|
11 |
+
st.title("GTE Chat App")
|
12 |
+
|
13 |
+
# Create a text input for the user to enter their message
|
14 |
+
message = st.text_input("Enter your message:")
|
15 |
+
|
16 |
+
# Create a button to trigger the chatbot response
|
17 |
+
button = st.button("Send")
|
18 |
+
|
19 |
+
# When the button is clicked, call the query function with the user's message as the payload
|
20 |
+
if button:
|
21 |
+
output = query({
|
22 |
+
"inputs": {
|
23 |
+
"source_sentence": message,
|
24 |
+
"sentences": [
|
25 |
+
"That is a happy dog",
|
26 |
+
"That is a very happy person",
|
27 |
+
"Today is a sunny day"
|
28 |
+
]
|
29 |
+
},
|
30 |
+
})
|
31 |
+
|
32 |
+
# Print the chatbot's response
|
33 |
+
st.write(output)
|