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import numpy as np | |
import requests | |
import streamlit as st | |
def main(): | |
st.title("Scientific Question Generation") | |
API_URL = "https://api-inference.huggingface.co/models/dhmeltzer/bart-large_askscience-qg" | |
headers = {"Authorization": "Bearer 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"} | |
def query(payload): | |
response = requests.post(API_URL, | |
headers=headers, | |
json=payload) | |
return response.json() | |
# User search | |
user_input = st.text_area("Question Generator", | |
"""Black holes are the most \ | |
gravitationally dense objects in the universe.""") | |
# Filters | |
st.sidebar.markdown("**Filters**") | |
temperature = st.sidebar.slider("Temperature", 0.0, 1.0, 0.0,.1) | |
num_results = st.sidebar.slider("Number of search results", 1, 50, 1) | |
vector = query([user_input]) | |
if user_input: | |
output = query({ | |
"inputs": user_input, | |
"temperature":temperature, | |
"wait_for_model":True}) | |
st.write(output) | |
if __name__ == "__main__": | |
main() | |