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import streamlit as st
import os
from huggingface_hub import InferenceClient
# Get token from Space secrets
API_TOKEN = os.getenv("HF_TOKEN")
# Initialize the Inference Client
client = InferenceClient(token=API_TOKEN)
# Title of the app
st.title("Sentence Improver App")
# Text input from the user
user_input = st.text_input("Enter a sentence to improve:", "I goed to the park and play.")
# Button to trigger the correction
if st.button("Improve Sentence"):
if user_input:
# Create a prompt for the LLM to improve the sentence
prompt = f"Correct and improve this sentence: '{user_input}'"
# Call the LLM via Hugging Face Inference API
try:
response = client.text_generation(
prompt,
model="mistralai/Mixtral-8x7B-Instruct-v0.1", # You can change this to another model
#model="deepseek-ai/deepseek-coder-6.7b-instruct",
max_new_tokens=100,
temperature=0.7,
)
# Extract the improved sentence (remove the prompt part if included)
improved_sentence = response.strip()
st.write("Improved Sentence:", improved_sentence)
except Exception as e:
st.error(f"Error calling the LLM: {str(e)}")
else:
st.warning("Please enter a sentence first!")
else:
st.write("Enter a sentence and click the button to see it improved!")
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