import streamlit as st
from transformers import pipeline, AutoTokenizer, AutoModelForSequenceClassification
from datasets import load_dataset

dataset = load_dataset('HUPD/hupd',
    name='sample',
    data_files="https://huggingface.co/datasets/HUPD/hupd/blob/main/hupd_metadata_2022-02-22.feather", 
    icpr_label=None,
    train_filing_start_date='2016-01-01',
    train_filing_end_date='2016-01-01',
    val_filing_start_date='2016-01-30',
    val_filing_end_date='2016-01-31',
)
p_number = dataset["validation"]["patent_number"][:10]
p_abstract = dataset["validation"]["abstract"][:10]
p_claims = dataset["validation"]["claims"][:10]
p_decision = dataset["validation"]["decision"][:10]

# Streamlit app
st.title("Patentability Score")
selected_model = st.selectbox("App. ID:", p_number)


# st.write("Select a patent application ID")
# text = st.text_input("Text:", "I love you!")
# # Prepare analysis model, tokenizer and pipeline
# def get_pipeline(selected_model):
#     model = AutoModelForSequenceClassification.from_pretrained(selected_model)
#     tokenizer = AutoTokenizer.from_pretrained(selected_model)
#     pl = pipeline("sentiment-analysis", model=model, tokenizer=tokenizer)
#     return pl

# # Load the model and perform sentiment analysis
# if st.button("Submit"):
#     with st.spinner("Analyzing sentiment..."):
#         pl = get_pipeline(selected_model)
#         result = pl(text)
#         label = result[0]['label']
#         if(selected_model == "cardiffnlp/twitter-roberta-base-sentiment"):
#             if label == "LABEL_0": st.write("Sentiment: Negative")
#             elif label == "LABEL_1": st.write("Sentiment: Neutral")
#             elif label == "LABEL_2": st.write("Sentiment: Positive")
#         elif(selected_model == "textattack/bert-base-uncased-SST-2"):
#             if label == "LABEL_0": st.write("Sentiment: Negative")
#             elif label == "LABEL_1": st.write("Sentiment: Positive")
#         else:
#             st.write(f"Sentiment: {label}")
#         st.write(f"Confidence Score: {result[0]['score']:.2f}")
# else:
#     st.write("Click 'Submit' for sentiment analysis.")