import streamlit as st
from transformers import pipeline
import requests
from bs4 import BeautifulSoup

SCITE_API_KEY = st.secrets["SCITE_API_KEY"]

def remove_html(x):
    soup = BeautifulSoup(x, 'html.parser')
    text = soup.get_text()
    return text

def search(term, limit=25):
    search = f"https://api.scite.ai/search?mode=citations&term={term}&limit={limit}&offset=0&user_slug=domenic-rosati-keW5&compute_aggregations=false"
    req = requests.get(
        search,
        headers={
            'Authorization': f'Bearer {SCITE_API_KEY}'
        }
    )
    return (
        remove_html('\n'.join(['\n'.join([cite['snippet'] for cite in doc['citations']]) for doc in req.json()['hits']])),
        [(doc['doi'], doc['citations'], doc['title']) for doc in req.json()['hits']]
    )


def find_source(text, docs):
    for doc in docs:
        if text in remove_html(doc[1][0]['snippet']):
            new_text = text
            for snip in remove_html(doc[1][0]['snippet']).split('.'):
                if text in snip:
                    new_text = snip
            return {
                'citation_statement': doc[1][0]['snippet'].replace('<strong class="highlight">', '').replace('</strong>', ''),
                'text': new_text,
                'from': doc[1][0]['source'],
                'supporting': doc[1][0]['target'],
                'source_title': doc[2],
                'source_link': f"https://scite.ai/reports/{doc[0]}"
            }
    return {
            'citation_statement': '',
            'text': text,
            'from': '',
            'supporting': '',
            'source_title': '',
            'source_link': ''
        }

@st.experimental_singleton
def init_models():
    question_answerer = pipeline("question-answering", model='sultan/BioM-ELECTRA-Large-SQuAD2-BioASQ8B')
    return question_answerer

qa_model = init_models()


def card(title, context, score, link):
    return st.markdown(f"""
    <div class="container-fluid">
        <div class="row align-items-start">
             <div  class="col-md-12 col-sm-12">
                 <br>
                 <span>
                     {context}
                     [<b>Score: </b>{score}]
                 </span>
                 <br>
                 <b>From <a href="{link}">{title}</a></b>
             </div>
        </div>
     </div>
        """, unsafe_allow_html=True)

st.title("Scientific Question Answering with Citations")

st.write("""
Ask a scientific question and get an answer drawn from [scite.ai](https://scite.ai) corpus of over 1.1bn citation statements.
Answers are linked to source documents containing citations where users can explore further evidence from scientific literature for the answer.
""")

st.markdown("""
<link rel="stylesheet" href="https://cdn.jsdelivr.net/npm/bootstrap@4.0.0/dist/css/bootstrap.min.css" integrity="sha384-Gn5384xqQ1aoWXA+058RXPxPg6fy4IWvTNh0E263XmFcJlSAwiGgFAW/dAiS6JXm" crossorigin="anonymous">
""", unsafe_allow_html=True)

def run_query(query):
    context, orig_docs = search(query)
    if not context.strip():
        return st.markdown("""
        <div class="container-fluid">
        <div class="row align-items-start">
             <div  class="col-md-12 col-sm-12">
            Sorry... no results for that question! Try another...
         </div>
        </div>
     </div>
        """, unsafe_allow_html=True)

    results = []
    model_results = qa_model(question=query, context=context, top_k=10)
    for result in model_results:
        support = find_source(result['answer'], orig_docs)
        results.append({
            "answer": support['text'],
            "title": support['source_title'],
            "link": support['source_link'],
            "context": support['citation_statement'],
            "score": result['score']
        })



    sorted_result = sorted(results, key=lambda x: x['score'], reverse=True)
    sorted_result = list({
        result['context']: result for result in sorted_result
    }.values())
    sorted_result = sorted(sorted_result, key=lambda x: x['score'], reverse=True)


    for r in sorted_result:
        answer = r["answer"]
        ctx = remove_html(r["context"]).replace(answer, f"<mark>{answer}</mark>").replace('<cite', '<a').replace('</cite', '</a').replace('data-doi="', 'href="https://scite.ai/reports/')
        title = r["title"].replace("_", " ")
        score = round(r["score"], 4)
        card(title, ctx, score, r['link'])

query = st.text_input("Ask scientific literature a question", "")

if query != "":
    run_query(query)