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| 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': '' | |
| } | |
| 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) | |