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| """ | |
| Streamlit app for the research assistant. | |
| - Search: search arXiv by field | |
| - Digest: generate a digest of the latest papers | |
| - Ideate: generate project ideas | |
| """ | |
| import pathlib, tempfile | |
| import os | |
| # set up for Hugging Face Spaces | |
| CACHE_DIR = pathlib.Path(tempfile.gettempdir()) / "hf_cache" | |
| os.environ["XDG_CACHE_HOME"] = str(pathlib.Path(tempfile.gettempdir()) / "hf_cache") | |
| for var in ( | |
| "HF_HOME", | |
| "HF_HUB_CACHE", | |
| "TRANSFORMERS_CACHE", | |
| "SENTENCE_TRANSFORMERS_HOME", | |
| "TRITON_CACHE_DIR", | |
| ): | |
| os.environ[var] = str(CACHE_DIR) | |
| import streamlit as st | |
| from datetime import date | |
| from config import MAX_RESULTS | |
| from scrape import scrape | |
| from digest import build_html | |
| from ideate import ideate_from_topic, ideate_from_ids | |
| from helpers import render_rows, rows_by_tag | |
| from db import get_conn | |
| from summarise import summarise_by_tag | |
| st.set_page_config(page_title="Research Assistant", layout="wide") | |
| tab1, tab2, tab3 = st.tabs(["🔍 Search", "📑 Digest", "💡 Ideate"]) | |
| with tab1: | |
| st.header("Search for papers you have not yet read") | |
| c1, c2, c3, c4 = st.columns(4) | |
| topic = c1.text_input("Topic") | |
| title = c2.text_input("Title") | |
| author = c3.text_input("Author") | |
| category = c4.text_input("Category (e.g. cs.CL)") | |
| k = st.slider("Max papers", 5, 50, 25) | |
| if st.button("Run search"): | |
| with st.spinner("Finding new papers for your search..."): | |
| search_results = scrape(max_results=k, topic=topic, title=title, | |
| author=author, category=category) | |
| if search_results: | |
| st.success(f"Found {len(search_results)} new papers for your search!") | |
| # Convert search results to the format expected by render_rows | |
| paper_rows = [(p['title'], p['authors'], p['abstract'], p['published']) | |
| for p in search_results] | |
| st.components.v1.html(render_rows(paper_rows), height=600, scrolling=True) | |
| else: | |
| st.info("No new papers found for this search. All recent papers on this topic are already in your database.") | |
| with tab2: | |
| st.header("Get a digest from the latest papers you have previously scraped") | |
| d_topic = st.text_input("Keyword to match tags", value="large language") | |
| if st.button("Generate digest"): | |
| with st.spinner("Finding papers and summarising them..."): | |
| summarise_by_tag(d_topic) | |
| rows = rows_by_tag(d_topic, MAX_RESULTS) | |
| if not rows: | |
| st.info("No papers found; try the Search tab.") | |
| else: | |
| st.components.v1.html(render_rows(rows), height=800, scrolling=True) | |
| with tab3: | |
| st.header("Brainstorm new research ideas based on previously scraped papers") | |
| mode = st.radio("Context source", ["Keyword", "ArXiv IDs"]) | |
| if mode == "Keyword": | |
| kw = st.text_input("Keyword") | |
| if st.button("Ideate"): | |
| with st.spinner("Thinking of new ideas..."): | |
| ideas = ideate_from_topic(kw) | |
| if ideas is None: | |
| st.info("No papers in the database match that keyword. " | |
| "Try running a search in the **Search** tab first.") | |
| else: | |
| st.markdown(f"```\n{ideas}\n```") | |
| else: | |
| ids_in = st.text_area("Comma-separated IDs", | |
| placeholder="2406.01234,2405.01234") | |
| if st.button("Ideate"): | |
| with st.spinner("Thinking of new ideas..."): | |
| ids = [x.strip() for x in ids_in.split(",") if x.strip()] | |
| ideas = ideate_from_ids(ids) | |
| if ideas is None: | |
| st.info("Those IDs aren't in the database yet. " | |
| "Fetch them via the Search tab, then try again.") | |
| else: | |
| st.markdown(f"```\n{ideas}\n```") | |