diff --git a/streamlit_app.py b/streamlit_app.py
index 68e7df0f..84069dee 100644
--- a/streamlit_app.py
+++ b/streamlit_app.py
@@ -1,1156 +1,1162 @@
-import os
-import io
-import re
-import tempfile
-import uuid
-from datetime import datetime, timedelta
-from typing import Optional, List, Dict
-
-import streamlit as st
-from fpdf import FPDF
-
-# Import project modules
-from paperscope.main import fetch_and_summarize, query_db
-from paperscope.pdf_parser import extract_text_from_pdf
-from paperscope.vector_store import build_index, search_similar
-
-# Optional: history storage API
-try:
- from paperscope.storage import get_history, clear_history, delete_entry, save_history_entry
- STORAGE_AVAILABLE = True
-except ImportError:
- STORAGE_AVAILABLE = False
- def get_history():
- return []
- def clear_history():
- pass
- def delete_entry(entry_id):
- return False
- def save_history_entry(entry):
- pass
-
-# Check for demo mode
-DEMO_MODE = os.getenv("DEMO_MODE", "").lower() in ("1", "true", "yes")
-if DEMO_MODE:
- from paperscope.summarizer_demo import summarize
-else:
- from paperscope.summarizer import summarize
-
-# Application configuration
-st.set_page_config(page_title="PaperScope", page_icon="📄", layout="wide")
-
-# ---------------------------------------------------------------------
-# Utility helpers
-# ---------------------------------------------------------------------
-
-def safe_filename(filename: str) -> str:
- """Sanitize a filename for safe filesystem/download use."""
- if not filename:
- return "file"
- filename = filename.split("/")[-1].split("\\")[-1]
- filename = re.sub(r"[^\w\-_.]", "_", filename)
- return filename[:200]
-
-
-def generate_pdf_from_text(title: str, metadata: dict, body_text: str, annotations: str = ""):
- """Generate a Unicode-safe PDF summary report using fpdf2."""
- pdf = FPDF()
- pdf.add_page()
-
- font_path = os.path.join(os.path.dirname(__file__), "paperscope", "DejaVuSans.ttf")
- if os.path.exists(font_path):
- pdf.add_font("DejaVu", "", font_path, uni=True)
- pdf.set_font("DejaVu", "", 16)
- else:
- pdf.set_font("Helvetica", "", 16)
-
- pdf.cell(0, 10, txt=title[:100], ln=True, align="C")
- pdf.ln(10)
-
- if os.path.exists(font_path):
- pdf.set_font("DejaVu", "", 12)
- else:
- pdf.set_font("Helvetica", "", 12)
-
- if metadata:
- for key, value in metadata.items():
- pdf.multi_cell(0, 8, f"{key}: {str(value)[:100]}")
- pdf.ln(6)
-
- pdf.multi_cell(0, 8, body_text)
- pdf.ln(10)
-
- if annotations:
- if os.path.exists(font_path):
- pdf.set_font("DejaVu", "B", 13)
- else:
- pdf.set_font("Helvetica", "B", 13)
- pdf.cell(0, 10, "Annotations:", ln=True)
- if os.path.exists(font_path):
- pdf.set_font("DejaVu", "", 12)
- else:
- pdf.set_font("Helvetica", "", 12)
- pdf.multi_cell(0, 8, annotations)
-
- try:
- pdf_bytes = pdf.output(dest="S")
- if isinstance(pdf_bytes, str):
- pdf_bytes = pdf_bytes.encode("latin-1")
- except Exception:
- pdf_bytes = pdf.output(dest="S").encode("utf-8")
-
- buffer = io.BytesIO(pdf_bytes)
- buffer.seek(0)
- return buffer
-
-
-def safe_write_temp_file(uploaded_file, filename="temp.pdf") -> str:
- """Save uploaded file to a safe temporary path and return path."""
- tmp_dir = tempfile.gettempdir()
- path = os.path.join(tmp_dir, f"{uuid.uuid4().hex}_{filename}")
- with open(path, "wb") as f:
- f.write(uploaded_file.read())
- return path
-
-
-def validate_summary(s: Optional[str]) -> bool:
- return bool(s and s.strip())
-
-
-def parse_iso(iso_str: str) -> datetime:
- """Parse ISO timestamp robustly, returning epoch if fails."""
- if not iso_str:
- return datetime.fromtimestamp(0)
- try:
- return datetime.fromisoformat(iso_str)
- except Exception:
- try:
- return datetime.strptime(iso_str, "%Y-%m-%d %H:%M:%S")
- except Exception:
- return datetime.fromtimestamp(0)
-
-
-def to_date(iso_str: str) -> Optional[datetime.date]:
- try:
- return parse_iso(iso_str).date()
- except Exception:
- return None
-
-
-# ---------------------------------------------------------------------
-# Custom CSS & Styles (Modern Dark Theme)
-# ---------------------------------------------------------------------
-st.markdown("""
-
-""", unsafe_allow_html=True)
-
-# ---------------------------------------------------------------------
-# Sidebar navigation
-# ---------------------------------------------------------------------
-with st.sidebar:
- st.markdown('', unsafe_allow_html=True)
-
- option = st.radio(
- label="Choose a section",
- options=[
- "Search arXiv Papers",
- "Query Stored Summaries",
- "Upload & Summarize PDF",
- "Semantic Search (FAISS)",
- "History"
- ],
- key="main_menu",
- label_visibility="collapsed"
- )
-
- if DEMO_MODE:
- st.markdown('Demo Mode
', unsafe_allow_html=True)
- st.caption("Results are approximate")
-
- if st.button("Load Demo Dataset"):
- try:
- from paperscope.demo_data import load_demo_data
- ok, msg = load_demo_data(build_index=False)
- if ok:
- st.success(msg)
- else:
- st.error("Failed to load demo database")
- except ImportError:
- st.error("Demo data module not found")
-
-# ---------------------------------------------------------------------
-# Page header
-# ---------------------------------------------------------------------
-st.markdown("""
-
-""", unsafe_allow_html=True)
-
-# ---------------------------------------------------------------------
-# Section: Search arXiv Papers
-# ---------------------------------------------------------------------
-if option == "Search arXiv Papers":
- st.markdown('', unsafe_allow_html=True)
- st.markdown('
Search arXiv Papers
', unsafe_allow_html=True)
-
- keyword_input = st.text_input(
- "Enter Keywords or Paper URL",
- placeholder="e.g., reinforcement learning for robots OR https://arxiv.org/abs/2301.12345"
- )
- st.markdown('
You can enter keywords to search arXiv, or paste a direct paper URL (arXiv or PDF link)
', unsafe_allow_html=True)
-
- if st.button("Fetch & Summarize"):
- if DEMO_MODE:
- st.info("This feature is disabled in Demo Mode. Use demo dataset or upload a PDF instead.")
- elif not keyword_input or keyword_input.strip() == "":
- st.warning("Please enter a keyword or URL to search")
- else:
- try:
- from paperscope.url_handler import is_url
-
- if is_url(keyword_input):
- with st.spinner("Fetching paper from URL and summarizing..."):
- data = fetch_and_summarize(keyword_input)
-
- if data:
- st.success("Paper fetched and summarized successfully")
- for idx, item in enumerate(data[-5:]):
- with st.expander(f"{item.get('title', 'Untitled Paper')}"):
- st.markdown("**Summary:**")
- st.write(item.get("summary", "No summary available"))
-
- # Download buttons
- summary_text = item.get('summary', '')
- md_bytes = f"# {item.get('title', 'Summary')}\n\n{summary_text}".encode("utf-8")
- txt_bytes = summary_text.encode("utf-8")
-
- metadata = {
- "source": item.get('source', 'arXiv'),
- "paper_id": item.get('id', 'N/A')
- }
- pdf_buf = generate_pdf_from_text(
- title=item.get('title', 'PaperScope Summary'),
- metadata=metadata,
- body_text=summary_text,
- annotations=item.get('annotations', '')
- )
-
- dl_col1, dl_col2, dl_col3 = st.columns([1, 1, 1])
- with dl_col1:
- st.download_button(
- label="Download TXT",
- data=txt_bytes,
- file_name=f"{safe_filename(item.get('title', 'summary'))}.txt",
- mime="text/plain",
- key=f"download_txt_arxiv_{idx}"
- )
- with dl_col2:
- st.download_button(
- label="Download MD",
- data=md_bytes,
- file_name=f"{safe_filename(item.get('title', 'summary'))}.md",
- mime="text/markdown",
- key=f"download_md_arxiv_{idx}"
- )
- with dl_col3:
- st.download_button(
- label="Download PDF",
- data=pdf_buf,
- file_name=f"{safe_filename(item.get('title', 'summary'))}.pdf",
- mime="application/pdf",
- key=f"download_pdf_arxiv_{idx}"
- )
- else:
- st.error("Failed to fetch paper from URL. Please check the URL and try again")
- st.info("Supported formats: arXiv URLs (abs or pdf) and direct PDF links")
-
- else:
- with st.spinner("Fetching and summarizing..."):
- data = fetch_and_summarize(keyword_input)
-
- if data:
- st.success(f"Found and processed {len(data)} paper(s)")
- for idx, item in enumerate(data[-10:][::-1]):
- with st.expander(f"{item.get('title', 'Untitled Paper')}"):
- st.markdown("**Summary:**")
- st.write(item.get("summary", "No summary available"))
-
- # Download buttons
- summary_text = item.get('summary', '')
- md_bytes = f"# {item.get('title', 'Summary')}\n\n{summary_text}".encode("utf-8")
- txt_bytes = summary_text.encode("utf-8")
-
- metadata = {
- "source": item.get('source', 'arXiv'),
- "paper_id": item.get('id', 'N/A')
- }
- pdf_buf = generate_pdf_from_text(
- title=item.get('title', 'PaperScope Summary'),
- metadata=metadata,
- body_text=summary_text,
- annotations=item.get('annotations', '')
- )
-
- dl_col1, dl_col2, dl_col3 = st.columns([1, 1, 1])
- with dl_col1:
- st.download_button(
- label="Download TXT",
- data=txt_bytes,
- file_name=f"{safe_filename(item.get('title', 'summary'))}.txt",
- mime="text/plain",
- key=f"download_txt_arxiv_{idx}"
- )
- with dl_col2:
- st.download_button(
- label="Download MD",
- data=md_bytes,
- file_name=f"{safe_filename(item.get('title', 'summary'))}.md",
- mime="text/markdown",
- key=f"download_md_arxiv_{idx}"
- )
- with dl_col3:
- st.download_button(
- label="Download PDF",
- data=pdf_buf,
- file_name=f"{safe_filename(item.get('title', 'summary'))}.pdf",
- mime="application/pdf",
- key=f"download_pdf_arxiv_{idx}"
- )
- else:
- st.warning("No results found")
-
- except Exception as e:
- st.error(f"Error processing: {str(e)}")
- st.info("Supported formats: arXiv URLs (abs or pdf) and direct PDF links")
-
- st.markdown('
', unsafe_allow_html=True)
- st.markdown('
Query Stored Summaries
', unsafe_allow_html=True)
-
- query_input = st.text_input(
- "Search stored summaries",
- placeholder="e.g., contrastive learning"
- )
-
- if st.button("Run Keyword Search"):
- if not query_input or query_input.strip() == "":
- st.warning("Please enter a search query")
- else:
- with st.spinner("Searching database..."):
- try:
- results = query_db(query_input)
-
- if not results:
- st.info("No matching summaries found")
- else:
- st.success(f"Found {len(results)} results")
- for idx, item in enumerate(results):
- with st.expander(f"{item.get('title', 'Untitled')}", expanded=(idx == 0)):
- st.markdown("**Summary:**")
- st.write(item.get('summary', 'No summary available'))
-
- # Download buttons
- download_col1, download_col2, download_col3 = st.columns([1, 1, 1])
- summary_text = item.get('summary', '')
- md_bytes = f"# {item.get('title', '')}\n\n{summary_text}".encode("utf-8")
- txt_bytes = summary_text.encode("utf-8")
- pdf_buf = generate_pdf_from_text(
- title=item.get('title', 'Summary'),
- metadata={"id": item.get('id', '')},
- body_text=summary_text,
- annotations=item.get('annotations', '')
- )
-
- with download_col1:
- st.download_button(
- label="TXT",
- data=txt_bytes,
- file_name=f"{safe_filename(item.get('title', 'summary'))}.txt",
- mime="text/plain",
- key=f"query_txt_{idx}"
- )
- with download_col2:
- st.download_button(
- label="MD",
- data=md_bytes,
- file_name=f"{safe_filename(item.get('title', 'summary'))}.md",
- mime="text/markdown",
- key=f"query_md_{idx}"
- )
- with download_col3:
- st.download_button(
- label="PDF",
- data=pdf_buf,
- file_name=f"{safe_filename(item.get('title', 'summary'))}.pdf",
- mime="application/pdf",
- key=f"query_pdf_{idx}"
- )
-
- except Exception as e:
- st.error(f"Search failed: {str(e)}")
-
- st.markdown('
', unsafe_allow_html=True)
- st.markdown('
Upload & Summarize PDF
', unsafe_allow_html=True)
-
- uploaded_file = st.file_uploader("Upload a PDF research paper", type=["pdf"])
-
- if uploaded_file:
- try:
- tmp_path = safe_write_temp_file(uploaded_file, filename="uploaded.pdf")
- except Exception as e:
- st.error(f"Error saving uploaded file: {e}")
- st.stop()
-
- with st.spinner("Extracting text from PDF..."):
- try:
- extracted_text = extract_text_from_pdf(tmp_path)
- except Exception as e:
- st.error(f"Extraction failed: {e}")
- st.info("Make sure PDF contains selectable text (not scanned images) or use OCR-enabled parsing")
- st.stop()
-
- if not extracted_text or len(extracted_text.strip()) == 0:
- st.error("No text extracted from PDF. The file may be scanned or encrypted")
- st.stop()
-
- with st.spinner("Generating AI-powered summary..."):
- try:
- summary_text = summarize(extracted_text)
- except Exception as e:
- st.error(f"Summarization failed: {e}")
- st.stop()
-
- if not validate_summary(summary_text):
- st.error("Generated an empty summary. Try again or adjust summarizer settings")
- st.stop()
-
- st.subheader("Generated Summary")
- st.success("Summary generated successfully")
- st.write(summary_text)
-
- # Save to history
- if STORAGE_AVAILABLE:
- try:
- history_entry = {
- "id": f"local-{uuid.uuid4().hex[:8]}",
- "title": uploaded_file.name,
- "abstract": "",
- "summary": summary_text,
- "timestamp": datetime.now().isoformat(),
- "source": "upload",
- "annotations": ""
- }
- save_history_entry(history_entry)
- except Exception:
- pass
-
- # Download options
- st.markdown("---")
- st.markdown("### Download Your Summary")
-
- col_txt, col_md, col_pdf = st.columns(3)
- txt_bytes = summary_text.encode("utf-8")
- md_bytes = f"# {uploaded_file.name}\n\n{summary_text}".encode("utf-8")
-
- metadata = {
- "Original Filename": uploaded_file.name,
- "Generated On": datetime.now().strftime("%Y-%m-%d %H:%M:%S"),
- "Source": "Uploaded PDF"
- }
- pdf_buffer = generate_pdf_from_text(
- title=uploaded_file.name,
- metadata=metadata,
- body_text=summary_text,
- annotations=""
- )
-
- with col_txt:
- st.download_button(
- label="Download TXT",
- data=txt_bytes,
- file_name=f"{safe_filename(uploaded_file.name)}_summary.txt",
- mime="text/plain",
- key="download_upload_txt"
- )
- with col_md:
- st.download_button(
- label="Download MD",
- data=md_bytes,
- file_name=f"{safe_filename(uploaded_file.name)}_summary.md",
- mime="text/markdown",
- key="download_upload_md"
- )
- with col_pdf:
- st.download_button(
- label="Download PDF",
- data=pdf_buffer,
- file_name=f"{safe_filename(uploaded_file.name)}_summary.pdf",
- mime="application/pdf",
- key="download_upload_pdf"
- )
-
- st.markdown('
', unsafe_allow_html=True)
- st.markdown('
Semantic Search (FAISS)
', unsafe_allow_html=True)
-
- if st.button("Rebuild Index"):
- if DEMO_MODE:
- st.info("Index building is simulated in Demo Mode. Load the demo instead")
- else:
- with st.spinner("Rebuilding semantic vector index..."):
- try:
- build_index()
- st.success("Index rebuilt successfully")
- except Exception as e:
- st.error(f"Failed to rebuild index: {e}")
-
- semantic_query = st.text_input(
- "Enter a semantic query",
- placeholder="e.g., visual prompt tuning in robotics"
- )
-
- if st.button("Search with FAISS"):
- if not semantic_query or semantic_query.strip() == "":
- st.warning("Please enter a semantic query")
- else:
- with st.spinner("Running semantic search..."):
- try:
- results = search_similar(semantic_query)
-
- if not results:
- st.info("No similar results found")
- else:
- st.success(f"Found {len(results)} similar items")
- for idx, item in enumerate(results):
- with st.expander(f"{item.get('title', 'Untitled')}", expanded=(idx == 0)):
- st.markdown("**Summary:**")
- st.write(item.get('summary', 'No summary available'))
-
- download_col1, download_col2, download_col3 = st.columns([1, 1, 1])
- summary_text = item.get('summary', '')
- md_bytes = f"# {item.get('title', '')}\n\n{summary_text}".encode("utf-8")
- txt_bytes = summary_text.encode("utf-8")
- pdf_buf = generate_pdf_from_text(
- title=item.get('title', 'Summary'),
- metadata={"id": item.get('id', '')},
- body_text=summary_text,
- annotations=item.get('annotations', '')
- )
-
- with download_col1:
- st.download_button(
- label="TXT",
- data=txt_bytes,
- file_name=f"{safe_filename(item.get('title', 'summary'))}.txt",
- mime="text/plain",
- key=f"faiss_txt_{idx}"
- )
- with download_col2:
- st.download_button(
- label="MD",
- data=md_bytes,
- file_name=f"{safe_filename(item.get('title', 'summary'))}.md",
- mime="text/markdown",
- key=f"faiss_md_{idx}"
- )
- with download_col3:
- st.download_button(
- label="PDF",
- data=pdf_buf,
- file_name=f"{safe_filename(item.get('title', 'summary'))}.pdf",
- mime="application/pdf",
- key=f"faiss_pdf_{idx}"
- )
-
- except Exception as e:
- st.error(f"Semantic search failed: {e}")
-
- st.markdown('
', unsafe_allow_html=True)
- st.markdown('
Summary History
', unsafe_allow_html=True)
- st.markdown('
View, filter, and download previously processed papers
', unsafe_allow_html=True)
-
- try:
- history = get_history() or []
- except Exception:
- history = []
-
- if history:
- metric_col1, metric_col2, metric_col3 = st.columns(3)
- with metric_col1:
- st.metric("Total Papers", len(history))
- with metric_col2:
- today = datetime.now().date()
- today_count = sum(
- 1 for item in history
- if to_date(item.get("timestamp")) == today
- )
- st.metric("Added Today", today_count)
- with metric_col3:
- week_ago = datetime.now() - timedelta(days=7)
- week_count = sum(
- 1 for item in history
- if parse_iso(item.get("timestamp")) > week_ago
- )
- st.metric("Last 7 Days", week_count)
- st.markdown("---")
-
- col_filter, col_sort, col_action = st.columns([3, 2, 1])
- with col_filter:
- search_filter = st.text_input("Filter by title or keyword", placeholder="Type to filter...")
- with col_sort:
- sort_order = st.selectbox("Sort by", ["Newest First", "Oldest First", "Title A-Z"])
- with col_action:
- if st.button("Clear All", type="secondary"):
- if st.session_state.get("confirm_clear", False):
- try:
- clear_history()
- st.success("History cleared!")
- st.session_state.confirm_clear = False
- st.rerun()
- except Exception as e:
- st.error(f"Failed to clear history: {e}")
- else:
- st.session_state.confirm_clear = True
- st.warning("Click again to confirm")
-
- st.markdown("---")
-
- if not history:
- st.info("No papers in history yet. Start by searching or uploading papers!")
- else:
- filtered = history
- if search_filter and search_filter.strip():
- q = search_filter.lower()
- filtered = [
- item for item in filtered
- if q in (item.get('title', '').lower() +
- item.get('abstract', '').lower() +
- item.get('summary', '').lower())
- ]
-
- if sort_order == "Newest First":
- filtered = sorted(filtered, key=lambda x: x.get('timestamp', ''), reverse=True)
- elif sort_order == "Oldest First":
- filtered = sorted(filtered, key=lambda x: x.get('timestamp', ''))
- elif sort_order == "Title A-Z":
- filtered = sorted(filtered, key=lambda x: x.get('title', '').lower())
-
- st.caption(f"Showing {len(filtered)} paper(s)")
-
- for idx, item in enumerate(filtered):
- with st.expander(f"{item.get('title', 'Untitled Paper')}", expanded=(idx == 0)):
- top_col1, top_col2, top_col3 = st.columns([4, 1, 1])
-
- with top_col1:
- timestamp = item.get('timestamp', 'Unknown date')
- if timestamp and timestamp != "Unknown date":
- try:
- ts = datetime.fromisoformat(timestamp)
- timestamp = ts.strftime("%B %d, %Y at %I:%M %p")
- except ValueError:
- pass
- st.caption(f"Added: {timestamp}")
- st.caption(f"ID: `{item.get('id', 'N/A')}`")
-
- with top_col2:
- summary_text = f"Title: {item.get('title', 'N/A')}\n\n"
- summary_text += f"Abstract:\n{item.get('abstract', 'N/A')}\n\n"
- summary_text += f"Summary:\n{item.get('summary', 'N/A')}\n\n"
- txt_bytes = summary_text.encode("utf-8")
-
- st.download_button(
- label="Download",
- data=txt_bytes,
- file_name=f"{safe_filename(item.get('id', 'paper'))}_summary.txt",
- mime="text/plain",
- key=f"history_download_{idx}",
- help="Download summary as TXT"
- )
-
- with top_col3:
- if st.button("Delete", key=f"delete_{idx}", help="Delete this paper", type="secondary"):
- try:
- if delete_entry(item.get('id')):
- st.success("Paper deleted!")
- st.rerun()
- else:
- st.error("Failed to delete paper")
- except Exception as e:
- st.error(f"Error deleting: {e}")
-
- st.markdown("---")
- st.markdown("**Abstract:**")
- st.markdown(f"> {item.get('abstract', 'No abstract available')}")
- st.markdown("**Summary:**")
- st.write(item.get('summary', 'No summary available'))
-
- paper_id = item.get('id', '')
- if paper_id and ('arxiv' in paper_id.lower() or '/' in paper_id):
- arxiv_id = paper_id.split('/')[-1] if '/' in paper_id else paper_id
- st.markdown(f"[View on arXiv](https://arxiv.org/abs/{arxiv_id})")
-
- st.markdown("---")
- st.markdown("**Additional Formats:**")
- dl_col1, dl_col2, dl_col3 = st.columns([1, 1, 1])
-
- md_content = f"# {item.get('title', '')}\n\n**Abstract:**\n\n{item.get('abstract','')}\n\n**Summary:**\n\n{item.get('summary','')}"
- md_bytes = md_content.encode("utf-8")
-
- pdf_buf = generate_pdf_from_text(
- title=item.get('title', 'History Entry'),
- metadata={
- "id": item.get('id', ''),
- "added_on": item.get('timestamp', '')
- },
- body_text=item.get('summary', ''),
- annotations=item.get('annotations', '')
- )
-
- with dl_col1:
- st.download_button(
- label="TXT",
- data=txt_bytes,
- file_name=f"{safe_filename(item.get('title', 'paper'))}.txt",
- mime="text/plain",
- key=f"history_txt_{idx}"
- )
- with dl_col2:
- st.download_button(
- label="MD",
- data=md_bytes,
- file_name=f"{safe_filename(item.get('title', 'paper'))}.md",
- mime="text/markdown",
- key=f"history_md_{idx}"
- )
- with dl_col3:
- st.download_button(
- label="PDF",
- data=pdf_buf,
- file_name=f"{safe_filename(item.get('title', 'paper'))}.pdf",
- mime="application/pdf",
- key=f"history_pdf_{idx}"
- )
-
- st.markdown('
Demo Mode
', unsafe_allow_html=True)
+ st.caption("Results are approximate")
+
+ if st.button("Load Demo Dataset"):
+ try:
+ from paperscope.demo_data import load_demo_data
+ ok, msg = load_demo_data(build_index=False)
+ if ok:
+ st.success(msg)
+ else:
+ st.error("Failed to load demo database")
+ except ImportError:
+ st.error("Demo data module not found")
+
+# ---------------------------------------------------------------------
+# Page header
+# ---------------------------------------------------------------------
+st.markdown("""
+
+""", unsafe_allow_html=True)
+
+# ---------------------------------------------------------------------
+# Section: Search arXiv Papers
+# ---------------------------------------------------------------------
+if option == "Search arXiv Papers":
+ st.markdown('', unsafe_allow_html=True)
+ st.markdown('
Search arXiv Papers
', unsafe_allow_html=True)
+
+ keyword_input = st.text_input(
+ "Enter Keywords or Paper URL",
+ placeholder="e.g., reinforcement learning for robots OR https://arxiv.org/abs/2301.12345"
+ )
+ st.markdown('
You can enter keywords to search arXiv, or paste a direct paper URL (arXiv or PDF link)
', unsafe_allow_html=True)
+
+ if st.button("Fetch & Summarize"):
+ if DEMO_MODE:
+ st.info("This feature is disabled in Demo Mode. Use demo dataset or upload a PDF instead.")
+ elif not keyword_input or keyword_input.strip() == "":
+ st.warning("Please enter a keyword or URL to search")
+ else:
+ try:
+ from paperscope.url_handler import is_url
+
+ if is_url(keyword_input):
+ with st.spinner("Fetching paper from URL and summarizing..."):
+ data = fetch_and_summarize(keyword_input)
+
+ if data:
+ st.success("Paper fetched and summarized successfully")
+ for idx, item in enumerate(data[-5:]):
+ with st.expander(f"{item.get('title', 'Untitled Paper')}"):
+ st.markdown("**Summary:**")
+ st.write(item.get("summary", "No summary available"))
+
+ # Download buttons
+ summary_text = item.get('summary', '')
+ md_bytes = f"# {item.get('title', 'Summary')}\n\n{summary_text}".encode("utf-8")
+ txt_bytes = summary_text.encode("utf-8")
+
+ metadata = {
+ "source": item.get('source', 'arXiv'),
+ "paper_id": item.get('id', 'N/A')
+ }
+ pdf_buf = generate_pdf_from_text(
+ title=item.get('title', 'PaperScope Summary'),
+ metadata=metadata,
+ body_text=summary_text,
+ annotations=item.get('annotations', '')
+ )
+
+ dl_col1, dl_col2, dl_col3 = st.columns([1, 1, 1])
+ with dl_col1:
+ st.download_button(
+ label="Download TXT",
+ data=txt_bytes,
+ file_name=f"{safe_filename(item.get('title', 'summary'))}.txt",
+ mime="text/plain",
+ key=f"download_txt_arxiv_{idx}"
+ )
+ with dl_col2:
+ st.download_button(
+ label="Download MD",
+ data=md_bytes,
+ file_name=f"{safe_filename(item.get('title', 'summary'))}.md",
+ mime="text/markdown",
+ key=f"download_md_arxiv_{idx}"
+ )
+ with dl_col3:
+ st.download_button(
+ label="Download PDF",
+ data=pdf_buf,
+ file_name=f"{safe_filename(item.get('title', 'summary'))}.pdf",
+ mime="application/pdf",
+ key=f"download_pdf_arxiv_{idx}"
+ )
+ else:
+ st.error("Failed to fetch paper from URL. Please check the URL and try again")
+ st.info("Supported formats: arXiv URLs (abs or pdf) and direct PDF links")
+
+ else:
+ with st.spinner("Fetching and summarizing..."):
+ data = fetch_and_summarize(keyword_input)
+
+ if data:
+ st.success(f"Found and processed {len(data)} paper(s)")
+ for idx, item in enumerate(data[-10:][::-1]):
+ with st.expander(f"{item.get('title', 'Untitled Paper')}"):
+ st.markdown("**Summary:**")
+ st.write(item.get("summary", "No summary available"))
+
+ # Download buttons
+ summary_text = item.get('summary', '')
+ md_bytes = f"# {item.get('title', 'Summary')}\n\n{summary_text}".encode("utf-8")
+ txt_bytes = summary_text.encode("utf-8")
+
+ metadata = {
+ "source": item.get('source', 'arXiv'),
+ "paper_id": item.get('id', 'N/A')
+ }
+ pdf_buf = generate_pdf_from_text(
+ title=item.get('title', 'PaperScope Summary'),
+ metadata=metadata,
+ body_text=summary_text,
+ annotations=item.get('annotations', '')
+ )
+
+ dl_col1, dl_col2, dl_col3 = st.columns([1, 1, 1])
+ with dl_col1:
+ st.download_button(
+ label="Download TXT",
+ data=txt_bytes,
+ file_name=f"{safe_filename(item.get('title', 'summary'))}.txt",
+ mime="text/plain",
+ key=f"download_txt_arxiv_{idx}"
+ )
+ with dl_col2:
+ st.download_button(
+ label="Download MD",
+ data=md_bytes,
+ file_name=f"{safe_filename(item.get('title', 'summary'))}.md",
+ mime="text/markdown",
+ key=f"download_md_arxiv_{idx}"
+ )
+ with dl_col3:
+ st.download_button(
+ label="Download PDF",
+ data=pdf_buf,
+ file_name=f"{safe_filename(item.get('title', 'summary'))}.pdf",
+ mime="application/pdf",
+ key=f"download_pdf_arxiv_{idx}"
+ )
+ else:
+ st.warning("No results found")
+
+ except Exception as e:
+ st.error(f"Error processing: {str(e)}")
+ st.info("Supported formats: arXiv URLs (abs or pdf) and direct PDF links")
+
+ st.markdown('
', unsafe_allow_html=True)
+ st.markdown('
Query Stored Summaries
', unsafe_allow_html=True)
+
+ query_input = st.text_input(
+ "Search stored summaries",
+ placeholder="e.g., contrastive learning"
+ )
+
+ if st.button("Run Keyword Search"):
+ if not query_input or query_input.strip() == "":
+ st.warning("Please enter a search query")
+ else:
+ with st.spinner("Searching database..."):
+ try:
+ results = query_db(query_input)
+
+ if not results:
+ st.info("No matching summaries found")
+ else:
+ st.success(f"Found {len(results)} results")
+ for idx, item in enumerate(results):
+ with st.expander(f"{item.get('title', 'Untitled')}", expanded=(idx == 0)):
+ st.markdown("**Summary:**")
+ st.write(item.get('summary', 'No summary available'))
+
+ # Download buttons
+ download_col1, download_col2, download_col3 = st.columns([1, 1, 1])
+ summary_text = item.get('summary', '')
+ md_bytes = f"# {item.get('title', '')}\n\n{summary_text}".encode("utf-8")
+ txt_bytes = summary_text.encode("utf-8")
+ pdf_buf = generate_pdf_from_text(
+ title=item.get('title', 'Summary'),
+ metadata={"id": item.get('id', '')},
+ body_text=summary_text,
+ annotations=item.get('annotations', '')
+ )
+
+ with download_col1:
+ st.download_button(
+ label="TXT",
+ data=txt_bytes,
+ file_name=f"{safe_filename(item.get('title', 'summary'))}.txt",
+ mime="text/plain",
+ key=f"query_txt_{idx}"
+ )
+ with download_col2:
+ st.download_button(
+ label="MD",
+ data=md_bytes,
+ file_name=f"{safe_filename(item.get('title', 'summary'))}.md",
+ mime="text/markdown",
+ key=f"query_md_{idx}"
+ )
+ with download_col3:
+ st.download_button(
+ label="PDF",
+ data=pdf_buf,
+ file_name=f"{safe_filename(item.get('title', 'summary'))}.pdf",
+ mime="application/pdf",
+ key=f"query_pdf_{idx}"
+ )
+
+ except Exception as e:
+ st.error(f"Search failed: {str(e)}")
+
+ st.markdown('
', unsafe_allow_html=True)
+ st.markdown('
Upload & Summarize PDF
', unsafe_allow_html=True)
+
+ uploaded_file = st.file_uploader("Upload a PDF research paper", type=["pdf"])
+
+ if uploaded_file:
+ try:
+ tmp_path = safe_write_temp_file(uploaded_file, filename="uploaded.pdf")
+ except Exception as e:
+ st.error(f"Error saving uploaded file: {e}")
+ st.stop()
+
+ with st.spinner("Extracting text from PDF..."):
+ try:
+ extracted_text = extract_text_from_pdf(tmp_path)
+ except Exception as e:
+ st.error(f"Extraction failed: {e}")
+ st.info("Make sure PDF contains selectable text (not scanned images) or use OCR-enabled parsing")
+ st.stop()
+
+ if not extracted_text or len(extracted_text.strip()) == 0:
+ st.error("No text extracted from PDF. The file may be scanned or encrypted")
+ st.stop()
+
+ with st.spinner("Generating AI-powered summary..."):
+ try:
+ summary_text = summarize(extracted_text)
+ except Exception as e:
+ st.error(f"Summarization failed: {e}")
+ st.stop()
+
+ if not validate_summary(summary_text):
+ st.error("Generated an empty summary. Try again or adjust summarizer settings")
+ st.stop()
+
+ st.subheader("Generated Summary")
+ st.success("Summary generated successfully")
+ st.write(summary_text)
+
+ # Save to history
+ if STORAGE_AVAILABLE:
+ try:
+ history_entry = {
+ "id": f"local-{uuid.uuid4().hex[:8]}",
+ "title": uploaded_file.name,
+ "abstract": "",
+ "summary": summary_text,
+ "timestamp": datetime.now().isoformat(),
+ "source": "upload",
+ "annotations": ""
+ }
+ save_history_entry(history_entry)
+ except Exception:
+ pass
+
+ # Download options
+ st.markdown("---")
+ st.markdown("### Download Your Summary")
+
+ col_txt, col_md, col_pdf = st.columns(3)
+ txt_bytes = summary_text.encode("utf-8")
+ md_bytes = f"# {uploaded_file.name}\n\n{summary_text}".encode("utf-8")
+
+ metadata = {
+ "Original Filename": uploaded_file.name,
+ "Generated On": datetime.now().strftime("%Y-%m-%d %H:%M:%S"),
+ "Source": "Uploaded PDF"
+ }
+ pdf_buffer = generate_pdf_from_text(
+ title=uploaded_file.name,
+ metadata=metadata,
+ body_text=summary_text,
+ annotations=""
+ )
+
+ with col_txt:
+ st.download_button(
+ label="Download TXT",
+ data=txt_bytes,
+ file_name=f"{safe_filename(uploaded_file.name)}_summary.txt",
+ mime="text/plain",
+ key="download_upload_txt"
+ )
+ with col_md:
+ st.download_button(
+ label="Download MD",
+ data=md_bytes,
+ file_name=f"{safe_filename(uploaded_file.name)}_summary.md",
+ mime="text/markdown",
+ key="download_upload_md"
+ )
+ with col_pdf:
+ st.download_button(
+ label="Download PDF",
+ data=pdf_buffer,
+ file_name=f"{safe_filename(uploaded_file.name)}_summary.pdf",
+ mime="application/pdf",
+ key="download_upload_pdf"
+ )
+
+ st.markdown('
', unsafe_allow_html=True)
+ st.markdown('
Semantic Search (FAISS)
', unsafe_allow_html=True)
+
+ if st.button("Rebuild Index"):
+ if DEMO_MODE:
+ st.info("Index building is simulated in Demo Mode. Load the demo instead")
+ else:
+ with st.spinner("Rebuilding semantic vector index..."):
+ try:
+ build_index()
+ st.success("Index rebuilt successfully")
+ except Exception as e:
+ st.error(f"Failed to rebuild index: {e}")
+
+ semantic_query = st.text_input(
+ "Enter a semantic query",
+ placeholder="e.g., visual prompt tuning in robotics"
+ )
+
+ if st.button("Search with FAISS"):
+ if not semantic_query or semantic_query.strip() == "":
+ st.warning("Please enter a semantic query")
+ else:
+ with st.spinner("Running semantic search..."):
+ try:
+ results = search_similar(semantic_query)
+
+ if not results:
+ st.info("No similar results found")
+ else:
+ st.success(f"Found {len(results)} similar items")
+ for idx, item in enumerate(results):
+ with st.expander(f"{item.get('title', 'Untitled')}", expanded=(idx == 0)):
+ st.markdown("**Summary:**")
+ st.write(item.get('summary', 'No summary available'))
+
+ download_col1, download_col2, download_col3 = st.columns([1, 1, 1])
+ summary_text = item.get('summary', '')
+ md_bytes = f"# {item.get('title', '')}\n\n{summary_text}".encode("utf-8")
+ txt_bytes = summary_text.encode("utf-8")
+ pdf_buf = generate_pdf_from_text(
+ title=item.get('title', 'Summary'),
+ metadata={"id": item.get('id', '')},
+ body_text=summary_text,
+ annotations=item.get('annotations', '')
+ )
+
+ with download_col1:
+ st.download_button(
+ label="TXT",
+ data=txt_bytes,
+ file_name=f"{safe_filename(item.get('title', 'summary'))}.txt",
+ mime="text/plain",
+ key=f"faiss_txt_{idx}"
+ )
+ with download_col2:
+ st.download_button(
+ label="MD",
+ data=md_bytes,
+ file_name=f"{safe_filename(item.get('title', 'summary'))}.md",
+ mime="text/markdown",
+ key=f"faiss_md_{idx}"
+ )
+ with download_col3:
+ st.download_button(
+ label="PDF",
+ data=pdf_buf,
+ file_name=f"{safe_filename(item.get('title', 'summary'))}.pdf",
+ mime="application/pdf",
+ key=f"faiss_pdf_{idx}"
+ )
+
+ except Exception as e:
+ st.error(f"Semantic search failed: {e}")
+
+ st.markdown('
', unsafe_allow_html=True)
+ st.markdown('
Summary History
', unsafe_allow_html=True)
+ st.markdown('
View, filter, and download previously processed papers
', unsafe_allow_html=True)
+
+ try:
+ history = get_history() or []
+ except Exception:
+ history = []
+
+ if history:
+ metric_col1, metric_col2, metric_col3 = st.columns(3)
+ with metric_col1:
+ st.metric("Total Papers", len(history))
+ with metric_col2:
+ today = datetime.now().date()
+ today_count = sum(
+ 1 for item in history
+ if to_date(item.get("timestamp")) == today
+ )
+ st.metric("Added Today", today_count)
+ with metric_col3:
+ week_ago = datetime.now() - timedelta(days=7)
+ week_count = sum(
+ 1 for item in history
+ if parse_iso(item.get("timestamp")) > week_ago
+ )
+ st.metric("Last 7 Days", week_count)
+ st.markdown("---")
+
+ col_filter, col_sort, col_action = st.columns([3, 2, 1])
+ with col_filter:
+ search_filter = st.text_input("Filter by title or keyword", placeholder="Type to filter...")
+ with col_sort:
+ sort_order = st.selectbox("Sort by", ["Newest First", "Oldest First", "Title A-Z"])
+ with col_action:
+ if st.button("Clear All", type="secondary"):
+ if st.session_state.get("confirm_clear", False):
+ try:
+ clear_history()
+ st.success("History cleared!")
+ st.session_state.confirm_clear = False
+ st.rerun()
+ except Exception as e:
+ st.error(f"Failed to clear history: {e}")
+ else:
+ st.session_state.confirm_clear = True
+ st.warning("Click again to confirm")
+
+ st.markdown("---")
+
+ if not history:
+ st.info("No papers in history yet. Start by searching or uploading papers!")
+ else:
+ filtered = history
+ if search_filter and search_filter.strip():
+ q = search_filter.lower()
+ filtered = [
+ item for item in filtered
+ if q in (item.get('title', '').lower() +
+ item.get('abstract', '').lower() +
+ item.get('summary', '').lower())
+ ]
+
+ if sort_order == "Newest First":
+ filtered = sorted(filtered, key=lambda x: x.get('timestamp', ''), reverse=True)
+ elif sort_order == "Oldest First":
+ filtered = sorted(filtered, key=lambda x: x.get('timestamp', ''))
+ elif sort_order == "Title A-Z":
+ filtered = sorted(filtered, key=lambda x: x.get('title', '').lower())
+
+ st.caption(f"Showing {len(filtered)} paper(s)")
+
+ for idx, item in enumerate(filtered):
+ with st.expander(f"{item.get('title', 'Untitled Paper')}", expanded=(idx == 0)):
+ top_col1, top_col2, top_col3 = st.columns([4, 1, 1])
+
+ with top_col1:
+ timestamp = item.get('timestamp', 'Unknown date')
+ if timestamp and timestamp != "Unknown date":
+ try:
+ ts = datetime.fromisoformat(timestamp)
+ timestamp = ts.strftime("%B %d, %Y at %I:%M %p")
+ except ValueError:
+ pass
+ st.caption(f"Added: {timestamp}")
+ st.caption(f"ID: `{item.get('id', 'N/A')}`")
+
+ with top_col2:
+ summary_text = f"Title: {item.get('title', 'N/A')}\n\n"
+ summary_text += f"Abstract:\n{item.get('abstract', 'N/A')}\n\n"
+ summary_text += f"Summary:\n{item.get('summary', 'N/A')}\n\n"
+ txt_bytes = summary_text.encode("utf-8")
+
+ st.download_button(
+ label="Download",
+ data=txt_bytes,
+ file_name=f"{safe_filename(item.get('id', 'paper'))}_summary.txt",
+ mime="text/plain",
+ key=f"history_download_{idx}",
+ help="Download summary as TXT"
+ )
+
+ with top_col3:
+ if st.button("Delete", key=f"delete_{idx}", help="Delete this paper", type="secondary"):
+ try:
+ if delete_entry(item.get('id')):
+ st.success("Paper deleted!")
+ st.rerun()
+ else:
+ st.error("Failed to delete paper")
+ except Exception as e:
+ st.error(f"Error deleting: {e}")
+
+ st.markdown("---")
+ st.markdown("**Abstract:**")
+ st.markdown(f"> {item.get('abstract', 'No abstract available')}")
+ st.markdown("**Summary:**")
+ st.write(item.get('summary', 'No summary available'))
+
+ paper_id = item.get('id', '')
+ if paper_id and ('arxiv' in paper_id.lower() or '/' in paper_id):
+ arxiv_id = paper_id.split('/')[-1] if '/' in paper_id else paper_id
+ st.markdown(f"[View on arXiv](https://arxiv.org/abs/{arxiv_id})")
+
+ st.markdown("---")
+ st.markdown("**Additional Formats:**")
+ dl_col1, dl_col2, dl_col3 = st.columns([1, 1, 1])
+
+ md_content = f"# {item.get('title', '')}\n\n**Abstract:**\n\n{item.get('abstract','')}\n\n**Summary:**\n\n{item.get('summary','')}"
+ md_bytes = md_content.encode("utf-8")
+
+ pdf_buf = generate_pdf_from_text(
+ title=item.get('title', 'History Entry'),
+ metadata={
+ "id": item.get('id', ''),
+ "added_on": item.get('timestamp', '')
+ },
+ body_text=item.get('summary', ''),
+ annotations=item.get('annotations', '')
+ )
+
+ with dl_col1:
+ st.download_button(
+ label="TXT",
+ data=txt_bytes,
+ file_name=f"{safe_filename(item.get('title', 'paper'))}.txt",
+ mime="text/plain",
+ key=f"history_txt_{idx}"
+ )
+ with dl_col2:
+ st.download_button(
+ label="MD",
+ data=md_bytes,
+ file_name=f"{safe_filename(item.get('title', 'paper'))}.md",
+ mime="text/markdown",
+ key=f"history_md_{idx}"
+ )
+ with dl_col3:
+ st.download_button(
+ label="PDF",
+ data=pdf_buf,
+ file_name=f"{safe_filename(item.get('title', 'paper'))}.pdf",
+ mime="application/pdf",
+ key=f"history_pdf_{idx}"
+ )
+
+ st.markdown('