Update app.py

app.py

@@ -2,108 +2,98 @@ import os
 import streamlit as st
 import arxiv
 import random
+import networkx as nx
+import matplotlib.pyplot as plt
 import datetime
 from groq import Groq
 
-# -------------------------------
-# API Clients
-# -------------------------------
-client = Groq(
-    api_key=os.environ.get("GROQ_API_KEY"),
-)
+client = Groq(api_key=os.environ.get("GROQ_API_KEY"))
 
-# -------------------------------
-# Helper Functions
-# -------------------------------
 def groq_summarize(text: str) -> str:
     response = client.chat.completions.create(
-        messages=[{"role": "user", "content": f"Summarize in 250 characters:
-
-{text}"}],
+        messages=[
+            {"role": "user", "content": f"Summarize in 250 characters:\n{text}"}
+        ],
         model="llama-3.3-70b-versatile",
     )
     return response.choices[0].message.content.strip()
 
-def groq_eli5(text: str) -> str:
+def groq_generate(text: str) -> str:
     response = client.chat.completions.create(
-        messages=[{"role": "user", "content": f"Explain like I'm 5:
-
-{text}"}],
+        messages=[{"role": "user", "content": text}],
         model="llama-3.3-70b-versatile",
     )
     return response.choices[0].message.content.strip()
 
-def calculate_trust_relevance(paper_title):
-    random.seed(hash(paper_title))
-    return random.randint(60, 95), random.randint(50, 90)
-
 def retrieve_papers(query, max_results=5):
     search = arxiv.Search(query=query, max_results=max_results)
     papers = []
     for result in search.results():
-        trust, relevance = calculate_trust_relevance(result.title)
-        paper_id = result.entry_id.split('/')[-1]
+        paper_id = result.entry_id.split("/")[-1]
         paper = {
             "title": result.title,
             "summary": result.summary,
             "url": result.pdf_url,
             "authors": [author.name for author in result.authors],
-            "published": result.published.strftime('%Y-%m-%d') if isinstance(result.published, datetime.datetime) else "n.d.",
+            "published": result.published,
             "doi": f"https://doi.org/10.48550/arXiv.{paper_id}",
-            "bib_explorer": f"https://arxiv.org/abs/{paper_id}",
+            "bibliographic_explorer": f"https://arxiv.org/abs/{paper_id}",
             "litmaps": f"https://app.litmaps.com/preview/{paper_id}",
-            "trust_score": trust,
-            "relevance_score": relevance
+            "trust_score": random.randint(60, 100),
+            "relevance_score": random.randint(50, 100)
         }
         papers.append(paper)
     return papers
 
-def get_random_papers():
-    sample_topics = ["AI ethics", "Quantum computing", "Neuroscience", "Robotics", "Renewable energy", "Space exploration"]
-    query = random.choice(sample_topics)
-    return retrieve_papers(query, random.randint(5, 15))
+def summarize_text(text):
+    return groq_summarize(text)
+
+def get_cached_summary(paper_id, text):
+    if 'summaries' not in st.session_state:
+        st.session_state.summaries = {}
+    if paper_id not in st.session_state.summaries:
+        st.session_state.summaries[paper_id] = summarize_text(text)
+    return st.session_state.summaries[paper_id]
+
+def random_paper_search():
+    topics = ["machine learning", "quantum computing", "climate change", "robotics", "health AI"]
+    return random.choice(topics)
+
+st.title("📚 PaperPilot – Intelligent Academic Navigator")
 
-# -------------------------------
-# Streamlit UI
-# -------------------------------
-st.title("📚 PaperPilot – Intelligent Research Navigator")
+st.sidebar.header("🔍 Search Parameters")
+query = st.sidebar.text_input("Research topic or question:")
+if st.sidebar.button("🎲 Random Search"):
+    query = random_paper_search()
+    st.sidebar.text(f"Random Topic: {query}")
+if st.sidebar.button("🚀 Find Articles"):
+    if query.strip():
+        with st.spinner("Searching arXiv..."):
+            papers = retrieve_papers(query, random.randint(5, 15))
+            if papers:
+                st.session_state.papers = papers
+                st.success(f"Found {len(papers)} papers!")
+                st.session_state.active_section = "articles"
+            else:
+                st.error("No papers found. Try different keywords.")
+    else:
+        st.warning("Please enter a search query")
 
-# Sidebar Controls
-with st.sidebar:
-    st.header("🔍 Search or Discover")
-    query = st.text_input("Search topic:")
-    if st.button("🚀 Find Articles"):
-        if query.strip():
-            with st.spinner("Searching arXiv..."):
-                st.session_state.papers = retrieve_papers(query)
-                st.success(f"Found {len(st.session_state.papers)} papers!")
-        else:
-            st.warning("Please enter a search query")
-    if st.button("🎲 Random Papers"):
-        with st.spinner("Fetching random papers..."):
-            st.session_state.papers = get_random_papers()
-            st.success(f"Found {len(st.session_state.papers)} random papers!")
+if 'active_section' not in st.session_state:
+    st.session_state.active_section = "none"
 
-if "papers" in st.session_state and st.session_state.papers:
-    st.header("📑 Research Feed")
-    for paper in st.session_state.papers:
-        with st.expander(f"🔍 {paper['title']}"):
-            st.markdown(f"**Authors:** {', '.join(paper['authors'])}")
-            st.markdown(f"**Published:** {paper['published']}")
-            st.markdown(f"**[PDF Link]({paper['url']})** | **[DOI]({paper['doi']})** | **[Bibliographic Explorer]({paper['bib_explorer']})** | **[Litmaps]({paper['litmaps']})**")
-            
-            with st.spinner("Summarizing..."):
-                summary = groq_summarize(paper['summary'])
-            st.markdown(f"**Summary:** {summary}")
-            
-            if st.button(f"Explain like I'm 5 🧸 - {paper['title']}"):
-                with st.spinner("Simplifying..."):
-                    st.write(groq_eli5(paper['summary']))
-            
-            st.markdown("**Trust & Relevance Scores:**")
-            st.progress(paper['trust_score'] / 100)
-            st.caption(f"🔹 Trust Score: {paper['trust_score']}%")
-            st.progress(paper['relevance_score'] / 100)
-            st.caption(f"🔹 Relevance Score: {paper['relevance_score']}%")
-else:
-    st.info("Enter a query or use the 🎲 Random Papers button to get started!")
+if 'papers' in st.session_state and st.session_state.papers:
+    papers = st.session_state.papers
+    if st.session_state.active_section == "articles":
+        st.header("📑 Retrieved Papers")
+        for idx, paper in enumerate(papers, 1):
+            with st.expander(f"{idx}. {paper['title']}"):
+                st.markdown(f"**Authors:** {', '.join(paper['authors'])}")
+                pub_date = paper['published'].strftime('%Y-%m-%d') if isinstance(paper['published'], datetime.datetime) else "n.d."
+                st.markdown(f"**Published:** {pub_date}")
+                st.markdown(f"**[PDF Link]({paper['url']}) | [DOI]({paper['doi']}) | [Bibliographic Explorer]({paper['bibliographic_explorer']}) | [Litmaps]({paper['litmaps']})**")
+                st.markdown(f"**Trust Score:** {paper['trust_score']} | **Relevance Score:** {paper['relevance_score']}")
+                summary = get_cached_summary(f"paper_{idx}", paper['summary'])
+                st.write(summary)
+                if st.button(f"🔍 Explain like I'm 5 (ELI5) {idx}"):
+                    st.write(groq_generate(f"Explain this in simple terms: {summary}"))