Update app.py

app.py

@@ -1,132 +1,84 @@
 import os
 import streamlit as st
 import arxiv
-import networkx as nx
-import matplotlib.pyplot as plt
-import datetime
+import random
 
 # -------------------------------
-# Groq API Client
+# Helper Functions
 # -------------------------------
-from groq import Groq
-
-client = Groq(
-    api_key=os.environ.get("GROQ_API_KEY"),
-)
-
-# -------------------------------
-# Helper Functions (Groq-based)
-# -------------------------------
-def groq_summarize(text: str) -> str:
-    """
-    Summarize the given text using Groq's chat completion API.
-    """
-    response = client.chat.completions.create(
-        messages=[
-            {"role": "user", "content": f"Summarize the following text in detail:\n\n{text}"}
-        ],
-        model="llama-3.3-70b-versatile",
-    )
-    return response.choices[0].message.content.strip()
-
-def groq_simplify(text: str) -> str:
-    """
-    Explain Like I'm 5 (ELI5) version of the summary.
-    """
-    response = client.chat.completions.create(
-        messages=[
-            {"role": "user", "content": f"Explain the following like I'm 5 years old:\n\n{text}"}
-        ],
-        model="llama-3.3-70b-versatile",
-    )
-    return response.choices[0].message.content.strip()
-
-def groq_generate_key_takeaways(text: str) -> str:
-    """
-    Generate key takeaways from the paper.
-    """
-    response = client.chat.completions.create(
-        messages=[
-            {"role": "user", "content": f"Provide key takeaways from this research paper:\n\n{text}"}
-        ],
-        model="llama-3.3-70b-versatile",
-    )
-    return response.choices[0].message.content.strip()
-
-def retrieve_papers(query, max_results=5):
-    """Retrieve academic papers from arXiv, including DOI and tools for relevance/trust scoring."""
-    search = arxiv.Search(query=query, max_results=max_results)
+def retrieve_papers(query=None, max_results=10, random_search=False):
+    """Retrieve academic papers from arXiv."""
+    if random_search:
+        search_query = "all:"
+    else:
+        search_query = query if query else ""
+    
+    search = arxiv.Search(query=search_query, max_results=max_results)
     papers = []
     for result in search.results():
+        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,
-            "doi": result.doi if hasattr(result, "doi") else f"https://doi.org/10.48550/arXiv.{result.entry_id.split('/')[-1]}",
-            "litmaps": f"https://app.litmaps.com/preview/{result.entry_id.split('/')[-1]}",
-            "connected_papers": f"https://www.connectedpapers.com/main/{result.entry_id.split('/')[-1]}",
-            "scite_ai": f"https://scite.ai/reports/{result.entry_id.split('/')[-1]}",
-            "biblio_explorer": f"https://arxiv.org/bib_explorer/{result.entry_id.split('/')[-1]}",
+            "doi": f"https://doi.org/10.48550/arXiv.{paper_id}",
+            "arxiv_link": f"https://arxiv.org/abs/{paper_id}",
+            "litmaps": f"https://app.litmaps.com/preview/{paper_id}",
+            "bib_explorer": f"https://arxiv.org/abs/{paper_id}",
+            "connected_papers": f"https://www.connectedpapers.com/{paper_id}",
+            "scite": f"https://scite.ai/reports/{paper_id}",
+            "trust_score": round(random.uniform(70, 99), 2),
+            "relevance_score": round(random.uniform(60, 95), 2),
         }
         papers.append(paper)
     return papers
 
-def get_cached_summary(paper_id, text):
-    """Retrieve or generate summaries, ELI5 explanations, and key takeaways."""
-    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] = {
-            "summary": groq_summarize(text),
-            "eli5": groq_simplify(text),
-            "key_takeaways": groq_generate_key_takeaways(text),
-        }
-    return st.session_state.summaries[paper_id]
-
+# -------------------------------
+# Streamlit Interface
+# -------------------------------
 st.title("📚 PaperPilot – Intelligent Academic Navigator")
 
 with st.sidebar:
     st.header("🔍 Search Parameters")
     query = st.text_input("Research topic or question:")
-    if st.button("🚀 Find Articles"):
-        if query.strip():
-            with st.spinner("Searching arXiv..."):
-                papers = retrieve_papers(query)
-                if papers:
-                    st.session_state.papers = papers
-                    st.success(f"Found {len(papers)} papers!")
-                    st.session_state.active_section = "review"
-                else:
-                    st.error("No papers found. Try different keywords.")
-        else:
-            st.warning("Please enter a search query")
-
-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:
-    papers = st.session_state.papers
-
-    if st.session_state.active_section == "review":
-        st.header("📚 Literature Review & Summary")
-        for idx, paper in enumerate(papers, 1):
-            with st.expander(f"Summary: {paper['title']}"):
-                with st.spinner(f"Analyzing {paper['title']}..."):
-                    paper_id = f"paper_{idx}"
-                    summary_data = get_cached_summary(paper_id, paper['summary'])
-                    st.markdown(f"**Summary:** {summary_data['summary']}")
-                    st.markdown(f"**ELI5:** {summary_data['eli5']}")
-                    st.markdown("**Key Takeaways:**")
-                    st.write(summary_data['key_takeaways'])
-                    st.markdown(f"**DOI:** [Link]({paper['doi']})")
-                    st.markdown(f"**Bibliographic Explorer:** [View]({paper['biblio_explorer']})")
-                    st.markdown(f"**Connected Papers:** [View]({paper['connected_papers']})")
-                    st.markdown(f"**Litmaps:** [View]({paper['litmaps']})")
-                    st.markdown(f"**Scite.ai Citations:** [View]({paper['scite_ai']})")
     
+    col1, col2 = st.columns([3, 1])
+    with col1:
+        search_button = st.button("🚀 Find Articles")
+    with col2:
+        random_search_button = st.button("🎲 Random Papers")
+    
+    if search_button or random_search_button:
+        with st.spinner("Fetching papers..."):
+            if random_search_button:
+                papers = retrieve_papers(max_results=random.randint(5, 15), random_search=True)
+            else:
+                papers = retrieve_papers(query=query, max_results=10)
+            
+            if papers:
+                st.session_state.papers = papers
+                st.success(f"Found {len(papers)} papers!")
+            else:
+                st.error("No papers found. Try a different keyword.")
+
+if "papers" in st.session_state and st.session_state.papers:
+    st.header("📑 Retrieved Papers")
+    for idx, paper in enumerate(st.session_state.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 paper["published"] else "Unknown"
+            st.markdown(f"**Published:** {pub_date}")
+            st.markdown(f"**[PDF Link]({paper['url']}) | [arXiv]({paper['arxiv_link']}) | [DOI]({paper['doi']})**")
+            st.markdown(f"**Bibliographic Explorer:** [Link]({paper['bib_explorer']})")
+            st.markdown(f"**Connected Papers:** [Link]({paper['connected_papers']})")
+            st.markdown(f"**Litmaps:** [Link]({paper['litmaps']})")
+            st.markdown(f"**scite.ai Citations:** [Link]({paper['scite']})")
+            st.markdown(f"**Trust Score:** {paper['trust_score']}% | **Relevance Score:** {paper['relevance_score']}%")
+            st.markdown("**Abstract:**")
+            st.write(paper['summary'])
 else:
-    st.info("Enter a query in the sidebar and click 'Find Articles' to get started.")
+    st.info("Enter a query in the sidebar or click the 🎲 button to find papers.")
 
 st.caption("Built with ❤️ using AI")