remove function

app.py

@@ -1,10 +1,6 @@
-# app.py
-
 import os
 import streamlit as st
 import arxiv
-import networkx as nx
-import matplotlib.pyplot as plt
 import datetime
 
 # -------------------------------
@@ -20,42 +16,36 @@ client = Groq(
 # Helper Functions (Groq-based)
 # -------------------------------
 def groq_summarize(text: str) -> str:
-    """
-    Summarize the given text using Groq's chat completion API.
-    Adjust the prompt or model as needed.
-    """
     response = client.chat.completions.create(
         messages=[
-            {
-                "role": "user",
-                "content": f"Summarize the following text in detail:\n\n{text}"
-            }
+            {"role": "user", "content": f"Summarize the following text concisely:\n\n{text}"}
+        ],
+        model="llama-3.3-70b-versatile",
+    )
+    return response.choices[0].message.content.strip()
+
+def groq_eli5(text: str) -> str:
+    response = client.chat.completions.create(
+        messages=[
+            {"role": "user", "content": f"Explain this 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(text: str) -> str:
-    """
-    Generate text (e.g., research proposals) using Groq's chat completion API.
-    Adjust the prompt or model as needed.
-    """
+def groq_key_takeaways(text: str) -> str:
     response = client.chat.completions.create(
         messages=[
-            {
-                "role": "user",
-                "content": text
-            }
+            {"role": "user", "content": f"List the key takeaways from this research:\n\n{text}"}
         ],
         model="llama-3.3-70b-versatile",
     )
     return response.choices[0].message.content.strip()
 
 # -------------------------------
-# Existing Helper Functions
+# Paper Retrieval & Processing
 # -------------------------------
 def retrieve_papers(query, max_results=5):
-    """Retrieve academic papers from arXiv."""
     search = arxiv.Search(query=query, max_results=max_results)
     papers = []
     for result in search.results():
@@ -69,74 +59,16 @@ def retrieve_papers(query, max_results=5):
         papers.append(paper)
     return papers
 
-def summarize_text(text):
-    """
-    Wrap the groq_summarize function so it's easy to switch 
-    implementations if needed.
-    """
-    return groq_summarize(text)
-
-def generate_concept_map(papers):
-    """Create a concept map (graph) based on author connections."""
-    G = nx.Graph()
-    for paper in papers:
-        G.add_node(paper['title'])
-    for i in range(len(papers)):
-        for j in range(i + 1, len(papers)):
-            if set(papers[i]['authors']) & set(papers[j]['authors']):
-                G.add_edge(papers[i]['title'], papers[j]['title'])
-    return G
-
-def generate_citation(paper):
-    """Generate APA-style citation for a paper."""
-    authors = ", ".join(paper['authors'])
-    if isinstance(paper['published'], datetime.datetime):
-        year = paper['published'].year
-    else:
-        year = "n.d."
-    return f"{authors} ({year}). {paper['title']}. Retrieved from {paper['url']}"
-
-def generate_proposal_suggestions(text):
-    """
-    Generate novel research proposal suggestions based on text,
-    wrapping the groq_generate function.
-    """
-    prompt = (
-        f"Based on this research summary:\n\n{text}\n\n"
-        "Propose novel research directions:"
-    )
-    return groq_generate(prompt)
-
-def get_cached_summary(paper_id, text):
-    """
-    Retrieve or create a cached summary for a given paper.
-    This ensures each paper's summary is generated only once.
-    """
-    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]
-
 # -------------------------------
 # Streamlit Interface
 # -------------------------------
 st.title("📚 PaperPilot – Intelligent Academic Navigator")
 
-# Add the Overview subheading
 st.write("""
-PaperPilot is an intelligent academic navigator designed to simplify your research workflow. 
-With a single query, it fetches relevant academic papers and provides you with a 
-comprehensive toolkit to explore them in depth. You can read a quick summary of each article, 
-view a visual concept map to see how different papers are interlinked, generate properly 
-formatted citations, and even receive suggestions for novel research proposals. By integrating 
-state-of-the-art AI models, PaperPilot streamlines the entire literature review process—making 
-it easier to stay organized, discover new insights, and advance your academic endeavors.
+PaperPilot helps you quickly analyze research papers by summarizing them, highlighting key takeaways, and explaining complex topics in simple terms. 
+Enter a query and get structured insights instantly!
 """)
 
-# ---------------------------------
-# Sidebar: Search & Navigation
-# ---------------------------------
 with st.sidebar:
     st.header("🔍 Search Parameters")
     query = st.text_input("Research topic or question:")
@@ -148,120 +80,37 @@ with st.sidebar:
                 if papers:
                     st.session_state.papers = papers
                     st.success(f"Found {len(papers)} papers!")
-                    # Default to showing articles after retrieval
-                    st.session_state.active_section = "articles"
+                    st.session_state.active_section = "review"
                 else:
                     st.error("No papers found. Try different keywords.")
         else:
             st.warning("Please enter a search query")
 
-    # Navigation buttons (only relevant if we have papers in session)
-    if 'papers' in st.session_state and st.session_state.papers:
-        st.header("🔀 Navigation")
-        if st.button("📑 Show Articles"):
-            st.session_state.active_section = "articles"
-        if st.button("📚 Literature Review & Summary"):
-            st.session_state.active_section = "review"
-        if st.button("🔍 Concept & Visual Graph"):
-            st.session_state.active_section = "graph"
-        if st.button("📝 Formatted Citations"):
-            st.session_state.active_section = "citations"
-        if st.button("💡 Research Proposal"):
-            st.session_state.active_section = "proposal"
-
-# ---------------------------------
-# Main Content Area
-# ---------------------------------
-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
-
-    # ---------------------------------
-    # 1) Show Articles
-    # ---------------------------------
-    if st.session_state.active_section == "articles":
-        st.header("📑 Retrieved Papers")
+    
+    if st.session_state.active_section == "review":
+        st.header("📚 Literature Review & Summary")
         for idx, paper in enumerate(papers, 1):
             with st.expander(f"{idx}. {paper['title']}"):
                 st.markdown(f"**Authors:** {', '.join(paper['authors'])}")
-                if isinstance(paper['published'], datetime.datetime):
-                    pub_date = paper['published'].strftime('%Y-%m-%d')
-                else:
-                    pub_date = "n.d."
+                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"**Link:** [PDF Link]({paper['url']})")
-                st.markdown("**Abstract:**")
-                st.write(paper['summary'])
-
-    # ---------------------------------
-    # 2) Literature Review & Summary
-    # ---------------------------------
-    elif st.session_state.active_section == "review":
-        st.header("📚 Literature Review & Summary")
-        combined_summary = ""
-
-        for idx, paper in enumerate(papers, 1):
-            with st.expander(f"Summary: {paper['title']}", expanded=False):
-                with st.spinner(f"Analyzing {paper['title']}..."):
-                    paper_id = f"paper_{idx}"
-                    summary = get_cached_summary(paper_id, paper['summary'])
-                    st.write(summary)
-                    combined_summary += summary + "\n\n"
-
-        st.session_state.combined_summary = combined_summary
-
-    # ---------------------------------
-    # 3) Concept & Visual Graph
-    # ---------------------------------
-    elif st.session_state.active_section == "graph":
-        st.header("🔍 Concept & Visual Graph")
-        st.write(
-            "Below is a concept map that visualizes how the authors are "
-            "connected across the retrieved articles. Each node represents a paper, "
-            "and edges indicate shared authors."
-        )
-
-        with st.spinner("Generating concept map..."):
-            G = generate_concept_map(papers)
-            if G.nodes():
-                fig, ax = plt.subplots(figsize=(10, 8))
-                pos = nx.spring_layout(G, k=0.5, seed=42)
-                nx.draw_networkx_nodes(G, pos, node_color='skyblue', node_size=2000, ax=ax)
-                nx.draw_networkx_edges(G, pos, edge_color='#666666', ax=ax)
-                nx.draw_networkx_labels(G, pos, font_size=10, ax=ax)
-                ax.axis('off')
-                st.pyplot(fig)
-            else:
-                st.info("No significant connections found between papers.")
-
-    # ---------------------------------
-    # 4) Formatted Citations
-    # ---------------------------------
-    elif st.session_state.active_section == "citations":
-        st.header("📝 Formatted Citations (APA Style)")
-        for paper in papers:
-            st.markdown(f"- {generate_citation(paper)}")
-
-    # ---------------------------------
-    # 5) Research Proposal
-    # ---------------------------------
-    elif st.session_state.active_section == "proposal":
-        st.header("💡 Research Proposal Suggestions")
-
-        # Make sure we have a combined summary for the proposals
-        if 'combined_summary' not in st.session_state:
-            with st.spinner("Synthesizing research overview..."):
-                full_text = "\n".join([p['summary'] for p in papers])
-                st.session_state.combined_summary = summarize_text(full_text)
-
-        with st.spinner("Generating innovative ideas..."):
-            proposal = generate_proposal_suggestions(st.session_state.combined_summary[:2000])
-        st.write(proposal)
-
-    else:
-        st.info("Please select an option from the sidebar to begin.")
+                st.markdown(f"**Link:** [PDF]({paper['url']})")
+                
+                with st.spinner("Generating insights..."):
+                    short_description = groq_summarize(paper['summary'])
+                    key_takeaways = groq_key_takeaways(paper['summary'])
+                    eli5_explanation = groq_eli5(paper['summary'])
+                    
+                st.subheader("Short Description")
+                st.write(short_description)
+                
+                st.subheader("Key Takeaways")
+                st.write(key_takeaways)
+                
+                st.subheader("Explain Like I'm 5 (ELI5)")
+                st.write(eli5_explanation)
 else:
     st.info("Enter a query in the sidebar and click 'Find Articles' to get started.")