Update app.py

app.py

@@ -1,6 +1,10 @@
 # ------------------------------
-# Imports & Dependencies
+# Imports & Initial Configuration
 # ------------------------------
+import streamlit as st
+# Set the page configuration immediately—this must be the first Streamlit command.
+st.set_page_config(page_title="NeuroResearch AI", layout="wide", initial_sidebar_state="expanded")
+
 from langchain_openai import OpenAIEmbeddings
 from langchain_community.vectorstores import Chroma
 from langchain_core.messages import HumanMessage, AIMessage, ToolMessage
@@ -13,7 +17,6 @@ from typing import Sequence, Dict, List, Optional, Any
 import chromadb
 import re
 import os
-import streamlit as st
 import requests
 import hashlib
 import json
@@ -64,9 +67,9 @@ Format: Markdown with LaTeX mathematical notation where applicable
 # Validate API key configuration
 if not ResearchConfig.DEEPSEEK_API_KEY:
     st.error("""**Research Portal Configuration Required**  
-    1. Obtain DeepSeek API key: [platform.deepseek.com](https://platform.deepseek.com/)  
-    2. Configure secret: `DEEPSEEK_API_KEY` in Space settings  
-    3. Rebuild deployment""")
+1. Obtain DeepSeek API key: [platform.deepseek.com](https://platform.deepseek.com/)  
+2. Configure secret: `DEEPSEEK_API_KEY` in Space settings  
+3. Rebuild deployment""")
     st.stop()
 
 # ------------------------------
@@ -87,7 +90,7 @@ class QuantumDocumentManager:
             separators=["\n\n", "\n", "|||"]
         )
         docs = splitter.create_documents(documents)
-        # Log how many chunks were created
+        # Debug: log the number of chunks created for the collection.
         st.write(f"Created {len(docs)} chunks for collection '{collection_name}'")
         return Chroma.from_documents(
             documents=docs,
@@ -202,7 +205,7 @@ class CognitiveProcessor:
         valid = [r for r in results if "error" not in r]
         if not valid:
             return {"error": "All API requests failed"}
-        # Choose the result with the longest content
+        # Choose the result with the longest content for robustness.
         return max(valid, key=lambda x: len(x.get('choices', [{}])[0].get('message', {}).get('content', '')))
 
 # ------------------------------
@@ -251,7 +254,6 @@ class ResearchWorkflow:
         try:
             query = state["context"]["raw_query"]
             docs = retriever.retrieve(query, "research")
-            # Log the retrieval result for debugging
             st.write(f"[DEBUG] Retrieved {len(docs)} documents from retrieval node.")
             return {
                 "messages": [AIMessage(content=f"Retrieved {len(docs)} documents")],
@@ -265,11 +267,11 @@ class ResearchWorkflow:
 
     def analyze_content(self, state: AgentState) -> Dict:
         try:
-            # Ensure documents are present before proceeding
+            # Ensure documents are present before proceeding.
             if "documents" not in state["context"] or not state["context"]["documents"]:
                 return self._error_state("No documents retrieved; please check your query or retrieval process.")
             
-            # Concatenate all document content for analysis
+            # Concatenate all document content for analysis.
             docs = "\n\n".join([d.page_content for d in state["context"]["documents"] if hasattr(d, "page_content")])
             st.write(f"[DEBUG] Analyzing content from {len(state['context']['documents'])} documents.")
             prompt = ResearchConfig.ANALYSIS_TEMPLATE.format(context=docs)
@@ -320,7 +322,6 @@ Improve:
 
     def _quality_check(self, state: AgentState) -> str:
         content = state["messages"][-1].content
-        # Check for the keyword "VALID" in the output; if missing, trigger refinement
         return "valid" if "VALID" in content else "invalid"
 
     def _error_state(self, message: str) -> Dict:
@@ -337,14 +338,7 @@ Improve:
 class ResearchInterface:
     def __init__(self):
         self.workflow = ResearchWorkflow()
-        self._initialize_interface()
-
-    def _initialize_interface(self):
-        st.set_page_config(
-            page_title="NeuroResearch AI",
-            layout="wide",
-            initial_sidebar_state="expanded"
-        )
+        # Do not call st.set_page_config here because it has already been called at the top.
         self._inject_styles()
         self._build_sidebar()
         self._build_main_interface()
@@ -410,7 +404,7 @@ class ResearchInterface:
     def _build_main_interface(self):
         st.title("🧠 NeuroResearch AI")
         query = st.text_area("Research Query:", height=200,
-                           placeholder="Enter technical research question...")
+                             placeholder="Enter technical research question...")
         
         if st.button("Execute Analysis", type="primary"):
             self._execute_analysis(query)
@@ -421,10 +415,8 @@ class ResearchInterface:
                 results = self.workflow.app.stream(
                     {"messages": [HumanMessage(content=query)], "context": {}, "metadata": {}}
                 )
-                
                 for event in results:
                     self._render_event(event)
-                
                 st.success("✅ Analysis Completed Successfully")
         except Exception as e:
             st.error(f"""**Analysis Failed**
@@ -438,7 +430,6 @@ Potential issues:
         if 'ingest' in event:
             with st.container():
                 st.success("✅ Query Ingested")
-                
         elif 'retrieve' in event:
             with st.container():
                 docs = event['retrieve']['context']['documents']
@@ -447,13 +438,11 @@ Potential issues:
                     for i, doc in enumerate(docs, 1):
                         st.markdown(f"**Document {i}**")
                         st.code(doc.page_content, language='text')
-                        
         elif 'analyze' in event:
             with st.container():
                 content = event['analyze']['messages'][0].content
                 with st.expander("Technical Analysis Report", expanded=True):
                     st.markdown(content)
-                    
         elif 'validate' in event:
             with st.container():
                 content = event['validate']['messages'][0].content