Update src/streamlit_app.py

src/streamlit_app.py

@@ -28,6 +28,7 @@ st.markdown("""
         border-radius: 5px;
         height: 3em;
         background-color: #f0f2f6;
+        border: 1px solid #d1d5db;
     }
     .reportview-container {
         background: #ffffff;
@@ -35,22 +36,34 @@ st.markdown("""
     </style>
 """, unsafe_allow_html=True)
 
-# Ensure keys exist
 if "OPENAI_API_KEY" not in os.environ:
     st.error("❌ OPENAI_API_KEY missing. Please check Space Settings.")
     st.stop()
 
-# --- 2. DATA MODELS ---
+# --- 2. DATA MODELS (WITH REQUIRED DOCSTRINGS) ---
 class AgentResponse(BaseModel):
+    """
+    Structured output for the financial agent. 
+    Contains the synthesized natural language answer, the list of cited sources, 
+    and the raw context chunks used to formulate the answer.
+    """
     answer: str
     sources: List[str]
     context_used: List[str]
 
 class TickerExtraction(BaseModel):
-    symbols: List[str] = Field(description="List of stock tickers.")
+    """
+    Extracts a list of stock tickers or company names mentioned in the user's query.
+    Used to identify which companies the user wants to research.
+    """
+    symbols: List[str] = Field(description="List of stock tickers or company names.")
 
 class RoutePrediction(BaseModel):
-    tools: List[Literal["financial_rag", "market_data", "general_chat"]] = Field(description="Tools list")
+    """
+    Determines which tools to use based on the user's query.
+    Can select multiple tools if the query requires both financial RAG and market data.
+    """
+    tools: List[Literal["financial_rag", "market_data", "general_chat"]] = Field(description="List of selected tools.")
 
 # --- 3. CACHED INITIALIZATION ---
 @st.cache_resource(show_spinner=False)
@@ -86,6 +99,9 @@ def initialize_resources():
     
     return nasdaq_df, index
 
+# Silently load resources
+nasdaq_df, pinecone_index = initialize_resources()
+
 # --- 4. HELPER FUNCTIONS ---
 def get_symbol_from_csv(query_str: str, df) -> Optional[str]:
     if df.empty: return None
@@ -206,31 +222,15 @@ def run_agent(user_query: str, index, df) -> AgentResponse:
 # --- 7. UI LOGIC ---
 with st.sidebar:
     st.image("https://img.icons8.com/color/96/000000/bullish.png", width=80)
-    st.title("System Status")
     
-    with st.spinner("Connecting to Wall St..."):
-        nasdaq_df, pinecone_index = initialize_resources()
-    
-    if not nasdaq_df.empty:
-        st.success(f"✅ Market Data: {len(nasdaq_df):,} Tickers")
-    else:
-        st.warning("⚠️ Market Data: Offline")
-        
-    if pinecone_index:
-        st.success("✅ Knowledge Base: Online")
-    else:
-        st.error("❌ Knowledge Base: Offline")
-    
-    st.markdown("---")
-    st.markdown("### 🧠 Capabilities")
+    st.markdown("### 🧠 Agent Capabilities")
     
     st.info("**Deep Dive (10-K Reports)**")
-    st.markdown("- 🍎 Apple (AAPL)\n- 🚗 Tesla (TSLA)\n- 🎮 Nvidia (NVDA)")
-    st.caption("*Ask about Strategy, Risks, Revenue*")
+    st.markdown("I have ingested the full SEC 10-K filings for the following companies:")
+    st.markdown("- 🍎 **Apple (AAPL)**\n- 🚗 **Tesla (TSLA)**\n- 🎮 **Nvidia (NVDA)**")
     
-    st.info("**Live Market Data**")
-    st.markdown("- 🌍 All NASDAQ Companies")
-    st.caption("*Ask about Price, PE Ratio, Volume*")
+    st.success("**Live Market Data**")
+    st.markdown("I can fetch real-time trading metrics for **all companies listed on the NASDAQ**.")
     
     st.markdown("---")
     if st.button("🧹 Clear Conversation"):
@@ -240,19 +240,30 @@ with st.sidebar:
 # Main Hero Section
 st.title("🏛️ Wall St. AI Analyst")
 st.markdown("""
-**Your Hybrid Financial Assistant.** I bridge the gap between **Real-Time Market Data** and **Deep 10-K Analysis**.
+Welcome! This hybrid AI agent bridges the gap between **Real-Time Market Data** and **Deep 10-K Analysis**. 
+It utilizes a dynamic routing engine to fetch real-time quantitative metrics via `yfinance` and qualitative insights from a Pinecone Vector Database.
 """)
 
-# Quick Start Buttons
-col1, col2, col3 = st.columns(3)
-if col1.button("🆚 Compare Risks"):
-    prompt = "Compare the supply chain risks of Apple and Tesla."
-elif col2.button("📊 Apple vs Nvidia Revenue"):
-    prompt = "Compare the revenue growth of Apple and Nvidia."
-elif col3.button("📈 Tesla PE & Price"):
-    prompt = "What is the current price and PE ratio of Tesla?"
-else:
-    prompt = None
+# Sample Questions Section
+with st.expander("💡 View Sample Questions", expanded=True):
+    st.markdown("""
+    **Try asking about Qualitative 10-K Data:**
+    * *"What are the primary supply chain risks mentioned in Apple's latest 10-K?"*
+    * *"Who is the CEO of Nvidia and what is their strategy?"*
+    
+    **Try asking for Real-Time Quantitative Data:**
+    * *"What is the current PE ratio and market cap of Tesla?"*
+    * *"Fetch the trading volume and 52-week high for Microsoft."*
+    
+    **Try a Hybrid Search (Live Data + RAG):**
+    * *"Compare the competitive threats facing Tesla with its current stock price."*
+    """)
+    
+    # Single Automated Action Button
+    if st.button("🚀 Auto-Run a Complex Query: Compare Apple & Tesla Risks"):
+        prompt = "Compare the supply chain risks of Apple and Tesla."
+    else:
+        prompt = None
 
 # Chat State
 if "messages" not in st.session_state:
@@ -272,7 +283,6 @@ for message in st.session_state.messages:
 
 # Handle Input (Button or Text)
 if user_input := st.chat_input("Ask a financial question...") or prompt:
-    # If button was clicked, override text input
     final_query = prompt if prompt else user_input
     
     st.session_state.messages.append({"role": "user", "content": final_query})
@@ -280,7 +290,7 @@ if user_input := st.chat_input("Ask a financial question...") or prompt:
         st.markdown(final_query)
 
     with st.chat_message("assistant"):
-        # Status container (collapsible)
+        # The spinner happens here
         with st.status("🧠 Analyzing 10-Ks and Market Data...", expanded=True) as status:
             try:
                 response = run_agent(final_query, pinecone_index, nasdaq_df)
@@ -290,7 +300,7 @@ if user_input := st.chat_input("Ask a financial question...") or prompt:
                 status.update(label="❌ Error", state="error")
                 st.stop()
 
-        # ANSWER DISPLAY (Now OUTSIDE the status block so it auto-shows)
+        # The answer prints outside the status block so it is immediately visible!
         st.markdown(response.answer)
         
         # Sources (Collapsible)