Update src/streamlit_app.py

src/streamlit_app.py

@@ -7,48 +7,78 @@ from llama_index.core.agent import ReActAgent
 from llama_index.core.workflow import Context 
 from llama_index.core.tools import FunctionTool
 
-# --- Import tools class ---
-from tools import PokemonAdvisorTools
-
-# --- 1. Setup Tools & LLM (Cached to prevent reloading on every click) ---
-@st.cache_resource
-def initialize_agent():
-    advisor = PokemonAdvisorTools()
-    tool_methods = [
-        advisor.get_card_info,
-        advisor.find_grading_opportunities,
-        advisor.assess_risk_volatility,
-        advisor.get_roi_metrics,
-        advisor.get_recent_price_spikes,
-        advisor.analyze_set_performance,
-        advisor.find_cards_by_artist,
-        advisor.get_market_movers
-    ]
-    tools = [FunctionTool.from_defaults(fn=func) for func in tool_methods]
-    llm = OpenAI(model="gpt-4o-mini")
-    
-    system_prompt = """### ROLE
-You are the **Poke-Alpha Investment Advisor**, an expert algorithmic trading assistant for the Pokémon TCG market.
-You rely **strictly** on data. You do not guess. You do not hallucinate prices.
+# --- 1. Setup Tools & LLM ---
+# Instantiate the class to load data
+advisor = PokemonAdvisorTools()
+
+# Create the list of tool methods to wrap
+tool_methods = [
+    advisor.get_card_info,
+    advisor.find_grading_opportunities,
+    advisor.assess_risk_volatility,
+    advisor.get_roi_metrics,
+    advisor.get_recent_price_spikes,
+    advisor.analyze_set_performance,
+    advisor.find_cards_by_artist,
+    advisor.get_market_movers
+]
+
+# Wrap tools into LlamaIndex FunctionTools
+tools = [FunctionTool.from_defaults(fn=func) for func in tool_methods]
+
+# Initialize the LLM (Ensure OPENAI_API_KEY is set in your env)
+llm = OpenAI(model="gpt-4o-mini", temperature=0.6)
+
+# --- 2. System Prompt ---
+system_prompt = """
+### ROLE
+You are the **cAsh, Pokemon Investment Advisor**, an expert algorithmic trading assistant for the Pokemon TCG market.
+You rely **strictly** on data. You do not guess. You do not hallucinate prices. Always answer in English.
 
 ### TOOL USAGE PROTOCOL
 1. **Verify First:** If a user asks about a card, ALWAYS use `get_card_info` first to ensure it exists.
 2. **Safety Check:** BEFORE recommending ANY card, you MUST call `assess_risk_volatility` (default to 6 months).
-3. **Refining Search:** If the user corrects you (e.g., "Not that card"), use `get_card_info` again.
-4. **Profit Hunting:** If a user asks "What should I buy?", use `find_grading_opportunities` or `get_market_movers`."""
-
-    agent = ReActAgent(
-        tools=tools, 
-        llm=llm, 
-        verbose=True, 
-        system_prompt=system_prompt,
-        timeout=120
-    )
-    # Context should be initialized once
-    ctx = Context(agent)
-    return agent, ctx
-
-agent, global_ctx = initialize_agent()
+3. **Refining Search:** If the user corrects you (e.g., "Not that card"), use `get_card_info` again with the corrected name or use `analyze_set_performance` to broaden the scope.
+4. **Profit Hunting:** If a user asks "What should I buy?", use `find_grading_opportunities` or `get_market_movers`.
+
+### TONE
+Professional, objective, and user-friendly.
+"""
+# --- 3. Initialize Agent & Global Memory ---
+# We use timeout=120 because deep reasoning sequences can take time
+agent = ReActAgent(
+    tools=tools, 
+    llm=llm, 
+    verbose=True, 
+    system_prompt=system_prompt,
+    timeout=120
+)
+
+# Global Context acts as the "Server Memory" for this session
+global_ctx = Context(agent)
+
+# --- 4. Define the Chat Function (Async) ---
+async def ask_advisor(user_message, history):
+    st.session_state.messages.append({"role": "user", "content": user_message})
+    """
+    Async function to handle the chat. 
+    It uses 'global_ctx' to maintain memory of previous turns/corrections.
+    """
+    if not user_message:
+        return "Please enter a message."
+
+    try:
+        # Execute the agent workflow
+        # The 'ctx' argument passes the memory of previous interactions
+        response = await agent.run(user_msg=user_message, ctx=global_ctx)
+        final_text = str(response)
+        response_placeholder.markdown(final_text)
+        st.session_state.messages.append({"role": "assistant", "content": final_text})        
+        # Return the final text response
+        return str(response)
+        
+    except Exception as e:
+        return f"⚠️ **Agent Error:** {str(e)}\n\n*Check the console logs for detailed tool output.*"
 
 # --- 2. Page Configuration ---
 st.set_page_config(page_title="cAsh Robo-Advisor", page_icon="🤖", layout="wide")
@@ -105,4 +135,5 @@ if prompt := st.chat_input("Ask your Pokemon Quants advisor..."):
     with st.chat_message("user"):
         st.markdown(prompt)
     
-    asyncio.run(process_chat(prompt))
+    # asyncio.run(process_chat(prompt))
+    await ask_advisor(prompt)