Update app.py

app.py

@@ -290,8 +290,6 @@ extracted_info = extracted_info or st.session_state.get("last_extracted_info", N
 
 # --------- Classic ReAct AGENT ---------
 def po_match_tool_func(input_text):
-    # This tool receives a string "query" (not structured context!) so it must access globals or session
-    # We'll use the extracted_info and po_df from session
     invoice = st.session_state.get("last_extracted_info")
     po_df = st.session_state.get("po_df")
 
@@ -320,13 +318,11 @@ def po_match_tool_func(input_text):
         return f"PO matched: {matched_po.to_dict()}"
     return "No matching PO found."
 
-# Save PO df to session for tool access
 if po_df is not None:
     st.session_state["po_df"] = po_df
 
 if extracted_info is not None and po_df is not None:
     if st.button("Make a decision (AI Agent)"):
-        # Define the tool for the agent (takes input string, outputs string)
         tools = [
             Tool(
                 name="po_match_tool",
@@ -334,7 +330,6 @@ if extracted_info is not None and po_df is not None:
                 description="Use this tool to check if the invoice matches any PO in the current PO list.",
             )
         ]
-        # Use session state for the LLM agent
         openai_api_key = os.getenv("OPENAI_API_KEY")
         llm = ChatOpenAI(
             openai_api_key=openai_api_key,
@@ -348,16 +343,22 @@ if extracted_info is not None and po_df is not None:
             agent=AgentType.ZERO_SHOT_REACT_DESCRIPTION,
             verbose=True,
         )
-        # Build the prompt
         prompt = (
             f"Below is an extracted invoice in JSON and a list of active POs is loaded in the system. "
-            f"Use po_match_tool to check if the invoice matches an active PO. "
+            f"Use po_match_tool to check if the invoice matches any PO in the current PO list. "
             f"Step by step, reason whether the invoice matches an active PO and can be approved. "
             f"If there is a match, state the matched PO, otherwise explain why not. "
-            f"Give a clear final decision: APPROVED or REJECTED.\n"
+            f"At the end, respond with a JSON like this: "
+            f'{{"decision": "APPROVED or REJECTED", "reason": "<short explanation>"}}.\n'
             f"Invoice JSON:\n{json.dumps(extracted_info, indent=2)}"
         )
         with st.spinner("AI is reasoning and making a decision..."):
             result = agent.run(prompt)
-        st.subheader("AI Decision")
-        st.write(result)
+        try:
+            result_json = json.loads(result)
+            st.subheader("AI Decision")
+            st.write(f"**Decision:** {result_json.get('decision', 'N/A')}")
+            st.write(f"**Reason:** {result_json.get('reason', 'N/A')}")
+        except Exception:
+            st.subheader("AI Decision & Reason")
+            st.write(result)