Read system prompt from file

agent.py

@@ -1,4 +1,5 @@
 import os
+from pathlib import Path
 from dotenv import load_dotenv
 from langgraph.graph import START, StateGraph, MessagesState
 from langgraph.prebuilt import tools_condition
@@ -15,6 +16,7 @@ from tools.search_tools import search_wikipedia, web_search
 from tools.image_video_tools import query_image
 from tools.file_tools import analyze_excel_file
 
+system_prompt = Path("system_prompt.txt").read_text()
 
 # embeddings = HuggingFaceEmbeddings(model_name="sentence-transformers/all-mpnet-base-v2") #  dim=768
 # supabase: Client = create_client(
@@ -50,7 +52,7 @@ def build_graph():
         messages = state["messages"]
         # Add system message if not present
         if not any(isinstance(m, SystemMessage) for m in messages):
-            messages = [SystemMessage(content="You are a helpful AI assistant. Use the available tools to answer questions accurately. When providing your final answer, use the format: FINAL ANSWER: [your answer]")] + messages
+            messages = [SystemMessage(content=system_prompt)] + messages
         response = llm_with_tools.invoke(messages)
         return {"messages": [response]}
     

app.py

@@ -32,10 +32,10 @@ class BasicAgent:
             if match:
                 final_answer = match.group(1).strip()
             else:
-                # Fallback: Use last non-empty line
-                lines = [line.strip() for line in last_message.split("\n") if line.strip()]
-                final_answer = lines[-1] if lines else last_message.strip()
-
+               # Try to find a name or string answer
+                candidates = [line.strip() for line in last_message.split("\n") if line.strip()]
+                final_answer = next((line for line in reversed(candidates) if len(line.split()) <= 5), last_message.strip())
+                
             return final_answer
         except Exception as e: 
             print("Agent processing failed")