Update app.py

app.py

@@ -14,6 +14,7 @@ from langchain_tavily import TavilySearch
 from tools import (
     download_task_file,
     read_attached_text_file,
+    answer_image_question,
     answer_excel_question,
     answer_python_question,
     get_youtube_transcript,
@@ -45,11 +46,12 @@ class BasicAgent:
             temperature=0,
             timeout=30,
             max_retries=1,
-            max_tokens=128,
+            max_tokens=1024,
         )
         self.tools = [
             download_task_file,
             read_attached_text_file,
+            answer_image_question,
             answer_excel_question,
             answer_python_question,
             get_youtube_transcript,
@@ -97,10 +99,27 @@ class BasicAgent:
             print(f"Agent error: {e}", flush=True)
             return ""
     def assistant(self, state: AgentState):
-        sys_msg = SystemMessage(content=f"""
-            You are a precise question-answering agent. 
-            Answer the question directly and concisely. 
-            Return only the final answer, without explanation, unless explanation is necessary.
+        sys_msg = SystemMessage(content="""
+        You are a precise question-answering agent.
+        
+        Use tools aggressively when the question involves:
+        - attached files
+        - images or screenshots
+        - spreadsheets
+        - Python code files
+        - YouTube videos
+        - web lookup
+        
+        Tool policy:
+        - For image, screenshot, chess position, chart image, diagram, or visual counting questions, use answer_image_question.
+        - For Excel or CSV questions, use answer_excel_question.
+        - For Python-code-output questions, use answer_python_question.
+        - For plain text attachments, use read_attached_text_file.
+        - For YouTube speech/transcript questions, use get_youtube_transcript.
+        - For current or external factual lookup, use web search.
+        
+        Answer directly and concisely.
+        Return only the final answer unless explanation is necessary.
         """)
         return {
             "messages": [self.chat_with_tools.invoke([sys_msg] + state["messages"])],