Deleted memory tool 3

crew.py

@@ -146,7 +146,17 @@ class GAIACrew():
 
 
 def run_crew(question, file_path):
-    # 0) Prepend file data if needed
+    """
+    Orchestrates the GAIA crew to answer a question, optionally with a file.
+
+    Args:
+        question (str): The user's question.
+        file_path (str): Optional path to a data file to include in the prompt.
+
+    Returns:
+        str: The final answer from the manager agent.
+    """
+    # Build the final prompt, including file JSON if needed
     final_question = question
     if file_path:
         if is_ext(file_path, ".csv") or is_ext(file_path, ".xls") \
@@ -156,33 +166,21 @@ def run_crew(question, file_path):
             final_question = f"{question} JSON data:\n{json_data}."
         else:
             final_question = f"{question} File path: {file_path}."
-
-    # 1) Load memory (relevant recall)
-    history = memory_tool.run("load", question)
-    # In case some other implementation returns a list, handle it:
-    if isinstance(history, list):
-        history = "\n".join(history)
-
-    # 2) Build the prompt we send to Crew
-    #    If there is history, prefix it; otherwise just use the question
-    full_input = (history + "\n" if history else "") + final_question
-
-    # 3) Run the multi-agent Crew
+    
+    # Instantiate the crew and kick off the workflow
     crew_instance = GAIACrew()
-    raw_answer   = crew_instance.get_crew().kickoff(inputs={"question": full_input})
-
-    # 4) Save only the **user** question for future recall
-    memory_tool.run("save", question)
-
-    # 5) Post-process for the “final answer”
-    final_answer = get_final_answer(FINAL_ANSWER_MODEL, question, str(raw_answer))
-
-    # 6) (Optional) print debug traces
-    print(f"=> History:\n{history}")
-    print(f"=> Prompt sent:\n{full_input}")
-    print(f"=> Raw answer:\n{raw_answer}")
-    print(f"=> Final answer:\n{final_answer}")
-
+    crew = crew_instance.get_crew()
+    answer = crew.kickoff(inputs={"question": final_question})
+    
+    # Post-process through the final-answer model
+    final_answer = get_final_answer(FINAL_ANSWER_MODEL, question, str(answer))
+
+    # Debug logging
+    print(f"=> Initial question: {question}")
+    print(f"=> Final question: {final_question}")
+    print(f"=> Initial answer: {answer}")
+    print(f"=> Final answer: {final_answer}")
+    
     return final_answer