Final Agent form

app.py

@@ -102,6 +102,14 @@ class BasicAgent:
                 new_rows.append(new_row)
             
             # Append all new rows at once
+            final_row = {
+                'task_id': task_id,
+                'step_class': 'FinalAnswerStep',
+                'model_input_messages': [question],
+                'model_output_message': fixed_answer,
+                'model_output': fixed_answer,
+            }
+            new_rows.append(final_row)
             if new_rows:
                 df_agent_steps = pd.concat([df_agent_steps, pd.DataFrame(new_rows)], ignore_index=True)
             

mini_agents.py

@@ -99,6 +99,7 @@ arithmetic_agent = CodeAgent(
     model=arithmetic_model,
     tools=[operate_two_numbers, convert_number],
     max_steps=4,
+    planning_interval=4,
     additional_authorized_imports=AUTHORIZED_IMPORTS,
     name="arithmetic_agent",
     description="This agent is responsible for performing arithmetic operations on two numbers."
@@ -114,6 +115,7 @@ pandas_agent = CodeAgent(
     model=pandas_model,
     tools=[load_dataframe_from_csv, load_dataframe_from_excel, to_dataframe, to_json, get_dataframe_data, get_dataframe_column, get_dataframe_row, get_dataframe_groupby],
     max_steps=4,
+    planning_interval=4,
     additional_authorized_imports=AUTHORIZED_IMPORTS,
     name="pandas_agent",
     description="This agent is responsible for converting data to a dataframe, performing pandas operations on such dataframe and converting the dataframe back to a json or a csv file."
@@ -167,10 +169,10 @@ class MasterAgentWrapper:
             managed_agents=[audio_agent, vlm_agent, arithmetic_agent, pandas_agent],
             tools=self.base_tools,  # Initialize without browser tools
             add_base_tools=False,
-            max_steps=16,
+            max_steps=17, #One final plan step, 16 intermediate steps
             additional_authorized_imports=AUTHORIZED_IMPORTS,
             verbosity_level=logging.INFO,
-            planning_interval=3,
+            planning_interval=4,
             prompt_templates=PROMPT_TEMPLATE["master_agent"],
             name="master_agent",
             description="This agent is responsible for managing audio, vlm, arithmetic and pandas agents."

prompts/prompts.yaml

@@ -23,8 +23,8 @@ system_prompt: |-
   All information in the 'Observation:' sequence will be available as input for the next step.
   In the end you have to return a final answer using the `final_answer` tool.
 
-  It is advised to have at least 2 steps in your plan. One step is not sufficient.
-  It is also advised to double check your answer before calling the `final_answer` tool.
+  It is advised to have at least 3 steps in your plan. One or two steps is not sufficient.
+  It is advised to double check your answer before calling the `final_answer` tool.
 
   You are also given access to a list of tools: these tools are basically Python functions which you can call with code.
   Here are a few examples using notional tools: