Implement Logging of Self-Feedback in logs/Debug Folder

autogpt/agent/agent.py

@@ -13,6 +13,8 @@
 from autogpt.log_cycle.log_cycle import (
     FULL_MESSAGE_HISTORY_FILE_NAME,
     NEXT_ACTION_FILE_NAME,
+    PROMPT_SUPERVISOR_FEEDBACK_FILE_NAME,
+    SUPERVISOR_FEEDBACK_FILE_NAME,
     USER_INPUT_FILE_NAME,
     LogCycleHandler,
 )
@@ -340,7 +342,24 @@ def get_self_feedback(self, thoughts: dict, llm_model: str) -> str:
         plan = thoughts.get("plan", "")
         thought = thoughts.get("thoughts", "")
         feedback_thoughts = thought + reasoning + plan
-        return create_chat_completion(
-            [{"role": "user", "content": feedback_prompt + feedback_thoughts}],
-            llm_model,
+
+        messages = {"role": "user", "content": feedback_prompt + feedback_thoughts}
+
+        self.log_cycle_handler.log_cycle(
+            self.config.ai_name,
+            self.created_at,
+            self.cycle_count,
+            messages,
+            PROMPT_SUPERVISOR_FEEDBACK_FILE_NAME,
+        )
+
+        feedback = create_chat_completion(messages)
+
+        self.log_cycle_handler.log_cycle(
+            self.config.ai_name,
+            self.created_at,
+            self.cycle_count,
+            feedback,
+            SUPERVISOR_FEEDBACK_FILE_NAME,
         )
+        return feedback

autogpt/log_cycle/log_cycle.py

@@ -10,6 +10,8 @@
 NEXT_ACTION_FILE_NAME = "next_action.json"
 PROMPT_SUMMARY_FILE_NAME = "prompt_summary.json"
 SUMMARY_FILE_NAME = "summary.txt"
+SUPERVISOR_FEEDBACK_FILE_NAME = "supervisor_feedback.txt"
+PROMPT_SUPERVISOR_FEEDBACK_FILE_NAME = "prompt_supervisor_feedback.json"
 USER_INPUT_FILE_NAME = "user_input.txt"
 
 

tests/unit/test_get_self_feedback.py

@@ -1,6 +1,9 @@
+from datetime import datetime
+
 from autogpt.agent.agent import Agent
 from autogpt.config import AIConfig
 from autogpt.llm import create_chat_completion
+from autogpt.log_cycle.log_cycle import LogCycleHandler
 
 
 def test_get_self_feedback(mocker):
@@ -31,6 +34,15 @@ def test_get_self_feedback(mocker):
     # Mock the config attribute of the Agent instance
     agent_mock.config = AIConfig()
 
+    # Mock the log_cycle_handler attribute of the Agent instance
+    agent_mock.log_cycle_handler = LogCycleHandler()
+
+    # Mock the create_nested_directory method of the LogCycleHandler instance
+    agent_mock.created_at = datetime.now().strftime("%Y%m%d_%H%M%S")
+
+    # Mock the cycle_count attribute of the Agent instance
+    agent_mock.cycle_count = 0
+
     # Call the get_self_feedback method
     feedback = Agent.get_self_feedback(
         agent_mock,