Remove self feedback

Signed-off-by: Merwane Hamadi <[email protected]>

autogpt/agent/agent.py

@@ -8,15 +8,12 @@
 from autogpt.config import Config
 from autogpt.config.ai_config import AIConfig
 from autogpt.json_utils.utilities import extract_json_from_response, validate_json
-from autogpt.llm.base import ChatSequence
-from autogpt.llm.chat import chat_with_ai, create_chat_completion
+from autogpt.llm.chat import chat_with_ai
 from autogpt.llm.providers.openai import OPEN_AI_CHAT_MODELS
 from autogpt.llm.utils import count_string_tokens
 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,
 )
@@ -208,24 +205,6 @@ def signal_handler(signum, frame):
                     if console_input.lower().strip() == self.config.authorise_key:
                         user_input = "GENERATE NEXT COMMAND JSON"
                         break
-                    elif console_input.lower().strip() == "s":
-                        logger.typewriter_log(
-                            "-=-=-=-=-=-=-= THOUGHTS, REASONING, PLAN AND CRITICISM WILL NOW BE VERIFIED BY AGENT -=-=-=-=-=-=-=",
-                            Fore.GREEN,
-                            "",
-                        )
-                        thoughts = assistant_reply_json.get("thoughts", {})
-                        self_feedback_resp = self.get_self_feedback(
-                            thoughts, self.config.fast_llm_model
-                        )
-                        logger.typewriter_log(
-                            f"SELF FEEDBACK: {self_feedback_resp}",
-                            Fore.YELLOW,
-                            "",
-                        )
-                        user_input = self_feedback_resp
-                        command_name = "self_feedback"
-                        break
                     elif console_input.lower().strip() == "":
                         logger.warn("Invalid input format.")
                         continue
@@ -281,8 +260,6 @@ def signal_handler(signum, frame):
                 result = f"Could not execute command: {arguments}"
             elif command_name == "human_feedback":
                 result = f"Human feedback: {user_input}"
-            elif command_name == "self_feedback":
-                result = f"Self feedback: {user_input}"
             else:
                 for plugin in self.config.plugins:
                     if not plugin.can_handle_pre_command():
@@ -336,45 +313,3 @@ def _resolve_pathlike_command_args(self, command_args):
                         self.workspace.get_path(command_args[pathlike])
                     )
         return command_args
-
-    def get_self_feedback(self, thoughts: dict, llm_model: str) -> str:
-        """Generates a feedback response based on the provided thoughts dictionary.
-        This method takes in a dictionary of thoughts containing keys such as 'reasoning',
-        'plan', 'thoughts', and 'criticism'. It combines these elements into a single
-        feedback message and uses the create_chat_completion() function to generate a
-        response based on the input message.
-        Args:
-            thoughts (dict): A dictionary containing thought elements like reasoning,
-            plan, thoughts, and criticism.
-        Returns:
-            str: A feedback response generated using the provided thoughts dictionary.
-        """
-        ai_role = self.ai_config.ai_role
-
-        feedback_prompt = f"Below is a message from me, an AI Agent, assuming the role of {ai_role}. whilst keeping knowledge of my slight limitations as an AI Agent Please evaluate my thought process, reasoning, and plan, and provide a concise paragraph outlining potential improvements. Consider adding or removing ideas that do not align with my role and explaining why, prioritizing thoughts based on their significance, or simply refining my overall thought process."
-        reasoning = thoughts.get("reasoning", "")
-        plan = thoughts.get("plan", "")
-        thought = thoughts.get("thoughts", "")
-        feedback_thoughts = thought + reasoning + plan
-
-        prompt = ChatSequence.for_model(llm_model)
-        prompt.add("user", feedback_prompt + feedback_thoughts)
-
-        self.log_cycle_handler.log_cycle(
-            self.ai_config.ai_name,
-            self.created_at,
-            self.cycle_count,
-            prompt.raw(),
-            PROMPT_SUPERVISOR_FEEDBACK_FILE_NAME,
-        )
-
-        feedback = create_chat_completion(prompt)
-
-        self.log_cycle_handler.log_cycle(
-            self.ai_config.ai_name,
-            self.created_at,
-            self.cycle_count,
-            feedback,
-            SUPERVISOR_FEEDBACK_FILE_NAME,
-        )
-        return feedback

autogpt/app.py

@@ -1,15 +1,9 @@
 """ Command and Control """
 import json
-from typing import Dict, List, Union
+from typing import Dict
 
 from autogpt.agent.agent import Agent
-from autogpt.agent.agent_manager import AgentManager
-from autogpt.command_decorator import command
-from autogpt.commands.web_requests import scrape_links, scrape_text
 from autogpt.models.command_registry import CommandRegistry
-from autogpt.processing.text import summarize_text
-from autogpt.speech import say_text
-from autogpt.url_utils.validators import validate_url
 
 
 def is_valid_int(value: str) -> bool:

autogpt/log_cycle/log_cycle.py

@@ -12,7 +12,7 @@
 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 = "triggering_prompt.txt"
+USER_INPUT_FILE_NAME = "user_input.txt"
 
 
 class LogCycleHandler:

autogpt/models/base_open_ai_plugin.py

@@ -214,13 +214,13 @@ def handle_text_embedding(self, text: str) -> list:
 
     def can_handle_user_input(self, user_input: str) -> bool:
         """This method is called to check that the plugin can
-        handle the triggering_prompt method.
+        handle the user_input method.
 
         Args:
             user_input (str): The user input.
 
         Returns:
-            bool: True if the plugin can handle the triggering_prompt method."""
+            bool: True if the plugin can handle the user_input method."""
         return False
 
     def user_input(self, user_input: str) -> str:

tests/unit/data/test_plugins/auto_gpt_guanaco/__init__.py

@@ -239,13 +239,13 @@ def handle_text_embedding(self, text: str) -> list:
 
     def can_handle_user_input(self, user_input: str) -> bool:
         """This method is called to check that the plugin can
-        handle the triggering_prompt method.
+        handle the user_input method.
 
         Args:
             user_input (str): The user input.
 
         Returns:
-            bool: True if the plugin can handle the triggering_prompt method."""
+            bool: True if the plugin can handle the user_input method."""
         return False
 
     def user_input(self, user_input: str) -> str: