Agent loop v2: Planning & Task Management (part 1: refactoring) (#4799)

* Move rename module `agent` -> `agents`

* WIP: abstract agent structure into base class and port Agent

* Move command arg path sanitization to decorator

* Add fallback token limit in llm.utils.create_chat_completion

* Rebase `MessageHistory` class on `ChatSequence` class

* Fix linting

* Consolidate logging modules

* Wham Bam Boom

* Fix tests & linting complaints

* Update Agent class docstring

* Fix Agent import in autogpt.llm.providers.openai

* Fix agent kwarg in test_execute_code.py

* Fix benchmarks.py

* Clean up lingering Agent(ai_name=...) initializations

* Fix agent kwarg

* Make sanitize_path_arg decorator more robust

* Fix linting

* Fix command enabling lambda's

* Use relative paths in file ops logger

* Fix test_execute_python_file_not_found

* Fix Config model validation breaking on .plugins

* Define validator for Config.plugins

* Fix Config model issues

* Fix agent iteration budget in testing

* Fix declaration of context_while_think

* Fix Agent.parse_and_process_response signature

* Fix Agent cycle_budget usages

* Fix budget checking in BaseAgent.__next__

* Fix cycle budget initialization

* Fix function calling in BaseAgent.think()

* Include functions in token length calculation

* Fix Config errors

* Add debug thing to patched_api_requestor to investigate HTTP 400 errors

* If this works I'm gonna be sad

* Fix BaseAgent cycle budget logic and document attributes

* Document attributes on `Agent`

* Fix import issues between Agent and MessageHistory

* Improve typing

* Extract application code from the agent (#4982)

* Extract application code from the agent

* Wrap interaction loop in a function and call in benchmarks

* Forgot the important function call

* Add docstrings and inline comments to run loop

* Update typing and docstrings in agent

* Docstring formatting

* Separate prompt construction from on_before_think

* Use `self.default_cycle_instruction` in `Agent.think()`

* Fix formatting

* hot fix the SIGINT handler (#4997)

The signal handler in the autogpt/main.py doesn't work properly because
of the clean_input(...) func. This commit remedies this issue. The issue
is mentioned in
3966cdfd69 (r1264278776)

* Update the sigint handler to be smart enough to actually work (#4999)

* Update the sigint handler to be smart enough to actually work

* Update autogpt/main.py

Co-authored-by: Reinier van der Leer <github@pwuts.nl>

* Can still use context manager

* Merge in upstream

---------

Co-authored-by: Reinier van der Leer <github@pwuts.nl>

* Fix CI

* Fix initial prompt construction

* off by one error

* allow exit/EXIT to shut down app

* Remove dead code

---------

Co-authored-by: collijk <collijk@uw.edu>
Co-authored-by: Cyrus <39694513+cyrus-hawk@users.noreply.github.com>

benchmarks.py

@@ -1,6 +1,6 @@
 from autogpt.agents import Agent
 from autogpt.config import AIConfig, Config, ConfigBuilder
-from autogpt.main import COMMAND_CATEGORIES
+from autogpt.main import COMMAND_CATEGORIES, run_interaction_loop
 from autogpt.memory.vector import get_memory
 from autogpt.models.command_registry import CommandRegistry
 from autogpt.prompts.prompt import DEFAULT_TRIGGERING_PROMPT
@@ -9,7 +9,7 @@ from autogpt.workspace import Workspace
 
 def run_task(task) -> None:
     agent = bootstrap_agent(task)
-    agent.start_interaction_loop()
+    run_interaction_loop(agent)
 
 
 def bootstrap_agent(task):
@@ -28,15 +28,11 @@ def bootstrap_agent(task):
         ai_goals=[task.user_input],
     )
     ai_config.command_registry = command_registry
-    system_prompt = ai_config.construct_full_prompt(config)
     return Agent(
-        ai_name="Auto-GPT",
         memory=get_memory(config),
         command_registry=command_registry,
         ai_config=ai_config,
         config=config,
-        next_action_count=0,
-        system_prompt=system_prompt,
         triggering_prompt=DEFAULT_TRIGGERING_PROMPT,
         workspace_directory=str(workspace_directory_path),
     )