feat: one time pass of autoflake + add autoflake to dev extras (#1097)

Co-authored-by: tombedor <tombedor@gmail.com>

examples/openai_client_assistants.py

@@ -1,5 +1,4 @@
 from openai import OpenAI
-import time
 
 """
 This script provides an example of how you can use OpenAI's python client with a MemGPT server.
@@ -33,7 +32,7 @@ def main():
     )
 
     # Store the run ID
-    run_id = run.id
+    run.id
 
     # Retrieve all messages from the thread
     messages = client.beta.threads.messages.list(thread_id=thread.id)

memgpt/agent.py

@@ -674,7 +674,7 @@ class Agent(object):
             # (if yes) Step 3: call the function
             # (if yes) Step 4: send the info on the function call and function response to LLM
             response_message = response.choices[0].message
-            response_message_copy = response_message.copy()
+            response_message.copy()
             all_response_messages, heartbeat_request, function_failed = self._handle_ai_response(response_message)
 
             # Add the extra metadata to the assistant response

memgpt/agent_store/chroma.py

@@ -1,7 +1,5 @@
 import uuid
-import json
-import re
-from typing import Optional, List, Iterator, Dict, Tuple, cast, Type
+from typing import Optional, List, Iterator, Dict, Tuple, cast
 
 import chromadb
 from chromadb.api.types import Include, GetResult

memgpt/agent_store/db.py

@@ -11,9 +11,8 @@ from sqlalchemy_json import mutable_json_type, MutableJson
 from sqlalchemy import TypeDecorator, CHAR
 import uuid
 
-import re
 from tqdm import tqdm
-from typing import Optional, List, Iterator, Dict, Tuple
+from typing import Optional, List, Iterator, Dict
 import numpy as np
 from tqdm import tqdm
 import pandas as pd
@@ -26,8 +25,6 @@ from memgpt.data_types import Record, Message, Passage, ToolCall, RecordType
 from memgpt.constants import MAX_EMBEDDING_DIM
 from memgpt.metadata import MetadataStore
 
-from datetime import datetime
-
 
 # Custom UUID type
 class CommonUUID(TypeDecorator):

memgpt/agent_store/storage.py

@@ -3,10 +3,7 @@
 We originally tried to use Llama Index VectorIndex, but their limited API was extremely problematic.
 """
 
-from typing import Any, Optional, List, Iterator, Union, Tuple, Type
-import re
-import pickle
-import os
+from typing import Optional, List, Iterator, Union, Tuple, Type
 import uuid
 from abc import abstractmethod
 

memgpt/autogen/memgpt_agent.py

@@ -265,7 +265,7 @@ def load_autogen_memgpt_agent(
     # Create the agent object directly from the loaded state (not via preset creation)
     try:
         memgpt_agent = MemGPTAgent(agent_state=agent_state, interface=interface)
-    except Exception as e:
+    except Exception:
         print(f"Failed to create an agent object from agent state =\n{agent_state}")
         raise
 
@@ -317,8 +317,8 @@ def create_autogen_memgpt_agent(
     embedding_config = config.default_embedding_config
 
     # Overwrite parts of the LLM and embedding configs that were passed into the config dicts
-    llm_config_was_modified = update_config_from_dict(llm_config, agent_config)
-    embedding_config_was_modified = update_config_from_dict(embedding_config, agent_config)
+    update_config_from_dict(llm_config, agent_config)
+    update_config_from_dict(embedding_config, agent_config)
 
     # Create the default user, or load the specified user
     ms = MetadataStore(config)

memgpt/benchmark/benchmark.py

@@ -3,7 +3,7 @@
 import uuid
 import typer
 import time
-from typing import Annotated, Optional
+from typing import Annotated
 
 from memgpt import create_client
 from memgpt.config import MemGPTConfig

memgpt/cli/cli.py

@@ -2,8 +2,6 @@ import uuid
 import json
 import requests
 import sys
-import shutil
-import io
 import logging
 from pathlib import Path
 import os
@@ -722,7 +720,7 @@ def delete_agent(
     try:
         ms.delete_agent(agent_id=agent.id)
         typer.secho(f"🕊️ Successfully deleted agent '{agent_name}' (id={agent.id})", fg=typer.colors.GREEN)
-    except Exception as e:
+    except Exception:
         typer.secho(f"Failed to delete agent '{agent_name}' (id={agent.id})", fg=typer.colors.RED)
         sys.exit(1)
 

memgpt/cli/cli_config.py

@@ -1,9 +1,7 @@
 import builtins
-import json
 import os
-import shutil
 import uuid
-from typing import Annotated, Tuple, Optional
+from typing import Annotated, Optional
 from enum import Enum
 from typing import Annotated
 
@@ -512,7 +510,7 @@ def configure_embedding_endpoint(config: MemGPTConfig, credentials: MemGPTCreden
             raise KeyboardInterrupt
         try:
             embedding_dim = int(embedding_dim)
-        except Exception as e:
+        except Exception:
             raise ValueError(f"Failed to cast {embedding_dim} to integer.")
     else:  # local models
         embedding_endpoint_type = "local"
@@ -627,7 +625,7 @@ def configure():
     # check credentials
     credentials = MemGPTCredentials.load()
     openai_key = get_openai_credentials()
-    azure_creds = get_azure_credentials()
+    get_azure_credentials()
 
     MemGPTConfig.create_config_dir()
 

memgpt/cli/cli_load.py

@@ -23,7 +23,6 @@ from memgpt.data_types import Source, Passage, Document, User
 from memgpt.utils import get_utc_time, suppress_stdout
 from memgpt.agent_store.storage import StorageConnector, TableType
 
-from datetime import datetime
 
 app = typer.Typer()
 

memgpt/client/client.py

@@ -1,4 +1,3 @@
-import os
 import datetime
 import requests
 import uuid

memgpt/credentials.py

@@ -1,8 +1,5 @@
 from memgpt.log import logger
-import inspect
-import json
 import os
-import uuid
 from dataclasses import dataclass
 import configparser
 import typer

memgpt/data_sources/connectors.py

@@ -4,7 +4,6 @@ from memgpt.agent_store.storage import StorageConnector, TableType
 from memgpt.embeddings import embedding_model
 from memgpt.data_types import Document, Passage
 
-import uuid
 from typing import List, Iterator, Dict, Tuple, Optional
 from llama_index.core import Document as LlamaIndexDocument
 
@@ -102,7 +101,6 @@ class DirectoryConnector(DataConnector):
             reader = SimpleDirectoryReader(input_files=[str(f) for f in self.input_files])
 
         llama_index_docs = reader.load_data(show_progress=True)
-        docs = []
         for llama_index_doc in llama_index_docs:
             # TODO: add additional metadata?
             # doc = Document(text=llama_index_doc.text, metadata=llama_index_doc.metadata)

memgpt/data_types.py

@@ -2,7 +2,6 @@
 
 import uuid
 from datetime import datetime
-from abc import abstractmethod
 from typing import Optional, List, Dict, TypeVar
 import numpy as np
 

memgpt/errors.py

@@ -1,8 +1,6 @@
 class LLMError(Exception):
     """Base class for all LLM-related errors."""
 
-    pass
-
 
 class LLMJSONParsingError(LLMError):
     """Exception raised for errors in the JSON parsing process."""

memgpt/functions/function_sets/base.py

@@ -1,6 +1,5 @@
 from typing import Optional
 import datetime
-import os
 import json
 import math
 
@@ -62,7 +61,7 @@ def core_memory_append(self, name: str, content: str) -> Optional[str]:
     Returns:
         Optional[str]: None is always returned as this function does not produce a response.
     """
-    new_len = self.memory.edit_append(name, content)
+    self.memory.edit_append(name, content)
     self.rebuild_memory()
     return None
 
@@ -79,7 +78,7 @@ def core_memory_replace(self, name: str, old_content: str, new_content: str) ->
     Returns:
         Optional[str]: None is always returned as this function does not produce a response.
     """
-    new_len = self.memory.edit_replace(name, old_content, new_content)
+    self.memory.edit_replace(name, old_content, new_content)
     self.rebuild_memory()
     return None
 

memgpt/interface.py

@@ -203,7 +203,6 @@ class CLIInterface(AgentInterface):
                         except Exception as e:
                             printd(str(e))
                             printd(msg_dict)
-                            pass
                     elif function_name in ["conversation_search", "conversation_search_date"]:
                         print_function_message("🧠", f"searching memory with {function_name}")
                         try:
@@ -216,7 +215,6 @@ class CLIInterface(AgentInterface):
                         except Exception as e:
                             printd(str(e))
                             printd(msg_dict)
-                            pass
                 else:
                     printd(f"{CLI_WARNING_PREFIX}did not recognize function message")
                     printd_function_message("", msg)

memgpt/llm_api_tools.py

@@ -2,7 +2,7 @@ import random
 import time
 import requests
 import time
-from typing import Callable, TypeVar, Union
+from typing import Union
 import urllib
 
 from memgpt.credentials import MemGPTCredentials

memgpt/local_llm/grammars/gbnf_grammar_generator.py

@@ -8,7 +8,7 @@ from docstring_parser import parse
 from pydantic import BaseModel, create_model, Field
 from typing import Any, Type, List, get_args, get_origin, Tuple, Union, Optional, _GenericAlias
 from enum import Enum
-from typing import get_type_hints, Callable
+from typing import Callable
 import re
 
 

memgpt/local_llm/koboldcpp/api.py

@@ -1,4 +1,3 @@
-import os
 from urllib.parse import urljoin
 import requests
 

memgpt/local_llm/llamacpp/api.py

@@ -1,4 +1,3 @@
-import os
 from urllib.parse import urljoin
 import requests
 

memgpt/local_llm/llm_chat_completion_wrappers/configurable_wrapper.py

@@ -1,5 +1,4 @@
 import json
-from typing import List
 
 import yaml
 

memgpt/local_llm/llm_chat_completion_wrappers/wrapper_base.py

@@ -5,9 +5,7 @@ class LLMChatCompletionWrapper(ABC):
     @abstractmethod
     def chat_completion_to_prompt(self, messages, functions, function_documentation=None):
         """Go from ChatCompletion to a single prompt string"""
-        pass
 
     @abstractmethod
     def output_to_chat_completion_response(self, raw_llm_output):
         """Turn the LLM output string into a ChatCompletion response"""
-        pass

memgpt/local_llm/llm_chat_completion_wrappers/zephyr.py

@@ -41,7 +41,6 @@ class ZephyrMistralWrapper(LLMChatCompletionWrapper):
 
         prompt = ""
 
-        IM_START_TOKEN = "<s>"
         IM_END_TOKEN = "</s>"
 
         # System instructions go first
@@ -205,7 +204,6 @@ class ZephyrMistralInnerMonologueWrapper(ZephyrMistralWrapper):
     def chat_completion_to_prompt(self, messages, functions, function_documentation=None):
         prompt = ""
 
-        IM_START_TOKEN = "<s>"
         IM_END_TOKEN = "</s>"
 
         # System insturctions go first

memgpt/local_llm/lmstudio/api.py

@@ -1,4 +1,3 @@
-import os
 from urllib.parse import urljoin
 import requests
 

memgpt/local_llm/ollama/api.py

@@ -1,4 +1,3 @@
-import os
 from urllib.parse import urljoin
 import requests
 

memgpt/local_llm/vllm/api.py

@@ -1,4 +1,3 @@
-import os
 from urllib.parse import urljoin
 import requests
 

memgpt/local_llm/webui/api.py

@@ -1,4 +1,3 @@
-import os
 from urllib.parse import urljoin
 import requests
 

memgpt/local_llm/webui/legacy_api.py

@@ -1,4 +1,3 @@
-import os
 from urllib.parse import urljoin
 import requests
 

memgpt/memory.py

@@ -142,7 +142,6 @@ class ArchivalMemory(ABC):
         :param memory_string: Memory string to insert
         :type memory_string: str
         """
-        pass
 
     @abstractmethod
     def search(self, query_string, count=None, start=None) -> Tuple[List[str], int]:
@@ -157,7 +156,6 @@ class ArchivalMemory(ABC):
 
         :return: Tuple of (list of results, total number of results)
         """
-        pass
 
     @abstractmethod
     def __repr__(self) -> str:
@@ -168,12 +166,10 @@ class RecallMemory(ABC):
     @abstractmethod
     def text_search(self, query_string, count=None, start=None):
         """Search messages that match query_string in recall memory"""
-        pass
 
     @abstractmethod
     def date_search(self, start_date, end_date, count=None, start=None):
         """Search messages between start_date and end_date in recall memory"""
-        pass
 
     @abstractmethod
     def __repr__(self) -> str:
@@ -182,7 +178,6 @@ class RecallMemory(ABC):
     @abstractmethod
     def insert(self, message: Message):
         """Insert message into recall memory"""
-        pass
 
 
 class DummyRecallMemory(RecallMemory):

memgpt/metadata.py

@@ -3,8 +3,7 @@
 import os
 import uuid
 import secrets
-from typing import Optional, List, Dict
-from datetime import datetime
+from typing import Optional, List
 
 from memgpt.constants import DEFAULT_HUMAN, DEFAULT_MEMGPT_MODEL, DEFAULT_PERSONA, DEFAULT_PRESET, LLM_MAX_TOKENS
 from memgpt.utils import get_local_time, enforce_types

memgpt/migrate.py

@@ -248,7 +248,7 @@ def migrate_agent(agent_name: str, data_dir: str = MEMGPT_DIR, ms: Optional[Meta
     try:
         with open(persistence_filename, "rb") as f:
             data = pickle.load(f)
-    except ModuleNotFoundError as e:
+    except ModuleNotFoundError:
         # Patch for stripped openai package
         # ModuleNotFoundError: No module named 'openai.openai_object'
         with open(persistence_filename, "rb") as f:
@@ -474,7 +474,7 @@ def migrate_agent(agent_name: str, data_dir: str = MEMGPT_DIR, ms: Optional[Meta
             interface=None,
         )
         save_agent(agent, ms=ms)
-    except Exception as e:
+    except Exception:
         # if "Agent with name" in str(e):
         #     print(e)
         #     return
@@ -540,7 +540,7 @@ def migrate_agent(agent_name: str, data_dir: str = MEMGPT_DIR, ms: Optional[Meta
     try:
         new_agent_folder = os.path.join(data_dir, MIGRATION_BACKUP_FOLDER, "agents", agent_name)
         shutil.move(agent_folder, new_agent_folder)
-    except Exception as e:
+    except Exception:
         print(f"Failed to move agent folder from {agent_folder} to {new_agent_folder}")
         raise
 

memgpt/models/openai.py

@@ -1,7 +1,6 @@
-from typing import List, Union, Optional, Dict, Literal
+from typing import List, Union, Optional, Dict
 from enum import Enum
 from pydantic import BaseModel, Field, Json
-import uuid
 
 
 class ImageFile(BaseModel):

memgpt/models/pydantic_models.py

@@ -1,5 +1,4 @@
-from typing import List, Union, Optional, Dict, Literal
-from enum import Enum
+from typing import List, Optional, Dict
 from pydantic import BaseModel, Field, Json
 import uuid
 from datetime import datetime

memgpt/persistence_manager.py

@@ -1,5 +1,4 @@
 from abc import ABC, abstractmethod
-import pickle
 from typing import List
 
 from memgpt.memory import (

memgpt/server/rest_api/agents/config.py

@@ -68,8 +68,8 @@ def setup_agents_config_router(server: SyncServer, interface: QueuingInterface,
         interface.clear()
         agent_state = server.get_agent_config(user_id=user_id, agent_id=agent_id)
         # return GetAgentResponse(agent_state=agent_state)
-        llm_config = LLMConfigModel(**vars(agent_state.llm_config))
-        embedding_config = EmbeddingConfigModel(**vars(agent_state.embedding_config))
+        LLMConfigModel(**vars(agent_state.llm_config))
+        EmbeddingConfigModel(**vars(agent_state.embedding_config))
 
         return GetAgentResponse(
             agent_state=AgentStateModel(

memgpt/server/rest_api/interface.py

@@ -53,7 +53,6 @@ class QueuingInterface(AgentInterface):
 
     def user_message(self, msg: str):
         """Handle reception of a user message"""
-        pass
 
     def internal_monologue(self, msg: str) -> None:
         """Handle the agent's internal monologue"""

memgpt/server/rest_api/models/index.py

@@ -1,4 +1,3 @@
-import uuid
 from functools import partial
 from typing import List
 
@@ -19,7 +18,7 @@ class ListModelsResponse(BaseModel):
 
 
 def setup_models_index_router(server: SyncServer, interface: QueuingInterface, password: str):
-    get_current_user_with_server = partial(partial(get_current_user, server), password)
+    partial(partial(get_current_user, server), password)
 
     @router.get("/models", tags=["models"], response_model=ListModelsResponse)
     async def list_models():

memgpt/server/rest_api/openai_assistants/assistants.py

@@ -1,10 +1,6 @@
-import asyncio
 from fastapi import FastAPI
-from asyncio import AbstractEventLoop
-from enum import Enum
-import json
 import uuid
-from typing import List, Optional, Union
+from typing import List, Optional
 from datetime import datetime
 
 from fastapi import APIRouter, Depends, Body, HTTPException, Query, Path

memgpt/server/server.py

@@ -435,7 +435,7 @@ class SyncServer(LockingServer):
             while len(memgpt_agent.messages) > 0:
                 if memgpt_agent.messages[-1].get("role") == "user":
                     # we want to pop up to the last user message and send it again
-                    user_message = memgpt_agent.messages[-1].get("content")
+                    memgpt_agent.messages[-1].get("content")
                     memgpt_agent.messages.pop()
                     break
                 memgpt_agent.messages.pop()

memgpt/server/ws_api/interface.py

@@ -30,7 +30,6 @@ class AsyncWebSocketInterface(BaseWebSocketInterface):
     async def user_message(self, msg):
         """Handle reception of a user message"""
         # Logic to process the user message and possibly trigger agent's response
-        pass
 
     async def internal_monologue(self, msg):
         """Handle the agent's internal monologue"""
@@ -85,7 +84,6 @@ class SyncWebSocketInterface(BaseWebSocketInterface):
     def user_message(self, msg):
         """Handle reception of a user message"""
         # Logic to process the user message and possibly trigger agent's response
-        pass
 
     def internal_monologue(self, msg):
         """Handle the agent's internal monologue"""

poetry.lock

@@ -218,6 +218,21 @@ tests = ["attrs[tests-no-zope]", "zope-interface"]
 tests-mypy = ["mypy (>=1.6)", "pytest-mypy-plugins"]
 tests-no-zope = ["attrs[tests-mypy]", "cloudpickle", "hypothesis", "pympler", "pytest (>=4.3.0)", "pytest-xdist[psutil]"]
 
+[[package]]
+name = "autoflake"
+version = "2.3.0"
+description = "Removes unused imports and unused variables"
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "autoflake-2.3.0-py3-none-any.whl", hash = "sha256:79a51eb8c0744759d2efe052455ab20aa6a314763510c3fd897499a402126327"},
+    {file = "autoflake-2.3.0.tar.gz", hash = "sha256:8c2011fa34701b9d7dcf05b9873bc4859d4fce4e62dfea90dffefd1576f5f01d"},
+]
+
+[package.dependencies]
+pyflakes = ">=3.0.0"
+tomli = {version = ">=2.0.1", markers = "python_version < \"3.11\""}
+
 [[package]]
 name = "azure-core"
 version = "1.30.1"
@@ -3779,6 +3794,17 @@ files = [
 [package.dependencies]
 typing-extensions = ">=4.6.0,<4.7.0 || >4.7.0"
 
+[[package]]
+name = "pyflakes"
+version = "3.2.0"
+description = "passive checker of Python programs"
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "pyflakes-3.2.0-py2.py3-none-any.whl", hash = "sha256:84b5be138a2dfbb40689ca07e2152deb896a65c3a3e24c251c5c62489568074a"},
+    {file = "pyflakes-3.2.0.tar.gz", hash = "sha256:1c61603ff154621fb2a9172037d84dca3500def8c8b630657d1701f026f8af3f"},
+]
+
 [[package]]
 name = "pygments"
 version = "2.17.2"
@@ -5874,4 +5900,4 @@ server = ["fastapi", "uvicorn", "websockets"]
 [metadata]
 lock-version = "2.0"
 python-versions = "<3.12,>=3.10"
-content-hash = "44a3dd2672236f037f34c7859a943d86a8a02297190ac4f826fe41d21955c4ca"
+content-hash = "4fe62729e4de4bdacedc6e969aafdecf5897f34762d2c7cdad61bc813de93651"

pyproject.toml

@@ -56,10 +56,11 @@ python-box = "^7.1.1"
 pytest-order = {version = "^1.2.0", optional = true}
 sqlmodel = "^0.0.16"
 llama-index-embeddings-azure-openai = "^0.1.6"
+autoflake = {version = "^2.3.0", optional = true}
 
 [tool.poetry.extras]
 postgres = ["pgvector", "pg8000"]
-dev = ["pytest", "pytest-asyncio", "pexpect", "black", "pre-commit", "datasets", "pyright", "pytest-order"]
+dev = ["pytest", "pytest-asyncio", "pexpect", "black", "pre-commit", "datasets", "pyright", "pytest-order", "autoflake"]
 server = ["websockets", "fastapi", "uvicorn"]
 autogen = ["pyautogen"]
 

tests/test_autogen_integration.py

@@ -1,5 +1,4 @@
 import os
-import sys
 import subprocess
 import pytest
 

tests/test_openai_assistant_api.py

@@ -1,6 +1,5 @@
 from fastapi import FastAPI
 from fastapi.testclient import TestClient
-import uuid
 
 from memgpt.server.server import SyncServer
 from memgpt.server.rest_api.server import app

tests/test_openai_client.py

@@ -1,5 +1,4 @@
 from openai import OpenAI
-import time
 import uvicorn
 
 

tests/test_server.py

@@ -187,8 +187,8 @@ def test_get_recall_memory(server, user_id, agent_id):
     cursor1, messages_1 = server.get_agent_recall_cursor(user_id=user_id, agent_id=agent_id, reverse=True, limit=2)
     cursor2, messages_2 = server.get_agent_recall_cursor(user_id=user_id, agent_id=agent_id, reverse=True, after=cursor1, limit=1000)
     cursor3, messages_3 = server.get_agent_recall_cursor(user_id=user_id, agent_id=agent_id, reverse=True, limit=1000)
-    ids3 = [m["id"] for m in messages_3]
-    ids2 = [m["id"] for m in messages_2]
+    [m["id"] for m in messages_3]
+    [m["id"] for m in messages_2]
     timestamps = [m["created_at"] for m in messages_3]
     print("timestamps", timestamps)
     assert messages_3[-1]["created_at"] < messages_3[0]["created_at"]