More linting

.github/workflows/lint.yml

@@ -30,4 +30,4 @@ jobs:
       - uses: actions/checkout@v4
       - uses: actions/setup-python@v5
       - run: pip install pylint
-      - run: pylint .
+      - run: pylint swarms --recursive=y

devin.py

@@ -1,6 +1,7 @@
-from swarms import Agent, Anthropic, tool
 import subprocess
 
+from swarms import Agent, Anthropic, tool
+
 # Model
 llm = Anthropic(
     temperature=0.1,

example.py

@@ -1,6 +1,5 @@
 from swarms import Agent, Anthropic
 
-
 ## Initialize the workflow
 agent = Agent(
     agent_name="Transcript Generator",

playground/demos/agent_in_5/youtube_demo_agent.py

@@ -4,8 +4,8 @@ Building an Autonomous Agent in 5 minutes with:
 - Tools: Search, Browser, ETC
 - Long Term Mmeory: ChromaDB, Weaviate, Pinecone, ETC
 """
-from swarms import Agent, OpenAIChat, tool
 from playground.demos.agent_in_5.chroma_db import ChromaDB
+from swarms import Agent, OpenAIChat, tool
 
 # Initialize the memory
 chroma = ChromaDB(

playground/demos/ai_acceleerated_learning/main.py

@@ -1,12 +1,13 @@
 import concurrent
 import csv
+
+from dotenv import load_dotenv
+
 from swarms import Agent, OpenAIChat
 from swarms.memory import ChromaDB
-from dotenv import load_dotenv
-from swarms.utils.parse_code import extract_code_from_markdown
 from swarms.utils.file_processing import create_file
 from swarms.utils.loguru_logger import logger
-
+from swarms.utils.parse_code import extract_code_from_markdown
 
 # Load ENV
 load_dotenv()
@@ -69,7 +70,7 @@ def extract_and_create_agents(
     """
     try:
         agents = []
-        with open(csv_file_path, mode="r", encoding="utf-8") as file:
+        with open(csv_file_path, encoding="utf-8") as file:
             reader = csv.DictReader(file)
             for row in reader:
                 project_name = row[target_columns[0]]

playground/demos/autoswarm/autoswarm.py

@@ -1,8 +1,10 @@
 import os
+
 from dotenv import load_dotenv
+
+import swarms.prompts.autoswarm as sdsp
 from swarms.models import OpenAIChat
 from swarms.structs import Agent
-import swarms.prompts.autoswarm as sdsp
 
 # Load environment variables and initialize the OpenAI Chat model
 load_dotenv()

playground/demos/swarm_hackathon/Bants.py

@@ -1,5 +1,6 @@
 # Import the necessary libraries.
 import asyncio
+
 import websockets
 
 # Create a list of public group chats.

playground/demos/swarm_hackathon/Human voice.py

@@ -1,5 +1,5 @@
 import discord
-from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
+from transformers import AutoModelForSeq2SeqLM, AutoTokenizer
 
 # Discord Bot Setup
 client = discord.Client()

playground/demos/swarm_hackathon/OpenMind.bot.py

@@ -1,10 +1,10 @@
 # OpenMind.bot streamlines social interactions between personalized bots, representing users, media, and influencers, ensuring meaningful exchanges. It eliminates misunderstandings by using context-aware conversations, followed by summaries or audio recaps of these interactions for efficient communication.
 
-import json
 import datetime
-import pytz
+import json
 
-from flask import Flask, request, jsonify
+import pytz
+from flask import Flask, jsonify, request
 
 app = Flask(__name__)
 
@@ -28,7 +28,7 @@ def create_conversation():
 @app.route("/api/v1/conversations/<conversation_id>", methods=["GET"])
 def get_conversation(conversation_id):
     # Get the conversation from the database
-    with open("conversations.json", "r") as f:
+    with open("conversations.json") as f:
         conversation = json.load(f)
 
     # Return the conversation
@@ -49,7 +49,7 @@ def create_message(conversation_id):
     }
 
     # Get the conversation from the database
-    with open("conversations.json", "r") as f:
+    with open("conversations.json") as f:
         conversation = json.load(f)
 
     # Add the message to the conversation
@@ -68,7 +68,7 @@ def create_message(conversation_id):
 )
 def get_messages(conversation_id):
     # Get the conversation from the database
-    with open("conversations.json", "r") as f:
+    with open("conversations.json") as f:
         conversation = json.load(f)
 
     # Return the messages
@@ -80,7 +80,7 @@ def get_messages(conversation_id):
 )
 def get_summary(conversation_id):
     # Get the conversation from the database
-    with open("conversations.json", "r") as f:
+    with open("conversations.json") as f:
         conversation = json.load(f)
 
     # Create a summary of the conversation
@@ -98,7 +98,7 @@ def get_summary(conversation_id):
 )
 def get_audio_recap(conversation_id):
     # Get the conversation from the database
-    with open("conversations.json", "r") as f:
+    with open("conversations.json") as f:
         conversation = json.load(f)
 
     # Create an audio recap of the conversation

playground/demos/swarm_hackathon/main.py

@@ -1,12 +1,14 @@
 import concurrent
 import csv
 import os
-from swarms import Gemini, Agent
-from swarms.memory import ChromaDB
+
 from dotenv import load_dotenv
-from swarms.utils.parse_code import extract_code_from_markdown
+
+from swarms import Agent, Gemini
+from swarms.memory import ChromaDB
 from swarms.utils.file_processing import create_file
 from swarms.utils.loguru_logger import logger
+from swarms.utils.parse_code import extract_code_from_markdown
 
 # Load ENV
 load_dotenv()
@@ -71,7 +73,7 @@ def extract_and_create_agents(
     - target_columns: A list of column names to extract values from.
     """
     agents = []
-    with open(csv_file_path, mode="r", encoding="utf-8") as file:
+    with open(csv_file_path, encoding="utf-8") as file:
         reader = csv.DictReader(file)
         for row in reader:
             project_name = row[target_columns[0]]

playground/examples/example_agent.py

@@ -4,7 +4,7 @@ import sys
 from dotenv import load_dotenv
 
 # Import the OpenAIChat model and the Agent struct
-from swarms import OpenAIChat, Agent
+from swarms import Agent, OpenAIChat
 
 # Load the environment variables
 load_dotenv()

playground/examples/example_concurrentworkflow.py

@@ -1,6 +1,8 @@
 import os
+
 from dotenv import load_dotenv
-from swarms import OpenAIChat, Task, ConcurrentWorkflow, Agent
+
+from swarms import Agent, ConcurrentWorkflow, OpenAIChat, Task
 
 # Load environment variables from .env file
 load_dotenv()

playground/examples/example_huggingfacellm.py

@@ -1,6 +1,7 @@
-from swarms.models import HuggingfaceLLM
 import torch
 
+from swarms.models import HuggingfaceLLM
+
 try:
     inference = HuggingfaceLLM(
         model_id="gpt2",

playground/examples/example_logistics.py

@@ -1,16 +1,18 @@
-from swarms.structs import Agent
 import os
+
 from dotenv import load_dotenv
+
 from swarms.models import GPT4VisionAPI
 from swarms.prompts.logistics import (
+    Efficiency_Agent_Prompt,
     Health_Security_Agent_Prompt,
-    Quality_Control_Agent_Prompt,
     Productivity_Agent_Prompt,
+    Quality_Control_Agent_Prompt,
     Safety_Agent_Prompt,
     Security_Agent_Prompt,
     Sustainability_Agent_Prompt,
-    Efficiency_Agent_Prompt,
 )
+from swarms.structs import Agent
 
 # Load ENV
 load_dotenv()

playground/examples/example_recursiveworkflow.py

@@ -1,6 +1,8 @@
 import os
+
 from dotenv import load_dotenv
-from swarms import OpenAIChat, Task, RecursiveWorkflow, Agent
+
+from swarms import Agent, OpenAIChat, RecursiveWorkflow, Task
 
 # Load environment variables from .env file
 load_dotenv()

playground/examples/example_sequentialworkflow.py

@@ -1,7 +1,9 @@
 import os
-from swarms import OpenAIChat, Agent, SequentialWorkflow
+
 from dotenv import load_dotenv
 
+from swarms import Agent, OpenAIChat, SequentialWorkflow
+
 load_dotenv()
 
 # Load the environment variables

playground/examples/example_simple_conversation_agent.py

@@ -3,8 +3,8 @@ import os
 from dotenv import load_dotenv
 
 from swarms import (
-    OpenAIChat,
     Conversation,
+    OpenAIChat,
 )
 
 conv = Conversation(

playground/examples/example_swarmnetwork.py

@@ -3,7 +3,7 @@ import os
 from dotenv import load_dotenv
 
 # Import the OpenAIChat model and the Agent struct
-from swarms import OpenAIChat, Agent, SwarmNetwork
+from swarms import Agent, OpenAIChat, SwarmNetwork
 
 # Load the environment variables
 load_dotenv()

playground/examples/example_toolagent.py

@@ -1,5 +1,6 @@
 # Import necessary libraries
 from transformers import AutoModelForCausalLM, AutoTokenizer
+
 from swarms import ToolAgent
 
 # Load the pre-trained model and tokenizer

playground/examples/example_worker.py

@@ -1,7 +1,9 @@
 # Importing necessary modules
 import os
+
 from dotenv import load_dotenv
-from swarms import Worker, OpenAIChat, tool
+
+from swarms import OpenAIChat, Worker, tool
 
 # Loading environment variables from .env file
 load_dotenv()

playground/models/azure_openai_example.py

@@ -1,5 +1,7 @@
 import os
+
 from dotenv import load_dotenv
+
 from swarms import AzureOpenAI
 
 # Load the environment variables

playground/models/custom_model_vllm.py

@@ -1,4 +1,5 @@
 from vllm import LLM
+
 from swarms import AbstractLLM, Agent, ChromaDB
 
 

playground/structs/hierarchical_swarm.py

@@ -1,7 +1,8 @@
 import os
-from swarms import OpenAIChat, Agent
+
 from dotenv import load_dotenv
 
+from swarms import Agent, OpenAIChat
 
 # Load environment variables
 load_dotenv()

playground/structs/majority_voting.py

@@ -1,4 +1,4 @@
-from swarms import Agent, MajorityVoting, ChromaDB, Anthropic
+from swarms import Agent, Anthropic, ChromaDB, MajorityVoting
 
 # Initialize the llm
 llm = Anthropic()

playground/structs/message_pool.py

@@ -1,7 +1,6 @@
-from swarms.structs.message_pool import MessagePool
 from swarms import Agent, OpenAIChat
 from swarms.memory.chroma_db import ChromaDB
-
+from swarms.structs.message_pool import MessagePool
 
 # Agents
 agent1 = Agent(

playground/structs/multi_process_workflow.py

@@ -1,8 +1,10 @@
 import os
-from swarms import Gemini, Agent
-from swarms.structs.multi_process_workflow import MultiProcessWorkflow
+
 from dotenv import load_dotenv
 
+from swarms import Agent, Gemini
+from swarms.structs.multi_process_workflow import MultiProcessWorkflow
+
 # Load the environment variables
 load_dotenv()
 

playground/structs/swarm_network_example.py

@@ -1,14 +1,16 @@
 # Import the OpenAIChat model and the Agent struct
 import os
+
+from dotenv import load_dotenv
+
 from swarms import (
     Agent,
+    Anthropic,
     OpenAIChat,
     SwarmNetwork,
-    Anthropic,
     TogetherLLM,
 )
 from swarms.memory import ChromaDB
-from dotenv import load_dotenv
 
 # load the environment variables
 load_dotenv()

playground/structs/tool_agent.py

@@ -1,4 +1,5 @@
 from transformers import AutoModelForCausalLM, AutoTokenizer
+
 from swarms import ToolAgent
 
 # Load the pre-trained model and tokenizer

playground/swarms/automate_docs.py

@@ -1,21 +1,21 @@
+import concurrent
 import inspect
 import os
 import threading
 from typing import Callable, List
 
-from swarms.prompts.documentation import DOCUMENTATION_WRITER_SOP
 from swarms import Agent, OpenAIChat
-from swarms.utils.loguru_logger import logger
-import concurrent
+from swarms.prompts.documentation import DOCUMENTATION_WRITER_SOP
 
 #########
 from swarms.utils.file_processing import (
+    create_file_in_folder,
     load_json,
     sanitize_file_path,
-    zip_workspace,
-    create_file_in_folder,
     zip_folders,
+    zip_workspace,
 )
+from swarms.utils.loguru_logger import logger
 
 
 class PythonDocumentationSwarm:

playground/swarms/hierarchical_swarm.py

@@ -3,7 +3,9 @@ Boss selects what agent to use
 B -> W1, W2, W3
 """
 from typing import List, Optional
+
 from pydantic import BaseModel, Field
+
 from swarms.utils.json_utils import str_to_json
 
 

pyproject.toml

@@ -71,10 +71,10 @@ pandas = "^2.2.2"
 fastapi = "^0.110.1"
 
 [tool.ruff]
-line-length = 127
+line-length = 1234
 
 [tool.ruff.lint]
-select = ["E4", "E7", "E9", "F", "W", "E501"]
+select = ["E4", "E7", "E9", "F", "W", "E501", "I", "UP"]
 ignore = []
 fixable = ["ALL"]
 unfixable = []

swarms/agents/base.py

@@ -1,5 +1,5 @@
 from abc import abstractmethod
-from typing import Dict, List, Union, Optional
+from typing import Dict, List, Optional, Union
 
 
 class AbstractAgent:

swarms/agents/tool_agent.py

@@ -1,4 +1,4 @@
-from typing import Any, Optional, Callable
+from typing import Any, Callable, Optional
 
 from swarms.structs.agent import Agent
 from swarms.tools.format_tools import Jsonformer

swarms/memory/chroma_db.py

@@ -7,9 +7,9 @@ import chromadb
 import numpy as np
 from dotenv import load_dotenv
 
+from swarms.memory.base_vectordb import AbstractVectorDatabase
 from swarms.utils.data_to_text import data_to_text
 from swarms.utils.markdown_message import display_markdown_message
-from swarms.memory.base_vectordb import AbstractVectorDatabase
 
 # Load environment variables
 load_dotenv()

swarms/memory/lanchain_chroma.py

@@ -6,8 +6,9 @@ from langchain.chains.question_answering import load_qa_chain
 from langchain.embeddings.openai import OpenAIEmbeddings
 from langchain.text_splitter import CharacterTextSplitter
 from langchain.vectorstores import Chroma
-from swarms.models.popular_llms import OpenAIChat
+
 from swarms.memory.base_vectordb import AbstractVectorDatabase
+from swarms.models.popular_llms import OpenAIChat
 
 
 def synchronized_mem(method):

swarms/memory/pg.py

@@ -5,6 +5,7 @@ from sqlalchemy import JSON, Column, String, create_engine
 from sqlalchemy.dialects.postgresql import UUID
 from sqlalchemy.ext.declarative import declarative_base
 from sqlalchemy.orm import Session
+
 from swarms.memory.base_vectordb import AbstractVectorDatabase
 
 

swarms/memory/qdrant.py

@@ -1,6 +1,7 @@
 from typing import List
 
 from httpx import RequestError
+
 from swarms.memory.base_vectordb import AbstractVectorDatabase
 
 try:

swarms/models/__init__.py

@@ -23,6 +23,7 @@ from swarms.models.popular_llms import (
 from swarms.models.popular_llms import (
     CohereChat as Cohere,
 )
+from swarms.models.popular_llms import OctoAIChat
 from swarms.models.popular_llms import (
     OpenAIChatLLM as OpenAIChat,
 )
@@ -32,9 +33,7 @@ from swarms.models.popular_llms import (
 from swarms.models.popular_llms import (
     ReplicateLLM as Replicate,
 )
-from swarms.models.popular_llms import OctoAIChat
 from swarms.models.qwen import QwenVLMultiModal  # noqa: E402
-
 from swarms.models.sampling_params import SamplingParams, SamplingType
 from swarms.models.together import TogetherLLM  # noqa: E402
 from swarms.models.types import (  # noqa: E402
@@ -46,7 +45,6 @@ from swarms.models.types import (  # noqa: E402
 )
 from swarms.models.vilt import Vilt  # noqa: E402
 
-
 __all__ = [
     "AbstractLLM",
     "Anthropic",

swarms/models/base_embedding_model.py

@@ -2,9 +2,10 @@ from __future__ import annotations
 
 from abc import ABC, abstractmethod
 from dataclasses import dataclass
+from typing import Callable
 
 import numpy as np
-from typing import Callable
+
 from swarms.artifacts.text_artifact import TextArtifact
 from swarms.utils.exponential_backoff import ExponentialBackoffMixin
 

swarms/models/openai_embeddings.py

@@ -5,7 +5,7 @@ import warnings
 from typing import Any, Callable, Literal, Sequence
 
 import numpy as np
-from pydantic import model_validator, ConfigDict, BaseModel, Field
+from pydantic import BaseModel, ConfigDict, Field, model_validator
 from tenacity import (
     AsyncRetrying,
     before_sleep_log,

swarms/models/palm.py

@@ -8,6 +8,7 @@ from langchain.llms import BaseLLM
 from langchain.pydantic_v1 import BaseModel
 from langchain.schema import Generation, LLMResult
 from langchain.utils import get_from_dict_or_env
+from pydantic import model_validator
 from tenacity import (
     before_sleep_log,
     retry,
@@ -15,7 +16,6 @@ from tenacity import (
     stop_after_attempt,
     wait_exponential,
 )
-from pydantic import model_validator
 
 logger = logging.getLogger(__name__)
 

swarms/prompts/worker_prompt.py

@@ -1,4 +1,5 @@
 import datetime
+
 from pydantic import BaseModel, Field
 
 time = datetime.datetime.now().strftime("%Y-%m-%d %H:%M:%S")

swarms/structs/__init__.py

@@ -4,6 +4,7 @@ from swarms.structs.agent_process import (
     AgentProcess,
     AgentProcessQueue,
 )
+from swarms.structs.agent_rearrange import AgentRearrange
 from swarms.structs.auto_swarm import AutoSwarm, AutoSwarmRouter
 from swarms.structs.autoscaler import AutoScaler
 from swarms.structs.base import BaseStructure
@@ -78,8 +79,6 @@ from swarms.structs.utils import (
     find_token_in_text,
     parse_tasks,
 )
-from swarms.structs.agent_rearrange import AgentRearrange
-
 
 __all__ = [
     "Agent",

swarms/structs/agent.py

@@ -19,14 +19,14 @@ from swarms.prompts.multi_modal_autonomous_instruction_prompt import (
 )
 from swarms.prompts.worker_prompt import worker_tools_sop_promp
 from swarms.structs.conversation import Conversation
+from swarms.tools.code_executor import CodeExecutor
+from swarms.tools.exec_tool import execute_tool_by_name
+from swarms.tools.function_util import process_tool_docs
 from swarms.tools.tool import BaseTool
 from swarms.utils.code_interpreter import SubprocessCodeInterpreter
 from swarms.utils.data_to_text import data_to_text
 from swarms.utils.parse_code import extract_code_from_markdown
 from swarms.utils.pdf_to_text import pdf_to_text
-from swarms.tools.exec_tool import execute_tool_by_name
-from swarms.tools.function_util import process_tool_docs
-from swarms.tools.code_executor import CodeExecutor
 
 
 # Utils

swarms/structs/agent_process.py

@@ -1,10 +1,10 @@
 from datetime import datetime
+from typing import Callable
 
 from pydantic import BaseModel
 
 from swarms.structs.omni_agent_types import agents
 from swarms.utils.loguru_logger import logger
-from typing import Callable
 
 
 class AgentProcess(BaseModel):

swarms/structs/agent_rearrange.py

@@ -1,6 +1,7 @@
 import logging
 from collections import defaultdict
 from typing import Callable, Sequence
+
 from swarms.structs.agent import Agent
 from swarms.structs.base_swarm import BaseSwarm
 

swarms/structs/base_swarm.py

@@ -15,8 +15,8 @@ import yaml
 
 from swarms.structs.agent import Agent
 from swarms.structs.conversation import Conversation
-from swarms.utils.loguru_logger import logger
 from swarms.structs.omni_agent_types import agent
+from swarms.utils.loguru_logger import logger
 
 
 class BaseSwarm(ABC):

swarms/structs/conversation.py

@@ -1,12 +1,11 @@
 import datetime
 import json
-from typing import Optional
+from typing import Any, Optional
 
 from termcolor import colored
 
 from swarms.memory.base_db import AbstractDatabase
 from swarms.structs.base import BaseStructure
-from typing import Any
 
 
 class Conversation(BaseStructure):

swarms/structs/meta_system_prompt.py

@@ -1,10 +1,11 @@
-from swarms.structs.agent import Agent
 from typing import Union
-from swarms.models.popular_llms import OpenAIChat
+
 from swarms.models.base_llm import AbstractLLM
+from swarms.models.popular_llms import OpenAIChat
 from swarms.prompts.meta_system_prompt import (
     meta_system_prompt_generator,
 )
+from swarms.structs.agent import Agent
 
 meta_prompter_llm = OpenAIChat(
     system_prompt=str(meta_system_prompt_generator)

swarms/structs/omni_agent_types.py

@@ -4,6 +4,7 @@ from typing import (
     Sequence,
     Union,
 )
+
 from swarms.models.base_llm import AbstractLLM
 from swarms.models.base_multimodal_model import BaseMultiModalModel
 from swarms.structs.agent import Agent

swarms/structs/rearrange.py

@@ -1,8 +1,9 @@
 import logging
 from collections import defaultdict
-from swarms.utils.loguru_logger import logger
+from typing import Callable, Sequence
+
 from swarms.structs.agent import Agent
-from typing import Sequence, Callable
+from swarms.utils.loguru_logger import logger
 
 
 class AgentRearrange:

swarms/structs/sermon_swarm.py

@@ -1,4 +1,5 @@
-from typing import Union, Sequence, List, Callable
+from typing import Callable, List, Sequence, Union
+
 from swarms.structs.agent import Agent
 from swarms.structs.base_swarm import BaseSwarm
 

swarms/structs/step.py

@@ -1,8 +1,9 @@
 from typing import Dict, List, Sequence
 
-from swarms.tools.tool import BaseTool
 from pydantic import BaseModel
 
+from swarms.tools.tool import BaseTool
+
 
 class Step(BaseModel):
     """

swarms/structs/swarm_net.py

@@ -5,7 +5,6 @@ import threading
 from typing import List, Optional
 
 # from fastapi import FastAPI
-
 from swarms.structs.agent import Agent
 from swarms.structs.base import BaseStructure
 from swarms.utils.logger import logger  # noqa: F401

swarms/structs/team.py

@@ -1,7 +1,7 @@
 import json
 from typing import List, Optional
 
-from pydantic import model_validator, BaseModel, Field, Json
+from pydantic import BaseModel, Field, Json, model_validator
 
 from swarms.structs.agent import Agent
 from swarms.structs.task import Task

swarms/telemetry/__init__.py

@@ -1,4 +1,5 @@
 from swarms.telemetry.log_all import log_all_calls, log_calls
+from swarms.telemetry.sentry_active import activate_sentry
 from swarms.telemetry.sys_info import (
     get_cpu_info,
     get_os_version,
@@ -16,7 +17,6 @@ from swarms.telemetry.user_utils import (
     get_system_info,
     get_user_device_data,
 )
-from swarms.telemetry.sentry_active import activate_sentry
 
 __all__ = [
     "log_all_calls",

swarms/telemetry/auto_upgrade_swarms.py

@@ -1,8 +1,9 @@
 import subprocess
 
-from swarms.telemetry.check_update import check_for_update
 from termcolor import colored
 
+from swarms.telemetry.check_update import check_for_update
+
 
 def auto_update():
     """auto update swarms"""

swarms/telemetry/bootup.py

@@ -1,5 +1,5 @@
-import os
 import logging
+import os
 import warnings
 
 from swarms.telemetry.auto_upgrade_swarms import auto_update

swarms/telemetry/sentry_active.py

@@ -1,6 +1,7 @@
 import os
-from dotenv import load_dotenv
+
 import sentry_sdk
+from dotenv import load_dotenv
 
 load_dotenv()
 

swarms/tools/__init__.py

@@ -1,4 +1,3 @@
-from swarms.tools.tool import BaseTool, Tool, StructuredTool, tool
 from swarms.tools.code_executor import CodeExecutor
 from swarms.tools.exec_tool import (
     AgentAction,
@@ -7,6 +6,7 @@ from swarms.tools.exec_tool import (
     execute_tool_by_name,
     preprocess_json_input,
 )
+from swarms.tools.tool import BaseTool, StructuredTool, Tool, tool
 from swarms.tools.tool_utils import (
     execute_tools,
     extract_tool_commands,

swarms/tools/exec_tool.py

@@ -1,5 +1,5 @@
-import json
 import concurrent.futures
+import json
 import re
 from abc import abstractmethod
 from typing import Dict, List, NamedTuple

swarms/tools/format_tools.py

@@ -1,15 +1,16 @@
 import json
 from typing import Any, Dict, List, Union
 
+from pydantic import BaseModel
 from termcolor import cprint
 from transformers import PreTrainedModel, PreTrainedTokenizer
-from pydantic import BaseModel
+
+from swarms.models.base_llm import AbstractLLM
 from swarms.tools.logits_processor import (
     NumberStoppingCriteria,
     OutputNumbersTokens,
     StringStoppingCriteria,
 )
-from swarms.models.base_llm import AbstractLLM
 
 GENERATION_MARKER = "|GENERATION|"
 

swarms/tools/tool.py

@@ -1,8 +1,8 @@
 from langchain.tools import (
     BaseTool,
-    Tool,
     StructuredTool,
+    Tool,
     tool,
-)  # noqa F401
+)
 
 __all__ = ["BaseTool", "Tool", "StructuredTool", "tool"]

swarms/tools/tool_utils.py

@@ -1,13 +1,12 @@
+import inspect
 import json
 import re
-from typing import Any, List
+from typing import Any, Callable, List
+
+from termcolor import colored
 
 from swarms.prompts.tools import SCENARIOS
 from swarms.tools.tool import BaseTool
-import inspect
-from typing import Callable
-
-from termcolor import colored
 
 
 def scrape_tool_func_docs(fn: Callable) -> str:

swarms/utils/__init__.py

@@ -1,5 +1,6 @@
 from swarms.utils.class_args_wrapper import print_class_parameters
 from swarms.utils.code_interpreter import SubprocessCodeInterpreter
+from swarms.utils.concurrent_utils import execute_concurrently
 from swarms.utils.csv_and_pandas import (
     csv_to_dataframe,
     dataframe_to_strings,
@@ -17,11 +18,11 @@ from swarms.utils.download_weights_from_url import (
 )
 from swarms.utils.exponential_backoff import ExponentialBackoffMixin
 from swarms.utils.file_processing import (
+    create_file_in_folder,
     load_json,
     sanitize_file_path,
-    zip_workspace,
-    create_file_in_folder,
     zip_folders,
+    zip_workspace,
 )
 from swarms.utils.find_img_path import find_image_path
 from swarms.utils.json_output_parser import JsonOutputParser
@@ -44,8 +45,6 @@ from swarms.utils.save_logs import parse_log_file
 # from swarms.utils.supervision_visualizer import MarkVisualizer
 from swarms.utils.try_except_wrapper import try_except_wrapper
 from swarms.utils.yaml_output_parser import YamlOutputParser
-from swarms.utils.concurrent_utils import execute_concurrently
-
 
 __all__ = [
     "print_class_parameters",

swarms/utils/function_calling_utils.py

@@ -1,7 +1,7 @@
+import asyncio
 import concurrent.futures
-from typing import Any, Callable, Dict, List
 from inspect import iscoroutinefunction
-import asyncio
+from typing import Any, Callable, Dict, List
 
 
 # Helper function to run an asynchronous function in a synchronous way

swarms/utils/main.py

@@ -50,22 +50,12 @@ def get_new_image_name(org_img_name, func_name="update"):
     if len(name_split) == 1:
         most_org_file_name = name_split[0]
         recent_prev_file_name = name_split[0]
-        new_file_name = "{}_{}_{}_{}.png".format(
-            this_new_uuid,
-            func_name,
-            recent_prev_file_name,
-            most_org_file_name,
-        )
+        new_file_name = f"{this_new_uuid}_{func_name}_{recent_prev_file_name}_{most_org_file_name}.png"
     else:
         assert len(name_split) == 4
         most_org_file_name = name_split[3]
         recent_prev_file_name = name_split[0]
-        new_file_name = "{}_{}_{}_{}.png".format(
-            this_new_uuid,
-            func_name,
-            recent_prev_file_name,
-            most_org_file_name,
-        )
+        new_file_name = f"{this_new_uuid}_{func_name}_{recent_prev_file_name}_{most_org_file_name}.png"
     return os.path.join(head, new_file_name)
 
 
@@ -78,22 +68,12 @@ def get_new_dataframe_name(org_img_name, func_name="update"):
     if len(name_split) == 1:
         most_org_file_name = name_split[0]
         recent_prev_file_name = name_split[0]
-        new_file_name = "{}_{}_{}_{}.csv".format(
-            this_new_uuid,
-            func_name,
-            recent_prev_file_name,
-            most_org_file_name,
-        )
+        new_file_name = f"{this_new_uuid}_{func_name}_{recent_prev_file_name}_{most_org_file_name}.csv"
     else:
         assert len(name_split) == 4
         most_org_file_name = name_split[3]
         recent_prev_file_name = name_split[0]
-        new_file_name = "{}_{}_{}_{}.csv".format(
-            this_new_uuid,
-            func_name,
-            recent_prev_file_name,
-            most_org_file_name,
-        )
+        new_file_name = f"{this_new_uuid}_{func_name}_{recent_prev_file_name}_{most_org_file_name}.csv"
     return os.path.join(head, new_file_name)
 
 

swarms/utils/serializable.py

@@ -1,7 +1,7 @@
 from abc import ABC
 from typing import Any, Dict, List, Literal, TypedDict, Union, cast
 
-from pydantic import ConfigDict, BaseModel, PrivateAttr
+from pydantic import BaseModel, ConfigDict, PrivateAttr
 
 
 class BaseSerialized(TypedDict):