Tools For SWE Kit

File Tool

Open file

Opens a file in the editor based on the provided file path, If line_number is provided, the window will be move to include that line

1 from langchain.agents import create_openai_functions_agent, AgentExecutor
2 from langchain import hub
3 from langchain_openai import ChatOpenAI
4 from composio_langchain import ComposioToolSet, Action, App
5 
6 llm = ChatOpenAI()
7 prompt = hub.pull("hwchase17/openai-functions-agent")
8 
9 composio_toolset = ComposioToolSet()
10 tools = composio_toolset.get_tools(actions=['FILETOOL_OPEN_FILE'])
11 
12 agent = create_openai_functions_agent(llm, tools, prompt)
13 agent_executor = AgentExecutor(agent=agent, tools=tools, verbose=True)
14 
15 task = "your task description here"
16 result = agent_executor.invoke({"input": task})
17 print(result)

Rename a file

Renames a file based on the provided file path

1 from langchain.agents import create_openai_functions_agent, AgentExecutor
2 from langchain import hub
3 from langchain_openai import ChatOpenAI
4 from composio_langchain import ComposioToolSet, Action, App
5 
6 llm = ChatOpenAI()
7 prompt = hub.pull("hwchase17/openai-functions-agent")
8 
9 composio_toolset = ComposioToolSet(api_key="")
10 tools = composio_toolset.get_tools(actions=['FILETOOL_RENAME_FILE'])
11 
12 agent = create_openai_functions_agent(llm, tools, prompt)
13 agent_executor = AgentExecutor(agent=agent, tools=tools, verbose=True)
14 
15 task = "your task description here"
16 result = agent_executor.invoke({"input": task})
17 print(result)

Edit a file

Use this tools to edit a file on specific line numbers

1 from langchain.agents import create_openai_functions_agent, AgentExecutor
2 from langchain import hub
3 from langchain_openai import ChatOpenAI
4 from composio_langchain import ComposioToolSet, Action, App
5 
6 llm = ChatOpenAI()
7 prompt = hub.pull("hwchase17/openai-functions-agent")
8 
9 composio_toolset = ComposioToolSet(api_key="")
10 tools = composio_toolset.get_tools(actions=['FILETOOL_EDIT_FILE'])
11 
12 agent = create_openai_functions_agent(llm, tools, prompt)
13 agent_executor = AgentExecutor(agent=agent, tools=tools, verbose=True)
14 
15 task = "your task description here"
16 result = agent_executor.invoke({"input": task})
17 print(result)

Create file

Creates a new file or directory within a shell session

1 from langchain.agents import create_openai_functions_agent, AgentExecutor
2 from langchain import hub
3 from langchain_openai import ChatOpenAI
4 from composio_langchain import ComposioToolSet, Action, App
5 
6 llm = ChatOpenAI()
7 prompt = hub.pull("hwchase17/openai-functions-agent")
8 
9 composio_toolset = ComposioToolSet(api_key="")
10 tools = composio_toolset.get_tools(actions=['FILETOOL_CREATE_FILE'])
11 
12 agent = create_openai_functions_agent(llm, tools, prompt)
13 agent_executor = AgentExecutor(agent=agent, tools=tools, verbose=True)
14 
15 task = "your task description here"
16 result = agent_executor.invoke({"input": task})
17 print(result)

Scroll

Scrolls the view of the opened file up or down by 100 lines

1 from langchain.agents import create_openai_functions_agent, AgentExecutor
2 from langchain import hub
3 from langchain_openai import ChatOpenAI
4 from composio_langchain import ComposioToolSet, Action, App
5 
6 llm = ChatOpenAI()
7 prompt = hub.pull("hwchase17/openai-functions-agent")
8 
9 composio_toolset = ComposioToolSet(api_key="")
10 tools = composio_toolset.get_tools(actions=['FILETOOL_SCROLL'])
11 
12 agent = create_openai_functions_agent(llm, tools, prompt)
13 agent_executor = AgentExecutor(agent=agent, tools=tools, verbose=True)
14 
15 task = "your task description here"
16 result = agent_executor.invoke({"input": task})
17 print(result)

Scroll

Scrolls the view of the opened file up or down by 100 lines

1 from langchain.agents import create_openai_functions_agent, AgentExecutor
2 from langchain import hub
3 from langchain_openai import ChatOpenAI
4 from composio_langchain import ComposioToolSet, Action, App
5 
6 llm = ChatOpenAI()
7 prompt = hub.pull("hwchase17/openai-functions-agent")
8 
9 composio_toolset = ComposioToolSet(api_key="")
10 tools = composio_toolset.get_tools(actions=['FILETOOL_SCROLL'])
11 
12 agent = create_openai_functions_agent(llm, tools, prompt)
13 agent_executor = AgentExecutor(agent=agent, tools=tools, verbose=True)
14 
15 task = "your task description here"
16 result = agent_executor.invoke({"input": task})
17 print(result)

List files

Lists files and directories in the current working directory

1 from langchain.agents import create_openai_functions_agent, AgentExecutor
2 from langchain import hub
3 from langchain_openai import ChatOpenAI
4 from composio_langchain import ComposioToolSet, Action, App
5 
6 llm = ChatOpenAI()
7 prompt = hub.pull("hwchase17/openai-functions-agent")
8 
9 composio_toolset = ComposioToolSet(api_key="")
10 tools = composio_toolset.get_tools(actions=['FILETOOL_LIST_FILES'])
11 
12 agent = create_openai_functions_agent(llm, tools, prompt)
13 agent_executor = AgentExecutor(agent=agent, tools=tools, verbose=True)
14 
15 task = "your task description here"
16 result = agent_executor.invoke({"input": task})
17 print(result)

Search word

Search for a specific word or phrase across multiple files in your workspace by specifying a pattern

1 from langchain.agents import create_openai_functions_agent, AgentExecutor
2 from langchain import hub
3 from langchain_openai import ChatOpenAI
4 from composio_langchain import ComposioToolSet, Action, App
5 
6 llm = ChatOpenAI()
7 prompt = hub.pull("hwchase17/openai-functions-agent")
8 
9 composio_toolset = ComposioToolSet(api_key="")
10 tools = composio_toolset.get_tools(actions=['FILETOOL_SEARCH_WORD'])
11 
12 agent = create_openai_functions_agent(llm, tools, prompt)
13 agent_executor = AgentExecutor(agent=agent, tools=tools, verbose=True)
14 
15 task = "your task description here"
16 result = agent_executor.invoke({"input": task})
17 print(result)

Find file

Finds files or directories matching the given pattern in the workspace

1 from langchain.agents import create_openai_functions_agent, AgentExecutor
2 from langchain import hub
3 from langchain_openai import ChatOpenAI
4 from composio_langchain import ComposioToolSet, Action, App
5 
6 llm = ChatOpenAI()
7 prompt = hub.pull("hwchase17/openai-functions-agent")
8 
9 composio_toolset = ComposioToolSet(api_key="")
10 tools = composio_toolset.get_tools(actions=['FILETOOL_FIND_FILE'])
11 
12 agent = create_openai_functions_agent(llm, tools, prompt)
13 agent_executor = AgentExecutor(agent=agent, tools=tools, verbose=True)
14 
15 task = "your task description here"
16 result = agent_executor.invoke({"input": task})
17 print(result)

Write

Write the given content to a file

1 from langchain.agents import create_openai_functions_agent, AgentExecutor
2 from langchain import hub
3 from langchain_openai import ChatOpenAI
4 from composio_langchain import ComposioToolSet, Action, App
5 
6 llm = ChatOpenAI()
7 prompt = hub.pull("hwchase17/openai-functions-agent")
8 
9 composio_toolset = ComposioToolSet(api_key="")
10 tools = composio_toolset.get_tools(actions=['FILETOOL_WRITE'])
11 
12 agent = create_openai_functions_agent(llm, tools, prompt)
13 agent_executor = AgentExecutor(agent=agent, tools=tools, verbose=True)
14 
15 task = "your task description here"
16 result = agent_executor.invoke({"input": task})
17 print(result)

Change working directory

Changes the current working directory of the file manager to the specified path

1 from langchain.agents import create_openai_functions_agent, AgentExecutor
2 from langchain import hub
3 from langchain_openai import ChatOpenAI
4 from composio_langchain import ComposioToolSet, Action, App
5 
6 llm = ChatOpenAI()
7 prompt = hub.pull("hwchase17/openai-functions-agent")
8 
9 composio_toolset = ComposioToolSet(api_key="")
10 tools = composio_toolset.get_tools(actions=['FILETOOL_CHANGE_WORKING_DIRECTORY'])
11 
12 agent = create_openai_functions_agent(llm, tools, prompt)
13 agent_executor = AgentExecutor(agent=agent, tools=tools, verbose=True)
14 
15 task = "your task description here"
16 result = agent_executor.invoke({"input": task})
17 print(result)

Git clone

This action allows you to clone a Git repository to your local directory

1 from langchain.agents import create_openai_functions_agent, AgentExecutor
2 from langchain import hub
3 from langchain_openai import ChatOpenAI
4 from composio_langchain import ComposioToolSet, Action, App
5 
6 llm = ChatOpenAI()
7 prompt = hub.pull("hwchase17/openai-functions-agent")
8 
9 composio_toolset = ComposioToolSet(api_key="")
10 tools = composio_toolset.get_tools(actions=['FILETOOL_GIT_CLONE'])
11 
12 agent = create_openai_functions_agent(llm, tools, prompt)
13 agent_executor = AgentExecutor(agent=agent, tools=tools, verbose=True)
14 
15 task = "your task description here"
16 result = agent_executor.invoke({"input": task})
17 print(result)

Git repo tree

Creates a tree representation of the Git repository

1 from langchain.agents import create_openai_functions_agent, AgentExecutor
2 from langchain import hub
3 from langchain_openai import ChatOpenAI
4 from composio_langchain import ComposioToolSet, Action, App
5 
6 llm = ChatOpenAI()
7 prompt = hub.pull("hwchase17/openai-functions-agent")
8 
9 composio_toolset = ComposioToolSet(api_key="")
10 tools = composio_toolset.get_tools(actions=['FILETOOL_GIT_REPO_TREE'])
11 
12 agent = create_openai_functions_agent(llm, tools, prompt)
13 agent_executor = AgentExecutor(agent=agent, tools=tools, verbose=True)
14 
15 task = "your task description here"
16 result = agent_executor.invoke({"input": task})
17 print(result)

Get Git Patch

Get the patch from the current working directory

1 from langchain.agents import create_openai_functions_agent, AgentExecutor
2 from langchain import hub
3 from langchain_openai import ChatOpenAI
4 from composio_langchain import ComposioToolSet, Action, App
5 
6 llm = ChatOpenAI()
7 prompt = hub.pull("hwchase17/openai-functions-agent")
8 
9 composio_toolset = ComposioToolSet(api_key="")
10 tools = composio_toolset.get_tools(actions=['FILETOOL_GIT_PATCH'])
11 
12 agent = create_openai_functions_agent(llm, tools, prompt)
13 agent_executor = AgentExecutor(agent=agent, tools=tools, verbose=True)
14 
15 task = "your task description here"
16 result = agent_executor.invoke({"input": task})
17 print(result)

Code Analysis Tool

Create index

Use this to create a code map for a repository by indexing and analyzing its contents

1 from langchain.agents import create_openai_functions_agent, AgentExecutor
2 from langchain import hub
3 from langchain_openai import ChatOpenAI
4 from composio_langchain import ComposioToolSet, Action, App
5 llm = ChatOpenAI()
6 prompt = hub.pull("hwchase17/openai-functions-agent")
7 
8 composio_toolset = ComposioToolSet(api_key="")
9 tools = composio_toolset.get_tools(actions=['CODE_ANALYSIS_TOOL_CREATE_CODE_MAP'])
10 
11 agent = create_openai_functions_agent(llm, tools, prompt)
12 agent_executor = AgentExecutor(agent=agent, tools=tools, verbose=True)
13 task = "your task description here"
14 result = agent_executor.invoke({"input": task})
15 print(result)

Get Class Info

This tool retrieves and formats detailed information about a specified class in a given repository

1 from langchain.agents import create_openai_functions_agent, AgentExecutor
2 from langchain import hub
3 from langchain_openai import ChatOpenAI
4 from composio_langchain import ComposioToolSet, Action, App
5 llm = ChatOpenAI()
6 prompt = hub.pull("hwchase17/openai-functions-agent")
7 
8 composio_toolset = ComposioToolSet(api_key="")
9 tools = composio_toolset.get_tools(actions=['CODE_ANALYSIS_TOOL_GET_CLASS_INFO'])
10 
11 agent = create_openai_functions_agent(llm, tools, prompt)
12 agent_executor = AgentExecutor(agent=agent, tools=tools, verbose=True)
13 task = "your task description here"
14 result = agent_executor.invoke({"input": task})
15 print(result)

Get Method Body

This tool retrieves the body of a specified method from a given repository

1 from langchain.agents import create_openai_functions_agent, AgentExecutor
2 from langchain import hub
3 from langchain_openai import ChatOpenAI
4 from composio_langchain import ComposioToolSet, Action, App
5 
6 llm = ChatOpenAI()
7 prompt = hub.pull("hwchase17/openai-functions-agent")
8 
9 composio_toolset = ComposioToolSet(api_key="")
10 tools = composio_toolset.get_tools(actions=['CODE_ANALYSIS_TOOL_GET_METHOD_BODY'])
11 
12 agent = create_openai_functions_agent(llm, tools, prompt)
13 agent_executor = AgentExecutor(agent=agent, tools=tools, verbose=True)
14 
15 task = "your task description here"
16 result = agent_executor.invoke({"input": task})
17 print(result)

Get Method Signature

This tool retrieves the signature of a specified method from a given repository.

1 from langchain.agents import create_openai_functions_agent, AgentExecutor
2 from langchain import hub
3 from langchain_openai import ChatOpenAI
4 from composio_langchain import ComposioToolSet, Action, App
5 
6 llm = ChatOpenAI()
7 prompt = hub.pull("hwchase17/openai-functions-agent")
8 
9 composio_toolset = ComposioToolSet(api_key="")
10 tools = composio_toolset.get_tools(actions=['CODE_ANALYSIS_TOOL_GET_METHOD_SIGNATURE'])
11 
12 agent = create_openai_functions_agent(llm, tools, prompt)
13 agent_executor = AgentExecutor(agent=agent, tools=tools, verbose=True)
14 
15 task = "your task description here"
16 result = agent_executor.invoke({"input": task})
17 print(result)

Get Relevant Code

Retrieves relevant code snippets from a repository based on a given query

1 from langchain.agents import create_openai_functions_agent, AgentExecutor
2 from langchain import hub
3 from langchain_openai import ChatOpenAI
4 from composio_langchain import ComposioToolSet, Action, App
5 
6 llm = ChatOpenAI()
7 prompt = hub.pull("hwchase17/openai-functions-agent")
8 
9 composio_toolset = ComposioToolSet(api_key="")
10 tools = composio_toolset.get_tools(actions=['CODE_ANALYSIS_TOOL_GET_RELEVANT_CODE'])
11 
12 agent = create_openai_functions_agent(llm, tools, prompt)
13 agent_executor = AgentExecutor(agent=agent, tools=tools, verbose=True)
14 
15 task = "your task description here"
16 result = agent_executor.invoke({"input": task})
17 print(result)

Shell Tool

Exec command

Run any command directly on shell

1 from langchain.agents import create_openai_functions_agent, AgentExecutor
2 from langchain import hub
3 from langchain_openai import ChatOpenAI
4 from composio_langchain import ComposioToolSet, Action, App
5 
6 llm = ChatOpenAI()
7 prompt = hub.pull("hwchase17/openai-functions-agent")
8 
9 composio_toolset = ComposioToolSet(api_key="")
10 tools = composio_toolset.get_tools(actions=['SHELLTOOL_EXEC_COMMAND'])
11 
12 agent = create_openai_functions_agent(llm, tools, prompt)
13 agent_executor = AgentExecutor(agent=agent, tools=tools, verbose=True)
14 
15 task = "your task description here"
16 result = agent_executor.invoke({"input": task})
17 print(result)

Create shell

Use this tool to create a new shell session

1 from langchain.agents import create_openai_functions_agent, AgentExecutor
2 from langchain import hub
3 from langchain_openai import ChatOpenAI
4 from composio_langchain import ComposioToolSet, Action, App
5 
6 llm = ChatOpenAI()
7 prompt = hub.pull("hwchase17/openai-functions-agent")
8 
9 composio_toolset = ComposioToolSet(api_key="")
10 tools = composio_toolset.get_tools(actions=['SHELLTOOL_CREATE_SHELL'])
11 
12 agent = create_openai_functions_agent(llm, tools, prompt)
13 agent_executor = AgentExecutor(agent=agent, tools=tools, verbose=True)
14 
15 task = "your task description here"
16 result = agent_executor.invoke({"input": task})
17 print(result)

Spawn process

Spawn a process

1 from langchain.agents import create_openai_functions_agent, AgentExecutor
2 from langchain import hub
3 from langchain_openai import ChatOpenAI
4 from composio_langchain import ComposioToolSet, Action, App
5 
6 llm = ChatOpenAI()
7 prompt = hub.pull("hwchase17/openai-functions-agent")
8 
9 composio_toolset = ComposioToolSet(api_key="")
10 tools = composio_toolset.get_tools(actions=['SHELLTOOL_SPAWN_PROCESS'])
11 
12 agent = create_openai_functions_agent(llm, tools, prompt)
13 agent_executor = AgentExecutor(agent=agent, tools=tools, verbose=True)
14 
15 task = "your task description here"
16 result = agent_executor.invoke({"input": task})
17 print(result)

Test command

Run the command for testing the patch

1 from langchain.agents import create_openai_functions_agent, AgentExecutor
2 from langchain import hub
3 from langchain_openai import ChatOpenAI
4 from composio_langchain import ComposioToolSet, Action, App
5 
6 llm = ChatOpenAI()
7 prompt = hub.pull("hwchase17/openai-functions-agent")
8 
9 composio_toolset = ComposioToolSet(api_key="")
10 tools = composio_toolset.get_tools(actions=['SHELLTOOL_TEST_COMMAND'])
11 
12 agent = create_openai_functions_agent(llm, tools, prompt)
13 agent_executor = AgentExecutor(agent=agent, tools=tools, verbose=True)
14 
15 task = "your task description here"
16 result = agent_executor.invoke({"input": task})
17 print(result)

RAG Tool

Add content to RAG

Tool for adding content to the knowledge base

1 from langchain.agents import create_openai_functions_agent, AgentExecutor
2 from langchain import hub
3 from langchain_openai import ChatOpenAI
4 from composio_langchain import ComposioToolSet, Action, App
5 
6 llm = ChatOpenAI()
7 prompt = hub.pull("hwchase17/openai-functions-agent")
8 
9 composio_toolset = ComposioToolSet(api_key="")
10 tools = composio_toolset.get_tools(actions=['RAGTOOL_ADD_CONTENT_TO_RAG_TOOL'])
11 
12 agent = create_openai_functions_agent(llm, tools, prompt)
13 agent_executor = AgentExecutor(agent=agent, tools=tools, verbose=True)
14 
15 task = "your task description here"
16 result = agent_executor.invoke({"input": task})
17 print(result)

Query Knowledge Base

Tool for querying a knowledge base

1 from langchain.agents import create_openai_functions_agent, AgentExecutor
2 from langchain import hub
3 from langchain_openai import ChatOpenAI
4 from composio_langchain import ComposioToolSet, Action, App
5 
6 llm = ChatOpenAI()
7 prompt = hub.pull("hwchase17/openai-functions-agent")
8 
9 composio_toolset = ComposioToolSet(api_key="")
10 tools = composio_toolset.get_tools(actions=['RAGTOOL_ADD_CONTENT_TO_RAG_TOOL'])
11 
12 agent = create_openai_functions_agent(llm, tools, prompt)
13 agent_executor = AgentExecutor(agent=agent, tools=tools, verbose=True)
14 
15 task = "your task description here"
16 result = agent_executor.invoke({"input": task})
17 print(result)

Embed Tool

Create Image Vector Store

Creates Vector Store for all image files in the specified folder

1 from langchain.agents import create_openai_functions_agent, AgentExecutor
2 from langchain import hub
3 from langchain_openai import ChatOpenAI
4 from composio_langchain import ComposioToolSet, Action, App
5 
6 llm = ChatOpenAI()
7 prompt = hub.pull("hwchase17/openai-functions-agent")
8 
9 composio_toolset = ComposioToolSet(api_key="")
10 tools = composio_toolset.get_tools(actions=['EMBED_TOOL_CREATE_IMAGE_VECTOR_STORE'])
11 
12 agent = create_openai_functions_agent(llm, tools, prompt)
13 agent_executor = AgentExecutor(agent=agent, tools=tools, verbose=True)
14 
15 task = "your task description here"
16 result = agent_executor.invoke({"input": task})
17 print(result)

Query Image Vector Store

Query Vector Store for images

1 from langchain.agents import create_openai_functions_agent, AgentExecutor
2 from langchain import hub
3 from langchain_openai import ChatOpenAI
4 from composio_langchain import ComposioToolSet, Action, App
5 
6 llm = ChatOpenAI()
7 prompt = hub.pull("hwchase17/openai-functions-agent")
8 
9 composio_toolset = ComposioToolSet(api_key="")
10 tools = composio_toolset.get_tools(actions=['EMBED_TOOL_QUERY_IMAGE_VECTOR_STORE'])
11 
12 agent = create_openai_functions_agent(llm, tools, prompt)
13 agent_executor = AgentExecutor(agent=agent, tools=tools, verbose=True)
14 
15 task = "your task description here"
16 result = agent_executor.invoke({"input": task})
17 print(result)

Other Useful Tools

SQL query

Executes a SQL Query and returns the results

1 from langchain.agents import create_openai_functions_agent, AgentExecutor
2 from langchain import hub
3 from langchain_openai import ChatOpenAI
4 from composio_langchain import ComposioToolSet, Action, App
5 
6 llm = ChatOpenAI()
7 prompt = hub.pull("hwchase17/openai-functions-agent")
8 
9 composio_toolset = ComposioToolSet(api_key="")
10 tools = composio_toolset.get_tools(actions=['SQLTOOL_SQL_QUERY'])
11 
12 agent = create_openai_functions_agent(llm, tools, prompt)
13 agent_executor = AgentExecutor(agent=agent, tools=tools, verbose=True)
14 
15 task = "your task description here"
16 result = agent_executor.invoke({"input": task})
17 print(result)

Advanced Codebase Search

Performs an advanced search across a codebase using regex patterns & optimized for large-scale software projects

1 from langchain.agents import create_openai_functions_agent, AgentExecutor
2 from langchain import hub
3 from langchain_openai import ChatOpenAI
4 from composio_langchain import ComposioToolSet, Action, App
5 
6 llm = ChatOpenAI()
7 prompt = hub.pull("hwchase17/openai-functions-agent")
8 
9 composio_toolset = ComposioToolSet(api_key="")
10 tools = composio_toolset.get_tools(actions=['CODE_GREP_TOOL_SEARCH_CODEBASE'])
11 
12 agent = create_openai_functions_agent(llm, tools, prompt)
13 agent_executor = AgentExecutor(agent=agent, tools=tools, verbose=True)
14 
15 task = "your task description here"
16 result = agent_executor.invoke({"input": task})
17 print(result)

Format and Lint Codebase

Performs code formatting and linting using ruff, addressing style issues and checking for errors

1 from langchain.agents import create_openai_functions_agent, AgentExecutor
2 from langchain import hub
3 from langchain_openai import ChatOpenAI
4 from composio_langchain import ComposioToolSet, Action, App
5 llm = ChatOpenAI()
6 prompt = hub.pull("hwchase17/openai-functions-agent")
7 
8 composio_toolset = ComposioToolSet(api_key="")
9 tools = composio_toolset.get_tools(actions=['CODE_FORMAT_TOOL_FORMAT_AND_LINT_CODEBASE'])
10 
11 agent = create_openai_functions_agent(llm, tools, prompt)
12 agent_executor = AgentExecutor(agent=agent, tools=tools, verbose=True)
13 task = "your task description here"
14 result = agent_executor.invoke({"input": task})
15 print(result)

Get workspace history

Returns history for workspace which includes state of the environment, last executed n commands & output from last n commands

1 from langchain.agents import create_openai_functions_agent, AgentExecutor
2 from langchain import hub
3 from langchain_openai import ChatOpenAI
4 from composio_langchain import ComposioToolSet, Action, App
5 
6 llm = ChatOpenAI()
7 prompt = hub.pull("hwchase17/openai-functions-agent")
8 
9 composio_toolset = ComposioToolSet(api_key="")
10 tools = composio_toolset.get_tools(actions=['HISTORY_FETCHER_GET_WORKSPACE_HISTORY'])
11 
12 agent = create_openai_functions_agent(llm, tools, prompt)
13 agent_executor = AgentExecutor(agent=agent, tools=tools, verbose=True)
14 
15 task = "your task description here"
16 result = agent_executor.invoke({"input": task})
17 print(result)