File Tool
Open file
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
from langchain.agents import create_openai_functions_agent, AgentExecutor
from langchain import hub
from langchain_openai import ChatOpenAI
from composio_langchain import ComposioToolSet, Action, App
llm = ChatOpenAI()
prompt = hub.pull("hwchase17/openai-functions-agent")
composio_toolset = ComposioToolSet()
tools = composio_toolset.get_tools(actions=['FILETOOL_OPEN_FILE'])
agent = create_openai_functions_agent(llm, tools, prompt)
agent_executor = AgentExecutor(agent=agent, tools=tools, verbose=True)
task = "your task description here"
result = agent_executor.invoke({"input": task})
print(result)
import { ChatOpenAI } from "@langchain/openai";
import { createOpenAIFunctionsAgent, AgentExecutor } from "langchain/agents";
import { LangchainToolSet } from "composio-core";
import { pull } from "langchain/hub";
const llm = new ChatOpenAI({
model: "gpt-4-turbo",
temperature: 0,
});
const prompt = await pull("hwchase17/openai-functions-agent");
const toolset = new LangchainToolSet({ apiKey: "<your-composio-api-key>" });
const tools = await toolset.getTools({ actions: ["FILETOOL_OPEN_FILE"] });
const agent = await createOpenAIFunctionsAgent({llm, tools, prompt});
const agentExecutor = new AgentExecutor({ agent, tools, verbose: true });
const response = await agentExecutor.invoke({ input: "your task description here" });
console.log(response);
Rename a file
Rename a file
Renames a file based on the provided file path
from langchain.agents import create_openai_functions_agent, AgentExecutor
from langchain import hub
from langchain_openai import ChatOpenAI
from composio_langchain import ComposioToolSet, Action, App
llm = ChatOpenAI()
prompt = hub.pull("hwchase17/openai-functions-agent")
composio_toolset = ComposioToolSet(api_key="")
tools = composio_toolset.get_tools(actions=['FILETOOL_RENAME_FILE'])
agent = create_openai_functions_agent(llm, tools, prompt)
agent_executor = AgentExecutor(agent=agent, tools=tools, verbose=True)
task = "your task description here"
result = agent_executor.invoke({"input": task})
print(result)
import { ChatOpenAI } from "@langchain/openai";
import { createOpenAIFunctionsAgent, AgentExecutor } from "langchain/agents";
import { LangchainToolSet } from "composio-core";
import { pull } from "langchain/hub";
const llm = new ChatOpenAI({
model: "gpt-4-turbo",
temperature: 0,
});
const prompt = await pull("hwchase17/openai-functions-agent");
const toolset = new LangchainToolSet({ apiKey: "<your-composio-api-key>" });
const tools = await toolset.getTools({ actions: ["FILETOOL_OPEN_FILE"] });
const agent = await createOpenAIFunctionsAgent({llm, tools, prompt});
const agentExecutor = new AgentExecutor({ agent, tools, verbose: true });
const response = await agentExecutor.invoke({ input: "your task description here" });
console.log(response);
Edit a file
Edit a file
Use this tools to edit a file on specific line numbers
from langchain.agents import create_openai_functions_agent, AgentExecutor
from langchain import hub
from langchain_openai import ChatOpenAI
from composio_langchain import ComposioToolSet, Action, App
llm = ChatOpenAI()
prompt = hub.pull("hwchase17/openai-functions-agent")
composio_toolset = ComposioToolSet(api_key="")
tools = composio_toolset.get_tools(actions=['FILETOOL_EDIT_FILE'])
agent = create_openai_functions_agent(llm, tools, prompt)
agent_executor = AgentExecutor(agent=agent, tools=tools, verbose=True)
task = "your task description here"
result = agent_executor.invoke({"input": task})
print(result)
import { ChatOpenAI } from "@langchain/openai";
import { createOpenAIFunctionsAgent, AgentExecutor } from "langchain/agents";
import { LangchainToolSet } from "composio-core";
import { pull } from "langchain/hub";
const llm = new ChatOpenAI({
model: "gpt-4-turbo",
temperature: 0,
});
const prompt = await pull("hwchase17/openai-functions-agent");
const toolset = new LangchainToolSet({ apiKey: "<your-composio-api-key>" });
const tools = await toolset.getTools({ actions: ["FILETOOL_EDIT_FILE"] });
const agent = await createOpenAIFunctionsAgent({llm, tools, prompt});
const agentExecutor = new AgentExecutor({ agent, tools, verbose: true });
const response = await agentExecutor.invoke({ input: "your task description here" });
console.log(response);
Create file
Create file
Creates a new file or directory within a shell session
from langchain.agents import create_openai_functions_agent, AgentExecutor
from langchain import hub
from langchain_openai import ChatOpenAI
from composio_langchain import ComposioToolSet, Action, App
llm = ChatOpenAI()
prompt = hub.pull("hwchase17/openai-functions-agent")
composio_toolset = ComposioToolSet(api_key="")
tools = composio_toolset.get_tools(actions=['FILETOOL_CREATE_FILE'])
agent = create_openai_functions_agent(llm, tools, prompt)
agent_executor = AgentExecutor(agent=agent, tools=tools, verbose=True)
task = "your task description here"
result = agent_executor.invoke({"input": task})
print(result)
import { ChatOpenAI } from "@langchain/openai";
import { createOpenAIFunctionsAgent, AgentExecutor } from "langchain/agents";
import { LangchainToolSet } from "composio-core";
import { pull } from "langchain/hub";
const llm = new ChatOpenAI({
model: "gpt-4-turbo",
temperature: 0,
});
const prompt = await pull("hwchase17/openai-functions-agent");
const toolset = new LangchainToolSet({ apiKey: "<your-composio-api-key>" });
const tools = await toolset.getTools({ actions: ["FILETOOL_CREATE_FILE"] });
const agent = await createOpenAIFunctionsAgent({llm, tools, prompt});
const agentExecutor = new AgentExecutor({ agent, tools, verbose: true });
const response = await agentExecutor.invoke({ input: "your task description here" });
console.log(response);
Scroll
Scroll
Scrolls the view of the opened file up or down by 100 lines
from langchain.agents import create_openai_functions_agent, AgentExecutor
from langchain import hub
from langchain_openai import ChatOpenAI
from composio_langchain import ComposioToolSet, Action, App
llm = ChatOpenAI()
prompt = hub.pull("hwchase17/openai-functions-agent")
composio_toolset = ComposioToolSet(api_key="")
tools = composio_toolset.get_tools(actions=['FILETOOL_SCROLL'])
agent = create_openai_functions_agent(llm, tools, prompt)
agent_executor = AgentExecutor(agent=agent, tools=tools, verbose=True)
task = "your task description here"
result = agent_executor.invoke({"input": task})
print(result)
import { ChatOpenAI } from "@langchain/openai";
import { createOpenAIFunctionsAgent, AgentExecutor } from "langchain/agents";
import { LangchainToolSet } from "composio-core";
import { pull } from "langchain/hub";
const llm = new ChatOpenAI({
model: "gpt-4-turbo",
temperature: 0,
});
const prompt = await pull("hwchase17/openai-functions-agent");
const toolset = new LangchainToolSet({ apiKey: "<your-composio-api-key>" });
const tools = await toolset.getTools({ actions: ["FILETOOL_SCROLL"] });
const agent = await createOpenAIFunctionsAgent({llm, tools, prompt});
const agentExecutor = new AgentExecutor({ agent, tools, verbose: true });
const response = await agentExecutor.invoke({ input: "your task description here" });
console.log(response);
Scroll
Scroll
Scrolls the view of the opened file up or down by 100 lines
from langchain.agents import create_openai_functions_agent, AgentExecutor
from langchain import hub
from langchain_openai import ChatOpenAI
from composio_langchain import ComposioToolSet, Action, App
llm = ChatOpenAI()
prompt = hub.pull("hwchase17/openai-functions-agent")
composio_toolset = ComposioToolSet(api_key="")
tools = composio_toolset.get_tools(actions=['FILETOOL_SCROLL'])
agent = create_openai_functions_agent(llm, tools, prompt)
agent_executor = AgentExecutor(agent=agent, tools=tools, verbose=True)
task = "your task description here"
result = agent_executor.invoke({"input": task})
print(result)
import { ChatOpenAI } from "@langchain/openai";
import { createOpenAIFunctionsAgent, AgentExecutor } from "langchain/agents";
import { LangchainToolSet } from "composio-core";
import { pull } from "langchain/hub";
const llm = new ChatOpenAI({
model: "gpt-4-turbo",
temperature: 0,
});
const prompt = await pull("hwchase17/openai-functions-agent");
const toolset = new LangchainToolSet({ apiKey: "<your-composio-api-key>" });
const tools = await toolset.getTools({ actions: ["FILETOOL_SCROLL"] });
const agent = await createOpenAIFunctionsAgent({llm, tools, prompt});
const agentExecutor = new AgentExecutor({ agent, tools, verbose: true });
const response = await agentExecutor.invoke({ input: "your task description here" });
console.log(response);
List files
List files
Lists files and directories in the current working directory
from langchain.agents import create_openai_functions_agent, AgentExecutor
from langchain import hub
from langchain_openai import ChatOpenAI
from composio_langchain import ComposioToolSet, Action, App
llm = ChatOpenAI()
prompt = hub.pull("hwchase17/openai-functions-agent")
composio_toolset = ComposioToolSet(api_key="")
tools = composio_toolset.get_tools(actions=['FILETOOL_LIST_FILES'])
agent = create_openai_functions_agent(llm, tools, prompt)
agent_executor = AgentExecutor(agent=agent, tools=tools, verbose=True)
task = "your task description here"
result = agent_executor.invoke({"input": task})
print(result)
import { ChatOpenAI } from "@langchain/openai";
import { createOpenAIFunctionsAgent, AgentExecutor } from "langchain/agents";
import { LangchainToolSet } from "composio-core";
import { pull } from "langchain/hub";
const llm = new ChatOpenAI({
model: "gpt-4-turbo",
temperature: 0,
});
const prompt = await pull("hwchase17/openai-functions-agent");
const toolset = new LangchainToolSet({ apiKey: "<your-composio-api-key>" });
const tools = await toolset.getTools({ actions: ["FILETOOL_LIST_FILES"] });
const agent = await createOpenAIFunctionsAgent({llm, tools, prompt});
const agentExecutor = new AgentExecutor({ agent, tools, verbose: true });
const response = await agentExecutor.invoke({ input: "your task description here" });
console.log(response);
Search word
Search word
Search for a specific word or phrase across multiple files in your workspace by specifying a pattern
from langchain.agents import create_openai_functions_agent, AgentExecutor
from langchain import hub
from langchain_openai import ChatOpenAI
from composio_langchain import ComposioToolSet, Action, App
llm = ChatOpenAI()
prompt = hub.pull("hwchase17/openai-functions-agent")
composio_toolset = ComposioToolSet(api_key="")
tools = composio_toolset.get_tools(actions=['FILETOOL_SEARCH_WORD'])
agent = create_openai_functions_agent(llm, tools, prompt)
agent_executor = AgentExecutor(agent=agent, tools=tools, verbose=True)
task = "your task description here"
result = agent_executor.invoke({"input": task})
print(result)
import { ChatOpenAI } from "@langchain/openai";
import { createOpenAIFunctionsAgent, AgentExecutor } from "langchain/agents";
import { LangchainToolSet } from "composio-core";
import { pull } from "langchain/hub";
const llm = new ChatOpenAI({
model: "gpt-4-turbo",
temperature: 0,
});
const prompt = await pull("hwchase17/openai-functions-agent");
const toolset = new LangchainToolSet({ apiKey: "<your-composio-api-key>" });
const tools = await toolset.getTools({ actions: ["FILETOOL_SEARCH_WORD"] });
const agent = await createOpenAIFunctionsAgent({llm, tools, prompt});
const agentExecutor = new AgentExecutor({ agent, tools, verbose: true });
const response = await agentExecutor.invoke({ input: "your task description here" });
console.log(response);
Find file
Find file
Finds files or directories matching the given pattern in the workspace
from langchain.agents import create_openai_functions_agent, AgentExecutor
from langchain import hub
from langchain_openai import ChatOpenAI
from composio_langchain import ComposioToolSet, Action, App
llm = ChatOpenAI()
prompt = hub.pull("hwchase17/openai-functions-agent")
composio_toolset = ComposioToolSet(api_key="")
tools = composio_toolset.get_tools(actions=['FILETOOL_FIND_FILE'])
agent = create_openai_functions_agent(llm, tools, prompt)
agent_executor = AgentExecutor(agent=agent, tools=tools, verbose=True)
task = "your task description here"
result = agent_executor.invoke({"input": task})
print(result)
import { ChatOpenAI } from "@langchain/openai";
import { createOpenAIFunctionsAgent, AgentExecutor } from "langchain/agents";
import { LangchainToolSet } from "composio-core";
import { pull } from "langchain/hub";
const llm = new ChatOpenAI({
model: "gpt-4-turbo",
temperature: 0,
});
const prompt = await pull("hwchase17/openai-functions-agent");
const toolset = new LangchainToolSet({ apiKey: "<your-composio-api-key>" });
const tools = await toolset.getTools({ actions: ["FILETOOL_FIND_FILE"] });
const agent = await createOpenAIFunctionsAgent({llm, tools, prompt});
const agentExecutor = new AgentExecutor({ agent, tools, verbose: true });
const response = await agentExecutor.invoke({ input: "your task description here" });
console.log(response);
Write
Write
Write the given content to a file
from langchain.agents import create_openai_functions_agent, AgentExecutor
from langchain import hub
from langchain_openai import ChatOpenAI
from composio_langchain import ComposioToolSet, Action, App
llm = ChatOpenAI()
prompt = hub.pull("hwchase17/openai-functions-agent")
composio_toolset = ComposioToolSet(api_key="")
tools = composio_toolset.get_tools(actions=['FILETOOL_WRITE'])
agent = create_openai_functions_agent(llm, tools, prompt)
agent_executor = AgentExecutor(agent=agent, tools=tools, verbose=True)
task = "your task description here"
result = agent_executor.invoke({"input": task})
print(result)
import { ChatOpenAI } from "@langchain/openai";
import { createOpenAIFunctionsAgent, AgentExecutor } from "langchain/agents";
import { LangchainToolSet } from "composio-core";
import { pull } from "langchain/hub";
const llm = new ChatOpenAI({
model: "gpt-4-turbo",
temperature: 0,
});
const prompt = await pull("hwchase17/openai-functions-agent");
const toolset = new LangchainToolSet({ apiKey: "<your-composio-api-key>" });
const tools = await toolset.getTools({ actions: ["FILETOOL_WRITE"] });
const agent = await createOpenAIFunctionsAgent({llm, tools, prompt});
const agentExecutor = new AgentExecutor({ agent, tools, verbose: true });
const response = await agentExecutor.invoke({ input: "your task description here" });
console.log(response);
Change working directory
Change working directory
Changes the current working directory of the file manager to the specified path
from langchain.agents import create_openai_functions_agent, AgentExecutor
from langchain import hub
from langchain_openai import ChatOpenAI
from composio_langchain import ComposioToolSet, Action, App
llm = ChatOpenAI()
prompt = hub.pull("hwchase17/openai-functions-agent")
composio_toolset = ComposioToolSet(api_key="")
tools = composio_toolset.get_tools(actions=['FILETOOL_CHANGE_WORKING_DIRECTORY'])
agent = create_openai_functions_agent(llm, tools, prompt)
agent_executor = AgentExecutor(agent=agent, tools=tools, verbose=True)
task = "your task description here"
result = agent_executor.invoke({"input": task})
print(result)
import { ChatOpenAI } from "@langchain/openai";
import { createOpenAIFunctionsAgent, AgentExecutor } from "langchain/agents";
import { LangchainToolSet } from "composio-core";
import { pull } from "langchain/hub";
const llm = new ChatOpenAI({
model: "gpt-4-turbo",
temperature: 0,
});
const prompt = await pull("hwchase17/openai-functions-agent");
const toolset = new LangchainToolSet({ apiKey: "<your-composio-api-key>" });
const tools = await toolset.getTools({ actions: ["FILETOOL_CHANGE_WORKING_DIRECTORY"] });
const agent = await createOpenAIFunctionsAgent({llm, tools, prompt});
const agentExecutor = new AgentExecutor({ agent, tools, verbose: true });
const response = await agentExecutor.invoke({ input: "your task description here" });
console.log(response);
Git clone
Git clone
This action allows you to clone a Git repository to your local directory
from langchain.agents import create_openai_functions_agent, AgentExecutor
from langchain import hub
from langchain_openai import ChatOpenAI
from composio_langchain import ComposioToolSet, Action, App
llm = ChatOpenAI()
prompt = hub.pull("hwchase17/openai-functions-agent")
composio_toolset = ComposioToolSet(api_key="")
tools = composio_toolset.get_tools(actions=['FILETOOL_GIT_CLONE'])
agent = create_openai_functions_agent(llm, tools, prompt)
agent_executor = AgentExecutor(agent=agent, tools=tools, verbose=True)
task = "your task description here"
result = agent_executor.invoke({"input": task})
print(result)
import { ChatOpenAI } from "@langchain/openai";
import { createOpenAIFunctionsAgent, AgentExecutor } from "langchain/agents";
import { LangchainToolSet } from "composio-core";
import { pull } from "langchain/hub";
const llm = new ChatOpenAI({
model: "gpt-4-turbo",
temperature: 0,
});
const prompt = await pull("hwchase17/openai-functions-agent");
const toolset = new LangchainToolSet({ apiKey: "<your-composio-api-key>" });
const tools = await toolset.getTools({ actions: ["FILETOOL_GIT_CLONE"] });
const agent = await createOpenAIFunctionsAgent({llm, tools, prompt});
const agentExecutor = new AgentExecutor({ agent, tools, verbose: true });
const response = await agentExecutor.invoke({ input: "your task description here" });
console.log(response);
Git repo tree
Git repo tree
Creates a tree representation of the Git repository
from langchain.agents import create_openai_functions_agent, AgentExecutor
from langchain import hub
from langchain_openai import ChatOpenAI
from composio_langchain import ComposioToolSet, Action, App
llm = ChatOpenAI()
prompt = hub.pull("hwchase17/openai-functions-agent")
composio_toolset = ComposioToolSet(api_key="")
tools = composio_toolset.get_tools(actions=['FILETOOL_GIT_REPO_TREE'])
agent = create_openai_functions_agent(llm, tools, prompt)
agent_executor = AgentExecutor(agent=agent, tools=tools, verbose=True)
task = "your task description here"
result = agent_executor.invoke({"input": task})
print(result)
import { ChatOpenAI } from "@langchain/openai";
import { createOpenAIFunctionsAgent, AgentExecutor } from "langchain/agents";
import { LangchainToolSet } from "composio-core";
import { pull } from "langchain/hub";
const llm = new ChatOpenAI({
model: "gpt-4-turbo",
temperature: 0,
});
const prompt = await pull("hwchase17/openai-functions-agent");
const toolset = new LangchainToolSet({ apiKey: "<your-composio-api-key>" });
const tools = await toolset.getTools({ actions: ["FILETOOL_GIT_REPO_TREE"] });
const agent = await createOpenAIFunctionsAgent({llm, tools, prompt});
const agentExecutor = new AgentExecutor({ agent, tools, verbose: true });
const response = await agentExecutor.invoke({ input: "your task description here" });
console.log(response);
Get Git Patch
Get Git Patch
Get the patch from the current working directory
from langchain.agents import create_openai_functions_agent, AgentExecutor
from langchain import hub
from langchain_openai import ChatOpenAI
from composio_langchain import ComposioToolSet, Action, App
llm = ChatOpenAI()
prompt = hub.pull("hwchase17/openai-functions-agent")
composio_toolset = ComposioToolSet(api_key="")
tools = composio_toolset.get_tools(actions=['FILETOOL_GIT_PATCH'])
agent = create_openai_functions_agent(llm, tools, prompt)
agent_executor = AgentExecutor(agent=agent, tools=tools, verbose=True)
task = "your task description here"
result = agent_executor.invoke({"input": task})
print(result)
import { ChatOpenAI } from "@langchain/openai";
import { createOpenAIFunctionsAgent, AgentExecutor } from "langchain/agents";
import { LangchainToolSet } from "composio-core";
import { pull } from "langchain/hub";
const llm = new ChatOpenAI({
model: "gpt-4-turbo",
temperature: 0,
});
const prompt = await pull("hwchase17/openai-functions-agent");
const toolset = new LangchainToolSet({ apiKey: "<your-composio-api-key>" });
const tools = await toolset.getTools({ actions: ["FILETOOL_GIT_PATCH"] });
const agent = await createOpenAIFunctionsAgent({llm, tools, prompt});
const agentExecutor = new AgentExecutor({ agent, tools, verbose: true });
const response = await agentExecutor.invoke({ input: "your task description here" });
console.log(response);
Code Analysis Tool
Create index
Create index
Use this to create a code map for a repository by indexing and analyzing its contents
from langchain.agents import create_openai_functions_agent, AgentExecutor
from langchain import hub
from langchain_openai import ChatOpenAI
from composio_langchain import ComposioToolSet, Action, App
llm = ChatOpenAI()
prompt = hub.pull("hwchase17/openai-functions-agent")
composio_toolset = ComposioToolSet(api_key="")
tools = composio_toolset.get_tools(actions=['CODE_ANALYSIS_TOOL_CREATE_CODE_MAP'])
agent = create_openai_functions_agent(llm, tools, prompt)
agent_executor = AgentExecutor(agent=agent, tools=tools, verbose=True)
task = "your task description here"
result = agent_executor.invoke({"input": task})
print(result)
import { ChatOpenAI } from "@langchain/openai";
import { createOpenAIFunctionsAgent, AgentExecutor } from "langchain/agents";
import { LangchainToolSet } from "composio-core";
import { pull } from "langchain/hub";
const llm = new ChatOpenAI({
model: "gpt-4-turbo",
temperature: 0,
});
const prompt = await pull("hwchase17/openai-functions-agent");
const toolset = new LangchainToolSet({ apiKey: "<your-composio-api-key>" });
const tools = await toolset.getTools({ actions: ["CODE_ANALYSIS_TOOL_CREATE_CODE_MAP"] });
const agent = await createOpenAIFunctionsAgent({llm, tools, prompt});
const agentExecutor = new AgentExecutor({ agent, tools, verbose: true });
const response = await agentExecutor.invoke({ input: "your task description here" });
console.log(response);
Get Class Info
Get Class Info
This tool retrieves and formats detailed information about a specified class in a given repository
from langchain.agents import create_openai_functions_agent, AgentExecutor
from langchain import hub
from langchain_openai import ChatOpenAI
from composio_langchain import ComposioToolSet, Action, App
llm = ChatOpenAI()
prompt = hub.pull("hwchase17/openai-functions-agent")
composio_toolset = ComposioToolSet(api_key="")
tools = composio_toolset.get_tools(actions=['CODE_ANALYSIS_TOOL_GET_CLASS_INFO'])
agent = create_openai_functions_agent(llm, tools, prompt)
agent_executor = AgentExecutor(agent=agent, tools=tools, verbose=True)
task = "your task description here"
result = agent_executor.invoke({"input": task})
print(result)
import { ChatOpenAI } from "@langchain/openai";
import { createOpenAIFunctionsAgent, AgentExecutor } from "langchain/agents";
import { LangchainToolSet } from "composio-core";
import { pull } from "langchain/hub";
const llm = new ChatOpenAI({
model: "gpt-4-turbo",
temperature: 0,
});
const prompt = await pull("hwchase17/openai-functions-agent");
const toolset = new LangchainToolSet({ apiKey: "<your-api-key>" });
const tools = await toolset.getTools({ actions: ["CODE_ANALYSIS_TOOL_GET_CLASS_INFO"] });
const agent = await createOpenAIFunctionsAgent({llm, tools, prompt});
const agentExecutor = new AgentExecutor({ agent, tools, verbose: true });
const response = await agentExecutor.invoke({ input: "your task description here" });
console.log(response);
Get Method Body
Get Method Body
This tool retrieves the body of a specified method from a given repository
from langchain.agents import create_openai_functions_agent, AgentExecutor
from langchain import hub
from langchain_openai import ChatOpenAI
from composio_langchain import ComposioToolSet, Action, App
llm = ChatOpenAI()
prompt = hub.pull("hwchase17/openai-functions-agent")
composio_toolset = ComposioToolSet(api_key="")
tools = composio_toolset.get_tools(actions=['CODE_ANALYSIS_TOOL_GET_METHOD_BODY'])
agent = create_openai_functions_agent(llm, tools, prompt)
agent_executor = AgentExecutor(agent=agent, tools=tools, verbose=True)
task = "your task description here"
result = agent_executor.invoke({"input": task})
print(result)
import { ChatOpenAI } from "@langchain/openai";
import { createOpenAIFunctionsAgent, AgentExecutor } from "langchain/agents";
import { LangchainToolSet } from "composio-core";
import { pull } from "langchain/hub";
const llm = new ChatOpenAI({
model: "gpt-4-turbo",
temperature: 0,
});
const prompt = await pull("hwchase17/openai-functions-agent");
const toolset = new LangchainToolSet({ apiKey: "<your-composio-api-key>" });
const tools = await toolset.getTools({ actions: ["CODE_ANALYSIS_TOOL_GET_METHOD_BODY"] });
const agent = await createOpenAIFunctionsAgent({llm, tools, prompt});
const agentExecutor = new AgentExecutor({ agent, tools, verbose: true });
const response = await agentExecutor.invoke({ input: "your task description here" });
console.log(response);
Get Method Signature
Get Method Signature
This tool retrieves the signature of a specified method from a given repository.
from langchain.agents import create_openai_functions_agent, AgentExecutor
from langchain import hub
from langchain_openai import ChatOpenAI
from composio_langchain import ComposioToolSet, Action, App
llm = ChatOpenAI()
prompt = hub.pull("hwchase17/openai-functions-agent")
composio_toolset = ComposioToolSet(api_key="")
tools = composio_toolset.get_tools(actions=['CODE_ANALYSIS_TOOL_GET_METHOD_SIGNATURE'])
agent = create_openai_functions_agent(llm, tools, prompt)
agent_executor = AgentExecutor(agent=agent, tools=tools, verbose=True)
task = "your task description here"
result = agent_executor.invoke({"input": task})
print(result)
import { ChatOpenAI } from "@langchain/openai";
import { createOpenAIFunctionsAgent, AgentExecutor } from "langchain/agents";
import { LangchainToolSet } from "composio-core";
import { pull } from "langchain/hub";
const llm = new ChatOpenAI({
model: "gpt-4-turbo",
temperature: 0,
});
const prompt = await pull("hwchase17/openai-functions-agent");
const toolset = new LangchainToolSet({ apiKey: "<your-composio-api-key>" });
const tools = await toolset.getTools({ actions: ["CODE_ANALYSIS_TOOL_GET_METHOD_SIGNATURE"] });
const agent = await createOpenAIFunctionsAgent({llm, tools, prompt});
const agentExecutor = new AgentExecutor({ agent, tools, verbose: true });
const response = await agentExecutor.invoke({ input: "your task description here" });
console.log(response);
Get Relevant Code
Get Relevant Code
Retrieves relevant code snippets from a repository based on a given query
from langchain.agents import create_openai_functions_agent, AgentExecutor
from langchain import hub
from langchain_openai import ChatOpenAI
from composio_langchain import ComposioToolSet, Action, App
llm = ChatOpenAI()
prompt = hub.pull("hwchase17/openai-functions-agent")
composio_toolset = ComposioToolSet(api_key="")
tools = composio_toolset.get_tools(actions=['CODE_ANALYSIS_TOOL_GET_RELEVANT_CODE'])
agent = create_openai_functions_agent(llm, tools, prompt)
agent_executor = AgentExecutor(agent=agent, tools=tools, verbose=True)
task = "your task description here"
result = agent_executor.invoke({"input": task})
print(result)
import { ChatOpenAI } from "@langchain/openai";
import { createOpenAIFunctionsAgent, AgentExecutor } from "langchain/agents";
import { LangchainToolSet } from "composio-core";
import { pull } from "langchain/hub";
const llm = new ChatOpenAI({
model: "gpt-4-turbo",
temperature: 0,
});
const prompt = await pull("hwchase17/openai-functions-agent");
const toolset = new LangchainToolSet({ apiKey: "<your-composio-api-key>" });
const tools = await toolset.getTools({ actions: ["CODE_ANALYSIS_TOOL_GET_RELEVANT_CODE"] });
const agent = await createOpenAIFunctionsAgent({llm, tools, prompt});
const agentExecutor = new AgentExecutor({ agent, tools, verbose: true });
const response = await agentExecutor.invoke({ input: "your task description here" });
console.log(response);
Shell Tool
Exec command
Exec command
Run any command directly on shell
from langchain.agents import create_openai_functions_agent, AgentExecutor
from langchain import hub
from langchain_openai import ChatOpenAI
from composio_langchain import ComposioToolSet, Action, App
llm = ChatOpenAI()
prompt = hub.pull("hwchase17/openai-functions-agent")
composio_toolset = ComposioToolSet(api_key="")
tools = composio_toolset.get_tools(actions=['SHELLTOOL_EXEC_COMMAND'])
agent = create_openai_functions_agent(llm, tools, prompt)
agent_executor = AgentExecutor(agent=agent, tools=tools, verbose=True)
task = "your task description here"
result = agent_executor.invoke({"input": task})
print(result)
import { ChatOpenAI } from "@langchain/openai";
import { createOpenAIFunctionsAgent, AgentExecutor } from "langchain/agents";
import { LangchainToolSet } from "composio-core";
import { pull } from "langchain/hub";
const llm = new ChatOpenAI({
model: "gpt-4-turbo",
temperature: 0,
});
const prompt = await pull("hwchase17/openai-functions-agent");
const toolset = new LangchainToolSet({ apiKey: "<your-composio-api-key>" });
const tools = await toolset.getTools({ actions: ["SHELLTOOL_EXEC_COMMAND"] });
const agent = await createOpenAIFunctionsAgent({llm, tools, prompt});
const agentExecutor = new AgentExecutor({ agent, tools, verbose: true });
const response = await agentExecutor.invoke({ input: "your task description here" });
console.log(response);
Create shell
Create shell
Use this tool to create a new shell session
from langchain.agents import create_openai_functions_agent, AgentExecutor
from langchain import hub
from langchain_openai import ChatOpenAI
from composio_langchain import ComposioToolSet, Action, App
llm = ChatOpenAI()
prompt = hub.pull("hwchase17/openai-functions-agent")
composio_toolset = ComposioToolSet(api_key="")
tools = composio_toolset.get_tools(actions=['SHELLTOOL_CREATE_SHELL'])
agent = create_openai_functions_agent(llm, tools, prompt)
agent_executor = AgentExecutor(agent=agent, tools=tools, verbose=True)
task = "your task description here"
result = agent_executor.invoke({"input": task})
print(result)
import { ChatOpenAI } from "@langchain/openai";
import { createOpenAIFunctionsAgent, AgentExecutor } from "langchain/agents";
import { LangchainToolSet } from "composio-core";
import { pull } from "langchain/hub";
const llm = new ChatOpenAI({
model: "gpt-4-turbo",
temperature: 0,
});
const prompt = await pull("hwchase17/openai-functions-agent");
const toolset = new LangchainToolSet({ apiKey: "<your-composio-api-key>" });
const tools = await toolset.getTools({ actions: ["SHELLTOOL_CREATE_SHELL"] });
const agent = await createOpenAIFunctionsAgent({llm, tools, prompt});
const agentExecutor = new AgentExecutor({ agent, tools, verbose: true });
const response = await agentExecutor.invoke({ input: "your task description here" });
console.log(response);
Spawn process
Spawn process
Spawn a process
from langchain.agents import create_openai_functions_agent, AgentExecutor
from langchain import hub
from langchain_openai import ChatOpenAI
from composio_langchain import ComposioToolSet, Action, App
llm = ChatOpenAI()
prompt = hub.pull("hwchase17/openai-functions-agent")
composio_toolset = ComposioToolSet(api_key="")
tools = composio_toolset.get_tools(actions=['SHELLTOOL_SPAWN_PROCESS'])
agent = create_openai_functions_agent(llm, tools, prompt)
agent_executor = AgentExecutor(agent=agent, tools=tools, verbose=True)
task = "your task description here"
result = agent_executor.invoke({"input": task})
print(result)
import { ChatOpenAI } from "@langchain/openai";
import { createOpenAIFunctionsAgent, AgentExecutor } from "langchain/agents";
import { LangchainToolSet } from "composio-core";
import { pull } from "langchain/hub";
const llm = new ChatOpenAI({
model: "gpt-4-turbo",
temperature: 0,
});
const prompt = await pull("hwchase17/openai-functions-agent");
const toolset = new LangchainToolSet({ apiKey: "<your-composio-api-key>" });
const tools = await toolset.getTools({ actions: ["SHELLTOOL_SPAWN_PROCESS"] });
const agent = await createOpenAIFunctionsAgent({llm, tools, prompt});
const agentExecutor = new AgentExecutor({ agent, tools, verbose: true });
const response = await agentExecutor.invoke({ input: "your task description here" });
console.log(response);
Test command
Test command
Run the command for testing the patch
from langchain.agents import create_openai_functions_agent, AgentExecutor
from langchain import hub
from langchain_openai import ChatOpenAI
from composio_langchain import ComposioToolSet, Action, App
llm = ChatOpenAI()
prompt = hub.pull("hwchase17/openai-functions-agent")
composio_toolset = ComposioToolSet(api_key="")
tools = composio_toolset.get_tools(actions=['SHELLTOOL_TEST_COMMAND'])
agent = create_openai_functions_agent(llm, tools, prompt)
agent_executor = AgentExecutor(agent=agent, tools=tools, verbose=True)
task = "your task description here"
result = agent_executor.invoke({"input": task})
print(result)
import { ChatOpenAI } from "@langchain/openai";
import { createOpenAIFunctionsAgent, AgentExecutor } from "langchain/agents";
import { LangchainToolSet } from "composio-core";
import { pull } from "langchain/hub";
const llm = new ChatOpenAI({
model: "gpt-4-turbo",
temperature: 0,
});
const prompt = await pull("hwchase17/openai-functions-agent");
const toolset = new LangchainToolSet({ apiKey: "<your-composio-api-key>" });
const tools = await toolset.getTools({ actions: ["SHELLTOOL_TEST_COMMAND"] });
const agent = await createOpenAIFunctionsAgent({llm, tools, prompt});
const agentExecutor = new AgentExecutor({ agent, tools, verbose: true });
const response = await agentExecutor.invoke({ input: "your task description here" });
console.log(response);
RAG Tool
Add content to RAG
Add content to RAG
Tool for adding content to the knowledge base
from langchain.agents import create_openai_functions_agent, AgentExecutor
from langchain import hub
from langchain_openai import ChatOpenAI
from composio_langchain import ComposioToolSet, Action, App
llm = ChatOpenAI()
prompt = hub.pull("hwchase17/openai-functions-agent")
composio_toolset = ComposioToolSet(api_key="")
tools = composio_toolset.get_tools(actions=['RAGTOOL_ADD_CONTENT_TO_RAG_TOOL'])
agent = create_openai_functions_agent(llm, tools, prompt)
agent_executor = AgentExecutor(agent=agent, tools=tools, verbose=True)
task = "your task description here"
result = agent_executor.invoke({"input": task})
print(result)
import { ChatOpenAI } from "@langchain/openai";
import { createOpenAIFunctionsAgent, AgentExecutor } from "langchain/agents";
import { LangchainToolSet } from "composio-core";
import { pull } from "langchain/hub";
const llm = new ChatOpenAI({
model: "gpt-4-turbo",
temperature: 0,
});
const prompt = await pull("hwchase17/openai-functions-agent");
const toolset = new LangchainToolSet({ apiKey: "<your-composio-api-key>" });
const tools = await toolset.getTools({ actions: ["RAGTOOL_ADD_CONTENT_TO_RAG_TOOL"] });
const agent = await createOpenAIFunctionsAgent({llm, tools, prompt});
const agentExecutor = new AgentExecutor({ agent, tools, verbose: true });
const response = await agentExecutor.invoke({ input: "your task description here" });
console.log(response);
Query Knowledge Base
Query Knowledge Base
Tool for querying a knowledge base
from langchain.agents import create_openai_functions_agent, AgentExecutor
from langchain import hub
from langchain_openai import ChatOpenAI
from composio_langchain import ComposioToolSet, Action, App
llm = ChatOpenAI()
prompt = hub.pull("hwchase17/openai-functions-agent")
composio_toolset = ComposioToolSet(api_key="")
tools = composio_toolset.get_tools(actions=['RAGTOOL_ADD_CONTENT_TO_RAG_TOOL'])
agent = create_openai_functions_agent(llm, tools, prompt)
agent_executor = AgentExecutor(agent=agent, tools=tools, verbose=True)
task = "your task description here"
result = agent_executor.invoke({"input": task})
print(result)
import { ChatOpenAI } from "@langchain/openai";
import { createOpenAIFunctionsAgent, AgentExecutor } from "langchain/agents";
import { LangchainToolSet } from "composio-core";
import { pull } from "langchain/hub";
const llm = new ChatOpenAI({
model: "gpt-4-turbo",
temperature: 0,
});
const prompt = await pull("hwchase17/openai-functions-agent");
const toolset = new LangchainToolSet({ apiKey: "<your-composio-api-key>" });
const tools = await toolset.getTools({ actions: ["RAGTOOL_ADD_CONTENT_TO_RAG_TOOL"] });
const agent = await createOpenAIFunctionsAgent({llm, tools, prompt});
const agentExecutor = new AgentExecutor({ agent, tools, verbose: true });
const response = await agentExecutor.invoke({ input: "your task description here" });
console.log(response);
Embed Tool
Create Image Vector Store
Create Image Vector Store
Creates Vector Store for all image files in the specified folder
from langchain.agents import create_openai_functions_agent, AgentExecutor
from langchain import hub
from langchain_openai import ChatOpenAI
from composio_langchain import ComposioToolSet, Action, App
llm = ChatOpenAI()
prompt = hub.pull("hwchase17/openai-functions-agent")
composio_toolset = ComposioToolSet(api_key="")
tools = composio_toolset.get_tools(actions=['EMBED_TOOL_CREATE_IMAGE_VECTOR_STORE'])
agent = create_openai_functions_agent(llm, tools, prompt)
agent_executor = AgentExecutor(agent=agent, tools=tools, verbose=True)
task = "your task description here"
result = agent_executor.invoke({"input": task})
print(result)
import { ChatOpenAI } from "@langchain/openai";
import { createOpenAIFunctionsAgent, AgentExecutor } from "langchain/agents";
import { LangchainToolSet } from "composio-core";
import { pull } from "langchain/hub";
const llm = new ChatOpenAI({
model: "gpt-4-turbo",
temperature: 0,
});
const prompt = await pull("hwchase17/openai-functions-agent");
const toolset = new LangchainToolSet({ apiKey: "<your-composio-api-key>" });
const tools = await toolset.getTools({ actions: ["EMBED_TOOL_CREATE_IMAGE_VECTOR_STORE"] });
const agent = await createOpenAIFunctionsAgent({llm, tools, prompt});
const agentExecutor = new AgentExecutor({ agent, tools, verbose: true });
const response = await agentExecutor.invoke({ input: "your task description here" });
console.log(response);
Query Image Vector Store
Query Image Vector Store
Query Vector Store for images
from langchain.agents import create_openai_functions_agent, AgentExecutor
from langchain import hub
from langchain_openai import ChatOpenAI
from composio_langchain import ComposioToolSet, Action, App
llm = ChatOpenAI()
prompt = hub.pull("hwchase17/openai-functions-agent")
composio_toolset = ComposioToolSet(api_key="")
tools = composio_toolset.get_tools(actions=['EMBED_TOOL_QUERY_IMAGE_VECTOR_STORE'])
agent = create_openai_functions_agent(llm, tools, prompt)
agent_executor = AgentExecutor(agent=agent, tools=tools, verbose=True)
task = "your task description here"
result = agent_executor.invoke({"input": task})
print(result)
import { ChatOpenAI } from "@langchain/openai";
import { createOpenAIFunctionsAgent, AgentExecutor } from "langchain/agents";
import { LangchainToolSet } from "composio-core";
import { pull } from "langchain/hub";
const llm = new ChatOpenAI({
model: "gpt-4-turbo",
temperature: 0,
});
const prompt = await pull("hwchase17/openai-functions-agent");
const toolset = new LangchainToolSet({ apiKey: "<your-composio-api-key>" });
const tools = await toolset.getTools({ actions: ["EMBED_TOOL_QUERY_IMAGE_VECTOR_STORE"] });
const agent = await createOpenAIFunctionsAgent({llm, tools, prompt});
const agentExecutor = new AgentExecutor({ agent, tools, verbose: true });
const response = await agentExecutor.invoke({ input: "your task description here" });
console.log(response);
Other Useful Tools
SQL query
SQL query
Executes a SQL Query and returns the results
from langchain.agents import create_openai_functions_agent, AgentExecutor
from langchain import hub
from langchain_openai import ChatOpenAI
from composio_langchain import ComposioToolSet, Action, App
llm = ChatOpenAI()
prompt = hub.pull("hwchase17/openai-functions-agent")
composio_toolset = ComposioToolSet(api_key="")
tools = composio_toolset.get_tools(actions=['SQLTOOL_SQL_QUERY'])
agent = create_openai_functions_agent(llm, tools, prompt)
agent_executor = AgentExecutor(agent=agent, tools=tools, verbose=True)
task = "your task description here"
result = agent_executor.invoke({"input": task})
print(result)
import { ChatOpenAI } from "@langchain/openai";
import { createOpenAIFunctionsAgent, AgentExecutor } from "langchain/agents";
import { LangchainToolSet } from "composio-core";
import { pull } from "langchain/hub";
const llm = new ChatOpenAI({
model: "gpt-4-turbo",
temperature: 0,
});
const prompt = await pull("hwchase17/openai-functions-agent");
const toolset = new LangchainToolSet({ apiKey: "<your-composio-api-key>" });
const tools = await toolset.getTools({ actions: ["SQLTOOL_SQL_QUERY"] });
const agent = await createOpenAIFunctionsAgent({llm, tools, prompt});
const agentExecutor = new AgentExecutor({ agent, tools, verbose: true });
const response = await agentExecutor.invoke({ input: "your task description here" });
console.log(response);
Advanced Codebase Search
Advanced Codebase Search
Performs an advanced search across a codebase using regex patterns & optimized for large-scale software projects
from langchain.agents import create_openai_functions_agent, AgentExecutor
from langchain import hub
from langchain_openai import ChatOpenAI
from composio_langchain import ComposioToolSet, Action, App
llm = ChatOpenAI()
prompt = hub.pull("hwchase17/openai-functions-agent")
composio_toolset = ComposioToolSet(api_key="")
tools = composio_toolset.get_tools(actions=['CODE_GREP_TOOL_SEARCH_CODEBASE'])
agent = create_openai_functions_agent(llm, tools, prompt)
agent_executor = AgentExecutor(agent=agent, tools=tools, verbose=True)
task = "your task description here"
result = agent_executor.invoke({"input": task})
print(result)
import { ChatOpenAI } from "@langchain/openai";
import { createOpenAIFunctionsAgent, AgentExecutor } from "langchain/agents";
import { LangchainToolSet } from "composio-core";
import { pull } from "langchain/hub";
const llm = new ChatOpenAI({
model: "gpt-4-turbo",
temperature: 0,
});
const prompt = await pull("hwchase17/openai-functions-agent");
const toolset = new LangchainToolSet({ apiKey: "<your-composio-api-key>" });
const tools = await toolset.getTools({ actions: ["CODE_GREP_TOOL_SEARCH_CODEBASE"] });
const agent = await createOpenAIFunctionsAgent({llm, tools, prompt});
const agentExecutor = new AgentExecutor({ agent, tools, verbose: true });
const response = await agentExecutor.invoke({ input: "your task description here" });
console.log(response);
Format and Lint Codebase
Format and Lint Codebase
Performs code formatting and linting using ruff, addressing style issues and checking for errors
from langchain.agents import create_openai_functions_agent, AgentExecutor
from langchain import hub
from langchain_openai import ChatOpenAI
from composio_langchain import ComposioToolSet, Action, App
llm = ChatOpenAI()
prompt = hub.pull("hwchase17/openai-functions-agent")
composio_toolset = ComposioToolSet(api_key="")
tools = composio_toolset.get_tools(actions=['CODE_FORMAT_TOOL_FORMAT_AND_LINT_CODEBASE'])
agent = create_openai_functions_agent(llm, tools, prompt)
agent_executor = AgentExecutor(agent=agent, tools=tools, verbose=True)
task = "your task description here"
result = agent_executor.invoke({"input": task})
print(result)
import { ChatOpenAI } from "@langchain/openai";
import { createOpenAIFunctionsAgent, AgentExecutor } from "langchain/agents";
import { LangchainToolSet } from "composio-core";
import { pull } from "langchain/hub";
const llm = new ChatOpenAI({
model: "gpt-4-turbo",
temperature: 0,
});
const prompt = await pull("hwchase17/openai-functions-agent");
const toolset = new LangchainToolSet({ apiKey: "<your-composio-api-key>" });
const tools = await toolset.getTools({ actions: ["CODE_FORMAT_TOOL_FORMAT_AND_LINT_CODEBASE"] });
const agent = await createOpenAIFunctionsAgent({llm, tools, prompt});
const agentExecutor = new AgentExecutor({ agent, tools, verbose: true });
const response = await agentExecutor.invoke({ input: "your task description here" });
console.log(response);
Get workspace history
Get workspace history
Returns history for workspace which includes state of the environment, last executed n commands & output from last n commands
from langchain.agents import create_openai_functions_agent, AgentExecutor
from langchain import hub
from langchain_openai import ChatOpenAI
from composio_langchain import ComposioToolSet, Action, App
llm = ChatOpenAI()
prompt = hub.pull("hwchase17/openai-functions-agent")
composio_toolset = ComposioToolSet(api_key="")
tools = composio_toolset.get_tools(actions=['HISTORY_FETCHER_GET_WORKSPACE_HISTORY'])
agent = create_openai_functions_agent(llm, tools, prompt)
agent_executor = AgentExecutor(agent=agent, tools=tools, verbose=True)
task = "your task description here"
result = agent_executor.invoke({"input": task})
print(result)
import { ChatOpenAI } from "@langchain/openai";
import { createOpenAIFunctionsAgent, AgentExecutor } from "langchain/agents";
import { LangchainToolSet } from "composio-core";
import { pull } from "langchain/hub";
const llm = new ChatOpenAI({
model: "gpt-4-turbo",
temperature: 0,
});
const prompt = await pull("hwchase17/openai-functions-agent");
const toolset = new LangchainToolSet({ apiKey: "<your-composio-api-key>" });
const tools = await toolset.getTools({ actions: ["HISTORY_FETCHER_GET_WORKSPACE_HISTORY"] });
const agent = await createOpenAIFunctionsAgent({llm, tools, prompt});
const agentExecutor = new AgentExecutor({ agent, tools, verbose: true });
const response = await agentExecutor.invoke({ input: "your task description here" });
console.log(response);