October 3, 2024 - from langchain.agents import AgentExecutor, initialize_agent from langchain.memory import ConversationBufferMemory from langchain.tools import BaseTool, StructuredTool, tool from langchain.agents.agent_types import AgentType import subprocess @tool def generate_code(query: str)->str: "Generate codes for a given problem" result = llm("Write a code snippet in Python for the given Problem.

Join us May 13th & May 14th at Interrupt, the Agent Conference by LangChain. Buy tickets > ... Tools extend what agents can do—letting them fetch real-time data, execute code, query external databases, and take actions in the world. Under the hood, tools are callable functions with well-defined inputs and outputs that get passed to a chat model.

May 18, 2023 - I wanted to have something similar to Langchain Python REPL, but that instead: Allowed the generated source code to be saved in a file. Allowed the agent to install pip packages. Allowed execution of the source code, with the full output/traceback · Allowed linters to be applied and different code generations sampled accordingly. Offered the option to delegate the code generation completely to the tool, so the main agent does not have to be necessarily good at coding (though the model used in code still has to be good at coding).

March 1, 2024 - We implement LangSmith custom evaluators for both (1) import evaluation and (2) code execution. We run evaluation on context stuffing with our 20 question eval set four times. Here is our eval result. With context stuffing we see ~98% of the import tests are correct and ~55% of the code execution tests (N=79 successful trials).

1 week ago - An Open-Source Asynchronous Coding Agent. Contribute to langchain-ai/open-swe development by creating an account on GitHub.

This package provides an integrated tool for generating and executing C/C++ code snippets externally in Langchain. Allows Langchain users to specify the desired C++ standard version and set optional CPU time limits for code execution.

2 weeks ago - Spin up a sandbox in a single line of code with the LangSmith SDK. Now in Private Preview.

This project combines two functionalities: a Code Interpreter using LLM Agent Orchestration and Tool Utilization, and a ReAct LangChain Agent example. Engineered an autonomous multi-agent system by integrating Code Interpreter, ReAct, and LangChain frameworks, which streamlined dynamic code execution and reasoning, resulting in a 35% boost in operational efficiency.

May 29, 2025 - LangChain Sandbox lets you safely run untrusted Python in your AI agents! Built on Pyodide (Python in WebAssembly), LangChain Sandbox lets you execute code...

November 26, 2025 - Learn how to build LangChain agents that execute code safely in isolated sandboxes. Complete tutorial with custom tools, PythonREPL replacement, and production-ready patterns.

June 13, 2024 - Now we define the format_to_tool_messages function to identify for each agent's action whether it corresponds to a specific tool. If it does, the function formats the action and observation into messages and appends them to the messages list, ensuring no duplicates. We create a prompt template that will be used by the agent to generate responses. We define and invoke the agent, during which we specify the prompt, which is to plot and show sinus. from typing import List, Sequence, Tuple from langchain_core.prompts import ChatPromptTemplate from langchain.agents import AgentExecutor from langcha

July 16, 2023 - The core of this project is a LangChain Agent, specifically the new OpenAIFunctionsAgent which gives the advantage of calling functions/tools to better handle the user needs. For the code interpreter, we need to give it access to a Python interpreter so it can execute Python code.

November 13, 2025 - By Vivek Trivedy Today we're excited to launch Sandboxes for Deep Agents, a new set of integrations that allow you to safely execute arbitrary Deep Agent code in remote sandboxes.

1 week ago - import unittest def test_generated_code(code: str): exec_globals = {} exec(code, exec_globals) assert exec_globals['factorial'](5) == 120 if __name__ == "__main__": # Generate code and test it user_prompt = "Write a Python function to calculate the factorial of a number." generated_code = generate_code(user_prompt) test_generated_code(generated_code) API Key Issues: Ensure your OpenAI API key is correctly set in your environment variables. Installation Errors: Verify that you have installed the correct versions of LangChain and OpenAI libraries. Execution Errors: If the generated code fails, check the prompt for clarity and specificity.

January 14, 2026 - A secure environment for running Python code using Pyodide (WebAssembly) and Deno · LangChain Sandbox provides a secure environment for executing untrusted Python code.