Home/LLM Frameworks/codespaces-langchain
codespaces-langchain logo

codespaces-langchain

lostintangent/codespaces-langchain

A Codespaces template for getting up-and-running with LangChain in seconds

GraphCanon updated today · GitHub synced today

113
Stars
22
Forks
5
Open issues
2
Watchers
3y
Last push
Created Jan 19, 2023

Trust & integrity

Full report
Maintenance
Dormant (1206d since push)
As of today · Source: github_public_v1
Provenance
Not a fork · Personal account
As of today · Source: github_public_v1
Security (OSV)
No criticals
As of today · Source: osv@v1

Public GitHub metadata and optional OSV dependency scans. Signals, not a guarantee. Trust methodology.

Overview

This repository provides a streamlined setup process for using LangChain within GitHub's Codespaces environment, enabling quick access to language model functionalities via the OpenAI API.

Capability facts

No sourced capability facts yet. Facts appear after ingest scans repo manifests (Dockerfile, package.json, MCP configs).

Categories

Compatibility

Sourced claims from the README excerpt - not unsourced marketing copy.

LangChain integrationLangChain

Source: README excerpt (regex_v1, Jul 11, 2026)

an account with [OpenAI](https://openai.com/api/), and generate an API key that LangChain can use. Once you have that, create a new [Codespaces repo secret](https://docs
Source link

Tags

README

Getting Started

  1. Create a repo from this template, by clicking the green Use this template button, and selecting Create a new repository. Name the repo whatever you'd like 👍

    Badge image
  2. In order to interact with GPT-3, you'll need to create an account with OpenAI, and generate an API key that LangChain can use. Once you have that, create a new Codespaces repo secret named OPENAI_API_KEY, and set it to the value of your API key.

  3. Open your new repo in a Codespace by clicking the green Code button on the repo's homepage, and selecting Create codespace on main

    Badge image
  4. Once you're within the web editor, simply open any of the notebooks within the /examples folder, and select Run All in the notebook's toolbar. From there, you can change any of the prompts and/or code, and then re-run the cell/notebook, in order to get a better intuition for how LangChain can help you build your own custom chains 🚀

Optionally, if you'd like to explore the sample that automates Google search qierues, create an account with SerpAPI, generate an API key, and set it as a Codespaces secret called SERPAPI_API_KEY.