# gkamradt/langchain-tutorials

Overview and tutorial of the LangChain Library

Repository: https://github.com/gkamradt/langchain-tutorials
Canonical: https://ross.abutalabs.com/products/langchain-tutorials
Language: Jupyter Notebook
License Family: other
Last push: 2024-08-05T09:18:46+00:00

## Health v2 (maintenance only)
Score: 31/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 0, release rhythm 35, longevity 92
- inputs: {"age_days": 1297, "days_push": 758, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases, no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 7484, forks 2016 (observed 2026-08-28T04:10:00.229105+00:00)

## What it is
A collection of Jupyter notebook tutorials and example projects teaching the LangChain library, including a two-part cookbook covering core concepts and use cases. It also curates a gallery of community-built LangChain projects organized by difficulty level.

## Use cases
- learn langchain from scratch
- langchain tutorial with code examples
- understand langchain core concepts
- find example langchain projects
- learn prompt engineering for llm apps
- build rag and document qa apps with langchain

## When to choose
- you are new to LangChain and want a guided learning path with notebooks and videos
- you want runnable example code for common LLM use cases like summarization and document Q&A
- you want curated real-world LangChain projects to study

## When to avoid
- you need up-to-date documentation for current LangChain APIs, as notebooks may lag behind library releases
- you want a production-ready framework rather than learning material
- you need a formally licensed codebase for reuse, since the repo has no license

## Facets
- artifact type: learning-resource
- maturity: maintenance
- function: llm-inference, rag, prompt-engineering, agent-framework
- domain: large-language-models, tutorials, artificial-intelligence
- platform: python, jvm-scripting
- tags: langchain, jupyter-notebooks, llm-tutorials, openai, example-projects, ai-agents

## Member repositories
- gkamradt/langchain-tutorials (main) score 31

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:10:00.229105+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-29T17:37:35.349209+00:00, confidence not recorded.
  - readme: https://github.com/gkamradt/langchain-tutorials (fetched 2026-08-28T04:10:00.229105+00:00, sha 0669acbb9c45)
- Data as of 2026-08-30T08:39:29.467469+00:00.