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Decision brief
langchain-tutorials offers educational material to aid in understanding and applying the LangChain library via Jupyter Notebooks.
Good fit when
- - When you're interested in hands-on learning through Jupyter Notebooks and want a structured approach to mastering LangChain with guided examples.
- - If you need beginner-friendly materials that transition into more complex use cases, as langchain-tutorials offers a recommended learning path from core concepts to advanced projects.
Avoid when
- - When you prefer video tutorials or written articles over interactive notebooks; although the repository links to supplementary videos and online resources, its primary medium is Jupyter Notebooks.
- - If your goal is immediate application without foundational knowledge, since langchain-tutorials emphasizes a learning path from basics up, which may add time before practical applications.
- Pricing:
- freemium - The repository is freely accessible with no stated fees; however, specific services or advanced features (if any) may require payment and aren't detailed in the provided data.
Observed Jul 12, 2026 · Source: enrich:decision_facts
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Maintenance and security
Full trust report- Maintenance
- Dormant (740d since push)
- As of 6d
- Provenance
- Not a fork · Personal account
- As of 6d
- Security (OSV)
- 174 low (174 low)
- As of 1mo
Public GitHub metadata and optional OSV scans. Signals, not a guarantee. Trust methodology.
Install
git clone https://github.com/gkamradt/langchain-tutorialsSimilar tools
Same-category neighbours. No typed graph edges are catalogued for this tool yet.
Evidence and technical details
Sourced facts, taxonomy, compatibility claims, README excerpt, and machine-readable endpoints.
Overview
Provides educational resources, tutorials, and examples for using the LangChain library through Jupyter Notebooks.
Capability facts
- Languages
- jupyter notebook
Source: github.language · Aug 15, 2026
Categories
Compatibility
Sourced claims from the README excerpt - not unsourced marketing copy.
Source: README excerpt (regex_v1, Aug 15, 2026)
# Learn LangChainSource link
Source: README excerpt (regex_v1, Aug 15, 2026)
2. [ChatGPT Prompt Engineering for Developers](https://www.deeplearning.ai/short-courses/chSource link
Tags
README
Learn LangChain
Overview, Tutorial, and Examples of LangChain
See the accompanying tutorials on YouTube
If you want to get updated when new tutorials are out, get them delivered to your inbox
If you're new to Jupyter Notebooks or Colab, check out this video
New To LangChain?
Recommended Learning Path:
- LangChain CookBook Part 1: 7 Core Concepts - Code, Video
- LangChain CookBook Part 2: 9 Use Cases - Code, Video
- Explore the projects below and jump into the deep dives
Prompt Engineering (my favorite resources):
- Prompt Engineering Overview by Elvis Saravia
- ChatGPT Prompt Engineering for Developers - Prompt engineering basics straight from OpenAI
- Brex's Prompt Engineering Guide
🤖 Project Gallery
🐇 Beginner = Entry level projects to practice LangChain
🐒 Intermediate = In depth use of LangChain
🦈 Advanced = Advanced or custom implementations of LangChain
📝 Summarization - Deep Dive: Code, Video
| Project | Contact | Difficulty | Open Sourced? | Notes |
|---|---|---|---|---|
| SummarizePaper.com | Quentin Kral | 🐒 Intermediate | ✅ Code | Summarize arXiv papers |
❓ Question and Answering Over Documents
| Project | Contact | Difficulty | Open Sourced? | Notes |
|---|---|---|---|---|
| ChatPDF | Ashish Talati | 🐒 Intermediate | ✅ Code | Chat and Ask on your own data |
📦 Extraction
| Project | Contact | Difficulty | Open Sourced? | Notes |
|---|---|---|---|---|
| Kor | Eugene Yurtsev | 🐒 Intermediate | ✅ Code | This is a half-baked prototype that “helps” you extract structured data from text using large language models (LLMs) 🧩. |
| OpeningAttributes | @gregkamradt | 🐇 Beginner | ✅ Code | Extract technologies & tools from job descriptions |
🔍 Evaluation
| Project | Contact | Difficulty | Open Sourced? | Notes |
|---|---|---|---|---|
| Auto-Evaluator | @RLanceMartin | 🦈 Advanced | ✅ Code | Evaluate Q&A Chains |
📊 Querying Tabular Data
| Project | Contact | Difficulty | Open Sourced? | Notes |
|---|---|---|---|---|
| TBD |
💻 Code Understanding
| Project | Contact | Difficulty | Open Sou
For agents
This page has a .md twin and JSON over the API.