{"data":{"slug":"gkamradt-langchain-tutorials","name":"langchain-tutorials","tagline":"Overview and tutorial of the LangChain Library","github_url":"https://github.com/gkamradt/langchain-tutorials","owner":"gkamradt","repo":"langchain-tutorials","owner_avatar_url":"https://avatars.githubusercontent.com/u/9809213?v=4","primary_language":"Jupyter Notebook","stars":7480,"forks":2013,"topics":[],"archived":false,"github_pushed_at":"2024-08-05T09:18:46+00:00","maintenance_label":"Dormant","stars_delta_30d":10,"url":"https://www.graphcanon.com/tools/gkamradt-langchain-tutorials","markdown_url":"https://www.graphcanon.com/tools/gkamradt-langchain-tutorials.md","api_url":"https://www.graphcanon.com/api/graphcanon/tools/gkamradt-langchain-tutorials","graph_url":"https://www.graphcanon.com/api/graphcanon/graph?tool=gkamradt-langchain-tutorials","description":"Overview and tutorial of the LangChain Library","homepage_url":null,"license":null,"open_issues":15,"watchers":117,"ai_summary":"Provides educational resources, tutorials, and examples for using the LangChain library through Jupyter Notebooks.","readme_excerpt":"# Learn LangChain\n\nOverview, Tutorial, and Examples of [LangChain](https://langchain.readthedocs.io/en/latest/)\n\nSee the accompanying tutorials on [YouTube](https://www.youtube.com/channel/UCyR2Ct3pDOeZSRyZH5hPO-Q)\n\nIf you want to get updated when new tutorials are out, get them [delivered to your inbox](https://prodigious-knitter-7293.ck.page/3bd9b7cea6)\n\nIf you're new to Jupyter Notebooks or Colab, check out [this video](https://www.youtube.com/watch?v=HW29067qVWk)\n\n### **New To LangChain?**\nRecommended Learning Path:\n1. LangChain CookBook Part 1: 7 Core Concepts - [Code](https://github.com/gkamradt/langchain-tutorials/blob/main/LangChain%20Cookbook%20Part%201%20-%20Fundamentals.ipynb), [Video](https://youtu.be/2xxziIWmaSA)\n2. LangChain CookBook Part 2: 9 Use Cases - [Code](https://github.com/gkamradt/langchain-tutorials/blob/main/LangChain%20Cookbook%20Part%202%20-%20Use%20Cases.ipynb), [Video](https://youtu.be/vGP4pQdCocw)\n3. Explore the projects below and jump into the deep dives\n\nPrompt Engineering (my favorite resources):\n1. [Prompt Engineering Overview](https://www.youtube.com/watch?v=dOxUroR57xs) by [Elvis Saravia](https://twitter.com/omarsar0)\n2. [ChatGPT Prompt Engineering for Developers](https://www.deeplearning.ai/short-courses/chatgpt-prompt-engineering-for-developers/) - Prompt engineering basics straight from OpenAI\n3. [Brex's Prompt Engineering Guide](https://github.com/brexhq/prompt-engineering)\n\n## π€ **Project Gallery**\n\nπ Beginner = Entry level projects to practice LangChain\n\nπ Intermediate = In depth use of LangChain\n\nπ¦ Advanced = Advanced or custom implementations of LangChain\n\n### **π Summarization** - *Deep Dive: [Code](https://github.com/gkamradt/langchain-tutorials/blob/main/data_generation/5%20Levels%20Of%20Summarization%20-%20Novice%20To%20Expert.ipynb), [Video](https://youtu.be/qaPMdcCqtWk)*\n| Project | Contact | Difficulty | Open Sourced? | Notes | \n| - | ----------- | ---------- | :-: | ---------- |\n| [SummarizePaper.com](https://www.summarizepaper.com/) | Quentin Kral | π Intermediate | β
[Code](https://github.com/summarizepaper/summarizepaper) | Summarize arXiv papers | \n\n
\n\n### β Question and Answering Over Documents\n| Project | Contact | Difficulty | Open Sourced? | Notes | \n| ----------- | ----------- | ---------- | :-: | ---------- |\n| [ChatPDF](https://github.com/akshata29/chatpdf) | [Ashish Talati](https://github.com/akshata29) | π Intermediate | β
[Code](https://github.com/akshata29/chatpdf) | Chat and Ask on your own data | \n\n
\n\n### **π¦ Extraction**\n| Project | Contact | Difficulty | Open Sourced? | Notes | \n| ----------- | ----------- | ---------- | :-: | ---------- |\n| [Kor](https://eyurtsev.github.io/kor/) | [Eugene Yurtsev](https://twitter.com/veryboldbagel) | π Intermediate | β
[Code](https://github.com/eyurtsev/kor) | This is a half-baked prototype that βhelpsβ you extract structured data from text using large language models (LLMs) π§©. | \n| [OpeningAttributes](https://twitter.com/GregKamradt/status/1643027796850253824) | [@gregkamradt](https://twitter.com/GregKamradt) | π Beginner | β
[Code](https://github.com/gkamradt/langchain-tutorials/blob/main/data_generation/Expert%20Structured%20Output%20(Using%20Kor).ipynb) | Extract technologies & tools from job descriptions | \n\n
\n\n### **π Evaluation** \n| Project | Contact | Difficulty | Open Sourced? | Notes | \n| ----------- | ----------- | ---------- | :-: | ---------- |\n| [Auto-Evaluator](https://autoevaluator.langchain.com/) | [@RLanceMartin](https://twitter.com/RLanceMartin) | π¦ Advanced | β
[Code](https://github.com/langchain-ai/auto-evaluator) | Evaluate Q&A Chains | \n\n
\n\n### **π Querying Tabular Data** \n| Project | Contact | Difficulty | Open Sourced? | Notes | \n| ----------- | ----------- | ---------- | :-: | ---------- |\n| TBD | | | | | \n\n
\n\n### **π» Code Understanding**\n| Project | Contact | Difficulty | Open Sou","github_created_at":"2023-02-13T18:24:18+00:00","created_at":"2026-07-11T10:52:15.251776+00:00","updated_at":"2026-08-15T12:01:04.680965+00:00","categories":[{"slug":"developer-tools","name":"Developer Tools","url":"https://www.graphcanon.com/categories/developer-tools","markdown_url":"https://www.graphcanon.com/categories/developer-tools.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/developer-tools"},{"slug":"model-training","name":"Model Training","url":"https://www.graphcanon.com/categories/model-training","markdown_url":"https://www.graphcanon.com/categories/model-training.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/model-training"}],"tags":[{"slug":"jupyter-notebook","name":"jupyter-notebook"},{"slug":"langchain","name":"langchain"},{"slug":"prompt-engineering","name":"prompt-engineering"},{"slug":"tutorials","name":"tutorials"}],"trust":{"provenance":{"is_fork":false,"github_id":601277247,"owner_type":"User","methodology":"github_public_v1","parent_repo":null,"near_duplicate_slugs":[]},"computed_at":"2026-08-15T12:01:03.466Z","maintenance":{"label":"Dormant","score":18,"methodology":"github_public_v1","releases_90d":0,"days_since_push":740,"last_release_at":null,"stars_delta_30d":10,"open_issues_delta_30d":0},"security_summary":{"status":"findings","scanner":"osv@v1","low_count":174,"high_count":0,"last_scan_at":"2026-07-11T10:52:16.921Z","medium_count":0,"scan_profile":"deps","critical_count":0}},"capability_facts":{"scan":{"source":"repo_scan","observed_at":"2026-08-15T12:01:04.074Z"},"languages":{"value":["jupyter notebook"],"source":"github.language","observed_at":"2026-08-15T12:01:04.074Z"}},"decision_facts":{"hosting":null,"pricing":{"model":"freemium","summary":"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."},"requirements":null,"constraints":{"pricing_model":"freemium"},"when_to_use":["- 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."],"when_not_to_use":["- 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."],"source":"enrich:decision_facts","observed_at":"2026-07-12T17:01:56.025Z"},"constraint_facets":{"pricing_model":"freemium"},"decision_summary":[{"label":"Pricing","value":"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."},{"label":"Adopt for","value":"langchain-tutorials offers educational material to aid in understanding and applying the LangChain library via Jupyter Notebooks."},{"label":"License detail","value":"The license details for this tool are unknown."}]}}