Comparison
Hands-On-Large-Language-Models vs codespaces-langchain
Verdict
Pick Hands-On-Large-Language-Models if hands-On-Large-Language-Models offers code examples and educational content for large language models, as detailed in the O'Reilly book 'Hands-On Large Language Models'. The repository is in Jupyter Notebook format and,遵; pick codespaces-langchain if codespaces-langchain is tailored for streamlined integration of LangChain within the GitHub Codespaces environment.
Markdown twin · Hands-On-Large-Language-Models alternatives · codespaces-langchain alternatives
GraphCanon updated Sep 20, 2026
vs
Trust & integrity
| Signal | Hands-On-Large-Language-Models | codespaces-langchain |
|---|---|---|
| Maintenance | Slowing (146d since push) As of Sep 18, 2026 · github_public_v1 | Dormant (1277d since push) As of Sep 20, 2026 · github_public_v1 |
| Provenance | Not a fork · Organization account As of Sep 18, 2026 · github_public_v1 | Not a fork · Personal account As of Sep 20, 2026 · github_public_v1 |
| OSV dependency advisories | Published findings As of Sep 18, 2026 · osv@v1 | No published findings from this source as of 2026-07-11 As of Jul 11, 2026 · osv@v1 |
| deps.dev advisories | Not queried deps.dev@v1 | Not queried deps.dev@v1 |
| OpenSSF Scorecard | Not queried openssf-scorecard@v1 | Not queried openssf-scorecard@v1 |
Tagline
- Hands-On-Large-Language-Models
- Code for the book 'Hands-On Large Language Models'
- codespaces-langchain
- A Codespaces template for getting up-and-running with LangChain in seconds
Stars
- Hands-On-Large-Language-Models
- 29k
- codespaces-langchain
- 113
Forks
- Hands-On-Large-Language-Models
- 6.7k
- codespaces-langchain
- 22
Open issues
- Hands-On-Large-Language-Models
- 40
- codespaces-langchain
- 5
Language
- Hands-On-Large-Language-Models
- Jupyter Notebook
- codespaces-langchain
- -
Adopt for
- Hands-On-Large-Language-Models
- Hands-On-Large-Language-Models offers code examples and educational content for large language models, as detailed in the O'Reilly book 'Hands-On Large Language Models'. The repository is in Jupyter Notebook format and,遵
- codespaces-langchain
- codespaces-langchain is tailored for streamlined integration of LangChain within the GitHub Codespaces environment.
Persona
- Hands-On-Large-Language-Models
- -
- codespaces-langchain
- -
Runtime
- Hands-On-Large-Language-Models
- -
- codespaces-langchain
- -
License
- Hands-On-Large-Language-Models
- Apache-2.0
- codespaces-langchain
- -
Last pushed
- Hands-On-Large-Language-Models
- Apr 24, 2026
- codespaces-langchain
- Mar 22, 2023
Categories
- Hands-On-Large-Language-Models
- Developer Tools, LLM Frameworks
- codespaces-langchain
- Developer Tools, LLM Frameworks
Trust and health
Maintenance
- Hands-On-Large-Language-Models
- Slowing (36%)
- codespaces-langchain
- Dormant (18%)
Days since push
- Hands-On-Large-Language-Models
- 146d
- codespaces-langchain
- 1277d
Open issues (now)
- Hands-On-Large-Language-Models
- 40
- codespaces-langchain
- 5
Stars delta
- Hands-On-Large-Language-Models
- +910 (30d)
- codespaces-langchain
- 0 (30d)
Open issues delta
- Hands-On-Large-Language-Models
- +2 (30d)
- codespaces-langchain
- 0 (30d)
Owner type
- Hands-On-Large-Language-Models
- Organization
- codespaces-langchain
- User
OSV dependency advisories
- Hands-On-Large-Language-Models
- Published findings
- codespaces-langchain
- No published findings from this source as of 2026-07-11
Full report
- Hands-On-Large-Language-Models
- Trust report
- codespaces-langchain
- Trust report
Choose Hands-On-Large-Language-Models if…
- Tags unique to Hands-On-Large-Language-Models: artificial-intelligence, book, large-language-models, llms.
- Use this tool if you are looking for practical, code-based learning resources that align with the book 'Hands-On Large Language Models'.
- More GitHub stars (29k vs 113) - visibility, not fit.
When NOT to use Hands-On-Large-Language-Models
- Avoid this tool if you are seeking a comprehensive theoretical background without practical examples, as the focus is on hands-on learning.
- Not recommended for users who prefer a different platform for running code examples, as the repository is optimized for Google Colab with a T4 GPU and 16GB VRAM.
- If you are looking for a tool that covers a broader range of AI topics beyond large language models, this repository may not be the best fit.
Choose codespaces-langchain if…
- Requirements: API keys from OpenAI (and optionally SerpAPI) are necessary to operate this tool..
- Tags unique to codespaces-langchain: codespaces, langchain, notebooks, openai-api.
- This tool is ideal when working specifically with LangChain and wanting to leverage GitHub Codespaces for a seamless setup experience.
When NOT to use codespaces-langchain
- Avoid this if your project requires customization beyond what's provided by default, as this template may not cover all specific needs without significant modification.
- They might be less suitable for users new to both LangChain and GitHub Codespaces, who need more detailed onboarding support than the repository README provides.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (HandsOnLLM/Hands-On-Large-Language-Models) · observed Sep 20, 2026
- GitHub forks (HandsOnLLM/Hands-On-Large-Language-Models) · observed Sep 20, 2026
- Last push (HandsOnLLM/Hands-On-Large-Language-Models) · observed Apr 24, 2026
- License file (Apache-2.0) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Sep 18, 2026
- Trust scan (lockfile / OSV) · observed Sep 18, 2026
- GitHub stars (lostintangent/codespaces-langchain) · observed Sep 20, 2026
- GitHub forks (lostintangent/codespaces-langchain) · observed Sep 20, 2026
- Last push (lostintangent/codespaces-langchain) · observed Mar 22, 2023
- License file (unknown) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Jul 12, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: Hands-On-Large-Language-Models 29k · codespaces-langchain 113 (synced Sep 20, 2026).
Common questions
- What is the difference between Hands-On-Large-Language-Models and codespaces-langchain?
- Hands-On-Large-Language-Models: Code for the book 'Hands-On Large Language Models'. codespaces-langchain: A Codespaces template for getting up-and-running with LangChain in seconds. See the comparison table for live GitHub stats and shared categories.
- When should I choose Hands-On-Large-Language-Models over codespaces-langchain?
- Choose Hands-On-Large-Language-Models over codespaces-langchain when Tags unique to Hands-On-Large-Language-Models: artificial-intelligence, book, large-language-models, llms; Use this tool if you are looking for practical, code-based learning resources that align with the book 'Hands-On Large Language Models'; More GitHub stars (29k vs 113) - visibility, not fit.
- When should I choose codespaces-langchain over Hands-On-Large-Language-Models?
- Choose codespaces-langchain over Hands-On-Large-Language-Models when Requirements: API keys from OpenAI (and optionally SerpAPI) are necessary to operate this tool.; Tags unique to codespaces-langchain: codespaces, langchain, notebooks, openai-api; This tool is ideal when working specifically with LangChain and wanting to leverage GitHub Codespaces for a seamless setup experience.
- When should I avoid Hands-On-Large-Language-Models?
- Avoid this tool if you are seeking a comprehensive theoretical background without practical examples, as the focus is on hands-on learning. Not recommended for users who prefer a different platform for running code examples, as the repository is optimized for Google Colab with a T4 GPU and 16GB VRAM. If you are looking for a tool that covers a broader range of AI topics beyond large language models, this repository may not be the best fit.
- When should I avoid codespaces-langchain?
- Avoid this if your project requires customization beyond what's provided by default, as this template may not cover all specific needs without significant modification. They might be less suitable for users new to both LangChain and GitHub Codespaces, who need more detailed onboarding support than the repository README provides.
- Is Hands-On-Large-Language-Models or codespaces-langchain more popular on GitHub?
- Hands-On-Large-Language-Models has more GitHub stars (29,162 vs 113). Stars measure visibility, not whether either tool fits your constraints.
- Are Hands-On-Large-Language-Models and codespaces-langchain open source?
- Yes - both are open-source projects on GitHub.
- Where can I find alternatives to Hands-On-Large-Language-Models or codespaces-langchain?
- GraphCanon lists graph-backed alternatives at Hands-On-Large-Language-Models alternatives and codespaces-langchain alternatives (Hands-On-Large-Language-Models markdown twin, codespaces-langchain markdown twin), ranked by typed relationship edges rather than popularity votes.
- Is there a machine-readable version of this comparison?
- Yes. The markdown twin at this comparison mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers.
- Which is better maintained, Hands-On-Large-Language-Models or codespaces-langchain?
- Hands-On-Large-Language-Models: Slowing. codespaces-langchain: Dormant. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance.
- Where are the full trust reports for Hands-On-Large-Language-Models and codespaces-langchain?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: Hands-On-Large-Language-Models trust report; codespaces-langchain trust report.