Comparison
generative_ai_with_langchain vs semantic-kernel
Verdict
Pick generative_ai_with_langchain if the `generative_ai_with_langchain` repository provides comprehensive companionship to a book on building production-level LLM applications and AI agents with LangChain; pick semantic-kernel if semantic-kernel is a framework for integrating large language models into applications using C#, Python, Java, and .NET, offering flexibility across multiple programming environments.
Markdown twin · generative_ai_with_langchain alternatives · semantic-kernel alternatives
GraphCanon updated Sep 20, 2026
6views this month
vs
Trust & integrity
| Signal | generative_ai_with_langchain | semantic-kernel |
|---|---|---|
| Maintenance | Active (24d since push) As of Sep 7, 2026 · github_public_v1 | Very active (0d since push) As of Sep 18, 2026 · github_public_v1 |
| Provenance | Not a fork · Personal account As of Sep 7, 2026 · github_public_v1 | Not a fork · Organization account As of Sep 18, 2026 · github_public_v1 |
| OSV dependency advisories | Published findings As of Jul 11, 2026 · osv@v1 | No lockfile (source not queried) As of Sep 18, 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
- generative_ai_with_langchain
- Build production-ready LLM applications and advanced agents using Python, LangChain, and LangGraph
- semantic-kernel
- Integrate cutting-edge LLM technology quickly and easily into your apps
Stars
- generative_ai_with_langchain
- 1.4k
- semantic-kernel
- 29k
Forks
- generative_ai_with_langchain
- 586
- semantic-kernel
- 4.8k
Open issues
- generative_ai_with_langchain
- 0
- semantic-kernel
- 304
Language
- generative_ai_with_langchain
- Jupyter Notebook
- semantic-kernel
- C#
Adopt for
- generative_ai_with_langchain
- The `generative_ai_with_langchain` repository provides comprehensive companionship to a book on building production-level LLM applications and AI agents with LangChain.
- semantic-kernel
- Semantic-kernel is a framework for integrating large language models into applications using C#, Python, Java, and .NET, offering flexibility across multiple programming environments.
Persona
- generative_ai_with_langchain
- -
- semantic-kernel
- -
Runtime
- generative_ai_with_langchain
- -
- semantic-kernel
- -
License
- generative_ai_with_langchain
- MIT
- semantic-kernel
- Semantic-kernel is licensed under the MIT license, allowing for free use, modification, and distribution of the software.
Last pushed
- generative_ai_with_langchain
- Aug 14, 2026
- semantic-kernel
- Sep 18, 2026
Categories
- generative_ai_with_langchain
- AI Agents, LLM Frameworks
- semantic-kernel
- AI Agents, LLM Frameworks
Trust and health
Maintenance
- generative_ai_with_langchain
- Active (82%)
- semantic-kernel
- Very active (96%)
Days since push
- generative_ai_with_langchain
- 24d
- semantic-kernel
- 0d
Open issues (now)
- generative_ai_with_langchain
- 0
- semantic-kernel
- 304
Stars delta
- generative_ai_with_langchain
- +14 (30d)
- semantic-kernel
- +148 (30d)
Open issues delta
- generative_ai_with_langchain
- 0 (30d)
- semantic-kernel
- +48 (30d)
Owner type
- generative_ai_with_langchain
- User
- semantic-kernel
- Organization
OSV dependency advisories
- generative_ai_with_langchain
- Published findings
- semantic-kernel
- No lockfile (source not queried)
Full report
- generative_ai_with_langchain
- Trust report
- semantic-kernel
- Trust report
Shared compatibility
- Python · generative_ai_with_langchain: Python runtime · semantic-kernel: Python runtime
Choose generative_ai_with_langchain if…
- generative_ai_with_langchain is primarily Jupyter Notebook; semantic-kernel is C#.
- Tags unique to generative_ai_with_langchain: agent, chatgpt, claude, claude-3-5-sonnet.
- generative_ai_with_langchain ships Docker support for self-hosted deployment.
- - When aiming for building robust, advanced language model applications in Python using the LangChain framework.
When NOT to use generative_ai_with_langchain
- - If you are seeking a toolkit that does not deeply integrate with Python or requires less dependency on specific frameworks like LangChain.
- - When your project specifically avoids the use of advanced agent implementations or you prefer more generalized LLM application development strategies without heavy reliance on LangGraph.
Choose semantic-kernel if…
- semantic-kernel is primarily C#; generative_ai_with_langchain is Jupyter Notebook.
- Requirements: System requirements include Python 3.10+, .NET 10.0+, and JDK 17+.; Operating system support includes Windows, macOS, and Linux..
- Tags unique to semantic-kernel: ai, artificial-intelligence, azure-openai, csharp.
- When you need to integrate large language models into applications using C#, Python, Java, or .NET, as semantic-kernel supports these languages natively.
When NOT to use semantic-kernel
- If your project is strictly limited to a single programming language that is not C#, Python, Java, or.NET, as semantic-kernel does not support other languages.
- When your application must exclusively use a specific AI service provider that is not Azure OpenAI or OpenAI, as semantic-kernel's primary integration is with these services.
- If your development environment is not Windows, macOS, or Linux, as semantic-kernel does not support other operating systems.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (benman1/generative_ai_with_langchain) · observed Sep 20, 2026
- GitHub forks (benman1/generative_ai_with_langchain) · observed Sep 20, 2026
- Last push (benman1/generative_ai_with_langchain) · observed Aug 14, 2026
- License file (MIT) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Jul 12, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (microsoft/semantic-kernel) · observed Sep 20, 2026
- GitHub forks (microsoft/semantic-kernel) · observed Sep 20, 2026
- Last push (microsoft/semantic-kernel) · observed Sep 18, 2026
- License file (MIT) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Sep 18, 2026
- Trust scan (lockfile / OSV) · observed Sep 18, 2026
GitHub stars on cards: generative_ai_with_langchain 1.4k · semantic-kernel 29k (synced Sep 20, 2026).
Common questions
- What is the difference between generative_ai_with_langchain and semantic-kernel?
- generative_ai_with_langchain: Build production-ready LLM applications and advanced agents using Python, LangChain, and LangGraph. semantic-kernel: Integrate cutting-edge LLM technology quickly and easily into your apps. See the comparison table for live GitHub stats and shared categories.
- When should I choose generative_ai_with_langchain over semantic-kernel?
- Choose generative_ai_with_langchain over semantic-kernel when generative_ai_with_langchain is primarily Jupyter Notebook; semantic-kernel is C#; Tags unique to generative_ai_with_langchain: agent, chatgpt, claude, claude-3-5-sonnet; generative_ai_with_langchain ships Docker support for self-hosted deployment; - When aiming for building robust, advanced language model applications in Python using the LangChain framework.
- When should I choose semantic-kernel over generative_ai_with_langchain?
- Choose semantic-kernel over generative_ai_with_langchain when semantic-kernel is primarily C#; generative_ai_with_langchain is Jupyter Notebook; Requirements: System requirements include Python 3.10+, .NET 10.0+, and JDK 17+.; Operating system support includes Windows, macOS, and Linux.; Tags unique to semantic-kernel: ai, artificial-intelligence, azure-openai, csharp; When you need to integrate large language models into applications using C#, Python, Java, or .NET, as semantic-kernel supports these languages natively.
- When should I avoid generative_ai_with_langchain?
- - If you are seeking a toolkit that does not deeply integrate with Python or requires less dependency on specific frameworks like LangChain. - When your project specifically avoids the use of advanced agent implementations or you prefer more generalized LLM application development strategies without heavy reliance on LangGraph.
- When should I avoid semantic-kernel?
- If your project is strictly limited to a single programming language that is not C#, Python, Java, or.NET, as semantic-kernel does not support other languages. When your application must exclusively use a specific AI service provider that is not Azure OpenAI or OpenAI, as semantic-kernel's primary integration is with these services. If your development environment is not Windows, macOS, or Linux, as semantic-kernel does not support other operating systems.
- Is generative_ai_with_langchain or semantic-kernel more popular on GitHub?
- semantic-kernel has more GitHub stars (28,575 vs 1,414). Stars measure visibility, not whether either tool fits your constraints.
- Are generative_ai_with_langchain and semantic-kernel open source?
- Yes - both are open-source projects on GitHub (generative_ai_with_langchain: MIT, semantic-kernel: MIT).
- Where can I find alternatives to generative_ai_with_langchain or semantic-kernel?
- GraphCanon lists graph-backed alternatives at generative_ai_with_langchain alternatives and semantic-kernel alternatives (generative_ai_with_langchain markdown twin, semantic-kernel 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, generative_ai_with_langchain or semantic-kernel?
- generative_ai_with_langchain: Active. semantic-kernel: Very active. 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 generative_ai_with_langchain and semantic-kernel?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: generative_ai_with_langchain trust report; semantic-kernel trust report.