Comparison
generative_ai_with_langchain vs langgraph
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 langgraph if langGraph is a low-level orchestration framework for building, managing, and deploying long-running, stateful agents, offering durable execution, human-in-the-loop oversight, and comprehensive memory management.
Markdown twin · generative_ai_with_langchain alternatives · langgraph alternatives
GraphCanon updated Sep 20, 2026
11views this month
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Trust & integrity
| Signal | generative_ai_with_langchain | langgraph |
|---|---|---|
| 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
- langgraph
- Low-level orchestration framework for building stateful agents
Stars
- generative_ai_with_langchain
- 1.4k
- langgraph
- 42k
Forks
- generative_ai_with_langchain
- 586
- langgraph
- 7.1k
Open issues
- generative_ai_with_langchain
- 0
- langgraph
- 794
Language
- generative_ai_with_langchain
- Jupyter Notebook
- langgraph
- Python
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.
- langgraph
- LangGraph is a low-level orchestration framework for building, managing, and deploying long-running, stateful agents, offering durable execution, human-in-the-loop oversight, and comprehensive memory management.
Persona
- generative_ai_with_langchain
- -
- langgraph
- -
Runtime
- generative_ai_with_langchain
- -
- langgraph
- -
License
- generative_ai_with_langchain
- MIT
- langgraph
- MIT
Last pushed
- generative_ai_with_langchain
- Aug 14, 2026
- langgraph
- Sep 18, 2026
Categories
- generative_ai_with_langchain
- AI Agents, LLM Frameworks
- langgraph
- AI Agents
Trust and health
Maintenance
- generative_ai_with_langchain
- Active (82%)
- langgraph
- Very active (96%)
Days since push
- generative_ai_with_langchain
- 24d
- langgraph
- 0d
Open issues (now)
- generative_ai_with_langchain
- 0
- langgraph
- 794
Stars delta
- generative_ai_with_langchain
- +14 (30d)
- langgraph
- +3.5k (30d)
Open issues delta
- generative_ai_with_langchain
- 0 (30d)
- langgraph
- +147 (30d)
Owner type
- generative_ai_with_langchain
- User
- langgraph
- Organization
OSV dependency advisories
- generative_ai_with_langchain
- Published findings
- langgraph
- No lockfile (source not queried)
Full report
- generative_ai_with_langchain
- Trust report
- langgraph
- Trust report
Shared compatibility
- Python · generative_ai_with_langchain: Python runtime · langgraph: Python runtime
Choose generative_ai_with_langchain if…
- generative_ai_with_langchain is primarily Jupyter Notebook; langgraph is Python.
- Tags unique to generative_ai_with_langchain: agent, chatgpt, claude, claude-3-5-sonnet.
- Also covers LLM Frameworks.
- 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 langgraph if…
- langgraph is primarily Python; generative_ai_with_langchain is Jupyter Notebook.
- Tags unique to langgraph: agents, ai-agents, framework, langchain.
- When you need to build agents that can persist through failures and resume from where they left off, ensuring durable execution.
When NOT to use langgraph
- If you are looking for a higher-level package that simplifies the process of building agents with planning and subagent capabilities, consider Deep Agents instead.
- For projects that do not require long-running, stateful workflows, LangGraph's features may be overkill and a simpler framework might be more appropriate.
- If your project is primarily focused on JavaScript or TypeScript, LangGraph.js might be a better fit, as LangGraph is primarily designed for Python environments.
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 (langchain-ai/langgraph) · observed Sep 20, 2026
- GitHub forks (langchain-ai/langgraph) · observed Sep 20, 2026
- Last push (langchain-ai/langgraph) · 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 · langgraph 42k (synced Sep 20, 2026).
Common questions
- What is the difference between generative_ai_with_langchain and langgraph?
- generative_ai_with_langchain: Build production-ready LLM applications and advanced agents using Python, LangChain, and LangGraph. langgraph: Low-level orchestration framework for building stateful agents. See the comparison table for live GitHub stats and shared categories.
- When should I choose generative_ai_with_langchain over langgraph?
- Choose generative_ai_with_langchain over langgraph when generative_ai_with_langchain is primarily Jupyter Notebook; langgraph is Python; Tags unique to generative_ai_with_langchain: agent, chatgpt, claude, claude-3-5-sonnet; Also covers LLM Frameworks; 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 langgraph over generative_ai_with_langchain?
- Choose langgraph over generative_ai_with_langchain when langgraph is primarily Python; generative_ai_with_langchain is Jupyter Notebook; Tags unique to langgraph: agents, ai-agents, framework, langchain; When you need to build agents that can persist through failures and resume from where they left off, ensuring durable execution.
- 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 langgraph?
- If you are looking for a higher-level package that simplifies the process of building agents with planning and subagent capabilities, consider Deep Agents instead. For projects that do not require long-running, stateful workflows, LangGraph's features may be overkill and a simpler framework might be more appropriate. If your project is primarily focused on JavaScript or TypeScript, LangGraph.js might be a better fit, as LangGraph is primarily designed for Python environments.
- Is generative_ai_with_langchain or langgraph more popular on GitHub?
- langgraph has more GitHub stars (41,866 vs 1,414). Stars measure visibility, not whether either tool fits your constraints.
- Are generative_ai_with_langchain and langgraph open source?
- Yes - both are open-source projects on GitHub (generative_ai_with_langchain: MIT, langgraph: MIT).
- Where can I find alternatives to generative_ai_with_langchain or langgraph?
- GraphCanon lists graph-backed alternatives at generative_ai_with_langchain alternatives and langgraph alternatives (generative_ai_with_langchain markdown twin, langgraph 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 langgraph?
- generative_ai_with_langchain: Active. langgraph: 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 langgraph?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: generative_ai_with_langchain trust report; langgraph trust report.