Home/Compare/langchain vs LLMStack

Comparison

langchain vs LLMStack

Verdict

Pick langchain if langChain is a Python framework for building agents and LLM-powered applications, offering interoperable components and third-party integrations to simplify AI application development; pick LLMStack if lLMStack is a no-code framework designed for building LLM Agents and complex workflows with data integration, suitable for teams that want to leverage AI without deep coding expertise.

Markdown twin · langchain alternatives · LLMStack alternatives

GraphCanon updated Sep 30, 2026

15views this month

langchain logo

langchain

langchain-ai/langchain

★ 147kpushed Sep 18, 2026
vs
LLMStack logo

LLMStack

trypromptly/LLMStack

★ 2.3kpushed Dec 11, 2024

Trust & integrity

SignallangchainLLMStack
Maintenance
Very active (0d since push)
As of Sep 18, 2026 · github_public_v1
Dormant (612d since push)
As of Aug 16, 2026 · github_public_v1
Provenance
Not a fork · Organization account
As of Sep 18, 2026 · github_public_v1
Not a fork · Organization account
As of Aug 16, 2026 · github_public_v1
OSV dependency advisories
No lockfile (source not queried)
As of Sep 18, 2026 · osv@v1
No lockfile (source not queried)
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

langchain
The agent engineering platform.
LLMStack
No-code multi-agent framework to build LLM Agents, workflows and applications with your data

Stars

langchain
147k
LLMStack
2.3k

Forks

langchain
25k
LLMStack
347

Open issues

langchain
541
LLMStack
23

Language

langchain
Python
LLMStack
Python

Adopt for

langchain
LangChain is a Python framework for building agents and LLM-powered applications, offering interoperable components and third-party integrations to simplify AI application development.
LLMStack
LLMStack is a no-code framework designed for building LLM Agents and complex workflows with data integration, suitable for teams that want to leverage AI without deep coding expertise.

Persona

langchain
-
LLMStack
-

Runtime

langchain
-
LLMStack
-

License

langchain
MIT
LLMStack
Other

Last pushed

langchain
Sep 18, 2026
LLMStack
Dec 11, 2024

Categories

langchain
AI Agents, LLM Frameworks
LLMStack
AI Agents, LLM Frameworks

Trust and health

Maintenance

langchain
Very active (96%)
LLMStack
Dormant (18%)

Days since push

langchain
0d
LLMStack
612d

Open issues (now)

langchain
541
LLMStack
23

Stars delta

langchain
+3.0k (30d)
LLMStack
+2 (30d)

Open issues delta

langchain
+78 (30d)
LLMStack
-1 (30d)

Full report

langchain
Trust report
LLMStack
Trust report

Typed relationship

langchain alternative LLMStackLLMStack can be considered an alternative to LangChain since both platforms provide means to build, manage, and deploy AI agents, but LLMStack emphasizes a no-code experience whereas LangChain provides more direct engineering capabilities.

Shared compatibility

  • Python · langchain: Python runtime · LLMStack: Python runtime

Choose langchain if…

  • License: langchain is MIT, LLMStack is Other.
  • LLMStack can be considered an alternative to LangChain since both platforms provide means to build, manage, and deploy AI agents, but LLMStack emphasizes a no-code experience whereas LangChain provides more direct engineering capabilities.
  • Tags unique to langchain: ai-agents, framework, langchain, multiagent.
  • When you need a framework that simplifies chaining together interoperable components and third-party integrations for AI application development.

When NOT to use langchain

  • If you prefer a framework that does not offer built-in capabilities for common usage patterns such as planning and subagents, as LangChain's Deep Agents provide these features.
  • When you need a higher-level abstraction that does not require detailed agent orchestration, as LangChain's LangGraph is designed for low-level control over agent workflows.

Choose LLMStack if…

  • License: LLMStack is Other, langchain is MIT.
  • LLMStack can be considered an alternative to LangChain since both platforms provide means to build, manage, and deploy AI agents, but LLMStack emphasizes a no-code experience whereas LangChain provides more direct engineering capabilities.
  • Tags unique to LLMStack: ai-agents-framework, generative-ai, llm-agents, llm-chain.
  • Use LLMStack when you need a no-code solution to develop multi-agent systems based on large language models.

When NOT to use LLMStack

  • Avoid using LLMStack if your project necessitates heavy customization or fine-tuning at the coding level, as it may limit flexibility compared to code-based alternatives.
  • Not recommended for teams with robust software engineering capabilities and a need for detailed control over underlying AI model architectures.

Explore

Sources

Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.

GitHub stars on cards: langchain 147k · LLMStack 2.3k (synced Sep 20, 2026).

Common questions

What is the difference between langchain and LLMStack?
langchain: The agent engineering platform.. LLMStack: No-code multi-agent framework to build LLM Agents, workflows and applications with your data. See the comparison table for live GitHub stats and shared categories.
When should I choose langchain over LLMStack?
Choose langchain over LLMStack when License: langchain is MIT, LLMStack is Other; LLMStack can be considered an alternative to LangChain since both platforms provide means to build, manage, and deploy AI agents, but LLMStack emphasizes a no-code experience whereas LangChain provides more direct engineering capabilities; Tags unique to langchain: ai-agents, framework, langchain, multiagent; When you need a framework that simplifies chaining together interoperable components and third-party integrations for AI application development.
When should I choose LLMStack over langchain?
Choose LLMStack over langchain when License: LLMStack is Other, langchain is MIT; LLMStack can be considered an alternative to LangChain since both platforms provide means to build, manage, and deploy AI agents, but LLMStack emphasizes a no-code experience whereas LangChain provides more direct engineering capabilities; Tags unique to LLMStack: ai-agents-framework, generative-ai, llm-agents, llm-chain; Use LLMStack when you need a no-code solution to develop multi-agent systems based on large language models.
When should I avoid langchain?
If you prefer a framework that does not offer built-in capabilities for common usage patterns such as planning and subagents, as LangChain's Deep Agents provide these features. When you need a higher-level abstraction that does not require detailed agent orchestration, as LangChain's LangGraph is designed for low-level control over agent workflows.
When should I avoid LLMStack?
Avoid using LLMStack if your project necessitates heavy customization or fine-tuning at the coding level, as it may limit flexibility compared to code-based alternatives. Not recommended for teams with robust software engineering capabilities and a need for detailed control over underlying AI model architectures.
Is langchain or LLMStack more popular on GitHub?
langchain has more GitHub stars (146,576 vs 2,309). Stars measure visibility, not whether either tool fits your constraints.
Are langchain and LLMStack open source?
Yes - both are open-source projects on GitHub (langchain: MIT, LLMStack: Other).
Where can I find alternatives to langchain or LLMStack?
GraphCanon lists graph-backed alternatives at langchain alternatives and LLMStack alternatives (langchain markdown twin, LLMStack 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, langchain or LLMStack?
langchain: Very active. LLMStack: 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 langchain and LLMStack?
GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: langchain trust report; LLMStack trust report.

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