hypit vs langgraph

langgraph is much bigger: 41.9k stars against 10.5k.

hypit leads on context depth and customization and privacy and model freedom. langgraph does not take any axis by a clear margin.

Stars and commit dates come from our own daily tracking. The six axes are read off each project's documentation by our review pipeline, so they describe what a project says about itself, not what we measured in its code.

Where they stand today

An end-to-end, agent-driven video workflow DSL that clones a reference video into editable, re-runnable compositions and ships mass variants (e.g., 100 variants) rather than producing single one-off renders.

Stars
10.5k
Tracked growth
not tracked long enough
Maturity
Last commit
3h ago
Language
TypeScript
License
NOASSERTION
Cost to run
Open-source; can run locally for free, external model API costs may apply.

Provides low-level orchestration for long-running, stateful agents with durable execution and human-in-the-loop capabilities that typical stateless workflow engines do not emphasize.

Stars
41.9k
Tracked growth
+18.5%
Maturity
Last commit
11h ago
Language
Python
License
MIT
Cost to run
Free, open-source
0%+447%90 tracked days
hypit-ai/hypitlangchain-ai/langgraph

Six axes, head to head

Each axis runs 0 to 5. The label under a score is what that project's own docs claim, not a category average.

Axishypitlanggraph
Context depth
How much of your codebase it sees before it answers: the open diff, the diff plus related files, or the whole repository.
Project directory
Diff only
Noise control
How it keeps output volume down — severity thresholds, deduplication, incremental runs over new commits only.
None mentioned
None mentioned
Customization
How far it bends to your team: custom rules, prompts, style guides, per-path config.
Pluggable components
No config
Privacy
Whether your code stays on your own infrastructure: fully local, self-hostable, or cloud API only.
Fully local option
Third-party cloud
Model freedom
Whether you can point it at any provider, or it is wired to one.
Multiple providers
Fixed provider
Setup ease
What it takes to get a first useful run out of it.
One-command install
One-command install

Which one to pick

Pick hypit if…

Open-source local workflows — run fully editable video-generation pipelines on your machine and produce many variants from a single command without per-render vendor fees.

  • Context depth: Project directory (3/5 against 1/5)
  • Customization: Pluggable components (5/5 against 1/5)
  • Privacy: Fully local option (5/5 against 1/5)
  • Model freedom: Multiple providers (3/5 against 1/5)
Runs in cli, coding-agent-plugin. Works with openai, anthropic, other-fixed.

Pick langgraph if…

Durable execution — choose LangGraph when you need persistent, stateful agents with human-in-the-loop oversight and production deployment support.

Runs in cli. Works with other-fixed.

What people want from each one

Questions people ask

Is hypit better than langgraph?

hypit leads on context depth and customization and privacy and model freedom. langgraph does not take any axis by a clear margin. hypit is worth picking when open-source local workflows — run fully editable video-generation pipelines on your machine and produce many variants from a single command without per-render vendor fees.

Which of hypit and langgraph keeps my code private?

hypit: Fully local option (5/5). langgraph: Third-party cloud (1/5).

What does each one cost to run?

hypit: Open-source; can run locally for free, external model API costs may apply.. langgraph: Free, open-source.

Full profiles: hypit-ai/hypit and langchain-ai/langgraph. Everything else in Workflow & graph engines.