LangGraph
LGFlangchain-ai/langgraph
Graph-based runtime for teams turning agent behavior into explicit state, transitions, retries, and supervision paths.
signal read
LangGraph matters when an assistant flow has become product architecture. The operator value is explicit control: states, branches, interrupts, retries, and human review points can be named and tested. The tradeoff is surface area. Reach for it when failures must be governed; avoid it when a direct SDK call or small workflow script would be easier to operate.
operator posture: evaluate deliberately
Repository activity is current enough for comparison; use the decision checklist to judge fit.
score 61
rank #3
recent push
today since push
recent release
1 day since release
operator decision read
best for
Product teams turning agent behavior into durable application architecture with state and checkpoints.
operating load
High: needs state design, observability, failure handling, and clear human supervision paths.
avoid when
Do not choose it when the team has not yet proven the agent flow needs durable state, branching, or human checkpoints.
workflow fit
Best for product teams building stateful agent flows with explicit steps, branching, retries, and supervision.
watch out
Overkill for simple assistant features where a small SDK call or direct workflow script would be easier to operate.
adoption signal
Strong signal when agent behavior needs durable state, auditability, and repeatable control paths.
compare by
Agent orchestration framework versus app-layer primitives.
stars
33.3k
GitHub-derived metrics artifact value
prev snapshot
+78 stars
since 2026-05-28
momentum
61
deterministic artifact score
watchers
0.15k
GitHub-derived watcher count
7d stars
not measured
no seven-day comparison snapshot
freshness age
0d
age of the repository pushed timestamp at collection