Category guide · Python agent runtime · agent orchestration
How to evaluate a Python agent runtime
A production runtime needs more than a graph API. Evaluate orchestration, durable state, replay, caching, tool boundaries, retrieval, security, and operational evidence as one system.
Runtime capabilities to test
Graph execution
Branches, retries, interrupts, subgraphs, deterministic transitions, and explicit failure behavior.
Durable state
Checkpoint recovery, idempotency, tenant isolation, and byte-level replay after a process restart.
Evidence and cost
Per-node timing, cache decisions, route history, tool calls, token use, and an exportable audit trail.
Security and retrieval
Stable ports for prompt-injection controls and taxonomy-scoped retrieval without forking the runtime.
Minimal ChorusGraph installation
pip install "chorusgraph==1.1.0"ChorusGraph is an Apache-2.0 Python agent runtime with its own graph engine, semantic cache, Route Ledger, memory, and plug-in ports for PrismGuard security and PrismRAG retrieval.
Use a controlled evaluation
| Dimension | Measure | Why it matters |
|---|---|---|
| Task completion | Success rate on fixed scenarios and seeds | Separates orchestration reliability from model variance. |
| Recovery | Resume correctness after node and process failure | Production agents must recover without repeating side effects. |
| Cost | Tokens, cache hits, tool calls, and latency by node | Total runtime cost is broader than framework overhead. |
| Auditability | Complete route, state, and decision evidence | Operators need to explain what ran and why. |
Published ChorusGraph evidence
Insight IT Solutions publishes an Azure scale comparison with a documented LangGraph baseline, 300 examples per scenario, configuration notes, fairness disclosure, and raw run artifacts. It is vendor-authored evidence, not a neutral industry benchmark. Reproduce it and test your own workflows before choosing a runtime.