Comparison
LangChain's .with_retry() and LlamaIndex's retry helpers keep an agent's
tool calls alive inside the process. klanex moves execution off the process
entirely — durable, asynchronous, and self-correcting. Here's how they compare, and
why most teams run both.
| Capability | In-process retries (LangChain / LlamaIndex) |
klanex |
|---|---|---|
| Retry with exponential backoff | Yes — synchronous, in-memory | Yes — asynchronous, queue-driven |
| Survives the agent process crashing or restarting | No — retry state lives in memory | Yes — state persisted; the queue redelivers |
| Blocks the agent loop while retrying | Yes — the call is held open | No — returns an execution_id in ~15 ms |
| Per-host circuit breakers | No | Yes |
| Catches hallucinated payloads before the call | No | Yes — JSON Schema gate returns an llm_hint |
| Idempotency (a retry can't double-execute) | Do it yourself | Built in — idempotency_key |
| Credentials kept out of the model's environment | No | Yes — KMS-sealed vault |
| Human approval before destructive calls | No | Yes — requires_approval |
| Audit trail + one-call replay after an outage | No | Yes |
| Works with no framework / other languages | Framework-bound | Yes — REST API + MCP |
In-process retries are genuinely useful for the near-happy path inside a single request: a transient blip, retried a few times, with the backoff state held in memory. But that state inherits the agent process's lifetime. If the pod is recycled, the request is cancelled, or the synchronous call times out while the model is still thinking, the retry state — and the in-flight tool call — is gone.
klanex treats the tool call as a durable job instead. You submit the
intent, get an execution_id in milliseconds, and klanex owns the retries
on the queue's redelivery, the exponential backoff, and the per-host circuit
breakers — independent of whether your agent is still running.
llm_hint to fix itself — before the call ever leaves.Keep LangChain or LlamaIndex for orchestration and reasoning. Route the tool calls that touch money, external systems, or flaky APIs through klanex — it's a single HTTP call (or an MCP tool), so it drops into a framework tool without rewriting your agent.
Submit the intent to klanex instead of calling the API directly. The 422 schema-gate self-correction loop comes free.
# inside your LangChain / LlamaIndex tool, instead of requests.post(...)
POST https://api.klanexai.com/v1/executions X-API-Key: klx_…
{ "target": { "url": "https://api.stripe.com/v1/refunds", "headers": {…} },
"payload": agent_json, "payload_schema": {…}, "idempotency_key": "refund-ch_9f2k" }
202 {"execution_id": "exe_4d0c85a6", "status": "QUEUED"} # agent moves on
# retries, backoff, breakers, and the signed webhook are klanex's problem nowStart free — 1,000 executions a month, the full reliability engine, no credit card to explore.