# Retries, Fallbacks and Timeouts — LangChain / LlamaIndex

Source: https://www.geekswithgeeks.com/en/langchain-llamaindex/a-reliable

> Make chains survive transient failures.

## Plan for the failing call

Network calls to model providers fail: rate limits, timeouts, temporary 5xx errors. Every runnable offers **`.with_retry(...)`** to retry on errors with a limit on attempts and (optionally) exponential backoff, and **`.with_fallbacks([...])`** to switch to an alternative runnable when it fails (for example a second provider or a cheaper model). Also set **timeouts** and a **maximum number of retries** on the model itself, and retry only errors that are safe to repeat; do not blindly retry steps with side effects such as sending an email.

## Retry and fallback, run

I ran this offline in a Python virtual environment with langchain-core 1.6.6, langchain-text-splitters 1.1.2 and llama-index-core 0.14.25. No API key or network call is needed because a fake model or a toy embedding stands in for the real one. The flaky function fails twice and succeeds on the third call, and `with_retry` returns "ok after 3 calls". A runnable that always fails (1/0) falls back to the backup and returns "fallback answer".

```python
from langchain_core.runnables import RunnableLambda

calls = {"n": 0}
def flaky(x):
    calls["n"] += 1
    if calls["n"] < 3:
        raise ValueError("temporary failure")
    return f"ok after {calls['n']} calls"

chain = RunnableLambda(flaky).with_retry(stop_after_attempt=4, wait_exponential_jitter=False)
print(chain.invoke("x"))

backup = RunnableLambda(lambda x: "fallback answer")
broken = RunnableLambda(lambda x: 1 / 0).with_fallbacks([backup])
print(broken.invoke("x"))

```

Output:

```
ok after 3 calls
fallback answer
```

**Quiz:** When should you NOT blindly retry a step?

- [ ] When it is a pure function
- [x] When it has side effects such as sending an email
- [ ] When it is a read-only lookup
- [ ] When it is fast

*Answer:* When it has side effects such as sending an email. Repeating a side-effecting step can duplicate its effect.