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langchain-sdk-patterns

Compose LangChain 1.0 Python runnables with the production defaults the docs do not warn about: parallel batching, narrow fallbacks, and brace-safe prompts. Use when building an LCEL chain with RunnableSequence / RunnableParallel, adding resilience via .with_fallbacks(), tuning throughput with .batch() or .abatch(), or wrapping user input in a prompt template. Trigger with "langchain runnable", "with_fallbacks", "langchain batch", "runnable sequence", "lcel", "runnableparallel", "chain composition".

plugins/saas-packs/langchain-py-pack/skills/langchain-sdk-patterns/SKILL.md

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# LangChain SDK Patterns (Python)

## Overview

`chain.batch(inputs)` in LangChain 1.0 does **not** parallelize by default. The
`max_concurrency` parameter defaults to **1** in several provider packages
(notably older `langchain-openai`), so a call like `chain.batch(inputs_1000)`
runs 1,000 sequential round-trips — same wall-clock time as a `for` loop, plus
the overhead of the batch machinery. Users file "batch is slow" tickets,
benchmark it against asyncio, and move to a different framework — when the fix
is two lines:

```python
# BAD — silently serializes (P08)
chain.batch(inputs_1000)
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