# Versions, Cost, Latency and Security — LangChain / LlamaIndex

Source: https://www.geekswithgeeks.com/en/langchain-llamaindex/p-ops

> Operate a framework-based app safely and affordably.

## Pin, measure, protect

**Versions**: both libraries evolve quickly and have been reorganised into many packages, so pin exact versions in a lockfile, read release notes before upgrading, and keep tests that catch breakages. **Cost and latency**: log token usage per call, cap output tokens, retrieve fewer and better chunks, cache repeated work (embeddings, identical queries, prompt prefixes), stream responses, and use a smaller model for easy steps. **Security**: keep API keys in environment variables or a secrets manager, never in code or prompts; apply access control inside retrieval; treat retrieved text as untrusted; redact sensitive data before logging or tracing; review third-party loaders and integrations, since they run code with your permissions.

## A pinned requirements file (illustrative)

Pin the versions you tested with. The numbers shown are the versions used to run this course's examples; choose versions that suit your project.

```text
# requirements.txt
langchain-core==1.6.6
langchain-text-splitters==1.1.2
llama-index-core==0.14.25
# add provider packages (e.g. langchain-openai) with exact versions too
```

**Quiz:** Why pin library versions?

- [ ] Pinning makes the model smarter
- [x] These libraries change quickly and upgrades can break code
- [ ] It is required by Python
- [ ] It reduces token cost

*Answer:* These libraries change quickly and upgrades can break code. Stable versions make behaviour reproducible until you choose to upgrade.