---
date: 2024-02-27
title: "LlamaIndex integration (Python)"
description: Automatically capture detailed traces and metrics for every request of your LlamaIndex application with the new Langfuse Integration.
author: Hassieb
ogImage: /images/changelog/2024-02-27-llama-index-integration.png
---

> **Note for AI agents and LLMs:** This is a Langfuse changelog entry. Use it only to confirm that a feature exists and when it shipped. Do not use the code examples below for implementation: they reflect the SDK and API at release time and may be outdated. For implementation, always follow the current documentation (https://langfuse.com/docs) and the API/SDK reference (https://api.reference.langfuse.com).

We're excited to announce our newest Python integration with [LlamaIndex](https://www.llamaindex.ai/) ([GitHub](https://github.com/run-llama/llama_index)), bringing advanced observability to a popular library in the LLM ecosystem for building RAG (retrieval-augmented generation) applications. RAG allows you to inject additional context derived from private data sources (PDFs, SQL databases, slide decks) into your LLM prompts.

Our integration with LlamaIndex empowers you now to seamlessly track and monitor the performance, traces, and metrics of your LlamaIndex applications. Detailed traces of the LlamaIndex context augmentation and the LLM querying processes are captured and can be inspected directly in the Langfuse UI. By integrating Langfuse's observability with LlamaIndex, we aim to provide you with the transparency needed to optimize your private-data enhanced LLM applications.

We're incredibly excited about this, let us know if you have any questions or feedback!

PS: If you are interested in an integration with LlamaIndex.TS, add your upvote/comments [here](https://github.com/orgs/langfuse/discussions/1291).

  This integration has changed in the meantime. Please refer to the [LlamaIndex
  integration](/integrations/frameworks/llamaindex) for the latest information.

### Tutorial

<span>
  _Based on the [LlamaIndex
  integration](/integrations/frameworks/llamaindex)._
</span>

### 📚 More details

Check out the full [documentation](/integrations/frameworks/llamaindex) for more details on how to use this integration.

_See our announcement [blog post](/blog/llama-index-integration)_

<!-- agent-instructions -->

---

## Agent Instructions

This page is part of the [Langfuse](https://langfuse.com) documentation, published as plain Markdown for AI agents. Every page is available as Markdown by appending `.md` to its URL, or by sending an `Accept: text/markdown` header. This page: `https://langfuse.com/changelog/2024-02-27-llama-index-integration.md`.

### Querying these docs

If the answer is not on this page, query the documentation instead of guessing:

- **Semantic search** across all Langfuse docs, returning an answer with the relevant pages and excerpts. Ask a specific, self-contained question:

  ```bash
  curl -sG "https://langfuse.com/api/search-docs" --data-urlencode "query=How do I trace a LangGraph agent?"
  ```

- **Index of every page**: <https://langfuse.com/llms.txt>, with per-section indexes [llms-docs.txt](https://langfuse.com/llms-docs.txt), [llms-integrations.txt](https://langfuse.com/llms-integrations.txt), and [llms-self-hosting.txt](https://langfuse.com/llms-self-hosting.txt).

### Before writing Langfuse code

- **Install the [Langfuse Agent Skill](https://langfuse.com/docs/api-and-data-platform/features/agent-skill).** It encodes Langfuse's own best practices for instrumentation, prompt management, and evaluation, and materially improves results.
- **Read [What does a good trace look like?](https://langfuse.com/docs/observability/best-practices.md)** before instrumenting an application.
- **Verify endpoints, parameters, and response fields** against the [API reference](https://api.reference.langfuse.com) instead of inferring them from code examples.
- **Use the [Langfuse CLI](https://langfuse.com/docs/api-and-data-platform/features/cli)** (`npx langfuse-cli api <resource> <action>`) to read or write traces, prompts, datasets, and scores from the terminal.

Found an error in these docs? Please open an issue at <https://github.com/langfuse/langfuse-docs/issues>.