# LlamaIndex

> Use LlamaIndex with AnyRouter. Connect OpenAILike (Python) or the OpenAI LLM (TypeScript) to power RAG and agents on free or paid models.


# Use LlamaIndex with AnyRouter

Drive your LlamaIndex indexes and agents with any model in AnyRouter's catalog. In Python, use LlamaIndex's `OpenAILike` class — its integration for OpenAI-compatible servers — because the plain `OpenAI` class only accepts OpenAI's own model names. In TypeScript, the `@llamaindex/openai` LLM takes a custom `baseURL`.

## Before you start

- A LlamaIndex project in Python or TypeScript.
- An AnyRouter API key (prefix `sk-ar-`). Create one in the [dashboard](https://anyrouter.dev/dashboard/keys).

## Set it up

Pick your language, install the integration, then configure the base URL, your key, and a model from the catalog. Use the LLM in your index querying or agent loops.

::::tabs

:::tab{label="Python"}
```bash
pip install llama-index-llms-openai-like
```

```python
import os
from llama_index.llms.openai_like import OpenAILike

llm = OpenAILike(
    model="anyrouter/free",
    api_base="https://anyrouter.dev/api/v1",
    api_key=os.environ["ANYROUTER_API_KEY"],  # sk-ar-...
    is_chat_model=True,
    context_window=128000,
)

response = llm.complete("Explain semantic search in one sentence.")
print(response.raw.model)  # the model that served the request
print(response)
```

`is_chat_model=True` sends requests to the Chat Completions endpoint. Set `context_window` to the context length of the model you use (listed on its catalog page) so LlamaIndex sizes prompts correctly.
:::

:::tab{label="TypeScript"}
```bash
npm install llamaindex @llamaindex/openai
```

```typescript
import { OpenAI } from "@llamaindex/openai"

const llm = new OpenAI({
  model: "anyrouter/free",
  apiKey: process.env.ANYROUTER_API_KEY, // sk-ar-...
  baseURL: "https://anyrouter.dev/api/v1",
})

const response = await llm.complete({
  prompt: "Explain vectors in machine learning in one sentence.",
})
console.log(response.text)
```
:::

::::

## Verify

Export your key, then run the snippet. A printed completion confirms LlamaIndex is routing through AnyRouter.

```bash
export ANYROUTER_API_KEY="sk-ar-your-key-here"
```

Every request also shows up in [Logs](https://anyrouter.dev/dashboard/logs) with the model, provider, tokens, and latency.

## Free models

Set the model to `anyrouter/free` and AnyRouter routes the request to a free model that is healthy right now — no credits used. Free models have no daily cap on any plan. Details on [Free Tier](/features/free-tier).

Use `anyrouter/auto` to let AnyRouter pick from the full catalog, or any `provider/model` id from the [catalog](https://anyrouter.dev/models) to pin one model.

## Bring your own keys

Already pay for OpenAI, Anthropic, Google, or another provider? Add those keys to AnyRouter and your requests use them, with no credits deducted. See [Get a provider API key](/guides/byok-provider-keys) and [BYOK](/features/byok).


## Troubleshooting

:::details{summary="401 Unauthorized"}
Confirm the key starts with `sk-ar-` and is passed as `api_key` (Python) or `apiKey` (TypeScript). Manage keys in the [dashboard](https://anyrouter.dev/dashboard/keys).
:::

:::details{summary="ValueError: Unknown model"}
The Python `OpenAI` class from `llama_index.llms.openai` rejects model ids that are not OpenAI's own. Use `OpenAILike` from `llama-index-llms-openai-like` as shown above.
:::

:::details{summary="404 model not found"}
Pass a full catalog id — `anyrouter/free`, `anyrouter/auto`, or a `provider/model` id such as `z-ai/glm-4.7-flash`. Valid ids live in the [catalog](https://anyrouter.dev/models).
:::

## Related

- [OpenAI SDK](/guides/openai-sdk) — the official client, Python and TypeScript
- [LangChain](/guides/langchain) — chains and agents
- [Vercel AI SDK](/guides/vercel-ai-sdk) — TypeScript-native framework
- [Chat Completions API](/api-reference/chat-completions) — the underlying endpoint
- [Models catalog](https://anyrouter.dev/models) — every model id you can pass