> For the complete documentation index, see [llms.txt](https://docs.ccv.brown.edu/ai-tools/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.ccv.brown.edu/ai-tools/services/librechat/frequently-asked-questions-faq.md).

# Frequently Asked Questions (FAQ)

<details>

<summary>Can I use an agent like OpenCode or Claude Code to connect to LibreChat?</summary>

No. We do not have an API at the moment, but you can [use these agents inside Oscar with open source models](https://docs.ccv.brown.edu/oscar/large-language-models/opencode).

</details>

<details>

<summary>If I have used up my monthly budget, is there a way to request for more credits?</summary>

No. Once the budget is exhausted, it will not reset until the next calendar month.

</details>

<details>

<summary>There are some models that I want to use on LibreChat but it is not available. Can I request this model to be added?</summary>

Yes. We regularly add the latest frontier models from OpenAI, Anthropic, and Google, along with some open source models. If there is a model that you want to add to LibreChat, please submit a support ticket. Please note that we only have access to a small collection open source models, so the addtion of open source models is not guaranteed.

</details>


---

# Agent Instructions
This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com.

## Querying This Documentation
If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
GET https://docs.ccv.brown.edu/ai-tools/services/librechat/frequently-asked-questions-faq.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.