# Description
Please include a summary of the changes and the related issue. Please
also include relevant motivation and context.
## Checklist before requesting a review
Please delete options that are not relevant.
- [ ] My code follows the style guidelines of this project
- [ ] I have performed a self-review of my code
- [ ] I have commented hard-to-understand areas
- [ ] I have ideally added tests that prove my fix is effective or that
my feature works
- [ ] New and existing unit tests pass locally with my changes
- [ ] Any dependent changes have been merged
## Screenshots (if appropriate):
This pull request introduces comprehensive documentation for configuring
Supabase in Quivr, including details on CLI usage, running migrations,
resetting the database, and deploying to a hosted version of Supabase.
- **Documentation Addition**: Adds a new document
`docs/configuring/supabase-setup.mdx` that provides a step-by-step guide
on setting up Supabase for Quivr. This includes initializing Supabase,
configuring environment variables, using the Supabase CLI for migrations
and database resets, and deploying to a hosted Supabase environment.
- **Documentation Navigation Update**: Updates `docs/mint.json` to
include a reference to the newly added `supabase-setup.mdx` in the
configuring section, ensuring users can easily find this resource.
---
For more details, open the [Copilot Workspace
session](https://copilot-workspace.githubnext.com/QuivrHQ/quivr?shareId=cadcc1b3-ff9d-4650-b92a-28cadcc3ebdf).
This pull request adds Llama Parse integration for complex document
parsing in Quivr. Llama Parse is a tool from Llama Index that allows you
to read complex documents in Quivr. It provides an API key that needs to
be added to the `.env` file as `LLAMA_CLOUD_API_KEY`. Once configured,
you can use the Llama Parse tool to read `pdf`, `docx`, and `doc` files
in Quivr.
This pull request updates the telemetry configuration in Quivr. The
guide now includes instructions on how to deactivate or configure the
telemetry service.
This pull request adds a new guide to the documentation that explains
how to configure reranking in Quivr. The guide covers the steps to
configure the reranking service using the FlashrankRerank library and
the Cohere ReRanker. It also provides information on the required
environment variables and the default behavior of the Ranker.
# Description
Please include a summary of the changes and the related issue. Please
also include relevant motivation and context.
## Checklist before requesting a review
Please delete options that are not relevant.
- [ ] My code follows the style guidelines of this project
- [ ] I have performed a self-review of my code
- [ ] I have commented hard-to-understand areas
- [ ] I have ideally added tests that prove my fix is effective or that
my feature works
- [ ] New and existing unit tests pass locally with my changes
- [ ] Any dependent changes have been merged
## Screenshots (if appropriate):
This pull request adds environment variables, increases user usage, and
adds new models to the Quivr application. It includes the following
commits:
- docs: Add environment variables, increase user usage, and add new
models
