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Mirage documentation lives beside the code in docs/. The docs/docs.json file controls navigation, and Mintlify serves each MDX page from the connected repository’s content directory.

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What updates automatically

After Mintlify is connected to the lab repository with docs/ as its content directory, pushes to the configured deployment branch (main) trigger a Mintlify build and deployment. External pushes also sync into the Mintlify editor. A local docs edit does not go live until it is committed and pushed. requirements.txt lists pinned direct runtime dependencies; pip resolves their transitive packages. requirements-dev.txt contains test-only tools. The first GitHub Actions check fails when a code or dependency change does not include a change under docs/. The next checks verify that the homepage and README result tables match the CSV, then validate Mintlify links.

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What to update with code changes

When changing an evaluation interface, update its matching page in the same change:

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Agent handoff: add DeepSeek-VL support

DeepSeek-VL is a requested future backend, not a currently runnable Mirage model. An agent implementing it should first identify the exact checkpoint and confirm its supported Transformers API and licensing requirements. Then add a wrapper following the existing model interface, register it in predict/factory.py with a documented model-path environment override, expose the model key in demo.py, and update the model and HPC pages in the same change. Preserve the existing prediction cache path and make the wrapper’s image and text inputs follow the contract in models/base.py. Before describing the backend as supported, the agent should run the existing tests, verify demo.py --help lists the model, and perform a one-image inference smoke test using a local checkpoint. Record the tested checkpoint and required package versions. Do not add a DeepSeek row to the reference results until the stated datasets and metrics have actually been evaluated and the result values have been reviewed. The automated checks catch missing documentation for code changes and broken internal links. They cannot decide whether a new metric description, resource estimate, result, or scientific interpretation is accurate, so review those details with the code change. To add a model to the reference results, add one measured CSV row per dataset and update both results tables. HPC result JSON stays on the cluster unless you deliberately bring selected results into this file and commit them.

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Preview and check a docs change

Install the Mintlify CLI with Node.js available, then run the local preview from the docs directory:
In another terminal from the docs directory, check internal links:
Commit the documentation with the code change and push to main. Once GitHub access and the content directory are configured, Mintlify handles the deployment from that push.