mirror of
https://github.com/BerriAI/litellm.git
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* feat(vector_stores/): initial commit adding Vertex AI Search API support for litellm new vector store provider * feat(vector_store/): use vector store id for vertex ai search api * fix: transformation.py cleanup * fix: implement abstract function * fix: fix linting error * fix: main.py fix check * feat: initial commit with working passthrough support for vertex ai search api through litellm * feat(llm_passthrough_endpoints.py): fix passing correct project on datastore passthrough * feat(vertex_ai/): support passthrough call for vertex ai search vector store * docs(vertex_ai_search_datastore.md): document new vertex ai passthrough endpoint * docs(sidebars.js): document new endpoint * feat: initial commit adding logging for vertex ai passthrough api allows vertex ai vector search api to work with cost calculation * feat(vertex_ai/): search vector store cost tracking * fix(vertex_passthrough_logging_handler.py): log the cost * fix: improve logged response * fix(vertex_passthrough_logging_handler.py): logging * feat(litellm_logging): main.py add cost tracking for vertex ai search api via unified api * refactor: fix ruff checks * fix(llm_passthrough_endpoints.py): fix linting |
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Website
This website is built using Docusaurus 2, a modern static website generator.
Installation
$ yarn
Local Development
$ yarn start
This command starts a local development server and opens up a browser window. Most changes are reflected live without having to restart the server.
Build
$ yarn build
This command generates static content into the build directory and can be served using any static contents hosting service.
Deployment
Using SSH:
$ USE_SSH=true yarn deploy
Not using SSH:
$ GIT_USER=<Your GitHub username> yarn deploy
If you are using GitHub pages for hosting, this command is a convenient way to build the website and push to the gh-pages branch.