mirror of
https://github.com/BerriAI/litellm.git
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58141df65d
* fix(azure/chat/gpt_transformation.py): add 'prediction' as a support azure param Closes https://github.com/BerriAI/litellm/issues/8500 * build(model_prices_and_context_window.json): add new 'gemini-2.0-pro-exp-02-05' model * style: cleanup invalid json trailing commma * feat(utils.py): support passing 'tokenizer_config' to register_prompt_template enables passing complete tokenizer config of model to litellm Allows calling deepseek on bedrock with the correct prompt template * fix(utils.py): fix register_prompt_template for custom model names * test(test_prompt_factory.py): fix test * test(test_completion.py): add e2e test for bedrock invoke deepseek ft model * feat(base_invoke_transformation.py): support hf_model_name param for bedrock invoke calls enables proxy admin to set base model for ft bedrock deepseek model * feat(bedrock/invoke): support deepseek_r1 route for bedrock makes it easy to apply the right chat template to that call * feat(constants.py): store deepseek r1 chat template - allow user to get correct response from deepseek r1 without extra work * test(test_completion.py): add e2e mock test for bedrock deepseek * docs(bedrock.md): document new deepseek_r1 route for bedrock allows us to use the right config * fix(exception_mapping_utils.py): catch read operation timeout |
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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.