* fix(callbacks): allow MAX_CALLBACKS override via env var (#20778)
* fix(callbacks): allow MAX_CALLBACKS override via env var
- Move MAX_CALLBACKS from logging_callback_manager.py to constants.py
- Add LITELLM_MAX_CALLBACKS env var override (default: 30)
- Add troubleshooting doc explaining the limit and override
Fixes issue where large deployments with 60+ teams using guardrails
would hit the hardcoded MAX_CALLBACKS=30 limit and fail to start.
* docs: add max_callbacks to sidebar navigation
---------
Co-authored-by: shin-bot-litellm <shin-bot-litellm@users.noreply.github.com>
* fix callbacks issue
---------
Co-authored-by: shin-bot-litellm <shin-bot-litellm@berri.ai>
Co-authored-by: shin-bot-litellm <shin-bot-litellm@users.noreply.github.com>
* feat: add support for anthropic_messages call type in prompt caching
* test: move anthropic_messages prompt caching test to main router test file
* add tutorial on using claude code with prompt cache routing
* feat(guardrails/): allow custom code execution for guardrails
first step in allowing teams to submit custom code for guardrails
* feat: custom_code_guardrail.md
support passing custom code for guardrails
* feat: initial commit adding ui for custom code guardrails
allows users to write guardrails based on custom code
* feat: expose new test custom code guardrail endpoint
allows ui testing playground to sanity check if guardrail is working as expected
* fix: fix linting errors
* fix: fix max recursion check
* fix: fix linting error
* docs: add Prisma migration troubleshooting guide
Add troubleshooting documentation for common Prisma migration errors
encountered when upgrading/downgrading LiteLLM proxy versions.
Covers:
- 'relation does not exist' errors after version rollback
- Blocked migrations from previous failures
- Migration state mismatch after version rollback
- General tips for prisma migrate resolve, db push, and migrate deploy
* docs: simplify prisma migration troubleshooting - focus on delete + restart
* Add request tags documentation for spend tracking
- Add new concise doc explaining how to tag model requests
- Include Python SDK and cURL examples
- Show where tags appear in spend logs
- Add common use cases table (AWS accounts, teams, projects)
- Include how to set default tags on API keys
- Add to Spend Tracking section in sidebar
Co-authored-by: ishaan <ishaan@berri.ai>
* Simplify request tags doc for AI Gateway usage
- Focus on config.yaml setup with default_key_generate_params
- Show both request body and header methods for sending tags
- Remove SDK examples, keep concise cURL examples
- Streamline for quick reference
Co-authored-by: ishaan <ishaan@berri.ai>
* Update request tags doc to show model-level config
- Set tags directly on model deployments in litellm_params
- Requests just specify model, tags applied automatically
- Use clear naming: AWS_IAM_PROD, AWS_IAM_DEV
Co-authored-by: ishaan <ishaan@berri.ai>
---------
Co-authored-by: Cursor Agent <cursoragent@cursor.com>
Co-authored-by: ishaan <ishaan@berri.ai>
* feat: add feature to make silent calls
* add test or silent feat
* add docs for silent feat
* fix lint issues and UI logs
* add docs of ab testing and deep copy
* feat: add GMI Cloud provider support
Add GMI Cloud as an OpenAI-compatible provider with:
- Provider configuration in providers.json
- Documentation page with usage examples
- Model pricing for 16 models (Claude, GPT, DeepSeek, Gemini, etc.)
- Sidebar entry for docs navigation
* Add gmi_cloud to provider_endpoints_support.json
Add provider entry to pass CI validation check that ensures all
providers in openai_like/providers.json are documented.
* Fix provider key: gmi_cloud -> gmi
Match the provider key with providers.json
---------
Co-authored-by: Krish Dholakia <krrishdholakia@gmail.com>
* add search provider for brave search api
Introduces a minimal implementation of the Brave Search API as a search provider. Additionally, this PR introduces a test file to ensure the provider works properly, and numerous other smaller changes (e.g., changes to docs to mention the new option).
* Update transformation.py
* fix: safely handle unmapped call type
* docs: cleanup links for ai coding tools
* docs(claude_non_anthropic_models.md): add tutorial showing non anthropic model connection to claude code
* docs: link to non-anthropic model tutorial for claude code
