* feat(azure/prompt_shield.py): initial commit adding prompt shield guardrail + auto discovery mechanism for guardrails
reduces amount of code needed outside of guardrail integration for instrumentation
* feat(azure/prompt_shield.py): working azure prompt shield guardrail integration
Addresses https://github.com/BerriAI/litellm/issues/12254
* test: unit tests for prompt_shield
* fix(prompt_shield.py): add event hook validation for prompt shield guardrail
ensures prompt shield guardrail raises error if asked to run post_call (only runs on user prompt)
* feat(azure/): working text_moderation integration
* fix(text_moderation.py): suppress linting error
* test(test_azure_text_moderation.py): add unit test
* test(test_azure_text_moderation.py): add unit test for responses
* fix(text_moderation.py): return streaming error correctly
ensures error returned to user
* fix: fix linting error
* fix: fix linting check
* test: change mistral model
service tier exceeded
* fix(exception_mapping_utils.py): cover mistral in exception mapping
* fixes for using bedrock guard
* fixes for output_content_bedrock guard
* test_convert_to_bedrock_format_input_source
* test_convert_to_bedrock_format_post_call_streaming_hook
* test bedrock guard
* Enhance Mistral API: Add support for parallel tool calls and refine name handling in tool messages. Plus, introduce a new test for parallel tool calls in the Mistral model.
* tests
* make mypy happy
* Refine name handling in Mistral chat transformation: clarify conditions for removing the 'name' field based on message role and content.
* refactor: streamline Mistral integration by removing deprecated references and adding a new handler
- Removed "mistral" from the list of compatible providers in constants.
- Updated the completion function in main.py to utilize the new Mistral handler.
- Deleted outdated Mistral chat and embedding files.
- Introduced a new handler for Mistral chat completions, implementing the llm_http_handler pattern.
- Added integration tests for the Mistral handler to ensure proper API base and key handling.
* lint
* fix: remove unneeded handler object
* add tests
* Addres PR comments
* fix(main.py): handle router custom azure model name for responses api bridge
* fix(responses/handler): ensure azure model name is stripped before sending to provider
Fixes model name error
* fix(google_genai/main.py): handle stream=true being set in kwargs
* docs: cleanup icons from sidebar
* fix(test-litellm.yml): add google-genai to test litellmyml
* fix(main.py): strip 'responses/' from bridge
* fix(main.py): fix linting errors
* fix(types/openai.py): allow item to be none
handle azure streaming response
* fix(base.py): allow extra fields + handle azure item = none value in response output item added event
* fix(main.py): correctly handle removing responses/
* test(test_main.py): add unit tests
When JSON_LOGS=True is set, error logs were not being formatted as JSON despite
the configuration. This was because the logging initialization code configured
individual loggers but failed to properly initialize all loggers with the JSON
formatter.
This fix ensures that when json_logs is enabled, the _initialize_loggers_with_handler()
function is called to:
- Configure all loggers (root, LiteLLM, Router, Proxy) with JSON formatter
- Disable logger propagation to prevent duplicate entries
- Set up exception handlers for JSON formatting
Fixes LIT-267
* add logos to callback list
* added logos
* minor
* cleanup console.log + remove unused functions + prettier
* more cleanup
* fix braintrust logo
* minor
* Enhance Mistral API: Add support for parallel tool calls and refine name handling in tool messages. Plus, introduce a new test for parallel tool calls in the Mistral model.
* tests
* make mypy happy
* Refine name handling in Mistral chat transformation: clarify conditions for removing the 'name' field based on message role and content.
* handle mistral returning '' instead of None
* fix(batches_endpoints/endpoints.py): support passing target model names for batch list as a query param
Fixes issue where cloud run fails calls because GET can't contain request body
* test(test_openai_batches_endpoints.py): add unit test
* docs(managed_batches.md): update docs
* feat(spend_tracking_utils.py): support STORE_PROMPTS_IN_SPEND_LOGS env var
ensures prompt is stored in spend logs
* fix(streaming_iterator.py): fix anthropic - completion streaming iterator to yield content block stop
ensures claude code renders messages
* test: skip local test
* fix(proxy_server.py): only rewrite server_root_path if path set
Fixes UI rendering issue on non-root images
* docs(custom_root_ui.md): clarify custom root path doesn't work on non-root images
* fix - tuple was never falsy so never triggered the exception
* test - add test suite for openmeter integration
* refactor - move tests for openmeter integration
* Move PANW Prisma AIRS test per feedback on PR #12116
- Move test to tests/test_litellm/proxy/guardrails/guardrail_hooks/
* Remove test file from old location
* Fix: Preserve full path structure for Gemini custom api_base (Fixes#11959)
This fix addresses an issue where custom api_base URLs (like Cloudflare AI Gateway)
were not working correctly with Google AI Studio (Gemini) models.
The problem was that the _check_custom_proxy method was simply appending the endpoint
to the custom base URL, resulting in malformed URLs like:
https://gateway.ai.cloudflare.com/v1/my-id/my-gateway/google-ai-studio:generateContent
Instead of the correct format:
https://gateway.ai.cloudflare.com/v1/my-id/my-gateway/google-ai-studio/v1beta/models/gemini-2.5-flash:generateContent
Changes:
- Modified _check_custom_proxy to preserve the full path structure from the original URL
- Extracts the path from the original Google AI URL and appends it to the custom base
- Maintains backward compatibility for Vertex AI models (unchanged behavior)
- Added comprehensive tests to verify the fix works correctly
Fixes#11959
* Fix: Update test to match actual Gemini URL format and fix double colon issue
- Fixed test expectation to include the full model path with 'gemini/' prefix
- Fixed double colon issue in Vertex AI URL construction when using custom api_base
- All tests now pass successfully
Ishaan Jaff