Closes old sessions before creating new ones to prevent accumulation. Replaces 'pass' placeholder with asyncio.create_task(old_session.close()) when sessions are recreated due to event loop changes.
Fixes RuntimeError "Session is closed" by:
- Checking session.closed before use and recreating if needed
- Catching RuntimeError during requests and retrying with new session
- Validating newly created sessions aren't already closed
Adds tests for both proactive detection and reactive retry scenarios.
* Fix: Add shared_session to all_litellm_params to prevent JSON serialization error
The shared_session parameter (aiohttp.ClientSession) was being passed through
to provider API calls, causing "Object of type ClientSession is not JSON
serializable" errors during embedding requests.
Added shared_session to the all_litellm_params list so it's properly filtered
out as a LiteLLM-internal parameter and not passed to the provider's API.
* Fix: Add shared_session support for embedding calls with connection pooling
The shared_session parameter was not being properly handled in embedding calls,
causing it to be passed through to provider API requests where it's not needed.
Changes:
- Added shared_session to all_litellm_params to filter it from provider API request body
- Extract shared_session in main embedding() function and pass it explicitly
- Updated OpenAI embedding handlers (embedding() and aembedding()) to accept shared_session
- Pass shared_session to _get_openai_client for HTTP client creation
This enables proper connection pooling for embedding requests when shared_session
is provided, improving performance for high-throughput scenarios.
* test: add regression test for shared_session in embedding calls
Add comprehensive test to prevent JSON serialization errors when using
shared_session.
The test verifies two critical aspects:
1. shared_session is in all_litellm_params to prevent "Object of type
ClientSession is not JSON serializable" errors
2. shared_session flows through the complete call chain across 6 layers:
- litellm.embedding()
- OpenAI.embedding/aembedding()
- _get_openai_client()
- AsyncHTTPHandler.create_client()
- _create_async_transport()
- _create_aiohttp_transport()
Similar to test_acompletion_session_reuse_e2e.py but focused on
embedding endpoints. Uses inspect.getsource() to verify the parameter
is not only accepted but actually passed through each layer.
* fix: preserve lists in SensitiveDataMasker to prevent string conversion
Added 'list' to allowed primitive types in mask_dict() to prevent lists like
tags from being converted to string representations in API responses.
Before: {"tags": "['East US 2', 'production', 'test']"}
After: {"tags": ["East US 2", "production", "test"]}
* add: unit test
* perf: optimize SSL/TLS handshake performance with prioritized cipher suites
Add configurable SSL cipher suite list that strongly prefers fast modern
ciphers (TLS 1.3, ECDHE+GCM) while maintaining backward compatibility with
widely-supported fallback ciphers. Set minimum TLS version to 1.2 for
better performance.
Changes:
- Add DEFAULT_SSL_CIPHERS constant with prioritized cipher list
(configurable via LITELLM_SSL_CIPHERS env var)
- Update get_ssl_configuration() to apply optimized ciphers by default
- Set TLS minimum version to 1.2
- Preserve existing ssl_security_level parameter for custom configs
This balances handshake performance (~50-100ms with modern ciphers) with
broad provider compatibility.
* fix: missing documented constants
- Replace `ResponsesAPIResponse(**raw_response_json)` with
`ResponsesAPIResponse.model_construct(**raw_response_json)`
to bypass strict Pydantic validation.
- Allows Response API to work with self-hosted or non-strict models
(e.g., vLLM) without raising literal/type errors.
- This is a temporary, low-risk relaxation to improve compatibility
with more backend implementations.
