* Fix Langfuse tracing for GoogleLLMService with universal LLMContext
- Fixed issue where input appeared as null in Langfuse dashboard for GoogleLLMService
- Added fallback to use adapter's get_messages_for_logging() for universal LLMContext
- Ensures proper message format conversion for Google/Gemini services
- Handles system message conversion to system_instruction format
- Also fixes serialization of empty message lists ([] now serializes correctly)
This fix ensures Langfuse tracing works correctly for Google services using
both OpenAILLMContext/GoogleLLMContext and the universal LLMContext.
* Add unit tests for Langfuse tracing with GoogleLLMService
- Test that tracing correctly captures messages with universal LLMContext
- Test that empty message lists are properly serialized
- Test that adapter's get_messages_for_logging is used instead of context method
- All tests verify that input is correctly added to Langfuse spans
* Fix test mocking to patch opentelemetry.trace.get_tracer correctly
The tests were failing in CI because they were trying to patch
'pipecat.utils.tracing.service_decorators.trace' which doesn't exist as
an attribute. The trace module is imported from opentelemetry, so we need
to patch 'opentelemetry.trace.get_tracer' instead.
* Skip tracing tests when opentelemetry is not installed
The tracing dependencies (opentelemetry) are optional in Pipecat and not
installed in the CI environment. Added a skipif marker to skip these tests
when opentelemetry is not available, preventing CI failures while still
allowing the tests to run when tracing dependencies are installed locally.
* Install tracing dependencies in GitHub Actions CI
Instead of skipping the tracing tests, install the 'tracing' extra
(opentelemetry) in the CI environment so the tests can run properly.
Removed the skipif condition from the tests since opentelemetry will
now be available in CI.
* Use the context type to determine which messages to use, fix tool_count and tools (#3032)
---------
Co-authored-by: Mark Backman <mark@daily.co>
I chose to go the somewhat hacky route of adding the `ToolsSchema` support into the `events.SessionProperties` model itself—even though we should never serialize that type when creating events—because the alternative seemed to be to create a new type for `OpenAIRealtimeLLMService` initialization parameters and then we'd have to contend with backward compatibility, which seemed like a bigger headache.
