before this change, we estimate the token count of the contents to cache and use it to compare with the threshold user set. but that's not precise , so we use the actual prompt token count of previous llm request.
We won't create cache for the very initial request
PiperOrigin-RevId: 814484840
Currently, the A2A Task -> ADK event conversion is producing the same events on the last two update events (the last is a status update marking the task complete)
The change here based on A2AClientEvent(task, update):
- if the update == None: handle the non-streaming task case and also streaming case for the initial task creation event
- if the update = TaskStatusUpdateEvent AND a message is set: emit an event with that message
- if a task status update AND no message is set: don't emit event (for example, the final status update)
- if the update is ArtifactUpdateEvent and it's final artifact: emit the event
PiperOrigin-RevId: 812878869
Static instructions:
Always added to system instructions for context caching
Dynamic instructions:
Added to system instructions when no static instruction exists (for backward compatibility), OR inserted before last batch of continuous user content when static instructions exist
PiperOrigin-RevId: 809170679
1. add a context cache config in app level which will apply to all agents in the app
2. pass on cache config through invocation context to llm_reqeust
3. store cache metadata in llm_response
4. lookup old cache metadata from latest event for reusing old cache
5. create new cache if old cache cannot be reused
PiperOrigin-RevId: 809158578
The new test verifies that `output_audio_transcription` and `input_audio_transcription` attributes are unique to each `RunConfig` instance, preventing unintended side effects from modifying one instance.
PiperOrigin-RevId: 806405671
Use the A2A Python SDK for client support for A2A Remote clients. This enables A2A based agents that use gRPC or RESTful interfaces, as well as the jsonrpc support. This also simplifies creation of clients and provides simpler mechanisms to inject credentials and observability into the remote agent interactions.
PiperOrigin-RevId: 804711466
This change introduces type descriptions for the functions which convert between A2A and GenAI `Part`s. It then allows passing instances of those functions to the various A2A-related functions/classes, effectively allowing users to inject their own logic for how part conversion should occur.
The benefit of this pattern is that users can create decorators around the core `Part` conversion logic, which allows them to intercept the cases they care about while delegating the ones they do not to the core converter. This is a pattern we use a lot in the A2A Python SDK.
One example where this type of logic is useful is for extensions: this allows extension logic to, for example, interpret an A2A DataPart into a FunctionResponse using extension-specific logic.
PiperOrigin-RevId: 803186799
Before this change, other agent's reply with thought will still be inserted in the outgoing LlmRequest due to the wrong `else` statement for calling all other type of part.
This commit also refactors test_contents.py to be behavior-oriented tests, instead of implementation-oriented, and add more test cases to cover expected scenarios.
The tests are divided into the following files with different focus:
- test_contents.py: covers the basic logic of event filter;
- test_contents_branch.py: covers the behavior related to branch, which takes effect when ParallelAgent is used.
- test_contents_other_agent.py: covers the retelling behavior to include other agents' reply as context for the current agent.
- test_contents_function.py: covers the function_call/function_response rearrangement logic mainly for `LongRunningFunctionTool`.
PiperOrigin-RevId: 802759821
