Add a `task_completed` function to the agent so when a model finished the task, it can send a signal and the program knows it can go to next agent.
This cl include:
* Implements the `_run_live_impl` in `sequential_agent` so it can handle live case.
* Add an example for sequential agent.
* Improve error message for unimplemented _run_live_impl in other agents.
Note:
1. Compared to non-live case, live agents process a continuous streams of audio
or video, so it doesn't have a native way to tell if it's finished and should pass
to next agent or not. So we introduce a task_compelted() function so the
model can call this function to signal that it's finished the task and we
can move on to next agent.
2. live agents doesn't seems to be very useful or natural in parallel or loop agents so we don't implement it for now. If there is user demand, we can implement it easily using similar approach.
PiperOrigin-RevId: 758315430
The old implementation:
1. We only started transcription at the beginning of agent transferring.
2. The transcription service we used is not as good / fast as the model/native transcription.
In the current implementation, the live agent will rely on the llm's transcription, instead of our transcription when llm support audio transcription in the input. And in that case, the live agent won't use our own audio transcriber. This reduces the latency from 5secs to 2 secs during agent transferring. It also improves the transcription quality.
When the llm doesn't support audio transcription, we still use our audio transcriber to transcribe audio input.
PiperOrigin-RevId: 758296647
Details:
- Add a in-memory SpanExporter to capture all trace information.
- Add /debug/trace/session/{session_id} endpoint to retrieve traces from the in-memory exporter.
- Add Session ID in Telemetry spans.
PiperOrigin-RevId: 757984565
Liang Wu
Google Team Member
Xiang (Sean) Zhou
Selcuk Gun
Ankur Sharma
Hangfei Lin
Yanfei Chen
Yifan Wang