Modified the BaseTextAggregator type so that when text gets aggregated, metadata can
be associated with it. Currently, that just means a `type`, so that the aggregation
can be classified or described. Changes made to support this:
- **IMPORTANT**: Aggregators are now expected to strip leading/trailing white space
characters before returning their aggregation from `aggregation()` or `.text`. This
way all aggregators have a consistent contract allowing downstream use to know how
to stitch aggregations back together
- Introduced a new `Aggregation` dataclass to represent both the aggregated `text` and
a string identifying the `type` of aggregation (ex. "sentence", "word", "my custom
aggregation")
- **BREAKING**: `BaseTextAggregator.text` now returns an `Aggregation` (instead of `str`).
To update: `aggregated_text = myAggregator.text` -> `aggregated_text = myAggregator.text.text`
- **BREAKING**: `BaseTextAggregator.aggregate()` now returns `Optional[Aggregation]`
(instead of `Optional[str]`). To update:
```
aggregation = myAggregator.aggregate(text)
if (aggregation):
print(f"successfully aggregated text: {aggregation.text}") // instead of {aggregation}
```
- `SimpleTextAggregator`, `SkipTagsAggregator`, `PatternPairAggregator` updated to
produce/consume `Aggregation` objects.
- All uses of the above Aggregators have been updated accordingly.
Now:
- For TTS word-by-word output and `TTSSpeakFrames`: `TTSTextFrame`s' have `includes_inter_frame_spaces=False`.
- For all other TTS output: `TTSTextFrame` pass through the received text frames' `includes_inter_frame_spaces` value. So far, this value has always been `True`: LLMs send text chunks already containing all necessary spaces.
- `LLMTextFrame`s set `includes_inter_frame_spaces=False` at init time, per the aforementioned assumption.
* feat: Add ErrorFrame emission to TTS/STT services for pipeline error detection
- Add ErrorFrame emission to all major TTS/STT services during initialization and runtime failures
- Services updated: Cartesia, ElevenLabs, Deepgram, AssemblyAI, Rime, Azure
- ErrorFrame objects emitted with fatal=False for graceful degradation
- Enables on_pipeline_error event handler to detect service failures programmatically
- Add comprehensive pytest test suite to verify ErrorFrame emission
- Fixes issue where services failed gracefully but didn't emit ErrorFrame objects
This allows developers to implement real-time error monitoring and alerting
using the on_pipeline_error event handler introduced in v0.0.90.
* Update STT and TTS services to use consistent error handling pattern
- Improves error handling consistency across all services
* Add changelog entry for STT/TTS error handling improvements
* Linting issues Resolved
* Azure STT ErrorFrames added with consistent patterns
* Cartesia STT and Deepgram STT; additional fixes made
* Removed Fatal Flags across services, removed duplication
* Moving the changelog entry to the correct place.
* Refactoring some classes to use yield instead of push_error directly.
* Fixing ruff format.
---------
Co-authored-by: Filipi Fuchter <filipi87@gmail.com>
- `GoogleHttpTTSService`
- `OpenAITTSService`
The reason I skipped this work in an earlier PR was because these services seemed to be emitting long, punctuation-free text frames. It turns out that the issue was with the LLM prompt, though, resulting in the LLM nondeterministically excluding all punctuation. An upcoming commit will address that prompt issue.
Note that for `LLMTextFrame`s, the right behavior is pretty much always `includes_inter_frame_spaces = True`. I decided *not* to go ahead and make that the default for `LLMTextFrame`s, though, simply to not introduce a subtle behavior change for creative/unexpected use-cases that were relying on text in hand-crafted `LLMTextFrame`s being handled a certain way. Ditto for `TTSTextFrame`s.
Also, fix an issue in `NeuphonicTTSService` where it wasn't pushing `TTSTextFrame`s.
Also, fix the broken `SarvamHttpTTSService` example.
Also, add a couple of missing examples.
