parse_llm_json is explicitly designed to return a list when the model emits a
top-level JSON array (it has a dedicated test for that). The QA analyzers then
call parsed.get("tags", ...) directly on the result. When parsed is a list,
that raises AttributeError, which is NOT caught by the surrounding
except (json.JSONDecodeError, ValueError) — so a single stray array response
from the QA model crashed the entire QA analysis run instead of degrading to
empty results.
The live variable-extraction path already guards this exact case with an
isinstance(..., dict) check; mirror it in both QA analysis call sites
(_run_qa_analysis per-node and _run_whole_call_qa_analysis fallback) so a
non-dict parse result coerces to {} and the run produces empty defaults.
Adds a regression test that drives the whole-call analyzer with an array
response and asserts empty results rather than a crash.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
* feat: add headless widget for deployment
* feat: call callbacks at the right time
* feat: add onCallConnected & onCallDisconnected callback
* feat: add a button with text for floating widget
* feat: add headless widget for deployment
* feat: call callbacks at the right time
* feat: add onCallConnected & onCallDisconnected callback
* feat: add a button with text for floating widget
* docs: web widget
* fix: format issue in pre-pr drift check
* fix: fix CD to rely on pipecat dev dependey
* chore: update message
---------
Co-authored-by: Abhishek Kumar <abhishek@a6k.me>
* chore: bump pipecat version and fix tests
* chore: add github workflow to run tests
* fix: install reqirements.dev.txt in test script
* fix: fix api-test action
* feat: add integration test
* test: add integration tests
* test: add test for function call mute strategy
