* feat: add ElevenLabs realtime STT provider support (#512)
Wire ElevenLabs scribe_v2_realtime into the STT registry and pipeline factory so BYOK transcribers can use the same provider already supported for TTS.
Co-authored-by: Cursor <cursoragent@cursor.com>
* fix: address ElevenLabs STT review feedback for language, commits, and host
Pass custom language codes through instead of defaulting to English, use ElevenLabs VAD commit strategy because Dograh VAD runs downstream of STT, and document hostname-only realtime base_url handling.
Co-authored-by: Cursor <cursoragent@cursor.com>
* fix: preserve ElevenLabs STT endpoint port in realtime host parsing
Use urlparse netloc instead of hostname so validated BYOK/proxy base URLs keep non-default ports when Pipecat builds the websocket endpoint.
Co-authored-by: Cursor <cursoragent@cursor.com>
* fix: preserve ElevenLabs STT proxy path prefix and remove duplicate tests
Include URL path segments in realtime host normalization for BYOK proxies and delete shadowed pytest definitions.
Co-authored-by: Cursor <cursoragent@cursor.com>
* fix: allow custom ElevenLabs model input
* fix: normalize ElevenLabs websocket URLs
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Co-authored-by: Cursor <cursoragent@cursor.com>
Co-authored-by: Abhishek Kumar <abhishek@a6k.me>
Expose MiniMax-M3 in the MiniMax model suggestions now that the provider integration supports MiniMax chat models.
Co-authored-by: octo-patch <266937838+octo-patch@users.noreply.github.com>
* fix(auth): allow invited org members to start workflow runs
Users invited to an org could not start workflows belonging to that org
because the authorization check compared actor.selected_organization_id
directly against workflow.organization_id. An invited user's selected
org correctly reflects the invited org, but if the Stack Auth token
resolves to a different org id than expected the strict equality fails.
Per api/AGENTS.md: "Whenever you read or write an organization-scoped
field, you must filter or validate by organization_id." The correct
policy is org membership, not selected-org identity.
- Add is_user_member_of_organization() to OrganizationClient; queries
the organization_users association table directly (no lazy-load risk).
- Replace the identity check in authorize_workflow_run_start() with a
membership lookup. Deny when actor_user.id is not in the org's member
set; error_code stays workflow_not_found to avoid leaking existence.
- Update test: rename rejects_actor_from_another_org to
rejects_actor_not_a_member (reflects actual policy), add positive test
allows_invited_member that seeds membership and asserts has_quota=True.
Closes#491
* fix(auth): skip membership check for personal workflows (organization_id=None)
When workflow.organization_id is None (personal or legacy workflow with no
org), the membership lookup was still called, producing a SQL IS NULL
comparison that matched nothing and denied the run.
Guard the check so it only runs when the workflow is org-scoped.
Adds a regression test confirming that an actor with a known id can start a
personal workflow without triggering is_user_member_of_organization.
* fix(auth): fail closed on workflow membership lookup errors
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Co-authored-by: Abhishek Kumar <abhishek@a6k.me>
* feat(tts): add xAI as a Voice (TTS) provider
pipecat already ships an xAI TTS service (XAITTSService, WebSocket
streaming) but dograh never wired it into the service configuration, so
xAI could not be selected as a Voice provider in the cascading pipeline.
Wire it through:
- registry: ServiceProviders.XAI + XAITTSConfiguration (voices
eve/ara/leo/rex/sal, language, computed model) registered in TTSConfig
- service_factory: build XAITTSService in create_tts_service
- check_validity: api-key validation hook
- tests for the factory + docs
The Voice provider dropdown is schema-driven, so xAI appears with no UI
changes.
* fix(tts): validate xAI API key and drop misleading auto-language hint
Addresses review feedback on the xAI Voice provider:
- check_validity: replace the no-op xAI key check with real validation
against xAI's OpenAI-compatible API (models.list on https://api.x.ai/v1),
so a bad BYOK key is caught at configuration time instead of at call time.
- registry: remove the "auto" language hint from the field description.
pipecat's Language enum has no "auto" member, so the factory fell back to
English silently; the description no longer advertises detection we don't do.
- tests: cover xAI key validation (registered, accepts valid, rejects bad).
* fix(tts): validate xAI key against the TTS voices endpoint
xAI supports endpoint-scoped API keys, so a key scoped to Text-to-Speech
may lack the /v1/models ACL and would be wrongly rejected by the previous
models.list() check. Validate against GET /v1/tts/voices instead — the
scope the key actually needs for TTS — treating 401/403 as an invalid key
and connection errors as a clean, actionable message.
* fix: harden xAI TTS integration
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Co-authored-by: Sabiha Khan <sabihak89@gmail.com>
Co-authored-by: Sabiha Khan <87858386+chewwbaka@users.noreply.github.com>
Two call sites dropped the MPS billing-v2 protocol, so orgs on model
config v2 got 400 "Service Key uses billing v2" from MPS:
- text_chat_runner built PipecatEngine without embeddings_provider
(extracted but never passed), so knowledge-base retrieval fell through
to the plain OpenAI-compatible client instead of DograhEmbeddingService
and sent no correlation_id/mps_billing_version metadata. Also pass
endpoint/api_version for Azure BYOK parity with run_pipeline.
- node_summary built its QA LLM without the run's correlation id, unlike
its sibling call in qa/analysis.py.
Co-authored-by: Claude Fable 5 <noreply@anthropic.com>
* fix: gate OSS email/password auth endpoints outside local auth mode
The /auth signup/login/me routes were mounted unconditionally, so the
SaaS deployment accepted unauthenticated signups that created oss_*
provider-id users (and auto-provisioned MPS service keys) bypassing
Stack Auth entirely.
Gate them with a router-level dependency that 404s when AUTH_PROVIDER
is not "local", rather than conditionally mounting the router, so the
OpenAPI spec and the clients generated from it stay identical across
deployment modes.
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
* fix: keep current user route available in stack auth
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Co-authored-by: Claude Fable 5 <noreply@anthropic.com>
* chore: drain active calls before rolling updates
* Use provisional VAD interruption strategy
* feat: wire provisional VAD configuration
* chore: refactor user turn strategies
* chore: bump pipecat
* feat(twilio): add Answering Machine Detection (AMD) support via telephony config
Closes#339
* chore: regenerate OpenAPI spec to fix drift-check
The openapi.json snapshot had drifted from the FastAPI app definition
because main gained new organization endpoints (billing, credits,
context) after this branch was created. Regenerate it with
'python -m scripts.dump_docs_openapi' to bring it back in sync.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
* feat: add provider-level AMD hooks
* fix: handle db error while persisting amd result
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Co-authored-by: Claude Sonnet 4.6 <noreply@anthropic.com>
Co-authored-by: Sabiha Khan <sabihak89@gmail.com>
Co-authored-by: Sabiha Khan <87858386+chewwbaka@users.noreply.github.com>
* fix: disable duplicate trigger nodes in workflow builder
AddNodePanel: disable trigger buttons and show tooltip when a trigger
already exists on the canvas, using bySpecName to identify trigger-
category specs from the live node list.
useWorkflowState: preflight in saveWorkflow rejects saves with multiple
trigger nodes via a sonner toast before the network request is made.
text_chat_session_service: include the original exception message in
TextChatSessionExecutionError so the HTTP 500 detail surfaces the root
cause without DB inspection.
Closes#378
* style: format test_text_chat_session_service.py with ruff
* chore: retrigger CI checks
* fix(workflow): enforce node instance constraints
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Co-authored-by: Abhishek Kumar <abhishek@a6k.me>
* fix(qa): tolerate non-dict JSON from QA LLM instead of crashing
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>
* fix(qa): log non-object QA JSON responses
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Co-authored-by: Claude Opus 4.8 <noreply@anthropic.com>
Co-authored-by: Abhishek Kumar <abhishek@a6k.me>
validate_trigger_paths used seen_paths.get(trigger_path) and treated a None
result as "path not seen yet". But None is also what node.get("id") returns
for a node without an id, so when the first trigger node sharing a path had no
id, it was stored as None and every later node with the same path was silently
accepted as unique — duplicate trigger paths slipped through validation.
Use a membership test (trigger_path not in seen_paths) so "first occurrence"
and "node_id happens to be None" are no longer conflated. Behavior is
unchanged for nodes that have ids.
Adds a regression test that fails before and passes after.
Co-authored-by: Claude Opus 4.8 <noreply@anthropic.com>
Add model_options to SmallestAITTSConfiguration's voice field so the UI
renders the correct voice list per model — 15 standard voices for
lightning_v3.1 and 6 premium voices (meher, rhea, aviraj, cressida,
willow, maverick) for lightning_v3.1_pro. All 21 voice IDs verified
against the Smallest AI API. The frontend's existing model_options
machinery already handles dropdown filtering and auto-reset on model
change, so no UI changes are needed.
* fix: add language field to CartesiaTTSConfiguration and pass to TTS service
Closes#432
* chore: regenerate OpenAPI spec to fix drift-check
The openapi.json snapshot had drifted from the FastAPI app definition
because main gained new organization endpoints (billing, credits,
context) after this branch was created. Regenerate it with
'python -m scripts.dump_docs_openapi' to bring it back in sync.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
* chore: clarify Cartesia language schema
---------
Co-authored-by: Claude Sonnet 4.6 <noreply@anthropic.com>
Co-authored-by: Abhishek Kumar <abhishek@a6k.me>
