diff --git a/api/routes/tool.py b/api/routes/tool.py index 80fb45d..ce3d217 100644 --- a/api/routes/tool.py +++ b/api/routes/tool.py @@ -29,6 +29,20 @@ class ToolParameter(BaseModel): ) +class PresetToolParameter(BaseModel): + """A parameter injected by Dograh at runtime.""" + + name: str = Field(description="Parameter name (used as key in request body)") + type: str = Field(description="Parameter type: string, number, or boolean") + value_template: str = Field( + description="Fixed value or template, e.g. {{initial_context.phone_number}}" + ) + required: bool = Field( + default=True, + description="Whether the parameter must resolve to a non-empty value", + ) + + class HttpApiConfig(BaseModel): """Configuration for HTTP API tools.""" @@ -43,6 +57,10 @@ class HttpApiConfig(BaseModel): parameters: Optional[List[ToolParameter]] = Field( default=None, description="Parameters that the tool accepts from LLM" ) + preset_parameters: Optional[List[PresetToolParameter]] = Field( + default=None, + description="Parameters injected by Dograh from fixed values or workflow context templates", + ) timeout_ms: Optional[int] = Field( default=5000, description="Request timeout in milliseconds" ) diff --git a/api/services/campaign/campaign_call_dispatcher.py b/api/services/campaign/campaign_call_dispatcher.py index ffe9a90..ece8cac 100644 --- a/api/services/campaign/campaign_call_dispatcher.py +++ b/api/services/campaign/campaign_call_dispatcher.py @@ -20,8 +20,8 @@ from api.utils.common import get_backend_endpoints if TYPE_CHECKING: # Type-only — importing api.services.telephony eagerly triggers the # provider package init, which can pull in this module via the routes - # chain and create a circular import. Runtime calls below go through - # ``factory.get_telephony_provider`` (lazy import inside the method). + # chain and create a circular import. Runtime calls below lazy-import the + # factory helpers inside methods instead. from api.services.telephony.base import TelephonyProvider @@ -31,12 +31,6 @@ class CampaignCallDispatcher: def __init__(self): self.default_concurrent_limit = int(DEFAULT_ORG_CONCURRENCY_LIMIT) - async def get_telephony_provider(self, organization_id: int) -> "TelephonyProvider": - """Get telephony provider instance for specific organization (default config).""" - from api.services.telephony.factory import get_default_telephony_provider - - return await get_default_telephony_provider(organization_id) - async def get_provider_for_campaign(self, campaign) -> "TelephonyProvider": """Get the telephony provider pinned to this campaign's config. Falls back to the org's default config for legacy campaigns whose diff --git a/api/services/configuration/check_validity.py b/api/services/configuration/check_validity.py index a78434d..ca46cfc 100644 --- a/api/services/configuration/check_validity.py +++ b/api/services/configuration/check_validity.py @@ -49,6 +49,7 @@ class UserConfigurationValidator: ServiceProviders.SPEACHES.value: self._check_speaches_api_key, ServiceProviders.OPENAI_REALTIME.value: self._check_openai_api_key, ServiceProviders.GOOGLE_REALTIME.value: self._check_google_api_key, + ServiceProviders.GOOGLE_VERTEX_REALTIME.value: self._check_google_vertex_realtime_api_key, ServiceProviders.ASSEMBLYAI.value: self._check_assemblyai_api_key, ServiceProviders.GLADIA.value: self._check_gladia_api_key, ServiceProviders.RIME.value: self._check_rime_api_key, @@ -116,6 +117,22 @@ class UserConfigurationValidator: return [{"model": service_name, "message": str(e)}] return [] + # Vertex Realtime uses service-account credentials (or ADC) instead of api_key + if provider == ServiceProviders.GOOGLE_VERTEX_REALTIME.value: + try: + if not self._check_google_vertex_realtime_api_key( + provider, service_config + ): + return [ + { + "model": service_name, + "message": f"Invalid {provider} configuration", + } + ] + except ValueError as e: + return [{"model": service_name, "message": str(e)}] + return [] + # AWS Bedrock uses AWS credentials instead of api_key if provider == ServiceProviders.AWS_BEDROCK.value: try: @@ -216,6 +233,13 @@ class UserConfigurationValidator: raise ValueError("base_url is required for Speaches services") return True + def _check_google_vertex_realtime_api_key(self, model: str, service_config) -> bool: + if not getattr(service_config, "project_id", None): + raise ValueError("project_id is required for Google Vertex Realtime") + if not getattr(service_config, "location", None): + raise ValueError("location is required for Google Vertex Realtime") + return True + def _check_aws_bedrock_api_key(self, model: str, service_config) -> bool: if not service_config.aws_access_key or not service_config.aws_secret_key: raise ValueError("AWS access key and secret key are required for Bedrock") diff --git a/api/services/configuration/registry.py b/api/services/configuration/registry.py index 758a24d..3875fc7 100644 --- a/api/services/configuration/registry.py +++ b/api/services/configuration/registry.py @@ -34,6 +34,7 @@ class ServiceProviders(str, Enum): RIME = "rime" OPENAI_REALTIME = "openai_realtime" GOOGLE_REALTIME = "google_realtime" + GOOGLE_VERTEX_REALTIME = "google_vertex_realtime" class BaseServiceConfiguration(BaseModel): @@ -53,6 +54,7 @@ class BaseServiceConfiguration(BaseModel): ServiceProviders.RIME, ServiceProviders.OPENAI_REALTIME, ServiceProviders.GOOGLE_REALTIME, + ServiceProviders.GOOGLE_VERTEX_REALTIME, # ServiceProviders.SARVAM, ] api_key: str | list[str] @@ -205,6 +207,7 @@ class OpenAILLMService(BaseLLMConfiguration): provider: Literal[ServiceProviders.OPENAI] = ServiceProviders.OPENAI model: str = Field( default="gpt-4.1", + description="OpenAI chat model to use.", json_schema_extra={"examples": OPENAI_MODELS, "allow_custom_input": True}, ) @@ -214,6 +217,7 @@ class GoogleLLMService(BaseLLMConfiguration): provider: Literal[ServiceProviders.GOOGLE] = ServiceProviders.GOOGLE model: str = Field( default="gemini-2.0-flash", + description="Gemini model on Google AI Studio (not Vertex).", json_schema_extra={"examples": GOOGLE_MODELS, "allow_custom_input": True}, ) @@ -223,6 +227,7 @@ class GroqLLMService(BaseLLMConfiguration): provider: Literal[ServiceProviders.GROQ] = ServiceProviders.GROQ model: str = Field( default="llama-3.3-70b-versatile", + description="Groq-hosted model identifier.", json_schema_extra={"examples": GROQ_MODELS, "allow_custom_input": True}, ) @@ -232,10 +237,14 @@ class OpenRouterLLMConfiguration(BaseLLMConfiguration): provider: Literal[ServiceProviders.OPENROUTER] = ServiceProviders.OPENROUTER model: str = Field( default="openai/gpt-4.1", + description="OpenRouter model slug in 'vendor/model' form.", json_schema_extra={"examples": OPENROUTER_MODELS, "allow_custom_input": True}, ) - base_url: str = Field(default="https://openrouter.ai/api/v1") + base_url: str = Field( + default="https://openrouter.ai/api/v1", + description="Override only if proxying OpenRouter through your own gateway.", + ) @register_llm @@ -243,10 +252,13 @@ class AzureLLMService(BaseLLMConfiguration): provider: Literal[ServiceProviders.AZURE] = ServiceProviders.AZURE model: str = Field( default="gpt-4.1-mini", + description="Azure deployment name (not the upstream OpenAI model id).", json_schema_extra={"examples": AZURE_MODELS, "allow_custom_input": True}, ) - endpoint: str + endpoint: str = Field( + description="Azure OpenAI resource endpoint (e.g. https://.openai.azure.com).", + ) @register_llm @@ -254,6 +266,7 @@ class DograhLLMService(BaseLLMConfiguration): provider: Literal[ServiceProviders.DOGRAH] = ServiceProviders.DOGRAH model: str = Field( default="default", + description="Dograh-hosted model tier.", json_schema_extra={"examples": DOGRAH_LLM_MODELS, "allow_custom_input": True}, ) @@ -263,12 +276,25 @@ class AWSBedrockLLMConfiguration(BaseLLMConfiguration): provider: Literal[ServiceProviders.AWS_BEDROCK] = ServiceProviders.AWS_BEDROCK model: str = Field( default="us.amazon.nova-pro-v1:0", + description="Bedrock model ID — include the region inference-profile prefix (e.g. 'us.').", json_schema_extra={"examples": AWS_BEDROCK_MODELS, "allow_custom_input": True}, ) - aws_access_key: str = Field(default="") - aws_secret_key: str = Field(default="") - aws_region: str = Field(default="us-east-1") - api_key: str | list[str] | None = Field(default=None) + aws_access_key: str = Field( + default="", + description="AWS access key ID with bedrock:InvokeModel permission.", + ) + aws_secret_key: str = Field( + default="", + description="AWS secret access key paired with the access key ID.", + ) + aws_region: str = Field( + default="us-east-1", + description="AWS region where the Bedrock model is available.", + ) + api_key: str | list[str] | None = Field( + default=None, + description="Not used for Bedrock — authentication is via the AWS credentials above. Leave blank.", + ) SPEACHES_LLM_MODELS = ["llama3", "mistral", "phi3", "qwen2", "gemma2", "deepseek-r1"] @@ -279,6 +305,7 @@ class SpeachesLLMConfiguration(BaseLLMConfiguration): provider: Literal[ServiceProviders.SPEACHES] = ServiceProviders.SPEACHES model: str = Field( default="llama3", + description="Model name as exposed by your OpenAI-compatible server.", json_schema_extra={ "examples": SPEACHES_LLM_MODELS, "allow_custom_input": True, @@ -286,12 +313,15 @@ class SpeachesLLMConfiguration(BaseLLMConfiguration): ) base_url: str = Field( default="http://localhost:11434/v1", - description="OpenAI-compatible endpoint (Ollama, vLLM, etc.)", + description="OpenAI-compatible endpoint (Ollama, vLLM, etc.).", + ) + api_key: str | list[str] | None = Field( + default=None, + description="Usually not required for self-hosted endpoints. Leave blank unless your server enforces one.", ) - api_key: str | list[str] | None = Field(default=None) -OPENAI_REALTIME_MODELS = ["gpt-4o-realtime-preview", "gpt-4o-mini-realtime-preview"] +OPENAI_REALTIME_MODELS = ["gpt-realtime-2"] OPENAI_REALTIME_VOICES = [ "alloy", "ash", @@ -304,22 +334,27 @@ OPENAI_REALTIME_VOICES = [ ] -# @register_service(ServiceType.REALTIME) -# class OpenAIRealtimeLLMConfiguration(BaseLLMConfiguration): -# provider: Literal[ServiceProviders.OPENAI_REALTIME] = ( -# ServiceProviders.OPENAI_REALTIME -# ) -# model: str = Field( -# default="gpt-4o-realtime-preview", -# json_schema_extra={ -# "examples": OPENAI_REALTIME_MODELS, -# "allow_custom_input": True, -# }, -# ) -# voice: str = Field( -# default="alloy", -# json_schema_extra={"examples": OPENAI_REALTIME_VOICES}, -# ) +@register_service(ServiceType.REALTIME) +class OpenAIRealtimeLLMConfiguration(BaseLLMConfiguration): + provider: Literal[ServiceProviders.OPENAI_REALTIME] = ( + ServiceProviders.OPENAI_REALTIME + ) + model: str = Field( + default="gpt-realtime-2", + description="OpenAI realtime (speech-to-speech) model.", + json_schema_extra={ + "examples": OPENAI_REALTIME_MODELS, + "allow_custom_input": True, + }, + ) + voice: str = Field( + default="alloy", + description="Voice the model speaks in.", + json_schema_extra={ + "examples": OPENAI_REALTIME_VOICES, + "allow_custom_input": True, + }, + ) GOOGLE_REALTIME_MODELS = ["gemini-3.1-flash-live-preview"] @@ -360,6 +395,7 @@ class GoogleRealtimeLLMConfiguration(BaseLLMConfiguration): ) model: str = Field( default="gemini-3.1-flash-live-preview", + description="Gemini Live model on Google AI Studio (not Vertex).", json_schema_extra={ "examples": GOOGLE_REALTIME_MODELS, "allow_custom_input": True, @@ -367,6 +403,7 @@ class GoogleRealtimeLLMConfiguration(BaseLLMConfiguration): ) voice: str = Field( default="Puck", + description="Voice the model speaks in.", json_schema_extra={ "examples": GOOGLE_REALTIME_VOICES, "allow_custom_input": True, @@ -374,6 +411,7 @@ class GoogleRealtimeLLMConfiguration(BaseLLMConfiguration): ) language: str = Field( default="en", + description="ISO 639-1 language code.", json_schema_extra={ "examples": GOOGLE_REALTIME_LANGUAGES, "allow_custom_input": True, @@ -381,9 +419,68 @@ class GoogleRealtimeLLMConfiguration(BaseLLMConfiguration): ) +GOOGLE_VERTEX_REALTIME_MODELS = [ + "google/gemini-live-2.5-flash-native-audio", +] +GOOGLE_VERTEX_REALTIME_VOICES = GOOGLE_REALTIME_VOICES +GOOGLE_VERTEX_REALTIME_LANGUAGES = GOOGLE_REALTIME_LANGUAGES + + +@register_service(ServiceType.REALTIME) +class GoogleVertexRealtimeLLMConfiguration(BaseLLMConfiguration): + provider: Literal[ServiceProviders.GOOGLE_VERTEX_REALTIME] = ( + ServiceProviders.GOOGLE_VERTEX_REALTIME + ) + model: str = Field( + default="google/gemini-live-2.5-flash-native-audio", + description="Vertex AI publisher/model identifier.", + json_schema_extra={ + "examples": GOOGLE_VERTEX_REALTIME_MODELS, + "allow_custom_input": True, + }, + ) + voice: str = Field( + default="Charon", + description="Voice the model speaks in.", + json_schema_extra={ + "examples": GOOGLE_VERTEX_REALTIME_VOICES, + "allow_custom_input": True, + }, + ) + language: str = Field( + default="en", + description="BCP-47 language code (e.g. 'en-US').", + json_schema_extra={ + "examples": GOOGLE_VERTEX_REALTIME_LANGUAGES, + "allow_custom_input": True, + }, + ) + project_id: str = Field(description="Google Cloud project ID for Vertex AI.") + location: str = Field( + default="us-east4", + description="GCP region for the Vertex AI endpoint (e.g. 'us-east4').", + ) + credentials: str | None = Field( + default=None, + description=( + "Paste the entire service-account JSON file contents. If omitted, " + "falls back to Application Default Credentials (ADC)." + ), + json_schema_extra={"multiline": True}, + ) + api_key: str | list[str] | None = Field( + default=None, + description=( + "Not used for Vertex AI — authentication is via the service account " + "in `credentials` (or ADC). Leave blank." + ), + ) + + REALTIME_PROVIDERS = { ServiceProviders.OPENAI_REALTIME.value, ServiceProviders.GOOGLE_REALTIME.value, + ServiceProviders.GOOGLE_VERTEX_REALTIME.value, } @@ -403,8 +500,9 @@ LLMConfig = Annotated[ RealtimeConfig = Annotated[ Union[ - # OpenAIRealtimeLLMConfiguration, + OpenAIRealtimeLLMConfiguration, GoogleRealtimeLLMConfiguration, + GoogleVertexRealtimeLLMConfiguration, ], Field(discriminator="provider"), ] @@ -415,7 +513,10 @@ RealtimeConfig = Annotated[ @register_tts class DeepgramTTSConfiguration(BaseServiceConfiguration): provider: Literal[ServiceProviders.DEEPGRAM] = ServiceProviders.DEEPGRAM - voice: str = "aura-2-helena-en" + voice: str = Field( + default="aura-2-helena-en", + description="Deepgram voice ID (model is inferred from the 'aura-N' prefix).", + ) @computed_field @property @@ -437,10 +538,14 @@ ELEVENLABS_TTS_MODELS = ["eleven_flash_v2_5"] @register_tts class ElevenlabsTTSConfiguration(BaseServiceConfiguration): provider: Literal[ServiceProviders.ELEVENLABS] = ServiceProviders.ELEVENLABS - voice: str = "21m00Tcm4TlvDq8ikWAM" # Rachel voice ID - speed: float = Field(default=1.0, ge=0.1, le=2.0, description="Speed of the voice") + voice: str = Field( + default="21m00Tcm4TlvDq8ikWAM", + description="ElevenLabs voice ID from your Voice Library.", + ) + speed: float = Field(default=1.0, ge=0.1, le=2.0, description="Speed of the voice.") model: str = Field( default="eleven_flash_v2_5", + description="ElevenLabs TTS model.", json_schema_extra={"examples": ELEVENLABS_TTS_MODELS}, ) base_url: str = Field( @@ -460,9 +565,14 @@ OPENAI_TTS_MODELS = ["gpt-4o-mini-tts"] class OpenAITTSService(BaseTTSConfiguration): provider: Literal[ServiceProviders.OPENAI] = ServiceProviders.OPENAI model: str = Field( - default="gpt-4o-mini-tts", json_schema_extra={"examples": OPENAI_TTS_MODELS} + default="gpt-4o-mini-tts", + description="OpenAI TTS model.", + json_schema_extra={"examples": OPENAI_TTS_MODELS}, + ) + voice: str = Field( + default="alloy", + description="OpenAI TTS voice name.", ) - voice: str = "alloy" DOGRAH_TTS_MODELS = ["default"] @@ -472,10 +582,15 @@ DOGRAH_TTS_MODELS = ["default"] class DograhTTSService(BaseTTSConfiguration): provider: Literal[ServiceProviders.DOGRAH] = ServiceProviders.DOGRAH model: str = Field( - default="default", json_schema_extra={"examples": DOGRAH_TTS_MODELS} + default="default", + description="Dograh TTS tier.", + json_schema_extra={"examples": DOGRAH_TTS_MODELS}, ) - voice: str = "default" - speed: float = Field(default=1.0, ge=0.5, le=2.0, description="Speed of the voice") + voice: str = Field( + default="default", + description="Voice preset.", + ) + speed: float = Field(default=1.0, ge=0.5, le=2.0, description="Speed of the voice.") CARTESIA_TTS_MODELS = ["sonic-3"] @@ -485,15 +600,20 @@ CARTESIA_TTS_MODELS = ["sonic-3"] class CartesiaTTSConfiguration(BaseTTSConfiguration): provider: Literal[ServiceProviders.CARTESIA] = ServiceProviders.CARTESIA model: str = Field( - default="sonic-3", json_schema_extra={"examples": CARTESIA_TTS_MODELS} + default="sonic-3", + description="Cartesia TTS model.", + json_schema_extra={"examples": CARTESIA_TTS_MODELS}, ) - voice: str = Field(default="3faa81ae-d3d8-4ab1-9e44-e50e46d33c30") - speed: float = Field(default=1.0, ge=0.6, le=1.5, description="Speed of the voice") + voice: str = Field( + default="3faa81ae-d3d8-4ab1-9e44-e50e46d33c30", + description="Cartesia voice UUID from your Cartesia dashboard.", + ) + speed: float = Field(default=1.0, ge=0.6, le=1.5, description="Speed of the voice.") volume: float = Field( default=1.0, ge=0.5, le=2.0, - description="Volume multiplier for generated speech", + description="Volume multiplier for generated speech.", ) @@ -568,10 +688,13 @@ SARVAM_LANGUAGES = [ class SarvamTTSConfiguration(BaseTTSConfiguration): provider: Literal[ServiceProviders.SARVAM] = ServiceProviders.SARVAM model: str = Field( - default="bulbul:v2", json_schema_extra={"examples": SARVAM_TTS_MODELS} + default="bulbul:v2", + description="Sarvam TTS model (voice list depends on this).", + json_schema_extra={"examples": SARVAM_TTS_MODELS}, ) voice: str = Field( default="anushka", + description="Sarvam voice name; must match the selected model's voice list.", json_schema_extra={ "examples": SARVAM_V2_VOICES, "model_options": { @@ -581,7 +704,9 @@ class SarvamTTSConfiguration(BaseTTSConfiguration): }, ) language: str = Field( - default="hi-IN", json_schema_extra={"examples": SARVAM_LANGUAGES} + default="hi-IN", + description="BCP-47 Indian-language code (e.g. hi-IN, en-IN).", + json_schema_extra={"examples": SARVAM_LANGUAGES}, ) @@ -592,10 +717,12 @@ CAMB_TTS_MODELS = ["mars-flash", "mars-pro", "mars-instruct"] class CambTTSConfiguration(BaseTTSConfiguration): provider: Literal[ServiceProviders.CAMB] = ServiceProviders.CAMB model: str = Field( - default="mars-flash", json_schema_extra={"examples": CAMB_TTS_MODELS} + default="mars-flash", + description="Camb.ai TTS model.", + json_schema_extra={"examples": CAMB_TTS_MODELS}, ) - voice: str = Field(default="147320", description="Camb.ai voice ID") - language: str = Field(default="en-us", description="BCP-47 language code") + voice: str = Field(default="147320", description="Camb.ai voice ID.") + language: str = Field(default="en-us", description="BCP-47 language code.") RIME_TTS_MODELS = ["arcana", "mistv3", "mistv2", "mist"] @@ -607,17 +734,19 @@ class RimeTTSConfiguration(BaseTTSConfiguration): provider: Literal[ServiceProviders.RIME] = ServiceProviders.RIME model: str = Field( default="arcana", + description="Rime TTS model.", json_schema_extra={"examples": RIME_TTS_MODELS, "allow_custom_input": True}, ) voice: str = Field( default="celeste", - description="Rime voice ID", + description="Rime voice ID.", ) speed: float = Field( - default=1.0, ge=0.5, le=2.0, description="Speech speed multiplier" + default=1.0, ge=0.5, le=2.0, description="Speech speed multiplier." ) language: str = Field( default="en", + description="ISO 639-1 language code.", json_schema_extra={"examples": RIME_TTS_LANGUAGES, "allow_custom_input": True}, ) @@ -630,6 +759,7 @@ class SpeachesTTSConfiguration(BaseTTSConfiguration): provider: Literal[ServiceProviders.SPEACHES] = ServiceProviders.SPEACHES model: str = Field( default="kokoro", + description="Model name as served by your TTS endpoint (e.g. Kokoro-FastAPI).", json_schema_extra={ "examples": SPEACHES_TTS_MODELS, "allow_custom_input": True, @@ -638,16 +768,19 @@ class SpeachesTTSConfiguration(BaseTTSConfiguration): voice: str = Field( default="af_heart", json_schema_extra={"allow_custom_input": True}, - description="Voice ID for the TTS engine", + description="Voice ID for the TTS engine.", ) base_url: str = Field( default="http://localhost:8000/v1", - description="OpenAI-compatible TTS endpoint (Kokoro-FastAPI, etc.)", + description="OpenAI-compatible TTS endpoint (Kokoro-FastAPI, etc.).", ) speed: float = Field( - default=1.0, ge=0.25, le=4.0, description="Speech speed (0.25 to 4.0)" + default=1.0, ge=0.25, le=4.0, description="Speech speed (0.25 to 4.0)." + ) + api_key: str | list[str] | None = Field( + default=None, + description="Usually not required for self-hosted TTS. Leave blank unless enforced.", ) - api_key: str | list[str] | None = Field(default=None) TTSConfig = Annotated[ @@ -758,10 +891,13 @@ DEEPGRAM_LANGUAGES = [ class DeepgramSTTConfiguration(BaseSTTConfiguration): provider: Literal[ServiceProviders.DEEPGRAM] = ServiceProviders.DEEPGRAM model: str = Field( - default="nova-3-general", json_schema_extra={"examples": DEEPGRAM_STT_MODELS} + default="nova-3-general", + description="Deepgram STT model.", + json_schema_extra={"examples": DEEPGRAM_STT_MODELS}, ) language: str = Field( default="multi", + description="Language code; 'multi' enables auto-detect (Nova-3 only).", json_schema_extra={ "examples": DEEPGRAM_LANGUAGES, "model_options": { @@ -779,7 +915,9 @@ CARTESIA_STT_MODELS = ["ink-whisper"] class CartesiaSTTConfiguration(BaseSTTConfiguration): provider: Literal[ServiceProviders.CARTESIA] = ServiceProviders.CARTESIA model: str = Field( - default="ink-whisper", json_schema_extra={"examples": CARTESIA_STT_MODELS} + default="ink-whisper", + description="Cartesia STT model.", + json_schema_extra={"examples": CARTESIA_STT_MODELS}, ) @@ -790,7 +928,9 @@ OPENAI_STT_MODELS = ["gpt-4o-transcribe"] class OpenAISTTConfiguration(BaseSTTConfiguration): provider: Literal[ServiceProviders.OPENAI] = ServiceProviders.OPENAI model: str = Field( - default="gpt-4o-transcribe", json_schema_extra={"examples": OPENAI_STT_MODELS} + default="gpt-4o-transcribe", + description="OpenAI transcription model.", + json_schema_extra={"examples": OPENAI_STT_MODELS}, ) @@ -803,10 +943,14 @@ DOGRAH_STT_LANGUAGES = DEEPGRAM_LANGUAGES class DograhSTTService(BaseSTTConfiguration): provider: Literal[ServiceProviders.DOGRAH] = ServiceProviders.DOGRAH model: str = Field( - default="default", json_schema_extra={"examples": DOGRAH_STT_MODELS} + default="default", + description="Dograh STT tier.", + json_schema_extra={"examples": DOGRAH_STT_MODELS}, ) language: str = Field( - default="multi", json_schema_extra={"examples": DOGRAH_STT_LANGUAGES} + default="multi", + description="Language code; use 'multi' for auto-detect.", + json_schema_extra={"examples": DOGRAH_STT_LANGUAGES}, ) @@ -818,10 +962,14 @@ SARVAM_STT_MODELS = ["saarika:v2.5", "saaras:v2"] class SarvamSTTConfiguration(BaseSTTConfiguration): provider: Literal[ServiceProviders.SARVAM] = ServiceProviders.SARVAM model: str = Field( - default="saarika:v2.5", json_schema_extra={"examples": SARVAM_STT_MODELS} + default="saarika:v2.5", + description="Sarvam STT model.", + json_schema_extra={"examples": SARVAM_STT_MODELS}, ) language: str = Field( - default="hi-IN", json_schema_extra={"examples": SARVAM_LANGUAGES} + default="hi-IN", + description="BCP-47 Indian-language code.", + json_schema_extra={"examples": SARVAM_LANGUAGES}, ) @@ -857,10 +1005,13 @@ SPEECHMATICS_STT_LANGUAGES = [ class SpeechmaticsSTTConfiguration(BaseSTTConfiguration): provider: Literal[ServiceProviders.SPEECHMATICS] = ServiceProviders.SPEECHMATICS model: str = Field( - default="enhanced", description="Operating point: standard or enhanced" + default="enhanced", + description="Speechmatics operating point: 'standard' or 'enhanced'.", ) language: str = Field( - default="en", json_schema_extra={"examples": SPEECHMATICS_STT_LANGUAGES} + default="en", + description="ISO 639-1 language code.", + json_schema_extra={"examples": SPEECHMATICS_STT_LANGUAGES}, ) @@ -876,6 +1027,7 @@ class SpeachesSTTConfiguration(BaseSTTConfiguration): provider: Literal[ServiceProviders.SPEACHES] = ServiceProviders.SPEACHES model: str = Field( default="Systran/faster-distil-whisper-small.en", + description="Whisper model identifier as served by your STT endpoint.", json_schema_extra={ "examples": SPEACHES_STT_MODELS, "allow_custom_input": True, @@ -883,6 +1035,7 @@ class SpeachesSTTConfiguration(BaseSTTConfiguration): ) language: str = Field( default="en", + description="ISO 639-1 language code.", json_schema_extra={ "examples": SPEACHES_STT_LANGUAGES, "allow_custom_input": True, @@ -890,9 +1043,12 @@ class SpeachesSTTConfiguration(BaseSTTConfiguration): ) base_url: str = Field( default="http://localhost:8000/v1", - description="OpenAI-compatible STT endpoint (Speaches, etc.)", + description="OpenAI-compatible STT endpoint (Speaches, etc.).", + ) + api_key: str | list[str] | None = Field( + default=None, + description="Usually not required for self-hosted STT. Leave blank unless enforced.", ) - api_key: str | list[str] | None = Field(default=None) ASSEMBLYAI_STT_MODELS = ["u3-rt-pro"] @@ -904,10 +1060,12 @@ class AssemblyAISTTConfiguration(BaseSTTConfiguration): provider: Literal[ServiceProviders.ASSEMBLYAI] = ServiceProviders.ASSEMBLYAI model: str = Field( default="u3-rt-pro", + description="AssemblyAI realtime STT model.", json_schema_extra={"examples": ASSEMBLYAI_STT_MODELS}, ) language: str = Field( default="en", + description="ISO 639-1 language code.", json_schema_extra={"examples": ASSEMBLYAI_STT_LANGUAGES}, ) @@ -1022,10 +1180,12 @@ class GladiaSTTConfiguration(BaseSTTConfiguration): provider: Literal[ServiceProviders.GLADIA] = ServiceProviders.GLADIA model: str = Field( default="solaria-1", + description="Gladia STT model.", json_schema_extra={"examples": GLADIA_STT_MODELS}, ) language: str = Field( default="en", + description="ISO 639-1 language code.", json_schema_extra={"examples": GLADIA_STT_LANGUAGES}, ) @@ -1055,6 +1215,7 @@ class OpenAIEmbeddingsConfiguration(BaseEmbeddingsConfiguration): provider: Literal[ServiceProviders.OPENAI] = ServiceProviders.OPENAI model: str = Field( default="text-embedding-3-small", + description="OpenAI embedding model.", json_schema_extra={"examples": OPENAI_EMBEDDING_MODELS}, ) @@ -1067,10 +1228,14 @@ class OpenRouterEmbeddingsConfiguration(BaseEmbeddingsConfiguration): provider: Literal[ServiceProviders.OPENROUTER] = ServiceProviders.OPENROUTER model: str = Field( default="openai/text-embedding-3-small", + description="OpenRouter-hosted embedding model slug.", json_schema_extra={"examples": OPENROUTER_EMBEDDING_MODELS}, ) - base_url: str = Field(default="https://openrouter.ai/api/v1") + base_url: str = Field( + default="https://openrouter.ai/api/v1", + description="Override only if proxying OpenRouter through your own gateway.", + ) EmbeddingsConfig = Annotated[ diff --git a/api/services/pipecat/realtime/__init__.py b/api/services/pipecat/realtime/__init__.py new file mode 100644 index 0000000..cd346c1 --- /dev/null +++ b/api/services/pipecat/realtime/__init__.py @@ -0,0 +1,9 @@ +"""Dograh-specific subclasses of pipecat realtime LLM services. + +Each subclass wires Dograh engine integration quirks (user-mute gating, +TTSSpeakFrame greeting trigger, node-transition handling, function-call +deferral, etc.) onto the corresponding pipecat realtime service. + +The pipecat fork's services stay close to upstream — Dograh behavior lives +here. +""" diff --git a/api/services/pipecat/realtime/gemini_live.py b/api/services/pipecat/realtime/gemini_live.py new file mode 100644 index 0000000..abcc3ea --- /dev/null +++ b/api/services/pipecat/realtime/gemini_live.py @@ -0,0 +1,237 @@ +"""Dograh subclass of pipecat's Gemini Live LLM service. + +Layers Dograh engine integration quirks onto upstream-pristine +:class:`GeminiLiveLLMService`: + +- **Deferred connect.** Connection is held back until ``system_instruction`` + is set via :meth:`_update_settings`, so pre-call-fetch template variables + land before the live session opens. +- **Reconnect on node transitions.** Gemini Live cannot update + ``system_instruction`` mid-session, so a setting change triggers a + reconnect (deferred until the bot turn ends if currently responding). +- **Function-call deferral.** Tool calls emitted mid-turn are queued and run + when the bot stops speaking, to avoid racing the turn's audio. +- **User-mute audio gating.** ``UserMuteStarted/StoppedFrame`` from the + user aggregator gates whether incoming audio is forwarded to Gemini. +- **TTSSpeakFrame as greeting trigger.** The engine queues a TTSSpeakFrame + to kick off the first response after node setup; the service intercepts + it and runs the initial-context path. +- **Finalize-pending on transcriptions.** Marks the transcription emitted + immediately after VAD-stop as finalized, distinguishing it from + mid-turn partials. +""" + +from typing import Any + +from loguru import logger + +from pipecat.frames.frames import ( + BotStoppedSpeakingFrame, + Frame, + TranscriptionFrame, + TTSSpeakFrame, + UserMuteStartedFrame, + UserMuteStoppedFrame, +) +from pipecat.processors.aggregators.llm_context import LLMContext +from pipecat.processors.frame_processor import FrameDirection +from pipecat.services.google.gemini_live.llm import GeminiLiveLLMService +from pipecat.services.llm_service import FunctionCallFromLLM +from pipecat.utils.time import time_now_iso8601 +from pipecat.utils.tracing.service_decorators import traced_gemini_live + + +class DograhGeminiLiveLLMService(GeminiLiveLLMService): + """Gemini Live with Dograh engine integration quirks. See module docstring.""" + + def __init__(self, **kwargs): + super().__init__(**kwargs) + # User-mute state, driven by broadcast UserMute{Started,Stopped}Frames. + # Audio is not forwarded to Gemini while muted. + self._user_is_muted: bool = False + # Guards initial-response triggering against double-firing across the + # initial TTSSpeakFrame and any LLMContextFrame that may arrive. + self._handled_initial_context: bool = False + # When a system_instruction change arrives mid-bot-turn, the reconnect + # is queued and drained when the turn ends. + self._reconnect_pending: bool = False + # Function calls emitted by Gemini mid-bot-turn are deferred here and + # invoked when the turn ends, so they don't race the turn's audio. + self._pending_function_calls: list[FunctionCallFromLLM] = [] + # Tracks whether the next transcription to arrive should be marked as + # the finalized transcription for the current user turn. + self._finalize_pending: bool = False + + # ------------------------------------------------------------------ + # Hooks from upstream GeminiLiveLLMService + # ------------------------------------------------------------------ + + def _should_connect_on_start(self) -> bool: + # Hold the connection until the engine sets a system_instruction. This + # lets pre-call fetch populate template variables first. + return bool(self._settings.system_instruction) + + async def _handle_changed_settings(self, changed: dict[str, Any]) -> set[str]: + if "system_instruction" not in changed: + return set() + if not self._session: + # First-time setting after deferred-connect. + await self._connect() + elif self._bot_is_responding: + # Bot is mid-turn — drain the reconnect when it ends so we don't + # cut the bot off mid-utterance. + self._reconnect_pending = True + else: + await self._reconnect() + return {"system_instruction"} + + async def _run_or_defer_function_calls( + self, function_calls_llm: list[FunctionCallFromLLM] + ): + if self._bot_is_responding: + # Latest batch wins; Gemini emits tool calls as one batch per + # tool_call message, so this overwrite is intentional. + self._pending_function_calls = function_calls_llm + logger.debug( + f"{self}: deferring {len(function_calls_llm)} function call(s) " + "until bot turn ends" + ) + return + await super()._run_or_defer_function_calls(function_calls_llm) + + # ------------------------------------------------------------------ + # State-transition side effects + # ------------------------------------------------------------------ + + async def _set_bot_is_responding(self, responding: bool): + was_responding = self._bot_is_responding + await super()._set_bot_is_responding(responding) + if was_responding and not responding: + await self._run_pending_function_calls() + if self._reconnect_pending: + self._reconnect_pending = False + await self._reconnect() + + async def _run_pending_function_calls(self): + """Run any function calls deferred during the bot's last turn.""" + if not self._pending_function_calls: + return + fcs = self._pending_function_calls + self._pending_function_calls = [] + logger.debug( + f"{self}: executing {len(fcs)} deferred function call(s) " + "after bot turn ended" + ) + await self.run_function_calls(fcs) + + # ------------------------------------------------------------------ + # Frame handling: mute, TTSSpeakFrame, BotStoppedSpeakingFrame flush + # ------------------------------------------------------------------ + + async def process_frame(self, frame: Frame, direction: FrameDirection): + if isinstance(frame, UserMuteStartedFrame): + self._user_is_muted = True + await self.push_frame(frame, direction) + return + if isinstance(frame, UserMuteStoppedFrame): + self._user_is_muted = False + await self.push_frame(frame, direction) + return + if isinstance(frame, TTSSpeakFrame): + # Greeting trigger: the engine queues a TTSSpeakFrame to start the + # bot's first turn after node setup. Gemini Live renders its own + # audio, so we don't pass the frame through — we re-enter + # _handle_context to kick off the initial response. + if not self._handled_initial_context: + await self._handle_context(self._context) + else: + logger.warning( + f"{self}: TTSSpeakFrame after initial context already " + "handled — Gemini Live owns audio generation, ignoring" + ) + return + if isinstance(frame, BotStoppedSpeakingFrame): + # Belt-and-suspenders: the main drain happens in + # _set_bot_is_responding(False), but if Gemini delays turn_complete + # past the audible end of the turn, flushing here ensures pending + # function calls fire promptly. + await self._run_pending_function_calls() + # Fall through to super for the actual push. + await super().process_frame(frame, direction) + + async def _send_user_audio(self, frame): + if self._user_is_muted: + return + await super()._send_user_audio(frame) + + # ------------------------------------------------------------------ + # Context lifecycle: Dograh pre-populates self._context via the engine, + # so upstream's "first arrival === self._context is None" check doesn't + # work. We gate on _handled_initial_context instead and skip the + # init-instruction reconciliation (Dograh updates system_instruction at + # runtime via _update_settings, not via init). + # ------------------------------------------------------------------ + + async def _handle_context(self, context: LLMContext): + if not self._handled_initial_context: + self._handled_initial_context = True + self._context = context + await self._create_initial_response() + else: + self._context = context + await self._process_completed_function_calls(send_new_results=True) + + # ------------------------------------------------------------------ + # Session lifecycle: drop upstream's automatic reconnect-seed and + # initial-context-seed paths. The TTSSpeakFrame trigger and the + # function-call-result LLMContextFrame are the only paths that should + # kick off bot turns in the Dograh flow. + # ------------------------------------------------------------------ + + @traced_gemini_live(operation="llm_setup") + async def _handle_session_ready(self, session): + logger.debug( + f"In _handle_session_ready self._run_llm_when_session_ready: {self._run_llm_when_session_ready}" + ) + self._session = session + self._ready_for_realtime_input = True + if self._run_llm_when_session_ready: + # Context arrived before session was ready — fulfil the queued + # initial response now. + self._run_llm_when_session_ready = False + await self._create_initial_response() + await self._drain_pending_tool_results() + # Otherwise: no automatic seed. Reconnect after a session-resumption + # update relies on the server-side restored state; reconnects without + # a handle (e.g. node transitions before any handle was issued) are + # followed by a function-call-result LLMContextFrame which feeds the + # updated-context branch in _handle_context. + + # ------------------------------------------------------------------ + # Transcription: broadcast (so downstream voicemail detector and + # logs buffer both see it) and set finalized= for turn-boundary + # semantics. + # ------------------------------------------------------------------ + + async def _handle_user_started_speaking(self, frame): + await super()._handle_user_started_speaking(frame) + # A new VAD start invalidates any pending finalize from a prior stop + # that hasn't been paired with a transcription yet. + self._finalize_pending = False + + async def _handle_user_stopped_speaking(self, frame): + await super()._handle_user_stopped_speaking(frame) + self._finalize_pending = True + + async def _push_user_transcription(self, text: str, result=None): + await self._handle_user_transcription(text, True, self._settings.language) + finalized = self._finalize_pending + self._finalize_pending = False + await self.broadcast_frame( + TranscriptionFrame, + text=text, + user_id="", + timestamp=time_now_iso8601(), + result=result, + finalized=finalized, + ) diff --git a/api/services/pipecat/realtime/gemini_live_vertex.py b/api/services/pipecat/realtime/gemini_live_vertex.py new file mode 100644 index 0000000..06dfa44 --- /dev/null +++ b/api/services/pipecat/realtime/gemini_live_vertex.py @@ -0,0 +1,42 @@ +"""Dograh subclass of pipecat's Gemini Live Vertex AI LLM service. + +Diamond inheritance: combines the Dograh engine-integration overrides from +:class:`DograhGeminiLiveLLMService` with the Vertex-specific tweaks from +upstream's :class:`GeminiLiveVertexLLMService` (no history config, +``NON_BLOCKING`` tools disabled, service-account credentials). + +MRO:: + + DograhGeminiLiveVertexLLMService + -> DograhGeminiLiveLLMService + -> GeminiLiveVertexLLMService + -> GeminiLiveLLMService + -> LLMService + -> ... +""" + +from api.services.pipecat.realtime.gemini_live import DograhGeminiLiveLLMService +from pipecat.services.google.gemini_live.vertex.llm import ( + GeminiLiveVertexLLMService, +) + + +class DograhGeminiLiveVertexLLMService( + DograhGeminiLiveLLMService, + GeminiLiveVertexLLMService, +): + """Vertex AI variant of Gemini Live with Dograh integration quirks.""" + + pass + + +# Guard against MRO regressions: a future refactor that flips inheritance +# order or breaks the diamond would silently bypass the Dograh overrides. +_mro = DograhGeminiLiveVertexLLMService.__mro__ +assert _mro[1] is DograhGeminiLiveLLMService, ( + f"Expected DograhGeminiLiveLLMService at MRO[1], got {_mro[1]}" +) +assert _mro[2] is GeminiLiveVertexLLMService, ( + f"Expected GeminiLiveVertexLLMService at MRO[2], got {_mro[2]}" +) +del _mro diff --git a/api/services/pipecat/realtime/openai_realtime.py b/api/services/pipecat/realtime/openai_realtime.py new file mode 100644 index 0000000..8822c06 --- /dev/null +++ b/api/services/pipecat/realtime/openai_realtime.py @@ -0,0 +1,274 @@ +"""Dograh subclass of pipecat's OpenAI Realtime LLM service. + +Layers Dograh engine integration quirks onto upstream-pristine +:class:`OpenAIRealtimeLLMService`. Substantially smaller than the Gemini +subclass because OpenAI Realtime supports runtime ``session.update`` for +both ``system_instruction`` and tools — no reconnect/defer-tool-call +machinery needed. + +Adds: + +- **User-mute audio gating** via ``UserMuteStarted/StoppedFrame``. +- **TTSSpeakFrame as initial-response trigger** so the engine's greeting + flow kicks off the bot's first response. +- **One-off LLMMessagesAppendFrame handling** for ephemeral realtime prompts + like user-idle checks, without mutating Dograh's local ``LLMContext``. +- **finalized=True on TranscriptionFrame** for parity with the Gemini + service (every OpenAI transcription via the ``completed`` event is + final by construction). +""" + +import json +from typing import Any + +from loguru import logger + +from pipecat.frames.frames import ( + BotStartedSpeakingFrame, + BotStoppedSpeakingFrame, + Frame, + LLMFullResponseStartFrame, + LLMMessagesAppendFrame, + TranscriptionFrame, + TTSSpeakFrame, + UserMuteStartedFrame, + UserMuteStoppedFrame, +) +from pipecat.processors.aggregators.llm_context import LLMContext +from pipecat.processors.frame_processor import FrameDirection +from pipecat.services.llm_service import FunctionCallFromLLM +from pipecat.services.openai.realtime import events +from pipecat.services.openai.realtime.llm import OpenAIRealtimeLLMService +from pipecat.transcriptions.language import Language +from pipecat.utils.time import time_now_iso8601 + + +class DograhOpenAIRealtimeLLMService(OpenAIRealtimeLLMService): + """OpenAI Realtime with Dograh engine integration quirks. See module docstring.""" + + def __init__(self, **kwargs): + super().__init__(**kwargs) + self._user_is_muted: bool = False + # Dograh pre-populates self._context via the engine before the first + # LLMContextFrame arrives, so upstream's "first arrival means + # self._context is None" check no longer works. + self._handled_initial_context: bool = False + # Track bot speech locally so tool calls can be deferred until the bot + # has finished speaking, matching Dograh's Gemini Live behavior. + self._bot_is_speaking: bool = False + self._deferred_function_calls: list[FunctionCallFromLLM] = [] + + # ------------------------------------------------------------------ + # Frame handling: mute, TTSSpeakFrame as greeting trigger + # ------------------------------------------------------------------ + + async def process_frame(self, frame: Frame, direction: FrameDirection): + if isinstance(frame, UserMuteStartedFrame): + self._user_is_muted = True + await self.push_frame(frame, direction) + return + if isinstance(frame, UserMuteStoppedFrame): + self._user_is_muted = False + await self.push_frame(frame, direction) + return + if isinstance(frame, TTSSpeakFrame): + # Greeting trigger: the engine queues a TTSSpeakFrame after node + # setup. OpenAI Realtime renders its own audio, so we don't pass + # the frame to TTS. Route through _handle_context so the initial + # response and later tool-result turns share the same context + # lifecycle even when Dograh has already pre-populated self._context. + if not self._handled_initial_context: + await self._handle_context(self._context) + else: + logger.warning( + f"{self}: TTSSpeakFrame after initial context already " + "handled — OpenAI Realtime owns audio generation, ignoring" + ) + # Don't forward the frame; the audio path is owned by the realtime + # service itself. + return + if isinstance(frame, LLMMessagesAppendFrame): + await self._handle_messages_append(frame) + return + if isinstance(frame, BotStartedSpeakingFrame): + self._bot_is_speaking = True + elif isinstance(frame, BotStoppedSpeakingFrame): + self._bot_is_speaking = False + await self._run_pending_function_calls() + await super().process_frame(frame, direction) + + async def _handle_messages_append(self, frame: LLMMessagesAppendFrame): + """Consume a one-off append frame without mutating the local LLMContext.""" + if self._disconnecting: + return + + if not self._api_session_ready: + if frame.run_llm: + logger.debug( + f"{self}: LLMMessagesAppendFrame received before session ready; " + "deferring response until the session is initialized" + ) + self._run_llm_when_api_session_ready = True + return + + appended_any = False + for message in frame.messages: + item = self._message_to_conversation_item(message) + if item is None: + continue + evt = events.ConversationItemCreateEvent(item=item) + self._messages_added_manually[evt.item.id] = True + await self.send_client_event(evt) + appended_any = True + + if frame.run_llm and appended_any: + await self._send_manual_response_create() + + async def _handle_context(self, context: LLMContext): + if not self._handled_initial_context: + if context is None: + logger.warning( + f"{self}: received initial context trigger before context was set" + ) + return + self._handled_initial_context = True + self._context = context + await self._create_response() + else: + self._context = context + await self._process_completed_function_calls(send_new_results=True) + + async def _send_user_audio(self, frame): + if self._user_is_muted: + return + await super()._send_user_audio(frame) + + def _message_to_conversation_item( + self, message: dict[str, Any] + ) -> events.ConversationItem | None: + if not isinstance(message, dict): + logger.warning( + f"{self}: skipping unsupported appended message payload {message!r}" + ) + return None + + role = message.get("role") + if role not in {"user", "system", "developer"}: + logger.warning( + f"{self}: skipping unsupported appended message role {role!r}" + ) + return None + + text = self._extract_text_content(message.get("content")) + if not text: + logger.warning( + f"{self}: skipping appended message with unsupported content {message!r}" + ) + return None + + item_role = "system" if role in {"system", "developer"} else "user" + return events.ConversationItem( + type="message", + role=item_role, + content=[events.ItemContent(type="input_text", text=text)], + ) + + @staticmethod + def _extract_text_content(content: Any) -> str | None: + if isinstance(content, str): + return content + if isinstance(content, list): + parts: list[str] = [] + for part in content: + if not isinstance(part, dict): + return None + if part.get("type") != "text": + return None + text = part.get("text") + if not isinstance(text, str): + return None + parts.append(text) + return "\n".join(parts) if parts else None + return None + + async def _send_manual_response_create(self): + """Trigger inference after manually appending conversation items.""" + await self.push_frame(LLMFullResponseStartFrame()) + await self.start_processing_metrics() + await self.start_ttfb_metrics() + await self.send_client_event( + events.ResponseCreateEvent( + response=events.ResponseProperties( + output_modalities=self._get_enabled_modalities() + ) + ) + ) + + async def _run_pending_function_calls(self): + if not self._deferred_function_calls: + return + function_calls = self._deferred_function_calls + self._deferred_function_calls = [] + logger.debug( + f"{self}: executing {len(function_calls)} deferred function call(s) " + "after bot turn ended" + ) + await self.run_function_calls(function_calls) + + async def _handle_evt_function_call_arguments_done(self, evt): + """Process or defer tool calls until the bot finishes speaking.""" + try: + args = json.loads(evt.arguments) + + function_call_item = self._pending_function_calls.get(evt.call_id) + if function_call_item: + del self._pending_function_calls[evt.call_id] + + function_calls = [ + FunctionCallFromLLM( + context=self._context, + tool_call_id=evt.call_id, + function_name=function_call_item.name, + arguments=args, + ) + ] + + if self._bot_is_speaking: + self._deferred_function_calls.extend(function_calls) + logger.debug( + f"{self}: deferring function call {function_call_item.name} " + "until bot stops speaking" + ) + else: + await self.run_function_calls(function_calls) + logger.debug(f"Processed function call: {function_call_item.name}") + else: + logger.warning( + f"No tracked function call found for call_id: {evt.call_id}" + ) + logger.warning( + f"Available pending calls: {list(self._pending_function_calls.keys())}" + ) + + except Exception as e: + logger.error(f"Failed to process function call arguments: {e}") + + # ------------------------------------------------------------------ + # Transcription: broadcast with finalized=True for parity with the + # Gemini service (consumers that check `finalized` should see True + # for every completed-transcription event from OpenAI). + # ------------------------------------------------------------------ + + async def handle_evt_input_audio_transcription_completed(self, evt): + await self._call_event_handler( + "on_conversation_item_updated", evt.item_id, None + ) + await self.broadcast_frame( + TranscriptionFrame, + text=evt.transcript, + user_id="", + timestamp=time_now_iso8601(), + result=evt, + finalized=True, + ) + await self._handle_user_transcription(evt.transcript, True, Language.EN) diff --git a/api/services/pipecat/run_pipeline.py b/api/services/pipecat/run_pipeline.py index b29f225..8bfda23 100644 --- a/api/services/pipecat/run_pipeline.py +++ b/api/services/pipecat/run_pipeline.py @@ -86,6 +86,43 @@ from pipecat.utils.run_context import set_current_org_id, set_current_run_id ensure_tracing() +def _create_realtime_user_turn_config(provider: str): + """Return user turn strategies and optional local VAD for realtime providers.""" + if provider in { + ServiceProviders.GOOGLE_REALTIME.value, + ServiceProviders.GOOGLE_VERTEX_REALTIME.value, + }: + # Let Gemini Live own barge-in via its server-side VAD, but keep local + # Silero VAD for early user-turn start and speaking-state tracking. + return ( + UserTurnStrategies( + start=[VADUserTurnStartStrategy(enable_interruptions=False)], + stop=[SpeechTimeoutUserTurnStopStrategy()], + ), + SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + ) + + if provider == ServiceProviders.OPENAI_REALTIME.value: + # OpenAI Realtime already emits speaking-state frames and interruption + # events from the provider, so the aggregator should follow those + # external signals rather than run its own local VAD. + return ( + UserTurnStrategies( + start=[ExternalUserTurnStartStrategy()], + stop=[ExternalUserTurnStopStrategy()], + ), + None, + ) + + return ( + UserTurnStrategies( + start=[VADUserTurnStartStrategy()], + stop=[SpeechTimeoutUserTurnStopStrategy()], + ), + SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + ) + + async def run_pipeline_telephony( websocket, *, @@ -138,6 +175,20 @@ async def run_pipeline_telephony( "telephony_configuration_id" ) + # Resolve effective user config here so the transport can tune its + # bot-stopped-speaking fallback based on is_realtime; pass the resolved + # values into _run_pipeline so it doesn't fetch them again. + from api.services.configuration.resolve import resolve_effective_config + + user_config = await db_client.get_user_configurations(user_id) + run_configs = ( + (workflow_run.definition.workflow_configurations or {}) if workflow_run else {} + ) + user_config = resolve_effective_config( + user_config, run_configs.get("model_overrides") + ) + is_realtime = bool(user_config.is_realtime and user_config.realtime is not None) + spec = telephony_registry.get(provider_name) audio_config = create_audio_config(provider_name) @@ -148,6 +199,7 @@ async def run_pipeline_telephony( workflow.organization_id, ambient_noise_config=ambient_noise_config, telephony_configuration_id=telephony_configuration_id, + is_realtime=is_realtime, **transport_kwargs, ) @@ -158,6 +210,8 @@ async def run_pipeline_telephony( workflow_run_id, user_id, audio_config=audio_config, + workflow_run=workflow_run, + resolved_user_config=user_config, ) except Exception as e: logger.error( @@ -198,11 +252,27 @@ async def run_pipeline_smallwebrtc( # Create audio configuration for WebRTC audio_config = create_audio_config(WorkflowRunMode.SMALLWEBRTC.value) + # Resolve workflow_run + effective user_config here so the transport can + # tune its bot-stopped-speaking fallback based on is_realtime. _run_pipeline + # reuses these via kwargs so we don't fetch twice. + from api.services.configuration.resolve import resolve_effective_config + + workflow_run = await db_client.get_workflow_run(workflow_run_id, user_id) + user_config = await db_client.get_user_configurations(user_id) + run_configs = ( + (workflow_run.definition.workflow_configurations or {}) if workflow_run else {} + ) + user_config = resolve_effective_config( + user_config, run_configs.get("model_overrides") + ) + is_realtime = bool(user_config.is_realtime and user_config.realtime is not None) + transport = await create_webrtc_transport( webrtc_connection, workflow_run_id, audio_config, ambient_noise_config, + is_realtime=is_realtime, ) await _run_pipeline( transport, @@ -212,6 +282,8 @@ async def run_pipeline_smallwebrtc( call_context_vars=call_context_vars, audio_config=audio_config, user_provider_id=user_provider_id, + workflow_run=workflow_run, + resolved_user_config=user_config, ) @@ -223,6 +295,8 @@ async def _run_pipeline( call_context_vars: dict = {}, audio_config: AudioConfig = None, user_provider_id: str | None = None, + workflow_run=None, + resolved_user_config=None, ) -> None: """ Run the pipeline with the given transport and configuration @@ -232,9 +306,12 @@ async def _run_pipeline( workflow_id: The ID of the workflow workflow_run_id: The ID of the workflow run user_id: The ID of the user - mode: The mode of the pipeline (twilio or smallwebrtc) + workflow_run: Pre-fetched workflow run row. Fetched here if None. + resolved_user_config: User configuration with model_overrides already + applied. Fetched and resolved here if None. """ - workflow_run = await db_client.get_workflow_run(workflow_run_id, user_id) + if workflow_run is None: + workflow_run = await db_client.get_workflow_run(workflow_run_id, user_id) # If the workflow run is already completed, we don't need to run it again if workflow_run.is_completed: @@ -246,9 +323,6 @@ async def _run_pipeline( if call_context_vars: merged_call_context_vars = {**merged_call_context_vars, **call_context_vars} - # Get user configuration - user_config = await db_client.get_user_configurations(user_id) - # Get workflow for metadata (name, organization_id, call_disposition_codes) workflow = await db_client.get_workflow(workflow_id, user_id) if not workflow: @@ -286,11 +360,17 @@ async def _run_pipeline( term.strip() for term in dictionary.split(",") if term.strip() ] - # Resolve model overrides from the version onto global user config - from api.services.configuration.resolve import resolve_effective_config + # Resolve model overrides from the version onto global user config (skip + # when the caller already resolved it). + if resolved_user_config is None: + from api.services.configuration.resolve import resolve_effective_config - model_overrides = run_configs.get("model_overrides") - user_config = resolve_effective_config(user_config, model_overrides) + user_config = await db_client.get_user_configurations(user_id) + user_config = resolve_effective_config( + user_config, run_configs.get("model_overrides") + ) + else: + user_config = resolved_user_config # Detect realtime mode (speech-to-speech services like OpenAI Realtime, Gemini Live) is_realtime = user_config.is_realtime and user_config.realtime is not None @@ -453,23 +533,20 @@ async def _run_pipeline( correct_aggregation_callback=engine.create_aggregation_correction_callback(), ) + user_mute_strategies = [ + MuteUntilFirstBotCompleteUserMuteStrategy(), + FunctionCallUserMuteStrategy(), + CallbackUserMuteStrategy(should_mute_callback=engine.should_mute_user), + ] + user_vad_analyzer = SileroVADAnalyzer(params=VADParams(stop_secs=0.2)) + # Configure turn strategies based on STT provider, model, and workflow configuration if is_realtime: - # Realtime services do server-side turn detection for response generation, - # but we still need a client-side stop strategy so the user aggregator emits - # UserStoppedSpeakingFrame. Without it, downstream consumers (e.g. voicemail - # detector) and Gemini Live's _finalize_pending flag never see a turn end. - user_turn_strategies = UserTurnStrategies( - start=[VADUserTurnStartStrategy()], - stop=[SpeechTimeoutUserTurnStopStrategy()], + # Realtime services still need user-turn tracking even when the model + # itself owns speech generation and interruption behavior. + user_turn_strategies, user_vad_analyzer = _create_realtime_user_turn_config( + user_config.realtime.provider ) - - # Lets not start the pipeline as muted for Realtime - # - CallbackUserMuteStrategy: mutes based on engine's _mute_pipeline state - user_mute_strategies = [ - FunctionCallUserMuteStrategy(), - CallbackUserMuteStrategy(should_mute_callback=engine.should_mute_user), - ] else: # Deepgram Flux uses external turn detection (VAD + External start/stop) # Other models use configurable turn detection strategy @@ -510,18 +587,11 @@ async def _run_pipeline( stop=[SpeechTimeoutUserTurnStopStrategy()], ) - # - CallbackUserMuteStrategy: mutes based on engine's _mute_pipeline state - user_mute_strategies = [ - MuteUntilFirstBotCompleteUserMuteStrategy(), - FunctionCallUserMuteStrategy(), - CallbackUserMuteStrategy(should_mute_callback=engine.should_mute_user), - ] - user_params = LLMUserAggregatorParams( user_turn_strategies=user_turn_strategies, user_mute_strategies=user_mute_strategies, user_idle_timeout=max_user_idle_timeout, - vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)), + vad_analyzer=user_vad_analyzer, ) context_aggregator = LLMContextAggregatorPair( context, assistant_params=assistant_params, user_params=user_params @@ -562,15 +632,14 @@ async def _run_pipeline( ) engine.set_fetch_recording_audio(fetch_audio) - # Voicemail detection works in both modes. In realtime mode the detector sits - # after the realtime LLM and consumes the TranscriptionFrames it broadcasts; - # the LLM gate / TTS gate are not used (the realtime LLM responds to audio - # directly, not LLMContextFrames), so on detection we rely on - # end_call_with_reason to drop the call. voicemail_config = (workflow.workflow_configurations or {}).get( "voicemail_detection", {} ) - if voicemail_config.get("enabled", False): + if is_realtime and voicemail_config.get("enabled", False): + logger.info( + f"Disabling voicemail detection for realtime workflow run {workflow_run_id}" + ) + if voicemail_config.get("enabled", False) and not is_realtime: logger.info(f"Voicemail detection enabled for workflow run {workflow_run_id}") # Create a separate LLM instance for the voicemail sub-pipeline # (can't share with main pipeline as it would mess up frame linking) diff --git a/api/services/pipecat/service_factory.py b/api/services/pipecat/service_factory.py index dcd5841..eb058fb 100644 --- a/api/services/pipecat/service_factory.py +++ b/api/services/pipecat/service_factory.py @@ -493,6 +493,9 @@ def create_realtime_llm_service(user_config, audio_config: "AudioConfig"): ) if provider == ServiceProviders.OPENAI_REALTIME.value: + from api.services.pipecat.realtime.openai_realtime import ( + DograhOpenAIRealtimeLLMService, + ) from pipecat.services.openai.realtime.events import ( AudioConfiguration, AudioInput, @@ -500,11 +503,10 @@ def create_realtime_llm_service(user_config, audio_config: "AudioConfig"): InputAudioTranscription, SessionProperties, ) - from pipecat.services.openai.realtime.llm import OpenAIRealtimeLLMService - return OpenAIRealtimeLLMService( + return DograhOpenAIRealtimeLLMService( api_key=api_key, - settings=OpenAIRealtimeLLMService.Settings( + settings=DograhOpenAIRealtimeLLMService.Settings( model=model, session_properties=SessionProperties( audio=AudioConfiguration( @@ -519,7 +521,9 @@ def create_realtime_llm_service(user_config, audio_config: "AudioConfig"): ), ) elif provider == ServiceProviders.GOOGLE_REALTIME.value: - from pipecat.services.google.gemini_live.llm import GeminiLiveLLMService + from api.services.pipecat.realtime.gemini_live import ( + DograhGeminiLiveLLMService, + ) # Gemini Live enables input/output audio transcription by default # in its _connect() method — no need to configure it explicitly. @@ -529,9 +533,30 @@ def create_realtime_llm_service(user_config, audio_config: "AudioConfig"): } if language: settings_kwargs["language"] = language - return GeminiLiveLLMService( + return DograhGeminiLiveLLMService( api_key=api_key, - settings=GeminiLiveLLMService.Settings(**settings_kwargs), + settings=DograhGeminiLiveLLMService.Settings(**settings_kwargs), + ) + elif provider == ServiceProviders.GOOGLE_VERTEX_REALTIME.value: + from api.services.pipecat.realtime.gemini_live_vertex import ( + DograhGeminiLiveVertexLLMService, + ) + + project_id = getattr(realtime_config, "project_id", None) + location = getattr(realtime_config, "location", None) or "us-east4" + credentials = getattr(realtime_config, "credentials", None) + + settings_kwargs = { + "model": model, + "voice": voice or "Charon", + } + if language: + settings_kwargs["language"] = language + return DograhGeminiLiveVertexLLMService( + credentials=credentials, + project_id=project_id, + location=location, + settings=DograhGeminiLiveVertexLLMService.Settings(**settings_kwargs), ) else: raise HTTPException( diff --git a/api/services/pipecat/transport_params.py b/api/services/pipecat/transport_params.py new file mode 100644 index 0000000..d206b20 --- /dev/null +++ b/api/services/pipecat/transport_params.py @@ -0,0 +1,25 @@ +"""Shared helpers for tuning pipecat ``TransportParams`` per run mode. + +These live outside ``transport_setup.py`` (which is non-telephony only) so +that both the WebRTC factory there and the telephony provider factories +under ``api.services.telephony.providers//transport.py`` can call +into the same place. +""" + +# Realtime (speech-to-speech) LLMs don't emit ``TTSStoppedFrame``, so the +# bot-stopped-speaking signal relies on the output-queue-drained fallback. +# The default 3s tail leaves a long gap before the assistant aggregator +# closes its turn; 0.5s keeps the conversation snappy without cutting into +# the bot's own audio (audio chunks arrive far more frequently than this). +REALTIME_BOT_VAD_STOP_SECS = 0.5 + + +def realtime_param_overrides(is_realtime: bool) -> dict: + """Return kwargs to splat into ``TransportParams`` for the given run mode. + + Currently this only tunes ``bot_vad_stop_secs``; new realtime-specific + knobs should be added here so each transport stays a thin shim. + """ + if not is_realtime: + return {} + return {"bot_vad_stop_secs": REALTIME_BOT_VAD_STOP_SECS} diff --git a/api/services/pipecat/transport_setup.py b/api/services/pipecat/transport_setup.py index 195c661..c5a4fca 100644 --- a/api/services/pipecat/transport_setup.py +++ b/api/services/pipecat/transport_setup.py @@ -6,6 +6,7 @@ This module hosts only the shared, non-telephony transports (WebRTC). from api.services.pipecat.audio_config import AudioConfig from api.services.pipecat.audio_mixer import build_audio_out_mixer +from api.services.pipecat.transport_params import realtime_param_overrides from pipecat.transports.base_transport import TransportParams from pipecat.transports.smallwebrtc.connection import SmallWebRTCConnection from pipecat.transports.smallwebrtc.transport import SmallWebRTCTransport @@ -16,6 +17,7 @@ async def create_webrtc_transport( workflow_run_id: int, audio_config: AudioConfig, ambient_noise_config: dict | None = None, + is_realtime: bool = False, ): """Create a transport for WebRTC connections.""" mixer = await build_audio_out_mixer( @@ -30,5 +32,6 @@ async def create_webrtc_transport( audio_in_sample_rate=audio_config.transport_in_sample_rate, audio_out_sample_rate=audio_config.transport_out_sample_rate, audio_out_mixer=mixer, + **realtime_param_overrides(is_realtime), ), ) diff --git a/api/services/pricing/workflow_run_cost.py b/api/services/pricing/workflow_run_cost.py index 1380312..2c86dc6 100644 --- a/api/services/pricing/workflow_run_cost.py +++ b/api/services/pricing/workflow_run_cost.py @@ -27,7 +27,9 @@ async def _fetch_telephony_cost(workflow_run) -> dict | None: logger.warning("Workflow not found for workflow run") raise Exception("Workflow not found") - provider = await get_telephony_provider_for_run(workflow_run, workflow.organization_id) + provider = await get_telephony_provider_for_run( + workflow_run, workflow.organization_id + ) call_cost_info = await provider.get_call_cost(call_id) if call_cost_info.get("status") == "error": diff --git a/api/services/telephony/README.md b/api/services/telephony/README.md index 812b864..37c113b 100644 --- a/api/services/telephony/README.md +++ b/api/services/telephony/README.md @@ -13,10 +13,16 @@ Business Logic → TelephonyProvider (Interface) → Concrete Provider (Twilio, ### Using the Provider in Code ```python -from api.services.telephony.factory import get_telephony_provider +from api.services.telephony.factory import ( + get_default_telephony_provider, + get_telephony_provider_by_id, +) -# Get provider based on organization config -provider = await get_telephony_provider(organization_id) +# Get the org's default outbound provider +provider = await get_default_telephony_provider(organization_id) + +# Or resolve a specific telephony configuration row +provider = await get_telephony_provider_by_id(config_id, organization_id) # Initiate a call result = await provider.initiate_call( @@ -47,7 +53,7 @@ See the [Custom Provider Guide](https://docs.dograh.com/integrations/telephony/c Quick checklist: 1. Create `providers/your_provider.py` implementing `TelephonyProvider` -2. Update `factory.py` to include your provider +2. Register the package in `providers/__init__.py` and add its schemas to `api/schemas/telephony_config.py` 3. Write unit tests 4. Update documentation @@ -107,7 +113,7 @@ class MockProvider(TelephonyProvider): # Implement other required methods... # In tests -@patch('api.services.telephony.factory.get_telephony_provider') +@patch('api.services.telephony.factory.get_default_telephony_provider') async def test_call_initiation(mock_get_provider): mock_get_provider.return_value = MockProvider() # Test your business logic @@ -141,8 +147,8 @@ await service.initiate_call(...) New code: ```python -from api.services.telephony.factory import get_telephony_provider -provider = await get_telephony_provider(org_id) +from api.services.telephony.factory import get_default_telephony_provider +provider = await get_default_telephony_provider(org_id) await provider.initiate_call(...) ``` @@ -164,4 +170,4 @@ await provider.initiate_call(...) - [User Documentation](https://docs.dograh.com/integrations/telephony/overview) - [Twilio Integration](https://docs.dograh.com/integrations/telephony/twilio) - [Custom Providers](https://docs.dograh.com/integrations/telephony/custom) -- [Webhooks Guide](https://docs.dograh.com/integrations/telephony/webhooks) \ No newline at end of file +- [Webhooks Guide](https://docs.dograh.com/integrations/telephony/webhooks) diff --git a/api/services/telephony/factory.py b/api/services/telephony/factory.py index cb2a702..5147a16 100644 --- a/api/services/telephony/factory.py +++ b/api/services/telephony/factory.py @@ -6,9 +6,7 @@ resolution paths exist: * by config id — the canonical path used by outbound (test calls, campaigns, API triggers) and by the websocket transport once a workflow run has ``initial_context.telephony_configuration_id`` stamped on it. -* by org default — used as a fallback when no specific config is requested - (e.g. the legacy ``/telephony-config`` endpoint, the back-compat - ``get_telephony_provider(organization_id)`` shim). +* by org default — used as a fallback when no specific config is requested. * for inbound — given a detected provider and an account-id from the webhook, iterate the org's configs of that provider and return the one whose stored account-id credential matches. @@ -196,28 +194,6 @@ async def load_credentials_for_transport( return config -# --------------------------------------------------------------------------- -# Back-compat shims -# --------------------------------------------------------------------------- - - -async def load_telephony_config(organization_id: int) -> Dict[str, Any]: - """Deprecated: returns the org's default config. - - Existing callers that don't carry a config id continue to work via this - shim. New code should pass an explicit telephony_configuration_id.""" - return await load_default_telephony_config(organization_id) - - -async def get_telephony_provider(organization_id: int) -> TelephonyProvider: - """Deprecated: returns a provider for the org's default config. - - See ``load_telephony_config`` above. New code should call - ``get_telephony_provider_by_id`` with the resolved config id. - """ - return await get_default_telephony_provider(organization_id) - - async def get_all_telephony_providers() -> List[Type[TelephonyProvider]]: """All registered provider classes — used by inbound webhook detection.""" return [spec.provider_cls for spec in registry.all_specs()] diff --git a/api/services/telephony/providers/CLAUDE.md b/api/services/telephony/providers/CLAUDE.md index 4db70d8..df634eb 100644 --- a/api/services/telephony/providers/CLAUDE.md +++ b/api/services/telephony/providers/CLAUDE.md @@ -28,7 +28,7 @@ If you find yourself editing anything else, re-read the registry plumbing first: | Want to change... | Source of truth | | --- | --- | -| Outbound provider lookup | `factory.get_telephony_provider*` reads `registry.get(name).provider_cls` | +| Outbound provider lookup | `factory.get_default_telephony_provider`, `get_telephony_provider_by_id`, and `get_telephony_provider_for_run` read `registry.get(name).provider_cls` | | Stored credentials → constructor dict | `ProviderSpec.config_loader` | | Audio sample rate / VAD rate | `ProviderSpec.transport_sample_rate` (full `AudioConfig` is built in `pipecat/audio_config.py::create_audio_config`) | | Which transport runs in `run_pipeline_telephony` | `ProviderSpec.transport_factory` | diff --git a/api/services/telephony/providers/ari/transport.py b/api/services/telephony/providers/ari/transport.py index 58efea5..53cfd92 100644 --- a/api/services/telephony/providers/ari/transport.py +++ b/api/services/telephony/providers/ari/transport.py @@ -8,6 +8,7 @@ from pipecat.transports.websocket.fastapi import ( from api.services.pipecat.audio_config import AudioConfig from api.services.pipecat.audio_mixer import build_audio_out_mixer +from api.services.pipecat.transport_params import realtime_param_overrides from api.services.telephony.factory import load_credentials_for_transport from .serializers import AsteriskFrameSerializer @@ -22,6 +23,7 @@ async def create_transport( *, ambient_noise_config: dict | None = None, telephony_configuration_id: int | None = None, + is_realtime: bool = False, channel_id: str, ): """Create a transport for Asterisk ARI connections.""" @@ -65,5 +67,6 @@ async def create_transport( audio_out_sample_rate=audio_config.transport_out_sample_rate, audio_out_mixer=mixer, serializer=serializer, + **realtime_param_overrides(is_realtime), ), ) diff --git a/api/services/telephony/providers/cloudonix/transport.py b/api/services/telephony/providers/cloudonix/transport.py index cd91518..c38c975 100644 --- a/api/services/telephony/providers/cloudonix/transport.py +++ b/api/services/telephony/providers/cloudonix/transport.py @@ -8,6 +8,7 @@ from pipecat.transports.websocket.fastapi import ( from api.services.pipecat.audio_config import AudioConfig from api.services.pipecat.audio_mixer import build_audio_out_mixer +from api.services.pipecat.transport_params import realtime_param_overrides from api.services.telephony.factory import load_credentials_for_transport from .serializers import CloudonixFrameSerializer @@ -22,6 +23,7 @@ async def create_transport( *, ambient_noise_config: dict | None = None, telephony_configuration_id: int | None = None, + is_realtime: bool = False, call_id: str, stream_sid: str, bearer_token: str | None = None, @@ -69,5 +71,6 @@ async def create_transport( audio_out_mixer=mixer, serializer=serializer, audio_out_10ms_chunks=2, + **realtime_param_overrides(is_realtime), ), ) diff --git a/api/services/telephony/providers/plivo/transport.py b/api/services/telephony/providers/plivo/transport.py index 039c562..d9cd04f 100644 --- a/api/services/telephony/providers/plivo/transport.py +++ b/api/services/telephony/providers/plivo/transport.py @@ -8,6 +8,7 @@ from pipecat.transports.websocket.fastapi import ( from api.services.pipecat.audio_config import AudioConfig from api.services.pipecat.audio_mixer import build_audio_out_mixer +from api.services.pipecat.transport_params import realtime_param_overrides from api.services.telephony.factory import load_credentials_for_transport from .serializers import PlivoFrameSerializer @@ -21,6 +22,7 @@ async def create_transport( *, ambient_noise_config: dict | None = None, telephony_configuration_id: int | None = None, + is_realtime: bool = False, stream_id: str, call_id: str, ): @@ -61,5 +63,6 @@ async def create_transport( audio_out_sample_rate=audio_config.transport_out_sample_rate, audio_out_mixer=mixer, serializer=serializer, + **realtime_param_overrides(is_realtime), ), ) diff --git a/api/services/telephony/providers/telnyx/transport.py b/api/services/telephony/providers/telnyx/transport.py index 393e688..189a741 100644 --- a/api/services/telephony/providers/telnyx/transport.py +++ b/api/services/telephony/providers/telnyx/transport.py @@ -8,6 +8,7 @@ from pipecat.transports.websocket.fastapi import ( from api.services.pipecat.audio_config import AudioConfig from api.services.pipecat.audio_mixer import build_audio_out_mixer +from api.services.pipecat.transport_params import realtime_param_overrides from api.services.telephony.factory import load_credentials_for_transport from .serializers import TelnyxFrameSerializer @@ -22,6 +23,7 @@ async def create_transport( *, ambient_noise_config: dict | None = None, telephony_configuration_id: int | None = None, + is_realtime: bool = False, stream_id: str, call_control_id: str, encoding: str = "PCMU", @@ -64,5 +66,6 @@ async def create_transport( audio_out_sample_rate=audio_config.transport_out_sample_rate, audio_out_mixer=mixer, serializer=serializer, + **realtime_param_overrides(is_realtime), ), ) diff --git a/api/services/telephony/providers/twilio/transport.py b/api/services/telephony/providers/twilio/transport.py index d3a4937..6c3f744 100644 --- a/api/services/telephony/providers/twilio/transport.py +++ b/api/services/telephony/providers/twilio/transport.py @@ -8,6 +8,7 @@ from pipecat.transports.websocket.fastapi import ( from api.services.pipecat.audio_config import AudioConfig from api.services.pipecat.audio_mixer import build_audio_out_mixer +from api.services.pipecat.transport_params import realtime_param_overrides from api.services.telephony.factory import load_credentials_for_transport from .serializers import TwilioFrameSerializer @@ -22,6 +23,7 @@ async def create_transport( *, ambient_noise_config: dict | None = None, telephony_configuration_id: int | None = None, + is_realtime: bool = False, stream_sid: str, call_sid: str, ): @@ -60,5 +62,6 @@ async def create_transport( audio_out_sample_rate=audio_config.transport_out_sample_rate, audio_out_mixer=mixer, serializer=serializer, + **realtime_param_overrides(is_realtime), ), ) diff --git a/api/services/telephony/providers/vobiz/transport.py b/api/services/telephony/providers/vobiz/transport.py index 46ac392..96ee333 100644 --- a/api/services/telephony/providers/vobiz/transport.py +++ b/api/services/telephony/providers/vobiz/transport.py @@ -14,6 +14,7 @@ from pipecat.transports.websocket.fastapi import ( from api.services.pipecat.audio_config import AudioConfig from api.services.pipecat.audio_mixer import build_audio_out_mixer +from api.services.pipecat.transport_params import realtime_param_overrides from api.services.telephony.factory import load_credentials_for_transport from .serializers import VobizFrameSerializer @@ -27,6 +28,7 @@ async def create_transport( *, ambient_noise_config: dict | None = None, telephony_configuration_id: int | None = None, + is_realtime: bool = False, stream_id: str, call_id: str, ): @@ -72,6 +74,7 @@ async def create_transport( audio_out_sample_rate=audio_config.transport_out_sample_rate, audio_out_mixer=mixer, serializer=serializer, + **realtime_param_overrides(is_realtime), ), ) diff --git a/api/services/telephony/providers/vonage/transport.py b/api/services/telephony/providers/vonage/transport.py index 0fae27f..f50398d 100644 --- a/api/services/telephony/providers/vonage/transport.py +++ b/api/services/telephony/providers/vonage/transport.py @@ -7,6 +7,7 @@ from pipecat.transports.websocket.fastapi import ( from api.services.pipecat.audio_config import AudioConfig from api.services.pipecat.audio_mixer import build_audio_out_mixer +from api.services.pipecat.transport_params import realtime_param_overrides from api.services.telephony.factory import load_credentials_for_transport from .serializers import VonageFrameSerializer @@ -20,6 +21,7 @@ async def create_transport( *, ambient_noise_config: dict | None = None, telephony_configuration_id: int | None = None, + is_realtime: bool = False, call_uuid: str, ): """Create a transport for Vonage connections.""" @@ -59,5 +61,6 @@ async def create_transport( audio_out_sample_rate=audio_config.transport_out_sample_rate, audio_out_mixer=mixer, serializer=serializer, + **realtime_param_overrides(is_realtime), ), ) diff --git a/api/services/telephony/registry.py b/api/services/telephony/registry.py index 4ecf6d7..48546b1 100644 --- a/api/services/telephony/registry.py +++ b/api/services/telephony/registry.py @@ -81,8 +81,8 @@ class ProviderSpec: stored config JSON and as the WorkflowRunMode value. provider_cls: The TelephonyProvider subclass. config_loader: Normalizes raw stored config into the dict shape the - provider constructor expects. Replaces the if/elif chain in the - old factory.load_telephony_config(). + provider constructor expects. Replaces the old factory if/elif + chain. transport_factory: Async callable that creates the pipecat transport for an accepted WebSocket. Provider-specific kwargs (stream_sid, call_sid, etc.) are forwarded as ``**kwargs``. diff --git a/api/services/workflow/pipecat_engine_custom_tools.py b/api/services/workflow/pipecat_engine_custom_tools.py index 844cc10..90eed7e 100644 --- a/api/services/workflow/pipecat_engine_custom_tools.py +++ b/api/services/workflow/pipecat_engine_custom_tools.py @@ -321,6 +321,7 @@ class CustomToolManager: tool=tool, arguments=function_call_params.arguments, call_context_vars=self._engine._call_context_vars, + gathered_context_vars=self._engine._gathered_context, organization_id=await self.get_organization_id(), ) diff --git a/api/services/workflow/tools/custom_tool.py b/api/services/workflow/tools/custom_tool.py index da8775b..626610f 100644 --- a/api/services/workflow/tools/custom_tool.py +++ b/api/services/workflow/tools/custom_tool.py @@ -1,5 +1,6 @@ """Custom tool execution for user-defined HTTP API tools.""" +import json import re from typing import Any, Dict, Optional @@ -8,6 +9,7 @@ from loguru import logger from api.db import db_client from api.utils.credential_auth import build_auth_header +from api.utils.template_renderer import render_template # Map tool parameter types to JSON schema types TYPE_MAP = { @@ -84,10 +86,94 @@ def tool_to_function_schema(tool: Any) -> Dict[str, Any]: } +def _coerce_parameter_value(value: Any, param_type: str) -> Any: + """Coerce a rendered preset parameter into the configured JSON type.""" + + if value is None: + return None + + if param_type == "string": + if isinstance(value, str): + return value + if isinstance(value, (dict, list)): + return json.dumps(value) + return str(value) + + if param_type == "number": + if isinstance(value, (int, float)) and not isinstance(value, bool): + return value + + rendered = str(value).strip() + if rendered == "": + return None + + if re.fullmatch(r"[-+]?\d+", rendered): + return int(rendered) + + return float(rendered) + + if param_type == "boolean": + if isinstance(value, bool): + return value + + if isinstance(value, (int, float)): + return bool(value) + + rendered = str(value).strip().lower() + if rendered in {"true", "1", "yes", "y", "on"}: + return True + if rendered in {"false", "0", "no", "n", "off"}: + return False + + raise ValueError(f"Cannot convert '{value}' to boolean") + + return value + + +def _resolve_preset_parameters( + config: Dict[str, Any], + call_context_vars: Optional[Dict[str, Any]], + gathered_context_vars: Optional[Dict[str, Any]], +) -> Dict[str, Any]: + """Resolve fixed/template-backed parameters before executing the HTTP request.""" + + preset_parameters = config.get("preset_parameters", []) or [] + if not preset_parameters: + return {} + + initial_context = dict(call_context_vars or {}) + render_context: Dict[str, Any] = { + **initial_context, + "initial_context": initial_context, + "gathered_context": dict(gathered_context_vars or {}), + } + + resolved: Dict[str, Any] = {} + for param in preset_parameters: + param_name = (param.get("name") or "").strip() + if not param_name: + continue + + rendered = render_template(param.get("value_template", ""), render_context) + if rendered in (None, ""): + if param.get("required", True): + raise ValueError( + f"Preset parameter '{param_name}' resolved to an empty value" + ) + continue + + resolved[param_name] = _coerce_parameter_value( + rendered, param.get("type", "string") + ) + + return resolved + + async def execute_http_tool( tool: Any, arguments: Dict[str, Any], call_context_vars: Optional[Dict[str, Any]] = None, + gathered_context_vars: Optional[Dict[str, Any]] = None, organization_id: Optional[int] = None, ) -> Dict[str, Any]: """Execute an HTTP API tool. @@ -95,7 +181,8 @@ async def execute_http_tool( Args: tool: ToolModel instance arguments: Arguments passed by the LLM (parameter name -> value) - call_context_vars: Additional context variables from the call (unused for now) + call_context_vars: Initial context variables available at runtime + gathered_context_vars: Variables extracted during the conversation organization_id: Organization ID for credential lookup Returns: @@ -133,17 +220,31 @@ async def execute_http_tool( timeout_ms = config.get("timeout_ms", 5000) timeout_seconds = timeout_ms / 1000 + try: + preset_arguments = _resolve_preset_parameters( + config, call_context_vars, gathered_context_vars + ) + except ValueError as e: + logger.error(f"Custom tool '{tool.name}' preset parameter error: {e}") + return {"status": "error", "error": str(e)} + + resolved_arguments = {**(arguments or {}), **preset_arguments} + # Build request: JSON body for POST/PUT/PATCH, query params for GET/DELETE body = None params = None if method in ("POST", "PUT", "PATCH"): - body = arguments - elif method in ("GET", "DELETE") and arguments: - params = arguments + body = resolved_arguments + elif method in ("GET", "DELETE") and resolved_arguments: + params = resolved_arguments logger.info( f"Executing custom tool '{tool.name}' ({tool.tool_uuid}): {method} {url}" ) + if preset_arguments: + logger.debug( + f"Resolved preset parameters for '{tool.name}': {list(preset_arguments.keys())}" + ) logger.debug(f"Request body: {body}, params: {params}") try: diff --git a/api/tests/test_custom_tools.py b/api/tests/test_custom_tools.py index 693afc7..4638e5f 100644 --- a/api/tests/test_custom_tools.py +++ b/api/tests/test_custom_tools.py @@ -140,6 +140,45 @@ class TestToolToFunctionSchema: assert "duration_minutes" in required assert "is_priority" not in required + def test_preset_parameters_are_not_exposed_to_llm_schema(self): + """Test that preset parameters are injected at runtime, not shown to the LLM.""" + tool = MockToolModel( + tool_uuid="test-uuid-preset", + name="Lookup Customer", + description="Lookup a customer using contextual identifiers", + category="http_api", + definition={ + "schema_version": 1, + "type": "http_api", + "config": { + "method": "POST", + "url": "https://api.example.com/customers/lookup", + "parameters": [ + { + "name": "customer_name", + "type": "string", + "description": "Customer name spoken by the caller", + "required": True, + } + ], + "preset_parameters": [ + { + "name": "phone_number", + "type": "string", + "value_template": "{{initial_context.phone_number}}", + "required": True, + } + ], + }, + }, + ) + + schema = tool_to_function_schema(tool) + props = schema["function"]["parameters"]["properties"] + + assert "customer_name" in props + assert "phone_number" not in props + def test_tool_name_sanitization(self): """Test that tool names with special characters are sanitized.""" tool = MockToolModel( @@ -255,6 +294,108 @@ class TestExecuteHttpTool: assert result["status_code"] == 201 assert result["data"]["id"] == 123 + @pytest.mark.asyncio + async def test_post_request_injects_preset_parameters(self): + """Test that preset parameters are resolved from runtime context.""" + tool = MockToolModel( + tool_uuid="test-uuid-preset", + name="Create Lead", + description="Create a lead with caller context", + category="http_api", + definition={ + "schema_version": 1, + "type": "http_api", + "config": { + "method": "POST", + "url": "https://api.example.com/leads", + "timeout_ms": 5000, + "preset_parameters": [ + { + "name": "phone_number", + "type": "string", + "value_template": "{{initial_context.phone_number}}", + "required": True, + }, + { + "name": "customer_id", + "type": "number", + "value_template": "{{gathered_context.customer_id}}", + "required": True, + }, + { + "name": "is_vip", + "type": "boolean", + "value_template": "{{initial_context.is_vip}}", + "required": False, + }, + ], + }, + }, + ) + + arguments = {"name": "John"} + + with patch( + "api.services.workflow.tools.custom_tool.httpx.AsyncClient" + ) as mock_client_class: + mock_client = AsyncMock() + mock_response = Mock() + mock_response.status_code = 201 + mock_response.json.return_value = {"id": 123} + mock_client.request.return_value = mock_response + mock_client_class.return_value.__aenter__.return_value = mock_client + + result = await execute_http_tool( + tool, + arguments, + call_context_vars={ + "phone_number": "+14155550123", + "is_vip": "true", + }, + gathered_context_vars={"customer_id": "42"}, + ) + + call_kwargs = mock_client.request.call_args.kwargs + assert call_kwargs["json"] == { + "name": "John", + "phone_number": "+14155550123", + "customer_id": 42, + "is_vip": True, + } + assert result["status"] == "success" + + @pytest.mark.asyncio + async def test_missing_required_preset_parameter_returns_error(self): + """Test that required preset parameters fail before the HTTP request.""" + tool = MockToolModel( + tool_uuid="test-uuid-preset-error", + name="Create Lead", + description="Create a lead with caller context", + category="http_api", + definition={ + "schema_version": 1, + "type": "http_api", + "config": { + "method": "POST", + "url": "https://api.example.com/leads", + "timeout_ms": 5000, + "preset_parameters": [ + { + "name": "phone_number", + "type": "string", + "value_template": "{{initial_context.phone_number}}", + "required": True, + } + ], + }, + }, + ) + + result = await execute_http_tool(tool, {"name": "John"}, call_context_vars={}) + + assert result["status"] == "error" + assert "phone_number" in result["error"] + @pytest.mark.asyncio async def test_get_request_sends_query_params(self): """Test that GET requests send arguments as query parameters.""" diff --git a/api/tests/test_gemini_live_reconnect_tool_results.py b/api/tests/test_gemini_live_reconnect_tool_results.py new file mode 100644 index 0000000..1ad0670 --- /dev/null +++ b/api/tests/test_gemini_live_reconnect_tool_results.py @@ -0,0 +1,86 @@ +import json +from types import SimpleNamespace +from unittest.mock import AsyncMock + +import pytest +from pipecat.processors.aggregators.llm_context import LLMContext + +from api.services.pipecat.realtime.gemini_live import DograhGeminiLiveLLMService + + +class _TestDograhGeminiLiveLLMService(DograhGeminiLiveLLMService): + """Dograh Gemini service with client creation stubbed for unit tests.""" + + def create_client(self): + self._client = SimpleNamespace( + aio=SimpleNamespace(live=SimpleNamespace(connect=None)) + ) + + +class _FakeSession: + def __init__(self): + self.send_tool_response = AsyncMock() + self.send_realtime_input = AsyncMock() + self.close = AsyncMock() + + +def _make_service() -> _TestDograhGeminiLiveLLMService: + service = _TestDograhGeminiLiveLLMService(api_key="test-key") + service.stop_all_metrics = AsyncMock() + service.start_ttfb_metrics = AsyncMock() + service.cancel_task = AsyncMock() + service.push_error = AsyncMock() + return service + + +def _make_tool_result_context(tool_call_id: str) -> LLMContext: + return LLMContext( + messages=[ + { + "role": "tool", + "content": json.dumps({"status": "done"}), + "tool_call_id": tool_call_id, + } + ] + ) + + +@pytest.mark.asyncio +async def test_updated_context_during_reconnect_keeps_result_pending_until_session_ready(): + service = _make_service() + service._handled_initial_context = True + service._tool_call_id_to_name = {"call-transition": "transition_to_next_node"} + service._session = _FakeSession() + + context = _make_tool_result_context("call-transition") + + await service._disconnect() + await service._handle_context(context) + + # A reconnect gap should not count as successful delivery to Gemini. + assert "call-transition" not in service._completed_tool_calls + + session = _FakeSession() + await service._handle_session_ready(session) + + session.send_tool_response.assert_awaited_once() + sent_response = session.send_tool_response.await_args.kwargs["function_responses"] + assert sent_response.id == "call-transition" + assert sent_response.name == "transition_to_next_node" + assert "call-transition" in service._completed_tool_calls + + +@pytest.mark.asyncio +async def test_disconnect_does_not_forget_previously_delivered_tool_results(): + service = _make_service() + service._context = _make_tool_result_context("call-transition") + service._completed_tool_calls = {"call-transition"} + service._tool_call_id_to_name = {"call-transition": "transition_to_next_node"} + service._session = _FakeSession() + service._tool_result = AsyncMock() + + await service._disconnect() + await service._process_completed_function_calls(send_new_results=True) + + service._tool_result.assert_not_awaited() + assert service._completed_tool_calls == {"call-transition"} diff --git a/api/tests/test_openai_realtime_initial_context.py b/api/tests/test_openai_realtime_initial_context.py new file mode 100644 index 0000000..214d0f6 --- /dev/null +++ b/api/tests/test_openai_realtime_initial_context.py @@ -0,0 +1,98 @@ +from types import SimpleNamespace +from unittest.mock import AsyncMock + +import pytest +from pipecat.frames.frames import TTSSpeakFrame +from pipecat.processors.aggregators.llm_context import LLMContext +from pipecat.processors.frame_processor import FrameDirection + +from api.services.pipecat.realtime.openai_realtime import ( + DograhOpenAIRealtimeLLMService, +) + + +def _make_service() -> DograhOpenAIRealtimeLLMService: + service = DograhOpenAIRealtimeLLMService(api_key="test-key") + service._create_response = AsyncMock() + service._process_completed_function_calls = AsyncMock() + return service + + +@pytest.mark.asyncio +async def test_initial_context_triggers_response_when_context_was_prepopulated(): + service = _make_service() + context = LLMContext() + service._context = context + + await service._handle_context(context) + + assert service._handled_initial_context is True + assert service._context is context + service._create_response.assert_awaited_once() + service._process_completed_function_calls.assert_not_awaited() + + +@pytest.mark.asyncio +async def test_updated_context_uses_tool_result_path_after_initial_context(): + service = _make_service() + context = LLMContext() + service._handled_initial_context = True + + await service._handle_context(context) + + assert service._context is context + service._create_response.assert_not_awaited() + service._process_completed_function_calls.assert_awaited_once_with( + send_new_results=True + ) + + +@pytest.mark.asyncio +async def test_tts_greeting_uses_initial_context_handler(): + service = _make_service() + service._context = LLMContext() + service._handle_context = AsyncMock() + + await service.process_frame( + TTSSpeakFrame("hello", append_to_context=True), + FrameDirection.DOWNSTREAM, + ) + + service._handle_context.assert_awaited_once_with(service._context) + service._create_response.assert_not_awaited() + + +@pytest.mark.asyncio +async def test_function_call_executes_immediately_when_bot_is_not_speaking(): + service = _make_service() + service._context = LLMContext() + service.run_function_calls = AsyncMock() + service._pending_function_calls["call-1"] = SimpleNamespace(name="customer_support") + + await service._handle_evt_function_call_arguments_done( + SimpleNamespace(call_id="call-1", arguments='{"department":"sales"}') + ) + + service.run_function_calls.assert_awaited_once() + assert service._deferred_function_calls == [] + + +@pytest.mark.asyncio +async def test_function_call_is_deferred_until_bot_stops_speaking(): + service = _make_service() + service._context = LLMContext() + service.run_function_calls = AsyncMock() + service._bot_is_speaking = True + service._pending_function_calls["call-1"] = SimpleNamespace(name="customer_support") + + await service._handle_evt_function_call_arguments_done( + SimpleNamespace(call_id="call-1", arguments='{"department":"sales"}') + ) + + service.run_function_calls.assert_not_awaited() + assert len(service._deferred_function_calls) == 1 + + await service._run_pending_function_calls() + + service.run_function_calls.assert_awaited_once() + assert service._deferred_function_calls == [] diff --git a/api/tests/test_realtime_message_append.py b/api/tests/test_realtime_message_append.py new file mode 100644 index 0000000..56ec892 --- /dev/null +++ b/api/tests/test_realtime_message_append.py @@ -0,0 +1,59 @@ +from types import SimpleNamespace +from unittest.mock import AsyncMock + +import pytest +from pipecat.frames.frames import LLMMessagesAppendFrame +from pipecat.services.openai.realtime import events + +from api.services.pipecat.realtime.openai_realtime import ( + DograhOpenAIRealtimeLLMService, +) +from api.services.workflow.pipecat_engine_callbacks import UserIdleHandler + + +@pytest.mark.asyncio +async def test_openai_realtime_messages_append_frame_sends_conversation_item(): + service = DograhOpenAIRealtimeLLMService(api_key="test") + service._api_session_ready = True + service.send_client_event = AsyncMock() + service._send_manual_response_create = AsyncMock() + + await service._handle_messages_append( + LLMMessagesAppendFrame( + [{"role": "user", "content": "Are you still there?"}], + run_llm=True, + ) + ) + + service.send_client_event.assert_awaited_once() + event = service.send_client_event.await_args.args[0] + assert isinstance(event, events.ConversationItemCreateEvent) + assert event.item.role == "user" + assert event.item.type == "message" + assert event.item.content == [ + events.ItemContent(type="input_text", text="Are you still there?") + ] + service._send_manual_response_create.assert_awaited_once() + + +@pytest.mark.asyncio +async def test_user_idle_handler_uses_realtime_append_path(): + engine = SimpleNamespace( + llm=SimpleNamespace(), + end_call_with_reason=AsyncMock(), + ) + aggregator = SimpleNamespace(push_frame=AsyncMock()) + handler = UserIdleHandler(engine) + + await handler.handle_idle(aggregator) + + aggregator.push_frame.assert_awaited_once() + frame = aggregator.push_frame.await_args.args[0] + assert isinstance(frame, LLMMessagesAppendFrame) + assert frame.run_llm is True + assert frame.messages == [ + { + "role": "user", + "content": "The user has been quiet. Politely and briefly ask if they're still there in the language that the user has been speaking so far.", + } + ] diff --git a/api/tests/test_run_pipeline_realtime_turn_config.py b/api/tests/test_run_pipeline_realtime_turn_config.py new file mode 100644 index 0000000..8f09e1b --- /dev/null +++ b/api/tests/test_run_pipeline_realtime_turn_config.py @@ -0,0 +1,61 @@ +from pipecat.audio.vad.silero import SileroVADAnalyzer +from pipecat.turns.user_start import ( + ExternalUserTurnStartStrategy, +) +from pipecat.turns.user_start.vad_user_turn_start_strategy import ( + VADUserTurnStartStrategy, +) +from pipecat.turns.user_stop import ( + ExternalUserTurnStopStrategy, + SpeechTimeoutUserTurnStopStrategy, +) + +from api.services.configuration.registry import ServiceProviders +from api.services.pipecat.run_pipeline import _create_realtime_user_turn_config + + +def test_gemini_realtime_uses_local_vad_without_local_interruptions(): + strategies, vad_analyzer = _create_realtime_user_turn_config( + ServiceProviders.GOOGLE_REALTIME.value + ) + + assert isinstance(vad_analyzer, SileroVADAnalyzer) + assert len(strategies.start) == 1 + assert isinstance(strategies.start[0], VADUserTurnStartStrategy) + assert strategies.start[0]._enable_interruptions is False + assert len(strategies.stop) == 1 + assert isinstance(strategies.stop[0], SpeechTimeoutUserTurnStopStrategy) + + +def test_gemini_vertex_realtime_uses_same_turn_config_as_gemini_live(): + strategies, vad_analyzer = _create_realtime_user_turn_config( + ServiceProviders.GOOGLE_VERTEX_REALTIME.value + ) + + assert isinstance(vad_analyzer, SileroVADAnalyzer) + assert len(strategies.start) == 1 + assert isinstance(strategies.start[0], VADUserTurnStartStrategy) + assert strategies.start[0]._enable_interruptions is False + + +def test_openai_realtime_uses_provider_turn_frames_without_local_vad(): + strategies, vad_analyzer = _create_realtime_user_turn_config( + ServiceProviders.OPENAI_REALTIME.value + ) + + assert vad_analyzer is None + assert len(strategies.start) == 1 + assert isinstance(strategies.start[0], ExternalUserTurnStartStrategy) + assert strategies.start[0]._enable_interruptions is False + assert len(strategies.stop) == 1 + assert isinstance(strategies.stop[0], ExternalUserTurnStopStrategy) + + +def test_unknown_realtime_providers_keep_local_vad(): + strategies, vad_analyzer = _create_realtime_user_turn_config("other_realtime") + + assert isinstance(vad_analyzer, SileroVADAnalyzer) + assert len(strategies.start) == 1 + assert isinstance(strategies.start[0], VADUserTurnStartStrategy) + assert len(strategies.stop) == 1 + assert isinstance(strategies.stop[0], SpeechTimeoutUserTurnStopStrategy) diff --git a/api/tests/test_unregistered_function_call.py b/api/tests/test_unregistered_function_call.py index 24ed9a1..5229b64 100644 --- a/api/tests/test_unregistered_function_call.py +++ b/api/tests/test_unregistered_function_call.py @@ -66,7 +66,7 @@ class TestUnregisteredFunctionCall: # Pipecat's missing-function handler returns a string error. assert isinstance(result_frame.result, str) - assert "not registered" in result_frame.result + assert "not currently available" in result_frame.result assert "nonexistent_tool" in result_frame.result # In-progress frame should also be emitted before the result so mute diff --git a/docs/api-reference/openapi.json b/docs/api-reference/openapi.json index 4276fca..424437e 100644 --- a/docs/api-reference/openapi.json +++ b/docs/api-reference/openapi.json @@ -1 +1 @@ -{"openapi":"3.1.0","info":{"title":"Dograh API","description":"API for the Dograh app","version":"1.0.0"},"servers":[{"url":"https://app.dograh.com","description":"Production"},{"url":"http://localhost:8000","description":"Local development"}],"paths":{"/api/v1/telephony/initiate-call":{"post":{"tags":["main"],"summary":"Initiate Call","description":"Initiate a call using the configured telephony provider from web browser. This is\nsupposed to be a test call method for the draft version of the agent.","operationId":"initiate_call_api_v1_telephony_initiate_call_post","parameters":[{"name":"authorization","in":"header","required":false,"schema":{"anyOf":[{"type":"string"},{"type":"null"}],"title":"Authorization"}},{"name":"X-API-Key","in":"header","required":false,"schema":{"anyOf":[{"type":"string"},{"type":"null"}],"title":"X-Api-Key"}}],"requestBody":{"required":true,"content":{"application/json":{"schema":{"$ref":"#/components/schemas/InitiateCallRequest"}}}},"responses":{"200":{"description":"Successful Response","content":{"application/json":{"schema":{}}}},"404":{"description":"Not found"},"422":{"description":"Validation Error","content":{"application/json":{"schema":{"$ref":"#/components/schemas/HTTPValidationError"}}}}},"x-sdk-method":"test_phone_call","x-sdk-description":"Place a test call from a workflow to a phone number."}},"/api/v1/telephony/inbound/run":{"post":{"tags":["main"],"summary":"Handle Inbound Run","description":"Workflow-agnostic inbound dispatcher.\n\nAll providers can point a single webhook at this endpoint instead of one\nURL per workflow. The dispatcher resolves the org from the webhook's\naccount_id and the workflow from the called number's\n``inbound_workflow_id``. This is what ``configure_inbound`` writes into\neach provider's resource so per-workflow webhook bookkeeping disappears.\n\nProvider-specific signature/timestamp headers are not enumerated here \u2014\neach provider's ``verify_inbound_signature`` reads its own headers from\nthe dict, so adding a new provider doesn't require changes to this route.","operationId":"handle_inbound_run_api_v1_telephony_inbound_run_post","responses":{"200":{"description":"Successful Response","content":{"application/json":{"schema":{}}}},"404":{"description":"Not found"}}}},"/api/v1/telephony/inbound/fallback":{"post":{"tags":["main"],"summary":"Handle Inbound Fallback","description":"Fallback endpoint that returns audio message when calls cannot be processed.","operationId":"handle_inbound_fallback_api_v1_telephony_inbound_fallback_post","responses":{"200":{"description":"Successful Response","content":{"application/json":{"schema":{}}}},"404":{"description":"Not found"}}}},"/api/v1/telephony/inbound/{workflow_id}":{"post":{"tags":["main"],"summary":"Handle Inbound Telephony","description":"[LEGACY] Per-workflow inbound webhook.\n\nSuperseded by ``POST /inbound/run``, which resolves the workflow from\nthe called number's ``inbound_workflow_id`` and lets a single webhook\nURL serve every workflow in the org. New integrations should point\ntheir provider at ``/inbound/run``; this route is kept only for\nexisting provider configurations that still encode ``workflow_id``\nin the URL.","operationId":"handle_inbound_telephony_api_v1_telephony_inbound__workflow_id__post","deprecated":true,"parameters":[{"name":"workflow_id","in":"path","required":true,"schema":{"type":"integer","title":"Workflow Id"}}],"responses":{"200":{"description":"Successful Response","content":{"application/json":{"schema":{}}}},"404":{"description":"Not found"},"422":{"description":"Validation Error","content":{"application/json":{"schema":{"$ref":"#/components/schemas/HTTPValidationError"}}}}}}},"/api/v1/telephony/transfer-result/{transfer_id}":{"post":{"tags":["main"],"summary":"Complete Transfer Function Call","description":"Webhook endpoint to complete the function call with transfer result.\n\nCalled by Twilio's StatusCallback when the transfer call status changes.","operationId":"complete_transfer_function_call_api_v1_telephony_transfer_result__transfer_id__post","parameters":[{"name":"transfer_id","in":"path","required":true,"schema":{"type":"string","title":"Transfer Id"}}],"responses":{"200":{"description":"Successful Response","content":{"application/json":{"schema":{}}}},"404":{"description":"Not found"},"422":{"description":"Validation Error","content":{"application/json":{"schema":{"$ref":"#/components/schemas/HTTPValidationError"}}}}}}},"/api/v1/telephony/cloudonix/status-callback/{workflow_run_id}":{"post":{"tags":["main"],"summary":"Handle Cloudonix Status Callback","description":"Handle Cloudonix-specific status callbacks.\n\nCloudonix sends call status updates to the callback URL specified during call initiation.","operationId":"handle_cloudonix_status_callback_api_v1_telephony_cloudonix_status_callback__workflow_run_id__post","parameters":[{"name":"workflow_run_id","in":"path","required":true,"schema":{"type":"integer","title":"Workflow Run Id"}}],"responses":{"200":{"description":"Successful Response","content":{"application/json":{"schema":{}}}},"404":{"description":"Not found"},"422":{"description":"Validation Error","content":{"application/json":{"schema":{"$ref":"#/components/schemas/HTTPValidationError"}}}}}}},"/api/v1/telephony/cloudonix/cdr":{"post":{"tags":["main"],"summary":"Handle Cloudonix Cdr","description":"Handle Cloudonix CDR (Call Detail Record) webhooks.\n\nCloudonix sends CDR records when calls complete. The CDR contains:\n- domain: Used to identify the organization\n- call_id: Used to find the workflow run\n- disposition: Call termination status (ANSWER, BUSY, CANCEL, FAILED, CONGESTION, NOANSWER)\n- duration/billsec: Call duration information","operationId":"handle_cloudonix_cdr_api_v1_telephony_cloudonix_cdr_post","responses":{"200":{"description":"Successful Response","content":{"application/json":{"schema":{}}}},"404":{"description":"Not found"}}}},"/api/v1/telephony/plivo/hangup-callback/{workflow_run_id}":{"post":{"tags":["main"],"summary":"Handle Plivo Hangup Callback","description":"Handle Plivo hangup callbacks.","operationId":"handle_plivo_hangup_callback_api_v1_telephony_plivo_hangup_callback__workflow_run_id__post","parameters":[{"name":"workflow_run_id","in":"path","required":true,"schema":{"type":"integer","title":"Workflow Run Id"}},{"name":"x-plivo-signature-v3","in":"header","required":false,"schema":{"anyOf":[{"type":"string"},{"type":"null"}],"title":"X-Plivo-Signature-V3"}},{"name":"x-plivo-signature-ma-v3","in":"header","required":false,"schema":{"anyOf":[{"type":"string"},{"type":"null"}],"title":"X-Plivo-Signature-Ma-V3"}},{"name":"x-plivo-signature-v3-nonce","in":"header","required":false,"schema":{"anyOf":[{"type":"string"},{"type":"null"}],"title":"X-Plivo-Signature-V3-Nonce"}}],"responses":{"200":{"description":"Successful Response","content":{"application/json":{"schema":{}}}},"404":{"description":"Not found"},"422":{"description":"Validation Error","content":{"application/json":{"schema":{"$ref":"#/components/schemas/HTTPValidationError"}}}}}}},"/api/v1/telephony/plivo/ring-callback/{workflow_run_id}":{"post":{"tags":["main"],"summary":"Handle Plivo Ring Callback","description":"Handle Plivo ring callbacks.","operationId":"handle_plivo_ring_callback_api_v1_telephony_plivo_ring_callback__workflow_run_id__post","parameters":[{"name":"workflow_run_id","in":"path","required":true,"schema":{"type":"integer","title":"Workflow Run Id"}},{"name":"x-plivo-signature-v3","in":"header","required":false,"schema":{"anyOf":[{"type":"string"},{"type":"null"}],"title":"X-Plivo-Signature-V3"}},{"name":"x-plivo-signature-ma-v3","in":"header","required":false,"schema":{"anyOf":[{"type":"string"},{"type":"null"}],"title":"X-Plivo-Signature-Ma-V3"}},{"name":"x-plivo-signature-v3-nonce","in":"header","required":false,"schema":{"anyOf":[{"type":"string"},{"type":"null"}],"title":"X-Plivo-Signature-V3-Nonce"}}],"responses":{"200":{"description":"Successful Response","content":{"application/json":{"schema":{}}}},"404":{"description":"Not found"},"422":{"description":"Validation Error","content":{"application/json":{"schema":{"$ref":"#/components/schemas/HTTPValidationError"}}}}}}},"/api/v1/telephony/telnyx/events/{workflow_run_id}":{"post":{"tags":["main"],"summary":"Handle Telnyx Events","description":"Handle Telnyx Call Control webhook events.\n\nTelnyx sends all call lifecycle events (call.initiated, call.answered,\ncall.hangup, streaming.started, streaming.stopped) as JSON POST requests.","operationId":"handle_telnyx_events_api_v1_telephony_telnyx_events__workflow_run_id__post","parameters":[{"name":"workflow_run_id","in":"path","required":true,"schema":{"type":"integer","title":"Workflow Run Id"}}],"responses":{"200":{"description":"Successful Response","content":{"application/json":{"schema":{}}}},"404":{"description":"Not found"},"422":{"description":"Validation Error","content":{"application/json":{"schema":{"$ref":"#/components/schemas/HTTPValidationError"}}}}}}},"/api/v1/telephony/telnyx/transfer-result/{transfer_id}":{"post":{"tags":["main"],"summary":"Handle Telnyx Transfer Result","description":"Handle Telnyx Call Control events for the transfer destination leg.\n\nThe destination leg is dialed by :meth:`TelnyxProvider.transfer_call` with\nthis URL as ``webhook_url``. Telnyx sends every event for that leg here.\nOutcomes:\n\n- ``call.answered``: seed a conference with the destination's live\n ``call_control_id``, stamp ``conference_id`` onto the TransferContext,\n and publish ``DESTINATION_ANSWERED`` so ``transfer_call_handler`` can\n end the pipeline. ``TelnyxConferenceStrategy`` then joins the caller\n into this conference at pipeline teardown.\n- ``call.hangup`` pre-answer (no ``conference_id`` on the context):\n publish ``TRANSFER_FAILED`` so the LLM can recover.\n- ``call.hangup`` post-answer (``conference_id`` set): the destination\n left a bridged conference; hang up the caller's leg to tear down the\n empty bridge (Telnyx's create_conference doesn't accept\n ``end_conference_on_exit`` on the seed leg).\n\nEvent references:\n - call.answered: https://developers.telnyx.com/api-reference/callbacks/call-answered\n - call.hangup: https://developers.telnyx.com/api-reference/callbacks/call-hangup","operationId":"handle_telnyx_transfer_result_api_v1_telephony_telnyx_transfer_result__transfer_id__post","parameters":[{"name":"transfer_id","in":"path","required":true,"schema":{"type":"string","title":"Transfer Id"}}],"responses":{"200":{"description":"Successful Response","content":{"application/json":{"schema":{}}}},"404":{"description":"Not found"},"422":{"description":"Validation Error","content":{"application/json":{"schema":{"$ref":"#/components/schemas/HTTPValidationError"}}}}}}},"/api/v1/telephony/twilio/status-callback/{workflow_run_id}":{"post":{"tags":["main"],"summary":"Handle Twilio Status Callback","description":"Handle Twilio-specific status callbacks.","operationId":"handle_twilio_status_callback_api_v1_telephony_twilio_status_callback__workflow_run_id__post","parameters":[{"name":"workflow_run_id","in":"path","required":true,"schema":{"type":"integer","title":"Workflow Run Id"}},{"name":"x-webhook-signature","in":"header","required":false,"schema":{"anyOf":[{"type":"string"},{"type":"null"}],"title":"X-Webhook-Signature"}}],"responses":{"200":{"description":"Successful Response","content":{"application/json":{"schema":{}}}},"404":{"description":"Not found"},"422":{"description":"Validation Error","content":{"application/json":{"schema":{"$ref":"#/components/schemas/HTTPValidationError"}}}}}}},"/api/v1/telephony/vobiz/hangup-callback/{workflow_run_id}":{"post":{"tags":["main"],"summary":"Handle Vobiz Hangup Callback","description":"Handle Vobiz hangup callback (sent when call ends).\n\nVobiz sends callbacks to hangup_url when the call terminates.\nThis includes call duration, status, and billing information.","operationId":"handle_vobiz_hangup_callback_api_v1_telephony_vobiz_hangup_callback__workflow_run_id__post","parameters":[{"name":"workflow_run_id","in":"path","required":true,"schema":{"type":"integer","title":"Workflow Run Id"}},{"name":"x-vobiz-signature","in":"header","required":false,"schema":{"anyOf":[{"type":"string"},{"type":"null"}],"title":"X-Vobiz-Signature"}},{"name":"x-vobiz-timestamp","in":"header","required":false,"schema":{"anyOf":[{"type":"string"},{"type":"null"}],"title":"X-Vobiz-Timestamp"}}],"responses":{"200":{"description":"Successful Response","content":{"application/json":{"schema":{}}}},"404":{"description":"Not found"},"422":{"description":"Validation Error","content":{"application/json":{"schema":{"$ref":"#/components/schemas/HTTPValidationError"}}}}}}},"/api/v1/telephony/vobiz/ring-callback/{workflow_run_id}":{"post":{"tags":["main"],"summary":"Handle Vobiz Ring Callback","description":"Handle Vobiz ring callback (sent when call starts ringing).\n\nVobiz can send callbacks to ring_url when the call starts ringing.\nThis is optional and used for tracking ringing status.","operationId":"handle_vobiz_ring_callback_api_v1_telephony_vobiz_ring_callback__workflow_run_id__post","parameters":[{"name":"workflow_run_id","in":"path","required":true,"schema":{"type":"integer","title":"Workflow Run Id"}},{"name":"x-vobiz-signature","in":"header","required":false,"schema":{"anyOf":[{"type":"string"},{"type":"null"}],"title":"X-Vobiz-Signature"}},{"name":"x-vobiz-timestamp","in":"header","required":false,"schema":{"anyOf":[{"type":"string"},{"type":"null"}],"title":"X-Vobiz-Timestamp"}}],"responses":{"200":{"description":"Successful Response","content":{"application/json":{"schema":{}}}},"404":{"description":"Not found"},"422":{"description":"Validation Error","content":{"application/json":{"schema":{"$ref":"#/components/schemas/HTTPValidationError"}}}}}}},"/api/v1/telephony/vobiz/hangup-callback/workflow/{workflow_id}":{"post":{"tags":["main"],"summary":"Handle Vobiz Hangup Callback By Workflow","description":"Handle Vobiz hangup callback with workflow_id - finds workflow run by call_id.","operationId":"handle_vobiz_hangup_callback_by_workflow_api_v1_telephony_vobiz_hangup_callback_workflow__workflow_id__post","parameters":[{"name":"workflow_id","in":"path","required":true,"schema":{"type":"integer","title":"Workflow Id"}},{"name":"x-vobiz-signature","in":"header","required":false,"schema":{"anyOf":[{"type":"string"},{"type":"null"}],"title":"X-Vobiz-Signature"}},{"name":"x-vobiz-timestamp","in":"header","required":false,"schema":{"anyOf":[{"type":"string"},{"type":"null"}],"title":"X-Vobiz-Timestamp"}}],"responses":{"200":{"description":"Successful Response","content":{"application/json":{"schema":{}}}},"404":{"description":"Not found"},"422":{"description":"Validation Error","content":{"application/json":{"schema":{"$ref":"#/components/schemas/HTTPValidationError"}}}}}}},"/api/v1/telephony/vonage/events/{workflow_run_id}":{"post":{"tags":["main"],"summary":"Handle Vonage Events","description":"Handle Vonage-specific event webhooks.\n\nVonage sends all call events to a single endpoint.\nEvents include: started, ringing, answered, complete, failed, etc.","operationId":"handle_vonage_events_api_v1_telephony_vonage_events__workflow_run_id__post","parameters":[{"name":"workflow_run_id","in":"path","required":true,"schema":{"type":"integer","title":"Workflow Run Id"}}],"responses":{"200":{"description":"Successful Response","content":{"application/json":{"schema":{}}}},"404":{"description":"Not found"},"422":{"description":"Validation Error","content":{"application/json":{"schema":{"$ref":"#/components/schemas/HTTPValidationError"}}}}}}},"/api/v1/superuser/impersonate":{"post":{"tags":["main","superuser"],"summary":"Impersonate","description":"Impersonate a user as a super-admin.\nInternally, Stack Auth requires the **provider user ID** (a UUID-ish string)\nto create an impersonation 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superuser privileges.\n\nFilters should be provided as a JSON-encoded array of filter criteria.\nExample: [{\"field\": \"id\", \"type\": \"number\", \"value\": {\"value\": 680}}]","operationId":"get_workflow_runs_api_v1_superuser_workflow_runs_get","parameters":[{"name":"page","in":"query","required":false,"schema":{"type":"integer","minimum":1,"description":"Page number (starts from 1)","default":1,"title":"Page"},"description":"Page number (starts from 1)"},{"name":"limit","in":"query","required":false,"schema":{"type":"integer","maximum":100,"minimum":1,"description":"Number of items per page","default":50,"title":"Limit"},"description":"Number of items per page"},{"name":"filters","in":"query","required":false,"schema":{"anyOf":[{"type":"string"},{"type":"null"}],"description":"JSON-encoded filter criteria","title":"Filters"},"description":"JSON-encoded filter 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Error","content":{"application/json":{"schema":{"$ref":"#/components/schemas/HTTPValidationError"}}}}}}},"/api/v1/workflow/{workflow_id}/validate":{"post":{"tags":["main"],"summary":"Validate Workflow","description":"Validate all nodes in a workflow to ensure they have required fields.\n\nArgs:\n workflow_id: The ID of the workflow to validate\n user: The authenticated user\n\nReturns:\n Object indicating if workflow is valid and any invalid nodes/edges","operationId":"validate_workflow_api_v1_workflow__workflow_id__validate_post","parameters":[{"name":"workflow_id","in":"path","required":true,"schema":{"type":"integer","title":"Workflow Id"}},{"name":"authorization","in":"header","required":false,"schema":{"anyOf":[{"type":"string"},{"type":"null"}],"title":"Authorization"}},{"name":"X-API-Key","in":"header","required":false,"schema":{"anyOf":[{"type":"string"},{"type":"null"}],"title":"X-Api-Key"}}],"responses":{"200":{"description":"Successful Response","content":{"application/json":{"schema":{"$ref":"#/components/schemas/ValidateWorkflowResponse"}}}},"404":{"description":"Not found"},"422":{"description":"Validation Error","content":{"application/json":{"schema":{"$ref":"#/components/schemas/HTTPValidationError"}}}}}}},"/api/v1/workflow/create/definition":{"post":{"tags":["main"],"summary":"Create Workflow","description":"Create a new workflow from the client\n\nArgs:\n request: The create workflow request\n user: The user to create the workflow for","operationId":"create_workflow_api_v1_workflow_create_definition_post","parameters":[{"name":"authorization","in":"header","required":false,"schema":{"anyOf":[{"type":"string"},{"type":"null"}],"title":"Authorization"}},{"name":"X-API-Key","in":"header","required":false,"schema":{"anyOf":[{"type":"string"},{"type":"null"}],"title":"X-Api-Key"}}],"requestBody":{"required":true,"content":{"application/json":{"schema":{"$ref":"#/components/schemas/CreateWorkflowRequest"}}}},"responses":{"200":{"description":"Successful Response","content":{"application/json":{"schema":{"$ref":"#/components/schemas/WorkflowResponse"}}}},"404":{"description":"Not found"},"422":{"description":"Validation Error","content":{"application/json":{"schema":{"$ref":"#/components/schemas/HTTPValidationError"}}}}},"x-sdk-method":"create_workflow","x-sdk-description":"Create a new workflow from a workflow definition."}},"/api/v1/workflow/create/template":{"post":{"tags":["main"],"summary":"Create Workflow From 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user's organization.","operationId":"create_service_key_api_v1_user_service_keys_post","parameters":[{"name":"authorization","in":"header","required":false,"schema":{"anyOf":[{"type":"string"},{"type":"null"}],"title":"Authorization"}},{"name":"X-API-Key","in":"header","required":false,"schema":{"anyOf":[{"type":"string"},{"type":"null"}],"title":"X-Api-Key"}}],"requestBody":{"required":true,"content":{"application/json":{"schema":{"$ref":"#/components/schemas/CreateServiceKeyRequest"}}}},"responses":{"200":{"description":"Successful Response","content":{"application/json":{"schema":{"$ref":"#/components/schemas/CreateServiceKeyResponse"}}}},"404":{"description":"Not found"},"422":{"description":"Validation Error","content":{"application/json":{"schema":{"$ref":"#/components/schemas/HTTPValidationError"}}}}}}},"/api/v1/user/service-keys/{service_key_id}":{"delete":{"tags":["main"],"summary":"Archive Service Key","description":"Archive a service key.","operationId":"archive_service_key_api_v1_user_service_keys__service_key_id__delete","parameters":[{"name":"service_key_id","in":"path","required":true,"schema":{"type":"string","title":"Service Key Id"}},{"name":"authorization","in":"header","required":false,"schema":{"anyOf":[{"type":"string"},{"type":"null"}],"title":"Authorization"}},{"name":"X-API-Key","in":"header","required":false,"schema":{"anyOf":[{"type":"string"},{"type":"null"}],"title":"X-Api-Key"}}],"responses":{"200":{"description":"Successful Response","content":{"application/json":{"schema":{}}}},"404":{"description":"Not found"},"422":{"description":"Validation Error","content":{"application/json":{"schema":{"$ref":"#/components/schemas/HTTPValidationError"}}}}}}},"/api/v1/user/service-keys/{service_key_id}/reactivate":{"put":{"tags":["main"],"summary":"Reactivate Service Key","description":"Reactivate an archived service key.\n\nNote: This endpoint is provided for API compatibility but service key\nreactivation is not supported by MPS. Once archived, a service key\ncannot be reactivated and a new key must be created instead.","operationId":"reactivate_service_key_api_v1_user_service_keys__service_key_id__reactivate_put","parameters":[{"name":"service_key_id","in":"path","required":true,"schema":{"type":"string","title":"Service Key Id"}},{"name":"authorization","in":"header","required":false,"schema":{"anyOf":[{"type":"string"},{"type":"null"}],"title":"Authorization"}},{"name":"X-API-Key","in":"header","required":false,"schema":{"anyOf":[{"type":"string"},{"type":"null"}],"title":"X-Api-Key"}}],"responses":{"200":{"description":"Successful Response","content":{"application/json":{"schema":{}}}},"404":{"description":"Not found"},"422":{"description":"Validation Error","content":{"application/json":{"schema":{"$ref":"#/components/schemas/HTTPValidationError"}}}}}}},"/api/v1/organizations/usage/current-period":{"get":{"tags":["main"],"summary":"Get Current Period Usage","description":"Get current billing period usage for the user's organization.","operationId":"get_current_period_usage_api_v1_organizations_usage_current_period_get","parameters":[{"name":"authorization","in":"header","required":false,"schema":{"anyOf":[{"type":"string"},{"type":"null"}],"title":"Authorization"}},{"name":"X-API-Key","in":"header","required":false,"schema":{"anyOf":[{"type":"string"},{"type":"null"}],"title":"X-Api-Key"}}],"responses":{"200":{"description":"Successful Response","content":{"application/json":{"schema":{"$ref":"#/components/schemas/CurrentUsageResponse"}}}},"404":{"description":"Not found"},"422":{"description":"Validation Error","content":{"application/json":{"schema":{"$ref":"#/components/schemas/HTTPValidationError"}}}}}}},"/api/v1/organizations/usage/mps-credits":{"get":{"tags":["main"],"summary":"Get Mps Credits","description":"Get aggregated usage and quota from MPS.\n\nOSS users: queries by provider_id (created_by).\nHosted users: queries by organization_id.","operationId":"get_mps_credits_api_v1_organizations_usage_mps_credits_get","parameters":[{"name":"authorization","in":"header","required":false,"schema":{"anyOf":[{"type":"string"},{"type":"null"}],"title":"Authorization"}},{"name":"X-API-Key","in":"header","required":false,"schema":{"anyOf":[{"type":"string"},{"type":"null"}],"title":"X-Api-Key"}}],"responses":{"200":{"description":"Successful Response","content":{"application/json":{"schema":{"$ref":"#/components/schemas/MPSCreditsResponse"}}}},"404":{"description":"Not found"},"422":{"description":"Validation Error","content":{"application/json":{"schema":{"$ref":"#/components/schemas/HTTPValidationError"}}}}}}},"/api/v1/organizations/usage/runs":{"get":{"tags":["main"],"summary":"Get Usage History","description":"Get paginated workflow runs with usage for the organization.","operationId":"get_usage_history_api_v1_organizations_usage_runs_get","parameters":[{"name":"start_date","in":"query","required":false,"schema":{"anyOf":[{"type":"string"},{"type":"null"}],"description":"ISO 8601 date-time string (UTC). Lower bound (inclusive) on `created_at`.","examples":["2026-04-01T00:00:00Z"],"title":"Start Date"},"description":"ISO 8601 date-time string (UTC). Lower bound (inclusive) on `created_at`."},{"name":"end_date","in":"query","required":false,"schema":{"anyOf":[{"type":"string"},{"type":"null"}],"description":"ISO 8601 date-time string (UTC). Upper bound (inclusive) on `created_at`.","examples":["2026-05-01T00:00:00Z"],"title":"End Date"},"description":"ISO 8601 date-time string (UTC). Upper bound (inclusive) on `created_at`."},{"name":"page","in":"query","required":false,"schema":{"type":"integer","minimum":1,"default":1,"title":"Page"}},{"name":"limit","in":"query","required":false,"schema":{"type":"integer","maximum":100,"minimum":1,"default":50,"title":"Limit"}},{"name":"filters","in":"query","required":false,"schema":{"anyOf":[{"type":"string"},{"type":"null"}],"description":"JSON-encoded array of filter objects. Each object has the shape:\n\n```json\n{ \"attribute\": \"\", \"type\": \"\", \"value\": }\n```\n\nSupported `attribute` / `type` / `value` combinations:\n\n| attribute | type | value shape | matches |\n|-----------------|---------------|----------------------------------------------|------------------------------------------------------|\n| `runId` | `number` | `{ \"value\": 12345 }` | exact run id |\n| `workflowId` | `number` | `{ \"value\": 42 }` | exact agent (workflow) id |\n| `campaignId` | `number` | `{ \"value\": 7 }` | exact campaign id |\n| `callerNumber` | `text` | `{ \"value\": \"415555\" }` | substring match on `initial_context.caller_number` |\n| `calledNumber` | `text` | `{ \"value\": \"9911848\" }` | substring match on `initial_context.called_number` |\n| `dispositionCode` | `multiSelect` | `{ \"codes\": [\"XFER\", \"DNC\"] }` | any of the codes in `gathered_context.mapped_call_disposition` |\n| `duration` | `numberRange` | `{ \"min\": 60, \"max\": 300 }` | call duration (seconds), inclusive bounds |\n\nUnknown attributes and unsupported `type` values are silently ignored.\n\nDate filtering on this endpoint is done via the dedicated `start_date` / `end_date` query params, not via a `dateRange` filter object.\n","examples":["[{\"attribute\":\"callerNumber\",\"type\":\"text\",\"value\":{\"value\":\"415555\"}}]","[{\"attribute\":\"campaignId\",\"type\":\"number\",\"value\":{\"value\":7}},{\"attribute\":\"duration\",\"type\":\"numberRange\",\"value\":{\"min\":60,\"max\":300}}]","[{\"attribute\":\"dispositionCode\",\"type\":\"multiSelect\",\"value\":{\"codes\":[\"XFER\",\"DNC\"]}}]"],"title":"Filters"},"description":"JSON-encoded array of filter objects. Each object has the shape:\n\n```json\n{ \"attribute\": \"\", \"type\": \"\", \"value\": }\n```\n\nSupported `attribute` / `type` / `value` combinations:\n\n| attribute | type | value shape | matches |\n|-----------------|---------------|----------------------------------------------|------------------------------------------------------|\n| `runId` | `number` | `{ \"value\": 12345 }` | exact run id |\n| `workflowId` | `number` | `{ \"value\": 42 }` | exact agent (workflow) id |\n| `campaignId` | `number` | `{ \"value\": 7 }` | exact campaign id |\n| `callerNumber` | `text` | `{ \"value\": \"415555\" }` | substring match on `initial_context.caller_number` |\n| `calledNumber` | `text` | `{ \"value\": \"9911848\" }` | substring match on `initial_context.called_number` |\n| `dispositionCode` | `multiSelect` | `{ \"codes\": [\"XFER\", \"DNC\"] }` | any of the codes in `gathered_context.mapped_call_disposition` |\n| `duration` | `numberRange` | `{ \"min\": 60, \"max\": 300 }` | call duration (seconds), inclusive bounds |\n\nUnknown attributes and unsupported `type` values are silently ignored.\n\nDate filtering on this endpoint is done via the dedicated `start_date` / `end_date` query params, not via a `dateRange` filter object.\n"},{"name":"authorization","in":"header","required":false,"schema":{"anyOf":[{"type":"string"},{"type":"null"}],"title":"Authorization"}},{"name":"X-API-Key","in":"header","required":false,"schema":{"anyOf":[{"type":"string"},{"type":"null"}],"title":"X-Api-Key"}}],"responses":{"200":{"description":"Successful Response","content":{"application/json":{"schema":{"$ref":"#/components/schemas/UsageHistoryResponse"}}}},"404":{"description":"Not found"},"422":{"description":"Validation Error","content":{"application/json":{"schema":{"$ref":"#/components/schemas/HTTPValidationError"}}}}}}},"/api/v1/organizations/usage/runs/report":{"get":{"tags":["main"],"summary":"Download Usage Runs Report","description":"Download a CSV of runs matching the same filters as `/usage/runs`.","operationId":"download_usage_runs_report_api_v1_organizations_usage_runs_report_get","parameters":[{"name":"start_date","in":"query","required":false,"schema":{"anyOf":[{"type":"string"},{"type":"null"}],"description":"ISO 8601 date-time string (UTC). Lower bound (inclusive) on `created_at`.","title":"Start Date"},"description":"ISO 8601 date-time string (UTC). Lower bound (inclusive) on `created_at`."},{"name":"end_date","in":"query","required":false,"schema":{"anyOf":[{"type":"string"},{"type":"null"}],"description":"ISO 8601 date-time string (UTC). Upper bound (inclusive) on `created_at`.","title":"End Date"},"description":"ISO 8601 date-time string (UTC). Upper bound (inclusive) on `created_at`."},{"name":"filters","in":"query","required":false,"schema":{"anyOf":[{"type":"string"},{"type":"null"}],"description":"JSON-encoded array of filter objects. Each object has the shape:\n\n```json\n{ \"attribute\": \"\", \"type\": \"\", \"value\": }\n```\n\nSupported `attribute` / `type` / `value` combinations:\n\n| attribute | type | value shape | matches |\n|-----------------|---------------|----------------------------------------------|------------------------------------------------------|\n| `runId` | `number` | `{ \"value\": 12345 }` | exact run id |\n| `workflowId` | `number` | `{ \"value\": 42 }` | exact agent (workflow) id |\n| `campaignId` | `number` | `{ \"value\": 7 }` | exact campaign id |\n| `callerNumber` | `text` | `{ \"value\": \"415555\" }` | substring match on `initial_context.caller_number` |\n| `calledNumber` | `text` | `{ \"value\": \"9911848\" }` | substring match on `initial_context.called_number` |\n| `dispositionCode` | `multiSelect` | `{ \"codes\": [\"XFER\", \"DNC\"] }` | any of the codes in `gathered_context.mapped_call_disposition` |\n| `duration` | `numberRange` | `{ \"min\": 60, \"max\": 300 }` | call duration (seconds), inclusive bounds |\n\nUnknown attributes and unsupported `type` values are silently ignored.\n\nDate filtering on this endpoint is done via the dedicated `start_date` / `end_date` query params, not via a `dateRange` filter object.\n","title":"Filters"},"description":"JSON-encoded array of filter objects. Each object has the shape:\n\n```json\n{ \"attribute\": \"\", \"type\": \"\", \"value\": }\n```\n\nSupported `attribute` / `type` / `value` combinations:\n\n| attribute | type | value shape | matches |\n|-----------------|---------------|----------------------------------------------|------------------------------------------------------|\n| `runId` | `number` | `{ \"value\": 12345 }` | exact run id |\n| `workflowId` | `number` | `{ \"value\": 42 }` | exact agent (workflow) id |\n| `campaignId` | `number` | `{ \"value\": 7 }` | exact campaign id |\n| `callerNumber` | `text` | `{ \"value\": \"415555\" }` | substring match on `initial_context.caller_number` |\n| `calledNumber` | `text` | `{ \"value\": \"9911848\" }` | substring match on `initial_context.called_number` |\n| `dispositionCode` | `multiSelect` | `{ \"codes\": [\"XFER\", \"DNC\"] }` | any of the codes in `gathered_context.mapped_call_disposition` |\n| `duration` | `numberRange` | `{ \"min\": 60, \"max\": 300 }` | call duration (seconds), inclusive bounds |\n\nUnknown attributes and unsupported `type` values are silently ignored.\n\nDate filtering on this endpoint is done via the dedicated `start_date` / `end_date` query params, not via a `dateRange` filter object.\n"},{"name":"authorization","in":"header","required":false,"schema":{"anyOf":[{"type":"string"},{"type":"null"}],"title":"Authorization"}},{"name":"X-API-Key","in":"header","required":false,"schema":{"anyOf":[{"type":"string"},{"type":"null"}],"title":"X-Api-Key"}}],"responses":{"200":{"description":"Successful Response","content":{"application/json":{"schema":{}}}},"404":{"description":"Not found"},"422":{"description":"Validation Error","content":{"application/json":{"schema":{"$ref":"#/components/schemas/HTTPValidationError"}}}}}}},"/api/v1/organizations/usage/daily-breakdown":{"get":{"tags":["main"],"summary":"Get Daily Usage Breakdown","description":"Get daily usage breakdown for the last N days. Only available for organizations with pricing.","operationId":"get_daily_usage_breakdown_api_v1_organizations_usage_daily_breakdown_get","parameters":[{"name":"days","in":"query","required":false,"schema":{"type":"integer","maximum":30,"minimum":1,"description":"Number of days to include","default":7,"title":"Days"},"description":"Number of days to include"},{"name":"authorization","in":"header","required":false,"schema":{"anyOf":[{"type":"string"},{"type":"null"}],"title":"Authorization"}},{"name":"X-API-Key","in":"header","required":false,"schema":{"anyOf":[{"type":"string"},{"type":"null"}],"title":"X-Api-Key"}}],"responses":{"200":{"description":"Successful Response","content":{"application/json":{"schema":{"$ref":"#/components/schemas/DailyUsageBreakdownResponse"}}}},"404":{"description":"Not found"},"422":{"description":"Validation Error","content":{"application/json":{"schema":{"$ref":"#/components/schemas/HTTPValidationError"}}}}}}},"/api/v1/organizations/reports/daily":{"get":{"tags":["main"],"summary":"Get Daily Report","description":"Get daily report for the specified date and timezone.\nIf workflow_id is provided, filters results to that specific workflow.\nIf workflow_id is None, includes all workflows for the organization.","operationId":"get_daily_report_api_v1_organizations_reports_daily_get","parameters":[{"name":"date","in":"query","required":true,"schema":{"type":"string","description":"Date in YYYY-MM-DD format","title":"Date"},"description":"Date in YYYY-MM-DD format"},{"name":"timezone","in":"query","required":true,"schema":{"type":"string","description":"IANA timezone (e.g., 'America/New_York')","title":"Timezone"},"description":"IANA timezone (e.g., 'America/New_York')"},{"name":"workflow_id","in":"query","required":false,"schema":{"anyOf":[{"type":"integer"},{"type":"null"}],"description":"Optional workflow ID to filter by","title":"Workflow Id"},"description":"Optional workflow ID to filter by"},{"name":"authorization","in":"header","required":false,"schema":{"anyOf":[{"type":"string"},{"type":"null"}],"title":"Authorization"}},{"name":"X-API-Key","in":"header","required":false,"schema":{"anyOf":[{"type":"string"},{"type":"null"}],"title":"X-Api-Key"}}],"responses":{"200":{"description":"Successful Response","content":{"application/json":{"schema":{"$ref":"#/components/schemas/DailyReportResponse"}}}},"404":{"description":"Not found"},"422":{"description":"Validation Error","content":{"application/json":{"schema":{"$ref":"#/components/schemas/HTTPValidationError"}}}}}}},"/api/v1/organizations/reports/workflows":{"get":{"tags":["main"],"summary":"Get Workflow Options","description":"Get all workflows for the user's organization.\nUsed to populate the workflow selector dropdown in the reports page.","operationId":"get_workflow_options_api_v1_organizations_reports_workflows_get","parameters":[{"name":"authorization","in":"header","required":false,"schema":{"anyOf":[{"type":"string"},{"type":"null"}],"title":"Authorization"}},{"name":"X-API-Key","in":"header","required":false,"schema":{"anyOf":[{"type":"string"},{"type":"null"}],"title":"X-Api-Key"}}],"responses":{"200":{"description":"Successful Response","content":{"application/json":{"schema":{"type":"array","items":{"$ref":"#/components/schemas/WorkflowOption"},"title":"Response Get Workflow Options Api V1 Organizations Reports Workflows Get"}}}},"404":{"description":"Not found"},"422":{"description":"Validation Error","content":{"application/json":{"schema":{"$ref":"#/components/schemas/HTTPValidationError"}}}}}}},"/api/v1/organizations/reports/daily/runs":{"get":{"tags":["main"],"summary":"Get Daily Runs Detail","description":"Get detailed workflow runs for the specified date.\nUsed for CSV export functionality.","operationId":"get_daily_runs_detail_api_v1_organizations_reports_daily_runs_get","parameters":[{"name":"date","in":"query","required":true,"schema":{"type":"string","description":"Date in YYYY-MM-DD format","title":"Date"},"description":"Date in YYYY-MM-DD format"},{"name":"timezone","in":"query","required":true,"schema":{"type":"string","description":"IANA timezone (e.g., 'America/New_York')","title":"Timezone"},"description":"IANA timezone (e.g., 'America/New_York')"},{"name":"workflow_id","in":"query","required":false,"schema":{"anyOf":[{"type":"integer"},{"type":"null"}],"description":"Optional workflow ID to filter by","title":"Workflow Id"},"description":"Optional workflow ID to filter by"},{"name":"authorization","in":"header","required":false,"schema":{"anyOf":[{"type":"string"},{"type":"null"}],"title":"Authorization"}},{"name":"X-API-Key","in":"header","required":false,"schema":{"anyOf":[{"type":"string"},{"type":"null"}],"title":"X-Api-Key"}}],"responses":{"200":{"description":"Successful Response","content":{"application/json":{"schema":{"type":"array","items":{"$ref":"#/components/schemas/WorkflowRunDetail"},"title":"Response Get Daily Runs Detail Api V1 Organizations Reports Daily Runs Get"}}}},"404":{"description":"Not found"},"422":{"description":"Validation Error","content":{"application/json":{"schema":{"$ref":"#/components/schemas/HTTPValidationError"}}}}}}},"/api/v1/turn/credentials":{"get":{"tags":["main","turn"],"summary":"Get Turn Credentials","description":"Get time-limited TURN credentials for WebRTC connections.\n\nThis endpoint generates ephemeral TURN credentials that are:\n- Valid for the configured TTL (default: 24 hours)\n- Cryptographically bound to the user via HMAC\n- Compatible with coturn's use-auth-secret mode\n\nReturns:\n TurnCredentialsResponse with username, password, ttl, and TURN URIs","operationId":"get_turn_credentials_api_v1_turn_credentials_get","parameters":[{"name":"authorization","in":"header","required":false,"schema":{"anyOf":[{"type":"string"},{"type":"null"}],"title":"Authorization"}},{"name":"X-API-Key","in":"header","required":false,"schema":{"anyOf":[{"type":"string"},{"type":"null"}],"title":"X-Api-Key"}}],"responses":{"200":{"description":"Successful Response","content":{"application/json":{"schema":{"$ref":"#/components/schemas/TurnCredentialsResponse"}}}},"404":{"description":"Not found"},"422":{"description":"Validation Error","content":{"application/json":{"schema":{"$ref":"#/components/schemas/HTTPValidationError"}}}}}}},"/api/v1/public/embed/init":{"post":{"tags":["main"],"summary":"Initialize Embed Session","description":"Initialize an embed session with token validation and domain checking.\n\nThis endpoint:\n1. Validates the embed token\n2. Checks domain whitelist\n3. Creates a workflow run\n4. Generates a temporary session token\n5. Returns configuration for the widget","operationId":"initialize_embed_session_api_v1_public_embed_init_post","requestBody":{"content":{"application/json":{"schema":{"$ref":"#/components/schemas/InitEmbedRequest"}}},"required":true},"responses":{"200":{"description":"Successful Response","content":{"application/json":{"schema":{"$ref":"#/components/schemas/InitEmbedResponse"}}}},"404":{"description":"Not found"},"422":{"description":"Validation Error","content":{"application/json":{"schema":{"$ref":"#/components/schemas/HTTPValidationError"}}}}}},"options":{"tags":["main"],"summary":"Options Init","description":"Handle CORS preflight for init endpoint","operationId":"options_init_api_v1_public_embed_init_options","responses":{"200":{"description":"Successful Response","content":{"application/json":{"schema":{}}}},"404":{"description":"Not found"}}}},"/api/v1/public/embed/config/{token}":{"get":{"tags":["main"],"summary":"Get Embed Config","description":"Get embed configuration without creating a session.\n\nThis endpoint is used to fetch widget configuration for display purposes\nwithout actually starting a call session.","operationId":"get_embed_config_api_v1_public_embed_config__token__get","parameters":[{"name":"token","in":"path","required":true,"schema":{"type":"string","title":"Token"}}],"responses":{"200":{"description":"Successful Response","content":{"application/json":{"schema":{"$ref":"#/components/schemas/EmbedConfigResponse"}}}},"404":{"description":"Not found"},"422":{"description":"Validation Error","content":{"application/json":{"schema":{"$ref":"#/components/schemas/HTTPValidationError"}}}}}},"options":{"tags":["main"],"summary":"Options Config","description":"Handle CORS preflight for config endpoint","operationId":"options_config_api_v1_public_embed_config__token__options","parameters":[{"name":"token","in":"path","required":true,"schema":{"type":"string","title":"Token"}}],"responses":{"200":{"description":"Successful Response","content":{"application/json":{"schema":{}}}},"404":{"description":"Not found"},"422":{"description":"Validation Error","content":{"application/json":{"schema":{"$ref":"#/components/schemas/HTTPValidationError"}}}}}}},"/api/v1/public/embed/turn-credentials/{session_token}":{"get":{"tags":["main"],"summary":"Get Public Turn Credentials","description":"Get TURN credentials for an embed session.\n\nThis endpoint allows embedded widgets to obtain TURN server credentials\nfor WebRTC connections without requiring authentication.\n\nArgs:\n session_token: The session token from embed initialization\n\nReturns:\n TurnCredentialsResponse with username, password, ttl, and TURN URIs","operationId":"get_public_turn_credentials_api_v1_public_embed_turn_credentials__session_token__get","parameters":[{"name":"session_token","in":"path","required":true,"schema":{"type":"string","title":"Session Token"}}],"responses":{"200":{"description":"Successful Response","content":{"application/json":{"schema":{"$ref":"#/components/schemas/TurnCredentialsResponse"}}}},"404":{"description":"Not found"},"422":{"description":"Validation Error","content":{"application/json":{"schema":{"$ref":"#/components/schemas/HTTPValidationError"}}}}}},"options":{"tags":["main"],"summary":"Options Turn Credentials","description":"Handle CORS preflight for TURN credentials endpoint","operationId":"options_turn_credentials_api_v1_public_embed_turn_credentials__session_token__options","parameters":[{"name":"session_token","in":"path","required":true,"schema":{"type":"string","title":"Session Token"}}],"responses":{"200":{"description":"Successful Response","content":{"application/json":{"schema":{}}}},"404":{"description":"Not found"},"422":{"description":"Validation Error","content":{"application/json":{"schema":{"$ref":"#/components/schemas/HTTPValidationError"}}}}}}},"/api/v1/public/agent/{uuid}":{"post":{"tags":["main"],"summary":"Initiate Call","description":"Initiate a phone call against the published agent.\n\nExecutes the workflow's currently released definition.","operationId":"initiate_call_api_v1_public_agent__uuid__post","parameters":[{"name":"uuid","in":"path","required":true,"schema":{"type":"string","title":"Uuid"}},{"name":"X-API-Key","in":"header","required":true,"schema":{"type":"string","title":"X-Api-Key"}}],"requestBody":{"required":true,"content":{"application/json":{"schema":{"$ref":"#/components/schemas/TriggerCallRequest"}}}},"responses":{"200":{"description":"Successful Response","content":{"application/json":{"schema":{"$ref":"#/components/schemas/TriggerCallResponse"}}}},"404":{"description":"Not found"},"422":{"description":"Validation Error","content":{"application/json":{"schema":{"$ref":"#/components/schemas/HTTPValidationError"}}}}}}},"/api/v1/public/agent/test/{uuid}":{"post":{"tags":["main"],"summary":"Initiate Call Test","description":"Initiate a phone call against the latest draft of the agent.\n\nUseful for verifying changes before publishing. Falls back to the\npublished definition when no draft exists.","operationId":"initiate_call_test_api_v1_public_agent_test__uuid__post","parameters":[{"name":"uuid","in":"path","required":true,"schema":{"type":"string","title":"Uuid"}},{"name":"X-API-Key","in":"header","required":true,"schema":{"type":"string","title":"X-Api-Key"}}],"requestBody":{"required":true,"content":{"application/json":{"schema":{"$ref":"#/components/schemas/TriggerCallRequest"}}}},"responses":{"200":{"description":"Successful Response","content":{"application/json":{"schema":{"$ref":"#/components/schemas/TriggerCallResponse"}}}},"404":{"description":"Not found"},"422":{"description":"Validation Error","content":{"application/json":{"schema":{"$ref":"#/components/schemas/HTTPValidationError"}}}}}}},"/api/v1/public/download/workflow/{token}/{artifact_type}":{"get":{"tags":["main"],"summary":"Download Workflow Artifact","description":"Download a workflow recording or transcript via public access token.\n\nThis endpoint:\n1. Validates the public access token\n2. Looks up the corresponding workflow run\n3. Generates a signed URL for the requested artifact\n4. 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The dispatcher resolves the org from the webhook's\naccount_id and the workflow from the called number's\n``inbound_workflow_id``. This is what ``configure_inbound`` writes into\neach provider's resource so per-workflow webhook bookkeeping disappears.\n\nProvider-specific signature/timestamp headers are not enumerated here \u2014\neach provider's ``verify_inbound_signature`` reads its own headers from\nthe dict, so adding a new provider doesn't require changes to this route.","operationId":"handle_inbound_run_api_v1_telephony_inbound_run_post","responses":{"200":{"description":"Successful Response","content":{"application/json":{"schema":{}}}},"404":{"description":"Not found"}}}},"/api/v1/telephony/inbound/fallback":{"post":{"tags":["main"],"summary":"Handle Inbound Fallback","description":"Fallback endpoint that returns audio message when calls cannot be processed.","operationId":"handle_inbound_fallback_api_v1_telephony_inbound_fallback_post","responses":{"200":{"description":"Successful Response","content":{"application/json":{"schema":{}}}},"404":{"description":"Not found"}}}},"/api/v1/telephony/inbound/{workflow_id}":{"post":{"tags":["main"],"summary":"Handle Inbound Telephony","description":"[LEGACY] Per-workflow inbound webhook.\n\nSuperseded by ``POST /inbound/run``, which resolves the workflow from\nthe called number's ``inbound_workflow_id`` and lets a single webhook\nURL serve every workflow in the org. 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user's organization.","operationId":"create_service_key_api_v1_user_service_keys_post","parameters":[{"name":"authorization","in":"header","required":false,"schema":{"anyOf":[{"type":"string"},{"type":"null"}],"title":"Authorization"}},{"name":"X-API-Key","in":"header","required":false,"schema":{"anyOf":[{"type":"string"},{"type":"null"}],"title":"X-Api-Key"}}],"requestBody":{"required":true,"content":{"application/json":{"schema":{"$ref":"#/components/schemas/CreateServiceKeyRequest"}}}},"responses":{"200":{"description":"Successful Response","content":{"application/json":{"schema":{"$ref":"#/components/schemas/CreateServiceKeyResponse"}}}},"404":{"description":"Not found"},"422":{"description":"Validation Error","content":{"application/json":{"schema":{"$ref":"#/components/schemas/HTTPValidationError"}}}}}}},"/api/v1/user/service-keys/{service_key_id}":{"delete":{"tags":["main"],"summary":"Archive Service Key","description":"Archive a service key.","operationId":"archive_service_key_api_v1_user_service_keys__service_key_id__delete","parameters":[{"name":"service_key_id","in":"path","required":true,"schema":{"type":"string","title":"Service Key Id"}},{"name":"authorization","in":"header","required":false,"schema":{"anyOf":[{"type":"string"},{"type":"null"}],"title":"Authorization"}},{"name":"X-API-Key","in":"header","required":false,"schema":{"anyOf":[{"type":"string"},{"type":"null"}],"title":"X-Api-Key"}}],"responses":{"200":{"description":"Successful Response","content":{"application/json":{"schema":{}}}},"404":{"description":"Not found"},"422":{"description":"Validation Error","content":{"application/json":{"schema":{"$ref":"#/components/schemas/HTTPValidationError"}}}}}}},"/api/v1/user/service-keys/{service_key_id}/reactivate":{"put":{"tags":["main"],"summary":"Reactivate Service Key","description":"Reactivate an archived service key.\n\nNote: This endpoint is provided for API compatibility but service key\nreactivation is not supported by MPS. Once archived, a service key\ncannot be reactivated and a new key must be created instead.","operationId":"reactivate_service_key_api_v1_user_service_keys__service_key_id__reactivate_put","parameters":[{"name":"service_key_id","in":"path","required":true,"schema":{"type":"string","title":"Service Key Id"}},{"name":"authorization","in":"header","required":false,"schema":{"anyOf":[{"type":"string"},{"type":"null"}],"title":"Authorization"}},{"name":"X-API-Key","in":"header","required":false,"schema":{"anyOf":[{"type":"string"},{"type":"null"}],"title":"X-Api-Key"}}],"responses":{"200":{"description":"Successful Response","content":{"application/json":{"schema":{}}}},"404":{"description":"Not found"},"422":{"description":"Validation Error","content":{"application/json":{"schema":{"$ref":"#/components/schemas/HTTPValidationError"}}}}}}},"/api/v1/organizations/usage/current-period":{"get":{"tags":["main"],"summary":"Get Current Period Usage","description":"Get current billing period usage for the user's organization.","operationId":"get_current_period_usage_api_v1_organizations_usage_current_period_get","parameters":[{"name":"authorization","in":"header","required":false,"schema":{"anyOf":[{"type":"string"},{"type":"null"}],"title":"Authorization"}},{"name":"X-API-Key","in":"header","required":false,"schema":{"anyOf":[{"type":"string"},{"type":"null"}],"title":"X-Api-Key"}}],"responses":{"200":{"description":"Successful Response","content":{"application/json":{"schema":{"$ref":"#/components/schemas/CurrentUsageResponse"}}}},"404":{"description":"Not found"},"422":{"description":"Validation Error","content":{"application/json":{"schema":{"$ref":"#/components/schemas/HTTPValidationError"}}}}}}},"/api/v1/organizations/usage/mps-credits":{"get":{"tags":["main"],"summary":"Get Mps Credits","description":"Get aggregated usage and quota from MPS.\n\nOSS users: queries by provider_id (created_by).\nHosted users: queries by organization_id.","operationId":"get_mps_credits_api_v1_organizations_usage_mps_credits_get","parameters":[{"name":"authorization","in":"header","required":false,"schema":{"anyOf":[{"type":"string"},{"type":"null"}],"title":"Authorization"}},{"name":"X-API-Key","in":"header","required":false,"schema":{"anyOf":[{"type":"string"},{"type":"null"}],"title":"X-Api-Key"}}],"responses":{"200":{"description":"Successful Response","content":{"application/json":{"schema":{"$ref":"#/components/schemas/MPSCreditsResponse"}}}},"404":{"description":"Not found"},"422":{"description":"Validation Error","content":{"application/json":{"schema":{"$ref":"#/components/schemas/HTTPValidationError"}}}}}}},"/api/v1/organizations/usage/runs":{"get":{"tags":["main"],"summary":"Get Usage History","description":"Get paginated workflow runs with usage for the organization.","operationId":"get_usage_history_api_v1_organizations_usage_runs_get","parameters":[{"name":"start_date","in":"query","required":false,"schema":{"anyOf":[{"type":"string"},{"type":"null"}],"description":"ISO 8601 date-time string (UTC). Lower bound (inclusive) on `created_at`.","examples":["2026-04-01T00:00:00Z"],"title":"Start Date"},"description":"ISO 8601 date-time string (UTC). Lower bound (inclusive) on `created_at`."},{"name":"end_date","in":"query","required":false,"schema":{"anyOf":[{"type":"string"},{"type":"null"}],"description":"ISO 8601 date-time string (UTC). Upper bound (inclusive) on `created_at`.","examples":["2026-05-01T00:00:00Z"],"title":"End Date"},"description":"ISO 8601 date-time string (UTC). Upper bound (inclusive) on `created_at`."},{"name":"page","in":"query","required":false,"schema":{"type":"integer","minimum":1,"default":1,"title":"Page"}},{"name":"limit","in":"query","required":false,"schema":{"type":"integer","maximum":100,"minimum":1,"default":50,"title":"Limit"}},{"name":"filters","in":"query","required":false,"schema":{"anyOf":[{"type":"string"},{"type":"null"}],"description":"JSON-encoded array of filter objects. Each object has the shape:\n\n```json\n{ \"attribute\": \"\", \"type\": \"\", \"value\": }\n```\n\nSupported `attribute` / `type` / `value` combinations:\n\n| attribute | type | value shape | matches |\n|-----------------|---------------|----------------------------------------------|------------------------------------------------------|\n| `runId` | `number` | `{ \"value\": 12345 }` | exact run id |\n| `workflowId` | `number` | `{ \"value\": 42 }` | exact agent (workflow) id |\n| `campaignId` | `number` | `{ \"value\": 7 }` | exact campaign id |\n| `callerNumber` | `text` | `{ \"value\": \"415555\" }` | substring match on `initial_context.caller_number` |\n| `calledNumber` | `text` | `{ \"value\": \"9911848\" }` | substring match on `initial_context.called_number` |\n| `dispositionCode` | `multiSelect` | `{ \"codes\": [\"XFER\", \"DNC\"] }` | any of the codes in `gathered_context.mapped_call_disposition` |\n| `duration` | `numberRange` | `{ \"min\": 60, \"max\": 300 }` | call duration (seconds), inclusive bounds |\n\nUnknown attributes and unsupported `type` values are silently ignored.\n\nDate filtering on this endpoint is done via the dedicated `start_date` / `end_date` query params, not via a `dateRange` filter object.\n","examples":["[{\"attribute\":\"callerNumber\",\"type\":\"text\",\"value\":{\"value\":\"415555\"}}]","[{\"attribute\":\"campaignId\",\"type\":\"number\",\"value\":{\"value\":7}},{\"attribute\":\"duration\",\"type\":\"numberRange\",\"value\":{\"min\":60,\"max\":300}}]","[{\"attribute\":\"dispositionCode\",\"type\":\"multiSelect\",\"value\":{\"codes\":[\"XFER\",\"DNC\"]}}]"],"title":"Filters"},"description":"JSON-encoded array of filter objects. Each object has the shape:\n\n```json\n{ \"attribute\": \"\", \"type\": \"\", \"value\": }\n```\n\nSupported `attribute` / `type` / `value` combinations:\n\n| attribute | type | value shape | matches |\n|-----------------|---------------|----------------------------------------------|------------------------------------------------------|\n| `runId` | `number` | `{ \"value\": 12345 }` | exact run id |\n| `workflowId` | `number` | `{ \"value\": 42 }` | exact agent (workflow) id |\n| `campaignId` | `number` | `{ \"value\": 7 }` | exact campaign id |\n| `callerNumber` | `text` | `{ \"value\": \"415555\" }` | substring match on `initial_context.caller_number` |\n| `calledNumber` | `text` | `{ \"value\": \"9911848\" }` | substring match on `initial_context.called_number` |\n| `dispositionCode` | `multiSelect` | `{ \"codes\": [\"XFER\", \"DNC\"] }` | any of the codes in `gathered_context.mapped_call_disposition` |\n| `duration` | `numberRange` | `{ \"min\": 60, \"max\": 300 }` | call duration (seconds), inclusive bounds |\n\nUnknown attributes and unsupported `type` values are silently ignored.\n\nDate filtering on this endpoint is done via the dedicated `start_date` / `end_date` query params, not via a `dateRange` filter object.\n"},{"name":"authorization","in":"header","required":false,"schema":{"anyOf":[{"type":"string"},{"type":"null"}],"title":"Authorization"}},{"name":"X-API-Key","in":"header","required":false,"schema":{"anyOf":[{"type":"string"},{"type":"null"}],"title":"X-Api-Key"}}],"responses":{"200":{"description":"Successful Response","content":{"application/json":{"schema":{"$ref":"#/components/schemas/UsageHistoryResponse"}}}},"404":{"description":"Not found"},"422":{"description":"Validation Error","content":{"application/json":{"schema":{"$ref":"#/components/schemas/HTTPValidationError"}}}}}}},"/api/v1/organizations/usage/runs/report":{"get":{"tags":["main"],"summary":"Download Usage Runs Report","description":"Download a CSV of runs matching the same filters as `/usage/runs`.","operationId":"download_usage_runs_report_api_v1_organizations_usage_runs_report_get","parameters":[{"name":"start_date","in":"query","required":false,"schema":{"anyOf":[{"type":"string"},{"type":"null"}],"description":"ISO 8601 date-time string (UTC). Lower bound (inclusive) on `created_at`.","title":"Start Date"},"description":"ISO 8601 date-time string (UTC). Lower bound (inclusive) on `created_at`."},{"name":"end_date","in":"query","required":false,"schema":{"anyOf":[{"type":"string"},{"type":"null"}],"description":"ISO 8601 date-time string (UTC). Upper bound (inclusive) on `created_at`.","title":"End Date"},"description":"ISO 8601 date-time string (UTC). Upper bound (inclusive) on `created_at`."},{"name":"filters","in":"query","required":false,"schema":{"anyOf":[{"type":"string"},{"type":"null"}],"description":"JSON-encoded array of filter objects. Each object has the shape:\n\n```json\n{ \"attribute\": \"\", \"type\": \"\", \"value\": }\n```\n\nSupported `attribute` / `type` / `value` combinations:\n\n| attribute | type | value shape | matches |\n|-----------------|---------------|----------------------------------------------|------------------------------------------------------|\n| `runId` | `number` | `{ \"value\": 12345 }` | exact run id |\n| `workflowId` | `number` | `{ \"value\": 42 }` | exact agent (workflow) id |\n| `campaignId` | `number` | `{ \"value\": 7 }` | exact campaign id |\n| `callerNumber` | `text` | `{ \"value\": \"415555\" }` | substring match on `initial_context.caller_number` |\n| `calledNumber` | `text` | `{ \"value\": \"9911848\" }` | substring match on `initial_context.called_number` |\n| `dispositionCode` | `multiSelect` | `{ \"codes\": [\"XFER\", \"DNC\"] }` | any of the codes in `gathered_context.mapped_call_disposition` |\n| `duration` | `numberRange` | `{ \"min\": 60, \"max\": 300 }` | call duration (seconds), inclusive bounds |\n\nUnknown attributes and unsupported `type` values are silently ignored.\n\nDate filtering on this endpoint is done via the dedicated `start_date` / `end_date` query params, not via a `dateRange` filter object.\n","title":"Filters"},"description":"JSON-encoded array of filter objects. Each object has the shape:\n\n```json\n{ \"attribute\": \"\", \"type\": \"\", \"value\": }\n```\n\nSupported `attribute` / `type` / `value` combinations:\n\n| attribute | type | value shape | matches |\n|-----------------|---------------|----------------------------------------------|------------------------------------------------------|\n| `runId` | `number` | `{ \"value\": 12345 }` | exact run id |\n| `workflowId` | `number` | `{ \"value\": 42 }` | exact agent (workflow) id |\n| `campaignId` | `number` | `{ \"value\": 7 }` | exact campaign id |\n| `callerNumber` | `text` | `{ \"value\": \"415555\" }` | substring match on `initial_context.caller_number` |\n| `calledNumber` | `text` | `{ \"value\": \"9911848\" }` | substring match on `initial_context.called_number` |\n| `dispositionCode` | `multiSelect` | `{ \"codes\": [\"XFER\", \"DNC\"] }` | any of the codes in `gathered_context.mapped_call_disposition` |\n| `duration` | `numberRange` | `{ \"min\": 60, \"max\": 300 }` | call duration (seconds), inclusive bounds |\n\nUnknown attributes and unsupported `type` values are silently ignored.\n\nDate filtering on this endpoint is done via the dedicated `start_date` / `end_date` query params, not via a `dateRange` filter object.\n"},{"name":"authorization","in":"header","required":false,"schema":{"anyOf":[{"type":"string"},{"type":"null"}],"title":"Authorization"}},{"name":"X-API-Key","in":"header","required":false,"schema":{"anyOf":[{"type":"string"},{"type":"null"}],"title":"X-Api-Key"}}],"responses":{"200":{"description":"Successful Response","content":{"application/json":{"schema":{}}}},"404":{"description":"Not found"},"422":{"description":"Validation Error","content":{"application/json":{"schema":{"$ref":"#/components/schemas/HTTPValidationError"}}}}}}},"/api/v1/organizations/usage/daily-breakdown":{"get":{"tags":["main"],"summary":"Get Daily Usage Breakdown","description":"Get daily usage breakdown for the last N days. Only available for organizations with pricing.","operationId":"get_daily_usage_breakdown_api_v1_organizations_usage_daily_breakdown_get","parameters":[{"name":"days","in":"query","required":false,"schema":{"type":"integer","maximum":30,"minimum":1,"description":"Number of days to include","default":7,"title":"Days"},"description":"Number of days to include"},{"name":"authorization","in":"header","required":false,"schema":{"anyOf":[{"type":"string"},{"type":"null"}],"title":"Authorization"}},{"name":"X-API-Key","in":"header","required":false,"schema":{"anyOf":[{"type":"string"},{"type":"null"}],"title":"X-Api-Key"}}],"responses":{"200":{"description":"Successful Response","content":{"application/json":{"schema":{"$ref":"#/components/schemas/DailyUsageBreakdownResponse"}}}},"404":{"description":"Not found"},"422":{"description":"Validation Error","content":{"application/json":{"schema":{"$ref":"#/components/schemas/HTTPValidationError"}}}}}}},"/api/v1/organizations/reports/daily":{"get":{"tags":["main"],"summary":"Get Daily Report","description":"Get daily report for the specified date and timezone.\nIf workflow_id is provided, filters results to that specific workflow.\nIf workflow_id is None, includes all workflows for the organization.","operationId":"get_daily_report_api_v1_organizations_reports_daily_get","parameters":[{"name":"date","in":"query","required":true,"schema":{"type":"string","description":"Date in YYYY-MM-DD format","title":"Date"},"description":"Date in YYYY-MM-DD format"},{"name":"timezone","in":"query","required":true,"schema":{"type":"string","description":"IANA timezone (e.g., 'America/New_York')","title":"Timezone"},"description":"IANA timezone (e.g., 'America/New_York')"},{"name":"workflow_id","in":"query","required":false,"schema":{"anyOf":[{"type":"integer"},{"type":"null"}],"description":"Optional workflow ID to filter by","title":"Workflow Id"},"description":"Optional workflow ID to filter by"},{"name":"authorization","in":"header","required":false,"schema":{"anyOf":[{"type":"string"},{"type":"null"}],"title":"Authorization"}},{"name":"X-API-Key","in":"header","required":false,"schema":{"anyOf":[{"type":"string"},{"type":"null"}],"title":"X-Api-Key"}}],"responses":{"200":{"description":"Successful Response","content":{"application/json":{"schema":{"$ref":"#/components/schemas/DailyReportResponse"}}}},"404":{"description":"Not found"},"422":{"description":"Validation Error","content":{"application/json":{"schema":{"$ref":"#/components/schemas/HTTPValidationError"}}}}}}},"/api/v1/organizations/reports/workflows":{"get":{"tags":["main"],"summary":"Get Workflow Options","description":"Get all workflows for the user's organization.\nUsed to populate the workflow selector dropdown in the reports page.","operationId":"get_workflow_options_api_v1_organizations_reports_workflows_get","parameters":[{"name":"authorization","in":"header","required":false,"schema":{"anyOf":[{"type":"string"},{"type":"null"}],"title":"Authorization"}},{"name":"X-API-Key","in":"header","required":false,"schema":{"anyOf":[{"type":"string"},{"type":"null"}],"title":"X-Api-Key"}}],"responses":{"200":{"description":"Successful Response","content":{"application/json":{"schema":{"type":"array","items":{"$ref":"#/components/schemas/WorkflowOption"},"title":"Response Get Workflow Options Api V1 Organizations Reports Workflows Get"}}}},"404":{"description":"Not found"},"422":{"description":"Validation Error","content":{"application/json":{"schema":{"$ref":"#/components/schemas/HTTPValidationError"}}}}}}},"/api/v1/organizations/reports/daily/runs":{"get":{"tags":["main"],"summary":"Get Daily Runs Detail","description":"Get detailed workflow runs for the specified date.\nUsed for CSV export functionality.","operationId":"get_daily_runs_detail_api_v1_organizations_reports_daily_runs_get","parameters":[{"name":"date","in":"query","required":true,"schema":{"type":"string","description":"Date in YYYY-MM-DD format","title":"Date"},"description":"Date in YYYY-MM-DD format"},{"name":"timezone","in":"query","required":true,"schema":{"type":"string","description":"IANA timezone (e.g., 'America/New_York')","title":"Timezone"},"description":"IANA timezone (e.g., 'America/New_York')"},{"name":"workflow_id","in":"query","required":false,"schema":{"anyOf":[{"type":"integer"},{"type":"null"}],"description":"Optional workflow ID to filter by","title":"Workflow Id"},"description":"Optional workflow ID to filter by"},{"name":"authorization","in":"header","required":false,"schema":{"anyOf":[{"type":"string"},{"type":"null"}],"title":"Authorization"}},{"name":"X-API-Key","in":"header","required":false,"schema":{"anyOf":[{"type":"string"},{"type":"null"}],"title":"X-Api-Key"}}],"responses":{"200":{"description":"Successful Response","content":{"application/json":{"schema":{"type":"array","items":{"$ref":"#/components/schemas/WorkflowRunDetail"},"title":"Response Get Daily Runs Detail Api V1 Organizations Reports Daily Runs Get"}}}},"404":{"description":"Not found"},"422":{"description":"Validation Error","content":{"application/json":{"schema":{"$ref":"#/components/schemas/HTTPValidationError"}}}}}}},"/api/v1/turn/credentials":{"get":{"tags":["main","turn"],"summary":"Get Turn Credentials","description":"Get time-limited TURN credentials for WebRTC connections.\n\nThis endpoint generates ephemeral TURN credentials that are:\n- Valid for the configured TTL (default: 24 hours)\n- Cryptographically bound to the user via HMAC\n- Compatible with coturn's use-auth-secret mode\n\nReturns:\n TurnCredentialsResponse with username, password, ttl, and TURN URIs","operationId":"get_turn_credentials_api_v1_turn_credentials_get","parameters":[{"name":"authorization","in":"header","required":false,"schema":{"anyOf":[{"type":"string"},{"type":"null"}],"title":"Authorization"}},{"name":"X-API-Key","in":"header","required":false,"schema":{"anyOf":[{"type":"string"},{"type":"null"}],"title":"X-Api-Key"}}],"responses":{"200":{"description":"Successful Response","content":{"application/json":{"schema":{"$ref":"#/components/schemas/TurnCredentialsResponse"}}}},"404":{"description":"Not found"},"422":{"description":"Validation Error","content":{"application/json":{"schema":{"$ref":"#/components/schemas/HTTPValidationError"}}}}}}},"/api/v1/public/embed/init":{"post":{"tags":["main"],"summary":"Initialize Embed Session","description":"Initialize an embed session with token validation and domain checking.\n\nThis endpoint:\n1. Validates the embed token\n2. Checks domain whitelist\n3. Creates a workflow run\n4. Generates a temporary session token\n5. Returns configuration for the widget","operationId":"initialize_embed_session_api_v1_public_embed_init_post","requestBody":{"content":{"application/json":{"schema":{"$ref":"#/components/schemas/InitEmbedRequest"}}},"required":true},"responses":{"200":{"description":"Successful Response","content":{"application/json":{"schema":{"$ref":"#/components/schemas/InitEmbedResponse"}}}},"404":{"description":"Not found"},"422":{"description":"Validation Error","content":{"application/json":{"schema":{"$ref":"#/components/schemas/HTTPValidationError"}}}}}},"options":{"tags":["main"],"summary":"Options Init","description":"Handle CORS preflight for init endpoint","operationId":"options_init_api_v1_public_embed_init_options","responses":{"200":{"description":"Successful Response","content":{"application/json":{"schema":{}}}},"404":{"description":"Not found"}}}},"/api/v1/public/embed/config/{token}":{"get":{"tags":["main"],"summary":"Get Embed Config","description":"Get embed configuration without creating a session.\n\nThis endpoint is used to fetch widget configuration for display purposes\nwithout actually starting a call session.","operationId":"get_embed_config_api_v1_public_embed_config__token__get","parameters":[{"name":"token","in":"path","required":true,"schema":{"type":"string","title":"Token"}}],"responses":{"200":{"description":"Successful Response","content":{"application/json":{"schema":{"$ref":"#/components/schemas/EmbedConfigResponse"}}}},"404":{"description":"Not found"},"422":{"description":"Validation Error","content":{"application/json":{"schema":{"$ref":"#/components/schemas/HTTPValidationError"}}}}}},"options":{"tags":["main"],"summary":"Options Config","description":"Handle CORS preflight for config endpoint","operationId":"options_config_api_v1_public_embed_config__token__options","parameters":[{"name":"token","in":"path","required":true,"schema":{"type":"string","title":"Token"}}],"responses":{"200":{"description":"Successful Response","content":{"application/json":{"schema":{}}}},"404":{"description":"Not found"},"422":{"description":"Validation Error","content":{"application/json":{"schema":{"$ref":"#/components/schemas/HTTPValidationError"}}}}}}},"/api/v1/public/embed/turn-credentials/{session_token}":{"get":{"tags":["main"],"summary":"Get Public Turn Credentials","description":"Get TURN credentials for an embed session.\n\nThis endpoint allows embedded widgets to obtain TURN server credentials\nfor WebRTC connections without requiring authentication.\n\nArgs:\n session_token: The session token from embed initialization\n\nReturns:\n TurnCredentialsResponse with username, password, ttl, and TURN URIs","operationId":"get_public_turn_credentials_api_v1_public_embed_turn_credentials__session_token__get","parameters":[{"name":"session_token","in":"path","required":true,"schema":{"type":"string","title":"Session Token"}}],"responses":{"200":{"description":"Successful Response","content":{"application/json":{"schema":{"$ref":"#/components/schemas/TurnCredentialsResponse"}}}},"404":{"description":"Not found"},"422":{"description":"Validation Error","content":{"application/json":{"schema":{"$ref":"#/components/schemas/HTTPValidationError"}}}}}},"options":{"tags":["main"],"summary":"Options Turn Credentials","description":"Handle CORS preflight for TURN credentials endpoint","operationId":"options_turn_credentials_api_v1_public_embed_turn_credentials__session_token__options","parameters":[{"name":"session_token","in":"path","required":true,"schema":{"type":"string","title":"Session Token"}}],"responses":{"200":{"description":"Successful Response","content":{"application/json":{"schema":{}}}},"404":{"description":"Not found"},"422":{"description":"Validation Error","content":{"application/json":{"schema":{"$ref":"#/components/schemas/HTTPValidationError"}}}}}}},"/api/v1/public/agent/{uuid}":{"post":{"tags":["main"],"summary":"Initiate Call","description":"Initiate a phone call against the published agent.\n\nExecutes the workflow's currently released definition.","operationId":"initiate_call_api_v1_public_agent__uuid__post","parameters":[{"name":"uuid","in":"path","required":true,"schema":{"type":"string","title":"Uuid"}},{"name":"X-API-Key","in":"header","required":true,"schema":{"type":"string","title":"X-Api-Key"}}],"requestBody":{"required":true,"content":{"application/json":{"schema":{"$ref":"#/components/schemas/TriggerCallRequest"}}}},"responses":{"200":{"description":"Successful Response","content":{"application/json":{"schema":{"$ref":"#/components/schemas/TriggerCallResponse"}}}},"404":{"description":"Not found"},"422":{"description":"Validation Error","content":{"application/json":{"schema":{"$ref":"#/components/schemas/HTTPValidationError"}}}}}}},"/api/v1/public/agent/test/{uuid}":{"post":{"tags":["main"],"summary":"Initiate Call Test","description":"Initiate a phone call against the latest draft of the agent.\n\nUseful for verifying changes before publishing. Falls back to the\npublished definition when no draft exists.","operationId":"initiate_call_test_api_v1_public_agent_test__uuid__post","parameters":[{"name":"uuid","in":"path","required":true,"schema":{"type":"string","title":"Uuid"}},{"name":"X-API-Key","in":"header","required":true,"schema":{"type":"string","title":"X-Api-Key"}}],"requestBody":{"required":true,"content":{"application/json":{"schema":{"$ref":"#/components/schemas/TriggerCallRequest"}}}},"responses":{"200":{"description":"Successful Response","content":{"application/json":{"schema":{"$ref":"#/components/schemas/TriggerCallResponse"}}}},"404":{"description":"Not found"},"422":{"description":"Validation Error","content":{"application/json":{"schema":{"$ref":"#/components/schemas/HTTPValidationError"}}}}}}},"/api/v1/public/download/workflow/{token}/{artifact_type}":{"get":{"tags":["main"],"summary":"Download Workflow Artifact","description":"Download a workflow recording or transcript via public access token.\n\nThis endpoint:\n1. Validates the public access token\n2. Looks up the corresponding workflow run\n3. Generates a signed URL for the requested artifact\n4. 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Follow the When using a Realtime provider like Gemini Live, you do not need to configure separate TTS and STT services — the realtime model handles speech in and out. However, you **must** still configure an **LLM** under the LLM tab: it powers variable extraction and QA analysis, which the realtime service does not perform. + + +## Gemini Live on Vertex AI + +If you want to run Gemini Live through your own Google Cloud project — for billing consolidation, VPC controls, regional residency, or enterprise IAM — Dograh also supports Gemini Live via **Vertex AI** as a separate provider (`google_vertex_realtime`). The default model is `google/gemini-live-2.5-flash-native-audio`. + +Unlike Google AI Studio (which uses a single Gemini API key), Vertex AI authenticates with a **service account** belonging to your Google Cloud project. + +### Prerequisites + +1. A Google Cloud project with billing enabled. +2. The Vertex AI API enabled on that project: + + ```bash + gcloud services enable aiplatform.googleapis.com --project=YOUR_PROJECT_ID + ``` + +3. A service account with the **Vertex AI User** role (`roles/aiplatform.user`) on the project: + + ```bash + gcloud projects add-iam-policy-binding YOUR_PROJECT_ID \ + --member="serviceAccount:YOUR_SA@YOUR_PROJECT_ID.iam.gserviceaccount.com" \ + --role="roles/aiplatform.user" + ``` + +4. A **JSON** key for that service account (P12 keys are not supported). + +### Creating the service account key + +1. In the GCP Console, go to **IAM & Admin → Service Accounts**. +2. Pick an existing service account (or create a new one). +3. Open the **Keys** tab → **Add Key → Create new key**. +4. Choose **JSON** as the key type and click **Create**. +5. The key file will download to your computer — store it securely and treat it as a secret. + + + Always pick **JSON**, not P12. The Vertex AI client libraries used by Dograh only accept service-account JSON keys; P12 is a legacy format retained for older Google Workspace integrations. + + +### Configuring Vertex AI Realtime in Dograh + +1. Go to **Model Configurations** in your Dograh dashboard. +2. Enable the **Realtime** toggle. +3. Under the **Realtime** section, select `google_vertex_realtime` as the provider. +4. Fill in the fields: + + | Field | What to put in | + |---|---| + | **Model** | Vertex publisher/model id, e.g. `google/gemini-live-2.5-flash-native-audio` | + | **Voice** | One of the built-in voices (Puck, Charon, Kore, Fenrir, Aoede) | + | **Language** | BCP-47 code (e.g. `en-US`) | + | **Project Id** | The `project_id` value from your service-account JSON | + | **Location** | GCP region where the model is available (e.g. `us-east4`) | + | **Credentials** | Paste the **entire contents** of the service-account JSON file | + | **API Key** | Leave blank — Vertex AI does not use API keys | + +5. Save the configuration. + + + Paste the whole JSON file into the **Credentials** field — including `private_key`, `client_email`, and all other entries. Don't try to extract individual fields. If `Credentials` is left blank, Dograh falls back to **Application Default Credentials (ADC)** from the host environment, which is useful when running Dograh on a GCP VM or GKE pod with an attached service account. + + + + IAM changes can take up to ~60 seconds to propagate. If you see `Permission 'aiplatform.endpoints.predict' denied`, wait a minute and retry — or double-check that the role was granted to the same service account whose JSON you pasted. \ No newline at end of file diff --git a/docs/integrations/telephony/custom.mdx b/docs/integrations/telephony/custom.mdx index 686ff7c..ad52208 100644 --- a/docs/integrations/telephony/custom.mdx +++ b/docs/integrations/telephony/custom.mdx @@ -193,7 +193,6 @@ If your provider POSTs webhooks to Dograh (answer URL, status callbacks, hangup ```python # providers/your_provider/routes.py from fastapi import APIRouter, Request -from api.services.telephony.factory import get_telephony_provider from api.services.telephony.status_processor import ( StatusCallbackRequest, _process_status_update, @@ -286,7 +285,7 @@ register(SPEC) | Field | Used by | | --- | --- | | `name` | Stored as the discriminator on every `TelephonyConfiguration` row and as the `WorkflowRunMode` value | -| `provider_cls` | `factory.get_telephony_provider*` | +| `provider_cls` | `factory.get_default_telephony_provider`, `get_telephony_provider_by_id`, `get_telephony_provider_for_run` | | `config_loader` | `factory._normalize_with_phone_numbers` (replaces the old if/elif chain) | | `transport_factory` | `run_pipeline_telephony` | | `audio_config` | `create_audio_config()` and `run_pipeline_telephony` | @@ -375,7 +374,7 @@ For end-to-end testing, save your provider through the telephony-configurations ## Best Practices -1. **Trust the registry** — never import another provider's class directly; resolve through `factory.get_telephony_provider*`. +1. **Trust the registry** — never import another provider's class directly; resolve through the factory helpers (`get_default_telephony_provider`, `get_telephony_provider_by_id`, etc.). 2. **Sensitive fields** — mark every credential field `sensitive=True` in `ProviderUIMetadata`. The save endpoint masks these on read and preserves the original when the client re-submits a masked value. 3. **Inbound signature verification** — always validate inbound webhook signatures in `verify_inbound_signature`. Returning `True` when no signature header is present is acceptable; return `False` when a signature *is* present but invalid. 4. **Transports load credentials lazily** — call `load_credentials_for_transport` with the `telephony_configuration_id` from the workflow run. Don't read the org's default config from `transport.py`. diff --git a/pipecat b/pipecat index 31199bd..8590e53 160000 --- a/pipecat +++ b/pipecat @@ -1 +1 @@ -Subproject commit 31199bd1f155a872690ff1de24b0fa5ccff49396 +Subproject commit 8590e5333d63eb69b78a193f9eeb2ff0584f9e9a diff --git a/scripts/format.sh b/scripts/format.sh index 93746b5..07de1ca 100755 --- a/scripts/format.sh +++ b/scripts/format.sh @@ -4,4 +4,6 @@ set -euo pipefail ruff check api --select I --select F401 --fix ruff format api +ruff format pipecat + (cd ui && npm run fix-lint) diff --git a/sdk/python/src/dograh_sdk/_generated_models.py b/sdk/python/src/dograh_sdk/_generated_models.py index cbb675c..7f09423 100644 --- a/sdk/python/src/dograh_sdk/_generated_models.py +++ b/sdk/python/src/dograh_sdk/_generated_models.py @@ -1,6 +1,6 @@ # generated by datamodel-codegen: -# filename: dograh-openapi-XXXXXX.json.ZdsSaa9ytb -# timestamp: 2026-05-16T09:21:15+00:00 +# filename: dograh-openapi-XXXXXX.json.UrxDUj7bBM +# timestamp: 2026-05-16T12:21:33+00:00 from __future__ import annotations diff --git a/ui/src/app/tools/[toolUuid]/components/HttpApiToolConfig.tsx b/ui/src/app/tools/[toolUuid]/components/HttpApiToolConfig.tsx index fc1f187..366f2db 100644 --- a/ui/src/app/tools/[toolUuid]/components/HttpApiToolConfig.tsx +++ b/ui/src/app/tools/[toolUuid]/components/HttpApiToolConfig.tsx @@ -11,6 +11,8 @@ import { KeyValueEditor, type KeyValueItem, ParameterEditor, + PresetParameterEditor, + type PresetToolParameter, type ToolParameter, UrlInput, } from "@/components/http"; @@ -35,6 +37,8 @@ export interface HttpApiToolConfigProps { onHeadersChange: (headers: KeyValueItem[]) => void; parameters: ToolParameter[]; onParametersChange: (parameters: ToolParameter[]) => void; + presetParameters: PresetToolParameter[]; + onPresetParametersChange: (parameters: PresetToolParameter[]) => void; timeoutMs: number; onTimeoutMsChange: (timeout: number) => void; customMessage: string; @@ -61,6 +65,8 @@ export function HttpApiToolConfig({ onHeadersChange, parameters, onParametersChange, + presetParameters, + onPresetParametersChange, timeoutMs, onTimeoutMsChange, customMessage, @@ -182,7 +188,7 @@ export function HttpApiToolConfig({
- +
+
+ + + +
+