mirror of
https://github.com/dograh-hq/dograh.git
synced 2026-06-16 08:25:18 +02:00
feat: add huggingface inferece provider endpoint
This commit is contained in:
Abhishek Kumar
parent
ef266daa6e
commit
dd3f2e7323
7 changed files with 315 additions and 2 deletions
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@ -49,6 +49,7 @@ class UserConfigurationValidator:
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ServiceProviders.CAMB.value: self._check_camb_api_key,
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ServiceProviders.AWS_BEDROCK.value: self._check_aws_bedrock_api_key,
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ServiceProviders.SPEACHES.value: self._check_speaches_api_key,
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ServiceProviders.HUGGINGFACE.value: self._check_huggingface_api_key,
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ServiceProviders.GOOGLE_VERTEX.value: self._check_google_vertex_llm_api_key,
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ServiceProviders.OPENAI_REALTIME.value: self._check_openai_api_key,
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ServiceProviders.GROK_REALTIME.value: self._check_grok_realtime_api_key,
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@ -360,6 +361,14 @@ class UserConfigurationValidator:
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raise ValueError("base_url is required for Speaches services")
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return True
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def _check_huggingface_api_key(self, model: str, api_key: str) -> bool:
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if not api_key.startswith("hf_"):
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raise ValueError(
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"Invalid Hugging Face API token format. Use a token that starts with "
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"'hf_' and has Inference Providers permission."
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)
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return True
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def _check_google_vertex_realtime_api_key(self, model: str, service_config) -> bool:
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if not getattr(service_config, "project_id", None):
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raise ValueError("project_id is required for Google Vertex Realtime")
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@ -68,6 +68,7 @@ class ServiceProviders(str, Enum):
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CAMB = "camb"
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AWS_BEDROCK = "aws_bedrock"
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SPEACHES = "speaches"
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HUGGINGFACE = "huggingface"
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ASSEMBLYAI = "assemblyai"
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GLADIA = "gladia"
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RIME = "rime"
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@ -94,6 +95,7 @@ class BaseServiceConfiguration(BaseModel):
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ServiceProviders.DOGRAH,
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ServiceProviders.AWS_BEDROCK,
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ServiceProviders.SPEACHES,
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ServiceProviders.HUGGINGFACE,
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ServiceProviders.ASSEMBLYAI,
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ServiceProviders.GLADIA,
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ServiceProviders.RIME,
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@ -255,6 +257,11 @@ SPEACHES_PROVIDER_MODEL_CONFIG = provider_model_config(
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),
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provider_docs_url="https://github.com/speaches-ai/speaches",
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)
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HUGGINGFACE_PROVIDER_MODEL_CONFIG = provider_model_config(
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"Hugging Face",
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description="Hosted Hugging Face Inference Providers API for usage-based inference.",
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provider_docs_url="https://huggingface.co/docs/inference-providers/en/index",
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)
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AZURE_SPEECH_PROVIDER_MODEL_CONFIG = provider_model_config(
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"Azure Speech Services",
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description="Azure Cognitive Services Speech — TTS and STT via the Azure Speech SDK.",
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@ -471,6 +478,35 @@ class SpeachesLLMConfiguration(BaseLLMConfiguration):
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)
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HUGGINGFACE_LLM_MODELS = [
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"openai/gpt-oss-120b:cerebras",
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"deepseek-ai/DeepSeek-R1:fastest",
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"Qwen/Qwen3-Coder-480B-A35B-Instruct:fastest",
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]
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@register_llm
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class HuggingFaceLLMConfiguration(BaseLLMConfiguration):
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model_config = HUGGINGFACE_PROVIDER_MODEL_CONFIG
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provider: Literal[ServiceProviders.HUGGINGFACE] = ServiceProviders.HUGGINGFACE
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model: str = Field(
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default="openai/gpt-oss-120b:cerebras",
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description="Hugging Face chat-completion model identifier, optionally with provider suffix.",
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json_schema_extra={
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"examples": HUGGINGFACE_LLM_MODELS,
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"allow_custom_input": True,
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},
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)
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base_url: str = Field(
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default="https://router.huggingface.co/v1",
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description="Hugging Face OpenAI-compatible chat-completions router base URL.",
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)
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bill_to: str | None = Field(
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default=None,
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description="Optional Hugging Face organization or user to bill using X-HF-Bill-To.",
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)
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MINIMAX_MODELS = [
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"MiniMax-M2.7",
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"MiniMax-M2.7-highspeed",
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@ -741,6 +777,7 @@ LLMConfig = Annotated[
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DograhLLMService,
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AWSBedrockLLMConfiguration,
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SpeachesLLMConfiguration,
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HuggingFaceLLMConfiguration,
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MiniMaxLLMConfiguration,
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SarvamLLMConfiguration,
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],
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@ -1334,6 +1371,38 @@ class SpeachesSTTConfiguration(BaseSTTConfiguration):
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)
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HUGGINGFACE_STT_MODELS = [
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"openai/whisper-large-v3-turbo",
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"openai/whisper-large-v3",
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]
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@register_stt
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class HuggingFaceSTTConfiguration(BaseSTTConfiguration):
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model_config = HUGGINGFACE_PROVIDER_MODEL_CONFIG
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provider: Literal[ServiceProviders.HUGGINGFACE] = ServiceProviders.HUGGINGFACE
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model: str = Field(
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default="openai/whisper-large-v3-turbo",
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description="Hugging Face ASR model identifier served through Inference Providers.",
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json_schema_extra={
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"examples": HUGGINGFACE_STT_MODELS,
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"allow_custom_input": True,
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},
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)
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base_url: str = Field(
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default="https://router.huggingface.co/hf-inference",
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description="Hugging Face Inference Providers router base URL.",
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)
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bill_to: str | None = Field(
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default=None,
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description="Optional Hugging Face organization or user to bill using X-HF-Bill-To.",
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)
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return_timestamps: bool = Field(
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default=False,
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description="Request timestamp chunks when supported by the selected provider/model.",
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)
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ASSEMBLYAI_STT_MODELS = ["u3-rt-pro"]
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ASSEMBLYAI_STT_LANGUAGES = ["en", "es", "de", "fr", "pt", "it"]
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@ -1406,6 +1475,7 @@ STTConfig = Annotated[
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SpeechmaticsSTTConfiguration,
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SarvamSTTConfiguration,
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SpeachesSTTConfiguration,
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HuggingFaceSTTConfiguration,
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AssemblyAISTTConfiguration,
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GladiaSTTConfiguration,
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AzureSpeechSTTConfiguration,
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@ -39,8 +39,17 @@ from pipecat.services.google.vertex.llm import (
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GoogleVertexLLMSettings,
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)
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from pipecat.services.groq.llm import GroqLLMService, GroqLLMSettings
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from pipecat.services.huggingface.llm import (
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HuggingFaceLLMService,
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HuggingFaceLLMSettings,
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)
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from pipecat.services.huggingface.stt import (
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HuggingFaceSTTService,
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HuggingFaceSTTSettings,
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)
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from pipecat.services.minimax.llm import MiniMaxLLMService
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from pipecat.services.minimax.tts import MiniMaxTTSSettings
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from pipecat.services.openai._constants import OPENAI_SAMPLE_RATE
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from pipecat.services.openai.base_llm import OpenAILLMSettings
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from pipecat.services.openai.llm import OpenAILLMService
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from pipecat.services.openai.stt import (
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@ -218,6 +227,22 @@ def create_stt_service(
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),
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sample_rate=audio_config.transport_in_sample_rate,
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)
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elif user_config.stt.provider == ServiceProviders.HUGGINGFACE.value:
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base_url = (
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getattr(user_config.stt, "base_url", None)
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or "https://router.huggingface.co/hf-inference"
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)
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_validate_runtime_service_url(base_url, "base_url")
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return HuggingFaceSTTService(
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api_key=user_config.stt.api_key,
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base_url=base_url,
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bill_to=getattr(user_config.stt, "bill_to", None),
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settings=HuggingFaceSTTSettings(
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model=user_config.stt.model,
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return_timestamps=getattr(user_config.stt, "return_timestamps", False),
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),
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sample_rate=audio_config.transport_in_sample_rate,
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)
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elif user_config.stt.provider == ServiceProviders.ASSEMBLYAI.value:
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language = getattr(user_config.stt, "language", None)
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settings_kwargs = {"model": user_config.stt.model, "language": language}
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@ -320,6 +345,7 @@ def create_tts_service(
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kwargs["base_url"] = base_url
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return OpenAITTSService(
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api_key=user_config.tts.api_key,
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sample_rate=OPENAI_SAMPLE_RATE,
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settings=OpenAITTSSettings(model=user_config.tts.model),
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text_filters=[xml_function_tag_filter],
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skip_aggregator_types=["recording_router", "recording"],
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@ -581,6 +607,7 @@ def create_llm_service_from_provider(
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location: str | None = None,
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credentials: str | None = None,
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temperature: float | None = None,
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bill_to: str | None = None,
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):
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"""Create an LLM service from explicit provider/model/api_key.
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@ -663,6 +690,15 @@ def create_llm_service_from_provider(
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api_key=api_key or "none",
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settings=SpeachesLLMSettings(model=model),
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)
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elif provider == ServiceProviders.HUGGINGFACE.value:
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base_url = base_url or "https://router.huggingface.co/v1"
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_validate_runtime_service_url(base_url, "base_url")
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return HuggingFaceLLMService(
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api_key=api_key,
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base_url=base_url,
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bill_to=bill_to,
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settings=HuggingFaceLLMSettings(model=model, temperature=0.1),
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)
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elif provider == ServiceProviders.MINIMAX.value:
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base_url = base_url or "https://api.minimax.io/v1"
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_validate_runtime_service_url(base_url, "base_url")
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@ -875,6 +911,9 @@ def create_llm_service(user_config, correlation_id: str | None = None):
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kwargs["endpoint"] = user_config.llm.endpoint
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elif provider == ServiceProviders.SPEACHES.value:
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kwargs["base_url"] = user_config.llm.base_url
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elif provider == ServiceProviders.HUGGINGFACE.value:
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kwargs["base_url"] = user_config.llm.base_url
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kwargs["bill_to"] = user_config.llm.bill_to
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elif provider == ServiceProviders.AWS_BEDROCK.value:
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kwargs["aws_access_key"] = user_config.llm.aws_access_key
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kwargs["aws_secret_key"] = user_config.llm.aws_secret_key
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131
api/tests/test_huggingface_stt_service_factory.py
Normal file
131
api/tests/test_huggingface_stt_service_factory.py
Normal file
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@ -0,0 +1,131 @@
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from types import SimpleNamespace
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from unittest.mock import patch
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from api.services.configuration.check_validity import UserConfigurationValidator
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from api.services.configuration.registry import (
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REGISTRY,
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HuggingFaceLLMConfiguration,
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HuggingFaceSTTConfiguration,
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ServiceProviders,
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ServiceType,
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)
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from api.services.pipecat.service_factory import (
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create_llm_service,
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create_stt_service,
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)
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def test_huggingface_stt_configuration_defaults_and_registry():
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config = HuggingFaceSTTConfiguration(api_key="hf_test")
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assert config.provider == ServiceProviders.HUGGINGFACE
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assert config.model == "openai/whisper-large-v3-turbo"
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assert config.base_url == "https://router.huggingface.co/hf-inference"
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assert config.return_timestamps is False
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assert (
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REGISTRY[ServiceType.STT][ServiceProviders.HUGGINGFACE]
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is HuggingFaceSTTConfiguration
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)
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def test_huggingface_llm_configuration_defaults_and_registry():
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config = HuggingFaceLLMConfiguration(api_key="hf_test")
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assert config.provider == ServiceProviders.HUGGINGFACE
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assert config.model == "openai/gpt-oss-120b:cerebras"
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assert config.base_url == "https://router.huggingface.co/v1"
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assert (
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REGISTRY[ServiceType.LLM][ServiceProviders.HUGGINGFACE]
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is HuggingFaceLLMConfiguration
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)
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def test_create_huggingface_llm_service_uses_openai_compatible_router():
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user_config = SimpleNamespace(
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llm=SimpleNamespace(
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provider=ServiceProviders.HUGGINGFACE.value,
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api_key="hf_test",
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model="deepseek-ai/DeepSeek-R1:fastest",
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base_url="https://router.huggingface.co/v1",
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bill_to="demo-org",
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)
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)
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with patch(
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"api.services.pipecat.service_factory.HuggingFaceLLMService"
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) as mock_service:
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create_llm_service(user_config)
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assert mock_service.call_count == 1
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kwargs = mock_service.call_args.kwargs
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assert kwargs["api_key"] == "hf_test"
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assert kwargs["base_url"] == "https://router.huggingface.co/v1"
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assert kwargs["bill_to"] == "demo-org"
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assert kwargs["settings"].model == "deepseek-ai/DeepSeek-R1:fastest"
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assert kwargs["settings"].temperature == 0.1
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def test_create_huggingface_stt_service_uses_hosted_defaults():
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user_config = SimpleNamespace(
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stt=SimpleNamespace(
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provider=ServiceProviders.HUGGINGFACE.value,
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api_key="hf_test",
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model="openai/whisper-large-v3-turbo",
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base_url="https://router.huggingface.co/hf-inference",
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bill_to="demo-org",
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return_timestamps=True,
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)
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)
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audio_config = SimpleNamespace(transport_in_sample_rate=16000)
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with patch(
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"api.services.pipecat.service_factory.HuggingFaceSTTService"
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) as mock_service:
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create_stt_service(user_config, audio_config)
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assert mock_service.call_count == 1
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kwargs = mock_service.call_args.kwargs
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assert kwargs["api_key"] == "hf_test"
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assert kwargs["base_url"] == "https://router.huggingface.co/hf-inference"
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assert kwargs["bill_to"] == "demo-org"
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assert kwargs["sample_rate"] == 16000
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assert kwargs["settings"].model == "openai/whisper-large-v3-turbo"
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assert kwargs["settings"].return_timestamps is True
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def test_validator_accepts_huggingface_stt_token_format():
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validator = UserConfigurationValidator()
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assert (
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validator._validate_service(
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HuggingFaceSTTConfiguration(api_key="hf_test"),
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"stt",
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)
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== []
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)
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assert (
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validator._validate_service(
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HuggingFaceLLMConfiguration(api_key="hf_test"),
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"llm",
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)
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== []
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)
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def test_validator_rejects_non_huggingface_token_format():
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validator = UserConfigurationValidator()
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errors = validator._validate_service(
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HuggingFaceSTTConfiguration(api_key="not-hf-token"),
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"stt",
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)
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assert errors == [
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{
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"model": "stt",
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"message": (
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"Invalid Hugging Face API token format. Use a token that starts with "
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"'hf_' and has Inference Providers permission."
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),
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}
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]
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31
api/tests/test_openai_tts_service_factory.py
Normal file
31
api/tests/test_openai_tts_service_factory.py
Normal file
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@ -0,0 +1,31 @@
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from types import SimpleNamespace
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from unittest.mock import patch
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from pipecat.services.openai._constants import OPENAI_SAMPLE_RATE
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from api.services.configuration.registry import ServiceProviders
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from api.services.pipecat.service_factory import create_tts_service
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def test_create_openai_tts_service_uses_openai_pcm_sample_rate():
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user_config = SimpleNamespace(
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tts=SimpleNamespace(
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provider=ServiceProviders.OPENAI.value,
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api_key="test-key",
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model="gpt-4o-mini-tts",
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voice="alloy",
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base_url=None,
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)
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)
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audio_config = SimpleNamespace(
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transport_out_sample_rate=16000,
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transport_in_sample_rate=16000,
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)
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with patch("api.services.pipecat.service_factory.OpenAITTSService") as mock_service:
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create_tts_service(user_config, audio_config)
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assert mock_service.call_count == 1
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kwargs = mock_service.call_args.kwargs
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assert kwargs["sample_rate"] == OPENAI_SAMPLE_RATE
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assert kwargs["settings"].model == "gpt-4o-mini-tts"
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2
pipecat
2
pipecat
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@ -1 +1 @@
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Subproject commit 0d64dc6e0e3e6b3c46cc66373e34b4f54f980268
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Subproject commit 78906afbfc2a2b0dd57c091a3e28e19ae4c5e52c
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@ -5,6 +5,8 @@ import {
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ChevronRight,
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CircleDollarSign,
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CreditCard,
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ExternalLink,
|
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Info,
|
||||
RefreshCw,
|
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} from "lucide-react";
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import Link from "next/link";
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|
|
@ -124,7 +126,8 @@ export default function BillingPage() {
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);
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const isBillingV2 = credits?.billing_version === "v2";
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const canPurchaseCredits = isBillingV2 && config?.deploymentMode !== "oss";
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const isOssMode = config?.deploymentMode === "oss";
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const canPurchaseCredits = isBillingV2 && !isOssMode;
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const totalQuota = credits?.total_quota ?? 0;
|
||||
const remainingCredits = credits?.remaining_credits ?? 0;
|
||||
const usedCredits = credits?.total_credits_used ?? 0;
|
||||
|
|
@ -265,6 +268,36 @@ export default function BillingPage() {
|
|||
</div>
|
||||
</div>
|
||||
|
||||
{isOssMode && (
|
||||
<div className="flex gap-3 rounded-lg border border-amber-200 bg-amber-50 p-4 dark:border-amber-900/50 dark:bg-amber-950/30">
|
||||
<Info className="mt-0.5 h-4 w-4 flex-shrink-0 text-amber-600 dark:text-amber-400" />
|
||||
<div className="text-sm text-amber-900 dark:text-amber-200">
|
||||
<p className="font-medium">Credit purchases are unavailable in OSS mode</p>
|
||||
<p className="mt-1">
|
||||
You can't purchase credits from this self-hosted app. Sign up and
|
||||
purchase credits at{" "}
|
||||
<a
|
||||
href="https://app.dograh.com"
|
||||
target="_blank"
|
||||
rel="noopener noreferrer"
|
||||
className="inline-flex items-center gap-1 font-medium underline underline-offset-2"
|
||||
>
|
||||
app.dograh.com
|
||||
<ExternalLink className="h-3 w-3" />
|
||||
</a>
|
||||
. Then add the generated service key in{" "}
|
||||
<Link
|
||||
href="/model-configurations"
|
||||
className="font-medium underline underline-offset-2"
|
||||
>
|
||||
Model Configurations
|
||||
</Link>
|
||||
. Usage for that service key is visible in app.dograh.com.
|
||||
</p>
|
||||
</div>
|
||||
</div>
|
||||
)}
|
||||
|
||||
<div className="grid gap-4 md:grid-cols-2">
|
||||
<Card>
|
||||
<CardHeader className="pb-2">
|
||||
|
|
|
|||
Loading…
Add table
Add a link
Reference in a new issue