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fix: prefix embedding provider env vars with EMBEDDINGS_

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This commit is contained in:
Greyson LaLonde
2025-09-26 10:50:45 -04:00
committed by GitHub
parent b5b10a8cde
commit 091d1267d8
17 changed files with 104 additions and 74 deletions
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2
src/crewai/rag/embeddings/providers/aws/bedrock.py
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@@ -46,7 +46,7 @@ class BedrockProvider(BaseEmbeddingsProvider[AmazonBedrockEmbeddingFunction]):
model_name: str = Field(
default="amazon.titan-embed-text-v1",
description="Model name to use for embeddings",
validation_alias="BEDROCK_MODEL_NAME",
validation_alias="EMBEDDINGS_BEDROCK_MODEL_NAME",
)
session: Any = Field(
default_factory=create_aws_session, description="AWS session object"

4
src/crewai/rag/embeddings/providers/cohere/cohere_provider.py
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@@ -15,10 +15,10 @@ class CohereProvider(BaseEmbeddingsProvider[CohereEmbeddingFunction]):
default=CohereEmbeddingFunction, description="Cohere embedding function class"
)
api_key: str = Field(
description="Cohere API key", validation_alias="COHERE_API_KEY"
description="Cohere API key", validation_alias="EMBEDDINGS_COHERE_API_KEY"
)
model_name: str = Field(
default="large",
description="Model name to use for embeddings",
validation_alias="COHERE_MODEL_NAME",
validation_alias="EMBEDDINGS_COHERE_MODEL_NAME",
)

6
src/crewai/rag/embeddings/providers/google/generative_ai.py
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@@ -18,13 +18,13 @@ class GenerativeAiProvider(BaseEmbeddingsProvider[GoogleGenerativeAiEmbeddingFun
model_name: str = Field(
default="models/embedding-001",
description="Model name to use for embeddings",
validation_alias="GOOGLE_GENERATIVE_AI_MODEL_NAME",
validation_alias="EMBEDDINGS_GOOGLE_GENERATIVE_AI_MODEL_NAME",
)
api_key: str = Field(
description="Google API key", validation_alias="GOOGLE_API_KEY"
description="Google API key", validation_alias="EMBEDDINGS_GOOGLE_API_KEY"
)
task_type: str = Field(
default="RETRIEVAL_DOCUMENT",
description="Task type for embeddings",
validation_alias="GOOGLE_GENERATIVE_AI_TASK_TYPE",
validation_alias="EMBEDDINGS_GOOGLE_GENERATIVE_AI_TASK_TYPE",
)

8
src/crewai/rag/embeddings/providers/google/vertex.py
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@@ -18,18 +18,18 @@ class VertexAIProvider(BaseEmbeddingsProvider[GoogleVertexEmbeddingFunction]):
model_name: str = Field(
default="textembedding-gecko",
description="Model name to use for embeddings",
validation_alias="GOOGLE_VERTEX_MODEL_NAME",
validation_alias="EMBEDDINGS_GOOGLE_VERTEX_MODEL_NAME",
)
api_key: str = Field(
description="Google API key", validation_alias="GOOGLE_CLOUD_API_KEY"
description="Google API key", validation_alias="EMBEDDINGS_GOOGLE_CLOUD_API_KEY"
)
project_id: str = Field(
default="cloud-large-language-models",
description="GCP project ID",
validation_alias="GOOGLE_CLOUD_PROJECT",
validation_alias="EMBEDDINGS_GOOGLE_CLOUD_PROJECT",
)
region: str = Field(
default="us-central1",
description="GCP region",
validation_alias="GOOGLE_CLOUD_REGION",
validation_alias="EMBEDDINGS_GOOGLE_CLOUD_REGION",
)

2
src/crewai/rag/embeddings/providers/huggingface/huggingface_provider.py
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@@ -16,5 +16,5 @@ class HuggingFaceProvider(BaseEmbeddingsProvider[HuggingFaceEmbeddingServer]):
description="HuggingFace embedding function class",
)
url: str = Field(
description="HuggingFace API URL", validation_alias="HUGGINGFACE_URL"
description="HuggingFace API URL", validation_alias="EMBEDDINGS_HUGGINGFACE_URL"
)

64
src/crewai/rag/embeddings/providers/ibm/watson.py
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@@ -21,7 +21,7 @@ class WatsonProvider(BaseEmbeddingsProvider[WatsonEmbeddingFunction]):
default=WatsonEmbeddingFunction, description="Watson embedding function class"
)
model_id: str = Field(
description="Watson model ID", validation_alias="WATSON_MODEL_ID"
description="Watson model ID", validation_alias="EMBEDDINGS_WATSON_MODEL_ID"
)
params: dict[str, str | dict[str, str]] | None = Field(
default=None, description="Additional parameters"
@@ -30,87 +30,107 @@ class WatsonProvider(BaseEmbeddingsProvider[WatsonEmbeddingFunction]):
project_id: str | None = Field(
default=None,
description="Watson project ID",
validation_alias="WATSON_PROJECT_ID",
validation_alias="EMBEDDINGS_WATSON_PROJECT_ID",
)
space_id: str | None = Field(
default=None, description="Watson space ID", validation_alias="WATSON_SPACE_ID"
default=None,
description="Watson space ID",
validation_alias="EMBEDDINGS_WATSON_SPACE_ID",
)
api_client: Any | None = Field(default=None, description="Watson API client")
verify: bool | str | None = Field(
default=None, description="SSL verification", validation_alias="WATSON_VERIFY"
default=None,
description="SSL verification",
validation_alias="EMBEDDINGS_WATSON_VERIFY",
)
persistent_connection: bool = Field(
default=True,
description="Use persistent connection",
validation_alias="WATSON_PERSISTENT_CONNECTION",
validation_alias="EMBEDDINGS_WATSON_PERSISTENT_CONNECTION",
)
batch_size: int = Field(
default=100,
description="Batch size for processing",
validation_alias="WATSON_BATCH_SIZE",
validation_alias="EMBEDDINGS_WATSON_BATCH_SIZE",
)
concurrency_limit: int = Field(
default=10,
description="Concurrency limit",
validation_alias="WATSON_CONCURRENCY_LIMIT",
validation_alias="EMBEDDINGS_WATSON_CONCURRENCY_LIMIT",
)
max_retries: int | None = Field(
default=None,
description="Maximum retries",
validation_alias="WATSON_MAX_RETRIES",
validation_alias="EMBEDDINGS_WATSON_MAX_RETRIES",
)
delay_time: float | None = Field(
default=None,
description="Delay time between retries",
validation_alias="WATSON_DELAY_TIME",
validation_alias="EMBEDDINGS_WATSON_DELAY_TIME",
)
retry_status_codes: list[int] | None = Field(
default=None, description="HTTP status codes to retry on"
)
url: str = Field(description="Watson API URL", validation_alias="WATSON_URL")
url: str = Field(
description="Watson API URL", validation_alias="EMBEDDINGS_WATSON_URL"
)
api_key: str = Field(
description="Watson API key", validation_alias="WATSON_API_KEY"
description="Watson API key", validation_alias="EMBEDDINGS_WATSON_API_KEY"
)
name: str | None = Field(
default=None, description="Service name", validation_alias="WATSON_NAME"
default=None,
description="Service name",
validation_alias="EMBEDDINGS_WATSON_NAME",
)
iam_serviceid_crn: str | None = Field(
default=None,
description="IAM service ID CRN",
validation_alias="WATSON_IAM_SERVICEID_CRN",
validation_alias="EMBEDDINGS_WATSON_IAM_SERVICEID_CRN",
)
trusted_profile_id: str | None = Field(
default=None,
description="Trusted profile ID",
validation_alias="WATSON_TRUSTED_PROFILE_ID",
validation_alias="EMBEDDINGS_WATSON_TRUSTED_PROFILE_ID",
)
token: str | None = Field(
default=None, description="Bearer token", validation_alias="WATSON_TOKEN"
default=None,
description="Bearer token",
validation_alias="EMBEDDINGS_WATSON_TOKEN",
)
projects_token: str | None = Field(
default=None,
description="Projects token",
validation_alias="WATSON_PROJECTS_TOKEN",
validation_alias="EMBEDDINGS_WATSON_PROJECTS_TOKEN",
)
username: str | None = Field(
default=None, description="Username", validation_alias="WATSON_USERNAME"
default=None,
description="Username",
validation_alias="EMBEDDINGS_WATSON_USERNAME",
)
password: str | None = Field(
default=None, description="Password", validation_alias="WATSON_PASSWORD"
default=None,
description="Password",
validation_alias="EMBEDDINGS_WATSON_PASSWORD",
)
instance_id: str | None = Field(
default=None,
description="Service instance ID",
validation_alias="WATSON_INSTANCE_ID",
validation_alias="EMBEDDINGS_WATSON_INSTANCE_ID",
)
version: str | None = Field(
default=None, description="API version", validation_alias="WATSON_VERSION"
default=None,
description="API version",
validation_alias="EMBEDDINGS_WATSON_VERSION",
)
bedrock_url: str | None = Field(
default=None, description="Bedrock URL", validation_alias="WATSON_BEDROCK_URL"
default=None,
description="Bedrock URL",
validation_alias="EMBEDDINGS_WATSON_BEDROCK_URL",
)
platform_url: str | None = Field(
default=None, description="Platform URL", validation_alias="WATSON_PLATFORM_URL"
default=None,
description="Platform URL",
validation_alias="EMBEDDINGS_WATSON_PLATFORM_URL",
)
proxies: dict | None = Field(default=None, description="Proxy configuration")

6
src/crewai/rag/embeddings/providers/instructor/instructor_provider.py
View File

@@ -18,15 +18,15 @@ class InstructorProvider(BaseEmbeddingsProvider[InstructorEmbeddingFunction]):
model_name: str = Field(
default="hkunlp/instructor-base",
description="Model name to use",
validation_alias="INSTRUCTOR_MODEL_NAME",
validation_alias="EMBEDDINGS_INSTRUCTOR_MODEL_NAME",
)
device: str = Field(
default="cpu",
description="Device to run model on (cpu or cuda)",
validation_alias="INSTRUCTOR_DEVICE",
validation_alias="EMBEDDINGS_INSTRUCTOR_DEVICE",
)
instruction: str | None = Field(
default=None,
description="Instruction for embeddings",
validation_alias="INSTRUCTOR_INSTRUCTION",
validation_alias="EMBEDDINGS_INSTRUCTOR_INSTRUCTION",
)

6
src/crewai/rag/embeddings/providers/jina/jina_provider.py
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@@ -14,9 +14,11 @@ class JinaProvider(BaseEmbeddingsProvider[JinaEmbeddingFunction]):
embedding_callable: type[JinaEmbeddingFunction] = Field(
default=JinaEmbeddingFunction, description="Jina embedding function class"
)
api_key: str = Field(description="Jina API key", validation_alias="JINA_API_KEY")
api_key: str = Field(
description="Jina API key", validation_alias="EMBEDDINGS_JINA_API_KEY"
)
model_name: str = Field(
default="jina-embeddings-v2-base-en",
description="Model name to use for embeddings",
validation_alias="JINA_MODEL_NAME",
validation_alias="EMBEDDINGS_JINA_MODEL_NAME",
)

18
src/crewai/rag/embeddings/providers/microsoft/azure.py
View File

@@ -17,26 +17,28 @@ class AzureProvider(BaseEmbeddingsProvider[OpenAIEmbeddingFunction]):
default=OpenAIEmbeddingFunction,
description="Azure OpenAI embedding function class",
)
api_key: str = Field(description="Azure API key", validation_alias="OPENAI_API_KEY")
api_key: str = Field(
description="Azure API key", validation_alias="EMBEDDINGS_OPENAI_API_KEY"
)
api_base: str | None = Field(
default=None,
description="Azure endpoint URL",
validation_alias="OPENAI_API_BASE",
validation_alias="EMBEDDINGS_OPENAI_API_BASE",
)
api_type: str = Field(
default="azure",
description="API type for Azure",
validation_alias="OPENAI_API_TYPE",
validation_alias="EMBEDDINGS_OPENAI_API_TYPE",
)
api_version: str | None = Field(
default=None,
description="Azure API version",
validation_alias="OPENAI_API_VERSION",
validation_alias="EMBEDDINGS_OPENAI_API_VERSION",
)
model_name: str = Field(
default="text-embedding-ada-002",
description="Model name to use for embeddings",
validation_alias="OPENAI_MODEL_NAME",
validation_alias="EMBEDDINGS_OPENAI_MODEL_NAME",
)
default_headers: dict[str, Any] | None = Field(
default=None, description="Default headers for API requests"
@@ -44,15 +46,15 @@ class AzureProvider(BaseEmbeddingsProvider[OpenAIEmbeddingFunction]):
dimensions: int | None = Field(
default=None,
description="Embedding dimensions",
validation_alias="OPENAI_DIMENSIONS",
validation_alias="EMBEDDINGS_OPENAI_DIMENSIONS",
)
deployment_id: str | None = Field(
default=None,
description="Azure deployment ID",
validation_alias="OPENAI_DEPLOYMENT_ID",
validation_alias="EMBEDDINGS_OPENAI_DEPLOYMENT_ID",
)
organization_id: str | None = Field(
default=None,
description="Organization ID",
validation_alias="OPENAI_ORGANIZATION_ID",
validation_alias="EMBEDDINGS_OPENAI_ORGANIZATION_ID",
)

4
src/crewai/rag/embeddings/providers/ollama/ollama_provider.py
View File

@@ -17,9 +17,9 @@ class OllamaProvider(BaseEmbeddingsProvider[OllamaEmbeddingFunction]):
url: str = Field(
default="http://localhost:11434/api/embeddings",
description="Ollama API endpoint URL",
validation_alias="OLLAMA_URL",
validation_alias="EMBEDDINGS_OLLAMA_URL",
)
model_name: str = Field(
description="Model name to use for embeddings",
validation_alias="OLLAMA_MODEL_NAME",
validation_alias="EMBEDDINGS_OLLAMA_MODEL_NAME",
)

2
src/crewai/rag/embeddings/providers/onnx/onnx_provider.py
View File

@@ -15,5 +15,5 @@ class ONNXProvider(BaseEmbeddingsProvider[ONNXMiniLM_L6_V2]):
preferred_providers: list[str] | None = Field(
default=None,
description="Preferred ONNX execution providers",
validation_alias="ONNX_PREFERRED_PROVIDERS",
validation_alias="EMBEDDINGS_ONNX_PREFERRED_PROVIDERS",
)

20
src/crewai/rag/embeddings/providers/openai/openai_provider.py
View File

@@ -18,25 +18,29 @@ class OpenAIProvider(BaseEmbeddingsProvider[OpenAIEmbeddingFunction]):
description="OpenAI embedding function class",
)
api_key: str | None = Field(
default=None, description="OpenAI API key", validation_alias="OPENAI_API_KEY"
default=None,
description="OpenAI API key",
validation_alias="EMBEDDINGS_OPENAI_API_KEY",
)
model_name: str = Field(
default="text-embedding-ada-002",
description="Model name to use for embeddings",
validation_alias="OPENAI_MODEL_NAME",
validation_alias="EMBEDDINGS_OPENAI_MODEL_NAME",
)
api_base: str | None = Field(
default=None,
description="Base URL for API requests",
validation_alias="OPENAI_API_BASE",
validation_alias="EMBEDDINGS_OPENAI_API_BASE",
)
api_type: str | None = Field(
default=None,
description="API type (e.g., 'azure')",
validation_alias="OPENAI_API_TYPE",
validation_alias="EMBEDDINGS_OPENAI_API_TYPE",
)
api_version: str | None = Field(
default=None, description="API version", validation_alias="OPENAI_API_VERSION"
default=None,
description="API version",
validation_alias="EMBEDDINGS_OPENAI_API_VERSION",
)
default_headers: dict[str, Any] | None = Field(
default=None, description="Default headers for API requests"
@@ -44,15 +48,15 @@ class OpenAIProvider(BaseEmbeddingsProvider[OpenAIEmbeddingFunction]):
dimensions: int | None = Field(
default=None,
description="Embedding dimensions",
validation_alias="OPENAI_DIMENSIONS",
validation_alias="EMBEDDINGS_OPENAI_DIMENSIONS",
)
deployment_id: str | None = Field(
default=None,
description="Azure deployment ID",
validation_alias="OPENAI_DEPLOYMENT_ID",
validation_alias="EMBEDDINGS_OPENAI_DEPLOYMENT_ID",
)
organization_id: str | None = Field(
default=None,
description="OpenAI organization ID",
validation_alias="OPENAI_ORGANIZATION_ID",
validation_alias="EMBEDDINGS_OPENAI_ORGANIZATION_ID",
)

6
src/crewai/rag/embeddings/providers/openclip/openclip_provider.py
View File

@@ -18,15 +18,15 @@ class OpenCLIPProvider(BaseEmbeddingsProvider[OpenCLIPEmbeddingFunction]):
model_name: str = Field(
default="ViT-B-32",
description="Model name to use",
validation_alias="OPENCLIP_MODEL_NAME",
validation_alias="EMBEDDINGS_OPENCLIP_MODEL_NAME",
)
checkpoint: str = Field(
default="laion2b_s34b_b79k",
description="Model checkpoint",
validation_alias="OPENCLIP_CHECKPOINT",
validation_alias="EMBEDDINGS_OPENCLIP_CHECKPOINT",
)
device: str | None = Field(
default="cpu",
description="Device to run model on",
validation_alias="OPENCLIP_DEVICE",
validation_alias="EMBEDDINGS_OPENCLIP_DEVICE",
)

6
src/crewai/rag/embeddings/providers/roboflow/roboflow_provider.py
View File

@@ -16,10 +16,12 @@ class RoboflowProvider(BaseEmbeddingsProvider[RoboflowEmbeddingFunction]):
description="Roboflow embedding function class",
)
api_key: str = Field(
default="", description="Roboflow API key", validation_alias="ROBOFLOW_API_KEY"
default="",
description="Roboflow API key",
validation_alias="EMBEDDINGS_ROBOFLOW_API_KEY",
)
api_url: str = Field(
default="https://infer.roboflow.com",
description="Roboflow API URL",
validation_alias="ROBOFLOW_API_URL",
validation_alias="EMBEDDINGS_ROBOFLOW_API_URL",
)

6
src/crewai/rag/embeddings/providers/sentence_transformer/sentence_transformer_provider.py
View File

@@ -20,15 +20,15 @@ class SentenceTransformerProvider(
model_name: str = Field(
default="all-MiniLM-L6-v2",
description="Model name to use",
validation_alias="SENTENCE_TRANSFORMER_MODEL_NAME",
validation_alias="EMBEDDINGS_SENTENCE_TRANSFORMER_MODEL_NAME",
)
device: str = Field(
default="cpu",
description="Device to run model on (cpu or cuda)",
validation_alias="SENTENCE_TRANSFORMER_DEVICE",
validation_alias="EMBEDDINGS_SENTENCE_TRANSFORMER_DEVICE",
)
normalize_embeddings: bool = Field(
default=False,
description="Whether to normalize embeddings",
validation_alias="SENTENCE_TRANSFORMER_NORMALIZE_EMBEDDINGS",
validation_alias="EMBEDDINGS_SENTENCE_TRANSFORMER_NORMALIZE_EMBEDDINGS",
)

2
src/crewai/rag/embeddings/providers/text2vec/text2vec_provider.py
View File

@@ -18,5 +18,5 @@ class Text2VecProvider(BaseEmbeddingsProvider[Text2VecEmbeddingFunction]):
model_name: str = Field(
default="shibing624/text2vec-base-chinese",
description="Model name to use",
validation_alias="TEXT2VEC_MODEL_NAME",
validation_alias="EMBEDDINGS_TEXT2VEC_MODEL_NAME",
)

16
src/crewai/rag/embeddings/providers/voyageai/voyageai_provider.py
View File

@@ -18,38 +18,38 @@ class VoyageAIProvider(BaseEmbeddingsProvider[VoyageAIEmbeddingFunction]):
model: str = Field(
default="voyage-2",
description="Model to use for embeddings",
validation_alias="VOYAGEAI_MODEL",
validation_alias="EMBEDDINGS_VOYAGEAI_MODEL",
)
api_key: str = Field(
description="Voyage AI API key", validation_alias="VOYAGEAI_API_KEY"
description="Voyage AI API key", validation_alias="EMBEDDINGS_VOYAGEAI_API_KEY"
)
input_type: str | None = Field(
default=None,
description="Input type for embeddings",
validation_alias="VOYAGEAI_INPUT_TYPE",
validation_alias="EMBEDDINGS_VOYAGEAI_INPUT_TYPE",
)
truncation: bool = Field(
default=True,
description="Whether to truncate inputs",
validation_alias="VOYAGEAI_TRUNCATION",
validation_alias="EMBEDDINGS_VOYAGEAI_TRUNCATION",
)
output_dtype: str | None = Field(
default=None,
description="Output data type",
validation_alias="VOYAGEAI_OUTPUT_DTYPE",
validation_alias="EMBEDDINGS_VOYAGEAI_OUTPUT_DTYPE",
)
output_dimension: int | None = Field(
default=None,
description="Output dimension",
validation_alias="VOYAGEAI_OUTPUT_DIMENSION",
validation_alias="EMBEDDINGS_VOYAGEAI_OUTPUT_DIMENSION",
)
max_retries: int = Field(
default=0,
description="Maximum retries for API calls",
validation_alias="VOYAGEAI_MAX_RETRIES",
validation_alias="EMBEDDINGS_VOYAGEAI_MAX_RETRIES",
)
timeout: float | None = Field(
default=None,
description="Timeout for API calls",
validation_alias="VOYAGEAI_TIMEOUT",
validation_alias="EMBEDDINGS_VOYAGEAI_TIMEOUT",
)