The AzureOpenAIEmbedder class is used to embed text data into vectors using the Azure OpenAI API. Get your key from here.

Usage

from phi.agent import Agent, AgentKnowledge
from phi.vectordb.pgvector import PgVector
from phi.embedder.azure_openai import AzureOpenAIEmbedder

# Create knowledge base
knowledge_base=AgentKnowledge(
    vector_db=PgVector(
        db_url=db_url,
        table_name=embeddings_table,
        embedder=AzureOpenAIEmbedder(api_key=***),
    ),
    # 2 references are added to the prompt
    num_documents=2,
),

# Add information to the knowledge base
knowledge_base.load_text("The sky is blue")

# Add the knowledge base to the Agent
agent = Agent(knowledge_base=knowledge_base)

Params

ParameterTypeDefaultDescription
modelstr"text-embedding-ada-002"The name of the model used for generating embeddings.
dimensionsint1536The dimensionality of the embeddings generated by the model.
encoding_formatLiteral['float', 'base64']"float"The format in which the embeddings are encoded. Options are “float” or “base64”.
userstr-The user associated with the API request.
api_keystr-The API key used for authenticating requests.
api_versionstr"2024-02-01"The version of the API to use for the requests.
azure_endpointstr-The Azure endpoint for the API requests.
azure_deploymentstr-The Azure deployment name for the API requests.
base_urlstr-The base URL for the API endpoint.
azure_ad_tokenstr-The Azure Active Directory token for authentication.
azure_ad_token_providerAny-The provider for obtaining the Azure AD token.
organizationstr-The organization associated with the API request.
request_paramsOptional[Dict[str, Any]]-Additional parameters to include in the API request. Optional.
client_paramsOptional[Dict[str, Any]]-Additional parameters for configuring the API client. Optional.
openai_clientOptional[AzureOpenAIClient]-An instance of the AzureOpenAIClient to use for making API requests. Optional.