Documentation IndexFetch the complete documentation index at: /llms.txtUse this file to discover all available pages before exploring further.
Fetch the complete documentation index at: /llms.txt
Use this file to discover all available pages before exploring further.
Generate embeddings using Azure OpenAI Service
from praisonaiagents import embedding result = embedding( input="Hello world", model="azure/text-embedding-ada-002" ) print(f"Dimensions: {len(result.embeddings[0])}")
praisonai embed "Hello world" --model azure/text-embedding-ada-002
export AZURE_API_KEY="your-azure-api-key" export AZURE_API_BASE="https://your-resource.openai.azure.com" export AZURE_API_VERSION="2024-02-01"
azure/text-embedding-ada-002
azure/text-embedding-3-small
azure/text-embedding-3-large
from praisonaiagents import embedding result = embedding( input="Hello world", model="azure/my-embedding-deployment", api_base="https://my-resource.openai.azure.com", api_key="your-key" )
from praisonaiagents import embedding texts = ["Document 1", "Document 2", "Document 3"] result = embedding( input=texts, model="azure/text-embedding-ada-002" ) print(f"Generated {len(result.embeddings)} embeddings")
from praisonaiagents import embedding from azure.identity import DefaultAzureCredential credential = DefaultAzureCredential() token = credential.get_token("https://cognitiveservices.azure.com/.default") result = embedding( input="Hello world", model="azure/text-embedding-ada-002", api_key=token.token )