Documentation Index
Fetch the complete documentation index at: https://docs.praison.ai/llms.txt
Use this file to discover all available pages before exploring further.
Overview
Azure OpenAI provides enterprise-grade embedding models with Azure’s security and compliance features.
Quick Start
from praisonaiagents import embedding
result = embedding(
input="Hello world",
model="azure/text-embedding-ada-002"
)
print(f"Dimensions: {len(result.embeddings[0])}")
CLI Usage
praisonai embed "Hello world" --model azure/text-embedding-ada-002
Setup
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"
Available Models
| Model | Dimensions | Max Tokens |
|---|
azure/text-embedding-ada-002 | 1536 | 8191 |
azure/text-embedding-3-small | 1536 | 8191 |
azure/text-embedding-3-large | 3072 | 8191 |
With Deployment Name
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"
)
Batch Embeddings
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")
Azure AD Authentication
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
)
