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Documentation Index

Fetch the complete documentation index at: https://docs.rotavision.com/llms.txt

Use this file to discover all available pages before exploring further.

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Overview

Rotavision integrates with Azure for data access, ML monitoring, and Azure OpenAI routing.

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Blob Storage

from rotavision import Rotavision

client = Rotavision()

# Analyze data from Azure Blob
result = client.vishwas.analyze(
    model_id="my-model",
    dataset={
        "data_url": "https://myaccount.blob.core.windows.net/container/data.parquet",
        "azure_credentials": {
            "connection_string": "DefaultEndpointsProtocol=https;..."
        }
    }
)

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Azure ML Integration

Monitor models deployed on Azure ML: 
from rotavision.integrations.azure import AzureMLMonitor

monitor = AzureMLMonitor(
    workspace_name="my-workspace",
    endpoint_name="my-endpoint",
    rotavision_api_key="rv_live_..."
)

monitor.start()

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Azure OpenAI

Route Sankalp requests via Azure OpenAI: 
response = client.sankalp.proxy(
    model="gpt-4",
    messages=[{"role": "user", "content": "Hello"}],
    routing={
        "provider": "azure_openai"
    }
)
Configure Azure OpenAI in dashboard: 
client.integrations.configure(
    provider="azure_openai",
    config={
        "endpoint": "https://my-resource.openai.azure.com",
        "api_key": "...",
        "deployment_id": "gpt-4-deployment"
    }
)