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[Docs] Add Azure AI - OCR to docs (#15768)
* add Azure OCR to docs * docs fix * docs fix * docs fix * docs OCR
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4 changed files with 167 additions and 3 deletions
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@ -5,6 +5,7 @@
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| Cost Tracking | ✅ |
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| Logging | ✅ (Basic Logging not supported) |
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| Load Balancing | ✅ |
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| Supported Providers | `mistral`, `azure_ai` |
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:::tip
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@ -260,4 +261,5 @@ The response follows Mistral's OCR format with the following structure:
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| Provider | Link to Usage |
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|-------------|--------------------|
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| Mistral AI | [Usage](#quick-start) |
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| Azure AI | [Usage](../docs/providers/azure_ocr) |
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@ -1,10 +1,17 @@
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# Azure Text to Speech (tts)
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Convert text to natural-sounding speech using Azure OpenAI's Text to Speech models. Supports multiple voices and audio formats.
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## Overview
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| Property | Details |
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|-------|-------|
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| Description | Convert text to natural-sounding speech using Azure OpenAI's Text to Speech models |
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| Provider Route on LiteLLM | `azure/` |
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| Supported Operations | `/audio/speech` |
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| Link to Provider Doc | [Azure OpenAI TTS ↗](https://learn.microsoft.com/en-us/azure/ai-services/openai/text-to-speech-quickstart)
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## Quick Start
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**LiteLLM SDK**
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### **LiteLLM SDK**
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```python showLineNumbers title="SDK Usage"
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from litellm import speech
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@ -26,7 +33,7 @@ response = speech(
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response.stream_to_file(speech_file_path)
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```
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**LiteLLM PROXY**
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### **LiteLLM PROXY**
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```yaml showLineNumbers title="proxy_config.yaml"
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model_list:
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154
docs/my-website/docs/providers/azure_ocr.md
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154
docs/my-website/docs/providers/azure_ocr.md
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# Azure AI OCR
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## Overview
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| Property | Details |
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|-------|-------|
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| Description | Azure AI OCR provides document intelligence capabilities powered by Mistral, enabling text extraction from PDFs and images |
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| Provider Route on LiteLLM | `azure_ai/` |
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| Supported Operations | `/ocr` |
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| Link to Provider Doc | [Azure AI ↗](https://ai.azure.com/)
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Extract text from documents and images using Azure AI's OCR models, powered by Mistral.
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## Quick Start
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### **LiteLLM SDK**
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```python showLineNumbers title="SDK Usage"
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import litellm
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import os
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# Set environment variables
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os.environ["AZURE_AI_API_KEY"] = ""
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os.environ["AZURE_AI_API_BASE"] = ""
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# OCR with PDF URL
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response = litellm.ocr(
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model="azure_ai/mistral-document-ai-2505",
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document={
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"type": "document_url",
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"document_url": "https://example.com/document.pdf"
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}
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)
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# Access extracted text
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for page in response.pages:
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print(page.text)
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```
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### **LiteLLM PROXY**
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```yaml showLineNumbers title="proxy_config.yaml"
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model_list:
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- model_name: azure-ocr
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litellm_params:
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model: azure_ai/mistral-document-ai-2505
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api_key: "os.environ/AZURE_AI_API_KEY"
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api_base: "os.environ/AZURE_AI_API_BASE"
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model_info:
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mode: ocr
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```
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## Document Types
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Azure AI OCR supports both PDFs and images.
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### PDF Documents
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```python showLineNumbers title="PDF OCR"
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response = litellm.ocr(
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model="azure_ai/mistral-document-ai-2505",
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document={
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"type": "document_url",
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"document_url": "https://example.com/document.pdf"
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}
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)
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```
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### Image Documents
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```python showLineNumbers title="Image OCR"
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response = litellm.ocr(
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model="azure_ai/mistral-document-ai-2505",
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document={
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"type": "image_url",
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"image_url": "https://example.com/image.png"
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}
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)
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```
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### Base64 Encoded Documents
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```python showLineNumbers title="Base64 PDF"
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import base64
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# Read and encode PDF
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with open("document.pdf", "rb") as f:
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pdf_base64 = base64.b64encode(f.read()).decode()
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response = litellm.ocr(
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model="azure_ai/mistral-document-ai-2505",
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document={
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"type": "document_url",
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"document_url": f"data:application/pdf;base64,{pdf_base64}"
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}
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)
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```
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## Supported Parameters
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```python showLineNumbers title="All Parameters"
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response = litellm.ocr(
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model="azure_ai/mistral-document-ai-2505",
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document={ # Required: Document to process
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"type": "document_url",
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"document_url": "https://..."
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},
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include_image_base64=True, # Optional: Include base64 images
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pages=[0, 1, 2], # Optional: Specific pages to process
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image_limit=10 # Optional: Limit number of images
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)
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```
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## Response Format
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```python showLineNumbers title="Response Structure"
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# Response has the following structure
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response.pages # List of pages with extracted text
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response.model # Model used
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response.object # "ocr"
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response.usage_info # Token usage information
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# Access page content
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for page in response.pages:
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print(f"Page {page.page_number}:")
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print(page.text)
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```
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## Async Support
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```python showLineNumbers title="Async Usage"
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import litellm
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response = await litellm.aocr(
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model="azure_ai/mistral-document-ai-2505",
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document={
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"type": "document_url",
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"document_url": "https://example.com/document.pdf"
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}
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)
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```
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## Important Notes
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:::info URL Conversion
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Azure AI OCR endpoints don't have internet access. LiteLLM automatically converts public URLs to base64 data URIs before sending requests to Azure AI.
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:::
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## Supported Models
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- `mistral-document-ai-2505` - Latest Mistral OCR model on Azure AI
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Use the Azure AI provider prefix: `azure_ai/<model-name>`
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@ -427,6 +427,7 @@ const sidebars = {
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label: "Azure AI",
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items: [
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"providers/azure_ai",
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"providers/azure_ocr",
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"providers/azure_ai_speech",
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"providers/azure_ai_img",
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]
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