agent-framework/python/samples/getting_started/multimodal_input

Multimodal Input Examples

This folder contains examples demonstrating how to send multimodal content (images, audio, PDF files) to AI agents using the Agent Framework.

Examples

OpenAI Chat Client

• File: openai_chat_multimodal.py
• Description: Shows how to send images, audio, and PDF files to OpenAI's Chat Completions API
• Supported formats: PNG/JPEG images, WAV/MP3 audio, PDF documents

Azure Chat Client

• File: azure_chat_multimodal.py
• Description: Shows how to send multimodal content to Azure OpenAI service
• Supported formats: PNG/JPEG images, WAV/MP3 audio, PDF documents

Environment Variables

Set the following environment variables before running the examples:

For OpenAI:

• OPENAI_API_KEY: Your OpenAI API key

For Azure OpenAI:

• AZURE_OPENAI_ENDPOINT: Your Azure OpenAI endpoint
• AZURE_OPENAI_CHAT_DEPLOYMENT_NAME: The name of your Azure OpenAI chat model deployment

Optionally for Azure OpenAI:

• AZURE_OPENAI_API_VERSION: The API version to use (default is 2024-10-21)
• AZURE_OPENAI_API_KEY: Your Azure OpenAI API key (if not using AzureCliCredential)

Note: You can also provide configuration directly in code instead of using environment variables:

# Example: Pass deployment_name directly
client = AzureOpenAIChatClient(
    credential=AzureCliCredential(),
    deployment_name="your-deployment-name",
    endpoint="https://your-resource.openai.azure.com"
)

Authentication

The Azure example uses AzureCliCredential for authentication. Run az login in your terminal before running the example, or replace AzureCliCredential with your preferred authentication method (e.g., provide api_key parameter).

Running the Examples

# Run OpenAI example
python openai_chat_multimodal.py

# Run Azure example (requires az login or API key)
python azure_chat_multimodal.py

Using Your Own Files

The examples include small embedded test files for demonstration. To use your own files:

Method 1: Data URIs (recommended)

import base64

# Load and encode your file
with open("path/to/your/image.jpg", "rb") as f:
    image_data = f.read()
    image_base64 = base64.b64encode(image_data).decode('utf-8')
    image_uri = f"data:image/jpeg;base64,{image_base64}"

# Use in DataContent
DataContent(
    uri=image_uri,
    media_type="image/jpeg"
)

Method 2: Raw bytes

# Load raw bytes
with open("path/to/your/image.jpg", "rb") as f:
    image_bytes = f.read()

# Use in DataContent
DataContent(
    data=image_bytes,
    media_type="image/jpeg"
)

Supported File Types

Type	Formats	Notes
Images	PNG, JPEG, GIF, WebP	Most common image formats
Audio	WAV, MP3	For transcription and analysis
Documents	PDF	Text extraction and analysis

API Differences

• Chat Completions API: Supports images, audio, and PDF files
• Assistants API: Only supports text and images (no audio/PDF)
• Responses API: Similar to Chat Completions

Choose the appropriate client based on your multimodal needs.