* Refactor Anthropic model option and provider clients Rename the Anthropic client model option from model_id to model, add provider-specific Anthropic wrappers for Foundry, Bedrock, and Vertex, and expose them through the Anthropic, Foundry, Amazon, and Google namespaces. Update core option handling, docs, samples, and tests accordingly. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Fix Anthropic skills sample typing Cast the Anthropic beta client to Any in the skills sample so the pre-commit sample pyright check no longer fails on beta skills and files endpoints that are not exposed by the current SDK stubs. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * undo sample mypy * Retry CI after transient external failures Retrigger PR validation after an unrelated Copilot review workflow SAML failure and a transient external tau2 git fetch failure in the Windows Python test setup. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Address review feedback on model option merging Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Address Anthropic compatibility review feedback Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * moved all to `model` * fixes for azure ai search * Python: standardize remaining sample env var names Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Python: fix foundry-local pyright compatibility Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * updated env vars in cicd --------- Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
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 OpenAI Chat Client
- File:
azure_chat_multimodal.py - Description: Shows how to send images to Azure OpenAI Chat Completions API
- Supported formats: PNG/JPEG images (PDF files are NOT supported by Chat Completions API)
Azure OpenAI Responses Client
- File:
azure_responses_multimodal.py - Description: Shows how to send images and PDF files to Azure OpenAI Responses API
- Supported formats: PNG/JPEG images, PDF documents (full multimodal support)
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 endpointAZURE_OPENAI_MODEL: The name of your Azure OpenAI chat model deploymentAZURE_OPENAI_MODEL: The name of your Azure OpenAI responses model deployment
Optionally for Azure OpenAI:
AZURE_OPENAI_API_VERSION: The API version to use (default is2024-10-21)AZURE_OPENAI_API_KEY: Your Azure OpenAI API key (if not usingAzureCliCredential)
Note: You can also provide configuration directly in code instead of using environment variables:
# Example: Pass the Foundry project endpoint directly
client = FoundryChatClient(
credential=AzureCliCredential(),
project_endpoint="https://your-project.services.ai.azure.com",
model="your-deployment-name",
)
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 Chat example (requires az login or API key)
python azure_chat_multimodal.py
# Run Azure Responses example (requires az login or API key)
python azure_responses_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
Content.from_uri(
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
Content.from_data(
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 | Text extraction and analysis |
API Differences
- OpenAI Chat Completions API: Supports images, audio, and PDF files
- Azure OpenAI Chat Completions API: Supports images only (no PDF/audio file types)
- Azure OpenAI Responses API: Supports images and PDF files (full multimodal support)
Choose the appropriate client based on your multimodal needs and available APIs.