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Eduard van Valkenburg 3e97425245 Python: [BREAKING]: Introducing Options as TypedDict and Generic (#3140 )

* WIP typeddict for options

* updated all clients and ChatAgents

* updated everything

* added ADR

* fix mypy

* proper typevar imports

* fixed import

* fixed other imports

* slight update in the sample

* updated from feedback

* fixes

* fixed missing covariants and test fixes

* fixed typing

* updated anthropic thinking config

* ruff fixes

* fixed int tests

* fix tests and mypy

* updated integration tests

* updated docstring and test fix

* improved options handling in obser

* mypy fix

* updated a host of integration tests

* fix tests

* bedrock fix

3e97425245 · 2026-01-13 16:41:05 +00:00

History

custom_agent.py

Python: [BREAKING]: removed display_name, renamed context_providers, middleware and AggregateContextProvider (#3139 )

2026-01-13 02:24:07 +00:00

custom_chat_client.py

Python: [BREAKING]: Introducing Options as TypedDict and Generic (#3140 )

2026-01-13 16:41:05 +00:00

README.md

Python: Add custom agent and chat client implementation examples (#849 )

2025-09-22 04:42:33 +00:00

README.md

Custom Agent and Chat Client Examples

This folder contains examples demonstrating how to implement custom agents and chat clients using the Microsoft Agent Framework.

Examples

File	Description
`custom_agent.py`	Shows how to create custom agents by extending the `BaseAgent` class. Demonstrates the `EchoAgent` implementation with both streaming and non-streaming responses, proper thread management, and message history handling.
`custom_chat_client.py`	Demonstrates how to create custom chat clients by extending the `BaseChatClient` class. Shows the `EchoingChatClient` implementation and how to integrate it with `ChatAgent` using the `create_agent()` method.

Key Takeaways

Custom Agents

Custom agents give you complete control over the agent's behavior
You must implement both run() (for complete responses) and run_stream() (for streaming responses)
Use self._normalize_messages() to handle different input message formats
Use self._notify_thread_of_new_messages() to properly manage conversation history

Custom Chat Clients

Custom chat clients allow you to integrate any backend service or create new LLM providers
You must implement both _inner_get_response() and _inner_get_streaming_response()
Custom chat clients can be used with ChatAgent to leverage all agent framework features
Use the create_agent() method to easily create agents from your custom chat clients

Both approaches allow you to extend the framework for your specific use cases while maintaining compatibility with the broader Agent Framework ecosystem.