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Merge branch 'main' into copilot/move-workflow-and-agent-samples
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@@ -68,7 +68,7 @@ Illustrates a basic agent using Azure OpenAI with structured responses.
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**Key concepts**: Azure OpenAI integration, credential management, structured outputs
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### 5. **OpenAI Responses Agent** ([`openai_responses_agent.py`](./openai_responses_agent.py))
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### 5. **OpenAI Responses Agent** ([`openai_agent.py`](./openai_agent.py))
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Demonstrates the simplest possible agent using OpenAI directly.
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@@ -159,7 +159,7 @@ agent_factory = AgentFactory(
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"MyProvider": {
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"package": "my_custom_module",
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"name": "MyCustomChatClient",
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"model_id_field": "model_id",
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"model_field": "model",
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}
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}
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)
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@@ -176,7 +176,7 @@ agent = agent_factory.create_agent_from_yaml_path(Path("custom_provider.yaml"))
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This allows you to extend the declarative framework with custom chat client implementations. The mapping requires:
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- **package**: The Python package/module to import from
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- **name**: The class name of your SupportsChatGetResponse implementation
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- **model_id_field**: The constructor parameter name that accepts the value of the `model.id` field from the YAML
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- **model_field**: The constructor parameter name that accepts the value of the `model.id` field from the YAML
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You can reference your custom provider using either `Provider.ApiType` format or just `Provider` in your YAML configuration, as long as it matches the registered mapping.
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