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sdk/ai/azure-ai-agentserver-core/CHANGELOG.md

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# Release History
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## 1.0.0
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## 1.0.0a1
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### Features Added
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sdk/ai/azure-ai-agentserver-core/README.md

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# Azure AI Agent Server Adapter
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## Install
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In current folder, run:
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## Getting started
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```bash
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pip install -e .
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pip install azure-ai-agentserver-core
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```
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## Usage
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## Key concepts
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This is the core package for Azure AI Agent server. It hosts your agent as a container on the cloud.
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You can talk to your agent using azure-ai-project sdk
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## Examples
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If your agent is not built using a supported framework such as LangGraph and Agent-framework, you can still make it compatible with Microsoft AI Foundry by manually implementing the predefined interface.
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my_agent.run()
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```
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## Troubleshooting
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First run your agent with azure-ai-agentserver-core locally.
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If it works on local by failed on cloud. Check your logs in the application insight connected to your Azure AI Foundry Project.
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### Reporting issues
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To report an issue with the client library, or request additional features, please open a GitHub issue [here](https://github.com/Azure/azure-sdk-for-python/issues). Mention the package name "azure-ai-agents" in the title or content.
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## Next steps
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Please visit [Samples](https://github.com/Azure/azure-sdk-for-python/tree/main/sdk/ai/azure-ai-agentserver-core/samples) folder. There are several cases for you to build your agent with azure-ai-agentserver
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## Contributing
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This project welcomes contributions and suggestions. Most contributions require
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you to agree to a Contributor License Agreement (CLA) declaring that you have
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the right to, and actually do, grant us the rights to use your contribution.
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For details, visit https://cla.microsoft.com.
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When you submit a pull request, a CLA-bot will automatically determine whether
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you need to provide a CLA and decorate the PR appropriately (e.g., label,
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comment). Simply follow the instructions provided by the bot. You will only
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need to do this once across all repos using our CLA.
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This project has adopted the
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[Microsoft Open Source Code of Conduct][code_of_conduct]. For more information,
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see the Code of Conduct FAQ or contact [email protected] with any
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additional questions or comments.
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# ---------------------------------------------------------
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# Copyright (c) Microsoft Corporation. All rights reserved.
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# ---------------------------------------------------------
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# pylint: disable=no-name-in-module
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from typing import Optional
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from .openai import response_create_params #pylint: disable=no-name-in-module
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from .openai import response_create_params # type: ignore
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from . import projects as _azure_ai_projects_models
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class CreateResponse(response_create_params.ResponseCreateParamsBase, total=False):
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class CreateResponse(response_create_params.ResponseCreateParamsBase, total=False): # type: ignore
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agent: Optional[_azure_ai_projects_models.AgentReference]
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stream: Optional[bool]

sdk/ai/azure-ai-agentserver-core/azure/ai/agentserver/core/models/projects/_models.py

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)
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if TYPE_CHECKING:
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from .. import _types, models as _models
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from .. import _types, models as _models # type: ignore
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class Tool(_Model):

sdk/ai/azure-ai-agentserver-core/azure/ai/agentserver/core/models/projects/py.typed

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sdk/ai/azure-ai-agentserver-core/azure/ai/agentserver/core/server/common/agent_run_context.py

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def get_agent_id_object(self) -> AgentId:
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agent = self.request.get("agent")
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if not agent:
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return None
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return None # type: ignore
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return AgentId(
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{
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"type": agent.type,
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def get_conversation_object(self) -> ResponseConversation1:
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if not self._conversation_id:
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return None
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return None # type: ignore
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return ResponseConversation1(id=self._conversation_id)
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def _deserialize_agent_reference(payload: dict) -> AgentReference:
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if not payload:
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return None
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return None # type: ignore
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return AgentReference(**payload)
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{
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"ignoreWords": [
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"Agentic",
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"UPIA",
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"ANSII",
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"inpainting",
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"CSDL",
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"azureai",
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"GLEU",
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"fstring",
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"alnum",
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"GENAI",
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"Prereqs",
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"mslearn",
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"PYTHONIOENCODING",
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"GETFL",
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"DETFL",
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"Planifica"
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],
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"ignorePaths": [
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"*.csv",
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"*.json",
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"*.rst",
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"./samples/**"
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]
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}

sdk/ai/azure-ai-agentserver-core/pyproject.toml

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[project]
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name = "azure-ai-agentserver-core"
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# Keep using your _version.py; setuptools reads it via [tool.setuptools.dynamic] below
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dynamic = ["version", "readme"]
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description = "Agents server adapter for Azure AI"
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requires-python = ">=3.10"
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authors = [{ name = "Microsoft Corporation" }]
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classifiers = ["Programming Language :: Python :: 3", "Programming Language :: Python :: 3.10"]
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authors = [
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{ name = "Microsoft Corporation", email = "[email protected]" },
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]
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license = "MIT"
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classifiers = [
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"Programming Language :: Python",
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"Programming Language :: Python :: 3 :: Only",
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"Programming Language :: Python :: 3",
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"Programming Language :: Python :: 3.10",
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"Programming Language :: Python :: 3.11",
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"Programming Language :: Python :: 3.12",
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"Programming Language :: Python :: 3.13",
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]
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keywords = ["azure", "azure sdk"]
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dependencies = [
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"azure-monitor-opentelemetry>=1.5.0",

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