Python: Wrapper + Samples 1st (#5177)

* Experiment * Update dependency and add non streaming * Add more samples * Rename samples * Add invocations * Comments 1 * Comments 2 * Comments 3 * Improve README * Add local shell sample * WIP: Add eval and memory samples * Update user agent prefix * Update user agent prefix doc
2026-06-16 21:04:09 +08:00 · 2026-04-10 10:18:32 -07:00
parent 7010dd7439
commit 615ef9049f
62 changed files with 1694 additions and 6 deletions
@@ -0,0 +1,13 @@
+# Basic example of hosting an agent with the `invocations` API
+
+Run the following command to start the server:
+
+```bash
+python main.py
+```
+
+Send a POST request to the server with a JSON body containing a "message" field to interact with the agent. For example:
+
+```bash
+curl -X POST http://localhost:8088/invocations -H "Content-Type: application/json" -d '{"message": "Hi!"}'
+```
@@ -0,0 +1,36 @@
+# Copyright (c) Microsoft. All rights reserved.
+
+import os
+
+from agent_framework import Agent
+from agent_framework.foundry import FoundryChatClient
+from agent_framework_foundry_hosting import InvocationsHostServer
+from azure.identity import AzureCliCredential
+from dotenv import load_dotenv
+
+# Load environment variables from .env file
+load_dotenv()
+
+
+def main():
+    client = FoundryChatClient(
+        project_endpoint=os.environ["FOUNDRY_PROJECT_ENDPOINT"],
+        model=os.environ["FOUNDRY_MODEL"],
+        credential=AzureCliCredential(),
+    )
+
+    agent = Agent(
+        client=client,
+        instructions="You are a friendly assistant. Keep your answers brief.",
+        # History will be managed by the hosting infrastructure, thus there
+        # is no need to store history by the service. Learn more at:
+        # https://developers.openai.com/api/reference/resources/responses/methods/create
+        default_options={"store": False},
+    )
+
+    server = InvocationsHostServer(agent)
+    server.run()
+
+
+if __name__ == "__main__":
+    main()
@@ -0,0 +1,2 @@
+agent-framework
+agent-framework-foundry-hosting
@@ -0,0 +1,6 @@
+.venv
+__pycache__
+*.pyc
+*.pyo
+*.pyd
+.Python
@@ -0,0 +1,16 @@
+FROM python:3.12-slim
+
+WORKDIR /app
+
+COPY . user_agent/
+WORKDIR /app/user_agent
+
+RUN if [ -f requirements.txt ]; then \
+        pip install -r requirements.txt; \
+    else \
+        echo "No requirements.txt found"; \
+    fi
+
+EXPOSE 8088
+
+CMD ["python", "main.py"]
@@ -0,0 +1,35 @@
+# Basic example of hosting an agent with the `responses` API
+
+## Running the server locally
+
+Run the following command to start the server:
+
+```bash
+python main.py
+```
+
+## Interacting with the agent
+
+Send a POST request to the server with a JSON body containing a "message" field to interact with the agent. For example:
+
+```bash
+curl -X POST http://localhost:8088/responses -H "Content-Type: application/json" -d '{"input": "Hi"}'
+```
+
+The server will respond with a JSON object containing the response text and a response ID. You can use this response ID to continue the conversation in subsequent requests.
+
+## Multi-turn conversation
+
+To have a multi-turn conversation with the agent, include the previous response id in the request body. For example:
+
+```bash
+curl -X POST http://localhost:8088/responses -H "Content-Type: application/json" -d '{"input": "How are you?", "previous_response_id": "REPLACE_WITH_PREVIOUS_RESPONSE_ID"}'
+```
+
+## Deploying to Foundry
+
+TODO
+
+## Using the deployed agent in Agent Framework
+
+TODO
@@ -0,0 +1,15 @@
+name: agent-framework-agent-basic
+description: >
+  A basic Agent Framework agent hosted by Foundry.
+metadata:
+  tags:
+    - AI Agent Hosting
+    - Azure AI AgentServer
+    - Responses Protocol
+    - Streaming
+template:
+  name: agent-framework-agent-basic
+  kind: hosted
+  protocols:
+    - protocol: responses
+      version: v0.1.0
@@ -0,0 +1,8 @@
+kind: hosted
+name: agent-framework-agent-basic
+protocols:
+  - protocol: responses
+    version: v0.1.0
+resources:
+  cpu: "0.25"
+  memory: 0.5Gi
@@ -0,0 +1,37 @@
+# Copyright (c) Microsoft. All rights reserved.
+
+import os
+
+from agent_framework import Agent
+from agent_framework.foundry import FoundryChatClient
+from agent_framework_foundry_hosting import ResponsesHostServer
+from azure.ai.agentserver.responses import InMemoryResponseProvider
+from azure.identity import AzureCliCredential
+from dotenv import load_dotenv
+
+# Load environment variables from .env file
+load_dotenv()
+
+
+def main():
+    client = FoundryChatClient(
+        project_endpoint=os.environ["FOUNDRY_PROJECT_ENDPOINT"],
+        model=os.environ["FOUNDRY_MODEL"],
+        credential=AzureCliCredential(),
+    )
+
+    agent = Agent(
+        client=client,
+        instructions="You are a friendly assistant. Keep your answers brief.",
+        # History will be managed by the hosting infrastructure, thus there
+        # is no need to store history by the service. Learn more at:
+        # https://developers.openai.com/api/reference/resources/responses/methods/create
+        default_options={"store": False},
+    )
+
+    server = ResponsesHostServer(agent, provider=InMemoryResponseProvider())
+    server.run()
+
+
+if __name__ == "__main__":
+    main()
@@ -0,0 +1,2 @@
+agent-framework
+agent-framework-foundry-hosting
@@ -0,0 +1,6 @@
+.venv
+__pycache__
+*.pyc
+*.pyo
+*.pyd
+.Python
@@ -0,0 +1,16 @@
+FROM python:3.12-slim
+
+WORKDIR /app
+
+COPY . user_agent/
+WORKDIR /app/user_agent
+
+RUN if [ -f requirements.txt ]; then \
+        pip install -r requirements.txt; \
+    else \
+        echo "No requirements.txt found"; \
+    fi
+
+EXPOSE 8088
+
+CMD ["python", "main.py"]
@@ -0,0 +1,13 @@
+# Basic example of hosting an agent with the `responses` API and local tools
+
+Run the following command to start the server:
+
+```bash
+python main.py
+```
+
+Send a POST request to the server with a JSON body containing a "message" field to interact with the agent. For example:
+
+```bash
+curl -X POST http://localhost:8088/responses -H "Content-Type: application/json" -d '{"input": "What is the weather in Seattle?"}'
+```
@@ -0,0 +1,15 @@
+name: agent-framework-agent-with-local-tools
+description: >
+  An Agent Framework agent with local toolshosted by Foundry.
+metadata:
+  tags:
+    - AI Agent Hosting
+    - Azure AI AgentServer
+    - Responses Protocol
+    - Streaming
+template:
+  name: agent-framework-agent-with-local-tools
+  kind: hosted
+  protocols:
+    - protocol: responses
+      version: v0.1.0
@@ -0,0 +1,8 @@
+kind: hosted
+name: agent-framework-agent-with-local-tools
+protocols:
+  - protocol: responses
+    version: v0.1.0
+resources:
+  cpu: "0.25"
+  memory: 0.5Gi
@@ -0,0 +1,50 @@
+# Copyright (c) Microsoft. All rights reserved.
+
+import os
+from random import randint
+
+from agent_framework import Agent, tool
+from agent_framework.foundry import FoundryChatClient
+from agent_framework_foundry_hosting import ResponsesHostServer
+from azure.ai.agentserver.responses import InMemoryResponseProvider
+from azure.identity import AzureCliCredential
+from dotenv import load_dotenv
+from pydantic import Field
+from typing_extensions import Annotated
+
+# Load environment variables from .env file
+load_dotenv()
+
+
+@tool(approval_mode="never_require")
+def get_weather(
+    location: Annotated[str, Field(description="The location to get the weather for.")],
+) -> str:
+    """Get the weather for a given location."""
+    conditions = ["sunny", "cloudy", "rainy", "stormy"]
+    return f"The weather in {location} is {conditions[randint(0, 3)]} with a high of {randint(10, 30)}°C."
+
+
+def main():
+    client = FoundryChatClient(
+        project_endpoint=os.environ["FOUNDRY_PROJECT_ENDPOINT"],
+        model=os.environ["FOUNDRY_MODEL"],
+        credential=AzureCliCredential(),
+    )
+
+    agent = Agent(
+        client=client,
+        instructions="You are a friendly assistant. Keep your answers brief.",
+        tools=[get_weather],
+        # History will be managed by the hosting infrastructure, thus there
+        # is no need to store history by the service. Learn more at:
+        # https://developers.openai.com/api/reference/resources/responses/methods/create
+        default_options={"store": False},
+    )
+
+    server = ResponsesHostServer(agent, provider=InMemoryResponseProvider())
+    server.run()
+
+
+if __name__ == "__main__":
+    main()
@@ -0,0 +1,2 @@
+agent-framework
+agent-framework-foundry-hosting
@@ -0,0 +1,6 @@
+.venv
+__pycache__
+*.pyc
+*.pyo
+*.pyd
+.Python
@@ -0,0 +1,16 @@
+FROM python:3.12-slim
+
+WORKDIR /app
+
+COPY . user_agent/
+WORKDIR /app/user_agent
+
+RUN if [ -f requirements.txt ]; then \
+        pip install -r requirements.txt; \
+    else \
+        echo "No requirements.txt found"; \
+    fi
+
+EXPOSE 8088
+
+CMD ["python", "main.py"]
@@ -0,0 +1,13 @@
+# Basic example of hosting an agent with the `responses` API and a remote MCP
+
+Run the following command to start the server:
+
+```bash
+python main.py
+```
+
+Send a POST request to the server with a JSON body containing a "message" field to interact with the agent. For example:
+
+```bash
+curl -X POST http://localhost:8088/responses -H "Content-Type: application/json" -d '{"input": "List all the repositories I own on GitHub."}'
+```
@@ -0,0 +1,15 @@
+name: agent-framework-agent-with-remote-mcp-tools
+description: >
+  An Agent Framework agent with remote MCP tools hosted by Foundry.
+metadata:
+  tags:
+    - AI Agent Hosting
+    - Azure AI AgentServer
+    - Responses Protocol
+    - Streaming
+template:
+  name: agent-framework-agent-with-remote-mcp-tools
+  kind: hosted
+  protocols:
+    - protocol: responses
+      version: v0.1.0
@@ -0,0 +1,8 @@
+kind: hosted
+name: agent-framework-agent-with-remote-mcp-tools
+protocols:
+  - protocol: responses
+    version: v0.1.0
+resources:
+  cpu: "0.25"
+  memory: 0.5Gi
@@ -0,0 +1,53 @@
+# Copyright (c) Microsoft. All rights reserved.
+
+import os
+
+from agent_framework import Agent
+from agent_framework.foundry import FoundryChatClient
+from agent_framework_foundry_hosting import ResponsesHostServer
+from azure.ai.agentserver.responses import InMemoryResponseProvider
+from azure.identity import AzureCliCredential
+from dotenv import load_dotenv
+
+# Load environment variables from .env file
+load_dotenv()
+
+
+def main():
+    client = FoundryChatClient(
+        project_endpoint=os.environ["FOUNDRY_PROJECT_ENDPOINT"],
+        model=os.environ["FOUNDRY_MODEL"],
+        credential=AzureCliCredential(),
+    )
+
+    github_pat = os.getenv("GITHUB_PAT")
+    if not github_pat:
+        raise ValueError(
+            "GITHUB_PAT environment variable must be set. Create a token at https://github.com/settings/tokens"
+        )
+
+    github_mcp_tool = client.get_mcp_tool(
+        name="GitHub",
+        url="https://api.githubcopilot.com/mcp/",
+        headers={
+            "Authorization": f"Bearer {github_pat}",
+        },
+        approval_mode="never_require",
+    )
+
+    agent = Agent(
+        client=client,
+        instructions="You are a friendly assistant. Keep your answers brief.",
+        tools=[github_mcp_tool],
+        # History will be managed by the hosting infrastructure, thus there
+        # is no need to store history by the service. Learn more at:
+        # https://developers.openai.com/api/reference/resources/responses/methods/create
+        default_options={"store": False},
+    )
+
+    server = ResponsesHostServer(agent, provider=InMemoryResponseProvider())
+    server.run()
+
+
+if __name__ == "__main__":
+    main()
@@ -0,0 +1,2 @@
+agent-framework
+agent-framework-foundry-hosting
@@ -0,0 +1,6 @@
+.venv
+__pycache__
+*.pyc
+*.pyo
+*.pyd
+.Python
@@ -0,0 +1,16 @@
+FROM python:3.12-slim
+
+WORKDIR /app
+
+COPY . user_agent/
+WORKDIR /app/user_agent
+
+RUN if [ -f requirements.txt ]; then \
+        pip install -r requirements.txt; \
+    else \
+        echo "No requirements.txt found"; \
+    fi
+
+EXPOSE 8088
+
+CMD ["python", "main.py"]
@@ -0,0 +1,13 @@
+# Basic example of hosting an agent with the `responses` API and a workflow
+
+Run the following command to start the server:
+
+```bash
+python main.py
+```
+
+Send a POST request to the server with a JSON body containing a "message" field to interact with the agent. For example:
+
+```bash
+curl -X POST http://localhost:8088/responses -H "Content-Type: application/json" -d '{"input": "Create a slogan for a new electric SUV that is affordable and fun to drive."}'
+```
@@ -0,0 +1,15 @@
+name: agent-framework-workflows
+description: >
+  An Agent Framework workflow hosted by Foundry.
+metadata:
+  tags:
+    - AI Agent Hosting
+    - Azure AI AgentServer
+    - Responses Protocol
+    - Streaming
+template:
+  name: agent-framework-workflows
+  kind: hosted
+  protocols:
+    - protocol: responses
+      version: v0.1.0
@@ -0,0 +1,8 @@
+kind: hosted
+name: agent-framework-workflows
+protocols:
+  - protocol: responses
+    version: v0.1.0
+resources:
+  cpu: "0.25"
+  memory: 0.5Gi
@@ -0,0 +1,74 @@
+# Copyright (c) Microsoft. All rights reserved.
+
+import os
+
+from agent_framework import Agent
+from agent_framework.foundry import FoundryChatClient
+from agent_framework.orchestrations import GroupChatBuilder, GroupChatState
+from agent_framework_foundry_hosting import ResponsesHostServer
+from azure.ai.agentserver.responses import InMemoryResponseProvider
+from azure.identity import AzureCliCredential
+from dotenv import load_dotenv
+
+# Load environment variables from .env file
+load_dotenv()
+
+
+def round_robin_selector(state: GroupChatState) -> str:
+    """A round-robin selector function that picks the next speaker based on the current round index."""
+
+    participant_names = list(state.participants.keys())
+    return participant_names[state.current_round % len(participant_names)]
+
+
+def main():
+    client = FoundryChatClient(
+        project_endpoint=os.environ["FOUNDRY_PROJECT_ENDPOINT"],
+        model=os.environ["FOUNDRY_MODEL"],
+        credential=AzureCliCredential(),
+    )
+
+    writer_agent = Agent(
+        client=client,
+        instructions=(
+            "You are an excellent content writer. You create new content and edit contents based on the feedback."
+        ),
+        name="writer",
+        # History will be managed by the hosting infrastructure, thus there
+        # is no need to store history by the service. Learn more at:
+        # https://developers.openai.com/api/reference/resources/responses/methods/create
+        default_options={"store": False},
+    )
+
+    reviewer_agent = Agent(
+        client=client,
+        instructions=(
+            "You are an excellent content reviewer."
+            "Provide actionable feedback to the writer about the provided content."
+            "Provide the feedback in the most concise manner possible."
+        ),
+        name="reviewer",
+        # History will be managed by the hosting infrastructure, thus there
+        # is no need to store history by the service. Learn more at:
+        # https://developers.openai.com/api/reference/resources/responses/methods/create
+        default_options={"store": False},
+    )
+
+    workflow_agent = (
+        GroupChatBuilder(
+            participants=[writer_agent, reviewer_agent],
+            # Set a hard termination condition to stop after 4 messages:
+            # User message + writer message + reviewer message + writer message
+            termination_condition=lambda conversation: len(conversation) >= 4,
+            selection_func=round_robin_selector,
+        )
+        .build()
+        .as_agent()
+    )
+
+    server = ResponsesHostServer(workflow_agent, provider=InMemoryResponseProvider())
+    server.run()
+
+
+if __name__ == "__main__":
+    main()
@@ -0,0 +1,2 @@
+agent-framework
+agent-framework-foundry-hosting
@@ -0,0 +1,6 @@
+.venv
+__pycache__
+*.pyc
+*.pyo
+*.pyd
+.Python
@@ -0,0 +1,16 @@
+FROM python:3.12-slim
+
+WORKDIR /app/user_agent
+
+COPY wheels/ /tmp/wheels/
+COPY requirements.txt .
+RUN pip install --no-cache-dir --find-links /tmp/wheels/ -r requirements.txt && rm -rf /tmp/wheels/
+
+COPY . .
+
+RUN useradd -r appuser
+USER appuser
+
+EXPOSE 8088
+
+CMD ["python", "main.py"]
@@ -0,0 +1,43 @@
+# Agent Framework Agent with Local Shell
+
+> Note: This agent can execute local shell commands. We recommend running it in an isolated environment for security reasons.
+
+## Running the server in a Docker container
+
+Build the Docker image:
+
+```bash
+docker build -t agent-framework-agent-with-local-shell .
+```
+
+Run the Docker container:
+
+```bash
+docker run -p 8088:8088 --env-file .env agent-framework-agent-with-local-shell
+```
+
+## Interacting with the agent
+
+Send a POST request to the server with a JSON body containing a "message" field to interact with the agent. For example:
+
+```bash
+curl -X POST http://localhost:8088/responses -H "Content-Type: application/json" -d '{"input": "Hi"}'
+```
+
+The server will respond with a JSON object containing the response text and a response ID. You can use this response ID to continue the conversation in subsequent requests.
+
+## Multi-turn conversation
+
+To have a multi-turn conversation with the agent, include the previous response id in the request body. For example:
+
+```bash
+curl -X POST http://localhost:8088/responses -H "Content-Type: application/json" -d '{"input": "How are you?", "previous_response_id": "REPLACE_WITH_PREVIOUS_RESPONSE_ID"}'
+```
+
+## Deploying to Foundry
+
+TODO
+
+## Using the deployed agent in Agent Framework
+
+TODO
@@ -0,0 +1,15 @@
+name: agent-framework-agent-with-local-shell
+description: >
+  An Agent Framework agent that can execute local shell commands hosted by Foundry.
+metadata:
+  tags:
+    - AI Agent Hosting
+    - Azure AI AgentServer
+    - Responses Protocol
+    - Streaming
+template:
+  name: agent-framework-agent-with-local-shell
+  kind: hosted
+  protocols:
+    - protocol: responses
+      version: v0.1.0
@@ -0,0 +1,8 @@
+kind: hosted
+name: agent-framework-agent-with-local-shell
+protocols:
+  - protocol: responses
+    version: v0.1.0
+resources:
+  cpu: "0.25"
+  memory: 0.5Gi
@@ -0,0 +1,63 @@
+# Copyright (c) Microsoft. All rights reserved.
+
+import os
+import subprocess
+
+from agent_framework import Agent, tool
+from agent_framework.foundry import FoundryChatClient
+from agent_framework_foundry_hosting import ResponsesHostServer
+from azure.ai.agentserver.responses import InMemoryResponseProvider
+from azure.identity import AzureCliCredential
+from dotenv import load_dotenv
+
+# Load environment variables from .env file
+load_dotenv()
+
+
+@tool(approval_mode="always_require")
+def run_bash(command: str) -> str:
+    """Execute a shell command locally and return stdout, stderr, and exit code."""
+    try:
+        result = subprocess.run(
+            command,
+            shell=True,
+            capture_output=True,
+            text=True,
+            timeout=30,
+        )
+        parts: list[str] = []
+        if result.stdout:
+            parts.append(result.stdout)
+        if result.stderr:
+            parts.append(f"stderr: {result.stderr}")
+        parts.append(f"exit_code: {result.returncode}")
+        return "\n".join(parts)
+    except subprocess.TimeoutExpired:
+        return "Command timed out after 30 seconds"
+    except Exception as e:
+        return f"Error executing command: {e}"
+
+
+def main():
+    client = FoundryChatClient(
+        project_endpoint=os.environ["FOUNDRY_PROJECT_ENDPOINT"],
+        model=os.environ["FOUNDRY_MODEL"],
+        credential=AzureCliCredential(),
+    )
+
+    agent = Agent(
+        client=client,
+        instructions="You are a friendly assistant. Keep your answers brief.",
+        tools=[run_bash],
+        # History will be managed by the hosting infrastructure, thus there
+        # is no need to store history by the service. Learn more at:
+        # https://developers.openai.com/api/reference/resources/responses/methods/create
+        default_options={"store": False},
+    )
+
+    server = ResponsesHostServer(agent, provider=InMemoryResponseProvider())
+    server.run()
+
+
+if __name__ == "__main__":
+    main()
@@ -0,0 +1,2 @@
+agent-framework-core
+agent-framework-foundry-hosting
@@ -0,0 +1,6 @@
+.venv
+__pycache__
+*.pyc
+*.pyo
+*.pyd
+.Python
@@ -0,0 +1,16 @@
+FROM python:3.12-slim
+
+WORKDIR /app
+
+COPY . user_agent/
+WORKDIR /app/user_agent
+
+RUN if [ -f requirements.txt ]; then \
+        pip install -r requirements.txt; \
+    else \
+        echo "No requirements.txt found"; \
+    fi
+
+EXPOSE 8088
+
+CMD ["python", "main.py"]
@@ -0,0 +1,35 @@
+# Agent Framework Agent with Evaluation
+
+## Running the server locally
+
+Run the following command to start the server:
+
+```bash
+python main.py
+```
+
+## Interacting with the agent
+
+Send a POST request to the server with a JSON body containing a "message" field to interact with the agent. For example:
+
+```bash
+curl -X POST http://localhost:8088/responses -H "Content-Type: application/json" -d '{"input": "Hi"}'
+```
+
+The server will respond with a JSON object containing the response text and a response ID. You can use this response ID to continue the conversation in subsequent requests.
+
+## Multi-turn conversation
+
+To have a multi-turn conversation with the agent, include the previous response id in the request body. For example:
+
+```bash
+curl -X POST http://localhost:8088/responses -H "Content-Type: application/json" -d '{"input": "How are you?", "previous_response_id": "REPLACE_WITH_PREVIOUS_RESPONSE_ID"}'
+```
+
+## Deploying to Foundry
+
+TODO
+
+## Using the deployed agent in Agent Framework
+
+TODO
@@ -0,0 +1,15 @@
+name: agent-framework-agent-with-eval
+description: >
+  An Agent Framework agent is evaluated on each response hosted by Foundry.
+metadata:
+  tags:
+    - AI Agent Hosting
+    - Azure AI AgentServer
+    - Responses Protocol
+    - Streaming
+template:
+  name: agent-framework-agent-with-eval
+  kind: hosted
+  protocols:
+    - protocol: responses
+      version: v0.1.0
@@ -0,0 +1,8 @@
+kind: hosted
+name: agent-framework-agent-with-eval
+protocols:
+  - protocol: responses
+    version: v0.1.0
+resources:
+  cpu: "0.25"
+  memory: 0.5Gi
@@ -0,0 +1,50 @@
+# Copyright (c) Microsoft. All rights reserved.
+
+import os
+from random import randint
+
+from agent_framework import Agent, tool
+from agent_framework.foundry import FoundryChatClient
+from agent_framework_foundry_hosting import ResponsesHostServer
+from azure.ai.agentserver.responses import InMemoryResponseProvider
+from azure.identity import AzureCliCredential
+from dotenv import load_dotenv
+from pydantic import Field
+from typing_extensions import Annotated
+
+# Load environment variables from .env file
+load_dotenv()
+
+
+@tool(approval_mode="never_require")
+def get_weather(
+    location: Annotated[str, Field(description="The location to get the weather for.")],
+) -> str:
+    """Get the weather for a given location."""
+    conditions = ["sunny", "cloudy", "rainy", "stormy"]
+    return f"The weather in {location} is {conditions[randint(0, 3)]} with a high of {randint(10, 30)}°C."
+
+
+def main():
+    client = FoundryChatClient(
+        project_endpoint=os.environ["FOUNDRY_PROJECT_ENDPOINT"],
+        model=os.environ["FOUNDRY_MODEL"],
+        credential=AzureCliCredential(),
+    )
+
+    agent = Agent(
+        client=client,
+        instructions="You are a friendly assistant. Keep your answers brief.",
+        tools=[get_weather],
+        # History will be managed by the hosting infrastructure, thus there
+        # is no need to store history by the service. Learn more at:
+        # https://developers.openai.com/api/reference/resources/responses/methods/create
+        default_options={"store": False},
+    )
+
+    server = ResponsesHostServer(agent, provider=InMemoryResponseProvider())
+    server.run()
+
+
+if __name__ == "__main__":
+    main()
@@ -0,0 +1,2 @@
+agent-framework
+agent-framework-foundry-hosting
@@ -0,0 +1,6 @@
+.venv
+__pycache__
+*.pyc
+*.pyo
+*.pyd
+.Python
@@ -0,0 +1,16 @@
+FROM python:3.12-slim
+
+WORKDIR /app
+
+COPY . user_agent/
+WORKDIR /app/user_agent
+
+RUN if [ -f requirements.txt ]; then \
+        pip install -r requirements.txt; \
+    else \
+        echo "No requirements.txt found"; \
+    fi
+
+EXPOSE 8088
+
+CMD ["python", "main.py"]
@@ -0,0 +1,35 @@
+# Agent Framework Agent with Foundry Memory
+
+## Running the server locally
+
+Run the following command to start the server:
+
+```bash
+python main.py
+```
+
+## Interacting with the agent
+
+Send a POST request to the server with a JSON body containing a "message" field to interact with the agent. For example:
+
+```bash
+curl -X POST http://localhost:8088/responses -H "Content-Type: application/json" -d '{"input": "Hi"}'
+```
+
+The server will respond with a JSON object containing the response text and a response ID. You can use this response ID to continue the conversation in subsequent requests.
+
+## Multi-turn conversation
+
+To have a multi-turn conversation with the agent, include the previous response id in the request body. For example:
+
+```bash
+curl -X POST http://localhost:8088/responses -H "Content-Type: application/json" -d '{"input": "How are you?", "previous_response_id": "REPLACE_WITH_PREVIOUS_RESPONSE_ID"}'
+```
+
+## Deploying to Foundry
+
+TODO
+
+## Using the deployed agent in Agent Framework
+
+TODO
@@ -0,0 +1,15 @@
+name: agent-framework-agent-with-foundry-memory
+description: >
+  An Agent Framework agent with memory support hosted by Foundry.
+metadata:
+  tags:
+    - AI Agent Hosting
+    - Azure AI AgentServer
+    - Responses Protocol
+    - Streaming
+template:
+  name: agent-framework-agent-with-foundry-memory
+  kind: hosted
+  protocols:
+    - protocol: responses
+      version: v0.1.0
@@ -0,0 +1,8 @@
+kind: hosted
+name: agent-framework-agent-with-foundry-memory
+protocols:
+  - protocol: responses
+    version: v0.1.0
+resources:
+  cpu: "0.25"
+  memory: 0.5Gi
@@ -0,0 +1,91 @@
+# Copyright (c) Microsoft. All rights reserved.
+
+import asyncio
+import logging
+import os
+from datetime import datetime, timezone
+
+from agent_framework import Agent
+from agent_framework.foundry import FoundryChatClient, FoundryMemoryProvider
+from agent_framework_foundry_hosting import ResponsesHostServer
+from azure.ai.agentserver.responses import InMemoryResponseProvider
+from azure.ai.projects.aio import AIProjectClient
+from azure.ai.projects.models import (
+    MemoryStoreDefaultDefinition,
+    MemoryStoreDefaultOptions,
+)
+from azure.identity import AzureCliCredential
+from dotenv import load_dotenv
+
+# Load environment variables from .env file
+load_dotenv()
+
+logging.basicConfig(level=logging.INFO)
+
+
+async def _create_memory_store(project_client: AIProjectClient) -> FoundryMemoryProvider:
+    memory_store_name = f"hosted_agent_memory_{datetime.now(timezone.utc).strftime('%Y%m%d')}"
+    options = MemoryStoreDefaultOptions(
+        chat_summary_enabled=True,
+        user_profile_enabled=True,
+        user_profile_details=(
+            "Avoid irrelevant or sensitive data, such as age, financials, precise location, and credentials"
+        ),
+    )
+    memory_store_definition = MemoryStoreDefaultDefinition(
+        chat_model=os.environ["FOUNDRY_MODEL"],
+        embedding_model=os.environ["AZURE_OPENAI_EMBEDDING_MODEL"],
+        options=options,
+    )
+    memory_store = await project_client.beta.memory_stores.create(
+        name=memory_store_name,
+        description="Memory store for Agent Framework with FoundryMemoryProvider",
+        definition=memory_store_definition,
+    )
+
+    return FoundryMemoryProvider(
+        project_client=project_client,
+        memory_store_name=memory_store.name,
+        # Scope memories to a specific user, if not set, the session_id
+        # will be used as scope, which means memories are only shared within the same session
+        scope="demo",
+        # Do not wait to update memories after each interaction (for demo purposes)
+        # In production, consider setting a delay to batch updates and reduce costs
+        update_delay=0,
+    )
+
+
+async def _delete_memory_store(project_client: AIProjectClient, memory_store_name: str):
+    await project_client.beta.memory_stores.delete(name=memory_store_name)
+
+
+async def main():
+    client = FoundryChatClient(
+        project_endpoint=os.environ["FOUNDRY_PROJECT_ENDPOINT"],
+        model=os.environ["FOUNDRY_MODEL"],
+        credential=AzureCliCredential(),
+    )
+
+    # Create the memory store
+    memory_provider = await _create_memory_store(client.project_client)
+
+    agent = Agent(
+        client=client,
+        instructions="You are a friendly assistant. Keep your answers brief.",
+        context_providers=[memory_provider],
+        # History will be managed by the hosting infrastructure, thus there
+        # is no need to store history by the service. Learn more at:
+        # https://developers.openai.com/api/reference/resources/responses/methods/create
+        default_options={"store": False},
+    )
+
+    server = ResponsesHostServer(agent, provider=InMemoryResponseProvider())
+
+    try:
+        await server.run_async()
+    finally:
+        await _delete_memory_store(client.project_client, memory_provider.memory_store_name)
+
+
+if __name__ == "__main__":
+    asyncio.run(main())
@@ -0,0 +1,2 @@
+agent-framework
+agent-framework-foundry-hosting