wip

.github/workflows/build-agent.yaml

@@ -1,6 +1,7 @@
 name: Build and Push Agent Image
 
 on:
+  pull_request:
   push:
     branches:
       - main
@@ -14,33 +15,33 @@ jobs:
       packages: write
 
     steps:
-    - name: Checkout code
-      uses: actions/checkout@v3
-
-    - name: Set up Python environment
-      uses: actions/setup-python@v4
-      with:
-        python-version: '3.x'
-
-    - name: Install BeeAI CLI
-      run: pip install beeai-cli
-
-    - name: Login to GitHub Container Registry
-      uses: docker/login-action@v2
-      with:
-        registry: ghcr.io
-        username: ${{ github.actor }}
-        password: ${{ secrets.GITHUB_TOKEN }}
-
-    - name: Set up Docker
-      uses: docker/setup-docker-action@v4
-      with:
-        daemon-config: '{"features": {"containerd-snapshotter": true}}'
-
-    - name: Set up Docker Buildx
-      uses: docker/setup-buildx-action@v3
-
-    - name: Build and Push
-      run: |
-        beeai build ./ --tag ghcr.io/${{ github.repository }}/my-agent:latest --no-import --multi-platform
-        docker push ghcr.io/${{ github.repository }}/my-agent:latest
+      - name: Checkout code
+        uses: actions/checkout@v3
+
+      - name: Set up Python environment
+        uses: actions/setup-python@v4
+        with:
+          python-version: '3.x'
+
+      - name: Install BeeAI CLI
+        run: pip install -U "git+https://github.com/i-am-bee/beeai-platform.git@switch-to-a2a-protocol#subdirectory=apps/beeai-cli"
+
+      - name: Login to GitHub Container Registry
+        uses: docker/login-action@v2
+        with:
+          registry: ghcr.io
+          username: ${{ github.actor }}
+          password: ${{ secrets.GITHUB_TOKEN }}
+
+      - name: Set up Docker
+        uses: docker/setup-docker-action@v4
+        with:
+          daemon-config: '{"features": {"containerd-snapshotter": true}}'
+
+      - name: Set up Docker Buildx
+        uses: docker/setup-buildx-action@v3
+
+      - name: Build and Push
+        run: |
+          beeai build ./ --tag ghcr.io/${{ github.repository }}/my-agent-a2a:latest --no-import --multi-platform
+          docker push ghcr.io/${{ github.repository }}/my-agent-a2a:latest

Dockerfile

@@ -1,4 +1,4 @@
-FROM python:3.11-slim-bookworm
+FROM python:3.13-slim-bookworm
 COPY --from=ghcr.io/astral-sh/uv:0.6.16 /uv /bin/
 
 ENV UV_LINK_MODE=copy \

README.md

@@ -1,12 +1,17 @@
 # BeeAI Platform Agent Template
 
-This repository provides a template for creating a Python agent that can be used with the [BeeAI Platform](https://docs.beeai.dev).
+# TODO: update readme
+
+This repository provides a template for creating a Python agent that can be used with
+the [BeeAI Platform](https://docs.beeai.dev).
 
 ## Overview
 
-BeeAI agents are Python-based services that can be run locally or deployed to the BeeAI Platform. Each agent exposes specific functionality through the ACP (Agent Communication Protocol) which is implemented via SDK.
+BeeAI agents are Python-based services that can be run locally or deployed to the BeeAI Platform. Each agent exposes
+specific functionality through the ACP (Agent Communication Protocol) which is implemented via SDK.
 
 In this template, you'll find:
+
 - A basic agent implementation
 - Docker configuration to ease the build of agent
 - Project structure for building your own agents
@@ -38,11 +43,13 @@ In this template, you'll find:
 
 ## Getting Started
 
-1. **Set up your project**. Start by using this template for your own agent. You may use this as a template or fork this repository.
+1. **Set up your project**. Start by using this template for your own agent. You may use this as a template or fork this
+   repository.
 
 2. **Install dependencies** using `uv sync`.
 
-3. **Implement your agent** by modifying the source code located in [src/beeai_agents/server.py](src/beeai_agents/agent.py).
+3. **Implement your agent** by modifying the source code located
+   in [src/beeai_agents/server.py](src/hello_world/agent.py).
 
 Here's an example of the included template agent:
 
@@ -61,7 +68,9 @@ async def example_agent(input: list[Message], context: Context) -> AsyncGenerato
 ```
 
 Modify this file to implement your own agent's logic. Here are some key points to consider when creating your agent:
-- The function name (example_agent above) is used as the unique id for the agent in the platform. You can override this in the metadata.
+
+- The function name (example_agent above) is used as the unique id for the agent in the platform. You can override this
+  in the metadata.
 - The docstring is used as the agent's description in the platform UI. You can also override this in the metadata.
 - The `@server.agent()` decorator registers your function as an agent and can customize its appearance and behavior
 - Your agent receives messages in the `input` list, with the most recent message at the end
@@ -73,14 +82,15 @@ Modify this file to implement your own agent's logic. Here are some key points t
 
 ### 🖥️ Enhancing the User Experience with `PlatformUIAnnotation`
 
-To create the most engaging and helpful interface for your users, define the following metadata in your agent decorator. This information shapes how your agent is presented in the GUI.
+To create the most engaging and helpful interface for your users, define the following metadata in your agent decorator.
+This information shapes how your agent is presented in the GUI.
 
 ```py
 @server.agent(
     name="chat",
     description=(
-        "Conversational agent with memory, supporting real-time search, "
-        "Wikipedia lookups, and weather updates through integrated tools"
+            "Conversational agent with memory, supporting real-time search, "
+            "Wikipedia lookups, and weather updates through integrated tools"
     ),
     metadata=Metadata(
         annotations=Annotations(
@@ -108,10 +118,13 @@ To create the most engaging and helpful interface for your users, define the fol
 )
 ```
 
->[!Note]
->The example above highlights the components that directly impact the **GUI experience**. For the complete metadata specification, see the [ACP Agent Detail](https://agentcommunicationprotocol.dev/core-concepts/agent-detail) documentation.
+> [!Note]
+> The example above highlights the components that directly impact the **GUI experience**. For the complete metadata
+> specification, see the [ACP Agent Detail](https://agentcommunicationprotocol.dev/core-concepts/agent-detail)
+> documentation.
 
-4. **Update project metadata and dependencies** in the `pyproject.toml` file. After updating, synchronize with `uv sync`.
+4. **Update project metadata and dependencies** in the `pyproject.toml` file. After updating, synchronize with
+   `uv sync`.
 
 ## Running Agents Locally
 
@@ -147,7 +160,9 @@ There are two ways to add your agent to the BeeAI Platform:
 
 ### Local Development Mode
 
-When running agents locally with `uv run server`, they are automatically registered with the BeeAI Platform. In this mode:
+When running agents locally with `uv run server`, they are automatically registered with the BeeAI Platform. In this
+mode:
+
 - The BeeAI Platform will communicate with your local server
 - You manage the agent's lifecycle (starting/stopping)
 - Changes are immediately available without redeployment
@@ -160,6 +175,7 @@ To share your agent with others or deploy it to the BeeAI Platform:
 - Add the agent to BeeAI using: `beeai add https://github.com/your-username/your-repo-name`
 
 The BeeAI Platform will automatically:
+
 - Clone your repository
 - Build a Docker image
 - Start the agent container

pyproject.toml

@@ -1,21 +1,22 @@
 [project]
-name = "beeai-agents"
+name = "hello-world"
 version = "0.1.1"
-description = "Add your description here"
+description = "hello world agent"
 readme = "README.md"
 authors = [{ name = "IBM Corp." }]
-requires-python = ">=3.11,<4.0"
+requires-python = ">=3.13,<4.0"
 dependencies = [
-    "acp-sdk>=0.13.0",
+    "a2a-sdk>=0.2.12",
     "pyyaml>=6.0.2",
+    "uvicorn>=0.35.0",
 ]
 
 [tool.ruff]
 line-length = 120
 target-version = "py311"
 
 [project.scripts]
-server = "beeai_agents.agent:run"
+server = "hello_world.__main__:run"
 
 [build-system]
 requires = ["hatchling"]

src/hello_world/__main__.py

@@ -0,0 +1,34 @@
+import uvicorn
+
+from a2a.server.apps import A2AStarletteApplication
+from a2a.server.request_handlers import DefaultRequestHandler
+from a2a.server.tasks import InMemoryTaskStore
+from a2a.types import AgentCapabilities, AgentCard, AgentSkill, AgentExtension
+
+from hello_world.agent import HelloWorldAgentExecutor
+
+
+def run():
+    agent_card = AgentCard(
+        name="Hello World Agent",
+        description="Just a hello world agent",
+        url="http://localhost:8000/",
+        version="1.0.0",
+        defaultInputModes=["text"],
+        defaultOutputModes=["text"],
+        capabilities=AgentCapabilities(
+            extensions=[
+                AgentExtension(uri="beeai_ui", params={"ui_type": "chat"}),
+                AgentExtension(uri="required_env", params={"env": [{"name": "HELLO_TEMPLATE", "required": False}]}),
+            ]
+        ),
+        skills=[AgentSkill(id="hello_world", name="hello_world", description="returns hello world", tags=["hello"])],
+    )
+
+    request_handler = DefaultRequestHandler(agent_executor=HelloWorldAgentExecutor(), task_store=InMemoryTaskStore())
+    server = A2AStarletteApplication(agent_card=agent_card, http_handler=request_handler)
+    uvicorn.run(server.build(), host="0.0.0.0", port=8000)
+
+
+if __name__ == "__main__":
+    run()

src/hello_world/agent.py

@@ -0,0 +1,15 @@
+import os
+
+from a2a.server.agent_execution import AgentExecutor, RequestContext
+from a2a.server.events import EventQueue
+from a2a.utils import new_agent_text_message
+
+
+class HelloWorldAgentExecutor(AgentExecutor):
+    async def execute(self, context: RequestContext, event_queue: EventQueue) -> None:
+        hello_template: str = os.getenv("HELLO_TEMPLATE", "Ciao %s!")
+        result = hello_template % context.message.parts[0].root.text
+        await event_queue.enqueue_event(new_agent_text_message(result))
+
+    async def cancel(self, context: RequestContext, event_queue: EventQueue) -> None:
+        raise NotImplementedError("cancel not supported")