Use new template repo

Author: nhynes

.github/workflows/publish.yml

@@ -16,8 +16,6 @@ jobs:
       matrix:
         include:
           # Update this to build your own agent images.
-          - name: adk-debate-judge
-            dockerfile: scenarios/debate/Dockerfile.adk-debate-judge
           - name: debate-judge
             dockerfile: scenarios/debate/Dockerfile.debate-judge
           - name: debater

README.md

@@ -1,7 +1,7 @@
 ## Quickstart
 1. Clone the repo
 ```
-git clone [email protected]:agentbeats/tutorial.git agentbeats-tutorial
+git clone [email protected]:RDI-Foundation/tutorial.git agentbeats-tutorial
 cd agentbeats-tutorial
 ```
 2. Install dependencies
@@ -12,7 +12,7 @@ uv sync
 ```
 cp sample.env .env
 ```
-Add your Google API key to the .env file
+Fill in the keys you plan to use (e.g. `GOOGLE_API_KEY` for the debate example and `OPENAI_API_KEY` for the tau2 example).
 
 4. Run the [debate example](#example)
 ```
@@ -25,6 +25,8 @@ This command will:
 
 **Note:** Use `--show-logs` to see agent outputs during the assessment, and `--serve-only` to start agents without running the assessment.
 
+**Note:** If you see `Error: Some agent endpoints are already in use`, change the ports in the scenario TOML (or stop the process using them).
+
 To run this example manually, start the agent servers in separate terminals, and then in another terminal run the A2A client on the scenario.toml file to initiate the assessment.
 
 After running, you should see an output similar to this.
@@ -33,21 +35,22 @@ After running, you should see an output similar to this.
 
 ## Project Structure
 ```
-src/
-└─ agentbeats/
-   ├─ green_executor.py        # base A2A green agent executor
-   ├─ models.py                # pydantic models for green agent IO
-   ├─ client.py                # A2A messaging helpers
-   ├─ client_cli.py            # CLI client to start assessment
-   └─ run_scenario.py          # run agents and start assessment
-
 scenarios/
-└─ debate/                     # implementation of the debate example
-   ├─ debate_judge.py          # green agent impl using the official A2A SDK
-   ├─ adk_debate_judge.py      # alternative green agent impl using Google ADK
-   ├─ debate_judge_common.py   # models and utils shared by above impls
-   ├─ debater.py               # debater agent (Google ADK)
-   └─ scenario.toml            # config for the debate example
+├─ debate/
+│  ├─ judge/src/               # green agent (green-agent-template structure)
+│  ├─ debater/src/             # purple agent (agent-template structure)
+│  ├─ Dockerfile.debate-judge
+│  ├─ Dockerfile.debater
+│  └─ scenario.toml
+└─ tau2/
+   ├─ evaluator/src/           # green agent (green-agent-template structure)
+   ├─ agent/src/               # purple agent (agent-template structure)
+   ├─ Dockerfile.tau2-evaluator
+   ├─ Dockerfile.tau2-agent
+   ├─ setup.sh                 # downloads tau2-bench data for local runs
+   └─ scenario.toml
+
+src/agentbeats/                # optional local runner + A2A client helpers (`agentbeats-run`)
 ```
 
 # AgentBeats Tutorial
@@ -118,7 +121,10 @@ To make things concrete, we will use a debate scenario as our toy example:
 - Two purple agents (`Debater`) participate by presenting arguments for their side of the topic.
 
 To run this example, we start all three servers and then use an A2A client to send an `assessment_request` to the green agent and observe its outputs.
-The full example code is given in the template repository. Follow the quickstart guide to setup the project and run the example.
+The debate example is implemented using the same structure as the supported templates:
+
+- Green agent: `scenarios/debate/judge/src/` (green-agent-template style)
+- Purple agent: `scenarios/debate/debater/src/` (agent-template style)
 
 ### Dockerizing Agent
 

pyproject.toml

@@ -9,16 +9,22 @@ description = "Agentbeats Tutorial"
 readme = "README.md"
 requires-python = ">=3.11"
 dependencies = [
-    "a2a-sdk>=0.3.5",
-    "google-adk>=1.14.1",
+    "a2a-sdk[http-server]>=0.3.20",
+    "httpx>=0.28.1",
+    "pydantic>=2.11.9",
+    "python-dotenv>=1.1.1",
+    "uvicorn>=0.38.0",
+]
+
+[project.optional-dependencies]
+debate = [
     "google-genai>=1.36.0",
+]
+tau2-agent = [
     "litellm>=1.0.0",
-    "loguru>=0.7.0",
+]
+tau2-evaluator = [
     "nest-asyncio>=1.6.0",
-    "pydantic>=2.11.9",
-    "python-dotenv>=1.1.1",
-    "uvicorn>=0.35.0",
-    # tau2 from GitHub
     "tau2 @ git+https://github.com/sierra-research/tau2-bench.git",
 ]
 

sample.env

@@ -1,2 +1,3 @@
 GOOGLE_GENAI_USE_VERTEXAI=FALSE
 GOOGLE_API_KEY=
+OPENAI_API_KEY=

scenarios/debate/Dockerfile.debate-judge

@@ -1,4 +1,6 @@
-FROM ghcr.io/astral-sh/uv:python3.12-trixie
+FROM ghcr.io/astral-sh/uv:python3.13-bookworm
+
+ENV UV_HTTP_TIMEOUT=300
 
 RUN adduser agentbeats
 USER agentbeats
@@ -9,10 +11,10 @@ COPY src src
 
 RUN \
     --mount=type=cache,target=/home/agentbeats/.cache/uv,uid=1000 \
-    uv sync --locked
+    uv sync --locked --no-dev --no-install-project --extra debate
 
 COPY scenarios scenarios
 
-ENTRYPOINT ["uv", "run", "scenarios/debate/debate_judge.py"]
+ENTRYPOINT ["uv", "run", "scenarios/debate/judge/src/server.py"]
 CMD ["--host", "0.0.0.0"]
 EXPOSE 9009

scenarios/debate/Dockerfile.debater

@@ -1,4 +1,6 @@
-FROM ghcr.io/astral-sh/uv:python3.12-trixie
+FROM ghcr.io/astral-sh/uv:python3.13-bookworm
+
+ENV UV_HTTP_TIMEOUT=300
 
 RUN adduser agentbeats
 USER agentbeats
@@ -9,10 +11,10 @@ COPY src src
 
 RUN \
     --mount=type=cache,target=/home/agentbeats/.cache/uv,uid=1000 \
-    uv sync --locked
+    uv sync --locked --no-dev --no-install-project --extra debate
 
 COPY scenarios scenarios
 
-ENTRYPOINT ["uv", "run", "scenarios/debate/debater.py"]
+ENTRYPOINT ["uv", "run", "scenarios/debate/debater/src/server.py"]
 CMD ["--host", "0.0.0.0"]
 EXPOSE 9019

scenarios/debate/debater/src/agent.py

@@ -0,0 +1,39 @@
+from dotenv import load_dotenv
+from google import genai
+
+from a2a.server.tasks import TaskUpdater
+from a2a.types import Message, Part, TaskState, TextPart
+from a2a.utils import get_message_text, new_agent_text_message
+
+
+load_dotenv()
+
+
+SYSTEM_PROMPT = """
+You are a professional debater.
+Follow the role instructions in the prompt (Pro/Affirmative or Con/Negative).
+Write a persuasive, well-structured argument. Keep it concise (<= 200 words).
+"""
+
+
+class Agent:
+    def __init__(self):
+        self.client = genai.Client()
+
+    async def run(self, message: Message, updater: TaskUpdater) -> None:
+        prompt = get_message_text(message)
+
+        await updater.update_status(TaskState.working, new_agent_text_message("Thinking..."))
+
+        response = self.client.models.generate_content(
+            model="gemini-2.5-flash-lite",
+            config=genai.types.GenerateContentConfig(system_instruction=SYSTEM_PROMPT),
+            contents=prompt,
+        )
+        text = response.text or ""
+
+        await updater.add_artifact(
+            parts=[Part(root=TextPart(text=text))],
+            name="Response",
+        )
+

scenarios/debate/debater/src/executor.py

@@ -0,0 +1,68 @@
+from a2a.server.agent_execution import AgentExecutor, RequestContext
+from a2a.server.events import EventQueue
+from a2a.server.tasks import TaskUpdater
+from a2a.types import (
+    InvalidRequestError,
+    Task,
+    TaskState,
+    UnsupportedOperationError,
+)
+from a2a.utils import (
+    new_agent_text_message,
+    new_task,
+)
+from a2a.utils.errors import ServerError
+
+from agent import Agent
+
+
+TERMINAL_STATES = {
+    TaskState.completed,
+    TaskState.canceled,
+    TaskState.failed,
+    TaskState.rejected,
+}
+
+
+class Executor(AgentExecutor):
+    def __init__(self):
+        self.agents: dict[str, Agent] = {}
+
+    async def execute(self, context: RequestContext, event_queue: EventQueue) -> None:
+        msg = context.message
+        if not msg:
+            raise ServerError(error=InvalidRequestError(message="Missing message in request"))
+
+        task = context.current_task
+        if task and task.status.state in TERMINAL_STATES:
+            raise ServerError(
+                error=InvalidRequestError(
+                    message=f"Task {task.id} already processed (state: {task.status.state})"
+                )
+            )
+
+        if not task:
+            task = new_task(msg)
+            await event_queue.enqueue_event(task)
+
+        context_id = task.context_id
+        updater = TaskUpdater(event_queue, task.id, context_id)
+        await updater.start_work()
+
+        try:
+            agent = self.agents.get(context_id)
+            if not agent:
+                agent = Agent()
+                self.agents[context_id] = agent
+
+            await agent.run(msg, updater)
+            if not updater._terminal_state_reached:
+                await updater.complete()
+        except Exception as e:
+            print(f"Task failed with agent error: {e}")
+            await updater.failed(
+                new_agent_text_message(f"Agent error: {e}", context_id=context_id, task_id=task.id)
+            )
+
+    async def cancel(self, context: RequestContext, event_queue: EventQueue) -> None:
+        raise ServerError(error=UnsupportedOperationError())

scenarios/debate/debater/src/server.py

@@ -0,0 +1,55 @@
+import argparse
+
+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,
+)
+
+from executor import Executor
+
+
+def main():
+    parser = argparse.ArgumentParser(description="Run the debate participant (purple agent).")
+    parser.add_argument("--host", type=str, default="127.0.0.1", help="Host to bind the server")
+    parser.add_argument("--port", type=int, default=9019, help="Port to bind the server")
+    parser.add_argument("--card-url", type=str, help="URL to advertise in the agent card")
+    args = parser.parse_args()
+
+    skill = AgentSkill(
+        id="debate_participant",
+        name="Debate Participant",
+        description="Participates in a debate as either Pro or Con given role instructions.",
+        tags=["debate"],
+        examples=["Debate topic: Should artificial intelligence be regulated? Present your opening argument."],
+    )
+
+    agent_card = AgentCard(
+        name="Debater",
+        description="A debater agent that produces persuasive arguments given role instructions.",
+        url=args.card_url or f"http://{args.host}:{args.port}/",
+        version="1.0.0",
+        default_input_modes=["text"],
+        default_output_modes=["text"],
+        capabilities=AgentCapabilities(streaming=True),
+        skills=[skill],
+    )
+
+    request_handler = DefaultRequestHandler(
+        agent_executor=Executor(),
+        task_store=InMemoryTaskStore(),
+    )
+    server = A2AStarletteApplication(
+        agent_card=agent_card,
+        http_handler=request_handler,
+    )
+    uvicorn.run(server.build(), host=args.host, port=args.port)
+
+
+if __name__ == "__main__":
+    main()
+