added sync, async, temporal, pydantic ai integration

Author: michael-chou359

examples/tutorials/00_sync/000_hello_acp/uv.lock

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+# Python
+__pycache__/
+*.py[cod]
+*$py.class
+*.so
+.Python
+build/
+develop-eggs/
+dist/
+downloads/
+eggs/
+.eggs/
+lib/
+lib64/
+parts/
+sdist/
+var/
+wheels/
+*.egg-info/
+.installed.cfg
+*.egg
+
+# Environments
+.env**
+.venv
+env/
+venv/
+ENV/
+env.bak/
+venv.bak/
+
+# IDE
+.idea/
+.vscode/
+*.swp
+*.swo
+
+# Git
+.git
+.gitignore
+
+# Misc
+.DS_Store

examples/tutorials/00_sync/030_langgraph/uv.lock

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+# syntax=docker/dockerfile:1.3
+FROM python:3.12-slim
+COPY --from=ghcr.io/astral-sh/uv:0.6.4 /uv /uvx /bin/
+
+# Install system dependencies
+RUN apt-get update && apt-get install -y \
+    htop \
+    vim \
+    curl \
+    tar \
+    python3-dev \
+    postgresql-client \
+    build-essential \
+    libpq-dev \
+    gcc \
+    cmake \
+    netcat-openbsd \
+    && apt-get clean \
+    && rm -rf /var/lib/apt/lists/*
+
+RUN uv pip install --system --upgrade pip setuptools wheel
+
+ENV UV_HTTP_TIMEOUT=1000
+
+# Copy pyproject.toml and README.md to install dependencies
+COPY 00_sync/040_pydantic_ai/pyproject.toml /app/040_pydantic_ai/pyproject.toml
+COPY 00_sync/040_pydantic_ai/README.md /app/040_pydantic_ai/README.md
+
+WORKDIR /app/040_pydantic_ai
+
+# Copy the project code
+COPY 00_sync/040_pydantic_ai/project /app/040_pydantic_ai/project
+
+# Copy the test files
+COPY 00_sync/040_pydantic_ai/tests /app/040_pydantic_ai/tests
+
+# Copy shared test utilities
+COPY test_utils /app/test_utils
+
+# Install the required Python packages with dev dependencies
+RUN uv pip install --system .[dev]
+
+# Set environment variables
+ENV PYTHONPATH=/app
+
+# Set test environment variables
+ENV AGENT_NAME=s040-pydantic-ai
+
+# Run the agent using uvicorn
+CMD ["uvicorn", "project.acp:acp", "--host", "0.0.0.0", "--port", "8000"]

examples/tutorials/00_sync/040_pydantic_ai/.dockerignore

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+# Tutorial 040: Sync Pydantic AI Agent
+
+This tutorial demonstrates how to build a **synchronous** Pydantic AI agent on AgentEx with:
+- Tool calling (Pydantic AI handles the tool loop internally)
+- Streaming token output (including token-by-token tool-call argument streaming)
+
+## Key Concepts
+
+### Sync ACP
+The sync ACP model uses HTTP request/response for communication. The `@acp.on_message_send` handler receives a message and yields streaming events back to the client.
+
+### Pydantic AI Integration
+- **Agent**: A single `pydantic_ai.Agent` that owns the model and tools. No graph required — Pydantic AI runs its own tool-call loop until the model is done.
+- **`@agent.tool_plain`**: Registers a Python function as a tool. Pydantic AI infers the schema from type hints and docstring.
+- **`agent.run_stream_events(...)`**: Yields `AgentStreamEvent`s (PartStartEvent / PartDeltaEvent / PartEndEvent / FunctionToolResultEvent) as the model produces them.
+
+### Streaming
+The agent streams tokens and tool-call arguments as they're generated using `convert_pydantic_ai_to_agentex_events()`, which adapts Pydantic AI's stream into AgentEx `TaskMessageUpdate` events. Notably, **tool-call arguments stream as `ToolRequestDelta` tokens** rather than arriving as a single complete payload — a richer experience than what OpenAI Agents SDK currently exposes.
+
+## Files
+
+| File | Description |
+|------|-------------|
+| `project/acp.py` | ACP server and message handler |
+| `project/agent.py` | Pydantic AI agent + tool registration |
+| `project/tools.py` | Tool definitions (weather example) |
+| `tests/test_agent.py` | Integration tests |
+| `manifest.yaml` | Agent configuration |
+
+## Running Locally
+
+```bash
+# From this directory
+agentex agents run
+```
+
+## Running Tests
+
+```bash
+pytest tests/test_agent.py -v
+```
+
+## Notes
+
+- Multi-turn conversation memory is not wired in this tutorial. Pydantic AI does not ship a checkpointer like LangGraph; to add memory, load prior messages via `adk.messages.list(task_id=...)` and pass them to `agent.run_stream_events(..., message_history=...)`.
+- Reasoning/thinking tokens are not exercised here because `gpt-4o-mini` does not emit `ThinkingPart`s. Swap to a reasoning-capable model (e.g. `openai:o1-mini` via Pydantic AI's appropriate provider) if you want to test that branch end-to-end.

examples/tutorials/00_sync/040_pydantic_ai/Dockerfile

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+build:
+  context:
+    root: ../../
+    include_paths:
+      - 00_sync/040_pydantic_ai
+      - test_utils
+    dockerfile: 00_sync/040_pydantic_ai/Dockerfile
+    dockerignore: 00_sync/040_pydantic_ai/.dockerignore
+
+local_development:
+  agent:
+    port: 8000
+    host_address: host.docker.internal
+  paths:
+    acp: project/acp.py
+
+agent:
+  acp_type: sync
+  name: s040-pydantic-ai
+  description: A sync Pydantic AI agent with tool calling and streaming
+
+  temporal:
+    enabled: false
+
+  credentials:
+    - env_var_name: OPENAI_API_KEY
+      secret_name: openai-api-key
+      secret_key: api-key
+    - env_var_name: REDIS_URL
+      secret_name: redis-url-secret
+      secret_key: url
+    - env_var_name: SGP_API_KEY
+      secret_name: sgp-api-key
+      secret_key: api-key
+    - env_var_name: SGP_ACCOUNT_ID
+      secret_name: sgp-account-id
+      secret_key: account-id
+    - env_var_name: SGP_CLIENT_BASE_URL
+      secret_name: sgp-client-base-url
+      secret_key: url
+
+deployment:
+  image:
+    repository: ""
+    tag: "latest"
+
+  global:
+    agent:
+      name: "s040-pydantic-ai"
+      description: "A sync Pydantic AI agent with tool calling and streaming"
+    replicaCount: 1
+    resources:
+      requests:
+        cpu: "500m"
+        memory: "1Gi"
+      limits:
+        cpu: "1000m"
+        memory: "2Gi"

examples/tutorials/00_sync/040_pydantic_ai/README.md

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+"""ACP (Agent Communication Protocol) handler for Agentex.
+
+This is the API layer — it owns the agent lifecycle and streams tokens
+and tool calls from the Pydantic AI agent to the Agentex frontend.
+"""
+
+from __future__ import annotations
+
+from typing import AsyncGenerator
+
+from dotenv import load_dotenv
+
+load_dotenv()
+
+from project.agent import create_agent
+from agentex.lib.adk import convert_pydantic_ai_to_agentex_events
+from agentex.lib.types.acp import SendMessageParams
+from agentex.lib.utils.logging import make_logger
+from agentex.lib.sdk.fastacp.fastacp import FastACP
+from agentex.types.task_message_update import TaskMessageUpdate
+from agentex.types.task_message_content import TaskMessageContent
+
+logger = make_logger(__name__)
+
+acp = FastACP.create(acp_type="sync")
+
+_agent = None
+
+
+def get_agent():
+    """Get or create the Pydantic AI agent instance."""
+    global _agent
+    if _agent is None:
+        _agent = create_agent()
+    return _agent
+
+
+@acp.on_message_send
+async def handle_message_send(
+    params: SendMessageParams,
+) -> TaskMessageContent | list[TaskMessageContent] | AsyncGenerator[TaskMessageUpdate, None]:
+    """Handle incoming messages from Agentex, streaming tokens and tool calls."""
+    agent = get_agent()
+
+    user_message = params.content.content
+    logger.info(f"Processing message for task {params.task.id}")
+
+    async with agent.run_stream_events(user_message) as stream:
+        async for event in convert_pydantic_ai_to_agentex_events(stream):
+            yield event

examples/tutorials/00_sync/040_pydantic_ai/manifest.yaml

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+"""Pydantic AI agent definition.
+
+The Agent is the boundary between this module and the API layer (acp.py).
+Pydantic AI handles its own tool-call loop internally — no graph required.
+"""
+
+from __future__ import annotations
+
+from datetime import datetime
+
+from pydantic_ai import Agent
+
+from project.tools import get_weather
+
+MODEL_NAME = "openai:gpt-4o-mini"
+SYSTEM_PROMPT = """You are a helpful AI assistant with access to tools.
+
+Current date and time: {timestamp}
+
+Guidelines:
+- Be concise and helpful
+- Use tools when they would help answer the user's question
+- If you're unsure, ask clarifying questions
+- Always provide accurate information
+"""
+
+
+def create_agent() -> Agent:
+    """Build and return the Pydantic AI agent with tools registered."""
+    agent = Agent(
+        MODEL_NAME,
+        system_prompt=SYSTEM_PROMPT.format(
+            timestamp=datetime.now().strftime("%Y-%m-%d %H:%M:%S")
+        ),
+    )
+
+    agent.tool_plain(get_weather)
+
+    return agent

examples/tutorials/00_sync/040_pydantic_ai/project/__init__.py

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+"""Tool definitions for the Pydantic AI agent.
+
+Pydantic AI tools are registered directly on the Agent via decorators
+(see project.agent). This module hosts the bare functions so they're
+easy to unit-test in isolation.
+"""
+
+from __future__ import annotations
+
+
+def get_weather(city: str) -> str:
+    """Get the current weather for a city.
+
+    Args:
+        city: The name of the city to get weather for.
+
+    Returns:
+        A string describing the weather conditions.
+    """
+    return f"The weather in {city} is sunny and 72°F"