GoogleCloudPlatform · xtan999 · Jun 4, 2026
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+# Data Engineering Agent A2A Client Example
+
+This directory contains a sample Python implementation of an
+[Agent-to-Agent (A2A)](https://a2a-protocol.org/) client designed to interact
+with the **Google Cloud Data Engineering Agent (DEA)**.
+
+## Background
+
+The Data Engineering Agent is a BigQuery and Dataform ELT expert capable of
+building, managing, and troubleshooting data pipelines. To enable
+interoperability across different platforms and agents, it exposes an interface
+following the A2A protocol.
+
+Official Documentation:
+[Data Engineering Agent API Overview](https://docs.cloud.google.com/gemini/data-agents/data-engineering-agent/api-overview)
+
+This example demonstrates how to use the open-source
+[A2A Python SDK](https://github.com/a2aproject/a2a-python) to: 1. **Discover**
+the agent's capabilities via its Agent Card. 2. **Authenticate** using Google
+Application Default Credentials (ADC). 3. **Maintain State** across multi-turn
+conversations using Conversation Tokens persisted to a local file. 4. **Handle
+Complex Tasks** by automatically resuming execution when agent finished with
+`DEADLINE_EXCEEDED`. 5. **Configure Extensions** like `Instruction` to customize
+agent behavior.
+
+## Features
+
+-   **Native A2A SDK Usage:** Uses `A2ACardResolver` and `create_client` for
+    idiomatic protocol interaction.
+-   **Streaming-only Execution:** Hardcoded to use response streaming for lowest
+    real-time latency and optimal interaction patterns.
+-   **Session Persistence:** Automatically saves and loads the
+    `conversationToken` from a local file, allowing multi-turn conversations via
+    repeated script executions.
+-   **Configurable Parameters:** Exposes `gcp_resource_id` for flexibility,
+    automatically extracting project and location details.
+-   **Instruction Loading:** Automatically reads custom instructions from local
+    files or directories, using filenames as the instruction name and file
+    content as the definition.
+-   **Extension Header Support:** Uses `ServiceParametersFactory` to correctly
+    set the `A2A-Extensions` HTTP header required by the agent.
+-   **Automated Resumption:** Detects `DEADLINE_EXCEEDED` via the
+    `finish_reason` extension and transparently continues the task.
+
+## Prerequisites
+
+-   Python 3.10 or higher.
+-   [Google Cloud SDK (gcloud)](https://cloud.google.com/sdk/docs/install)
+    installed and configured.
+-   Enable required APIs
+    [Use the Data Engineering Agent to build and modify data pipelines](https://docs.cloud.google.com/bigquery/docs/data-engineering-agent-pipelines#required-apis)
+
+## Setup
+
+1.  **Create and activate a virtual environment:**
+
+    ```bash
+    python3 -m venv .dea
+    source .dea/bin/activate
+    ```
+
+2.  **Install dependencies:**
+
+    ```bash
+    pip install -r requirements.txt
+    ```
+
+3.  **Authenticate with Google Cloud:**
+
+    ```bash
+    gcloud auth application-default login
+    ```
+
+## Usage
+
+### Single Message Mode
+
+Sends a single message and exits. `gcp_resource_id` and `message` are required.
+
+```
+python3 dea_a2a_client.py \
+    --gcp_resource_id projects/my-project/locations/us-central1/repositories/my-repo/workspaces/default \
+    --message "List my Dataform tables"
+```
+
+### Multi-turn Conversation (State Persistence)
+
+To maintain a conversation across multiple calls, use the
+`--conversation_token_path` argument. The script will save the conversation
+token to this file and reload it in subsequent calls.
+
+```
+# First turn (starts session)
+python3 dea_a2a_client.py \
+    --gcp_resource_id projects/my-project/locations/us-central1/repositories/my-repo/workspaces/default \
+    --message "hi" \
+    --conversation_token_path ./token.txt
+
+# Second turn (continues previous context)
+python3 dea_a2a_client.py \
+    --gcp_resource_id projects/my-project/locations/us-central1/repositories/my-repo/workspaces/default \
+    --message "Explain the first table" \
+    --conversation_token_path ./token.txt
+```
+
+### Advanced: Providing Local Instructions
+
+You can point the client to local files (e.g., SQL style guides) to influence
+the agent's behavior.
+
+```
+python3 dea_a2a_client.py \
+    --gcp_resource_id projects/my-project/locations/us-central1/repositories/my-repo/workspaces/default \
+    --message "List my tables" \
+    --instruction_path ./style_guide.md
+```
+
+#### Command-line Arguments
+
+Argument                    | Required | Description
+:-------------------------- | :------- | :----------
+`--gcp_resource_id`         | **Yes**  | The target resource ID. Supported formats `projects/{p}/locations/{l}/repositories/{r}/workspaces/{w}` (Dataform)
+`--message`                 | **Yes**  | The message to send to the agent.
+`--conversation_token_path` | No       | Path to a local file to persist conversation token. Allows for multi-turn conversations.
+`--instruction_path`        | No       | Path to a file or directory containing instructions. Can be repeated.
+
+### Running Unit Tests
+
+Make sure the virtual environment is activated, then run:
+
+```bash
+python3 dea_a2a_client_test.py
+```
+
+Alternatively, if the virtual environment is not activated, you can run it
+directly using the venv python:
+
+```bash
+./.dea/bin/python3 dea_a2a_client_test.py
+```