feat: add asp adk samples

.github/dependabot.yml

@@ -113,6 +113,70 @@ updates:
         patterns:
           - "*"
 
+  - package-ecosystem: "uv"
+    directory: "/python/agents/RAG"
+    schedule:
+      interval: "weekly"
+      day: "monday"
+      time: "02:00"
+    commit-message:
+      prefix: "chore"
+      include: "scope"
+    labels:
+      - "dependencies"
+    groups:
+      all-dependencies:
+        patterns:
+          - "*"
+
+  - package-ecosystem: "uv"
+    directory: "/python/agents/customer-service"
+    schedule:
+      interval: "weekly"
+      day: "monday"
+      time: "02:00"
+    commit-message:
+      prefix: "chore"
+      include: "scope"
+    labels:
+      - "dependencies"
+    groups:
+      all-dependencies:
+        patterns:
+          - "*"
+
+  - package-ecosystem: "uv"
+    directory: "/python/agents/personalized-shopping"
+    schedule:
+      interval: "weekly"
+      day: "monday"
+      time: "02:00"
+    commit-message:
+      prefix: "chore"
+      include: "scope"
+    labels:
+      - "dependencies"
+    groups:
+      all-dependencies:
+        patterns:
+          - "*"
+
+  - package-ecosystem: "uv"
+    directory: "/python/agents/travel-concierge"
+    schedule:
+      interval: "weekly"
+      day: "monday"
+      time: "02:00"
+    commit-message:
+      prefix: "chore"
+      include: "scope"
+    labels:
+      - "dependencies"
+    groups:
+      all-dependencies:
+        patterns:
+          - "*"
+
   # Keep GitHub Actions up to date
   - package-ecosystem: "github-actions"
     directory: "/"

python/agents/RAG/README.md

@@ -36,11 +36,16 @@ This diagram outlines the agent's workflow, designed to provide informed and con
 ### Prerequisites
 
 *   **Google Cloud Account:** You need a Google Cloud account.
-*   **Python 3.9+:** Ensure you have Python 3.9 or a later version installed.
-*   **Poetry:** Install Poetry by following the instructions on the official Poetry website: [https://python-poetry.org/docs/](https://python-poetry.org/docs/)
+*   **Python 3.10+:** Ensure you have Python 3.10 or a later version installed.
+*   **uv:** For dependency management and packaging. Please follow the instructions on the official [uv website](https://docs.astral.sh/uv/) for installation.
+
+    ```bash
+    curl -LsSf https://astral.sh/uv/install.sh | sh
+    ```
+
 *   **Git:** Ensure you have git installed.
 
-### Project Setup with Poetry
+### Project Setup
 
 1.  **Clone the Repository:**
 
@@ -49,38 +54,20 @@ This diagram outlines the agent's workflow, designed to provide informed and con
     cd adk-samples/python/agents/RAG
     ```
 
-2.  **Install Dependencies with Poetry:**
-
-    **Note for Linux users:** If you get an error related to `keyring` during the installation, you can disable it by running the following command:
-    ```bash
-    poetry config keyring.enabled false
-    ```
-    This is a one-time setup.
+2.  **Install Dependencies:**
 
     ```bash
-    poetry install
+    uv sync
     ```
 
-    This command reads the `pyproject.toml` file and installs all the necessary dependencies into a virtual environment managed by Poetry.
+    This command reads the `pyproject.toml` file and installs all the necessary dependencies into a virtual environment.
 
-3.  **Activate the Poetry Shell:**
-
-    ```bash
-    poetry env activate
-    ```
-
-    This activates the virtual environment, allowing you to run commands within the project's environment.
-    Make sure the environment is active. If not, you can also activate it through 
-
-     ```bash
-    source .venv/bin/activate 
-    ```   
-4.  **Set up Environment Variables:**
+3.  **Set up Environment Variables:**
     Rename the file ".env.example" to ".env" 
     Follow the steps in the file to set up the environment variables.
 
-5. **Setup Corpus:**
-    If you have an existing corpus in Vertex AI RAG Engine, please set corpus information in your .env file. For example: RAG_CORPUS='projects/123/locations/us-central1/ragCorpora/456'. 
+4. **Setup Corpus:**
+    If you have an existing corpus in Vertex AI RAG Engine, please set corpus information in your .env file. For example: RAG_CORPUS='projects/123/locations/us-central1/ragCorpora/456'.
 
     If you don't have a corpus setup yet, please follow "How to upload my file to my RAG corpus" section. The `prepare_corpus_and_data.py` script will automatically create a corpus (if needed) and update the `RAG_CORPUS` variable in your `.env` file with the resource name of the created or retrieved corpus.
 
@@ -104,7 +91,7 @@ The `rag/shared_libraries/prepare_corpus_and_data.py` script helps you set up a
     *   **To use the default behavior (upload Alphabet's 10K PDF):**
         Simply run the script:
         ```bash
-        python rag/shared_libraries/prepare_corpus_and_data.py
+        uv run python rag/shared_libraries/prepare_corpus_and_data.py
         ```
         This will create a corpus named `Alphabet_10K_2024_corpus` (if it doesn't exist) and upload the PDF `goog-10-k-2024.pdf` downloaded from the URL specified in the script.
 
@@ -122,7 +109,7 @@ The `rag/shared_libraries/prepare_corpus_and_data.py` script helps you set up a
            ```
         c. Run the script:
            ```bash
-           python rag/shared_libraries/prepare_corpus_and_data.py
+           uv run python rag/shared_libraries/prepare_corpus_and_data.py
            ```
 
     *   **To upload a local PDF file:**
@@ -155,7 +142,7 @@ The `rag/shared_libraries/prepare_corpus_and_data.py` script helps you set up a
            ```
         d. Run the script:
            ```bash
-           python rag/shared_libraries/prepare_corpus_and_data.py
+           uv run python rag/shared_libraries/prepare_corpus_and_data.py
            ```
 
 More details about managing data in Vertex RAG Engine can be found in the
@@ -196,8 +183,9 @@ Agent: According to Alphabet's 2024 10-K report, the key business segments are:
 The evaluation can be run from the `RAG` directory using
 the `pytest` module:
 
-```
-poetry run pytest eval
+```bash
+uv sync --dev
+uv run pytest eval
 ```
 
 ### Evaluation Process
@@ -229,8 +217,8 @@ This evaluation helps ensure the agent correctly leverages the RAG capabilities
 The Agent can be deployed to Vertex AI Agent Engine using the following
 commands:
 
-```
-python deployment/deploy.py
+```bash
+uv run python deployment/deploy.py
 ```
 
 After deploying the agent, you'll be able to read the following INFO log message:
@@ -273,7 +261,7 @@ After deploying the agent, follow these steps to test it:
 3. **Test the Remote Agent:**
    - Run the test script:
      ```bash
-     python deployment/run.py
+     uv run python deployment/run.py
      ```
    This script will:
    - Connect to your deployed agent
@@ -282,6 +270,32 @@ After deploying the agent, follow these steps to test it:
 
 The test script includes example queries about Alphabet's 10-K report. You can modify the queries in `deployment/run.py` to test different aspects of your deployed agent.
 
+### Alternative: Using Agent Starter Pack
+
+You can also use the [Agent Starter Pack](https://goo.gle/agent-starter-pack) to create a production-ready version of this agent with additional deployment options:
+
+```bash
+# Create and activate a virtual environment
+python -m venv .venv && source .venv/bin/activate # On Windows: .venv\Scripts\activate
+
+# Install the starter pack and create your project
+pip install --upgrade agent-starter-pack
+agent-starter-pack create my-rag-agent -a adk@rag
+```
+
+<details>
+<summary>⚡️ Alternative: Using uv</summary>
+
+If you have [`uv`](https://github.com/astral-sh/uv) installed, you can create and set up your project with a single command:
+```bash
+uvx agent-starter-pack create my-rag-agent -a adk@rag
+```
+This command handles creating the project without needing to pre-install the package into a virtual environment.
+
+</details>
+
+The starter pack will prompt you to select deployment options and provides additional production-ready features including automated CI/CD deployment scripts.
+
 ## Customization
 
 ### Customize Agent

python/agents/RAG/pyproject.toml

@@ -6,31 +6,96 @@ authors = [
         { name = "Hangfei Lin", email = "[email protected]" },
         { name = "Chouaieb Nemri", email = "[email protected]" },
 ]
-
-license = "Apache License 2.0"
+license = "Apache-2.0"
 readme = "README.md"
+dependencies = [
+    "google-cloud-aiplatform[adk,agent-engines]>=1.108.0",
+    "google-adk>=1.10.0",
+    "pydantic-settings>=2.8.1",
+    "tabulate>=0.9.0",
+    "google-auth>=2.36.0",
+    "requests>=2.32.3",
+    "llama-index>=0.12",
+]
+
+requires-python = ">=3.10,<3.13"
+
+[dependency-groups]
+dev = [
+    "pytest>=8.3.5",
+    "pytest-mock>=3.14.0",
+    "scikit-learn>=1.6.1",
+    "pytest-cov>=6.0.0",
+    "pytest-asyncio>=0.26.0",
+    "agent-starter-pack>=0.14.1",
+]
 
-[tool.poetry.dependencies]
-python = "^3.11"
-pydantic-settings = "^2.8.1"
-tabulate = "^0.9.0"
-google-auth = "^2.36.0"
-requests = "^2.32.3"
-google-adk = "^1.10.0"
-google-cloud-aiplatform = { extras = [
-        "adk",
-        "agent-engines",
-], version = "^1.108.0" }
-llama-index = "^0.12"
-
-[tool.poetry.group.dev.dependencies]
-pytest = "^8.3.5"
-pytest-mock = "^3.14.0"
-scikit-learn = "^1.6.1"
-pytest-cov = "^6.0.0"
-pytest-asyncio = "^0.26.0"
-black = "^25.1.0"
+[project.optional-dependencies]
+lint = [
+    "ruff>=0.4.6",
+    "mypy>=1.15.0",
+    "codespell>=2.2.0",
+    "types-pyyaml>=6.0.12.20240917",
+    "types-requests>=2.32.0.20240914",
+]
+
+[tool.ruff]
+line-length = 88
+target-version = "py310"
+
+[tool.ruff.lint]
+select = [
+    "E",   # pycodestyle
+    "F",   # pyflakes
+    "W",   # pycodestyle warnings
+    "I",   # isort
+    "C",  # flake8-comprehensions
+    "B",   # flake8-bugbear
+    "UP", # pyupgrade
+    "RUF", # ruff specific rules
+]
+ignore = ["E501", "C901"] # ignore line too long, too complex
+
+[tool.ruff.lint.isort]
+known-first-party = ["rag"]
+
+[tool.mypy]
+disallow_untyped_calls = true
+disallow_untyped_defs = true
+disallow_incomplete_defs = true
+no_implicit_optional = true
+check_untyped_defs = true
+disallow_subclassing_any = true
+warn_incomplete_stub = true
+warn_redundant_casts = true
+warn_unused_ignores = true
+warn_unreachable = true
+follow_imports = "silent"
+ignore_missing_imports = true
+explicit_package_bases = true
+disable_error_code = ["misc", "no-untyped-call", "no-any-return"]
+
+exclude = [".venv"]
+
+[tool.codespell]
+ignore-words-list = "rouge"
+skip = "./locust_env/*,uv.lock,.venv,./frontend,**/*.ipynb"
+
+[tool.pytest.ini_options]
+pythonpath = "."
+asyncio_default_fixture_loop_scope = "function"
 
 [build-system]
-requires = ["poetry-core>=2.0.0,<3.0.0"]
-build-backend = "poetry.core.masonry.api"
+requires = ["uv_build>=0.8.14,<0.9.0"]
+build-backend = "uv_build"
+
+[tool.uv.build-backend]
+module-root = ""
+
+# This configuration file is used by goo.gle/agent-starter-pack to power remote templating.
+# It defines the template's properties and settings.
+[tool.agent-starter-pack]
+example_question = "What are the key business segments mentioned in Alphabet's 2024 10-K report?"
+
+[tool.agent-starter-pack.settings]
+agent_directory = "rag"

python/agents/RAG/rag/__init__.py

@@ -12,4 +12,13 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
+import os
+
+import google.auth
+
+_, project_id = google.auth.default()
+os.environ.setdefault("GOOGLE_CLOUD_PROJECT", project_id)
+os.environ.setdefault("GOOGLE_CLOUD_LOCATION", "global")
+os.environ.setdefault("GOOGLE_GENAI_USE_VERTEXAI", "True")
+
 from . import agent