docs(samples): add retail search service samples

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samples/interactive-tutorials/README.md

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+# Google Retail Search: Python code samples
+## Get started
+### Select your project and enable the Retail API
+
+Google Cloud organizes resources into projects. This lets you
+collect all the related resources for a single application in one place.
+
+If you don't have a Google Cloud project yet or you're not the owner of an existing one, you can
+[create a new project](https://console.cloud.google.com/projectcreate).
+
+After the project is created, set your PROJECT_ID to a ```project``` variable.
+1. Run the following command in Terminal:
+    ```bash
+    gcloud config set project <YOUR_PROJECT_ID>
+    ```
+
+1. Check that the Retail API is enabled for your Project in the [Admin Console](https://console.cloud.google.com/ai/retail/).
+
+### Set up authentication
+
+To run a code sample from the Cloud Shell, you need to authenticate. To do this, use the Application Default Credentials.
+
+1. Set your user credentials to authenticate your requests to the Retail API
+
+    ```bash
+    gcloud auth application-default login
+    ```
+
+1. Type `Y` and press **Enter**. Click the link in Terminal. A browser window should appear asking you to log in using your Gmail account.
+
+1. Provide the Google Auth Library with access to your credentials and paste the code from the browser to the Terminal.
+
+1. Run the code sample and check the Retail API in action.
+
+**Note**: Click the copy button on the side of the code box to paste the command in the Cloud Shell terminal and run it.
+
+### Set the GOOGLE_CLOUD_PROJECT_NUMBER environment variable
+
+Because you are going to run the code samples in your own Google Cloud project, you should specify the **project_number** as an environment variable. It will be used in every request to the Retail API.
+
+1. You can find the ```project_number``` in the Project Info card displayed on **Home/Dashboard**.
+
+1. Set the environment variable with the following command:
+    ```bash
+    export GOOGLE_CLOUD_PROJECT_NUMBER=<YOUR_PROJECT_NUMBER>
+    ```
+
+### Install Google Cloud Retail libraries
+
+To run Python code samples for the Retail API tutorial, you need to set up your virtual environment.
+
+1. Run the following commands in a Terminal to create an isolated Python environment:
+    ```bash
+    pip install virtualenv
+    virtualenv myenv
+    source myenv/bin/activate
+    ```
+1. Next, install Google packages:
+    ```bash
+    pip install google
+    pip install google-cloud-retail
+    pip install google.cloud.storage
+    pip install google.cloud.bigquery
+
+    ```
+
+## Clone the Retail code samples
+
+This step is required if this is the first Retail API Tutorial you run.
+Otherwise, you can skip it.
+
+Clone the Git repository with all the code samples to learn the Retail features and check them in action.
+
+<!-- TODO(ianan): change the repository link -->
+1. Run the following command in the Terminal:
+    ```bash
+    git clone https://github.com/t-karasova/grs-samples-python.git
+    ```
+
+    The code samples for each of the Retail services are stored in different directories.
+
+1. Go to the ```grs-samples-python``` directory. It's our starting point to run more commands.
+    ```bash
+    cd grs-samples-python
+    ```
+
+## Import catalog data
+
+This step is required if this is the first Retail API Tutorial you run.
+Otherwise, you can skip it.
+
+### Upload catalog data to Cloud Storage
+
+There is a JSON file with valid products prepared in the `product` directory:
+`product/resources/products.json`.
+
+Another file, `product/resources/products_some_invalid.json`, contains both valid and invalid products, and you will use it to check the error handling.
+
+In your own project, create a Cloud Storage bucket and put the JSON file there.
+The bucket name must be unique. For convenience, you can name it `<YOUR_PROJECT_ID>_<TIMESTAMP>`.
+
+1. To create the bucket and upload the JSON file, run the following command in the Terminal:
+
+    ```bash
+    python product/setup/create_gcs_bucket.py
+    ```
+
+    Now you can see the bucket is created in the [Cloud Storage](https://console.cloud.google.com/storage/browser), and the files are uploaded.
+
+1. The name of the created Retail Search bucket is printed in the Terminal. Copy the name and set it as the environment variable `BUCKET_NAME`:
+
+    ```bash
+    export BUCKET_NAME=<YOUR_BUCKET_NAME>
+    ```
+
+### Import products to the Retail Catalog
+
+To import the prepared products to a catalog, run the following command in the Terminal:
+
+```bash
+python product/import_products_gcs.py
+```
+
+## Run your code sample
+
+Run the sample in a terminal with the following command:
+```bash
+python search/search_with_boost_spec.py
+```