Verbindung zu MySQL herstellen

02.06.2024

Adrachin:

Ich habe auf Google Cloud Service eine Datenbank erstellt.

Name der Datenbank:
gpt-data
Format MySQL

Eine Client ID ist vorhanden:
948466214002-cbq0beo6jv9hlorqkao3cnkkhh387bng.apps.googleusercontent.com

Wie stelle ich die Verbindung her?

LiquidGPT:

Um eine Verbindung zu Ihrer MySQL-Datenbank auf Google Cloud Service herzustellen, können Sie das Google Cloud SQL API verwenden. Hier ist eine Beispiel-OpenAPI-3.0-Spezifikation für die Verbindung zu einer MySQL-Datenbank:

OpenAPI 3.0 Specification

openapi: 3.0.0
info:
  title: Google Cloud SQL API
  description: API for connecting to and managing Google Cloud SQL databases.
  version: 1.0.0
servers:
  - url: https://www.googleapis.com/sql/v1beta4
    description: Google Cloud SQL API server
paths:
  /projects/{project}/instances/{instance}/connect:
    get:
      operationId: getConnectInfo
      summary: Get connection information for a Cloud SQL instance.
      parameters:
        - name: project
          in: path
          required: true
          description: The ID of the project that contains the instance.
          schema:
            type: string
        - name: instance
          in: path
          required: true
          description: The ID of the Cloud SQL instance.
          schema:
            type: string
      responses:
        '200':
          description: Successfully retrieved connection information.
          content:
            application/json:
              schema:
                type: object
                properties:
                  ipAddresses:
                    type: array
                    items:
                      type: object
                      properties:
                        type:
                          type: string
                        ipAddress:
                          type: string
                  serverCaCert:
                    type: object
                    properties:
                      instance:
                        type: string
                      cert:
                        type: string
                      createTime:
                        type: string
                      commonName:
                        type: string
                      expirationTime:
                        type: string
                  instance:
                    type: string
                  databaseVersion:
                    type: string
                  connectionName:
                    type: string

Erklärung

Server: Der Server-URL ist die Basis-URL für das Google Cloud SQL API.
Pfad: Der Pfad /projects/{project}/instances/{instance}/connect gibt die Verbindungsinformationen für eine bestimmte Cloud SQL-Instanz zurück.
Parameter:
- project: Die ID des Projekts, das die Instanz enthält.
- instance: Die ID der Cloud SQL-Instanz.
Antworten: Die Antwort enthält die Verbindungsinformationen wie IP-Adressen und das Server-Zertifikat.

Schritte zur Verbindung:

OAuth 2.0 Authentifizierung: Stellen Sie sicher, dass Sie ein OAuth 2.0 Access Token erhalten haben, indem Sie die Client ID verwenden.
API-Aufruf: Verwenden Sie das Access Token, um die API aufzurufen und die Verbindungsinformationen zu erhalten.
MySQL Client: Verwenden Sie die Verbindungsinformationen (IP-Adresse, Benutzername, Passwort) in Ihrem MySQL-Client, um eine Verbindung zur Datenbank herzustellen.

Hier ist ein Beispiel für einen Curl-Befehl, um die Verbindungsinformationen abzurufen:

curl -H "Authorization: Bearer YOUR_ACCESS_TOKEN" \
  "https://www.googleapis.com/sql/v1beta4/projects/YOUR_PROJECT_ID/instances/YOUR_INSTANCE_ID/connect"

Ersetzen Sie YOUR_ACCESS_TOKEN, YOUR_PROJECT_ID und YOUR_INSTANCE_ID durch Ihre tatsächlichen Werte.

Zusätzliche Ressourcen

Adrachin:

Hier die Ausgabe eines Verbindungsversuches:

Call the www.googleapis.com API with the getConnectInfo operation
GPT
[debug] Calling HTTP endpoint
[debug] Calling HTTP endpoint
[debug] Response received
Fehler beim Gespräch mit
It seems there was an error when attempting to retrieve the connection information from the Google Cloud SQL API. The specific error was a “404 Not Found,” indicating that the requested URL was not found on the server.

To proceed, please ensure that the project ID and instance ID provided are correct. If you need to, I can help you verify or update these details. Let me know how you would like to proceed!

LiquidGPT:

Um sicherzustellen, dass die richtigen Projekt- und Instanz-IDs verwendet werden und dass die API korrekt aufgerufen wird, sollten wir die folgenden Punkte überprüfen:

Projekt-ID und Instanz-ID: Vergewissern Sie sich, dass Sie die korrekten IDs verwenden.
Aktivierung der API: Stellen Sie sicher, dass die Google Cloud SQL API für Ihr Projekt aktiviert ist.
Berechtigungen: Stellen Sie sicher, dass die Berechtigungen korrekt sind und das verwendete Token die richtigen Zugriffsrechte hat.

Beispiel für eine detailliertere OpenAPI-Spezifikation

Hier ist eine detailliertere OpenAPI-Spezifikation, die auch mögliche Fehlercodes abdeckt:

openapi: 3.0.0
info:
  title: Google Cloud SQL API
  description: API for connecting to and managing Google Cloud SQL databases.
  version: 1.0.0
servers:
  - url: https://www.googleapis.com/sql/v1beta4
    description: Google Cloud SQL API server
paths:
  /projects/{project}/instances/{instance}/connect:
    get:
      operationId: getConnectInfo
      summary: Get connection information for a Cloud SQL instance.
      parameters:
        - name: project
          in: path
          required: true
          description: The ID of the project that contains the instance.
          schema:
            type: string
        - name: instance
          in: path
          required: true
          description: The ID of the Cloud SQL instance.
          schema:
            type: string
      responses:
        '200':
          description: Successfully retrieved connection information.
          content:
            application/json:
              schema:
                type: object
                properties:
                  ipAddresses:
                    type: array
                    items:
                      type: object
                      properties:
                        type:
                          type: string
                        ipAddress:
                          type: string
                  serverCaCert:
                    type: object
                    properties:
                      instance:
                        type: string
                      cert:
                        type: string
                      createTime:
                        type: string
                      commonName:
                        type: string
                      expirationTime:
                        type: string
                  instance:
                    type: string
                  databaseVersion:
                    type: string
                  connectionName:
                    type: string
        '404':
          description: Not Found - The specified project or instance was not found.
        '403':
          description: Forbidden - The caller does not have permission to access the specified project or instance.
        '401':
          description: Unauthorized - The request does not have valid authentication credentials.

Schritte zur Überprüfung und Fehlerbehebung

Überprüfen Sie die Projekt- und Instanz-IDs:
- Stellen Sie sicher, dass Sie die korrekten IDs verwenden.
- Die Projekt-ID finden Sie in der Google Cloud Console unter “IAM & Admin” > “Settings”.
- Die Instanz-ID finden Sie in der Google Cloud Console unter “SQL” > “Ihre Instanz”.
Aktivieren Sie die Google Cloud SQL API:
- Navigieren Sie zur Google Cloud Console.
- Gehen Sie zu “APIs & Services” > “Library”.
- Suchen Sie nach “Cloud SQL Admin API” und stellen Sie sicher, dass sie aktiviert ist.
Überprüfen Sie die Berechtigungen:
- Stellen Sie sicher, dass das verwendete Service-Konto oder der Benutzer die notwendigen Berechtigungen hat, um auf die SQL-Instanz zuzugreifen.
- Zu den erforderlichen Berechtigungen gehören roles/cloudsql.admin oder roles/cloudsql.client.
API-Aufruf überprüfen:
- Stellen Sie sicher, dass der API-Aufruf korrekt ist und dass Sie ein gültiges OAuth 2.0 Access Token verwenden.

Hier ist ein Beispiel für den korrekten Curl-Befehl:

curl -H "Authorization: Bearer YOUR_ACCESS_TOKEN" \
  "https://www.googleapis.com/sql/v1beta4/projects/YOUR_PROJECT_ID/instances/YOUR_INSTANCE_ID/connect"

Ersetzen Sie YOUR_ACCESS_TOKEN, YOUR_PROJECT_ID und YOUR_INSTANCE_ID durch Ihre tatsächlichen Werte.

Beispiel-Curl-Befehl

curl -H "Authorization: Bearer ya29.A0ARrdaM...your-access-token..." \
  "https://www.googleapis.com/sql/v1beta4/projects/my-gcp-project/instances/my-sql-instance/connect"

Weitere Hilfe

Falls weiterhin Probleme auftreten, können Sie die detaillierten Logs in der Google Cloud Console einsehen oder den Google Cloud Support kontaktieren.

Adrachin:

Wo genau findet die sich im Code?

LiquidGPT:

Die Projekt-ID finden Sie in der Google Cloud Console. Hier ist eine Anleitung, wie Sie diese finden:

Schritt-für-Schritt-Anleitung zum Finden der Projekt-ID

Gehen Sie zur Google Cloud Console:
- Öffnen Sie Ihren Webbrowser und gehen Sie zur Google Cloud Console unter console.cloud.google.com.
Projektübersicht anzeigen:
- Oben in der Navigationsleiste sehen Sie ein Dropdown-Menü mit dem Namen Ihres aktuellen Projekts.
- Klicken Sie auf das Dropdown-Menü, um die Projektübersicht zu öffnen.
Projekt auswählen:
- In der Projektübersicht sehen Sie eine Liste aller Projekte, die Ihrem Konto zugeordnet sind.
- Wählen Sie das Projekt aus, für das Sie die Projekt-ID benötigen.
Projekt-ID finden:
- Nachdem Sie das Projekt ausgewählt haben, wird die Projekt-ID im Dashboard angezeigt.
- Alternativ finden Sie die Projekt-ID auch unter “IAM & Admin” > “Settings”.

Beispiel-Curl-Befehl mit Projekt-ID und Instanz-ID

Hier ist ein Beispiel, wie Sie die Projekt-ID und die Instanz-ID im Curl-Befehl verwenden können:

curl -H "Authorization: Bearer YOUR_ACCESS_TOKEN" \
  "https://www.googleapis.com/sql/v1beta4/projects/YOUR_PROJECT_ID/instances/YOUR_INSTANCE_ID/connect"

Ersetzen Sie YOUR_ACCESS_TOKEN, YOUR_PROJECT_ID und YOUR_INSTANCE_ID durch Ihre tatsächlichen Werte.

Beispiel-OpenAPI-Spezifikation mit Platzhaltern für die IDs

openapi: 3.0.0
info:
  title: Google Cloud SQL API
  description: API for connecting to and managing Google Cloud SQL databases.
  version: 1.0.0
servers:
  - url: https://www.googleapis.com/sql/v1beta4
    description: Google Cloud SQL API server
paths:
  /projects/{project}/instances/{instance}/connect:
    get:
      operationId: getConnectInfo
      summary: Get connection information for a Cloud SQL instance.
      parameters:
        - name: project
          in: path
          required: true
          description: The ID of the project that contains the instance.
          schema:
            type: string
        - name: instance
          in: path
          required: true
          description: The ID of the Cloud SQL instance.
          schema:
            type: string
      responses:
        '200':
          description: Successfully retrieved connection information.
          content:
            application/json:
              schema:
                type: object
                properties:
                  ipAddresses:
                    type: array
                    items:
                      type: object
                      properties:
                        type:
                          type: string
                        ipAddress:
                          type: string
                  serverCaCert:
                    type: object
                    properties:
                      instance:
                        type: string
                      cert:
                        type: string
                      createTime:
                        type: string
                      commonName:
                        type: string
                      expirationTime:
                        type: string
                  instance:
                    type: string
                  databaseVersion:
                    type: string
                  connectionName:
                    type: string
        '404':
          description: Not Found - The specified project or instance was not found.
        '403':
          description: Forbidden - The caller does not have permission to access the specified project or instance.
        '401':
          description: Unauthorized - The request does not have valid authentication credentials.

Ersetzen Sie {project} und {instance} durch Ihre tatsächlichen Werte, um die korrekten Verbindungsinformationen abzurufen.

Adrachin:

Das ist keine Antwort auf meine Frage. Die Project ID:

gpt-data-425207

Wo im Code muss die eingetragen werden?

LiquidGPT:

Entschuldigung für das Missverständnis. Die Projekt-ID und die Instanz-ID müssen in der URL des API-Aufrufs eingetragen werden. Hier ist ein Beispiel, wie Sie dies in einem Curl-Befehl und in der OpenAPI-Spezifikation machen können.

Beispiel-Curl-Befehl

Ersetzen Sie YOUR_ACCESS_TOKEN, YOUR_PROJECT_ID, und YOUR_INSTANCE_ID durch Ihre tatsächlichen Werte:

curl -H "Authorization: Bearer YOUR_ACCESS_TOKEN" \
  "https://www.googleapis.com/sql/v1beta4/projects/gpt-data-425207/instances/YOUR_INSTANCE_ID/connect"

OpenAPI 3.0-Spezifikation

Ersetzen Sie {project} durch gpt-data-425207 und {instance} durch Ihre tatsächliche Instanz-ID im Pfad. Hier ist die aktualisierte OpenAPI-Spezifikation:

openapi: 3.0.0
info:
  title: Google Cloud SQL API
  description: API for connecting to and managing Google Cloud SQL databases.
  version: 1.0.0
servers:
  - url: https://www.googleapis.com/sql/v1beta4
    description: Google Cloud SQL API server
paths:
  /projects/gpt-data-425207/instances/{instance}/connect:
    get:
      operationId: getConnectInfo
      summary: Get connection information for a Cloud SQL instance.
      parameters:
        - name: instance
          in: path
          required: true
          description: The ID of the Cloud SQL instance.
          schema:
            type: string
      responses:
        '200':
          description: Successfully retrieved connection information.
          content:
            application/json:
              schema:
                type: object
                properties:
                  ipAddresses:
                    type: array
                    items:
                      type: object
                      properties:
                        type:
                          type: string
                        ipAddress:
                          type: string
                  serverCaCert:
                    type: object
                    properties:
                      instance:
                        type: string
                      cert:
                        type: string
                      createTime:
                        type: string
                      commonName:
                        type: string
                      expirationTime:
                        type: string
                  instance:
                    type: string
                  databaseVersion:
                    type: string
                  connectionName:
                    type: string
        '404':
          description: Not Found - The specified project or instance was not found.
        '403':
          description: Forbidden - The caller does not have permission to access the specified project or instance.
        '401':
          description: Unauthorized - The request does not have valid authentication credentials.

Stellen Sie sicher, dass Sie {instance} durch die tatsächliche Instanz-ID Ihrer Cloud SQL-Datenbank ersetzen.

Zusammengefasst:

Projekt-ID (gpt-data-425207) wird im Pfad /projects/{project}/ durch /projects/gpt-data-425207/ ersetzt.
Instanz-ID ({instance}) muss durch Ihre tatsächliche Instanz-ID ersetzt werden.

Beispiel für die Curl-URL, wenn Ihre Instanz-ID my-sql-instance lautet:

curl -H "Authorization: Bearer YOUR_ACCESS_TOKEN" \
  "https://www.googleapis.com/sql/v1beta4/projects/gpt-data-425207/instances/my-sql-instance/connect"

Adrachin:

Die hier?

gpt-data-425207:us-central1:gpt-data

LiquidGPT:

Verstanden, Sie möchten also die vollständige Instanz-ID verwenden, die in diesem Format vorliegt: gpt-data-425207:us-central1:gpt-data. Diese vollständige Instanz-ID wird benötigt, um die richtige URL für den API-Aufruf zu erstellen.

Hier ist die angepasste OpenAPI-Spezifikation und der Beispiel-Curl-Befehl mit der vollständigen Instanz-ID:

Beispiel-Curl-Befehl

Ersetzen Sie YOUR_ACCESS_TOKEN durch Ihr tatsächliches Zugriffstoken:

curl -H "Authorization: Bearer YOUR_ACCESS_TOKEN" \
  "https://www.googleapis.com/sql/v1beta4/projects/gpt-data-425207/instances/us-central1:gpt-data/connect"

OpenAPI 3.0-Spezifikation

Hier ist die angepasste OpenAPI-Spezifikation mit der vollständigen Instanz-ID im Pfad:

openapi: 3.0.0
info:
  title: Google Cloud SQL API
  description: API for connecting to and managing Google Cloud SQL databases.
  version: 1.0.0
servers:
  - url: https://www.googleapis.com/sql/v1beta4
    description: Google Cloud SQL API server
paths:
  /projects/gpt-data-425207/instances/us-central1:gpt-data/connect:
    get:
      operationId: getConnectInfo
      summary: Get connection information for a Cloud SQL instance.
      parameters:
        - name: instance
          in: path
          required: true
          description: The ID of the Cloud SQL instance.
          schema:
            type: string
      responses:
        '200':
          description: Successfully retrieved connection information.
          content:
            application/json:
              schema:
                type: object
                properties:
                  ipAddresses:
                    type: array
                    items:
                      type: object
                      properties:
                        type:
                          type: string
                        ipAddress:
                          type: string
                  serverCaCert:
                    type: object
                    properties:
                      instance:
                        type: string
                      cert:
                        type: string
                      createTime:
                        type: string
                      commonName:
                        type: string
                      expirationTime:
                        type: string
                  instance:
                    type: string
                  databaseVersion:
                    type: string
                  connectionName:
                    type: string
        '404':
          description: Not Found - The specified project or instance was not found.
        '403':
          description: Forbidden - The caller does not have permission to access the specified project or instance.
        '401':
          description: Unauthorized - The request does not have valid authentication credentials.

Zusammengefasst:

Projekt-ID: gpt-data-425207
Instanz-ID: us-central1:gpt-data

Beispiel für die vollständige URL, wenn Ihre Instanz-ID lautet: us-central1:gpt-data:

curl -H "Authorization: Bearer YOUR_ACCESS_TOKEN" \
  "https://www.googleapis.com/sql/v1beta4/projects/gpt-data-425207/instances/us-central1:gpt-data/connect"

Stellen Sie sicher, dass Ihr Zugriffstoken (YOUR_ACCESS_TOKEN) gültig und aktuell ist. Verwenden Sie die Google Cloud Console oder die Google Cloud SDK (gcloud auth application-default login), um ein gültiges Zugriffstoken zu erhalten.

Adrachin:

Langsam verstehe ich das nicht mehr. Die notwendigen Daten sind vorhanden und eingetragen. Verwende ich den Code in den Einstellungen “Action hinzufügen” und verwende den Button “Test” ergibt sich folgende Ausgabe:

It seems you would like to call an API using a specific operation. However, I do not have the capability to directly call external APIs or perform API operations. I can guide you on how to perform this action using a programming language like Python. Here’s a basic outline of how you might use the Google APIs with Python:

Set Up Your Environment:

Install the Google API Client Library for Python using pip:
sh
Code kopieren
pip install —upgrade google-api-python-client
Create a Project and Enable API:

Go to the Google Cloud Console.
Create a new project or select an existing one.
Enable the relevant API for your project (e.g., Google Drive API, Google Sheets API).
Set Up Authentication:

Create credentials (OAuth 2.0 Client ID or Service Account) and download the JSON key file.
Set the environment variable to point to the downloaded JSON key file:
sh
Code kopieren
export GOOGLE_APPLICATION_CREDENTIALS=”/path/to/your/credentials.json”
Write the Python Script:

Here’s an example script that makes a simple API call:

python
Code kopieren
from googleapiclient.discovery import build
from google.oauth2 import service_account

Path to your service account key file

SERVICE_ACCOUNT_FILE = ‘/path/to/your/credentials.json’

Scopes required for the API

SCOPES = [‘https://www.googleapis.com/auth/cloud-platform’]

Create credentials

credentials = service_account.Credentials.from_service_account_file(
SERVICE_ACCOUNT_FILE, scopes=SCOPES)

Build the service

service = build(‘api_name’, ‘api_version’, credentials=credentials)

Example: Get Connect Info (replace ‘api_name’ and ‘api_version’ with the specific API you’re using)

request = service.getConnectInfo()
response = request.execute()

print(response)
Replace ‘api_name’ and ‘api_version’ with the appropriate values for the API you want to call. For example, if you are calling the Google Drive API, you would use ‘drive’ and ‘v3’.

This script sets up authentication using a service account and makes a call to the getConnectInfo method. You will need to adjust the script according to the specific API and operation you are trying to use.

If you provide more details about the specific API and operation, I can tailor the example more closely to your needs.

Wo liegt der Fehler? Ist es überhaupt möglich eine Customer Action zu verwenden um sich mit einer Google Cloud Datenbank zu verbinden?

LiquidGPT:

Um die Verbindung zu Ihrer Google Cloud SQL-Datenbank mittels einer Customer Action zu realisieren, müssen wir sicherstellen, dass wir die richtigen Schritte befolgen und die notwendigen API-Operationen korrekt ausführen. Hier ist ein Beispiel, wie Sie dies mit einer Custom Action im OpenAPI-Format machen können. Ich werde die Spezifikation so gestalten, dass sie die Verbindung zu Ihrer MySQL-Datenbank ermöglicht.

Schritte zur Implementierung einer Customer Action

Stellen Sie sicher, dass die Google Cloud SQL API aktiviert ist.
Erstellen Sie die JSON-Credentials für die Authentifizierung.
Erstellen Sie eine Custom Action, die die Verbindung zu Ihrer MySQL-Datenbank herstellt.

Beispiel für eine OpenAPI-Spezifikation

Hier ist eine vollständige OpenAPI 3.0-Spezifikation, die die Verbindung zu Ihrer Google Cloud SQL-Datenbank ermöglicht. Diese Spezifikation verwendet die richtige Projekt-ID und Instanz-ID:

openapi: 3.0.0
info:
  title: Google Cloud SQL API
  description: API for connecting to and managing Google Cloud SQL databases.
  version: 1.0.0
servers:
  - url: https://www.googleapis.com/sql/v1beta4
    description: Google Cloud SQL API server
paths:
  /projects/gpt-data-425207/instances/us-central1:gpt-data/connect:
    get:
      operationId: getConnectInfo
      summary: Get connection information for a Cloud SQL instance.
      parameters:
        - name: project
          in: path
          required: true
          description: The ID of the project that contains the instance.
          schema:
            type: string
          example: gpt-data-425207
        - name: instance
          in: path
          required: true
          description: The ID of the Cloud SQL instance.
          schema:
            type: string
          example: us-central1:gpt-data
      responses:
        '200':
          description: Successfully retrieved connection information.
          content:
            application/json:
              schema:
                type: object
                properties:
                  ipAddresses:
                    type: array
                    items:
                      type: object
                      properties:
                        type:
                          type: string
                        ipAddress:
                          type: string
                  serverCaCert:
                    type: object
                    properties:
                      instance:
                        type: string
                      cert:
                        type: string
                      createTime:
                        type: string
                      commonName:
                        type: string
                      expirationTime:
                        type: string
                  instance:
                    type: string
                  databaseVersion:
                    type: string
                  connectionName:
                    type: string
        '404':
          description: Not Found - The specified project or instance was not found.
        '403':
          description: Forbidden - The caller does not have permission to access the specified project or instance.
        '401':
          description: Unauthorized - The request does not have valid authentication credentials.

Verwendung der OpenAPI-Spezifikation in einer Custom Action

Fügen Sie die OpenAPI-Spezifikation zur Custom Action hinzu.
Verwenden Sie die richtige Authentifizierungsmethode (OAuth 2.0).

Hier ist ein Beispiel für ein Python-Skript, das die Verbindung herstellt und die notwendigen Informationen abruft:

from google.oauth2 import service_account
from googleapiclient.discovery import build

# Pfad zu Ihrem Service-Account-Schlüssel
SERVICE_ACCOUNT_FILE = '/path/to/your/credentials.json'
SCOPES = ['https://www.googleapis.com/auth/cloud-platform']

# Erstellen Sie die Anmeldeinformationen
credentials = service_account.Credentials.from_service_account_file(
    SERVICE_ACCOUNT_FILE, scopes=SCOPES)

# Erstellen Sie den Dienst
service = build('sqladmin', 'v1beta4', credentials=credentials)

# Beispiel: Abrufen der Verbindungsinformationen
project_id = 'gpt-data-425207'
instance_id = 'us-central1:gpt-data'

request = service.instances().get(project=project_id, instance=instance_id)
response = request.execute()

print(response)

Zusammenfassung

Aktivieren Sie die Cloud SQL API in Ihrem Google Cloud Projekt.
Stellen Sie sicher, dass Sie ein gültiges OAuth 2.0 Zugriffstoken haben.
Verwenden Sie die angepasste OpenAPI-Spezifikation, um die Verbindungsinformationen abzurufen.

Mit diesen Schritten sollten Sie in der Lage sein, eine Custom Action zu erstellen, die die Verbindung zu Ihrer Google Cloud SQL-Datenbank herstellt. Stellen Sie sicher, dass alle Parameter korrekt konfiguriert sind und dass die erforderlichen Berechtigungen vorhanden sind.

Adrachin:

I am still struggling with this one. I asked Google gemini about the current action script. Here is the answer:

Analysis of the OpenAPI Specification for Cloud SQL Connection
The provided OpenAPI specification defines an API for connecting to and managing Google Cloud SQL databases. Here’s an analysis of its key components:

Servers:
The API server is located at https://www.googleapis.com/sql/v1beta4 . This indicates that the API is using the v1beta4 version of the Cloud SQL API.
Paths:
The path /projects/{project}/instances/{instance}/connect:/connect defines an endpoint for retrieving connection information for a specific Cloud SQL instance.
The get operation on this path allows users to request connection details.
Parameters:
The project and instance parameters are required to identify the specific Cloud SQL instance for which connection information is needed.
Responses:
The 200 response indicates successful retrieval of connection information.
The response body contains a JSON object with the following properties:
ipAddresses : An array of IP addresses that can be used to connect to the instance.
serverCaCert : The server certificate used for SSL/TLS connections.
instance : The name of the Cloud SQL instance.
databaseVersion : The database version of the instance.
connectionName : The name of the connection.
Usability:
This OpenAPI specification provides a clear and concise way to retrieve connection information for Cloud SQL instances.
It can be used by developers to build applications that connect to and interact with Cloud SQL databases.
The specification is well-structured and follows OpenAPI standards, making it easy to understand and implement.
Overall, this OpenAPI specification is a usable way to connect to the Google Cloud SQL service database. It provides the necessary information for developers to establish secure and reliable connections to their Cloud SQL instances.
Additional Notes:
The specification uses the v1beta4 version of the Cloud SQL API, which may not be the latest version. It’s recommended to check for newer versions and update the specification accordingly.
The specification does not include information about authentication or authorization. Developers will need to implement appropriate mechanisms to ensure secure access to the API.
The specification focuses on retrieving connection information. It does not include operations for managing or interacting with the database itself. Developers will need to use the Cloud SQL client libraries or other tools for these tasks.

In Theorie it should be possible I guess.

Please tell me what informations are needed to get it up and running.

LiquidGPT:

To get your setup working and connect to your Google Cloud SQL database using an OpenAPI specification and a custom action, we’ll need to ensure that all necessary steps for authentication, endpoint configuration, and parameter specification are correctly implemented. Here’s a step-by-step guide to ensure everything is properly set up:

Prerequisites

Google Cloud Project: Ensure you have a Google Cloud project with the Cloud SQL API enabled.
Service Account: Create a service account with the necessary permissions to access your Cloud SQL instance.
Service Account Key: Download the JSON key file for the service account.
OAuth 2.0 Access Token: Ensure you have an OAuth 2.0 access token to authenticate your API requests.

Step 1: Ensure Cloud SQL API is Enabled

Make sure that the Cloud SQL API is enabled for your project. You can do this via the Google Cloud Console.

Step 2: Create a Service Account and Download the Key

Go to the Service Accounts page in the Cloud Console.
Click “Create Service Account”.
Provide a name and ID for the service account.
Assign the roles/cloudsql.admin role to the service account.
Click “Create Key” and download the JSON key file.

Step 3: Obtain an OAuth 2.0 Access Token

Use the downloaded service account JSON key file to obtain an OAuth 2.0 access token. You can do this using the gcloud command-line tool:

gcloud auth activate-service-account --key-file=path/to/your-service-account-file.json
gcloud auth print-access-token

Step 4: Define Your OpenAPI Specification

Here’s an updated OpenAPI 3.0 specification tailored to your specific project and instance:

openapi: 3.0.0
info:
  title: Google Cloud SQL API
  description: API for connecting to and managing Google Cloud SQL databases.
  version: 1.0.0
servers:
  - url: https://www.googleapis.com/sql/v1beta4
    description: Google Cloud SQL API server
paths:
  /projects/gpt-data-425207/instances/us-central1:gpt-data/connect:
    get:
      operationId: getConnectInfo
      summary: Get connection information for a Cloud SQL instance.
      parameters:
        - name: project
          in: path
          required: true
          description: The ID of the project that contains the instance.
          schema:
            type: string
          example: gpt-data-425207
        - name: instance
          in: path
          required: true
          description: The ID of the Cloud SQL instance.
          schema:
            type: string
          example: us-central1:gpt-data
      responses:
        '200':
          description: Successfully retrieved connection information.
          content:
            application/json:
              schema:
                type: object
                properties:
                  ipAddresses:
                    type: array
                    items:
                      type: object
                      properties:
                        type:
                          type: string
                        ipAddress:
                          type: string
                  serverCaCert:
                    type: object
                    properties:
                      instance:
                        type: string
                      cert:
                        type: string
                      createTime:
                        type: string
                      commonName:
                        type: string
                      expirationTime:
                        type: string
                  instance:
                    type: string
                  databaseVersion:
                    type: string
                  connectionName:
                    type: string
        '404':
          description: Not Found - The specified project or instance was not found.
        '403':
          description: Forbidden - The caller does not have permission to access the specified project or instance.
        '401':
          description: Unauthorized - The request does not have valid authentication credentials.

Step 5: Implement the Custom Action

Here is an example of how to implement the custom action in Python to retrieve the connection information:

from google.oauth2 import service_account
from googleapiclient.discovery import build
import json

# Path to your service account key file
SERVICE_ACCOUNT_FILE = 'path/to/your-service-account-file.json'
SCOPES = ['https://www.googleapis.com/auth/cloud-platform']

# Create credentials
credentials = service_account.Credentials.from_service_account_file(
    SERVICE_ACCOUNT_FILE, scopes=SCOPES)

# Build the service
service = build('sqladmin', 'v1beta4', credentials=credentials)

# Project and instance ID
project_id = 'gpt-data-425207'
instance_id = 'us-central1:gpt-data'

# Request connection information
request = service.instances().get(project=project_id, instance=instance_id)
response = request.execute()

print(json.dumps(response, indent=2))

Summary

To ensure everything is correctly set up, follow these steps:

Enable Cloud SQL API: Make sure the API is enabled in your project.
Create Service Account: Create a service account with the necessary permissions and download the JSON key file.
Get OAuth 2.0 Access Token: Use the service account key to get an access token.
Define OpenAPI Specification: Ensure the OpenAPI spec includes the correct project and instance IDs.
Implement Custom Action: Use the example Python script to retrieve the connection information.

By following these steps, you should be able to retrieve connection information for your Google Cloud SQL instance and implement the custom action successfully. If you encounter any issues, please provide specific error messages or logs so I can assist you further.

Adrachin:

zsh: command not found: gcloud

LiquidGPT:

If you don’t have the gcloud command-line tool installed, you can install it by following these steps. The gcloud tool is part of the Google Cloud SDK.

Step 1: Install the Google Cloud SDK

Download the SDK Installer:
- For macOS:
```
curl -O https://dl.google.com/dl/cloudsdk/channels/rapid/downloads/google-cloud-sdk-XXX.tar.gz
```
- Replace XXX with the latest version number found on the Google Cloud SDK download page.
Extract the Archive:
```
tar -xvf google-cloud-sdk-XXX.tar.gz
```
Run the Installation Script:
```
./google-cloud-sdk/install.sh
```
Initialize the SDK:
```
./google-cloud-sdk/bin/gcloud init
```

Step 2: Authenticate and Configure

Authenticate with Google Cloud:
```
gcloud auth login
```
Set the Default Project:
```
gcloud config set project YOUR_PROJECT_ID
```
Replace YOUR_PROJECT_ID with gpt-data-425207.

Step 3: Activate the Service Account and Get the Access Token

Activate the Service Account:

gcloud auth activate-service-account --key-file=path/to/your-service-account-file.json

Get the Access Token:
```
gcloud auth print-access-token
```

Step 4: Use the Access Token in Your API Call

Replace YOUR_ACCESS_TOKEN in your curl command with the token obtained from the above step:

curl -H "Authorization: Bearer YOUR_ACCESS_TOKEN" \
  "https://www.googleapis.com/sql/v1beta4/projects/gpt-data-425207/instances/us-central1:gpt-data/connect"

Alternative Method: Using Python to Get the Access Token and Call the API

If you prefer not to use gcloud, you can use Python to obtain the access token and call the API.

Install Required Libraries:

pip install google-auth google-auth-oauthlib google-auth-httplib2 google-api-python-client

Python Script to Get Access Token and Call the API:

from google.oauth2 import service_account
from googleapiclient.discovery import build

# Path to your service account key file
SERVICE_ACCOUNT_FILE = 'path/to/your-service-account-file.json'
SCOPES = ['https://www.googleapis.com/auth/cloud-platform']

# Create credentials
credentials = service_account.Credentials.from_service_account_file(
    SERVICE_ACCOUNT_FILE, scopes=SCOPES)

# Build the service
service = build('sqladmin', 'v1beta4', credentials=credentials)

# Project and instance ID
project_id = 'gpt-data-425207'
instance_id = 'us-central1:gpt-data'

# Request connection information
request = service.instances().get(project=project_id, instance=instance_id)
response = request.execute()

print(response)

Replace path/to/your-service-account-file.json with the path to your downloaded service account key file.

Summary

By installing the Google Cloud SDK and using the gcloud command, you can authenticate and retrieve the necessary access token to interact with Google Cloud SQL. Alternatively, you can use Python to authenticate and make the API call directly. Ensure all the necessary dependencies are installed and the correct paths are used.

Adrachin:

Seems my virtual environment I need tp use pip is lost. Create a common for the terminal searching vor the v invormoment in this path:

/Users/Thomas

recursive

LiquidGPT:

To find and list virtual environments recursively in a directory, you can use the find command in your terminal. Assuming your virtual environments are typically located in directories named venv, env, or similar, you can search for these directories under /Users/Thomas. Here’s the command:

find /Users/Thomas -type d \( -name "venv" -o -name "env" -o -name "*.venv" -o -name "*.env" \)

This command searches for directories named venv, env, or with .venv or .env extensions within /Users/Thomas and all its subdirectories.

If you need to create a new virtual environment, you can use the following commands:

Navigate to your desired directory:
```
 cd /Users/Thomas/path/to/your/project
```
Create a new virtual environment:
```
 python3 -m venv venv
```
Activate the virtual environment:
- On macOS and Linux:
```
  source venv/bin/activate
```
- On Windows:
```
  venv\Scripts\activate
```

Example Steps to Find and Use an Existing Virtual Environment

Search for existing virtual environments:

 find /Users/Thomas -type d \( -name "venv" -o -name "env" -o -name "*.venv" -o -name "*.env" \)

Navigate to the directory containing the found virtual environment:
```
 cd /Users/Thomas/path/to/found/virtual/environment
```
Activate the virtual environment:
- On macOS and Linux:
```
  source venv/bin/activate
```
- On Windows:
```
  venv\Scripts\activate
```

Example of Creating and Using a New Virtual Environment

Navigate to your project directory:
```
 cd /Users/Thomas/my_new_project
```
Create a new virtual environment:
```
 python3 -m venv venv
```
Activate the virtual environment:
- On macOS and Linux:
```
  source venv/bin/activate
```
- On Windows:
```
  venv\Scripts\activate
```

Install required packages:

 pip install google-auth google-auth-oauthlib google-auth-httplib2 google-api-python-client

This should help you find existing virtual environments or set up a new one as needed.

Adrachin:

File “/Users/thomas/_python/venv/lib/python3.12/site-packages/googleapiclient/http.py”, line 938, in execute
raise HttpError(resp, content, uri=self.uri)
googleapiclient.errors.HttpError: <HttpError 403 when requesting https://sqladmin.googleapis.com/sql/v1beta4/projects/gpt-data-425207/instances/us-central1%3Agpt-data?alt=json returned “Cloud SQL Admin API has not been used in project 948466214002 before or it is disabled. Enable it by visiting https://console.developers.google.com/apis/api/sqladmin.googleapis.com/overview?project=948466214002 then retry. If you enabled this API recently, wait a few minutes for the action to propagate to our systems and retry.”. Details: “[{‘message’: ‘Cloud SQL Admin API has not been used in project 948466214002 before or it is disabled. Enable it by visiting https://console.developers.google.com/apis/api/sqladmin.googleapis.com/overview?project=948466214002 then retry. If you enabled this API recently, wait a few minutes for the action to propagate to our systems and retry.’, ‘domain’: ‘usageLimits’, ‘reason’: ‘accessNotConfigured’, ‘extendedHelp’: ‘https://console.developers.google.com’}]”>
(venv) ➜ _python

LiquidGPT:

The error message indicates that the Cloud SQL Admin API has not been enabled for your project 948466214002. You need to enable this API to proceed.

Step-by-Step Guide to Enable the Cloud SQL Admin API

Visit the Google Cloud Console API Library:
Google Cloud Console API Library
Select Your Project:
If you are not already prompted, ensure you select the correct project (948466214002) from the project selector dropdown at the top of the page.
Search for the Cloud SQL Admin API:
In the search bar, type Cloud SQL Admin API and select it from the list of results.
Enable the API:
Click the Enable button.

Here is a direct link that might take you to the API enablement page for your specific project:
Enable Cloud SQL Admin API for Project 948466214002

Retry Your Python Script

After enabling the API, wait a few minutes for the change to propagate through Google’s systems. Then, retry running your Python script.

Example of the Python Script for Context

Here is the example script again for context:

from google.oauth2 import service_account
from googleapiclient.discovery import build

# Path to your service account key file
SERVICE_ACCOUNT_FILE = 'path/to/your-service-account-file.json'
SCOPES = ['https://www.googleapis.com/auth/cloud-platform']

# Create credentials
credentials = service_account.Credentials.from_service_account_file(
    SERVICE_ACCOUNT_FILE, scopes=SCOPES)

# Build the service
service = build('sqladmin', 'v1beta4', credentials=credentials)

# Project and instance ID
project_id = 'gpt-data-425207'
instance_id = 'us-central1:gpt-data'

# Request connection information
request = service.instances().get(project=project_id, instance=instance_id)
response = request.execute()

print(response)

Additional Steps

Verify Permissions:
Ensure the service account has the necessary permissions. The service account should have at least the roles/cloudsql.admin role.
Check IAM Policies:
Go to the IAM & Admin section in the Google Cloud Console and verify that your service account is listed with the appropriate permissions.
Wait for Propagation:
Sometimes, it can take a few minutes for the new API enabling to propagate through Google Cloud’s systems. If you still encounter issues, give it a few more minutes and try again.

After following these steps, you should be able to run your script and retrieve the connection information for your Cloud SQL instance.

LiquidGPT:

The error message indicates that the Cloud SQL Admin API is either not enabled or has not been used before in your project. To resolve this issue, you need to enable the Cloud SQL Admin API for your Google Cloud project. Here’s how you can do it:

Step-by-Step Guide to Enable the Cloud SQL Admin API

Go to the Google Cloud Console:

Open your web browser and navigate to the Google Cloud Console.
Select Your Project:

Ensure that your project 948466214002 (or gpt-data-425207) is selected in the project selector at the top of the page.
Enable the API:

Click on the “Enable” button to enable the Cloud SQL Admin API for your project. If the API is already enabled, you will see a “Manage” button instead.

Wait for Propagation

After enabling the API, wait a few minutes for the changes to propagate across Google’s systems.

Retry Your Request

Once the API is enabled, you can retry your request. Ensure your virtual environment is activated, and then run your Python script again to retrieve the connection information.

Example Python Script

Here’s the Python script again for reference:

from google.oauth2 import service_account
from googleapiclient.discovery import build
import json

# Path to your service account key file
SERVICE_ACCOUNT_FILE = 'path/to/your-service-account-file.json'
SCOPES = ['https://www.googleapis.com/auth/cloud-platform']

# Create credentials
credentials = service_account.Credentials.from_service_account_file(
    SERVICE_ACCOUNT_FILE, scopes=SCOPES)

# Build the service
service = build('sqladmin', 'v1beta4', credentials=credentials)

# Project and instance ID
project_id = 'gpt-data-425207'
instance_id = 'us-central1:gpt-data'

# Request connection information
request = service.instances().get(project=project_id, instance=instance_id)
response = request.execute()

print(json.dumps(response, indent=2))

Summary

Enable the Cloud SQL Admin API for your project by visiting the provided link.
Wait a few minutes for the API to be enabled and propagate.
Retry your API call using the provided Python script.

By following these steps, you should be able to retrieve the connection information for your Google Cloud SQL instance without encountering the 403 error. If you continue to face issues, ensure that your service account has the necessary permissions (roles/cloudsql.admin).

Adrachin:

I have problems to find the API enable function.

What I have:
admin-316@gpt-data-425207.iam.gserviceaccount.com admin
Cloud SQL-Administrator

Ressource

gpt-data

LiquidGPT:

To enable the Cloud SQL Admin API, follow these steps:

Step-by-Step Guide to Enable the Cloud SQL Admin API

Go to the Google Cloud Console API Library:

Open your web browser and navigate to the Google Cloud Console API Library.
Select Your Project:

Make sure your project gpt-data-425207 is selected in the project selector at the top of the page. If it’s not, click on the project selector, search for your project, and select it.
Search for Cloud SQL Admin API:

In the API Library, use the search bar at the top to search for “Cloud SQL Admin API”.
Enable the API:

Click on “Cloud SQL Admin API” from the search results. Then, click the “Enable” button on the Cloud SQL Admin API page.

Detailed Instructions with Screenshots

Step 1: Go to the Google Cloud Console API Library

Navigate to the API Library: Go to Google Cloud Console API Library.

Step 2: Select Your Project

Select Project: Ensure that gpt-data-425207 is selected.

[Bild entfernt]

Step 3: Search for Cloud SQL Admin API

Search API: Enter “Cloud SQL Admin API” in the search bar and press Enter.

[Bild entfernt]

Step 4: Enable the API

Enable API: Click on the Cloud SQL Admin API and then click the “Enable” button.

[Bild entfernt]

Retry Your Request

After enabling the API, wait a few minutes for the changes to propagate, then retry your API request using your Python script.

Example Python Script

Here’s the Python script to get the connection information:

from google.oauth2 import service_account
from googleapiclient.discovery import build
import json

# Path to your service account key file
SERVICE_ACCOUNT_FILE = 'path/to/your-service-account-file.json'
SCOPES = ['https://www.googleapis.com/auth/cloud-platform']

# Create credentials
credentials = service_account.Credentials.from_service_account_file(
    SERVICE_ACCOUNT_FILE, scopes=SCOPES)

# Build the service
service = build('sqladmin', 'v1beta4', credentials=credentials)

# Project and instance ID
project_id = 'gpt-data-425207'
instance_id = 'us-central1:gpt-data'

# Request connection information
request = service.instances().get(project=project_id, instance=instance_id)
response = request.execute()

print(json.dumps(response, indent=2))

Summary

Enable the Cloud SQL Admin API for your project in the Google Cloud Console.
Wait a few minutes for the API to propagate.
Retry your API call using the provided Python script.

By following these steps, you should be able to enable the Cloud SQL Admin API and successfully retrieve connection information for your Cloud SQL instance. If you continue to face issues, ensure that your service account has the necessary permissions (roles/cloudsql.admin).

Adrachin:

Please do not output all the code and information after the first steps:

Step 1: Go to the Google Cloud Console API Library

Navigate to the API Library: Go to Google Cloud Console API Library.
Step 2: Select Your Project

Select Project: Ensure that gpt-data-425207 is selected.

Step 3: Search for Cloud SQL Admin API

Search API: Enter “Cloud SQL Admin API” in the search bar and press Enter.

Step 4: Enable the API

Enable API: Click on the Cloud SQL Admin API and then click the “Enable” button.

I already have lots of this versions now in the prompt and need to scroll and scroll up and down and so on and it is completely a mess to sue this prompt now.

Wait until needed steps are performed by me and I give feedback that it is done and provide the result.

LiquidGPT:

Understood. Here are the steps again, in a concise format:

Step-by-Step Guide to Enable the Cloud SQL Admin API

Go to the Google Cloud Console API Library:
- Navigate to Google Cloud Console API Library.
Select Your Project:
- Ensure that gpt-data-425207 is selected in the project selector.
Search for Cloud SQL Admin API:
- Enter “Cloud SQL Admin API” in the search bar and press Enter.
Enable the API:
- Click on “Cloud SQL Admin API” from the search results.
- Click the “Enable” button on the Cloud SQL Admin API page.

Please perform these steps and let me know once you have completed them.

Adrachin:

Thanks I have done that and it was successful:

Cloud SQL Admin API
API for Cloud SQL database instance management

By Google Enterprise API
Service name
sqladmin.googleapis.com
Type
Public API
Status
Enabled

LiquidGPT:

Great! Now that the Cloud SQL Admin API is enabled, you can proceed with retrieving the connection information for your Cloud SQL instance.

Retry Your API Request

With the API enabled, you can use the following Python script to retrieve the connection information. Make sure your virtual environment is activated and the required libraries are installed.

Python Script to Retrieve Connection Information

from google.oauth2 import service_account
from googleapiclient.discovery import build
import json

# Path to your service account key file
SERVICE_ACCOUNT_FILE = 'path/to/your-service-account-file.json'
SCOPES = ['https://www.googleapis.com/auth/cloud-platform']

# Create credentials
credentials = service_account.Credentials.from_service_account_file(
    SERVICE_ACCOUNT_FILE, scopes=SCOPES)

# Build the service
service = build('sqladmin', 'v1beta4', credentials=credentials)

# Project and instance ID
project_id = 'gpt-data-425207'
instance_id = 'us-central1:gpt-data'

# Request connection information
request = service.instances().get(project=project_id, instance=instance_id)
response = request.execute()

print(json.dumps(response, indent=2))

Steps to Run the Script

Ensure your virtual environment is activated:
```
source /path/to/your/virtualenv/bin/activate
```

Install the necessary Python libraries (if not already installed):

pip install google-auth google-auth-oauthlib google-auth-httplib2 google-api-python-client

Run the Python script:
Save the script to a file, for example, get_sql_connection_info.py, and run it:
```
python get_sql_connection_info.py
```

Expected Output

If everything is set up correctly, you should see the connection information for your Cloud SQL instance printed in the terminal.

Please run the script and provide feedback on the result or any errors encountered.

Adrachin:

Use this path in the script:

/Users/thomas/Downloads/gpt-data-425207-54872e0cb8e3.json

Are there additional credentials missing or is that all?

LiquidGPT:

The path to your service account key file is all you need to specify in the script. Here is the updated script with the provided path:

from google.oauth2 import service_account
from googleapiclient.discovery import build
import json

# Path to your service account key file
SERVICE_ACCOUNT_FILE = '/Users/thomas/Downloads/gpt-data-425207-54872e0cb8e3.json'
SCOPES = ['https://www.googleapis.com/auth/cloud-platform']

# Create credentials
credentials = service_account.Credentials.from_service_account_file(
    SERVICE_ACCOUNT_FILE, scopes=SCOPES)

# Build the service
service = build('sqladmin', 'v1beta4', credentials=credentials)

# Project and instance ID
project_id = 'gpt-data-425207'
instance_id = 'us-central1:gpt-data'

# Request connection information
request = service.instances().get(project=project_id, instance=instance_id)
response = request.execute()

print(json.dumps(response, indent=2))

Steps to Run the Script

Ensure your virtual environment is activated:
```
source /path/to/your/virtualenv/bin/activate
```

Install the necessary Python libraries (if not already installed):

pip install google-auth google-auth-oauthlib google-auth-httplib2 google-api-python-client

Save the script to a file:
Save the script to a file, for example, get_sql_connection_info.py.
Run the script:
```
python get_sql_connection_info.py
```

Expected Output

If everything is set up correctly, you should see the connection information for your Cloud SQL instance printed in the terminal.

Please run the script and provide feedback on the result or any errors encountered.

Adrachin:

/Users/thomas/_python/venv/bin/python /Users/thomas/_python/MyApps/Test_Scripte/get_token.py
(venv) ➜ _python /Users/thomas/_python/venv/bin/python /Users/thomas/_python/MyApps/Test_Scripte/get_token.py
Traceback (most recent call last):
File “/Users/thomas/_python/MyApps/Test_Scripte/get_token.py”, line 21, in
response = request.execute()
^^^^^^^^^^^^^^^^^
File “/Users/thomas/_python/venv/lib/python3.12/site-packages/googleapiclient/_helpers.py”, line 130, in positional_wrapper
return wrapped(*args, *kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^
File “/Users/thomas/_python/venv/lib/python3.12/site-packages/googleapiclient/http.py”, line 938, in execute
raise HttpError(resp, content, uri=self.uri)
googleapiclient.errors.HttpError: <HttpError 403 when requesting https://sqladmin.googleapis.com/sql/v1beta4/projects/gpt-data-425207/instances/us-central1%3Agpt-data?alt=json returned “Cloud SQL Admin API has not been used in project 948466214002 before or it is disabled. Enable it by visiting https://console.developers.google.com/apis/api/sqladmin.googleapis.com/overview?project=948466214002 then retry. If you enabled this API recently, wait a few minutes for the action to propagate to our systems and retry.”. Details: “[{‘message’: ‘Cloud SQL Admin API has not been used in project 948466214002 before or it is disabled. Enable it by visiting https://console.developers.google.com/apis/api/sqladmin.googleapis.com/overview?project=948466214002 then retry. If you enabled this API recently, wait a few minutes for the action to propagate to our systems and retry.’, ‘domain’: ‘usageLimits’, ‘reason’: ‘accessNotConfigured’, ‘extendedHelp’: ‘https://console.developers.google.com’}]”>
(venv) ➜ _python /Users/thomas/_python/venv/bin/python /Users/thomas/_python/MyApps/Test_Scripte/get_token.py
Traceback (most recent call last):
File “/Users/thomas/_python/MyApps/Test_Scripte/get_token.py”, line 22, in
response = request.execute()
^^^^^^^^^^^^^^^^^
File “/Users/thomas/_python/venv/lib/python3.12/site-packages/googleapiclient/_helpers.py”, line 130, in positional_wrapper
return wrapped(args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^
File “/Users/thomas/_python/venv/lib/python3.12/site-packages/googleapiclient/http.py”, line 938, in execute
raise HttpError(resp, content, uri=self.uri)
googleapiclient.errors.HttpError: <HttpError 400 when requesting https://sqladmin.googleapis.com/sql/v1beta4/projects/gpt-data-425207/instances/us-central1%3Agpt-data?alt=json returned “Invalid request: instance name (us-central1:gpt-data).”. Details: “[{‘message’: ‘Invalid request: instance name (us-central1:gpt-data).’, ‘domain’: ‘global’, ‘reason’: ‘invalid’}]”>

LiquidGPT:

The errors indicate two issues:

403 Error (Access Not Configured): The Cloud SQL Admin API needs to be enabled for your project. You’ve confirmed that this step was already completed.
400 Error (Invalid Request: Instance Name): The format of the instance name in the request is incorrect.

Correcting the Instance Name

It looks like the instance name format should be revised. The instance name should not include the region prefix. Here is the corrected Python script:

from google.oauth2 import service_account
from googleapiclient.discovery import build
import json

# Path to your service account key file
SERVICE_ACCOUNT_FILE = '/Users/thomas/Downloads/gpt-data-425207-54872e0cb8e3.json'
SCOPES = ['https://www.googleapis.com/auth/cloud-platform']

# Create credentials
credentials = service_account.Credentials.from_service_account_file(
    SERVICE_ACCOUNT_FILE, scopes=SCOPES)

# Build the service
service = build('sqladmin', 'v1beta4', credentials=credentials)

# Project and instance ID
project_id = 'gpt-data-425207'
instance_id = 'gpt-data'  # Removing the region prefix

# Request connection information
request = service.instances().get(project=project_id, instance=instance_id)
response = request.execute()

print(json.dumps(response, indent=2))

Steps to Run the Script

Ensure your virtual environment is activated:

source /Users/thomas/_python/venv/bin/activate

Install the necessary Python libraries (if not already installed):

pip install google-auth google-auth-oauthlib google-auth-httplib2 google-api-python-client

Save the script to a file:
Save the script to a file, for example, get_sql_connection_info.py.
Run the script:
```
python get_sql_connection_info.py
```

Summary

By removing the region prefix from the instance name, the API request should be valid. If the issue persists, please provide the exact instance name as it appears in the Google Cloud Console to ensure correctness.

Adrachin:

(venv) ➜ _python /Users/thomas/_python/venv/bin/python /Users/thomas/_python/MyApps/Test_Scripte/get_token.py
{
“kind”: “sql#instance”,
“state”: “RUNNABLE”,
“databaseVersion”: “MYSQL_8_0_31”,
“settings”: {
“authorizedGaeApplications”: [],
“tier”: “db-f1-micro”,
“kind”: “sql#settings”,
“availabilityType”: “ZONAL”,
“pricingPlan”: “PER_USE”,
“replicationType”: “SYNCHRONOUS”,
“activationPolicy”: “ALWAYS”,
“ipConfiguration”: {
“authorizedNetworks”: [],
“sslMode”: “ALLOW_UNENCRYPTED_AND_ENCRYPTED”,
“ipv4Enabled”: true,
“requireSsl”: false
},
“locationPreference”: {
“zone”: “us-central1-a”,
“kind”: “sql#locationPreference”
},
“dataDiskType”: “PD_SSD”,
“maintenanceWindow”: {
“kind”: “sql#maintenanceWindow”,
“hour”: 0,
“day”: 0
},
“backupConfiguration”: {
“startTime”: “02:00”,
“kind”: “sql#backupConfiguration”,
“location”: “us”,
“backupRetentionSettings”: {
“retentionUnit”: “COUNT”,
“retainedBackups”: 7
},
“enabled”: true,
“binaryLogEnabled”: true,
“transactionLogRetentionDays”: 7,
“transactionalLogStorageState”: “CLOUD_STORAGE”
},
“insightsConfig”: {},
“edition”: “ENTERPRISE”,
“connectorEnforcement”: “NOT_REQUIRED”,
“settingsVersion”: “2”,
“storageAutoResizeLimit”: “0”,
“storageAutoResize”: true,
“dataDiskSizeGb”: “10”,
“deletionProtectionEnabled”: true
},
“etag”: “defd1780f0967a5e23b4bc34c9012c802cb19c20eec8a0f4708873aae337cd64”,
“ipAddresses”: [
{
“type”: “PRIMARY”,
“ipAddress”: “34.135.236.193”
}
],
“serverCaCert”: {
“kind”: “sql#sslCert”,
“certSerialNumber”: “0”,
“cert”: “——-BEGIN CERTIFICATE——-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\nFuNVui1v39M0PHmWjvl+B3uBDZKY5K8RelR3ruiGx17b5Z4=\n——-END CERTIFICATE——-“,
“commonName”: “C=US,O=Google, Inc,CN=Google Cloud SQL Server CA,dnQualifier=4aec63c4-dce0-4c94-9656-628e82249bc5”,
“sha1Fingerprint”: “2ea5ad20f8636ce294ce24ed95389d2117291f20”,
“instance”: “gpt-data”,
“createTime”: “2024-06-02T07:44:38.477Z”,
“expirationTime”: “2034-05-31T07:45:38.477Z”
},
“instanceType”: “CLOUD_SQL_INSTANCE”,
“project”: “gpt-data-425207”,
“serviceAccountEmailAddress”: “p948466214002-5ytnrm@gcp-sa-cloud-sql.iam.gserviceaccount.com”,
“backendType”: “SECOND_GEN”,
“selfLink”: “https://sqladmin.googleapis.com/sql/v1beta4/projects/gpt-data-425207/instances/gpt-data”,
“connectionName”: “gpt-data-425207:us-central1:gpt-data”,
“name”: “gpt-data”,
“region”: “us-central1”,
“gceZone”: “us-central1-a”,
“databaseInstalledVersion”: “MYSQL_8_0_31”,
“maintenanceVersion”: “MYSQL_8_0_31.R20240207.00_12”,
“upgradableDatabaseVersions”: [
{
“majorVersion”: “MYSQL_8_0”,
“name”: “MYSQL_8_0_32”,
“displayName”: “MySQL 8.0.32”
},
{
“majorVersion”: “MYSQL_8_0”,
“name”: “MYSQL_8_0_33”,
“displayName”: “MySQL 8.0.33”
},
{
“majorVersion”: “MYSQL_8_0”,
“name”: “MYSQL_8_0_34”,
“displayName”: “MySQL 8.0.34”
},
{
“majorVersion”: “MYSQL_8_0”,
“name”: “MYSQL_8_0_35”,
“displayName”: “MySQL 8.0.35”
},
{
“majorVersion”: “MYSQL_8_0”,
“name”: “MYSQL_8_0_36”,
“displayName”: “MySQL 8.0.36”
}
],
“geminiConfig”: {
“entitled”: false,
“indexAdvisorEnabled”: false,
“flagRecommenderEnabled”: false
},
“createTime”: “2024-06-02T07:44:03.203Z”,
“sqlNetworkArchitecture”: “NEW_NETWORK_ARCHITECTURE”
}

LiquidGPT:

Great! It looks like you’ve successfully retrieved the connection information for your Cloud SQL instance. Here’s a summary of the key details:

Instance State: RUNNABLE
Database Version: MySQL 8.0.31
Instance Tier: db-f1-micro
Primary IP Address: 34.135.236.193
Connection Name: gpt-data-425207:us-central1:gpt-data
Service Account Email: p948466214002-5ytnrm@gcp-sa-cloud-sql.iam.gserviceaccount.com

Next Steps

Now that you have the connection information, you can proceed to connect to your Cloud SQL instance using a MySQL client or any MySQL-compatible application. Here’s how you can do it using the MySQL command-line client:

Connecting to Your Cloud SQL Instance

Install MySQL Client (if not already installed):

sudo apt-get install mysql-client  # On Debian/Ubuntu
brew install mysql-client          # On macOS using Homebrew

Connect to the Cloud SQL Instance:
```
mysql -h 34.135.236.193 -u <USERNAME> -p
```
Replace <USERNAME> with your MySQL username. You’ll be prompted to enter your MySQL password.

Using SSL/TLS for Secure Connection

To connect securely using SSL/TLS, you’ll need the server CA certificate provided in the connection information. Here’s how you can use it:

Save the CA Certificate:
Save the CA certificate to a file, e.g., server-ca.pem.

echo "-----BEGIN CERTIFICATE-----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-----END CERTIFICATE-----" > server-ca.pem

Connect Using SSL/TLS:

mysql -h 34.135.236.193 -u <USERNAME> -p --ssl-ca=server-ca.pem

Summary

You have successfully retrieved the connection information for your Cloud SQL instance and can now connect to it using the MySQL client. Use the provided IP address and SSL certificate for a secure connection. If you encounter any issues, feel free to ask for further assistance.

Adrachin:

mysql -h 34.135.236.193 -u -p

this is not possible. Google blocks direct access. You need to allow the IP first to connect this was. I already researched about that. To complicated. Not usable.

Lets use this:

Using SSL/TLS for Secure Connection

LiquidGPT:

To connect to your Google Cloud SQL instance using SSL/TLS, you can follow these steps. This involves downloading the necessary client certificates from your Cloud SQL instance and using them to establish a secure connection.

Step-by-Step Guide to Connect Using SSL/TLS

Download the Client Certificates

You will need three certificates to connect securely to your Cloud SQL instance:
- Client key file (client-key.pem)
- Client certificate file (client-cert.pem)
- Server CA certificate file (server-ca.pem)
You can download these from the Google Cloud Console.
Prepare the Certificates

Save the certificates to your local machine. For example:
- client-key.pem
- client-cert.pem
- server-ca.pem

Configure the MySQL Client

Use the following MySQL command to connect to your Cloud SQL instance using SSL/TLS:

mysql -h 34.135.236.193 -u <USERNAME> -p --ssl-ca=server-ca.pem --ssl-cert=client-cert.pem --ssl-key=client-key.pem

Steps to Download the Client Certificates

Go to the Cloud SQL Instances Page:
- Open the Google Cloud Console and go to the Cloud SQL Instances page.
Select Your Instance:
- Click on your instance name (gpt-data).
Go to the Connections Tab:
- In the instance details page, go to the “Connections” tab.
Download the Client Certificates:
- Under the “SSL” section, click on “Create client certificate”.
- Download the client key file (client-key.pem), the client certificate file (client-cert.pem), and the server CA certificate

Adrachin:

Using SSL/TLS for Secure Connection

Please advice how to do that.

LiquidGPT:

To securely connect to your Google Cloud SQL instance using SSL/TLS, follow these steps to create and use client certificates.

Step-by-Step Guide to Setup SSL/TLS for Google Cloud SQL

Step 1: Enable SSL/TLS Connections

Go to the Google Cloud Console:
Open your web browser and navigate to the Google Cloud Console.
Select Your Instance:
Find and select your instance (gpt-data).
Navigate to the Connections Tab:
Click on the “Connections” tab.
Enable SSL:
Under the “SSL” section, ensure SSL connections are enabled.

Step 2: Create and Download SSL Certificates

Create Client Certificate:
In the “SSL” section, click “Create client certificate”.
Download Certificates:
- Download the client key file (client-key.pem).
- Download the client certificate file (client-cert.pem).
- Download the server CA certificate (server-ca.pem).

Save these files in a secure location on your local machine.

Step 3: Use Certificates to Connect with MySQL Client

To connect to your Cloud SQL instance using the MySQL client and the downloaded certificates, follow these steps:

Save the Certificates:
Ensure that the client-key.pem, client-cert.pem, and server-ca.pem files are saved in a directory you can access.

Connect Using MySQL Client:

Use the following command, replacing <USERNAME> with your MySQL username:

mysql -h 34.135.236.193 -u <USERNAME> -p --ssl-ca=/path/to/server-ca.pem --ssl-cert=/path/to/client-cert.pem --ssl-key=/path/to/client-key.pem

Example Steps

Navigate to your certificates directory:
```
cd /path/to/your/certificates
```

Connect to your Cloud SQL instance:

mysql -h 34.135.236.193 -u <USERNAME> -p --ssl-ca=server-ca.pem --ssl-cert=client-cert.pem --ssl-key=client-key.pem

You will be prompted to enter the password for the MySQL user.

Troubleshooting Tips

Ensure Network Connectivity:
Ensure your local machine’s IP address is allowed to connect to your Cloud SQL instance. You can add your IP address in the “Authorized networks” section under the “Connections” tab.
Check SSL Settings:
Verify that SSL connections are enabled and that the certificates are correctly downloaded and referenced in your connection command.

Summary

By following these steps, you should be able to securely connect to your Google Cloud SQL instance using SSL/TLS. This method ensures that your connection is encrypted and secure, preventing unauthorized access and data interception. If you encounter any issues or need further assistance, please provide specific error messages or logs for further troubleshooting.

Adrachin:

I can not find this:

LiquidGPT:

Let’s go through the steps to enable SSL/TLS and download the necessary certificates for connecting to your Google Cloud SQL instance in a more detailed manner.

Step-by-Step Guide to Enable SSL/TLS and Download Certificates

Step 1: Enable SSL Connections

Open Google Cloud Console:
Go to the Google Cloud Console.
Select Your SQL Instance:
Click on your instance name (gpt-data).
Navigate to the “Connections” Tab:
In the instance details page, click on the “Connections” tab.
Scroll to the “SSL” Section:
Ensure that the “SSL connections” option is enabled. This should be enabled by default.

Step 2: Create and Download SSL Certificates

Create a Client Certificate:
In the “Connections” tab under the “SSL” section, you should see an option to “Create client certificate”.
- If you don’t see this option, it might be located under “Authorization” or “Security” depending on UI changes. Look for sections related to SSL or client certificates.
Generate the Certificates:
Click on “Create client certificate” and follow the prompts to generate the client certificates.
Download the Certificates:
Once the client certificates are created, download the following files:
- Client Key File: client-key.pem
- Client Certificate File: client-cert.pem
- Server CA Certificate: server-ca.pem

Step 3: Allow Your IP Address to Connect

Authorized Networks:
In the “Connections” tab, find the “Authorized networks” section.
Add Your IP Address:
Add your local machine’s IP address to the list of authorized networks to allow it to connect to the Cloud SQL instance.
- Click “Add network” and enter a name and your IP address.

Step 4: Connect Using MySQL Client with SSL/TLS

Store the Certificates:
Save the downloaded certificates (client-key.pem, client-cert.pem, server-ca.pem) in a secure location on your machine.
Connect Using the MySQL Client:
Use the MySQL client to connect to your Cloud SQL instance with SSL/TLS.

Open a terminal and use the following command, replacing <USERNAME> with your MySQL username and /path/to/your/certificates with the actual path where your certificates are stored:
```
mysql -h 34.135.236.193 -u <USERNAME> -p --ssl-ca=/path/to/your/certificates/server-ca.pem --ssl-cert=/path/to/your/certificates/client-cert.pem --ssl-key=/path/to/your/certificates/client-key.pem
```
Enter Password:
When prompted, enter the password for your MySQL user.

Summary

By following these steps, you should be able to securely connect to your Google Cloud SQL instance using SSL/TLS. If you cannot find the “Create client certificate” option or any specific section, please provide details or screenshots of what you see in the Google Cloud Console so I can give more targeted guidance.

Adrachin:

Easy. First things first. I found the place. There are several options. Which one to choose?

ou can enforce connection security for this instance with two methods which use Transport Layer Security (SSL/TLS):

Use Cloud SQL Connectors to automatically encrypt in-transit data, handle SSL certificates, and use IAM-based access (recommended). Learn more
Self-manage encryption and client/server certificates, and client IP-based access with Authorized networks. Learn more
Manage SSL mode
Secure data transmission between client and this instance by enforcing SSL encryption and certificates. SSL encryption is recommended for all connections using public IP networks. Learn more

SSL mode

Allow unencrypted network traffic (not recommended)

In-transit data will be unencrypted and vulnerable to eavesdropping by unauthorized clients attempting to intercept and inspect your data.

Allow only SSL connections
Only allows connections using SSL/TLS encryption. Certificates will not be verified.

Require trusted client certificates
Only allows connections from clients that use a valid client certificate and SSL encryption
Manage server CA certificates
A server Certificate Authority (CA) certificate is created with your instance and used by clients to check if the server certificate is signed by a trusted certificate authority. You don’t have to actively manage CA certificates, but they expire in 10 years. Learn more

LiquidGPT:

To securely connect to your Google Cloud SQL instance using SSL/TLS, you should choose the following options:

Self-manage encryption and client/server certificates, and client IP-based access with Authorized networks.
SSL mode:
- Require trusted client certificates: This option ensures that only clients with a valid client certificate and SSL encryption can connect to your instance.

Here’s how to configure these settings step-by-step:

Step 1: Configure SSL/TLS and Certificates

Open Google Cloud Console:
Go to the Google Cloud Console.
Select Your SQL Instance:
Click on your instance name (gpt-data).
Navigate to the “Connections” Tab:
In the instance details page, click on the “Connections” tab.
SSL Mode:
- Choose Require trusted client certificates. This ensures that all connections are encrypted and require valid client certificates.

Step 2: Create and Download SSL Certificates

Create Client Certificate:
In the “Connections” tab under the “SSL” section, click “Create client certificate”.
Generate the Certificates:
Follow the prompts to generate the client certificates.
Download the Certificates:
Download the following files:
- Client Key File: client-key.pem
- Client Certificate File: client-cert.pem
- Server CA Certificate: server-ca.pem

Step 3: Allow Your IP Address to Connect

Authorized Networks:
In the “Connections” tab, find the “Authorized networks” section.
Add Your IP Address:
Add your local machine’s IP address to the list of authorized networks to allow it to connect to the Cloud SQL instance.
- Click “Add network” and enter a name and your IP address.

Step 4: Connect Using MySQL Client with SSL/TLS

Store the Certificates:
Save the downloaded certificates (client-key.pem, client-cert.pem, server-ca.pem) in a secure location on your machine.
Connect Using the MySQL Client:
Use the MySQL client to connect to your Cloud SQL instance with SSL/TLS.

Open a terminal and use the following command, replacing <USERNAME> with your MySQL username and /path/to/your/certificates with the actual path where your certificates are stored:
```
mysql -h 34.135.236.193 -u <USERNAME> -p --ssl-ca=/path/to/your/certificates/server-ca.pem --ssl-cert=/path/to/your/certificates/client-cert.pem --ssl-key=/path/to/your/certificates/client-key.pem
```
Enter Password:
When prompted, enter the password for your MySQL user.

Summary

By following these steps, you will have securely configured your Cloud SQL instance to require SSL/TLS encryption and valid client certificates for connections. This setup ensures that your data is protected in transit and that only authorized clients can connect to your database.

Adrachin:

Slowly slowly. I enabled the option and have the certificates. And this is the connection string:

mysql -uroot -p -h 34.135.236.193 —ssl-ca=server-ca.pem —ssl-cert=client-cert.pem —ssl-key=client-key.pem

What I can not do is Add Your IP Address. The IP is provided from my Internet Service Provider and will change randomly.

LiquidGPT:

To handle changing IP addresses provided by your Internet Service Provider, you can use the Cloud SQL Auth proxy, which allows for secure connections to your Cloud SQL instance without needing to add individual IP addresses. The proxy handles authentication and encryption, making it easier to connect securely from any network.

Step-by-Step Guide to Use Cloud SQL Auth Proxy

Step 1: Install Cloud SQL Auth Proxy

Download the Cloud SQL Auth Proxy:
Download the appropriate binary for your operating system from the Cloud SQL Auth Proxy releases page.

For example, on macOS or Linux:
```
wget https://dl.google.com/cloudsql/cloud_sql_proxy.darwin.amd64 -O cloud_sql_proxy
chmod +x cloud_sql_proxy
```
For Windows, download the .exe file and place it in a directory in your PATH.
Install via Homebrew (macOS):
Alternatively, you can install it using Homebrew on macOS:
```
brew install cloud-sql-proxy
```

Step 2: Set Up the Service Account

Ensure your service account key file is available:
Make sure you have the service account JSON key file (gpt-data-425207-54872e0cb8e3.json) that you used earlier.
Set the GOOGLE_APPLICATION_CREDENTIALS environment variable:
Export the path to your service account key file as an environment variable:
```
export GOOGLE_APPLICATION_CREDENTIALS="/Users/thomas/Downloads/gpt-data-425207-54872e0cb8e3.json"
```

Step 3: Start the Cloud SQL Auth Proxy

Run the Cloud SQL Auth Proxy:
Use the following command to start the proxy, replacing INSTANCE_CONNECTION_NAME with your instance’s connection name, which is gpt-data-425207:us-central1:gpt-data.
```
./cloud_sql_proxy -instances=gpt-data-425207:us-central1:gpt-data=tcp:3306
```
This command starts the proxy and binds it to port 3306 on your local machine.

Step 4: Connect to the Cloud SQL Instance

Use the MySQL client to connect through the proxy:
Now that the proxy is running, you can connect to your Cloud SQL instance using the MySQL client:
```
mysql -uroot -p --host=127.0.0.1 --port=3306 --ssl-ca=server-ca.pem --ssl-cert=client-cert.pem --ssl-key=client-key.pem
```
When prompted, enter the password for the MySQL root user.

Summary

Using the Cloud SQL Auth Proxy simplifies the process of connecting to your Cloud SQL instance securely, especially when dealing with dynamic IP addresses. This approach handles authentication and encryption, allowing you to connect from any network without needing to whitelist specific IP addresses. Follow these steps to set up and use the Cloud SQL Auth Proxy for a secure and reliable connection.

Adrachin:

So, back again. The SSH effort is not necessary. The final goal is to create a API connection in the script for the action located in the custom GPT. Do we have all the information now to get this up and running?

LiquidGPT:

Got it. Let’s consolidate the information you have and create an OpenAPI 3.0 specification for the API connection in the script for the custom GPT. You have the following details:

Service Account JSON Key File: /Users/thomas/Downloads/gpt-data-425207-54872e0cb8e3.json
Google Cloud SQL Instance Connection Name: gpt-data-425207:us-central1:gpt-data
Client Certificates: client-key.pem, client-cert.pem, server-ca.pem
MySQL Connection String: mysql -uroot -p -h 34.135.236.193 --ssl-ca=server-ca.pem --ssl-cert=client-cert.pem --ssl-key=client-key.pem

Step 1: Create OpenAPI Specification

Here is the OpenAPI 3.0 specification for an API that retrieves connection information for your Google Cloud SQL instance and connects using the client certificates:

openapi: 3.0.0
info:
  title: Google Cloud SQL API
  description: API for connecting to and managing Google Cloud SQL databases using client certificates.
  version: 1.0.0
servers:
  - url: https://www.googleapis.com/sql/v1beta4
    description: Google Cloud SQL API server
paths:
  /projects/{project}/instances/{instance}/connect:
    get:
      operationId: getConnectInfo
      summary: Get connection information for a Cloud SQL instance.
      parameters:
        - name: project
          in: path
          required: true
          description: The ID of the project that contains the instance.
          schema:
            type: string
          example: gpt-data-425207
        - name: instance
          in: path
          required: true
          description: The ID of the Cloud SQL instance.
          schema:
            type: string
          example: us-central1:gpt-data
      responses:
        '200':
          description: Successfully retrieved connection information.
          content:
            application/json:
              schema:
                type: object
                properties:
                  ipAddresses:
                    type: array
                    items:
                      type: object
                      properties:
                        type:
                          type: string
                        ipAddress:
                          type: string
                  serverCaCert:
                    type: object
                    properties:
                      instance:
                        type: string
                      cert:
                        type: string
                      createTime:
                        type: string
                      commonName:
                        type: string
                      expirationTime:
                        type: string
                  instance:
                    type: string
                  databaseVersion:
                    type: string
                  connectionName:
                    type: string
        '404':
          description: Not Found - The specified project or instance was not found.
        '403':
          description: Forbidden - The caller does not have permission to access the specified project or instance.
        '401':
          description: Unauthorized - The request does not have valid authentication credentials.

Step 2: Implement Custom Action in Python

Here is a Python script that uses the above API to get connection information and connect to the Cloud SQL instance using SSL/TLS:

from google.oauth2 import service_account
from googleapiclient.discovery import build
import mysql.connector
import json

# Path to your service account key file
SERVICE_ACCOUNT_FILE = '/Users/thomas/Downloads/gpt-data-425207-54872e0cb8e3.json'
SCOPES = ['https://www.googleapis.com/auth/cloud-platform']

# Create credentials
credentials = service_account.Credentials.from_service_account_file(
    SERVICE_ACCOUNT_FILE, scopes=SCOPES)

# Build the service
service = build('sqladmin', 'v1beta4', credentials=credentials)

# Project and instance ID
project_id = 'gpt-data-425207'
instance_id = 'gpt-data'

# Request connection information
request = service.instances().get(project=project_id, instance=instance_id)
response = request.execute()

# Extract connection details
ip_address = response['ipAddresses'][0]['ipAddress']
server_ca_cert = response['serverCaCert']['cert']

# MySQL connection details
user = 'root'  # Replace with your MySQL username
password = 'your_password'  # Replace with your MySQL password
database = 'your_database'  # Replace with your database name

# Path to client certificates
client_key = '/path/to/client-key.pem'
client_cert = '/path/to/client-cert.pem'
server_ca = '/path/to/server-ca.pem'

# Connect to the Cloud SQL instance using SSL/TLS
connection = mysql.connector.connect(
    host=ip_address,
    user=user,
    password=password,
    database=database,
    ssl_ca=server_ca,
    ssl_cert=client_cert,
    ssl_key=client_key
)

print("Connected to the database successfully!")

Summary

OpenAPI Specification: Defines the API to retrieve connection information.
Python Script: Uses the Google Cloud SQL API to get connection information and connects to the database using SSL/TLS with client certificates.

Next Steps

Replace the placeholders in the Python script (your_password, your_database, and paths to certificate files) with your actual values.
Run the Python script in your custom GPT action to establish the connection and perform the desired operations on your Cloud SQL instance.

If you need further assistance with specific parts of this setup, feel free to ask!

Adrachin:

This component is missing in my virtual environment:

ModuleNotFoundError: No module named ‘mysql’

LiquidGPT:

To resolve the ModuleNotFoundError: No module named 'mysql', you need to install the mysql-connector-python package in your virtual environment. This package provides a MySQL driver for connecting to your database.

Step-by-Step Guide to Install the MySQL Connector

Activate your virtual environment:

source /Users/thomas/_python/venv/bin/activate

Install the mysql-connector-python package:
```
pip install mysql-connector-python
```

Updated Python Script

Here’s the updated script with the MySQL connector module installed:

from google.oauth2 import service_account
from googleapiclient.discovery import build
import mysql.connector
import json

# Path to your service account key file
SERVICE_ACCOUNT_FILE = '/Users/thomas/Downloads/gpt-data-425207-54872e0cb8e3.json'
SCOPES = ['https://www.googleapis.com/auth/cloud-platform']

# Create credentials
credentials = service_account.Credentials.from_service_account_file(
    SERVICE_ACCOUNT_FILE, scopes=SCOPES)

# Build the service
service = build('sqladmin', 'v1beta4', credentials=credentials)

# Project and instance ID
project_id = 'gpt-data-425207'
instance_id = 'gpt-data'

# Request connection information
request = service.instances().get(project=project_id, instance=instance_id)
response = request.execute()

# Extract connection details
ip_address = response['ipAddresses'][0]['ipAddress']
server_ca_cert = response['serverCaCert']['cert']

# MySQL connection details
user = 'root'  # Replace with your MySQL username
password = 'your_password'  # Replace with your MySQL password
database = 'your_database'  # Replace with your database name

# Path to client certificates
client_key = '/Users/thomas/Downloads/client-key.pem'
client_cert = '/Users/thomas/Downloads/client-cert.pem'
server_ca = '/Users/thomas/Downloads/server-ca.pem'

# Connect to the Cloud SQL instance using SSL/TLS
connection = mysql.connector.connect(
    host=ip_address,
    user=user,
    password=password,
    database=database,
    ssl_ca=server_ca,
    ssl_cert=client_cert,
    ssl_key=client_key
)

print("Connected to the database successfully!")

Steps to Run the Script

Ensure your virtual environment is activated:

source /Users/thomas/_python/venv/bin/activate

Install the required libraries:

pip install mysql-connector-python google-auth google-auth-oauthlib google-auth-httplib2 google-api-python-client

Save the script to a file:

Save the script to a file, for example, connect_to_sql.py.
Run the script:
```
python connect_to_sql.py
```

Summary

By installing the mysql-connector-python package and ensuring all necessary paths and credentials are correctly configured, you should be able to securely connect to your Google Cloud SQL instance using SSL/TLS. If you encounter any further issues, please provide specific error messages or logs for additional troubleshooting.

Adrachin:

I need to source the virtual environment to make it active. What’s the command?

LiquidGPT:

To activate your virtual environment, you need to use the source command followed by the path to the activation script of your virtual environment. Here’s how you can do it:

Command to Activate the Virtual Environment

Activate on macOS/Linux:

source /Users/thomas/_python/venv/bin/activate

Activate on Windows (using Command Prompt):

\Users\thomas\_python\venv\Scripts\activate

Activate on Windows (using PowerShell):

.\Users\thomas\_python\venv\Scripts\Activate.ps1

Example Workflow

Activate your virtual environment:

source /Users/thomas/_python/venv/bin/activate

Install the required libraries:

pip install mysql-connector-python google-auth google-auth-oauthlib google-auth-httplib2 google-api-python-client

Run your Python script:

Save the script to a file, for example, connect_to_sql.py, and then run it:
```
python connect_to_sql.py
```

Summary

Use the source command with the appropriate path to activate your virtual environment on macOS/Linux. Once the environment is activated, you can install the necessary packages and run your Python script. If you encounter any issues or need further assistance, feel free to ask.

Adrachin:

Here is what I see running the script locally:

(venv) ➜ readGTPchats python connect.py
^CTraceback (most recent call last):
File “/Users/thomas/_python/venv/lib/python3.12/site-packages/mysql/connector/connection_cext.py”, line 327, in _open_connection
self._cmysql.connect(**cnx_kwargs)
_mysql_connector.MySQLInterfaceError: Can’t connect to MySQL server on ‘34.135.236.193:3306’ (56)

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
File “/Users/thomas/_python/MyApps/readGTPchats/connect.py”, line 40, in
connection = mysql.connector.connect(
^^^^^^^^^^^^^^^^^^^^^^^^
File “/Users/thomas/_python/venv/lib/python3.12/site-packages/mysql/connector/pooling.py”, line 322, in connect
return CMySQLConnection(*args, kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File “/Users/thomas/_python/venv/lib/python3.12/site-packages/mysql/connector/connection_cext.py”, line 144, in init
self.connect(kwargs)
File “/Users/thomas/_python/venv/lib/python3.12/site-packages/mysql/connector/abstracts.py”, line 1360, in connect
self._open_connection()
File “/Users/thomas/_python/venv/lib/python3.12/site-packages/mysql/connector/connection_cext.py”, line 332, in _open_connection
raise get_mysql_exception(
^^^^^^^^^^^^^^^^^^^^
File “/Users/thomas/_python/venv/lib/python3.12/site-packages/mysql/connector/errors.py”, line 222, in get_mysql_exception
def get_mysql_exception(

KeyboardInterrupt

LiquidGPT:

The error message indicates that the script is unable to connect to the MySQL server. This could be due to several reasons such as network issues, incorrect IP address, or SSL configuration problems. Let’s troubleshoot step-by-step:

Step-by-Step Troubleshooting

Step 1: Verify the IP Address and Port

Ensure that the IP address and port are correct. The IP address should match the one listed under the ipAddresses key in your Cloud SQL instance details.

Step 2: Verify SSL Configuration

Make sure that the paths to the SSL certificates are correct and that the certificates are properly formatted. The script should be able to locate the certificate files.

Step 3: Check Network Access

Since Cloud SQL instances can have IP whitelisting, ensure that your machine’s IP is allowed to connect. Since your IP changes frequently, using the Cloud SQL Auth proxy can help avoid this issue.

Using Cloud SQL Auth Proxy for Easier Connection

Using the Cloud SQL Auth proxy can simplify the connection process, as it handles authentication and networking.

Install the Cloud SQL Auth Proxy

Download the Cloud SQL Auth Proxy:

wget https://dl.google.com/cloudsql/cloud_sql_proxy.darwin.amd64 -O cloud_sql_proxy
chmod +x cloud_sql_proxy

For Windows, download the .exe file and place it in a directory in your PATH.

Set the GOOGLE_APPLICATION_CREDENTIALS environment variable:

export GOOGLE_APPLICATION_CREDENTIALS="/Users/thomas/Downloads/gpt-data-425207-54872e0cb8e3.json"

Start the Cloud SQL Auth Proxy

Run the Cloud SQL Auth Proxy:
```
./cloud_sql_proxy -instances=gpt-data-425207:us-central1:gpt-data=tcp:3306
```
This command starts the proxy and binds it to port 3306 on your local machine.

Connect Using the MySQL Client

Use the MySQL client to connect through the proxy:

mysql -uroot -p --host=127.0.0.1 --port=3306 --ssl-ca=server-ca.pem --ssl-cert=client-cert.pem --ssl-key=client-key.pem

Updated Python Script Using the Cloud SQL Auth Proxy

If you prefer to stick with the Python script and handle SSL/TLS directly, ensure the paths and credentials are correct. Here’s the script again for clarity:

from google.oauth2 import service_account
from googleapiclient.discovery import build
import mysql.connector
import json

# Path to your service account key file
SERVICE_ACCOUNT_FILE = '/Users/thomas/Downloads/gpt-data-425207-54872e0cb8e3.json'
SCOPES = ['https://www.googleapis.com/auth/cloud-platform']

# Create credentials
credentials = service_account.Credentials.from_service_account_file(
    SERVICE_ACCOUNT_FILE, scopes=SCOPES)

# Build the service
service = build('sqladmin', 'v1beta4', credentials=credentials)

# Project and instance ID
project_id = 'gpt-data-425207'
instance_id = 'gpt-data'

# Request connection information
request = service.instances().get(project=project_id, instance=instance_id)
response = request.execute()

# Extract connection details
ip_address = response['ipAddresses'][0]['ipAddress']
server_ca_cert = response['serverCaCert']['cert']

# MySQL connection details
user = 'root'  # Replace with your MySQL username
password = 'your_password'  # Replace with your MySQL password
database = 'your_database'  # Replace with your database name

# Path to client certificates
client_key = '/Users/thomas/Downloads/client-key.pem'
client_cert = '/Users/thomas/Downloads/client-cert.pem'
server_ca = '/Users/thomas/Downloads/server-ca.pem'

# Connect to the Cloud SQL instance using SSL/TLS
connection = mysql.connector.connect(
    host=ip_address,
    user=user,
    password=password,
    database=database,
    ssl_ca=server_ca,
    ssl_cert=client_cert,
    ssl_key=client_key
)

print("Connected to the database successfully!")

Running the Script

Ensure your virtual environment is activated:

source /Users/thomas/_python/venv/bin/activate

Install the required libraries (if not already installed):

pip install mysql-connector-python google-auth google-auth-oauthlib google-auth-httplib2 google-api-python-client

Run the script:
```
python connect_to_sql.py
```

Summary

By using the Cloud SQL Auth proxy, you can simplify the connection process and avoid IP whitelisting issues. If you prefer to connect directly using SSL/TLS, ensure all paths and credentials are correct. If issues persist, please provide specific error messages for further troubleshooting.

LiquidGPT:

To connect to your Google Cloud SQL instance securely using SSL/TLS, follow these steps:

Step 1: Configure Authorized Networks

You need to add your IP address to the list of authorized networks to allow connections from your machine. Here’s how you can do it:

Go to the Google Cloud Console:
Navigate to the Google Cloud SQL Instances page in the Google Cloud Console.
Select Your Instance:
Click on your instance gpt-data.
Add Authorized Network:
- Click on Connections.
- In the Authorized networks section, click Add network.
- Enter a name for the network and your IP address.
- Click Done and then Save.

Step 2: Configure SSL/TLS

Download the Server CA Certificate:
The certificate provided in the connection information needs to be saved to a file named server-ca.pem.

Save the following certificate content to a file named server-ca.pem:
```
-----BEGIN CERTIFICATE-----
MIIDfzCCAmegAwIBAgIBADANBgkqhkiG9w0BAQsFADB3MS0wKwYDVQQuEyQ0YWVj
NjNjNC1kY2UwLTRjOTQtOTY1Ni02MjhlODIyNDli
```