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from langchain.llms import OpenAI | |
from langchain import OpenAI, SQLDatabase, SQLDatabaseChain | |
from langchain.prompts.prompt import PromptTemplate | |
import os | |
def chat_with_mysql_database(prompt: str): | |
""" | |
Args: | |
prompt (str): Question to ask e.g. "Generate an SQL query to retrieve all users" | |
Returns: |
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# The following is an example of a command to clone an development(ex-app-development) as an production(ex-app-production). | |
kubectl get deployment ex-app-development -o json \ | |
| jq '.metadata.name = "ex-app-production"' \ | |
| kubectl apply -f - |
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##### | |
# | |
# GitHub Actions will deploy your app to Cloud Run in Google Cloud Platform (GCP) when you push to master or main branch. | |
# | |
# 1. Set up your GCP project and Cloud Run service account | |
# 2. Ensure your service account has permissions to push images to Artifact Registry and deploy to Cloud Run. | |
# 3. Create a key.json file for the service account and add it to your GitHub repo as a secret. (In this example, the secret name is GCP_DEPLOYER_KEY) | |
# 4. Enable the Cloud Run API and Artifact Registry API in your GCP project | |
# 5. Add this file as .github/workflows/deployer.yml | |
# 6. Add a Dockerfile to your repo to build your app |
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