Dennis Seah

  Image from https://www.pexels.com/@pavel-danilyuk/ One of the cool features of OpenAI version 2023-07-01 is its custom Functions feature. This feature is close to me because I am working on a project where we require OpenAI to generate JSON responses. We always want the generated JSON to be consistent, otherwise, we need to do some post-processing tasks to get the JSON object in the correct schema. In the blog, we observe the completion with and without this new feature. Development Setup python -m venv .venv poetry init poetry shell poetry add openai poetry add python-dotenv poetry add pydantic I am using Python version 3.11 Create .env file OPENAI_API_TYPE="azure" OPENAI_API_BASE="<OpenAI endpoint>" OPENAI_API_KEY="<OpenAI secret>" OPENAI_API_VERSION="2023-07-01-preview" OPENAI_DEPLOYMENT_ID="<deployment identifier>" Without OpenAI functions feature We use two sample texts for experimentation. We want to get the na

  Image from https://www.pexels.com/@tara-winstead/ There are many options to store text embeddings. In this blog, we shall look at storing embedding in Azure Database for PostgreSQL. Installing Azure Database for PostgreSQL Install Azure Database for PostgreSQL Flexible Server.  Once it is deployed, enable two extensions. Install Python modules python -m venv .venv poetry init poetry shell poetry add openai[datalib] poetry add python-dotenv poetry add psycopg2-binary My Python version is 3.10. Create .env OPENAI_API_TYPE="azure" OPENAI_API_BASE="<HTTP endpoint to Azure OpenAI Service>" OPENAI_API_KEY="<secret to Azure OpenAI Service>" OPENAI_API_VERSION="2023-05-15" TEXT_MODEL="<deployment id of text embedding model>" PGHOST="<my-service>.postgres.database.azure.com" PGUSER="<user name>" PGPASSWORD="<secret>" PGPORT="5432" PGDATABASE="< database name