postgres-ai

Automate vector search, RAG, and memory in Azure PostgreSQL with pgvector and azure_ai.

Updated Jan 15, 2026
One-click install
npx skills add https://github.com/samelhousseini/microhacks --skill postgres-ai
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: postgres-ai
Source: https://github.com/samelhousseini/microhacks/tree/main/.github/skills/postgres-ai
Command: npx skills add https://github.com/samelhousseini/microhacks --skill postgres-ai

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires psycopg2, pgvector, python-dotenv, openai, langchain-core, langchain-openai, langchain-postgres, langchain, langgraph, langgraph-checkpoint-postgres, and includes scripts (resource) components.

What problem does it solve?

Azure PostgreSQL AI workloads are complex to set up and maintain; this Skill delivers a ready-to-run integration for vector search, RAG pipelines, and persistent agent memory using pgvector and azure_ai extensions to accelerate AI-powered data apps.

Core Features & Use Cases

  • Vector search with pgvector on Azure PostgreSQL for fast similarity queries over embeddings
  • RAG pipelines using LangChain, Azure OpenAI, and a PostgreSQL-backed vector store for retrieval-augmented generation
  • Persistent agent memory and checkpointing with LangGraph to maintain context across sessions

Quick Start

Configure environment variables (PGHOST, PGDATABASE, PGUSER, PGPASSWORD, AZURE_OPENAI_ENDPOINT, AZURE_OPENAI_API_KEY) and run the scripts in .github/skills/postgres-ai/scripts to initialize the vector table, insert documents, and perform a sample search or RAG query.

Frequently Asked Questions about postgres-ai

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I set up vector search in Azure PostgreSQL using pgvector?▼

Vector search in Azure PostgreSQL requires installing pgvector and azure_ai extensions to create a vector table, insert embeddings, and run similarity queries. The Skill automates this initialization using configured environment variables.

Can I use LangChain and Azure OpenAI for RAG pipelines in PostgreSQL?▼

Yes, you can build RAG pipelines using LangChain, Azure OpenAI, and a PostgreSQL-backed vector store. This Skill provides scripts to execute retrieval-augmented generation queries directly inside your database.

How does LangGraph maintain persistent agent memory in PostgreSQL?▼

LangGraph maintains persistent agent memory in PostgreSQL through checkpointing to store and retrieve context across sessions. This Skill integrates langgraph-checkpoint-postgres to preserve state continuity for data-driven apps.

What environment variables are required to connect Azure OpenAI with PostgreSQL?▼

Connecting Azure OpenAI with PostgreSQL requires configuring PGHOST, PGDATABASE, PGUSER, PGPASSWORD, AZURE_OPENAI_ENDPOINT, and AZURE_OPENAI_API_KEY. These variables authenticate both the database and AI embedding services.

What is the best way to implement scalable embeddings and retrieval in Azure PostgreSQL?▼

The best way to implement scalable embeddings and retrieval in Azure PostgreSQL is using pgvector for similarity queries and LangGraph for state management. This Skill delivers a ready-to-run integration for these specific workloads.