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lightrag/api/docs/LightRagWithPostGRESQL.md

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-# Installing and Using PostgreSQL with LightRAG
-
-This guide provides step-by-step instructions on setting up PostgreSQL for use with LightRAG, a tool designed to enhance large language model (LLM) performance using retrieval-augmented generation techniques.
-
-## Prerequisites
-
-Before beginning this setup, ensure that you have administrative access to your server or local machine and can install software packages.
-
-### 1. Install PostgreSQL
-
-First, update your package list and install PostgreSQL:
-
-```bash
-sudo apt update
-sudo apt install postgresql postgresql-contrib
-```
-
-Start the PostgreSQL service if it isn’t already running:
-
-```bash
-sudo systemctl start postgresql
-```
-
-Ensure that PostgreSQL starts on boot:
-
-```bash
-sudo systemctl enable postgresql
-```
-
-### 2. Set a Password for Your Postgres Role
-
-By default, PostgreSQL creates a user named `postgres`. You'll need to set a password for this role or create another role with a password.
-
-To set a password for the `postgres` user:
-
-```bash
-sudo -u postgres psql
-```
-
-Inside the PostgreSQL shell, run:
-
-```sql
-ALTER USER postgres WITH PASSWORD 'your_secure_password';
-\q
-```
-
-Alternatively, to create a new role with a password:
-
-```bash
-sudo -u postgres createuser --interactive
-```
-
-You'll be prompted for the name of the new role and whether it should have superuser permissions. Then set a password:
-
-```sql
-ALTER USER your_new_role WITH PASSWORD 'your_secure_password';
-\q
-```
-
-### 3. Install PGVector and Age Extensions
-
-Install PGVector:
-```bash
-sudo apt install postgresql-server-dev-all
-cd /tmp
-git clone --branch v0.8.0 https://github.com/pgvector/pgvector.git
-cd pgvector
-make
-sudo make install
-```
-Install age:
-```bash
-sudo apt-get install build-essential libpq-dev
-cd /tmp
-git clone https://github.com/apache/age.git
-cd age
-make
-sudo make install
-```
-
-### 4. Create a Database for LightRAG
-
-Create an empty database to store your data:
-
-```bash
-sudo -u postgres createdb your_database
-```
-
-### 5. Activate PGVector Extension in the Database
-
-Switch to the newly created database and enable the `pgvector` extension:
-
-```bash
-sudo -u postgres psql -d your_database
-```
-
-Inside the PostgreSQL shell, run:
-
-```sql
-CREATE EXTENSION vector;
-```
-
-Verify installation by checking the extension version within this specific database:
-
-```sql
-SELECT extversion FROM pg_extension WHERE extname = 'vector';
-\q
-```
-
-### 6. Install LightRAG with API Access
-
-Install LightRAG using pip, targeting the API package for server-side use:
-
-```bash
-pip install "lightrag-hku[api]"
-```
-
-### 7. Configure `config.ini`
-
-Create a configuration file to specify PostgreSQL connection details and other settings:
-
-In your project directory, create a `config.ini` file with the following content:
-
-```ini
-[postgres]
-host = localhost
-port = 5432
-user = your_role_name
-password = your_password
-database = your_database
-workspace = default
-```
-
-Replace placeholders like `your_role_name`, `your_password`, and `your_database` with actual values.
-
-### 8. Run LightRAG Server
-
-Start the LightRAG server using specified options:
-
-```bash
-lightrag-server --port 9621 --key sk-somepassword --kv-storage PGKVStorage --graph-storage PGGraphStorage --vector-storage PGVectorStorage --doc-status-storage PGDocStatusStorage
-```
-
-Replace the `port` number with your desired port number (default is 9621) and `your-secret-key` with a secure key.
-
-## Conclusion
-
-With PostgreSQL set up to work with LightRAG, you can now leverage vector storage and retrieval-augmented capabilities for enhanced language model operations. Adjust configurations as needed based on your specific environment and use case requirements.