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132 lines
3.3 KiB
Markdown
132 lines
3.3 KiB
Markdown
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# Installing and Using PostgreSQL with LightRAG
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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.
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## Prerequisites
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Before beginning this setup, ensure that you have administrative access to your server or local machine and can install software packages.
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### 1. Install PostgreSQL
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First, update your package list and install PostgreSQL:
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```bash
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sudo apt update
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sudo apt install postgresql postgresql-contrib
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```
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Start the PostgreSQL service if it isn’t already running:
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```bash
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sudo systemctl start postgresql
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```
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Ensure that PostgreSQL starts on boot:
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```bash
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sudo systemctl enable postgresql
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```
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### 2. Set a Password for Your Postgres Role
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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.
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To set a password for the `postgres` user:
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```bash
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sudo -u postgres psql
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```
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Inside the PostgreSQL shell, run:
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```sql
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ALTER USER postgres WITH PASSWORD 'your_secure_password';
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\q
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```
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Alternatively, to create a new role with a password:
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```bash
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sudo -u postgres createuser --interactive
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```
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You'll be prompted for the name of the new role and whether it should have superuser permissions. Then set a password:
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```sql
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ALTER USER your_new_role WITH PASSWORD 'your_secure_password';
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\q
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```
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### 3. Install PGVector Extension
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Install necessary dependencies and compile the extension:
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```bash
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sudo apt install postgresql-server-dev-all
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cd /tmp
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git clone --branch v0.8.0 https://github.com/pgvector/pgvector.git
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cd pgvector
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make
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sudo make install
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```
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Enable the `pgvector` extension in your PostgreSQL database:
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```sql
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CREATE EXTENSION vector;
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```
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Verify installation by checking the extension version:
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```sql
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SELECT extversion FROM pg_extension WHERE extname = 'vector';
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```
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### 4. Create a Database
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Create an empty database to store your data:
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```bash
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sudo -u postgres createdb your_database
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```
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### 5. Install LightRAG with API Access
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Install LightRAG using pip, targeting the API package for server-side use:
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```bash
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pip install https://github.com/ParisNeo/LightRAG.git[api]
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```
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### 6. Configure `config.ini`
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Create a configuration file to specify PostgreSQL connection details and other settings:
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In your project directory, create a `config.ini` file with the following content:
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```ini
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[postgres]
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host = localhost
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port = 5432
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user = your_role_name
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password = your_password
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database = your_database
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workspace = default
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```
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Replace placeholders like `your_role_name`, `your_password`, and `your_database` with actual values.
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### 7. Run LightRAG Server
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Start the LightRAG server using specified options:
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```bash
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lightrag-server --port the-port-number --key your-secret-key --kv-storage PGKVStorage --graph-storage PGGraphStorage --vector-storage PGVectorStorage
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```
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Replace `the-port-number` with your desired port number (default is 9621) and `your-secret-key` with a secure key.
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## Conclusion
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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.
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