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Prerequisites

  • Docker and Docker Compose
  • An LLM API key (works with OpenAI, Anthropic, OpenRouter, or any OpenAI-compatible provider)
1

Clone the repository

git clone https://github.com/getprofile/getprofile.git
cd getprofile
2

Configure environment

cp .env.docker.example .env
Edit .env and add your LLM API key:
# Works with any provider (OpenAI, Anthropic, OpenRouter, etc.)
LLM_API_KEY=sk-your-key-here

# Or use provider-specific keys
# OPENAI_API_KEY=sk-...
# ANTHROPIC_API_KEY=sk-...
Provider Configuration: Edit config/getprofile.json to choose your provider:
{
  "llm": {
    "provider": "openai",  // or "anthropic" or "custom"
    "model": "gpt-5-mini"  // or "claude-4-5-sonnet"
  }
}
The .env.docker.example file is optimized for Docker deployment. For local development without Docker, use .env.example instead.
3

Start services

source .env && export LLM_API_KEY && docker compose -f docker/docker-compose.yml up -d
This starts:
  • GetProfile Proxy on http://localhost:3100
  • PostgreSQL database
Note: We source the .env file before starting to ensure long API keys are loaded correctly. Database migrations run automatically on first start. Monitor logs with:
docker compose -f docker/docker-compose.yml logs -f proxy
4

Configure API key (optional)

If you want to protect your proxy with an API key, set it in your .env:
GETPROFILE_API_KEY=your-secret-key-here
If not set, the proxy will accept all requests (useful for local development).
Configuration: You can configure GetProfile via config/getprofile.json or environment variables. Environment variables take precedence. See Configuration for details.
After changing .env, restart services:
docker compose -f docker/docker-compose.yml down
source .env && export LLM_API_KEY && docker compose -f docker/docker-compose.yml up -d
5

Test the proxy

curl http://localhost:3100/health
You should see:
{
  "status": "ok",
  "version": "0.1.0",
  "timestamp": "2024-01-01T00:00:00.000Z"
}

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Option 2: Local Development

1

Prerequisites

  • Node.js 20+
  • pnpm
  • PostgreSQL 15+ (pgvector enabled)
2

Clone and install

git clone https://github.com/getprofile/getprofile.git && cd
getprofile && pnpm install ```
</Step>

<Step title="Set up environment">
```bash
cp .env.example .env
Edit .env with your DATABASE_URL and LLM_API_KEY:
DATABASE_URL=postgresql://user:pass@localhost:5432/getprofile
LLM_API_KEY=sk-your-key-here  # Works with OpenAI, Anthropic, etc.
Optional: Set GETPROFILE_API_KEY to require authentication on the proxy.
Other settings like rate limiting, message retention, and provider configuration are now in config/getprofile.json. See Configuration.
3

Run migrations

bash pnpm db:migrate
4

(Optional) Load sample data

bash pnpm db:seed:sample Seeds a demo profile for smoke-testing the dashboard and API.
5

Configure API key (optional)

If you want to protect your proxy with an API key, set it in your .env: bash GETPROFILE_API_KEY=your-secret-key-here If not set, the proxy will accept all requests (useful for local development).
6

Start development server

pnpm dev

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Using the Proxy

Once running, update your OpenAI client to use GetProfile. Works with any LLM provider: 
import { GetProfileClient } from "@getprofile/sdk-js";

const client = new GetProfileClient({
  apiKey: process.env.GETPROFILE_API_KEY || "not-needed-for-local",
  baseURL: "http://localhost:3100/v1",
  defaultHeaders: {
    "X-GetProfile-Id": "user-123",
    "X-Upstream-Key": process.env.OPENAI_API_KEY,
    "X-Upstream-Provider": "openai",
  },
});

const response = await client.chat.completions.create({
  model: "gpt-5-mini",
  messages: [{ role: "user", content: "Hello!" }],
});
Headers: Provider headers (X-Upstream-Provider, X-Upstream-Key) override the config file. If not provided, GetProfile uses the default provider configured in config/getprofile.json.

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Customizing Extraction

GetProfile includes default trait schemas and prompts in the config/ directory: 
config/
├── getprofile.example.json     # Main configuration template
├── prompts/                     # LLM extraction prompts
│   ├── extraction.md           # Memory extraction prompt
│   ├── summarization.md        # Profile summarization prompt
│   └── trait-extraction.md     # Trait extraction prompt
└── traits/                      # Trait schema definitions
    └── default.traits.json     # Default trait schema

​
Customizing Traits

Edit config/traits/default.traits.json to define what GetProfile extracts from conversations: 
{
  "traits": [
    {
      "key": "communication_style",
      "valueType": "enum",
      "enumValues": ["technical", "casual", "formal"],
      "extraction": {
        "promptSnippet": "Identify the user's preferred communication style"
      },
      "injection": {
        "template": "User prefers {{value}} communication"
      }
    }
  ]
}

​
Customizing Prompts

Edit the markdown files in config/prompts/ to change how GetProfile:
  • Extracts memories from conversations (extraction.md)
  • Generates profile summaries (summarization.md)
  • Identifies trait values (trait-extraction.md)
For Docker: After modifying config files, rebuild and restart: 
docker compose -f docker/docker-compose.yml up -d --build

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Next Steps

How It Works

Understand the architecture

Integration Options

Compare proxy vs SDK

Configure Traits

Customize what GetProfile extracts

JavaScript SDK

Programmatic access from Node.js/TypeScript