Self-Hosting

Architecture Overview

A self-hosted Memwyre deployment consists of four primary components:

Backend API (memwyre-backend): The core FastAPI/Python service handling ingestion, search pipelines, and client requests.
Celery Worker (celery-worker): Resolves background tasks such as parsing web documents, downloading YouTube transcripts, and rebuilding relationship edges.
Database (postgres with pgvector): Stores relational structured data and high-dimensional semantic vector embeddings.
Cache & Queue (redis): Serves as the message broker for Celery and caching layer for rapid API queries.

                  ┌──────────────────────┐
                  │    Client / IDE      │
                  └──────────┬───────────┘
                             │
                             ▼
                  ┌──────────────────────┐
                  │   memwyre-backend    │
                  └─────┬──────────┬─────┘
                        │          │
                        ▼          ▼
                  ┌──────────┐ ┌──────────┐
                  │ postgres │ │  redis   │
                  └──────────┘ └────┬─────┘
                                    │
                                    ▼
                  ┌──────────────────────┐
                  │    celery-worker     │
                  └──────────────────────┘

Docker Compose Quickstart

Create a docker-compose.yml file in your installation directory:

version: '3.8'

services:
  db:
    image: pgvector/pgvector:pg16
    container_name: memwyre-db
    environment:
      POSTGRES_DB: memwyre
      POSTGRES_USER: memwyre_user
      POSTGRES_PASSWORD: super_secure_db_password
    ports:
      - "5432:5432"
    volumes:
      - pgdata:/var/lib/postgresql/data
    restart: unless-stopped
    healthcheck:
      test: ["CMD-SHELL", "pg_isready -U memwyre_user -d memwyre"]
      interval: 5s
      timeout: 5s
      retries: 5

  redis:
    image: redis:7-alpine
    container_name: memwyre-redis
    ports:
      - "6379:6379"
    volumes:
      - redisdata:/data
    restart: unless-stopped
    healthcheck:
      test: ["CMD", "redis-cli", "ping"]
      interval: 5s
      timeout: 5s
      retries: 5

  backend:
    image: ramblinghermit0403/memwyre-backend:latest
    container_name: memwyre-backend
    environment:
      - DATABASE_URL=postgresql://memwyre_user:super_secure_db_password@db:5432/memwyre
      - REDIS_URL=redis://redis:6379/0
      - SECRET_KEY=generate_a_random_jwt_secret_here
      - EMBEDDING_MODEL=nomic-embed-text
      - OLLAMA_HOST=http://host.docker.internal:11434
      - LLM_PROVIDER=ollama
      - LLM_MODEL=llama3
    ports:
      - "8000:8000"
    depends_on:
      db:
        condition: service_healthy
      redis:
        condition: service_healthy
    extra_hosts:
      - "host.docker.internal:host-gateway"
    restart: unless-stopped

  worker:
    image: ramblinghermit0403/memwyre-backend:latest
    container_name: memwyre-worker
    command: celery -A app.worker worker --loglevel=info
    environment:
      - DATABASE_URL=postgresql://memwyre_user:super_secure_db_password@db:5432/memwyre
      - REDIS_URL=redis://redis:6379/0
      - EMBEDDING_MODEL=nomic-embed-text
      - OLLAMA_HOST=http://host.docker.internal:11434
      - LLM_PROVIDER=ollama
      - LLM_MODEL=llama3
    depends_on:
      db:
        condition: service_healthy
      redis:
        condition: service_healthy
    extra_hosts:
      - "host.docker.internal:host-gateway"
    restart: unless-stopped

volumes:
  pgdata:
  redisdata:

Environment Variables

Configure these variables inside your .env file or docker-compose block:

Variable	Description	Default / Example
`DATABASE_URL`	SQLAlchemy-compatible connection string. If omitted, Memwyre defaults to local SQLite.	`postgresql://user:pass@db:5432/db` or `sqlite:///brain_vault.db`
`REDIS_URL`	Redis URL used for celery message passing and query cache.	`redis://redis:6379/0`
`SECRET_KEY`	Hex token used to sign authentication JWT keys.	`3a5d8f...` (Use `openssl rand -hex 32`)
`DEV_MODE`	If set to `True`, subscription checks are bypassed (unlimited usage gating).	`False`
`FREE_MEMORY_LIMIT`	Maximum memories allowed for a free user account.	`50`
`FREE_DOCUMENT_LIMIT`	Maximum documents allowed for a free user account.	`10`
`FREE_CHAT_LIMIT`	Maximum chats allowed for a free user account.	`30`
`MAX_CHARS_PER_MEMORY`	Character limit threshold for a single memory unit.	`25000`
`TURNSTILE_SECRET_KEY`	Cloudflare Turnstile token used for bot challenge validations.	`0x4AAAAAA...`
`DODO_PAYMENTS_API_KEY`	API authorization token for Dodo Payments gateway.	`dp_live_...`
`LLM_PROVIDER`	Language model platform. Options: `ollama`, `openai`, `anthropic`.	`ollama`
`LLM_MODEL`	Main inference model for relationship parsing and summarization.	`llama3` or `gpt-4o-mini`
`EMBEDDING_MODEL`	Model used to generate vector dimensions for retrieval.	`nomic-embed-text`
`OLLAMA_HOST`	Host URL pointing to your local Ollama runtime.	`http://host.docker.internal:11434`

Local LLM Setup (Ollama)

To run a zero-cloud setup, route all embedding and extraction tasks to Ollama.

Step 1: Install & Launch Ollama

Install Ollama on your host system (macOS, Windows, or Linux). Ensure Ollama runs locally by verifying:

curl http://localhost:11434/api/tags

Step 2: Download Required Models

Memwyre requires a dense vector embedding model and an inference model. Pull them using the CLI:

# Pull the semantic embedding model (768 dimensions)
ollama pull nomic-embed-text

# Pull the inference model for memory graph extraction
ollama pull llama3

Step 3: Run Docker Containers

Ensure extra_hosts is mapped to host.docker.internal:host-gateway in your docker-compose.yml so that Docker containers can contact your host’s Ollama port (11434). Spin up your cluster:

docker-compose up -d

Step 4: Verify Local Connection

Inspect logs to verify that Memwyre connects to Ollama successfully during startup:

docker logs memwyre-backend

If you see vector dimension initialisation messages pointing to nomic-embed-text, your offline memory vault is up and running! 🚀

Getting Started

MCP Server

Plugins

Concepts

Architecture Overview

Docker Compose Quickstart

Environment Variables

Local LLM Setup (Ollama)

Step 1: Install & Launch Ollama

Step 2: Download Required Models

Step 3: Run Docker Containers

Step 4: Verify Local Connection

​Architecture Overview

​Docker Compose Quickstart

​Environment Variables

​Local LLM Setup (Ollama)

​Step 1: Install & Launch Ollama

​Step 2: Download Required Models

​Step 3: Run Docker Containers

​Step 4: Verify Local Connection

Architecture Overview

Docker Compose Quickstart

Environment Variables

Local LLM Setup (Ollama)

Step 1: Install & Launch Ollama

Step 2: Download Required Models

Step 3: Run Docker Containers

Step 4: Verify Local Connection