森 forest

森 forest is a lightweight intelligence layer that manages your workspace knowledge directly from your chats, so that you don't have to.

Naturally, teams will share files from different platforms and discuss them in chat — forest listens and organizes.

Say sayionara to organizing these yourself (or even worse, having someone else organize them!); just let your teammates create/store them in their platforms of preference, and let 森 forest manage the rest.

Usage

Browse your workspace tree with @forest show, or fomd any file by context with @forest find.

Self Hosting

For full privacy, we let you host it — it's simple to set up, just follow the steps below.

Requirements

• Python 3.11+
• Poetry
• Docker (for local Postgres + pgvector)

Slack

Create a Slack app, add the required scopes and event subscriptions, then copy the bot token and signing secret into .env. Full walkthrough: docs/slack-app-setup.md.

Local setup

1. Copy environment template and fill in secrets:

   cp .env.example .env

   Set SLACK_BOT_TOKEN, SLACK_SIGNING_SECRET, LLM_API_KEY (or OPENROUTER_API_KEY), CHAT_MODEL_ID, and EMBEDDING_MODEL_ID. Default URL is OpenRouter; to use direct OpenAI or another OpenAI-compatible API instead, set LLM_BASE_URL — see docs/llm-configuration.md.

2. Run everything with Docker Compose (Postgres + Forest):

   docker compose up --build

   Or run only Postgres and use Poetry on the host:

   docker compose up -d postgres
   poetry install
   poetry run alembic upgrade head
   poetry run forest

   HTTP is on port 8000. GET /healthz for liveness, GET /ready for DB readiness.

3. Slack needs a public HTTPS URL. For local dev, use cloudflared:

   cloudflared tunnel --url http://127.0.0.1:8000

   Copy the https://….trycloudflare.com URL and set it as your Slack app's Event Subscriptions → Request URL (https://<tunnel-host>/slack/events).

Full local setup details (migrations, embedding dimensions, troubleshooting): docs/installation.md. LLM endpoints and model IDs: docs/llm-configuration.md.

Remote setup (AWS / GCP)

Forest is a single container + managed Postgres — the pattern is the same on any cloud:

1. Provision PostgreSQL with pgvector (RDS on AWS, Cloud SQL on GCP).
2. Push the Docker image to a container registry (ECR / Artifact Registry).
3. Deploy the container with environment variables pointing at the database and your Slack/LLM credentials (LLM_API_KEY or OPENROUTER_API_KEY; see LLM configuration).
4. Point Slack at the public HTTPS endpoint (https://<host>/slack/events).

	AWS	GCP
Database	RDS PostgreSQL 16 (CREATE EXTENSION vector)	Cloud SQL PostgreSQL 16 (cloudsql.enable_pgvector=on)
Compute	ECS Fargate + ALB, or App Runner	Cloud Run
Registry	ECR	Artifact Registry
HTTPS	ALB with ACM cert, or App Runner built-in	Cloud Run built-in
Secrets	Secrets Manager / SSM Parameter Store	Secret Manager

Full step-by-step CLI commands for both providers: docs/deployment.md.

Tests

poetry run pytest

For DB integration tests, set FOREST_RUN_DB_INTEGRATION=1 with Postgres running.

More Documentation

Longer-form docs (purpose, architecture, installation, LLM setup, FAQ) live under docs/.

License

森 forest is released under the GNU Affero General Public License v3.0 (AGPL-3.0).

This means you are free to use, modify, and self-host it — but if you distribute or run it as a network service, you must release your modifications under the same license.

TODOs

• Semantic search (@forest find) and pgvector ANN tuning (repository search, query embeddings, ANN index).
• Telemetry (/metrics, OpenTelemetry, or similar) and a small observability facade.