diff --git a/README.md b/README.md index 9c4f8bc..e3876f6 100644 --- a/README.md +++ b/README.md @@ -4,197 +4,214 @@ [](rust-toolchain.toml) [](https://crates.io/crates/omnigraph-cli) -**Lakehouse native graph engine built for context assembly** +**Lakehouse graph db for context assembly & multi-agent coordination** +Multimodal retrieval, Git-style branching, object storage-native -Omnigraph acts as operational state & coordination layer for agents. -Hundreds of agents can enrich the graph on parallel isolated branches and changes can be reviewed and merged safely. +Omnigraph is the operational state and coordination layer for fleets of agents. +Run it as a server, declared as code; hundreds of agents operate and enrich the graph on +parallel isolated branches, and every change is reviewed and merged safely. -- Git-style versioning & branching -- Multimodal retrieval (graph+vector/fts+filters) optimized for context assembly -- Runs on the local filesystem or any S3-compatible object store (AWS S3, R2, MinIO, RustFS) -- Native blob-as-data support (docs, images, videos, etc) -- VPC, On-prem, hybrid deployment -- [`Lance`](https://github.com/lance-format/lance) format as open storage layer +## Key capabilities -| AS CODE | What it means | +- **A graph server you run, declared as code** — a `cluster.yaml` declares graphs, schemas, stored queries, embedding providers, and policies. `cluster apply` converges it; `omnigraph-server` boots from it and brings every graph online at `/graphs/{id}/…`. +- **Built for fleets of agents** — hundreds of agents enrich the graph on **parallel isolated branches**; changes are reviewed and merged safely, Git-style, across the whole graph. +- **Multimodal retrieval for context assembly** — graph traversal + vector ANN + full-text + Reciprocal Rank Fusion in **one** query runtime. +- **Security as code** — Cedar policy enforced **server-side on every mutation**, per-graph and server-wide; bearer auth; actor/audit tracking. +- **Runs on your infrastructure** — any S3-compatible object store: **on-prem via RustFS / MinIO**, or AWS S3 / R2 / GCS. VPC, on-prem, hybrid — your data never leaves your store. +- **Open, versioned storage** — [`Lance`](https://github.com/lance-format/lance) columnar format: branchable, time-travelable, with native blob-as-data (docs, images, video). + +## What you can build + +| Use case | What it's for | |---|---| -| **Schema AS CODE** | Typed `.pg` schemas, planned, applied, enforced | -| **Context AS CODE** | Linted queries & agentic nudges, versioned and reusable | -| **Security AS CODE** | Cedar policies enforced server-side on every mutation | -| **Dashboards AS CODE** | Declarative views & controls over the graph *(coming)* | +| **Company brain** | Org knowledge unified into one graph every agent can query | +| **Agentic memory** | Durable, versioned memory — a branch per agent or per task, merged on review | +| **Context graph** | Decision traces and codified tribal knowledge for retrieval | +| **Dev graph** | Issues & dependency model that coding agents read and write | +| **R&D / ML data layer** | Experiments and trials written into branches, versioned for training & eval | -## Core Use Cases - -| Use case | What it's for -|---|---| -| **Company brain** | Org knowledge unified into one queryable graph | -| **Context graph** | Decision traces and codified tribal knowledge | -| **Agentic memory** | Durable, versioned memory for long-running agents | -| **Dev graph** | Issues & dependency model for coding agents | -| **R&D data layer** | Experiments & trials data written into branches | -| **ML workflows** | Versioned, branchable graphs for training & eval | -| **Karpathy's LLM wiki** | A living, agent-updatable knowledge base | - -## Quick Install +## Install ```bash curl -fsSL https://raw.githubusercontent.com/ModernRelay/omnigraph/main/scripts/install.sh | bash ``` -This installs `omnigraph` and `omnigraph-server` into `~/.local/bin` from -published release binaries. - -Or install with Homebrew: +This installs `omnigraph` (CLI) and `omnigraph-server` into `~/.local/bin` from +published release binaries. Or with Homebrew: ```bash brew tap ModernRelay/tap brew install ModernRelay/tap/omnigraph ``` -## Quick start +## Drive it with an AI agent -The fastest path is an **embedded, local file-backed graph** — no server, no -object store, no Docker: +Omnigraph is built to be run by coding agents — two ways in. -```bash -# A schema and one row of data -cat > schema.pg <<'PG' -node Person { - slug: String @key - name: String - title: String? -} -PG -echo '{"type":"Person","data":{"slug":"alice","name":"Alice","title":"Engineer"}}' > people.jsonl - -# Create → load (--mode is required) → query -omnigraph init --schema schema.pg ./graph.omni -omnigraph load --data people.jsonl --mode overwrite --store ./graph.omni -omnigraph query find_people --store ./graph.omni --params '{"t":"Engineer"}' \ - -e 'query find_people($t: String) { match { $p: Person { title: $t } } return { $p.name } }' - -# Branch, write in isolation, merge — Git-style across the whole graph -omnigraph branch create --from main review/new-hires --store ./graph.omni -omnigraph branch merge review/new-hires --into main --store ./graph.omni -``` - -**Storage backends** — the same flow runs on any backend; only the graph address changes: - -| Backend | Use it for | Graph address | -|---|---|---| -| **Embedded** (local filesystem) | dev, demos, single machine — the default | `./graph.omni` | -| **Object storage** (AWS S3, R2, GCS-S3) | shared, multi-host, durable | `s3://bucket/graph.omni` (+ the `AWS_*` env) | -| **RustFS / MinIO** | rehearse the S3 path locally, no cloud account | `s3://…` against a local endpoint → [deployment guide](docs/user/deployment.md#testing-against-s3-locally) | - -`init` takes the address as its positional argument (`omnigraph init --schema schema.pg
`); `load`, `query`, and `branch` take it via `--store `. - -For a **served, multi-graph deployment** (the cluster model), see [Common Commands](#common-commands) below. - -## Set it up with an AI agent - -Omnigraph is built to be set up by coding agents. Paste this into Claude Code, -Cursor, or any agent that can read a URL, install a package, and run a shell -command — it installs the skill, reads the docs, and walks you through setup for -your use case: - -```text -Help me set up Omnigraph (a lakehouse-native graph engine for agents). - -1. Install the Omnigraph skill so you operate it correctly: - npx skills add ModernRelay/omnigraph@omnigraph -2. Read the docs at https://github.com/ModernRelay/omnigraph — start with - docs/user/quickstart.md, then docs/user/clusters/index.md. -3. Skim the starter graphs and seed data in the cookbooks: - https://github.com/ModernRelay/omnigraph-cookbooks -4. Ask me what I want to build (company brain, agent memory, dev graph, - research / R&D layer, …). Then install the CLI, stand up a first graph for - that use case, load a little data, and run a query so I can see it working. -``` - -Works with any agent that can browse a URL, install a package, and run a shell. - -## Agent skill & starter graphs - -This repo ships the [**`omnigraph` agent skill**](skills/omnigraph) — the -operational playbook (cluster mode, the two config surfaces, schema evolution, -query linting, data writes, branches, Cedar policy, and common gotchas) that -teaches a coding agent to drive Omnigraph correctly. Install it with: +**Teach your agent the playbook.** This repo ships the +[**`omnigraph` agent skill**](skills/omnigraph): the operational playbook — +cluster mode, the two config surfaces, schema evolution, query linting, data +writes, branches, Cedar policy, and the common gotchas. ```bash npx skills add ModernRelay/omnigraph@omnigraph ``` +**Or have an agent set it up from scratch.** Paste this into Claude Code, +Cursor, or any agent that can read a URL and run a shell command: + +```text +Help me set up Omnigraph + +1. Read the docs at https://github.com/ModernRelay/omnigraph — start with + docs/user/clusters/index.md, then docs/user/deployment.md. +2. Skim the starter graphs and seed data in the cookbooks: + https://github.com/ModernRelay/omnigraph-cookbooks +3. Ask me what I want to build (company brain, agent memory, dev graph, + research / R&D layer, …). Then stand up a cluster for it, load a little + data, and run a query so I can see it working. +``` + For ready-to-run graphs with real seed data (company brain, VC operating system, pharma & industry intel), [`ModernRelay/omnigraph-cookbooks`](https://github.com/ModernRelay/omnigraph-cookbooks) -is the fastest way to see Omnigraph shaped to a real domain. To rehearse the S3 -path locally, see [deployment.md → Testing against S3 locally](docs/user/deployment.md#testing-against-s3-locally). +is the fastest way to see Omnigraph shaped to a real domain. -## Common Commands +## Deploy -A deployment is a **cluster**. A `cluster.yaml` declares its graphs, schemas, -stored queries, and policies; you converge it with `cluster apply` and serve it. -The server is cluster-first — it boots only from a cluster and serves every graph -under `/graphs/{id}/…`. Day-to-day work goes through that server: graphs are -addressed with `--server