* perf(engine): scope the CSR topology index to traversed edges, reuse it cross-branch The in-memory CSR graph index was built over every edge type in the catalog and cache-keyed by the resolved snapshot id, so a single-edge join (`$x identifiesPerson $p`) full-scanned every edge table in the graph (the 40-60s / 428s-first-traversal hang), and a lazy-fork branch cold-rebuilt main's index. Two cuts close that: - Scope (A2): build only the edge types the query traverses (`referenced_edge_types` over Expand/AntiJoin, exhaustive match), not the whole catalog. Threaded through GraphIndexHandle -> RuntimeCache; cache-keyed on the scoped set. - Cross-branch reuse (A1): key RuntimeCache by each edge table's physical identity (table_key, version, table_branch, e_tag) instead of the snapshot id, so a lazy-fork branch whose edge tables physically are main's reuses main's built index. Local-FS (e_tag None) falls back to refresh-invalidation. Adds graph_build_count/graph_edges_built probes for the cost tests. * test(engine): cost tests for scoped + cross-branch-reused topology index fresh_branch_traversal_reuses_main_graph_index (A1: a lazy-fork branch reuses main's cached CSR index, 0 rebuilds) and single_edge_query_builds_only_referenced_edge (A2: a one-edge query builds only that edge, not the whole catalog), via the graph_build_count/graph_edges_built probes. Forced CSR mode, #[serial]. Updates the recreated-branch incarnation test comment for the physical-identity key. * docs(engine): topology-index scoping + physical-identity cache key Document the scoped CSR build and the physical-identity (e_tag) graph-index cache key with its local-FS refresh-invalidation fallback across invariants, testing, execution, and architecture docs. * fix(test): move CSR-forced topology cost tests to the all-serial binary The two topology-build cost tests force OMNIGRAPH_TRAVERSAL_MODE via process- global env mutation, which query.rs reads. In warm_read_cost.rs (a mixed serial/non-serial binary) a concurrent non-serial traversal test could race the env write (UB under Rust 2024's unsafe set_var contract) and be forced onto CSR. Move them to traversal_indexed.rs — the dedicated all-serial binary with no non-serial env reader (its documented-safe home) — and add a ModeGuard RAII helper so a panic mid-test cannot leak the override. Addresses a PR review (P2). * fix(engine): include edge endpoints in the graph-index cache key The A1 physical-identity key omitted the edge's (from_type, to_type). GraphIndex keys its TypeIndexes by those endpoint names and execute_expand_csr looks them up by the current catalog's names, so a schema repoint of an edge type that leaves the edge table's physical identity unchanged would reuse a stale index built with the old endpoint namespace and fail with "no type index for <new type>". The old snapshot_id (carrying the manifest version) masked this; dropping it exposed it. Adding the endpoints to the key rebuilds on a repoint while preserving lazy-fork cross-branch reuse (same endpoints -> same key). Addresses a PR review (P1). * test(engine): scoped with_traversal_mode seam + e_tag graph-index coverage Replace the process-global OMNIGRAPH_TRAVERSAL_MODE env-mutation test hack (which forced #[serial] + dedicated all-serial binaries and was triplicated as ModeGuard + set_mode/clear_mode) with one general abstraction: a task-local `with_traversal_mode` seam mirroring `with_query_io_probes`. It is scope-bound (leak-free even on panic) and process-safe (never touches shared state), so a forced-mode test cannot affect a concurrent test in the same binary. `traversal_indexed_override` consults the seam first, then the env var (which stays the documented ops escape hatch). - Migrate traversal_indexed.rs, proptest_equivalence.rs, and the two topology cost tests (moved back to warm_read_cost.rs) to the seam; drop all ModeGuard / set_mode / clear_mode / #[serial] / per-file column0 helpers. - Consolidate the duplicated first-column extractors into one shared `helpers::first_column_sorted`. - Add `s3_storage.rs::s3_fresh_branch_traversal_reuses_main_graph_index_with_etags`: the CSR cache-key cross-branch reuse path on a REAL per-table e_tag (None on local FS, so local tests can't reach it). Confirmed empirically that RustFS — the CI S3 backend — surfaces ETags into version_metadata.e_tag(). CI path filter now triggers the rustfs job on runtime_cache/graph_index changes. |
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|---|---|---|
| .cargo | ||
| .context | ||
| .github | ||
| assets | ||
| crates | ||
| docker | ||
| docs | ||
| scripts | ||
| skills/omnigraph | ||
| .dockerignore | ||
| .gitignore | ||
| AGENTS.md | ||
| Cargo.lock | ||
| Cargo.toml | ||
| CLAUDE.md | ||
| CODE_OF_CONDUCT.md | ||
| CONTRIBUTING.md | ||
| Dockerfile | ||
| GOVERNANCE.md | ||
| LICENSE | ||
| og-cheet-sheet.md | ||
| omnigraph.example.yaml | ||
| openapi.json | ||
| README.md | ||
| rust-toolchain.toml | ||
| SECURITY.md | ||
Lakehouse graph database for context assembly & multi-agent coordination
Multimodal retrieval · Git-style branching · object-storage native
Quickstart · Docs · Cookbooks · CLI
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.
Key capabilities
| Capability | What it gives you |
|---|---|
| Declared as code | A cluster.yaml declares graphs, schemas, stored queries, embedding providers, and policies; cluster apply converges it and omnigraph-server 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 | Graph traversal + vector ANN + full-text + Reciprocal Rank Fusion in one query runtime, for context assembly. |
| 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 columnar format: branchable, time-travelable, with native blob-as-data (docs, images, video). |
What you can build
| Use case | What it's for |
|---|---|
| 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 |
Install
curl -fsSL https://raw.githubusercontent.com/ModernRelay/omnigraph/main/scripts/install.sh | bash
This installs omnigraph (CLI) and omnigraph-server into ~/.local/bin from
published release binaries. Or with Homebrew:
brew tap ModernRelay/tap
brew install ModernRelay/tap/omnigraph
Set it up with an AI agent
Omnigraph is built to be run by coding agents. Two ways in:
Teach your agent the playbook. This repo ships the
omnigraph agent skill: the operational playbook
covering cluster mode, the two config surfaces, schema evolution, query linting,
data writes, branches, Cedar policy, and the common gotchas.
npx skills add ModernRelay/omnigraph@omnigraph
Or have an agent set it up from scratch. Paste this into Claude Code, Codex, or any agent that can read a URL and run a shell command:
Help me set up Omnigraph
1. Read the docs at https://github.com/ModernRelay/omnigraph, starting 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
is the fastest way to see Omnigraph shaped to a real domain.
Deploy
A deployment is a cluster: a multigraph config directory that declares
its graphs, schemas, stored queries, and policies as code. You manage it
Terraform-style: cluster plan previews the diff, cluster apply converges
it. omnigraph-server then boots from the cluster and brings every graph online
at /graphs/{id}/…, each behind its own policy.
1. Declare the cluster.
company-brain/
├── cluster.yaml
├── people.pg # schema for the "knowledge" graph
├── queries/ # stored queries: the .gq files ARE the declaration
│ └── people.gq
└── base.policy.yaml # a Cedar policy bundle
# cluster.yaml
version: 1
metadata:
name: company-brain
storage: s3://company/clusters/company-brain # ledger, catalog, and graph data live here
graphs:
knowledge:
schema: people.pg
queries: queries/ # every `query <name>` in queries/*.gq registers
policies:
base:
file: base.policy.yaml
applies_to: [knowledge] # graph-bound; use [cluster] for server-level
2. Stand up your object store. On-prem, run RustFS (or MinIO); Omnigraph
writes Lance to it over the standard S3
API. In the cloud, point the same AWS_* env at S3 / R2 / GCS instead.
3. Converge and run. apply creates each graph, applies its schema, and
publishes queries and policies into the content-addressed catalog. It is
idempotent; re-running is always safe.
omnigraph cluster validate # parse + typecheck everything
omnigraph cluster plan # preview what apply would do
omnigraph cluster apply # converge
# Boot the server from the cluster dir; storage resolves through cluster.yaml
omnigraph-server --cluster company-brain --bind 0.0.0.0:8080
See the cluster guide for the day-2 loop
(edit → plan → apply → restart), approval gates for destructive changes, drift
inspection, and recovery; the deployment guide for
containers, AWS/Railway, auth, and the full AWS_* contract.
Query and mutate
Set a default server and graph once in ~/.omnigraph/config.yaml, and the
everyday commands stay short. Stored queries and mutations run by name:
omnigraph query search_docs --params '{"q":"AI safety"}'
omnigraph mutate add_person --params '{"name":"Mina"}'
# Branch, review, merge across the whole graph; agents write in isolation
omnigraph branch create --from main agent/ingest-42
omnigraph branch merge agent/ingest-42 --into main
An alias is shorter still: bind a server, graph, and stored query to one
name, then omnigraph alias triage runs it. For an ad-hoc target, any command
still takes --server <name|url> --graph <id> (or --store <uri> for a local
graph). See the CLI reference.
Security & governance
- Engine-wide enforcement: every write path goes through the same Cedar gate, so the HTTP server, the CLI, and the embedded SDK obey identical rules.
- Declared in the cluster: a policy bundle is bound to graphs (or the whole server) via
policies:→applies_to. - Scoped: rules apply per graph, per branch, or server-wide.
- No plaintext tokens: bearer tokens are hashed at startup and compared in constant time.
- Forge-proof identity: the actor is resolved server-side from the token; clients can't set it.
See the policy guide.
Clients & SDKs
| Client | Use it for | Where |
|---|---|---|
| TypeScript SDK | typed access from Node / TS | @modernrelay/omnigraph · source |
| MCP server | bridge Omnigraph to LLM hosts (Claude, Codex, …) | @modernrelay/omnigraph-mcp |
| HTTP / OpenAPI | any language, the wire contract | the server's OpenAPI spec |
| Python SDK | typed access from Python | coming soon |
Both npm packages are versioned in lockstep with omnigraph-server.
Local quick test (no server)
1-min setup to try it: an embedded, local file-backed graph (no server, no object store). For dev and experiments; production is the deployed cluster above.
cat > schema.pg <<'PG'
node Signal { slug: String @key, title: String }
node Pattern { slug: String @key, name: String }
edge Indicates: Signal -> Pattern
PG
printf '%s\n' \
'{"type":"Signal","data":{"slug":"s1","title":"OSS model adoption surging"}}' \
'{"type":"Pattern","data":{"slug":"p1","name":"adoption"}}' \
'{"edge":"Indicates","from":"s1","to":"p1"}' > data.jsonl
omnigraph init --schema schema.pg ./graph.omni
omnigraph load --data data.jsonl --mode overwrite --store ./graph.omni
# "What pattern does signal s1 indicate?"
omnigraph query --store ./graph.omni \
-e 'query indicates() { match { $s: Signal { slug: "s1" } $s indicates $p } return { $p.name } }'
# → adoption
Docs
Build And Test
cargo build --workspace
cargo test --workspace
Notes:
- Rust stable toolchain, edition 2024
- CI runs
cargo test --workspace --locked - Full CI and some local test flows require
protobuf-compiler - S3 integration tests expect an S3-compatible endpoint such as RustFS
Workspace Crates
crates/omnigraph-compiler: shared schema/query parser, typechecker, catalog, and IR lowering (zero Lance dependency)crates/omnigraph(packageomnigraph-engine): storage/runtime, branching, merge, change detection, query execution, and embeddingscrates/omnigraph-policy: Cedar policy compilation and enforcementcrates/omnigraph-api-types: shared HTTP wire DTOs used by both the server and the CLIcrates/omnigraph-cluster: cluster config validation, planning, and apply (the control plane)crates/omnigraph-server: Axum HTTP server, cluster-first, runs N graphs under/graphs/{id}/…crates/omnigraph-cli: CLI for graph lifecycle, query/mutate, branch/commit/merge, schema/lint, snapshot/export, cluster control, policy/queries, profiles, and maintenance
Contributing
Please open an issue, spec, or design discussion before sending large code changes. Design feedback and concrete problem statements are the fastest way to collaborate on the roadmap.
Community
Join the Omnigraph Slack community to ask questions, share feedback, and follow development.