relay-knowledge
relay-knowledge is a local-first knowledge substrate for graph-backed
retrieval. It stores evidence, graph facts, code-repository structure, derived
indexes, freshness state, diagnostics, worker proposals, audit records, and
agent-facing context packs. It does not try to be a general agent runtime or
final-answer generator.
Quick Start
The default local profile is zero configuration: runtime directories are resolved from platform defaults, SQLite is used locally, and deterministic semantic/vector read models are enabled without external services.
Use JSON output when scripting:
Installing Releases
Stable releases are distributed through GitHub Releases with prebuilt archives
for Linux x64/ARM64, macOS Intel/Apple Silicon, and Windows x64/ARM64. Verify
the downloaded archive with checksums.txt before placing the binary on your
PATH. GitHub artifact attestations cover the same archive digests and can be
verified with gh attestation verify <artifact> -R coolplayagent/relay-knowledge.
Windows ARM64 archives are produced by the release workflow as
cross-built artifacts until native Windows ARM64 CI runners are available.
Rust users can install the crate from crates.io:
What Works Today
- Hybrid GraphRAG context packs with BM25, local semantic signatures, local hashed-vector retrieval, graph evidence fallback, schema paths, temporal/community context, freshness metadata, truncation state, and ranking explanations.
- Structured graph facts for evidence, entities, typed relations, claims, events, source spans, confidence, graph versions, and accepted/proposed grounding status.
- Code repository registration, tree-sitter indexing, full and incremental refresh, worktree overlay indexing, symbol/reference/chunk retrieval, and impact analysis.
- Local file-location indexing without Everything, Spotlight, Windows Search, locate, or other external search software: explicitly scan authorized roots and use SQLite/FTS5 to quickly find files by name, path, extension, and directory.
- Bounded index refresh queues, persistent leases, retry/dead-letter handling, startup reconciliation, stale diagnostics, and scoped cursor metadata.
- Worker queues, deterministic fallback proposals, manual proposal acceptance, persistent audit events, silent-update operator state, and service definition generation for platform service managers.
- MCP Streamable HTTP and local ACP adapter access through the shared application service, with scope policy, QoS admission, cancellation, resources/prompts, durable audit metadata, and OTLP-ready agent metrics.
- Real OTLP HTTP/protobuf traces and metrics export for resident service mode, with local diagnostics when Collector export fails.
- Static Web diagnostics, categorized agent/model settings, persisted model
provider profiles, and operation composers served by the Rust HTTP service on
the same local port as
/api/*and MCP when enabled. - Setup diagnostics and named setup profiles for local, read-only agent, platform service, and external embedding configurations.
Documentation
- Documentation Bookshelf: book-style entry point for the user guide, implemented capabilities, architecture specs, research, benchmarks, and verification records.
- Book 1, Chapter 0: User Guide: executable local workflows for install/runtime directories, CLI output modes, knowledge graphs, code repository graphs, Web operations, MCP/ACP access, resident services, troubleshooting, and advanced configuration.
- Book 4, Chapter 1: 2026 Industry Capability Snapshot: current GraphRAG, MCP, A2A, hosted retrieval, and graph-agent ecosystem signals, plus relay-knowledge gaps.
- Book 4, Chapter 4: ai-knowledge-graph Reference Analysis: architecture, algorithm, performance, and reliability lessons from an external LLM-extracted knowledge graph project.
- Book 4, Chapter 8: Competitive, High-Performance, and Local File Retrieval Research: broader paper and industry-system references for GraphRAG, hybrid search, vector indexes, code search, fast local file retrieval, graph storage, and SRE.
- Book 2, Chapter 1: Capability Overview: foundational behaviors and competitive differentiators.
- Book 2, Chapter 4: Query and Context Pack Basics: query metadata, context items, budgets, truncation, and source spans.
- Book 2, Chapter 5: Hybrid Retrieval Advantage: BM25, semantic, vector, graph evidence, code graph, RRF, and ranking explanations.
- Book 2, Chapter 9: Code Graph Competitive Features: symbols, references, calls, imports, chunks, identities, and edge diagnostics.
- Book 2, Chapter 13: Agent Access Capabilities: MCP Streamable HTTP, resources, prompts, ACP session access, scope policy, and audit.
- Appendix A.5: Competitive and High-Performance Benchmark Targets: metric targets for graph, code, local file, indexing, and worker performance gates.
- Appendix B.1: Documentation Refresh Audits: dated verification records for documentation freshness and implemented capability closures.
Key specs:
- Book 3, Chapter 1: Architecture Vision and Algorithm Map
- Book 3, Chapter 2: Engineering Hard Constraints
- Book 3, Chapter 9: Hybrid Retrieval and Context Packing
- Book 3, Chapter 13: Code Retrieval Ranking and Impact Analysis
- Book 3, Chapter 15: Resident Agent Graph Access Protocol
- Book 3, Chapter 19: Installation, Release, and Upgrade
Development
Use the repository scripts by responsibility:
For unattended code and semantic/vector retrieval optimization experiments, the independent self-iteration loop can be started with:
It stores run history, reports, patches, and score curves under
.git/relay-knowledge-self-iteration/ and only commits candidates that improve
the configured score. The semantic/vector fixture inherits the same
RELAY_KNOWLEDGE_* embedding environment as normal runtime commands and does
not persist secrets in benchmark cases.
The underlying quality gates are:
The binary starts a Tokio runtime, and the shared application service exposes async entrypoints from the CLI boundary inward.
SQLite storage is opened through the storage boundary, and blocking database work is isolated behind Tokio blocking workers.
The storage contract also includes the v1 code graph data surface for tree-sitter output: versioned code files, symbols, references, chunks, and parse-status diagnostics are committed through storage traits rather than direct SQLite access.
Code repository indexing currently parses Rust, Python, JavaScript/JSX, TypeScript/TSX, Go, Java, Kotlin, Scala, C, C++, C#, Ruby, PHP, Swift, and Bash with tree-sitter grammars, falling back to text chunks for unsupported or degraded files. Full repository indexing uses resource-bounded SQLite batches with durable checkpoints and a finalize phase for cross-batch references, includes, and call edges, so large scopes expose indexing progress without replacing the previous fresh scope until finalization succeeds. Git branch, tag, and worktree selectors resolve to scoped commit/tree snapshots; indexed scopes remain queryable by explicit ref, rebase or force-moved heads require a new index before query, and same-tree branches reuse the same scope while preserving requested-ref audit metadata. Registering the same repository root with an additional alias preserves prior aliases and resolves all aliases to the same repository id.
Code graph v1 responses distinguish stable canonical_symbol_id values from snapshot-bound symbol_snapshot_id values. Reference, call, and import hits expose target_hint, resolution_state, confidence basis points, and confidence tier so unresolved or ambiguous edges are visible instead of being reported as certain calls.
Code repository lexical retrieval uses a SQLite FTS candidate table for symbols, references, calls, imports, and chunks. Effective path filters are applied inside the FTS candidate window before bounded scoring, graph-edge candidates are ordered by BM25 before truncation, fuzzy symbol recall can match any query term while typed graph edge queries keep their narrower semantics, and Rust scoring recognizes snake_case/CamelCase identifier parts, multi-part symbol names, call-direction context, and declaration-shaped API chunks. Call excerpts use a source_scope + symbol_snapshot_id chunk lookup and line containment so high fan-out caller/callee queries do not multiply one call edge across unrelated chunks.
Hybrid retrieval uses SQLite-backed BM25, local semantic token signatures, local hashed-vector ANN, configurable external semantic/vector backend metadata, graph evidence fallback, schema-guided path traversal, temporal event retrieval, community summaries, and code graph documents. It fuses candidates with reciprocal-rank fusion, applies a deterministic local rerank before final truncation, and returns a context pack with retriever sources, ranking and rerank explanations, entities, source spans, structured graph facts, direct graph path evidence, code artifacts, backend availability, freshness, truncation, and budget metadata. The BM25 read model indexes generated lexical aliases for entity labels and code symbols without returning those aliases as canonical labels.
Evidence can carry multimodal extraction metadata for text spans, image assets, OCR text, captions, image embeddings, tables, and layout regions. Derived OCR/caption/image evidence references a parent evidence item, retrieval groups those hits by parent to avoid duplicate context items, and background or maintenance workers commit OCR/caption/table/layout outputs through commit_multimodal_extraction rather than query hot paths.
Operational productization persists worker tasks, manual proposals, audit events, and silent-update operator state. Multimodal ingest queues embedding/OCR/vision/extractor work; worker run-once calls a configured HTTP endpoint when available or creates a deterministic fallback proposal; proposal accept commits through the same graph mutation path; and service manager commands generate platform service definitions without running privileged installation.
The evaluation module provides a pure GraphRAG harness plus a CI fixture gate for exact fact, multi-hop, temporal, negative rejection, stale index, ambiguous entity, and code impact observations.
Graph commits also persist Phase 2 index recovery metadata: mutation log entries record affected scopes, entity ids, evidence ids, and source hashes, including scope moves and structured-fact evidence references; scoped index cursors track kind/scope/modality freshness plus source hash, backend cursor, and optional model name/dimension metadata for semantic/vector workers; and ingest, query --freshness wait-until-fresh, index refresh, health, and service doctor share the bounded refresh queue, active lease/attempt guards, retry/dead-letter, and stale diagnostics path. Diagnostic reconcilers preserve dead-letter isolation, explicit refresh paths surface queue-cap failures instead of reporting false freshness, and index_refresh.stale_reasons explains index-family and scoped-cursor lag or failure by kind, scope, modality, lag versions, and last error.
Current CLI commands use the compiled relay-knowledge binary with git-style subcommands:
RELAY_KNOWLEDGE_FILE_INDEX_ROOTS=/opt/docs
RELAY_KNOWLEDGE_MCP_ALLOWED_SCOPES=docs
CLI parameter meaning is part of the public contract. Skills and other LLM tools
should inspect relay-knowledge help --format json before issuing commands; it
describes each command path, operation, read/write effect, required parameters,
defaults, allowed values, repeatability, examples, and notes.
Local file indexing roots must be absolute and present in
RELAY_KNOWLEDGE_FILE_INDEX_ROOTS; relative entries are rejected before a
background or explicit scan starts. RELAY_KNOWLEDGE_FILE_INDEX_SCAN_TIMEOUT_MS
sets the per-root scan timeout budget.
Semantic/vector read-model backend metadata is configured only through the
env boundary. The default mode is local deterministic read models; external
worker metadata can be selected with:
RELAY_KNOWLEDGE_SEMANTIC_BACKEND=external
RELAY_KNOWLEDGE_VECTOR_BACKEND=external
RELAY_KNOWLEDGE_LLM_PROVIDER=openai_compatible
RELAY_KNOWLEDGE_EMBEDDING_BASE_URL=https://api.example.com/v1
RELAY_KNOWLEDGE_EMBEDDING_API_KEY=...
RELAY_KNOWLEDGE_TEXT_EMBEDDING_MODEL=text-embed-3-small
RELAY_KNOWLEDGE_IMAGE_EMBEDDING_MODEL=clip-vit-b32
RELAY_KNOWLEDGE_EMBEDDING_DIMENSION=1536
RELAY_KNOWLEDGE_SEMANTIC_BACKEND and
RELAY_KNOWLEDGE_VECTOR_BACKEND also accept local and disabled. Disabled
read-model backends are excluded from semantic/vector retrieval execution and
refresh scheduling; blank embedding model names fail during runtime
configuration.
The Web Settings page groups agent interoperability, retrieval defaults, and
model providers. Agent/retrieval settings read the same redacted runtime and
service diagnostics to prepare MCP exposure, scope policy, audit, and external
model environment variables, including the configured MCP origin allow-list.
Model provider settings manage named chat/completion profiles, fallback
policies, catalog refresh from models.dev, endpoint probes, and model
discovery through /api/configs/model/*. Profile and fallback files live under
the resolved config directory as model-profiles.json and
model-fallback.json; the public catalog cache lives under the resolved cache
directory as model-catalog-cache.json. Secret values are accepted only on save
and are returned to the browser as configured booleans or redacted headers.
Profile updates preserve redacted stored header secrets unless a replacement
value is supplied, and API callers can set clear_api_key=true to explicitly
remove a stored API key during header-only migrations.
The CLI ingest command writes evidence plus entity labels. The shared API also
accepts richer Phase 1 graph facts for adapters: evidence source_path, source
span, confidence, lifecycle status, typed relations, claims, and events that
reference evidence ids. Structured facts must cite supporting evidence, supplied
confidence, span, and version-range fields are revalidated after deserialization,
and retrieval only uses accepted or proposed evidence as context. Context
pack items now expose direct graph_paths derived from those structured facts
so agent callers can cite one-hop relation, claim, or event paths alongside raw
fact provenance.
service run --web --mcp streamable-http starts the same-port Web diagnostics,
/api/*, and resident MCP Streamable HTTP adapters on the configured local HTTP
bind, defaulting to http://127.0.0.1:8791/ and
http://127.0.0.1:8791/mcp. MCP is disabled unless requested by the command or
RELAY_KNOWLEDGE_MCP_STREAMABLE_HTTP_ENABLED=true; graph tools require
RELAY_KNOWLEDGE_MCP_ALLOWED_SCOPES unless
RELAY_KNOWLEDGE_MCP_ALLOW_UNSPECIFIED_SCOPE=true is explicitly configured or
the requested scope matches a code repository alias already registered in this
runtime. Registered repository aliases are promoted into a process-local MCP
allow-list on first use; unknown scopes are still rejected with the missing
scope and the exact RELAY_KNOWLEDGE_MCP_ALLOWED_SCOPES=<scope> repair hint.
The adapter validates initialize params, then issues an unpredictable
Mcp-Session-Id. Clients must send notifications/initialized, then include
that session header and MCP-Protocol-Version on later calls so ping, tool
requests and notifications/cancelled stay bound to the issued session.
Missing session headers are rejected with HTTP 400; unknown or evicted session
IDs are rejected with HTTP 404.
The MCP tool surface includes graph retrieval, graph inspection, health,
service status, index status, authorized code graph queries, and authorized
code impact analysis. MCP does not expose index refresh or repository indexing;
run relay-knowledge repo index, relay-knowledge repo update, or
relay-knowledge index refresh from an explicit CLI/Web workflow before MCP
queries depend on fresh indexes.
The MCP server also advertises resources and prompts: resources expose service
status, health, index status, and Prometheus text metrics; the graph-wide
summary resource is advertised only when
RELAY_KNOWLEDGE_MCP_ALLOW_UNSPECIFIED_SCOPE=true. Prompts provide retrieval
and code-impact planning templates. /mcp/metrics exports a
small Prometheus-compatible snapshot for graph version, index refresh backlog,
dead letters, QoS request counts, and per-index stale state.
Agent requests write bounded in-process audit events with runtime identity,
scope, freshness, QoS decision, budget, truncation, result count, and status.
Set RELAY_KNOWLEDGE_AGENT_AUDIT_SINK_ENABLED=true to mirror those events to
the path-owned JSONL file logs/agent-audit.jsonl; the sink uses a bounded
async queue controlled by RELAY_KNOWLEDGE_AGENT_AUDIT_QUEUE_DEPTH and capped
at 65536 entries.
The local ACP session adapter exposes the same retrieval contract for
agent-client sessions, including progress updates, cancellation, and context
artifacts. Foreground service startup runs a recovery pass that refreshes stale
index cursors before accepting resident adapter work.
Web diagnostics, operation workspace, and browser integration checks:
The static Web workspace renders project health, GraphRAG readiness, graph
counts, a compact SVG graph overview for evidence/code/index/worker topology,
the interactive Graph canvas, scoped index freshness, refresh queue diagnostics,
stale reasons, runtime budgets, and interactive operation composers for
retrieval, ingestion, graph inspection, code repository workflows, index refresh,
provider probes, worker/proposal/audit operations, service runtime commands,
agent interoperability settings, retrieval defaults, and model provider profile
management. The same Rust HTTP service serves static Web assets plus
/api/project/status, /api/health, /api/service/status, and
/api/web/operations/execute on one local port. The execute endpoint accepts
the current composer snapshot, calls the shared application service, and returns
operation metadata plus result JSON for the page to display. Web service run
returns a service runtime snapshot rather than starting a resident loop from the
browser. Web execute requests are bounded by
RELAY_KNOWLEDGE_HTTP_MAX_BODY_BYTES, and non-loopback HTTP binds require the
remote-client access policy to be enabled explicitly.
Optional local hooks: