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ContextLattice

sheawinkler/contextlattice
113HTTPregistry active
Summary

ContextLattice gives your MCP clients persistent memory through a local-first orchestration layer. It exposes unified write/read endpoints for durable context storage, staged retrieval across vector lanes (Qdrant, pgvector, topic rollups), and a memory graph API for explicit and inferred relationships between entities. The Go/Rust runtime handles ingestion fanout and degradation policies while keeping everything on your machine by default. Reach for this when you need your agents to remember across sessions without sending context to external services, or when you want typed memory edges and semantic neighbor queries beyond simple RAG. Ships with Docker Compose profiles from lite (8GB RAM) to full operator stacks, plus CLI tools for checkpointing and search.

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ContextLattice

ContextLattice architecture overview

Private-by-default memory and context orchestration for AI agents.

MCP HTTP Gateway Docker Compose BSL 1.1

context-lattice MCP server

What ContextLattice Does

ContextLattice provides a single memory contract for agentic systems:

  • Unified write/read contract for memory and context.
  • Durable fanout across retrieval/storage lanes.
  • Staged retrieval (fast now, deep continuation when needed).
  • Agent sessions that turn prior work, objective lineage, graph touches, skills, checkpoints, and handoffs into prompt-ready packages and exportable run cards.
  • Go/Rust runtime ownership for the active application path.
  • Legacy Python runtime archived under archive/services/orchestrator_legacy_python for tooling/test compatibility only.
  • Local-first deployment with optional hosted surfaces.

Current Public Baseline

v3.4.2 is the public agent runtime contract baseline: universal adapter lifecycle, native agent sessions, objective runtime state, scoped recall, checkpoints, handoffs, completion flow, runtime telemetry, one-command runtime proof, storage-governance hardening, and local session-store diagnostics behind one local contract.

v4 remains the private tuning lane for experiments that still need benchmark, recall, and soak gates before public promotion.

Public Runtime Stack (v3.4)

  • Ingress: gateway-go.
  • Core memory + retrieval lanes: Go + Rust services.
  • Degradation policy: fail-open retrieval with continuation lifecycle.
  • Tooling compatibility: MCP + HTTP clients.
  • Single-container lite builds (Dockerfile.hf-lite) also run gateway-go (no Python runtime dependency).
  • Public single-container lite vector default: topic_rollups only.
  • Public local lite core default: topic_rollups + qdrant; pgvector and memory-bank spike adapters are not started by default.
  • Public local lite advanced: opt-in adapter lab via gmake mem-up-lite-advanced.
  • Full/operator stacks: Qdrant remains the primary vector-native lane; pgvector stays supported for SQL-co-located vector workloads.

Quickstart

1) Clone and configure

git clone git@github.com:sheawinkler/ContextLattice.git
cd ContextLattice
cp .env.example .env

2) Launch (recommended)

gmake quickstart

gmake quickstart prompts for runtime profile and then launches the selected stack.

3) Verify

curl -fsS http://127.0.0.1:8075/health | jq
scripts/agent/agent-runtime-proof-pack --pretty
scripts/agent/agent-adoption-proof-matrix --skip-provider-smoke --progress --pretty

Expected:

  • /health returns {"ok": true, ...}
  • agent-runtime-proof-pack completes bootstrap, scoped recall, checkpoint, handoff, completion, status, prompt context package, and runtime telemetry phases.
  • agent-adoption-proof-matrix verifies configured agent profiles and reports the skills, context, session, graph, and handoff evidence shaping each run, with trace commands for run-card export.

Model Runtime

Task inference defaults to ORCH_INFER_PROVIDER=auto. gateway-go detects the host profile and probes local backends before selecting a route.

  • Apple Silicon default priority: mlx,vllm-metal,ane_sidecar,llama-cpp,ollama.
  • CUDA/ROCm default priority: sglang,vllm,openai-compatible,llama-cpp,lmstudio,ollama.
  • Generic CPU default priority: openai-compatible,llama-cpp,lmstudio,ollama.
  • Supported provider ids include sglang, vllm, vllm-metal, mlx, mtplx (alias for MLX), openai-compatible, lmstudio, llama-cpp, tgi, tensorrt-llm, ane_sidecar, and ollama.
  • /v1/inference/runtime-policy returns live provider health plus resource-aware model guidance. If host memory/VRAM is not identifiable, it falls back to generic local advice: start with Q4/IQ4 7B-9B models, benchmark, then scale up.
  • The current opt-in local model shortlist lives in docs/runtime/local-model-options.md; it includes small/medium MLX, GGUF, and HF/safetensors candidates plus frontier-provider connection guidance. GGUF models use an external llama.cpp-compatible connector; ContextLattice does not start or bundle llama.cpp in Lite.
  • Large Qwen3.6 Dream Mode models are opt-in only; ContextLattice does not bundle or pull them by default. The default GGUF recommendation is mudler/Qwen3.6-35B-A3B-Claude-4.7-Opus-Reasoning-Distilled-APEX-MTP-GGUF for llama.cpp-compatible advanced users. Abliterated variants are private-eval only behind CONTEXTLATTICE_DREAM_ALLOW_PRIVATE_EVAL_MODELS=true (GO_DREAM_ALLOW_UNCENSORED_MODELS=true remains a legacy alias).
  • Inference runtimes must emit final assistant content through their API. Reasoning-only responses fail with repair instructions instead of being accepted. For MLX Qwen thinking templates, use scripts/inference_mlx_server.sh --model /path/to/mlx/model --template-profile qwen-final-content, then verify with scripts/inference_template_conformance.sh --provider mlx --model /path/to/mlx/model.
  • Dream Mode reflects on LLM-generated hypotheses by default and performs one bounded deepening pass when the best output misses the sigma target (GO_DREAM_REFLECT_ENABLED=true, GO_DREAM_DEEPEN_ON_WEAK_OUTPUT=true, GO_DREAM_REFLECTION_MIN_SCORE=0.74). If structured LLM synthesis is unavailable, Dream Mode returns dream_unavailable; non-LLM evidence packaging belongs to context-pack or review.
  • Ollama remains a compatibility fallback, not the preferred always-on embedding path.
  • Local helpers enforce one active LLM backend by default (CONTEXTLATTICE_SINGLE_ACTIVE_INFER_BACKEND=true).

Inspect live routing and benchmark configured backends:

scripts/inference_runtime_policy.sh
scripts/benchmark_inference_backends.sh
scripts/inference_template_conformance.sh --provider mlx --model /path/to/mlx/model

Embedding defaults to the Rust fastembed-rs sidecar. Ollama stays available as an explicit compatibility fallback, not the preferred embedding path.

Useful model runtime knobs:

ORCH_INFER_PROVIDER=auto
ORCH_INFER_PROVIDER_PRIORITY=mlx,vllm-metal,ane_sidecar,sglang,vllm,openai-compatible,llama-cpp,ollama
ORCH_INFER_AUTO_PROBE_ENABLED=true
SGLANG_BASE_URL=http://127.0.0.1:30000
VLLM_BASE_URL=http://127.0.0.1:8000
VLLM_METAL_BASE_URL=http://127.0.0.1:8000
MLX_API_BASE=http://127.0.0.1:18087/v1
LLAMA_CPP_BASE_URL=http://127.0.0.1:8080

Agent CLI

Installer and quickstart paths install agent helpers under ~/.contextlattice/bin.

contextlattice_agent_adapter profiles
contextlattice_adopt status --pretty
contextlattice_doctor --agents codex --skip-provider-smoke --pretty
contextlattice_agent_start --soft --compact
contextlattice_agent_trace --session-id <session-id> --tree
contextlattice_pack "what should the next agent know?" --project my-project --pretty
contextlattice_search -h
contextlattice_write -h
contextlattice_checkpoint -h
contextlattice_skills_index search "browser automation" --pretty
  • contextlattice_agent_adapter is the first-class lifecycle helper for bootstrap, context-pack, checkpoint, handoff, event, and completion flows.
  • contextlattice_adopt is the zero-friction front door for local readiness, install guidance, profiles, and lifecycle proof; contextlattice_doctor combines readiness, proof, and trace evidence in one bounded report.
  • contextlattice_agent_start runs the lightweight startup guard for agents.
  • contextlattice_agent_trace renders the bounded run-shaping trail as a terminal tree, JSON, or Markdown run card.
  • contextlattice_pack compiles a bounded prompt-ready packet with ranked evidence, files to inspect, risks, checks, source coverage, and a reference_prompt.
  • contextlattice_checkpoint writes a checkpoint and verifies readback.
  • contextlattice_skills_index discovers capabilities without loading every skill into startup context.
  • contextlattice_source_backfill is an optional development helper, installed with scripts/install_global_agent_tools.sh --include-dev-python-tools, for bounded data imports.
  • Hook pack details: docs/agent-hooks.md.

Agent Runtime Sessions

ContextLattice tracks live agent work as first-class sessions, independent of the runner or model provider.

  • Start/list/read sessions through GET|POST /v1/agents/sessions and GET /v1/agents/sessions/{session_id}.
  • Emit normalized events through POST /v1/agents/sessions/event or POST /v1/agents/sessions/{session_id}/events.
  • Inspect a bounded run trace through GET /v1/agents/sessions/{session_id}/trace; the trace reports context, skills that may be helpful, source coverage, graph touches, handoffs, checkpoints, and timeline events without raw provider payloads.
  • Read live runtime telemetry from GET /telemetry/agents/runtime.
  • Compile task context through POST /memory/context-pack, POST /tools/context_pack, or global contextlattice_pack; responses include context_compiler, ranked evidence, deterministic agent_guidance for themes/risk markers/candidate attention links, prompt sections, and a bounded reference_prompt.
  • Watch long-running recall through scripts/agent/contextlattice-session watch --session-id <id> --continuation-token <token>; continuation responses include retrieval_progress.v1, dashboard status links, and agent-visible steering when async work is ready.
  • Preflight, context-pack, and Dream Mode return objective_runtime_state.v1 with objective_state, action_executed, evidence, objective_delta, risk_or_blocker, and next_action.
  • Use scripts/agent/contextlattice-agent-adapter or global contextlattice_agent_adapter as the first-class product path for agent bootstrap, context-pack, checkpoint, handoff, event, and completion flows.
  • Use scripts/agent/contextlattice-adopt or global contextlattice_adopt before handing ContextLattice to a new agent/account; doctor combines gateway health, helper install state, shell PATH, storage posture, session store, profile coverage, runtime-doctor checks, lifecycle proof, and run trace evidence into one bounded report.
  • Run contextlattice_doctor --agents codex --skip-provider-smoke --pretty for the fastest new-agent adoption proof.
  • The same doctor works for other agent profiles: contextlattice_doctor --agents claude-code --skip-provider-smoke --pretty, contextlattice_doctor --agents opencode --skip-provider-smoke --pretty, or contextlattice_doctor --agents codex,claude-code,opencode --skip-provider-smoke --pretty.
  • Run scripts/agent/agent-runtime-proof-pack --pretty or global contextlattice_agent_runtime_proof --pretty for a one-command live proof that bootstrap, scoped recall, checkpoint, handoff, completion, status, and runtime telemetry are wired end to end.
  • Use scripts/agent/contextlattice-session for CLI start/event/complete/fail/status/runtime/trace flows.
  • Use scripts/agent/agent-run-trace --session-id <id> --tree or global contextlattice_agent_trace --session-id <id> --tree to see the terminal trace, then --markdown to export the run card.
  • Use scripts/agent/contextlattice-session sweep-stale-audits --all-projects --pretty for dry-run-first cleanup of stale objective-runtime audit/preflight sessions; add --confirm only after reviewing matches.
  • scripts/agent/contextlattice-pack, scripts/agent/contextlattice-dream, scripts/agent/writeback, and compaction hooks auto-start or recover a session when CONTEXTLATTICE_SESSION_ID is absent.
  • Pass --session-id or CONTEXTLATTICE_SESSION_ID to force a specific session. Set CONTEXTLATTICE_AUTO_SESSION_DISABLED=1 to disable automatic session creation.

Canonical event families include session.started, context_pack.completed, retrieval.continuation.progress, retrieval.continuation.ready, retrieval.continuation.degraded, dream.completed, graph.neighbors_returned, graph.edge_touched, decision.made, test.ran, handoff.created, writeback.completed, and session.completed.

Download Installers

  • macOS DMG: https://github.com/sheawinkler/ContextLattice/releases/latest/download/ContextLattice-macOS-universal.dmg
  • macOS signing/notarization operator notes: docs/releases/macos-signing-notarization.md
  • Homebrew cask: brew tap sheawinkler/contextlattice && brew install --cask contextlattice
  • Windows MSI: https://github.com/sheawinkler/ContextLattice/releases/latest/download/ContextLattice-windows-x64.msi
  • Linux bundle: https://github.com/sheawinkler/ContextLattice/releases/latest/download/ContextLattice-linux-bootstrap.tar.gz

Resource Profiles

ProfileCPURAMStorage
Lite core2-4 vCPU8-12 GB25-80 GB
Lite advanced4-6 vCPU12-16 GB80-140 GB
Full6-8 vCPU12-20 GB100-180 GB

Memory Graph

  • GET|POST /v1/memory/edges persists explicit typed relationships.
  • POST /v1/memory/edges/backfill audits or applies deterministic retroactive edges and opt-in same-project inferred_related scoring. It is dry-run by default.
  • POST /v1/memory/neighbors returns explicit/inferred edge neighbors merged with semantic/topic neighbors.
./scripts/agent/memory-edge-backfill
./scripts/agent/memory-edge-backfill --include-inferred --min-confidence 0.90
./scripts/agent/memory-edge-backfill --write
./scripts/agent/memory-edge-inferred-retrofill --all-projects
./scripts/agent/memory-edge-inferred-retrofill --all-projects --profile exploratory
./scripts/agent/memory-edge-inferred-retrofill --all-projects --profile exploratory --write --confirm-retrofill ALL_PROJECTS
./scripts/agent/memory-edge-inferred-retrofill --project hermes-agent-ultra --corpus disk --profile exploratory

Source Backfill

Bring existing data into ContextLattice without changing the ingest boundary. Backfill is dry-run by default, writes go through /memory/write, and writes require --write --confirm-write <project>.

./scripts/agent/source-backfill-memory --source jsonl --path exports/tasks.jsonl --project my-project --pretty
./scripts/agent/source-backfill-memory --source sqlite --path app.db --table notes --project my-project --pretty
./scripts/agent/source-backfill-memory --source parquet --path warehouse/events.parquet --project my-project --pretty
./scripts/agent/source-backfill-memory --source postgres --dsn "$DATABASE_URL" --query "select id,title,body from notes limit 100" --project my-project --pretty
./scripts/agent/source-backfill-memory --source jsonl --path exports/tasks.jsonl --project my-project --write --confirm-write my-project --apply-edges --pretty

Supported adapters: files/directories, JSONL, JSON, CSV, SQLite, DuckDB, Parquet via DuckDB, and Postgres via optional psycopg. Import caps cover records, row bytes, document bytes, total bytes, and structured-list items. Secret-like fields are redacted by default, and graph edge repair is optional and bounded.

Skills Index And Quarantine Discovery

ContextLattice exposes active skills as a native Go Skills Index so agents can discover relevant capabilities without loading every SKILL.md into prompt context. In local installs, the active index mounts ${HOME}/.codex/skills read-only by default. Quarantined/vendor skill discovery remains a separate read-only lane and does not auto-load quarantined skills.

  • Active index endpoint: GET|POST /v1/skills/index/search
  • Active index tool: GET|POST /tools/skills_index_search
  • Active index status/reindex endpoint: POST /v1/skills/index/reindex (live native scan; no prompt loading)
  • Search endpoint: GET|POST /v1/skills/quarantine/search
  • Tool alias: GET|POST /tools/skills_quarantine_search
  • Reindex endpoint: POST /v1/skills/quarantine/reindex (off by default; enable explicitly)

Runtime knobs:

ORCH_SKILLS_QUARANTINE_ENABLED=true
ORCH_SKILLS_QUARANTINE_HOST_BIN_DIR=${HOME}/.local/bin
ORCH_SKILLS_INDEX_HOST_ACTIVE_ROOT_DIR=${HOME}/.codex/skills
ORCH_SKILLS_INDEX_HOST_SYSTEM_ROOT_DIR=${HOME}/.codex/skills/.system
ORCH_SKILLS_INDEX_ROOTS=/opt/contextlattice/skills_active:/opt/contextlattice/skills_system
ORCH_SKILLS_QUARANTINE_HOST_ROOT_DIR=${HOME}/.codex/skills_quarantine
ORCH_SKILLS_QUARANTINE_SEARCH_CMD=/opt/contextlattice/skills/bin/codex-skills-quarantine-search
ORCH_SKILLS_QUARANTINE_REINDEX_CMD=/opt/contextlattice/skills/bin/codex-skills-quarantine-reindex
ORCH_SKILLS_QUARANTINE_TIMEOUT_SECS=8
ORCH_SKILLS_QUARANTINE_DEFAULT_LIMIT=20
ORCH_SKILLS_QUARANTINE_MAX_LIMIT=100
ORCH_SKILLS_QUARANTINE_REINDEX_ENABLED=false
CODEX_SKILLS_QUARANTINE_ROOT=/opt/contextlattice/skills_quarantine
CODEX_SKILLS_QUARANTINE_INDEX_DIR=/opt/contextlattice/skills_quarantine/index
CODEX_SKILLS_QUARANTINE_INDEX=/opt/contextlattice/skills_quarantine/index/skills_index.jsonl

Security and Privacy

  • Local-first by default.
  • API-key protected operational routes.
  • Secret-like content redaction controls.
  • Premium billing/provider route maps are intentionally kept out of public docs.

Docs Index

  • Overview: https://contextlattice.io/
  • Architecture: https://contextlattice.io/architecture.html
  • Local AI workspace comparison: https://contextlattice.io/local-ai-workspaces.html
  • Scaling memory: https://contextlattice.io/scaling-memory.html
  • Wiki: https://contextlattice.io/wiki.html
  • Installation: https://contextlattice.io/installation.html
  • Integrations: https://contextlattice.io/integration.html
  • Troubleshooting: https://contextlattice.io/troubleshooting.html
  • Updates: https://contextlattice.io/updates.html
  • Release notes:
    • docs/releases/v3.5.0.md
    • docs/releases/v3.4.25.md
    • docs/releases/v3.4.14.md
    • docs/releases/v3.4.13.md
    • docs/releases/v3.4.12.md
    • docs/releases/v3.4.11.md
    • docs/releases/v3.4.10.md
    • docs/releases/v3.4.5.md
    • docs/releases/v3.4.2.md
    • docs/releases/v3.4.1.md
  • Local model options: docs/runtime/local-model-options.md

License

Business Source License 1.1 (LICENSE).

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