M.I.M.I.R - Multi-agent Intelligent Memory & Insight Repository

# NornicDB ARM64 Metal + Heimdall (Cognitive Guardian) # Self-contained build with local embedding AND Heimdall SLM support # # This image includes: # - BGE-M3 embedding model for vector search # - Qwen2.5-0.5B-Instruct (Q4_K_M) for Heimdall (cognitive database guardian) # # Build: # docker build -f docker/Dockerfile.arm64-metal-heimdall -t timothyswt/nornicdb-arm64-metal-bge-heimdall . # # Run: # docker run -p 7474:7474 -p 7687:7687 -v nornicdb-data:/data timothyswt/nornicdb-arm64-metal-bge-heimdall # # This is a "batteries included" deployment - no additional model downloads required. # Heimdall provides: anomaly detection, runtime diagnosis, and memory curation via Bifrost chat. # ============================================================================= # Stage 1: UI # ============================================================================= FROM node:20-alpine AS ui WORKDIR /ui COPY ui/package*.json ./ RUN npm ci 2>/dev/null || npm install --legacy-peer-deps COPY ui/ . RUN npm run build # ============================================================================= # Stage 2: llama.cpp static library (ARM64) # ============================================================================= FROM debian:bookworm-slim AS llama RUN apt-get update && apt-get install -y --no-install-recommends \ build-essential cmake git ca-certificates && rm -rf /var/lib/apt/lists/* ARG LLAMA_VERSION=b7285 WORKDIR /llama RUN git clone --depth 1 --branch ${LLAMA_VERSION} https://github.com/ggerganov/llama.cpp.git . && \ cmake -B build \ -DLLAMA_STATIC=ON -DBUILD_SHARED_LIBS=OFF \ -DLLAMA_BUILD_TESTS=OFF -DLLAMA_BUILD_EXAMPLES=OFF -DLLAMA_BUILD_SERVER=OFF \ -DLLAMA_CURL=OFF \ -DGGML_NATIVE=OFF -DGGML_OPENMP=OFF \ -DCMAKE_C_FLAGS="-mcpu=generic" -DCMAKE_CXX_FLAGS="-mcpu=generic" && \ cmake --build build --config Release -j$(nproc) # Combine static libs into single archive RUN mkdir -p /out && \ find build -name "*.a" -exec cp {} /out/ \; && \ echo "Libraries found:" && ls -la /out/*.a && \ echo "CREATE /out/libllama_combined.a" > /tmp/ar.mri && \ for lib in /out/lib*.a; do echo "ADDLIB $lib" >> /tmp/ar.mri; done && \ echo "SAVE" >> /tmp/ar.mri && \ echo "END" >> /tmp/ar.mri && \ cat /tmp/ar.mri && \ ar -M < /tmp/ar.mri && \ cp include/llama.h ggml/include/*.h /out/ && \ echo "Combined library:" && ls -lh /out/libllama_combined.a # ============================================================================= # Stage 3: Go build # ============================================================================= FROM golang:1.25-bookworm AS builder WORKDIR /build RUN apt-get update && apt-get install -y --no-install-recommends build-essential && rm -rf /var/lib/apt/lists/* # Copy llama artifacts COPY --from=llama /out/libllama_combined.a /build/lib/llama/libllama_linux_arm64.a COPY --from=llama /out/*.h /build/lib/llama/ # Go dependencies COPY go.mod go.sum ./ RUN go mod download # Source + UI COPY . . COPY --from=ui /ui/dist ./ui/dist # Build with full features (localllm for both embedding and SLM generation) RUN echo "Building NornicDB with Heimdall support..." && \ CGO_ENABLED=1 go build -tags=localllm \ -ldflags="-s -w -X main.buildTime=$(date -u +%Y%m%d-%H%M%S)" \ -o nornicdb ./cmd/nornicdb # Build APOC plugin RUN echo "Building APOC plugin..." && \ mkdir -p apoc/built-plugins && \ cd apoc/plugin-src/apoc && go build -buildmode=plugin -o ../../../apoc/built-plugins/apoc.so apoc_plugin.go && \ echo "✓ Built plugin:" && ls -lh /build/apoc/built-plugins/*.so # ============================================================================= # Stage 4: Runtime with embedded models # ============================================================================= FROM debian:bookworm-slim WORKDIR /app RUN apt-get update && apt-get install -y --no-install-recommends \ ca-certificates tzdata wget && rm -rf /var/lib/apt/lists/* && \ mkdir -p /data /app/models COPY --from=builder /build/nornicdb /app/ COPY --from=builder /build/apoc/built-plugins /app/plugins/ COPY docker/entrypoint.sh /app/ RUN chmod +x /app/entrypoint.sh # Embed BOTH models: BGE-M3 (embeddings) and Qwen2.5-0.5B (Heimdall SLM) # Using BuildKit mount to avoid layer bloat during COPY RUN --mount=type=bind,source=models,target=/models,ro \ echo "=== Embedding models for batteries-included deployment ===" && \ # BGE-M3 embedding model (required) if [ -f /models/bge-m3.gguf ]; then \ cp /models/bge-m3.gguf /app/models/ && \ echo "✓ Embedded bge-m3.gguf ($(du -h /app/models/bge-m3.gguf | cut -f1))"; \ else \ echo "ERROR: models/bge-m3.gguf not found" && exit 1; \ fi && \ # Qwen2.5-0.5B-Instruct for Heimdall (required for this build) if [ -f /models/qwen2.5-0.5b-instruct-q4_k_m.gguf ]; then \ cp /models/qwen2.5-0.5b-instruct-q4_k_m.gguf /app/models/ && \ echo "✓ Embedded qwen2.5-0.5b-instruct-q4_k_m.gguf ($(du -h /app/models/qwen2.5-0.5b-instruct-q4_k_m.gguf | cut -f1))"; \ else \ echo "ERROR: models/qwen2.5-0.5b-instruct-q4_k_m.gguf not found - required for Heimdall" && exit 1; \ fi && \ echo "=== Model embedding complete ===" && \ ls -lh /app/models/ EXPOSE 7474 7687 HEALTHCHECK --interval=30s --timeout=10s --start-period=10s --retries=3 \ CMD wget --spider -q http://localhost:7474/health || exit 1 # Environment configuration for Heimdall-enabled deployment ENV NORNICDB_DATA_DIR=/data \ NORNICDB_HTTP_PORT=7474 \ NORNICDB_BOLT_PORT=7687 \ # Embedding configuration NORNICDB_EMBEDDING_PROVIDER=local \ NORNICDB_EMBEDDING_MODEL=bge-m3 \ NORNICDB_EMBEDDING_DIMENSIONS=1024 \ NORNICDB_MODELS_DIR=/app/models \ NORNICDB_EMBEDDING_GPU_LAYERS=0 \ # Heimdall configuration (cognitive guardian) NORNICDB_HEIMDALL_ENABLED=true \ NORNICDB_HEIMDALL_MODEL=qwen2.5-0.5b-instruct-q4_k_m \ NORNICDB_HEIMDALL_GPU_LAYERS=-1 \ NORNICDB_HEIMDALL_MAX_TOKENS=512 \ NORNICDB_HEIMDALL_TEMPERATURE=0.1 \ NORNICDB_HEIMDALL_ANOMALY_DETECTION=true \ NORNICDB_HEIMDALL_RUNTIME_DIAGNOSIS=true \ NORNICDB_HEIMDALL_MEMORY_CURATION=false \ # General settings NORNICDB_NO_AUTH=true \ NORNICDB_PLUGINS_DIR=/app/plugins ENTRYPOINT ["/app/entrypoint.sh"]