(docs) how to build the lightspeed core image

Author: gallettilance

Containerfile

@@ -1,25 +1,45 @@
 # vim: set filetype=dockerfile
-FROM registry.access.redhat.com/ubi9/python-312-minimal AS builder
+FROM registry.access.redhat.com/ubi9/ubi-minimal AS builder
 
 ARG APP_ROOT=/app-root
 ARG LSC_SOURCE_DIR=.
 
 # UV_PYTHON_DOWNLOADS=0 : Disable Python interpreter downloads and use the system interpreter.
 ENV UV_COMPILE_BYTECODE=0 \
     UV_LINK_MODE=copy \
-    UV_PYTHON_DOWNLOADS=0
+    UV_PYTHON_DOWNLOADS=0 \
+    PATH="$PATH:/root/.local/bin"
 
 WORKDIR /app-root
 
-# Install uv package manager
-RUN pip3.12 install uv
+RUN microdnf install -y --nodocs --setopt=keepcache=0 --setopt=tsflags=nodocs \
+    python3.12 python3.12-devel python3.12-pip git tar \
+    gcc gcc-c++ make
 
 # Add explicit files and directories
 # (avoid accidental inclusion of local directories or env files or credentials)
 COPY ${LSC_SOURCE_DIR}/src ./src
 COPY ${LSC_SOURCE_DIR}/pyproject.toml ${LSC_SOURCE_DIR}/LICENSE ${LSC_SOURCE_DIR}/README.md ${LSC_SOURCE_DIR}/uv.lock ./
 
-RUN uv sync --locked --no-dev
+RUN curl -LsSf https://astral.sh/uv/install.sh | sh
+
+RUN uv sync --locked --no-dev && \
+    uv pip install \
+    opentelemetry-sdk \
+    opentelemetry-exporter-otlp \
+    opentelemetry-instrumentation \
+    aiosqlite \
+    litellm \
+    blobfile \
+    datasets \
+    sqlalchemy \
+    faiss-cpu \
+    mcp \
+    autoevals \
+    psutil \
+    torch \
+    peft \
+    trl
 
 
 # Final image without uv package manager

README.md

@@ -290,6 +290,70 @@ Container images are built for the following platforms:
 1. `linux/amd64` - main platform for deployment
 1. `linux/arm64`- Mac users with M1/M2/M3 CPUs
 
+## Building Container Images
+
+The repository includes production-ready container configurations that support two deployment modes:
+
+1. **Server Mode**: lightspeed-core connects to llama-stack as a separate service
+2. **Library Mode**: llama-stack runs as a library within lightspeed-core
+
+### Llama-Stack as Separate Service (Server Mode)
+
+When using llama-stack as a separate service, the existing `docker-compose.yaml` provides the complete setup.
+
+**Configuration** (`lightspeed-stack.yaml`):
+```yaml
+llama_stack:
+  use_as_library_client: false
+  url: http://llama-stack:8321  # container name from docker-compose.yaml
+  api_key: xyzzy
+```
+
+In the root of this project simply run:
+
+```bash
+# Set your OpenAI API key
+export OPENAI_API_KEY="your-api-key-here"
+
+# Start both services
+docker-compose up --build
+
+# Access lightspeed-core at http://localhost:8080
+# Access llama-stack at http://localhost:8321
+```
+
+### Llama-Stack as Library (Library Mode)
+
+When embedding llama-stack directly in the container, use the existing `test.containerfile`. First modify the `lightspeed-stack.yaml` config to use llama stack in library mode.
+
+**Configuration** (`lightspeed-stack.yaml`):
+```yaml
+llama_stack:
+  use_as_library_client: true
+  library_client_config_path: /app-root/run.yaml
+```
+
+**Build and run**:
+```bash
+# Build lightspeed-core with embedded llama-stack
+docker build -f Containerfile -t my-lightspeed-core:latest .
+
+# Run with embedded llama-stack
+docker run -d \
+  -p 8080:8080 \
+  -v ./lightspeed-stack.yaml:/app-root/lightspeed-stack.yaml:ro \
+  -v ./run.yaml:/app-root/run.yaml:ro \
+  -e OPENAI_API_KEY=your-api-key \
+  my-lightspeed-core:latest
+```
+
+### Verify it's running properly
+
+A simple sanity check:
+
+```bash
+curl -H "Accept: application/json" http://localhost:8080/v1/models
+```
 
 
 # Endpoints

lightspeed-stack.yaml

@@ -1,6 +1,6 @@
 name: Lightspeed Core Service (LCS)
 service:
-  host: localhost
+  host: 0.0.0.0
   port: 8080
   auth_enabled: false
   workers: 1
@@ -13,7 +13,7 @@ llama_stack:
   # Alternative for "as library use"
   # use_as_library_client: true
   # library_client_config_path: <path-to-llama-stack-run.yaml-file>
-  url: http://localhost:8321
+  url: http://llama-stack:8321
   api_key: xyzzy
 user_data_collection:
   feedback_enabled: true

run.yaml

@@ -0,0 +1,125 @@
+version: '2'
+image_name: minimal-viable-llama-stack-configuration
+
+apis:
+  - agents
+  - datasetio
+  - eval
+  - inference
+  - post_training
+  - safety
+  - scoring
+  - telemetry
+  - tool_runtime
+  - vector_io
+benchmarks: []
+container_image: null
+datasets: []
+external_providers_dir: null
+inference_store:
+  db_path: .llama/distributions/ollama/inference_store.db
+  type: sqlite
+logging: null
+metadata_store:
+  db_path: .llama/distributions/ollama/registry.db
+  namespace: null
+  type: sqlite
+providers:
+  agents:
+  - config:
+      persistence_store:
+        db_path: .llama/distributions/ollama/agents_store.db
+        namespace: null
+        type: sqlite
+      responses_store:
+        db_path: .llama/distributions/ollama/responses_store.db
+        type: sqlite
+    provider_id: meta-reference
+    provider_type: inline::meta-reference
+  datasetio:
+  - config:
+      kvstore:
+        db_path: .llama/distributions/ollama/huggingface_datasetio.db
+        namespace: null
+        type: sqlite
+    provider_id: huggingface
+    provider_type: remote::huggingface
+  - config:
+      kvstore:
+        db_path: .llama/distributions/ollama/localfs_datasetio.db
+        namespace: null
+        type: sqlite
+    provider_id: localfs
+    provider_type: inline::localfs
+  eval:
+  - config:
+      kvstore:
+        db_path: .llama/distributions/ollama/meta_reference_eval.db
+        namespace: null
+        type: sqlite
+    provider_id: meta-reference
+    provider_type: inline::meta-reference
+  inference:
+    - provider_id: openai
+      provider_type: remote::openai
+      config:
+        api_key: ${env.OPENAI_API_KEY}
+  post_training:
+  - config:
+      checkpoint_format: huggingface
+      device: cpu
+      distributed_backend: null
+    provider_id: huggingface
+    provider_type: inline::huggingface
+  safety:
+  - config:
+      excluded_categories: []
+    provider_id: llama-guard
+    provider_type: inline::llama-guard
+  scoring:
+  - config: {}
+    provider_id: basic
+    provider_type: inline::basic
+  - config: {}
+    provider_id: llm-as-judge
+    provider_type: inline::llm-as-judge
+  - config:
+      openai_api_key: '********'
+    provider_id: braintrust
+    provider_type: inline::braintrust
+  telemetry:
+  - config:
+      service_name: 'lightspeed-stack-telemetry'
+      sinks: sqlite
+      sqlite_db_path: .llama/distributions/ollama/trace_store.db
+    provider_id: meta-reference
+    provider_type: inline::meta-reference
+  tool_runtime:
+    - provider_id: model-context-protocol
+      provider_type: remote::model-context-protocol
+      config: {}
+  vector_io:
+  - config:
+      kvstore:
+        db_path: .llama/distributions/ollama/faiss_store.db
+        namespace: null
+        type: sqlite
+    provider_id: faiss
+    provider_type: inline::faiss
+scoring_fns: []
+server:
+  auth: null
+  host: null
+  port: 8321
+  quota: null
+  tls_cafile: null
+  tls_certfile: null
+  tls_keyfile: null
+shields: []
+vector_dbs: []
+
+models:
+  - model_id: gpt-4-turbo
+    provider_id: openai
+    model_type: llm
+    provider_model_id: gpt-4-turbo

test.containerfile

@@ -14,7 +14,8 @@ COPY README.md ./
 COPY src/ ./src/
 
 RUN microdnf install -y --nodocs --setopt=keepcache=0 --setopt=tsflags=nodocs \
-    python3.12 python3.12-devel python3.12-pip git tar
+    python3.12 python3.12-devel python3.12-pip git tar \
+    gcc gcc-c++ make
 
 RUN curl -LsSf https://astral.sh/uv/install.sh | sh