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Synopsis

moorcheh-edge up [options]

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Options

FlagDefaultDescription
--server-port8080Host port for http://localhost:<port>
--server-imagemoorcheh/moorcheh-edge:latestDocker image to run
-y, --yesoffNon-interactive: no prompts, use defaults + flags
--skip-embeddingoffSkip BGE entirely (vector-only; no warm embed daemon)
--with-llmoffInstall Ollama and pull the answer model (~400 MB)
--skip-ollamaoffExplicit search-only (same as default without --with-llm)
--warm-llmoffWith --with-llm: preload LLM in RAM (default keep-alive 24h)

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Defaults

ComponentDefault up
Docker serverYes
BGE embed daemon (warm)Yes
Ollama + LLM modelNo (use --with-llm)
LLM kept in RAMNo (use --with-llm --warm-llm)
In an interactive terminal, up asks up to three questions (embedding, AI answer, keep LLM in RAM). Use -y or flags to skip prompts.

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Examples

moorcheh-edge up
moorcheh-edge up -y
moorcheh-edge up --with-llm
moorcheh-edge up --with-llm --warm-llm
moorcheh-edge up --skip-embedding
moorcheh-edge up --server-port 8083
moorcheh-edge up --server-image moorcheh/moorcheh-edge:0.1.0
On first run with embedding enabled, up downloads BGE-base-en-v1.5 (~210 MB) and starts a warm embedding daemon (stopped by down). With --with-llm on Linux, up also installs Ollama into ~/.moorcheh-edge/ollama/ and pulls qwen2.5:0.5b-instruct for answer.

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Output

On success: 
Data directory: ~/.moorcheh-edge/data
Moorcheh Edge API: http://localhost:8080
With --with-llm: 
[moorcheh-edge] LLM endpoint (in container): http://host.docker.internal:11434/v1
If the container is already running, up attaches and prints the same lines without starting a second container. Run moorcheh-edge down then up after upgrades so LLM settings are applied to the container.

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Requirements

  • Docker running
  • Pull access for moorcheh/moorcheh-edge:latest (or a local cached image)