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docs: add OpenCode injector image Dockerfile and registry.json guide
- Replace Gemini/Claude dual-provider example with a single OpenCode provider using OPENAI_API_KEY - Add Procedure step with a minimal Dockerfile for building a custom injector image, based on che-incubator/che-ai-tool-images/dockerfiles/ opencode/Dockerfile; explains multi-stage build, wrapper script for OpenShift arbitrary UIDs, and multi-arch build command - Reference che-incubator/che-ai-tool-images for maintained examples - Document all registry.json fields with numbered callouts Assisted-by: Claude Sonnet 4.6 Signed-off-by: Oleksii Orel <oorel@redhat.com>
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‎modules/administration-guide/pages/configuring-ai-providers.adoc‎

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:_content-type: PROCEDURE
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:description: Register AI providers in Eclipse Che so that developers can select and use AI coding assistants when creating workspaces.
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:keywords: administration, ai, ai provider, gemini, claude, configmap, ai-tool-registry, api key
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:keywords: administration, ai, ai provider, opencode, configmap, ai-tool-registry, api key, injector image, dockerfile
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:navtitle: Configuring AI providers
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:page-aliases:
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.Procedure
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. Create a `registry.json` file defining providers, tools, and default selections:
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. Optional: Build and push a custom AI tool injector image.
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The injector image is a container that carries the AI tool binary. During workspace startup, {prod-short} runs it as an init container to copy the binary into a shared volume. The following minimal `Dockerfile` is based on the link:https://github.com/che-incubator/che-ai-tool-images/blob/main/dockerfiles/opencode/Dockerfile[OpenCode injector image]:
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[source,dockerfile]
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----
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FROM alpine:3.21 AS builder
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ARG OPENCODE_VERSION=v1.2.27
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ARG TARGETARCH
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RUN apk add --no-cache curl tar gzip
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RUN set -e && \
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case "${TARGETARCH}" in \
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amd64) ARCH="x64" ;; \
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arm64) ARCH="arm64" ;; \
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*) echo "Unsupported architecture: ${TARGETARCH}" && exit 1 ;; \
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esac && \
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curl -fsSL -o /tmp/opencode.tar.gz \
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"https://github.com/anomalyco/opencode/releases/download/${OPENCODE_VERSION}/opencode-linux-${ARCH}.tar.gz" && \
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tar -xzf /tmp/opencode.tar.gz -C /tmp && \
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mv /tmp/opencode /usr/local/bin/opencode && \
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chmod +x /usr/local/bin/opencode
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FROM registry.access.redhat.com/ubi10/ubi-minimal:10.0
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COPY --from=builder /usr/local/bin/opencode /usr/local/bin/opencode-bin
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RUN printf '#!/bin/sh\n\
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SCRIPT_DIR="$(cd "$(dirname "$0")" && pwd)"\n\
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OC_HOME="/tmp/opencode-home"\n\
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mkdir -p "$OC_HOME/.config" "$OC_HOME/.local/share"\n\
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export XDG_CONFIG_HOME="${XDG_CONFIG_HOME:-$OC_HOME/.config}"\n\
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export XDG_DATA_HOME="${XDG_DATA_HOME:-$OC_HOME/.local/share}"\n\
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exec "$SCRIPT_DIR/opencode-bin" "$@"\n' > /usr/local/bin/opencode && \
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chmod +x /usr/local/bin/opencode
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LABEL org.opencontainers.image.description="OpenCode CLI tool for DevWorkspace injection" \
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org.opencontainers.image.source="https://github.com/che-incubator/che-ai-tool-images.git"
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----
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Key design points:
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** *Multi-stage build*: the `builder` stage downloads the architecture-specific binary; the minimal runtime stage keeps the final image small.
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** *Wrapper script*: redirects `XDG_CONFIG_HOME`, `XDG_DATA_HOME`, and related variables to writable paths under `/tmp`, allowing the tool to run as an arbitrary UID on OpenShift.
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** *Multi-arch*: pass `--platform linux/amd64,linux/arm64` to `docker build` to produce a multi-arch image.
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Build and push the image:
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[subs="+quotes"]
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----
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$ docker build --platform linux/amd64,linux/arm64 \
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-t __<your-registry>__/__<your-org>__/opencode:next \
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--push .
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----
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See link:https://github.com/che-incubator/che-ai-tool-images[che-incubator/che-ai-tool-images] for maintained injector image examples.
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. Create a `registry.json` file that defines providers, tools, and optional defaults:
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[source,json,subs="+quotes"]
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----
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{
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"providers": [
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{
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"id": "google/gemini",
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"name": "Gemini",
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"publisher": "Google",
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"description": "Google Gemini AI assistant for the terminal.",
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"docsUrl": "https://ai.google.dev/gemini-api/docs/quickstart",
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"icon": "https://example.com/gemini-icon.svg"
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},
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{
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"id": "anthropic/claude",
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"name": "Claude",
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"publisher": "Anthropic",
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"description": "Anthropic Claude AI coding assistant for terminal.",
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"docsUrl": "https://docs.anthropic.com/claude/reference/getting-started-with-the-api",
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"icon": "https://example.com/claude-icon.svg"
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"id": "opencodeai/opencode", <1>
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"name": "OpenCode",
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"publisher": "opencode.ai",
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"description": "Open-source terminal AI coding agent supporting 75+ LLM providers.",
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"docsUrl": "https://opencode.ai",
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"icon": "https://example.com/opencode-icon.svg"
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}
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],
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"tools": [
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{
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"providerId": "google/gemini", <1>
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"tag": "next", <2>
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"name": "Gemini CLI",
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"url": "https://ai.google.dev/gemini-api/docs",
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"binary": "gemini", <3>
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"pattern": "bundle", <4>
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"injectorImage": "quay.io/example/gemini-cli:next", <5>
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"envVarName": "GEMINI_API_KEY" <6>
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},
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{
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"providerId": "anthropic/claude",
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"tag": "next",
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"name": "Claude Code",
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"url": "https://claude.ai/code",
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"binary": "claude",
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"pattern": "init",
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"injectorImage": "quay.io/example/claude-code:next",
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"envVarName": "ANTHROPIC_API_KEY"
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"providerId": "opencodeai/opencode", <2>
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"tag": "next", <3>
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"name": "OpenCode",
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"url": "https://opencode.ai",
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"binary": "opencode", <4>
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"pattern": "init", <5>
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"injectorImage": "__<your-registry>__/__<your-org>__/opencode:next", <6>
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"envVarName": "OPENAI_API_KEY" <7>
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}
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],
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"defaultAiProviders": ["google/gemini"] <7>
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"defaultAiProviders": ["opencodeai/opencode"] <8>
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}
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----
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<1> Links the tool to a provider by the provider's `id`.
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<2> Version tag. When multiple tools share the same `providerId`, the dashboard selects by tag priority: `next` > `latest` > highest semver.
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<3> Binary name available in `PATH` after injection.
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<4> Injection pattern: `init` copies a single binary; `bundle` copies a full runtime directory and creates a symlink.
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<5> Container image used as an init container to copy the tool binary into a shared volume.
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<6> Environment variable name for the API key. The dashboard creates a {kubernetes} Secret with this key.
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<7> Optional. List of provider IDs pre-selected in the AI Selector widget for new workspaces.
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<1> Unique provider identifier in `__<vendor>__/__<product>__` format.
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<2> Links the tool to its provider by `id`.
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<3> Version tag. When multiple tools share the same `providerId`, the dashboard selects by priority: `next` > `latest` > highest semver.
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<4> Binary name that must be available in `PATH` inside the workspace after injection.
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<5> Injection pattern: `init` copies a single binary into the shared volume; `bundle` copies a full runtime directory and creates a symlink.
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<6> Container image that carries the tool binary. Run as an init container at workspace start.
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<7> Environment variable name for the API key. The dashboard creates a {kubernetes} Secret using this name as the data key.
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<8> Optional. Provider IDs pre-selected in the AI Selector widget for new workspaces.
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. Create the `ConfigMap` in the `{prod-namespace}` namespace with the required labels:
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