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Merge pull request #940 from constructive-io/devin/1774944693-embedder-config-docs
feat(codegen): generate embedder config reference for CLI docs
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‎graphql/codegen/src/core/codegen/cli/docs-generator.ts‎

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Original file line numberDiff line numberDiff line change
@@ -370,6 +370,64 @@ export function generateSkills(
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}),
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});
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// Embedder reference (generated once when any table has Vector fields)
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const hasEmbeddings = tables.some((t) =>
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categorizeSpecialFields(t, registry).some((g) => g.category === 'embedding'),
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);
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if (hasEmbeddings) {
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referenceNames.push('embedder');
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files.push({
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fileName: `${skillName}/references/embedder.md`,
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content: buildSkillReference({
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title: 'Embedder Configuration',
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description:
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`Configure text-to-vector embedding for \`--auto-embed\` support in ${toolName}.\n\n` +
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'When an embedder is configured, you can pass plain text to vector fields and ' +
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'the CLI will automatically convert it to an embedding vector.\n\n' +
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'**Supported providers:** ollama, openai\n\n' +
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'**Configuration methods:** appstash config (persisted per-context) or environment variables',
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usage: [
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`# Configure via appstash config (persisted per-context)`,
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`${toolName} config set embedder.provider <provider>`,
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`${toolName} config set embedder.model <model>`,
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`${toolName} config set embedder.baseUrl <url>`,
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'',
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`# Or configure via environment variables`,
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`EMBEDDER_PROVIDER=<provider> EMBEDDER_MODEL=<model> EMBEDDER_BASE_URL=<url> ${toolName} <command>`,
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],
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examples: [
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{
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description: 'Ollama with nomic-embed-text (open-source, local)',
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code: [
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`# Start Ollama locally and pull the model`,
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`ollama pull nomic-embed-text`,
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'',
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`# Register the embedder`,
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`${toolName} config set embedder.provider ollama`,
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`${toolName} config set embedder.model nomic-embed-text`,
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`${toolName} config set embedder.baseUrl http://localhost:11434`,
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'',
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`# Now use --auto-embed with any vector field`,
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`${toolName} ${toKebabCase(getTableNames(tables[0]).singularName)} search "my query" --auto-embed`,
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],
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},
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{
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description: 'OpenAI with an API key',
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code: [
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`# Register the embedder`,
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`${toolName} config set embedder.provider openai`,
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`${toolName} config set embedder.model text-embedding-3-small`,
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`${toolName} config set embedder.apiKey sk-proj-...your-api-key`,
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'',
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`# Or use environment variables`,
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`EMBEDDER_PROVIDER=openai EMBEDDER_MODEL=text-embedding-3-small EMBEDDER_API_KEY=sk-proj-...your-api-key ${toolName} ${toKebabCase(getTableNames(tables[0]).singularName)} search "my query" --auto-embed`,
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],
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},
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],
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}),
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});
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}
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// Table references
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for (const table of tables) {
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const { singularName } = getTableNames(table);
@@ -989,6 +1047,68 @@ export function generateMultiTargetSkills(
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}),
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});
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// Embedder reference (generated once when any target has tables with Vector fields)
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const allTargetTables = targets.flatMap((t) => t.tables);
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const hasEmbeddings = allTargetTables.some((t) =>
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categorizeSpecialFields(t, registry).some((g) => g.category === 'embedding'),
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);
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if (hasEmbeddings) {
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const firstTableName = allTargetTables.length > 0
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? toKebabCase(getTableNames(allTargetTables[0]).singularName)
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: 'model';
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commonReferenceNames.push('embedder');
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files.push({
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fileName: `${commonSkillName}/references/embedder.md`,
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content: buildSkillReference({
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title: 'Embedder Configuration',
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description:
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`Configure text-to-vector embedding for \`--auto-embed\` support in ${toolName}.\n\n` +
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'When an embedder is configured, you can pass plain text to vector fields and ' +
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'the CLI will automatically convert it to an embedding vector.\n\n' +
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'**Supported providers:** ollama, openai\n\n' +
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'**Configuration methods:** appstash config (persisted per-context) or environment variables',
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usage: [
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`# Configure via appstash config (persisted per-context)`,
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`${toolName} ${builtinNames.config} set embedder.provider <provider>`,
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`${toolName} ${builtinNames.config} set embedder.model <model>`,
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`${toolName} ${builtinNames.config} set embedder.baseUrl <url>`,
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'',
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`# Or configure via environment variables`,
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`EMBEDDER_PROVIDER=<provider> EMBEDDER_MODEL=<model> EMBEDDER_BASE_URL=<url> ${toolName} <command>`,
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],
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examples: [
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{
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description: 'Ollama with nomic-embed-text (open-source, local)',
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code: [
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`# Start Ollama locally and pull the model`,
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`ollama pull nomic-embed-text`,
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'',
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`# Register the embedder`,
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`${toolName} ${builtinNames.config} set embedder.provider ollama`,
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`${toolName} ${builtinNames.config} set embedder.model nomic-embed-text`,
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`${toolName} ${builtinNames.config} set embedder.baseUrl http://localhost:11434`,
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'',
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`# Now use --auto-embed with any vector field`,
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`${toolName} ${targets[0]?.name ? `${targets[0].name}:` : ''}${firstTableName} search "my query" --auto-embed`,
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],
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},
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{
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description: 'OpenAI with an API key',
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code: [
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`# Register the embedder`,
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`${toolName} ${builtinNames.config} set embedder.provider openai`,
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`${toolName} ${builtinNames.config} set embedder.model text-embedding-3-small`,
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`${toolName} ${builtinNames.config} set embedder.apiKey sk-proj-...your-api-key`,
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'',
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`# Or use environment variables`,
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`EMBEDDER_PROVIDER=openai EMBEDDER_MODEL=text-embedding-3-small EMBEDDER_API_KEY=sk-proj-...your-api-key ${toolName} ${targets[0]?.name ? `${targets[0].name}:` : ''}${firstTableName} search "my query" --auto-embed`,
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],
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},
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],
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}),
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});
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}
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// Common SKILL.md
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files.push({
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fileName: `${commonSkillName}/SKILL.md`,

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