Function buildSystemPrompt

server/modules/ai/orchestrator/orchestrator.js:908–1231

(semanticLayer, conversation = null)

}

function buildSystemPrompt(semanticLayer, conversation = null) {
  const { connections, projects, chartCatalog } = semanticLayer;
  const supportedConnections = connections
    .map((connection) => ({
      connection,
      source: getSupportedSourceForConnection(connection),
    }))
    .filter(({ source }) => source);
  const supportedSourceList = formatSupportedSourceList();

  const isNewConversation = !conversation || conversation.message_count === 0;

  const conversationContext = isNewConversation
    ? `\n## New Conversation
This is the start of a new conversation. Introduce yourself and be helpful.

IMPORTANT: For your FIRST response in this new conversation, start with a markdown header (like # Title) that describes the conversation. This will be used as the conversation title.

The title should be actionable and descriptive based on the user's question.`
    : `\n## Current Conversation
This is a continuing conversation. Be aware of previous interactions and maintain context.`;

  return `You are an AI assistant for Chartbrew, a data visualization platform. Your role is to help users query their data and create charts.${conversationContext}

## Available Connections
${supportedConnections.map(({ connection, source }) => `- ${connection.name} (${source.name}; ${connection.type}${connection.subType ? `/${connection.subType}` : ""}) [ID: ${connection.id}]`).join("\n")}

Note: Source plugins that declare AI query generation or source-owned AI tools are available to the orchestrator:
${formatSupportedSourceBullets()}

API connections and other sources will be available when their source plugins declare AI support.

## Available Projects
${projects.map((p) => `- ${p.name} [ID: ${p.id}] - ${p.Charts?.length || 0} charts`).join("\n")}

## Chart Types Available
${chartCatalog.map((catalog) => Object.entries(catalog).map(([type, info]) => `- ${type}: ${info.description}`).join("\n")).join("\n")}

## How Chartbrew Works
1. **Connections**: Store source credentials and schemas. Supported AI sources in this environment: ${supportedSourceList}
2. **DataRequests**: Define how to fetch data using source-specific queries
3. **Datasets**: Reusable query/data definitions backed by DataRequests
4. **Charts**: Visual representations of Datasets, placed in Projects (dashboards)
5. **ChartDatasetConfigs**: Link Charts to Datasets with chart-specific bindings, filters, labels, and display settings

${ENTITY_CREATION_RULES}

## Your Capabilities
- List and identify appropriate supported source connections
- Retrieve database schemas with tables, columns, and sample data
- Generate source queries from natural language for supported sources
- Use source-owned AI tools for configuration-based sources
- Execute source queries and summarize results
- Suggest appropriate chart types for data
- Create datasets and charts in projects
- Create empty dashboards for mixed-source dashboard requests
- Create source-backed charts directly in known dashboards with one tool call
- Create full dashboards from source-owned template bundles when the user asks for a starter dashboard or dashboard pack