Function buildSystemPrompt

packages/runtime-core/src/agent-handler.ts:109–146

(
  notebookContext: string,
  integrations?: Array<{ id: string; name: string; type: string }>
)

}

export function buildSystemPrompt(
  notebookContext: string,
  integrations?: Array<{ id: string; name: string; type: string }>
): string {
  let prompt = `You are a data science assistant working inside a Deepnote notebook. You can add code blocks and markdown blocks to the notebook.

## Current notebook state

${notebookContext}

## Instructions

- Use add_code_block to write and execute Python code. You will see the output.
- Use add_markdown_block to add explanations, section headers, or documentation.
- Analyze data step by step: load, explore, transform, visualize, summarize.
- If a code block errors, read the error and try a different approach.
- When you are done, provide a brief summary of what you did and found.
- Be concise in markdown blocks. Prefer code that shows results over long explanations.`

  if (integrations && integrations.length > 0) {
    prompt += `

## Available database integrations

The following database integrations are configured and available. To query them,
use add_code_block with the deepnote-toolkit SQL helper:

\`\`\`python
import deepnote_toolkit as dntk
df = dntk.execute_sql("SELECT * FROM users LIMIT 10", "SQL_<INTEGRATION_ID>")
\`\`\`

Available integrations:
${integrations.map(i => `- "${i.name}" (${i.type}, id: ${i.id})`).join('\n')}`
  }

  return prompt
}

export async function executeAgentBlock(block: AgentBlock, context: AgentBlockContext): Promise<AgentBlockResult> {
  const openai = createOpenAI({