mlld/dist/prose-execution-BCUOZNHM.mjs.map

mlld: llm scripting language

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* Prose Execution Handler\n *\n * Handles execution of prose executables (prose:@config { ... }).\n * Prose blocks are executed by:\n * 1. Resolving the config reference for model settings\n * 2. Interpolating variables in the prose content\n * 3. Wrapping with skill injection prompt\n * 4. Executing via the model executor\n *\n * The skill name is configurable via config.skillName (default: \"prose\").\n * This allows users to use custom interpreters instead of OpenProse.\n */\n\nimport type { Environment } from '../env/Environment';\nimport type { ProseExecutable } from '@core/types/executable';\nimport { interpolate } from '../core/interpreter';\nimport { InterpolationContext } from '../core/interpolation-context';\nimport { createSimpleTextVariable, isExecutableVariable } from '@core/types/variable';\nimport type { Variable } from '@core/types/variable';\nimport { logger } from '@core/utils/logger';\nimport { evaluateExecInvocation } from './exec-invocation';\nimport type { ExecInvocation, CommandReference } from '@core/types';\n\n/**\n * Build the skill injection prompt for a given skill name\n * Default skill is \"prose\" (OpenProse), but users can specify custom interpreters\n */\nfunction buildSkillInjectionPrompt(skills: string[]): string {\n  const runSkill = skills.find(s => s.includes('run')) || skills[0];\n\n  return `Run /${runSkill} with this program:\n\n`;\n}\n\nfunction buildSkillInjectionEnd(skills: string[]): string {\n  return `\n\nReturn only the output. If the skill is unavailable, respond: ERROR: SKILLS_NOT_FOUND`;\n}\n\n/**\n * Execute a prose executable\n *\n * @param definition - The prose executable definition\n * @param args - Arguments passed to the executable\n * @param env - The execution environment\n * @returns The result of prose execution\n */\nexport async function executeProseExecutable(\n  definition: ProseExecutable,\n  args: Record<string, string>,\n  env: Environment\n): Promise<string> {\n  if (process.env.DEBUG_EXEC) {\n    logger.debug('Executing prose executable:', {\n      contentType: definition.contentType,\n      hasConfig: !!definition.configRef,\n      paramNames: definition.paramNames\n    });\n  }\n\n  // 1. Resolve the config reference\n  const configRef = definition.configRef;\n  if (!configRef || configRef.length === 0) {\n    throw new Error('Prose executable missing config reference');\n  }\n\n  const configRefNode = configRef[0];\n  let configVarName: string;\n  if (configRefNode.type === 'VariableReference') {\n    configVarName = (configRefNode as any).identifier;\n  } else if (configRefNode.type === 'Text') {\n    configVarName = (configRefNode as any).content;\n  } else {\n    throw new Error('Invalid config reference in prose executable');\n  }\n\n  const configVar = env.getVariable(configVarName);\n  if (!configVar) {\n    throw new Error(`Prose config not found: @${configVarName}`);\n  }\n\n  // Extract and validate config values\n  const config = extractProseConfig(configVar, configVarName, env);\n\n  // 2. Create parameter environment\n  const proseEnv = env.createChild();\n  for (const [key, value] of Object.entries(args)) {\n    proseEnv.setParameterVariable(key, createSimpleTextVariable(key, value));\n  }\n\n  // 3. Get the prose content based on content type\n  let proseContent: string;\n\n  if (definition.contentType === 'inline') {\n    // Inline prose: prose:@config { session \"...\" }\n    if (!definition.contentTemplate) {\n      throw new Error('Inline prose executable missing content');\n    }\n    proseContent = await interpolate(\n      definition.contentTemplate,\n      proseEnv,\n      InterpolationContext.Default\n    );\n  } else if (definition.contentType === 'file') {\n    // File-based prose: prose:@config \"file.prose\"\n    // Also handles .prose.att and .prose.mtt with auto-detection\n    if (!definition.pathTemplate) {\n      throw new Error('File-based prose executable missing path');\n    }\n    const filePath = await interpolate(\n      definition.pathTemplate,\n      proseEnv,\n      InterpolationContext.Default\n    );\n\n    let fileContent: string;\n    try {\n      fileContent = await env.readFile(filePath);\n    } catch (err: any) {\n      throw new Error(\n        `Failed to read prose file \"${filePath}\": ${err.message || err}`\n      );\n    }\n\n    // Check for template extensions (.prose.att or .prose.mtt)\n    const lowerPath = filePath.toLowerCase();\n    if (lowerPath.endsWith('.prose.att')) {\n      // ATT-style template: @var interpolation\n      proseContent = await parseAndInterpolateTemplate(fileContent, 'att', proseEnv);\n    } else if (lowerPath.endsWith('.prose.mtt')) {\n      // MTT-style template: {{var}} interpolation\n      proseContent = await parseAndInterpolateTemplate(fileContent, 'mtt', proseEnv);\n    } else {\n      // Plain .prose file - still interpolate @vars for convenience\n      proseContent = await interpolateProseTemplate(fileContent, proseEnv);\n    }\n  } else if (definition.contentType === 'template') {\n    // Explicit template prose: prose:@config template \"file.prose.att\"\n    if (!definition.pathTemplate) {\n      throw new Error('Template prose executable missing path');\n    }\n    const filePath = await interpolate(\n      definition.pathTemplate,\n      proseEnv,\n      InterpolationContext.Default\n    );\n\n    let fileContent: string;\n    try {\n      fileContent = await env.readFile(filePath);\n    } catch (err: any) {\n      throw new Error(\n        `Failed to read prose template \"${filePath}\": ${err.message || err}`\n      );\n    }\n\n    // Detect template style from extension\n    const lowerPath = filePath.toLowerCase();\n    const templateStyle = lowerPath.endsWith('.mtt') ? 'mtt' : 'att';\n    proseContent = await parseAndInterpolateTemplate(fileContent, templateStyle, proseEnv);\n  } else {\n    throw new Error(`Unknown prose content type: ${definition.contentType}`);\n  }\n\n  // 4. Validate prose content is not empty\n  if (!proseContent || proseContent.trim() === '') {\n    const source = definition.contentType === 'inline' ? 'inline block' :\n                   definition.contentType === 'file' ? 'file' : 'template';\n    throw new Error(\n      `Prose ${source} is empty. Prose content must contain at least one instruction.`\n    );\n  }\n\n  // 5. Construct the skill-injected prompt\n  // Use custom prompts if provided, otherwise build from skills list\n  const skillPrompt = config.skillPrompt || buildSkillInjectionPrompt(config.skills);\n  const skillPromptEnd = config.skillPromptEnd || buildSkillInjectionEnd(config.skills);\n  const fullPrompt = skillPrompt + proseContent + skillPromptEnd;\n\n  if (process.env.DEBUG_EXEC) {\n    logger.debug('Prose prompt constructed:', {\n      contentLength: proseContent.length,\n      fullPromptLength: fullPrompt.length,\n      modelName: config.modelName,\n      skills: config.skills\n    });\n  }\n\n  // 6. Execute via model executor\n  const result = await invokeModelExecutor(fullPrompt, config, env);\n\n  // 7. Check for skills-not-found error\n  if (result.includes('ERROR: SKILLS_NOT_FOUND:')) {\n    throw new Error(\n      `Prose execution failed: OpenProse skills not available. ` +\n        `Skills must be installed AND approved. Required skills: ${config.skills.join(', ')}`\n    );\n  }\n\n  return result;\n}\n\n/**\n * Extract and validate prose configuration from a config variable\n * The model field must be an executable Variable (e.g., @opus from @mlld/claude)\n */\nfunction extractProseConfig(configVar: any, configVarName: string, env: Environment): ProseConfig {\n  const value = configVar.value;\n\n  // Handle null/undefined\n  if (value === null || value === undefined) {\n    throw new Error(\n      `Prose config @${configVarName} is ${value === null ? 'null' : 'undefined'}. ` +\n      `Expected an object with { model: @executor, skillName?: string }.`\n    );\n  }\n\n  // Handle object config\n  if (typeof value === 'object' && !Array.isArray(value)) {\n    // Validate model is present\n    if (!value.model) {\n      throw new Error(\n        `Prose config @${configVarName} missing required 'model' field. ` +\n        `Expected: { model: @opus } where @opus is an executable from @mlld/claude.`\n      );\n    }\n\n    // Model should be a Variable (executable)\n    let modelVar: Variable;\n    let modelName: string;\n\n    if (isExecutableVariable(value.model)) {\n      // model is directly an executable Variable\n      modelVar = value.model;\n      modelName = modelVar.name || 'model';\n    } else if (typeof value.model === 'string') {\n      // model is a string reference to an executable (e.g., \"opus\")\n      // Look it up in the environment\n      const resolved = env.getVariable(value.model);\n      if (!resolved) {\n        throw new Error(\n          `Prose config @${configVarName}.model references unknown variable @${value.model}. ` +\n          `Import an executor like: import { @opus } from @mlld/claude`\n        );\n      }\n      if (!isExecutableVariable(resolved)) {\n        throw new Error(\n          `Prose config @${configVarName}.model must be an executable, but @${value.model} is not. ` +\n          `Use an executor like @opus from @mlld/claude.`\n        );\n      }\n      modelVar = resolved;\n      modelName = value.model;\n    } else {\n      throw new Error(\n        `Prose config @${configVarName}.model must be an executable (like @opus from @mlld/claude), ` +\n        `got ${typeof value.model}.`\n      );\n    }\n\n    // Validate skills if provided\n    if (value.skills !== undefined && !Array.isArray(value.skills)) {\n      throw new Error(\n        `Prose config @${configVarName}.skills must be an array, got ${typeof value.skills}.`\n      );\n    }\n\n    // Default skills for OpenProse plugin\n    const defaultSkills = [\n      'open-prose:prose-boot',\n      'open-prose:prose-compile',\n      'open-prose:prose-run'\n    ];\n\n    return {\n      model: modelVar,\n      modelName,\n      cwd: value.cwd,\n      skills: value.skills || defaultSkills,\n      skillPrompt: value.skillPrompt,\n      skillPromptEnd: value.skillPromptEnd,\n      maxTokens: value.maxTokens,\n      temperature: value.temperature\n    };\n  }\n\n  // Handle executable variable directly (shorthand: prose:@opus)\n  if (isExecutableVariable(configVar)) {\n    return {\n      model: configVar,\n      modelName: configVar.name || configVarName,\n      skills: [\n        'open-prose:prose-boot',\n        'open-prose:prose-compile',\n        'open-prose:prose-run'\n      ]\n    };\n  }\n\n  // Handle arrays and other types\n  if (Array.isArray(value)) {\n    throw new Error(\n      `Prose config @${configVarName} is an array. ` +\n      `Expected: { model: @opus } where @opus is an executable.`\n    );\n  }\n\n  throw new Error(\n    `Prose config @${configVarName} has invalid type '${typeof value}'. ` +\n    `Expected an object with { model: @executor } or an executable directly.`\n  );\n}\n\ninterface ProseConfig {\n  model: Variable;  // Executable variable (e.g., @opus from @mlld/claude)\n  modelName: string;  // Name of the executable for error messages\n  cwd?: string;\n  skills: string[];  // Skills needed for prose execution (e.g., [\"open-prose:prose-run\"])\n  skillPrompt?: string;\n  skillPromptEnd?: string;\n  maxTokens?: number;\n  temperature?: number;\n}\n\n/**\n * Parse and interpolate a prose template using the proper grammar parser\n * Supports both ATT (@var) and MTT ({{var}}) styles\n */\nasync function parseAndInterpolateTemplate(\n  templateContent: string,\n  style: 'att' | 'mtt',\n  env: Environment\n): Promise<string> {\n  const { parseSync } = await import('@grammar/parser');\n  const startRule = style === 'mtt' ? 'TemplateBodyMtt' : 'TemplateBodyAtt';\n\n  let templateNodes: any[];\n  try {\n    templateNodes = parseSync(templateContent, { startRule });\n  } catch (parseErr: any) {\n    // Fallback to simple interpolation if parser fails\n    if (process.env.DEBUG_EXEC) {\n      logger.debug('Template parse failed, using fallback:', parseErr.message);\n    }\n\n    if (style === 'mtt') {\n      // Normalize {{var}} to @var for fallback interpolation\n      const normalized = templateContent.replace(/{{\\s*([A-Za-z_][\\w.]*)\\s*}}/g, '@$1');\n      return interpolateProseTemplate(normalized, env);\n    }\n    return interpolateProseTemplate(templateContent, env);\n  }\n\n  // Interpolate the parsed template nodes\n  return interpolate(templateNodes, env, InterpolationContext.Default);\n}\n\n/**\n * Interpolate a prose template file with ATT-style variables (@var)\n * Simple fallback interpolation when parser is not available\n */\nasync function interpolateProseTemplate(\n  templateContent: string,\n  env: Environment\n): Promise<string> {\n  // Simple ATT interpolation - replace @varName with variable values\n  const regex = /@([a-zA-Z_][\\w.]*)/g;\n  let result = templateContent;\n  let match: RegExpExecArray | null;\n\n  const seen = new Set<string>();\n  while ((match = regex.exec(templateContent)) !== null) {\n    const varPath = match[1];\n    if (seen.has(varPath)) continue;\n    seen.add(varPath);\n\n    // Split by dots for nested access\n    const parts = varPath.split('.');\n    const varName = parts[0];\n    const variable = env.getVariable(varName);\n\n    if (variable) {\n      let value = variable.value;\n      // Navigate nested fields\n      for (let i = 1; i < parts.length; i++) {\n        if (value && typeof value === 'object') {\n          value = (value as any)[parts[i]];\n        } else {\n          value = undefined;\n          break;\n        }\n      }\n\n      if (value !== undefined) {\n        const stringValue = typeof value === 'string' ? value : JSON.stringify(value);\n        result = result.replace(new RegExp(`@${varPath.replace('.', '\\\\.')}`, 'g'), stringValue);\n      }\n    }\n  }\n\n  return result;\n}\n\n/**\n * Invoke the model executor with the wrapped prose prompt.\n *\n * The model executor (e.g., @opus from @mlld/claude) takes a prompt parameter\n * and returns the LLM's response.\n */\nasync function invokeModelExecutor(\n  prompt: string,\n  config: ProseConfig,\n  env: Environment\n): Promise<string> {\n  const modelVar = config.model;\n  const modelName = config.modelName;\n\n  if (!isExecutableVariable(modelVar)) {\n    throw new Error(\n      `Prose config model is not an executable. ` +\n      `Expected an executor like @opus from @mlld/claude.`\n    );\n  }\n\n  // Construct an ExecInvocation node to call the model executor with the prompt\n  // The executor signature is: exe @opus(prompt) = @prompt | cmd { claude -p ... }\n  const commandRef: CommandReference = {\n    type: 'CommandReference',\n    identifier: modelName,\n    args: [\n      {\n        type: 'VariableReference',\n        identifier: '__prose_prompt__',\n        location: null\n      } as any\n    ]\n  };\n\n  const invocation: ExecInvocation = {\n    type: 'ExecInvocation',\n    commandRef,\n    location: null\n  };\n\n  // Set up the prompt as a temporary variable\n  const execEnv = env.createChild();\n  execEnv.setVariable('__prose_prompt__', createSimpleTextVariable('__prose_prompt__', prompt));\n\n  // Also make the model executor available by the name we're calling\n  // (in case it was passed as an object field rather than directly in scope)\n  if (!execEnv.getVariable(modelName)) {\n    execEnv.setVariable(modelName, modelVar);\n  }\n\n  try {\n    const result = await evaluateExecInvocation(invocation, execEnv);\n\n    // Extract the string value from the result\n    if (typeof result.value === 'string') {\n      return result.value;\n    }\n    if (result.value && typeof result.value === 'object' && 'value' in result.value) {\n      return String((result.value as any).value);\n    }\n    return String(result.value ?? '');\n  } catch (err: any) {\n    throw new Error(\n      `Prose execution via @${modelName} failed: ${err.message || err}`\n    );\n  }\n}\n"]}