@axiomhq/ai/dist/bin.cjs.map

Axiom AI SDK provides an API to wrap your AI calls with observability instrumentation.

{"version":3,"sources":["../src/bin.ts","../src/commands/push.ts","../src/transpiler.ts","../src/commands/pull.ts","../src/commands/run.ts","../src/evals/run-vitest.ts","../src/evals/reporter.ts","../src/evals/instrument.ts"],"sourcesContent":["#!/usr/bin/env node\n\n// Load environment variables using @next/env\nimport pkg from '@next/env';\nconst { loadEnvConfig } = pkg;\n\n// Load .env files from the current working directory\nloadEnvConfig(process.cwd());\n\nimport { Command } from 'commander';\nimport { loadPushCommand } from './commands/push';\nimport { loadPullCommand } from './commands/pull';\nimport { loadRunCommand } from './commands/run';\n\nconst program = new Command();\n\nprogram\n  .name('axiom')\n  .description(\"Axiom's CLI to manage your objects and run evals\")\n  .version(__SDK_VERSION__);\n\nloadPushCommand(program);\nloadPullCommand(program);\nloadRunCommand(program);\n\nprogram.parse();\n","import { Command } from 'commander';\nimport {\n  loadPromptModule,\n  extractPromptFromModule,\n  generatePromptFileFromApiResponse,\n} from '../transpiler';\nimport type { Prompt } from '../types';\nimport fs from 'node:fs/promises';\nimport readline from 'node:readline';\n\nasync function askConfirmation(message: string): Promise<boolean> {\n  const rl = readline.createInterface({\n    input: process.stdin,\n    output: process.stdout,\n  });\n\n  return new Promise((resolve) => {\n    rl.question(`${message} (y/N): `, (answer) => {\n      rl.close();\n      resolve(answer.toLowerCase() === 'y' || answer.toLowerCase() === 'yes');\n    });\n  });\n}\n\nexport const loadPushCommand = (program: Command) => {\n  const push = new Command('push')\n    .description('Push a new version of an object')\n    .argument(\n      '<object>',\n      'The object to push, could be a prompt, en eval, a monitor, a dashboard, etc.',\n    )\n    .option('--prod', 'Adds the production tag to the prompt')\n    .option('--yes', 'Automatically confirm overwriting the file with server response')\n    .action(async (filePath: string, options: { yes?: boolean; prod?: boolean }) => {\n      let content: Prompt | null = null;\n      if (!filePath.endsWith('.prompt.ts')) {\n        console.error('Prompt files must end with .prompt.ts');\n        process.exit(1);\n      }\n\n      try {\n        const moduleContent = await loadPromptModule(filePath);\n        const promptData = extractPromptFromModule(moduleContent, filePath);\n\n        content = promptData;\n\n        console.log(`Transpiled prompt: ${promptData.name} (${promptData.slug})`);\n      } catch (error) {\n        console.error('Failed to transpile prompt file:', error);\n        process.exit(1);\n      }\n\n      if (!content) {\n        console.error('No content found');\n        process.exit(1);\n      }\n\n      let shouldProceed = options.yes;\n      if (!shouldProceed) {\n        shouldProceed = await askConfirmation(\n          `This will push \"${content.name}\" to Axiom and overwrite ${filePath}, are you sure you want to continue?`,\n        );\n      }\n\n      if (!shouldProceed) {\n        console.log('Push operation cancelled.');\n        process.exit(0);\n      }\n\n      try {\n        const response = await fetch(`${process.env.AXIOM_URL}/v1/prompts`, {\n          method: 'POST',\n          headers: {\n            Authorization: `Bearer ${process.env.AXIOM_TOKEN}`,\n            'Content-Type': 'application/json',\n            'x-axiom-client': 'axiom-ai-cli',\n            'x-axiom-check': 'good',\n          },\n          body: JSON.stringify({\n            ...content,\n            tags: options.yes ? ['production'] : [],\n          }),\n        });\n\n        if (!response.ok) {\n          try {\n            const errorText = await response.clone().json();\n            console.error(`Failed to fetch prompt: ${response.status} ${response.statusText}`);\n            console.error(JSON.stringify(errorText, null, 2));\n            process.exit(1);\n          } catch (_error) {\n            const errorText = await response.clone().text();\n            console.error(`Failed to fetch prompt: ${response.status} ${response.statusText}`);\n            console.error(errorText);\n            process.exit(1);\n          }\n        }\n\n        const apiResponse = await response.json();\n        console.log(\n          `Successfully pushed prompt: ${apiResponse.prompt.name} (${apiResponse.prompt.slug})`,\n        );\n        console.log(`Version: ${apiResponse.version.version}`);\n\n        const updatedTsContent = generatePromptFileFromApiResponse(apiResponse);\n\n        await fs.writeFile(filePath, updatedTsContent, 'utf-8');\n\n        console.log(`Successfully updated ${filePath}`);\n      } catch (error) {\n        console.error('Failed to push prompt:', error);\n        process.exit(1);\n      }\n    });\n\n  program.addCommand(push);\n};\n","import { build } from 'esbuild';\nimport os from 'node:os';\nimport fs from 'node:fs/promises';\nimport path from 'node:path';\nimport { basename } from 'node:path';\nimport type { Prompt } from './types';\n\nexport async function loadPromptModule(filePath: string) {\n  const result = await build({\n    entryPoints: [filePath],\n    bundle: true,\n    write: false,\n    platform: 'node',\n    format: 'esm',\n    target: ['node18'],\n    sourcemap: false,\n    external: [\n      // Only Node.js built-ins should be external\n      'fs',\n      'fs/promises',\n      'node:fs',\n      'node:fs/promises',\n      'readline',\n      'node:readline',\n      'path',\n      'node:path',\n      'os',\n      'node:os',\n      'url',\n      'node:url',\n      'util',\n      'node:util',\n      'crypto',\n      'node:crypto',\n      'events',\n      'node:events',\n      'stream',\n      'node:stream',\n      'buffer',\n      'node:buffer',\n      'process',\n      'node:process',\n    ],\n  });\n\n  const code = result.outputFiles[0].text;\n\n  // Create a unique temporary file\n  const tempDir = os.tmpdir();\n  const tempFileName = `axiom-ai-prompt-${Date.now()}-${Math.random().toString(36).substring(2)}.mjs`;\n  const tempFilePath = path.join(tempDir, tempFileName);\n\n  try {\n    // Write the bundled code to temporary file\n    await fs.writeFile(tempFilePath, code, 'utf-8');\n\n    // Dynamically import the temporary module\n    const moduleUrl = `file://${tempFilePath}`;\n    const module = await import(moduleUrl);\n\n    return module.default || module;\n  } finally {\n    // Clean up the temporary file\n    try {\n      await fs.unlink(tempFilePath);\n    } catch (error) {\n      // Ignore cleanup errors - temp files will be cleaned up by OS eventually\n      console.warn(`Failed to clean up temporary file ${tempFilePath}:`, error);\n    }\n  }\n}\n\n/**\n * Convert TypeBox arguments to JSON Schema format expected by the API\n */\nfunction convertTypeBoxArgumentsToJsonSchema(arguments_: Record<string, any>): any {\n  if (!arguments_ || typeof arguments_ !== 'object') {\n    return {\n      type: 'object',\n      properties: {},\n      required: [],\n      additionalProperties: false,\n    };\n  }\n\n  const properties: Record<string, any> = {};\n  const required: string[] = [];\n\n  for (const [key, value] of Object.entries(arguments_)) {\n    if (value && typeof value === 'object' && value.type) {\n      // This is a TypeBox schema object that has been serialized\n      properties[key] = {\n        type: value.type,\n        ...(value.description && { description: value.description }),\n        ...(value.enum && { enum: value.enum }),\n        ...(value.items && { items: value.items }),\n        ...(value.properties && { properties: value.properties }),\n        ...(value.required && { required: value.required }),\n      };\n\n      // For now, treat all arguments as required (this matches the existing behavior)\n      // In the future, we could detect Type.Optional() usage\n      required.push(key);\n    }\n  }\n\n  return {\n    type: 'object',\n    properties,\n    required,\n    additionalProperties: false,\n  };\n}\n\nexport function extractPromptFromModule(moduleContent: any, filePath: string): Prompt {\n  // Generate ID from file path if not provided\n  const fileBaseName = basename(filePath, '.ts'); // Remove .ts extension\n  const defaultId = fileBaseName.toLowerCase().replace(/[^a-z0-9]/g, '-');\n\n  // Convert TypeBox arguments to JSON Schema format\n  const convertedArguments = convertTypeBoxArgumentsToJsonSchema(moduleContent.arguments);\n\n  // Extract and validate required fields from the module content\n  const prompt: Prompt = {\n    name: moduleContent.name || 'Untitled Prompt',\n    slug: moduleContent.slug || defaultId,\n    messages: moduleContent.messages || [],\n    model: moduleContent.model,\n    options: moduleContent.options,\n    arguments: convertedArguments,\n    id: moduleContent.id || defaultId,\n    version: moduleContent.version || '1.0.0',\n    // Optional fields from API response\n    ...(moduleContent.promptId && { promptId: moduleContent.promptId }),\n    ...(moduleContent.description && { description: moduleContent.description }),\n  };\n\n  // Validate required fields\n  if (!prompt.name) {\n    throw new Error('Prompt must have a name');\n  }\n  if (!prompt.slug) {\n    throw new Error('Prompt must have a slug');\n  }\n  if (!Array.isArray(prompt.messages)) {\n    throw new Error('Prompt messages must be an array');\n  }\n\n  if (!prompt.model) {\n    throw new Error('Prompt must have a model');\n  }\n\n  return prompt;\n}\n\n/**\n * Transform JSON Schema to TypeBox/Template validator format\n */\nexport function transformJsonSchemaToTypeBox(schema: any): string {\n  if (schema.type === 'string') {\n    if (schema.enum && Array.isArray(schema.enum)) {\n      // Handle enum as Union of Literals\n      const literals = schema.enum.map((value: string) => `Type.Literal('${value}')`).join(', ');\n      const options = schema.description ? `, { description: '${schema.description}' }` : '';\n      return `Type.Union([${literals}]${options})`;\n    } else {\n      // Regular string\n      const options = schema.description ? `{ description: '${schema.description}' }` : '';\n      return `Type.String(${options})`;\n    }\n  }\n\n  if (schema.type === 'number' || schema.type === 'integer') {\n    const typeMethod = schema.type === 'integer' ? 'Integer' : 'Number';\n    const options = schema.description ? `{ description: '${schema.description}' }` : '';\n    return `Type.${typeMethod}(${options})`;\n  }\n\n  if (schema.type === 'boolean') {\n    const options = schema.description ? `{ description: '${schema.description}' }` : '';\n    return `Type.Boolean(${options})`;\n  }\n\n  if (schema.type === 'array') {\n    const itemsType = schema.items ? transformJsonSchemaToTypeBox(schema.items) : 'Type.String()';\n    const options = schema.description ? `, { description: '${schema.description}' }` : '';\n    return `Type.Array(${itemsType}${options})`;\n  }\n\n  if (schema.type === 'object') {\n    if (schema.properties) {\n      const props = Object.entries(schema.properties)\n        .map(([key, value]: [string, any]) => {\n          const isRequired = schema.required && schema.required.includes(key);\n          const propType = transformJsonSchemaToTypeBox(value);\n          return `    ${key}: ${isRequired ? propType : `Type.Optional(${propType})`}`;\n        })\n        .join(',\\n');\n\n      const options = schema.description ? `, { description: '${schema.description}' }` : '';\n      return `Type.Object({\\n${props}\\n  }${options})`;\n    } else {\n      const options = schema.description ? `{ description: '${schema.description}' }` : '';\n      return `Type.Object({}${options ? `, ${options}` : ''})`;\n    }\n  }\n\n  // Fallback for unknown types\n  return 'Type.String()';\n}\n\n/**\n * Generate TypeScript prompt file content from API response\n */\nexport function generatePromptFileFromApiResponse(apiResponse: any): string {\n  const { prompt, version } = apiResponse;\n  const { data, options } = version;\n\n  // Transform arguments from JSON Schema to TypeBox format\n  let argumentsCode = '{}';\n  if (data.arguments && data.arguments.properties) {\n    const argEntries = Object.entries(data.arguments.properties)\n      .map(([key, schema]: [string, any]) => {\n        const isRequired = data.arguments.required && data.arguments.required.includes(key);\n        const typeCode = transformJsonSchemaToTypeBox(schema);\n        return `    ${key}: ${isRequired ? typeCode : `Type.Optional(${typeCode})`}`;\n      })\n      .join(',\\n');\n\n    if (argEntries) {\n      argumentsCode = `{\\n${argEntries}\\n  }`;\n    }\n  }\n\n  // Generate the TypeScript file content\n  return `import { Type } from '@axiomhq/ai';\n\nexport default {\n  name: '${prompt.name}',\n  slug: '${prompt.slug}',\n  description: '${prompt.description || ''}',\n  messages: [${data.messages\n    .map(\n      (msg: any) => `\n    {\n      role: '${msg.role}',\n      content: '${msg.content.replace(/'/g, \"\\\\'\")}',\n    }`,\n    )\n    .join(',')}\n  ],\n  model: '${data.model || 'gpt-4'}',\n  options: {\n${\n  options\n    ? Object.entries(options)\n        .map(([key, value]) => `    ${key}: ${value}`)\n        .join(',\\n')\n    : ''\n}\n  },\n  arguments: ${argumentsCode},\n  version: '${version.version}',\n  promptId: '${prompt.promptId}',\n};\n`;\n}\n","import { Command } from 'commander';\nimport { generatePromptFileFromApiResponse } from '../transpiler';\nimport * as fs from 'fs/promises';\nimport * as path from 'path';\n\nexport const loadPullCommand = (program: Command) => {\n  const pull = new Command('pull')\n    .description('Pull a version of an object')\n    .argument(\n      '<slug>',\n      'The object to pull, could be a prompt, en eval, a monitor, a dashboard, etc.',\n    )\n    .option('--version <version>', 'The version to pull, default: latest', 'latest')\n    .option('--output <path>', 'Output file path (optional, defaults to <slug>.prompt.ts)')\n    .action(async (slug: string, options: { version: string; output?: string }) => {\n      try {\n        console.log(`Pulling prompt: ${slug} (version: ${options.version})`);\n\n        const url = `${process.env.AXIOM_URL}/v1/prompts/${slug}`;\n        const response = await fetch(url, {\n          method: 'GET',\n          headers: {\n            Authorization: `Bearer ${process.env.AXIOM_TOKEN}`,\n            'Content-Type': 'application/json',\n            'x-axiom-client': 'axiom-ai-cli',\n            'x-axiom-check': 'good',\n          },\n        });\n\n        if (!response.ok) {\n          try {\n            const errorText = await response.clone().json();\n            console.error(`Failed to fetch prompt: ${response.status} ${response.statusText}`);\n            console.error(JSON.stringify(errorText, null, 2));\n            process.exit(1);\n          } catch (_error) {\n            const errorText = await response.clone().text();\n            console.error(`Failed to fetch prompt: ${response.status} ${response.statusText}`);\n            console.error(errorText);\n            process.exit(1);\n          }\n        }\n\n        const apiResponse = await response.json();\n\n        const tsContent = generatePromptFileFromApiResponse(apiResponse);\n\n        const outputPath = options.output || `${slug}.prompt.ts`;\n        const fullPath = path.resolve(outputPath);\n\n        await fs.writeFile(fullPath, tsContent, 'utf-8');\n\n        console.log(`Successfully generated prompt file: ${fullPath}`);\n        console.log(`Prompt: ${apiResponse.prompt.name} (${apiResponse.prompt.slug})`);\n        console.log(`Version: ${apiResponse.version.version}`);\n      } catch (error) {\n        console.error('Failed to pull prompt:', error);\n        process.exit(1);\n      }\n    });\n\n  program.addCommand(pull);\n};\n","import { Command } from 'commander';\nimport { runVitest } from '../evals/run-vitest';\n\nexport const loadRunCommand = (program: Command) => {\n  return program.addCommand(\n    new Command('run')\n      .description('run evals locally')\n      .argument('<path>', 'Path to an eval test file, should be in the form of name.eval.ts')\n      .action(async (file: string) => {\n        if (!process.env.AXIOM_URL || !process.env.AXIOM_TOKEN || !process.env.AXIOM_DATASET) {\n          throw new Error('AXIOM_URL, AXIOM_TOKEN, and AXIOM_DATASET must be set');\n        }\n        await runVitest(file);\n      }),\n  );\n};\n","import { createVitest, registerConsoleShortcuts } from 'vitest/node';\nimport { AxiomReporter } from './reporter';\nimport { flush } from './instrument';\n\nexport const runVitest = async (file: string) => {\n  const vi = await createVitest('test', {\n    // root: process.cwd(),\n    mode: 'test',\n    include: [file ? file : '**/*.eval.ts'],\n    reporters: ['verbose', new AxiomReporter()],\n    environment: 'node',\n    browser: undefined,\n  });\n\n  await vi.start();\n\n  const dispose = registerConsoleShortcuts(vi, process.stdin, process.stdout);\n\n  if (!vi.shouldKeepServer()) {\n    dispose();\n    await flush();\n    await vi.close();\n    process.exit(0);\n  }\n\n  await flush();\n};\n","import type { SerializedError } from 'vitest';\nimport type { Reporter, TestModule, TestRunEndReason, TestSuite } from 'vitest/node.js';\nimport type { TaskMeta } from 'vitest/index.cjs';\nimport type { EvalReport } from './eval';\n\n/**\n * Custom Vitest reporter for Axiom AI evaluations.\n *\n * This reporter collects evaluation results and scores from tests\n * and processes them for further analysis and reporting.\n *\n * @experimental This API is experimental and may change in future versions.\n */\nexport class AxiomReporter implements Reporter {\n  onTestSuiteReady(_testSuite: TestSuite) {}\n\n  onTestSuiteResult(testSuite: TestSuite) {\n    for (const test of testSuite.children.array()) {\n      if (test.type !== 'test') continue;\n      const testMeta = test.meta() as TaskMeta & { eval: EvalReport };\n\n      if (!testMeta.eval) {\n        return;\n      }\n\n      // build scores array\n      const scores: { name: string; score: number }[] = [];\n      for (const s of Object.entries(testMeta.eval.scores)) {\n        scores.push({ name: s[1].name, score: s[1].score });\n      }\n    }\n  }\n\n  async onTestRunEnd(\n    _testModules: ReadonlyArray<TestModule>,\n    _errors: ReadonlyArray<SerializedError>,\n    _reason: TestRunEndReason,\n  ) {}\n}\n","import { BatchSpanProcessor, NodeTracerProvider } from '@opentelemetry/sdk-trace-node';\nimport { resourceFromAttributes } from '@opentelemetry/resources';\nimport { OTLPTraceExporter } from '@opentelemetry/exporter-trace-otlp-http';\nimport { trace, type Context, type SpanOptions } from '@opentelemetry/api';\n\nconst collectorOptions = {\n  url: process.env.AXIOM_URL\n    ? `${process.env.AXIOM_URL}/v1/traces`\n    : 'https://api.axiom.co/v1/traces', // Axiom API endpoint for trace data\n  headers: {\n    Authorization: `Bearer ${process.env.AXIOM_TOKEN}`, // Replace API_TOKEN with your actual API token\n    'X-Axiom-Dataset': process.env.AXIOM_DATASET || '', // Replace DATASET_NAME with your dataset\n  },\n  concurrencyLimit: 10, // an optional limit on pending requests\n};\n\n// export const consoleExporter = new ConsoleSpanExporter()\nexport const exporter = new OTLPTraceExporter(collectorOptions);\n\nconst processor = new BatchSpanProcessor(exporter, {\n  maxQueueSize: 2048,\n  maxExportBatchSize: 512,\n  scheduledDelayMillis: 5000,\n  exportTimeoutMillis: 30000,\n});\n\nconst provider = new NodeTracerProvider({\n  resource: resourceFromAttributes({\n    ['service.name']: 'axiom-ai',\n    ['service.version']: __SDK_VERSION__,\n  }),\n  spanProcessors: [processor],\n});\n\nprovider.register();\n\n// Create a shared tracer instance\nconst tracer = trace.getTracer('axiom-ai', __SDK_VERSION__);\n\nexport const flush = async () => {\n  await provider.forceFlush();\n};\n\nexport const startSpan = (name: string, opts: SpanOptions, context?: Context) => {\n  return tracer.startSpan(name, opts, 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