{"version":3,"file":"index.cjs","sources":["../../../src/ai/cron-expression.ts","../../../src/ai/lookback-window.ts"],"sourcesContent":["import type { OpenAI } from 'openai';\n\ntype OpenAIChatCompletionResponseType = OpenAI.Chat.Completions.ChatCompletion & {\n _request_id?: string | null;\n};\n\nexport type ValidateHumanReadableCronExpressionPromptReturnType = {\n isValid: boolean;\n reason: string;\n _completion: OpenAIChatCompletionResponseType;\n};\n\nconst model = 'gpt-4o-mini';\n\n/**\n * Validates if a human-readable prompt is related to generating cron expressions or scheduling tasks\n * @param openai - The OpenAI client\n * @param prompt - The human-readable prompt\n * @returns The validation result\n */\nexport async function validateHumanReadableCronExpressionPrompt(\n openai: OpenAI,\n prompt: string,\n): Promise {\n const response = await openai.chat.completions.create({\n model,\n messages: [\n {\n role: 'system',\n content: `You are a validator that determines if a user's prompt is related to generating cron expressions or scheduling tasks.\n\n Return a JSON object with two fields:\n 1. \"isValid\": boolean - true if the prompt is asking about creating a cron expression or scheduling, false otherwise. It should also be\n false if the prompt is asking to generate an invalid cron expression.\n 2. \"reason\": string - a brief explanation of your decision\n\n Examples of valid prompts:\n - \"I need a cron job that runs every day at midnight\"\n - \"every 15 minutes\"\n - \"Every year\"\n - \"every 50 minutes\"\n - \"every hour\"\n - \"every day at 2 AM\"\n\n Examples of invalid prompts:\n - \"What's the weather like today?\"\n - \"Write me a poem about cats\"\n - \"How do I make chocolate chip cookies?\"\n `,\n },\n {\n role: 'user',\n content: prompt,\n },\n ],\n });\n\n const content = response.choices[0]?.message?.content;\n\n if (!content) {\n throw new Error('Failed to validate the prompt');\n }\n\n try {\n // Parse the JSON response\n const validation = JSON.parse(content);\n return {\n ...validation,\n _completion: response,\n };\n } catch (error) {\n throw new Error('Error parsing validation response');\n }\n}\n\nexport type HumanReadableToCronExpressionReturnType = {\n cronExpression: string;\n _completion: OpenAIChatCompletionResponseType;\n};\n\n/**\n * Generates a cron expression from a human-readable prompt\n * @param openai - The OpenAI client\n * @param prompt - The human-readable prompt\n * @returns The cron expression\n */\nexport async function humanReadableToCronExpression(\n openai: OpenAI,\n prompt: string,\n): Promise {\n // Request the OpenAI API for the response without streaming\n const response = await openai.chat.completions.create({\n model,\n temperature: 0,\n messages: [\n {\n role: 'system',\n content: `Below is text describing a cron expression.\n Your goal is to:\n - Convert the text to a valid cron expression.\n - The cron expression you generate must be in 5-field format: minute hour day month dayOfWeek\n - The cron expression must match this pattern: minute hour day month dayOfWeek\n - Return only the generated cron expression and nothing else.\n\n Here are some examples:\n - Text: A cron that runs every hour\n - Cron: 0 * * * *\n - Text: A cron that runs every 12 hours\n - Cron: 0 */12 * * *\n - Text: A cron that runs every 30 minutes\n - Cron: */30 * * * *\n - Text: A cron that runs every day at 2 AM\n - Cron: 0 2 * * *\n - Text: A cron that runs every 50 minutes\n - Cron: */50 * * * *\n - Text: A cron that runs every week on Monday at 9 AM\n - Cron: 0 9 * * 1`,\n },\n {\n role: 'user',\n content: prompt,\n },\n ],\n });\n\n // Validate the response\n const content = response.choices[0]?.message?.content?.trim();\n if (!content) {\n throw new Error('Failed to generate a cron expression');\n }\n\n return {\n cronExpression: content,\n _completion: response,\n };\n}\n","import type { OpenAI } from 'openai';\n\nexport type HumanReadableToLookbackMinutesReturnType = {\n minutes: number;\n _raw?: string;\n};\n\nconst MINUTE = 1;\nconst HOUR = 60;\nconst DAY = 24 * HOUR;\n\nconst COMMON_MAP: Record = {\n '1h': HOUR,\n '1 hour': HOUR,\n 'one hour': HOUR,\n '2h': 2 * HOUR,\n '2 hours': 2 * HOUR,\n '6h': 6 * HOUR,\n '6 hours': 6 * HOUR,\n '12h': 12 * HOUR,\n '12 hours': 12 * HOUR,\n '24h': 24 * HOUR,\n '24 hours': 24 * HOUR,\n '1d': DAY,\n '1 day': DAY,\n day: DAY,\n '30m': 30,\n '30 minutes': 30,\n '15m': 15,\n '15 minutes': 15,\n};\n\n/**\n * Lightweight local parser for common patterns: \"X minutes/hours/days\"\n */\nexport function parseLookbackToMinutesLocal(text: string): number | null {\n const t = text.toLowerCase().trim();\n if (t in COMMON_MAP) return COMMON_MAP[t];\n\n // e.g. \"last 6 hours\", \"6h\", \"6 hours\", \"90 minutes\", \"1 day\"\n const re = /(last\\s+)?(\\d+(?:\\.\\d+)?)\\s*(minutes?|mins?|m|hours?|hrs?|h|days?|d)\\b/;\n const m = t.match(re);\n if (!m) return null;\n const value = parseFloat(m[2]);\n const unit = m[3];\n if (Number.isNaN(value)) return null;\n\n if (/^m(in(ute)?s?)?$/.test(unit)) return Math.round(value * MINUTE);\n if (/^h((ou)?rs?)?$/.test(unit)) return Math.round(value * HOUR);\n if (/^d(ays?)?$/.test(unit)) return Math.round(value * DAY);\n return null;\n}\n\n/**\n * Uses OpenAI to convert a human prompt like \"last 6 hours\" into minutes\n */\nexport async function humanReadableToLookbackMinutes(\n openai: OpenAI,\n prompt: string,\n): Promise {\n const local = parseLookbackToMinutesLocal(prompt);\n if (local !== null) {\n return { minutes: local, _raw: 'local' };\n }\n\n const resp = await openai.chat.completions.create({\n model: 'gpt-4o-mini',\n temperature: 0,\n messages: [\n {\n role: 'system',\n content:\n 'Convert the user text describing a time window into a single integer number of minutes. 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