feat/PDFGenPdfLib

export/pdf/README.MD

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+<!-- START_INFOCARD -->
+
+# AI-Powered PDF Report Generator
+
+**Automatically generate and upload AI-analyzed PDF reports from Flatfile data**
+
+The `AI-Powered PDF Report Generator` is a Flatfile Listener plugin that creates comprehensive PDF reports with AI-driven analysis when a job is ready. It fetches sheet data, utilizes Anthropic's AI for in-depth analysis, generates a visually appealing PDF report, and seamlessly uploads it back to Flatfile.
+
+**Event Type:**
+`listener.on('job:ready')`
+
+**Supported field types:**
+All field types are supported as the plugin processes entire sheets.
+
+<!-- END_INFOCARD -->
+
+## Features
+
+- Automatic PDF report generation when a job is ready
+- AI-powered data analysis using Anthropic's Claude model
+- Dynamic PDF creation with data summaries and placeholders for charts
+- Seamless upload of generated reports back to Flatfile
+- Error handling and logging for robust operation
+
+## Installation
+
+1. Install the required dependencies:
+
+```bash
+npm install @flatfile/listener @flatfile/api pdf-lib @anthropic-ai/sdk
+```
+
+2. Set up the necessary environment variables:
+
+```
+FLATFILE_API_KEY=your_flatfile_api_key
+ANTHROPIC_API_KEY=your_anthropic_api_key
+FLATFILE_SPACE_ID=your_flatfile_space_id
+FLATFILE_ENVIRONMENT_ID=your_flatfile_environment_id
+```
+
+3. Import and use the plugin in your Flatfile configuration.
+
+## Example Usage
+
+```javascript
+import listener from './path-to-plugin';
+
+// Use the listener in your Flatfile configuration
+export default {
+  name: "My Flatfile Project",
+  plugins: [listener],
+  // ... other configuration options
+};
+```
+
+## Configuration
+
+The plugin requires the following environment variables to be set:
+
+- `FLATFILE_API_KEY`: Your Flatfile API key
+- `ANTHROPIC_API_KEY`: Your Anthropic API key
+- `FLATFILE_SPACE_ID`: The ID of your Flatfile space
+- `FLATFILE_ENVIRONMENT_ID`: The ID of your Flatfile environment
+
+Ensure these are properly set in your environment before running the plugin.
+
+## Behavior
+
+1. When a `job:ready` event is triggered, the plugin fetches the sheet data from Flatfile.
+2. It then sends the first 10 rows of data to Anthropic's AI for analysis.
+3. A PDF report is generated, including:
+   - A title
+   - A summary of the total records
+   - A placeholder for charts or graphs
+   - The AI-generated analysis
+4. The PDF is temporarily saved and then uploaded back to Flatfile.
+5. The temporary PDF file is deleted after successful upload.
+
+In case of any errors during this process, they are logged, and the job is marked as failed with an error message.
+
+This plugin provides a powerful way to automatically generate insightful reports from your Flatfile data, enhancing data analysis and visualization capabilities.

export/pdf/package.json

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+{
+  "name": "@flatfile/plugin-export-pdf",
+  "version": "0.0.0",
+  "url": "https://github.com/FlatFilers/flatfile-plugins/tree/main/export/pdf",
+  "description": "A Flatfile plugin for generating PDF reports from a Flatfile Workbook",
+  "registryMetadata": {
+    "category": "export"
+  },
+  "engines": {
+    "node": ">= 16"
+  },
+  "browser": {
+    "./dist/index.cjs": "./dist/index.browser.cjs",
+    "./dist/index.mjs": "./dist/index.browser.mjs"
+  },
+  "exports": {
+    "types": "./dist/index.d.ts",
+    "node": {
+      "import": "./dist/index.mjs",
+      "require": "./dist/index.cjs"
+    },
+    "browser": {
+      "require": "./dist/index.browser.cjs",
+      "import": "./dist/index.browser.mjs"
+    },
+    "default": "./dist/index.mjs"
+  },
+  "main": "./dist/index.cjs",
+  "module": "./dist/index.mjs",
+  "source": "./src/index.ts",
+  "types": "./dist/index.d.ts",
+  "files": [
+    "dist/**"
+  ],
+  "scripts": {
+    "build": "rollup -c",
+    "build:watch": "rollup -c --watch",
+    "build:prod": "NODE_ENV=production rollup -c",
+    "check": "tsc ./**/*.ts --noEmit --esModuleInterop",
+    "test": "jest src/*.spec.ts --detectOpenHandles",
+    "test:unit": "jest src/*.spec.ts --testPathIgnorePatterns=.*\\.e2e\\.spec\\.ts$ --detectOpenHandles",
+    "test:e2e": "jest src/*.e2e.spec.ts --detectOpenHandles"
+  },
+  "keywords": [
+    "flatfile-plugins",
+    "category-export"
+  ],
+  "author": "Flatfile, Inc.",
+  "repository": {
+    "type": "git",
+    "url": "https://github.com/FlatFilers/flatfile-plugins.git",
+    "directory": "export/pdf"
+  },
+  "license": "ISC",
+  "dependencies": {
+    "@anthropic-ai/sdk": "^0.29.0",
+    "@flatfile/api": "^1.9.19",
+    "@flatfile/plugin-space-configure": "0.6.1",
+    "@flatfile/util-common": "^1.4.1",
+    "pdf-lib": "^1.17.1"
+  },
+  "peerDependencies": {
+    "@flatfile/listener": "^1.0.5"
+  },
+  "devDependencies": {
+    "@flatfile/hooks": "^1.5.0",
+    "@flatfile/rollup-config": "^0.1.1",
+    "@types/node": "^22.7.4",
+    "typescript": "^5.6.2"
+  }
+}

export/pdf/rollup.config.mjs

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+import { buildConfig } from '@flatfile/rollup-config'
+
+export default buildConfig({})

export/pdf/src/export.pdf.analyze.ts

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+import Anthropic from '@anthropic-ai/sdk'
+import { TextBlock } from '@anthropic-ai/sdk/resources'
+
+export async function analyzeDataWithAI(
+  sheetData: any[],
+  ANTHROPIC_API_KEY: string
+): Promise<TextBlock> {
+  const dataDescription = JSON.stringify(sheetData)
+
+  const anthropic = new Anthropic({
+    apiKey: ANTHROPIC_API_KEY,
+  })
+
+  const prompt = `Given the following dataset: ${dataDescription}
+
+  Please provide a concise analysis of this data, including:
+  1. A summary of the main features or columns in the dataset.
+  2. Any notable patterns or trends you can identify.
+  3. Potential insights or recommendations based on this data.
+
+  Limit your response to 3-4 paragraphs.`
+
+  const response = await anthropic.messages.create({
+    max_tokens: 1024,
+    messages: [{ role: 'user', content: prompt }],
+    model: 'claude-3-opus-20240229',
+  })
+
+  return response.content[0] as TextBlock
+}

export/pdf/src/export.pdf.generate.ts

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+import { FlatfileEvent } from '@flatfile/listener'
+import { PDFDocument, StandardFonts, rgb } from 'pdf-lib'
+import { analyzeDataWithAI } from './export.pdf.analyze'
+
+export async function generatePDFReport(
+  sheetData: any[],
+  event: FlatfileEvent
+) {
+  const pdfDoc = await PDFDocument.create()
+  const page = pdfDoc.addPage()
+  const { height } = page.getSize()
+  const font = await pdfDoc.embedFont(StandardFonts.Helvetica)
+  const anthropicApiKey =
+    process.env.ANTHROPIC_API_KEY || (await event.secrets('ANTHROPIC_API_KEY'))
+
+  if (!anthropicApiKey) {
+    throw new Error('Anthropic API key is not set')
+  }
+  // Add title
+  page.drawText('Data Analysis Report', {
+    x: 50,
+    y: height - 50,
+    size: 24,
+    font,
+    color: rgb(0, 0, 0),
+  })
+
+  // Add data summary
+  let yOffset = height - 100
+  page.drawText(`Total Records: ${sheetData.length}`, {
+    x: 50,
+    y: yOffset,
+    size: 12,
+    font,
+    color: rgb(0, 0, 0),
+  })
+
+  // Placeholder for chart/graph
+  yOffset -= 30
+  page.drawRectangle({
+    x: 50,
+    y: yOffset - 200,
+    width: 300,
+    height: 200,
+    borderColor: rgb(0, 0, 0),
+    borderWidth: 1,
+  })
+  page.drawText('Chart Placeholder', {
+    x: 175,
+    y: yOffset - 100,
+    size: 12,
+    font,
+    color: rgb(0.5, 0.5, 0.5),
+  })
+
+  // AI analysis
+  yOffset -= 250
+  page.drawText('AI Analysis:', {
+    x: 50,
+    y: yOffset,
+    size: 14,
+    font,
+    color: rgb(0, 0, 0),
+  })
+  yOffset -= 20
+
+  const aiAnalysis = await analyzeDataWithAI(sheetData, anthropicApiKey)
+  console.log('aiAnalysis', aiAnalysis)
+  const words = aiAnalysis.text.split(' ')
+  let line = ''
+  for (const word of words) {
+    if ((line + word).length > 70) {
+      page.drawText(line, {
+        x: 50,
+        y: yOffset,
+        size: 10,
+        font,
+        color: rgb(0, 0, 0),
+      })
+      yOffset -= 15
+      line = ''
+    }
+    line += (line ? ' ' : '') + word
+  }
+  if (line) {
+    page.drawText(line, {
+      x: 50,
+      y: yOffset,
+      size: 10,
+      font,
+      color: rgb(0, 0, 0),
+    })
+  }
+
+  return pdfDoc.save()
+}

export/pdf/src/export.pdf.plugin.ts

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+import api from '@flatfile/api'
+import type { FlatfileEvent, FlatfileListener } from '@flatfile/listener'
+import { jobHandler } from '@flatfile/plugin-job-handler'
+import * as fs from 'fs'
+import { generatePDFReport } from './export.pdf.generate'
+
+export function exportPDF() {
+  return function (listener: FlatfileListener) {
+    listener.use(
+      jobHandler('sheet:generatePDFReport', async (event: FlatfileEvent) => {
+        const { sheetId, spaceId, environmentId } = event.context
+
+        if (!sheetId) {
+          throw new Error('Sheet ID is missing from the event context')
+        }
+
+        const { data: records } = await api.records.get(sheetId, {
+          pageSize: 50,
+        })
+
+        const pdfBytes = await generatePDFReport(records.records, event)
+
+        const fileName = `report_${sheetId}_${Date.now()}.pdf`
+
+        const tempFilePath = `/tmp/${fileName}`
+        fs.writeFileSync(tempFilePath, Buffer.from(pdfBytes))
+        const fileStream = fs.createReadStream(tempFilePath)
+
+        try {
+          await api.files.upload(fileStream, {
+            spaceId,
+            environmentId,
+          })
+          fs.unlinkSync(tempFilePath)
+
+          return {
+            info: 'PDF report generated',
+          }
+        } catch (error) {
+          fs.unlinkSync(tempFilePath)
+          console.error('Failed to upload PDF report', error)
+          throw new Error('Failed to upload PDF report')
+        }
+      })
+    )
+  }
+}

export/pdf/src/index.ts

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+export * from './export.pdf.plugin'