PDF → Structured JSON Extractor (Apify Actor) This Apify Actor extracts structured JSON from PDF files using PDF parsing + optional OCR + LLM-based schema extraction. ## Features - Accepts a pdfUrl (HTTP) or pdfBase64 (string) as input - Extracts raw text using pdf-parse and optionally OCR (stub) - Sends the text and a user-provided schema to an LLM to return strict JSON - Pushes extraction result to Dataset ## Quick start 1. Update main.js's callLLM function to call your chosen LLM provider (OpenAI, Anthropic, Google) 2. (Optional) Implement runOCR using Tesseract or a cloud OCR API 3. apify push to your Apify account and run the actor with input.json ## Example input.json json { "pdfUrl": "https://example.com/invoice123.pdf", "schema": { "invoice_number": "string", "invoice_date": "date", "total_amount": "number", "items": [{ "name": "string", "qty": "number", "price": "number" }] }, "aiModel": "gpt-4o-mini", "ocr": false, "returnFormat": "json" } ## Notes - The starter callLLM function is a stub for testing and must be replaced with an actual LLM API call before production use. - Consider rate limits and cost of LLM calls. Offer batching or model selection in your product. ## Suggested pricing - Free: 20 PDFs / month - Starter: $19 / month (200 PDFs) - Pro: $49 / month (1000 PDFs) - Business: $149 / month (10k PDFs) ## Validation & LLM retry behavior This Actor now validates the extracted JSON using ajv when you provide a JSON Schema as the schema input. If the JSON does not validate, the Actor will automatically attempt to repair it by sending a targeted prompt to the LLM (up to 2 repair attempts). LLM calls use p-retry with exponential backoff for transient failures (retries on 5xx and rate-limit responses). You can control retry counts and model via the input parameters. ## OCR Options (Tesseract or Google Vision) This Actor supports optional OCR when ocr is enabled in the input. You can select the OCR engine via the input ocrOptions.engine field. ### ocrOptions example json "ocr": true, "ocrOptions": { "engine": "tesseract" } or for Google Vision: json "ocr": true, "ocrOptions": { "engine": "google" } ### Tesseract (offline) - Uses tesseract.js (Node). This allows OCR without external APIs but adds a larger dependency. - No env vars needed. Install dependencies and run the Actor as usual. ### Google Vision (cloud OCR) - Uses Google Vision DOCUMENT_TEXT_DETECTION endpoint. Requires GOOGLE_API_KEY env var with an API key that has Vision API enabled. - Set the key in environment before running: bash export GOOGLE_API_KEY="YOUR_GOOGLE_VISION_API_KEY" ### Behavior notes - The Actor will attempt pdf-parse extraction first. If ocr is true and extracted text is short or empty, the configured OCR engine will be invoked. - OCR can be slower and more expensive (Google Vision costs), so use it only for scanned PDFs.