| import pytesseract |
| from pdf2image import convert_from_path |
| import google.generativeai as genai |
| import os, json |
|
|
| |
| FORMS = { |
| "pancard_form": [ |
| "Name", "DOB", "Gender", "FatherName", "MotherName", |
| "Address", "City", "State", "Pincode", "Mobile", "Email", |
| "DocumentType", "DocumentNumber", "IssueAuthority", |
| "IssueDate", "ExpiryDate" |
| ] |
| } |
|
|
| |
| api_key = os.getenv("GEMINI_API_KEY") |
| if not api_key: |
| raise ValueError("❌ GEMINI_API_KEY not found. Please set it in Hugging Face Space Secrets.") |
| genai.configure(api_key=api_key) |
|
|
| def extract_text_from_pdf(pdf_path): |
| pages = convert_from_path(pdf_path) |
| text = "" |
| for page in pages: |
| text += pytesseract.image_to_string(page) + "\n" |
| return text.strip() |
| def extract_key_values_with_gemini(raw_text, form_type="pancard_form"): |
| prompt = f""" |
| You are an intelligent document parser. |
| Given the following document text, extract only these fields: {FORMS[form_type]}. |
| Return strictly as JSON key-value pairs. |
| Document text: |
| {raw_text} |
| """ |
| model = genai.GenerativeModel("models/gemini-2.5-flash") |
| print("Gemini API called successfully ✅") |
| response = model.generate_content(prompt) |
| text = response.text.strip() |
|
|
| |
| text = text.replace("```json", "").replace("```", "").strip() |
|
|
| try: |
| return json.loads(text) |
| except Exception: |
| return {"raw_output": text} |
