Instructions to use CaseLoop/rights-navigator with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CaseLoop/rights-navigator with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("CaseLoop/rights-navigator") model = AutoModelForSeq2SeqLM.from_pretrained("CaseLoop/rights-navigator", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 916 Bytes
50a8ea3 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 | import pymupdf
import re
def extract_pdf_chunks(pdf_path: str, chunk_size: int = 200, max_chunks: int = 5) -> list[str]:
doc = pymupdf.open(pdf_path)
clean_paragraphs = []
for page in doc:
text = page.get_text("text")
# Split into logical lines/paragraphs
lines = [line.strip() for line in text.split("\n") if line.strip()]
for line in lines:
# Skip short index table rows, page numbers, and headers
if len(line.split()) < 8 or re.search(r'(\bPage\b|\bS\.No\b|\bLPA NO\b|\bWP\(C\)\b)', line, re.IGNORECASE):
continue
clean_paragraphs.append(line)
full_text = " ".join(clean_paragraphs)
words = full_text.split()
if not words:
return []
chunks = [" ".join(words[i:i + chunk_size]) for i in range(0, len(words), chunk_size)]
return chunks[:max_chunks] |