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Lexoid is an efficient document parsing library that supports both LLM-based and non-LLM-based (static) PDF document parsing.
- Use the multi-modal advancement of LLMs
- Enable convenience for users
- Collaborate with a permissive license
pip install lexoid
To use LLM-based parsing, define the following environment variables or create a .env file with the following definitions
OPENAI_API_KEY=""
GOOGLE_API_KEY=""
Optionally, to use Playwright for retrieving web content (instead of the requests library):
playwright install --with-deps --only-shell chromium
make build
To install dependencies:
make install
or, to install with dev-dependencies:
make dev
To activate virtual environment:
source .venv/bin/activate
Here's a quick example to parse documents using Lexoid:
from lexoid.api import parse
from lexoid.api import ParserType
parsed_md = parse("https://www.justice.gov/eoir/immigration-law-advisor", parser_type="LLM_PARSE")["raw"]
# or
pdf_path = "path/to/immigration-law-advisor.pdf"
parsed_md = parse(pdf_path, parser_type="LLM_PARSE")["raw"]
print(parsed_md)- path (str): The file path or URL.
- parser_type (str, optional): The type of parser to use ("LLM_PARSE" or "STATIC_PARSE"). Defaults to "AUTO".
- pages_per_split (int, optional): Number of pages per split for chunking. Defaults to 4.
- max_threads (int, optional): Maximum number of threads for parallel processing. Defaults to 4.
- **kwargs: Additional arguments for the parser.
- OpenAI
- Hugging Face
- Together AI
- OpenRouter
- Fireworks
Results aggregated across 11 documents.
Note: Benchmarks are currently done in the zero-shot setting.
| Rank | Model | SequenceMatcher Similarity | TFIDF Similarity | Time (s) | Cost ($) |
|---|---|---|---|---|---|
| 1 | gemini-2.5-pro | 0.907 (±0.151) | 0.973 (±0.053) | 22.23 | 0.02305 |
| 2 | AUTO | 0.905 (±0.111) | 0.967 (±0.051) | 10.31 | 0.00068 |
| 3 | gemini-2.5-flash | 0.902 (±0.151) | 0.984 (±0.030) | 48.67 | 0.01051 |
| 4 | gemini-2.0-flash | 0.900 (±0.127) | 0.971 (±0.040) | 12.43 | 0.00081 |
| 5 | mistral-ocr-latest | 0.890 (±0.097) | 0.930 (±0.095) | 5.69 | 0.00127 |
| 6 | claude-3-5-sonnet-20241022 | 0.873 (±0.195) | 0.937 (±0.095) | 16.86 | 0.01779 |
| 7 | gemini-1.5-flash | 0.868 (±0.198) | 0.965 (±0.041) | 17.19 | 0.00044 |
| 8 | claude-sonnet-4-20250514 | 0.814 (±0.197) | 0.903 (±0.150) | 21.99 | 0.02045 |
| 9 | accounts/fireworks/models/llama4-scout-instruct-basic | 0.804 (±0.242) | 0.931 (±0.067) | 9.76 | 0.00087 |
| 10 | claude-opus-4-20250514 | 0.798 (±0.230) | 0.878 (±0.159) | 21.01 | 0.09233 |
| 11 | gpt-4o | 0.796 (±0.264) | 0.898 (±0.117) | 28.23 | 0.01473 |
| 12 | accounts/fireworks/models/llama4-maverick-instruct-basic | 0.792 (±0.206) | 0.914 (±0.128) | 10.71 | 0.00149 |
| 13 | gemini-1.5-pro | 0.782 (±0.341) | 0.833 (±0.252) | 27.13 | 0.01275 |
| 14 | gpt-4.1-mini | 0.767 (±0.243) | 0.807 (±0.197) | 22.64 | 0.00352 |
| 15 | gpt-4o-mini | 0.727 (±0.245) | 0.832 (±0.136) | 17.20 | 0.00650 |
| 16 | meta-llama/Llama-Vision-Free | 0.682 (±0.223) | 0.847 (±0.135) | 12.31 | 0.00000 |
| 17 | meta-llama/Llama-3.2-11B-Vision-Instruct-Turbo | 0.677 (±0.226) | 0.850 (±0.134) | 7.23 | 0.00015 |
| 18 | microsoft/phi-4-multimodal-instruct | 0.665 (±0.258) | 0.800 (±0.217) | 10.96 | 0.00049 |
| 19 | claude-3-7-sonnet-20250219 | 0.634 (±0.395) | 0.752 (±0.298) | 70.10 | 0.01775 |
| 20 | google/gemma-3-27b-it | 0.624 (±0.357) | 0.750 (±0.327) | 24.51 | 0.00020 |
| 21 | gpt-4.1 | 0.622 (±0.314) | 0.782 (±0.191) | 34.66 | 0.01461 |
| 22 | meta-llama/Llama-3.2-90B-Vision-Instruct-Turbo | 0.559 (±0.233) | 0.822 (±0.119) | 27.74 | 0.01102 |
| 23 | ds4sd/SmolDocling-256M-preview | 0.486 (±0.378) | 0.583 (±0.355) | 108.91 | 0.00000 |
| 24 | qwen/qwen-2.5-vl-7b-instruct | 0.469 (±0.364) | 0.617 (±0.441) | 13.23 | 0.00060 |