Loki is our open-source solution designed to automate the process of verifying factuality. It provides a comprehensive pipeline for dissecting long texts into individual claims, assessing their worthiness for verification, generating queries for evidence search, crawling for evidence, and ultimately verifying the claims. This tool is especially useful for journalists, researchers, and anyone interested in the factuality of information. To stay updated, please subscribe to our newsletter at our website or join us on Discord!
- Decomposer: Breaks down extensive texts into digestible, independent claims, setting the stage for detailed analysis.
- Checkworthy: Assesses each claim's potential significance, filtering out vague or ambiguous statements to focus on those that truly matter. For example, vague claims like "MBZUAI has a vast campus" are considered unworthy because of the ambiguous nature of "vast."
- Query Generator: Transforms check-worthy claims into precise queries, ready to navigate the vast expanse of the internet in search of truth.
- Evidence Crawler: Ventures into the digital realm, retrieving relevant evidence that forms the foundation of informed verification.
- ClaimVerify: Examines the gathered evidence, determining the veracity of each claim to uphold the integrity of information.
- Python 3.9 or newer
- Required Python packages are listed in
requirements.txt
- Clone the repository:
git clone https://github.com/Libr-AI/factcheckservice.git
- Navigate to the project directory and install the required packages:
cd factcheckservice
pip install -r requirements.txt
- Configure api keys
cp factcheck/config/secret_dict.template factcheck/config/secret_dict.py
You can choose to export essential api key to the environment, or configure it in factcheck/config/secret_dict.py
.
- Example: Export essential api key to the environment
export SERPER_API_KEY=... # this is required in evidence retrieval if serper being used
export OPENAI_API_KEY=... # this is required in all tasks
export ANTHROPIC_API_KEY=... # this is required only if you want to replace openai with anthropic
To test the project, you can run the factcheck.py
script:
# String
python factcheck.py --modal string --input "MBZUAI is the first AI university in the world"
# Text
python factcheck.py --modal text --input demo_data/text.txt
# Speech
python factcheck.py --modal speech --input demo_data/speech.mp3
# Image
python factcheck.py --modal image --input demo_data/image.webp
# Video
python factcheck.py --modal video --input demo_data/video.m4v
The main interface of the Fact-check Pipeline is located in factcheck/core/FactCheck.py
, which contains the check_response
method. This method integrates the complete pipeline, where each functionality is encapsulated in its class as described in the Features section.
Example usage:
from factcheck.core.FactCheck import check_response
# Example text
text = "Your text here"
# Run the fact-check pipeline
results = check_response(text)
print(results)
Web app usage:
python webapp.py
We welcome contributions from the community! If you'd like to contribute, please follow these steps:
- Fork the repository.
- Create a new branch for your feature (
git checkout -b feature/AmazingFeature
). - Commit your changes (
git commit -m 'Add some AmazingFeature'
). - Push to the branch (
git push origin feature/AmazingFeature
). - Open a pull request.
πͺ Join Our Journey to Innovation with the Supporter Edition
As we continue to evolve and enhance our fact-checking solution, we're excited to invite you to become an integral part of our journey. By registering for our Supporter Edition, you're not just unlocking a suite of advanced features and benefits; you're also fueling the future of trustworthy information.
Your support enables us to:
π Innovate continuously: Develop new, cutting-edge features that keep you ahead in the fight against misinformation.
π‘ Improve and refine: Enhance the user experience, making our app not just powerful, but also a joy to use.
π± Grow our community: Invest in the resources and tools our community needs to thrive and expand.
π And as a token of our gratitude, registering now grants you complimentary token creditsβa little thank you from us to you, for believing in our mission and supporting our growth!
Feature | Open-Source Edition | Supporter Edition |
---|---|---|
Trustworthy Verification Results | β | β |
Diverse Evidence from the Open Web | β | β |
Automated Correction of Misinformation | β | β |
Privacy and Data Security | β | β |
Multimodal Input | β | β |
One-Stop Custom Solution | β | β |
Customizable Verification Data Sources | β | β |
Enhanced User Experience | β | β |
Faster Efficiency and Higher Accuracy | β | β |
Donβt miss out on the latest updates, feature releases, and community insights! We invite you to subscribe to our newsletter and become a part of our growing community.
π Subscribe now at our website!
This project is licensed under the MIT license - see the LICENSE file for details.
- Special thanks to all contributors who have helped in shaping this project.
@misc{Loki,
author = {Wang, Hao and Wang, Yuxia and Wang, Minghan and Geng, Yilin and Zhao, Zhen and Zhai, Zenan and Nakov, Preslav and Baldwin, Timothy and Han, Xudong and Li, Haonan},
title = {Loki: An Open-source Tool for Fact Verification},
year = {2024},
publisher = {GitHub},
journal = {GitHub repository},
howpublished = {\url{https://github.com/Libr-AI/Loki}},
}