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Welcome to the RECAPS wiki!
Welcome to the RECAPS Wiki! This is a comprehensive resource for understanding and using the RECAPS (Research Exploration and Collaboration Agent for Proposition Synthesis) platform. Here, you'll find detailed documentation, guides, and examples to help you get started and make the most out of this powerful research tool.
- Inputting Research Questions
- Recursive Question Subdivision
- Candidate Solution Proposal
- Directed Acyclic Graph (DAG) Representation
- Bidirectional Graph Building
- Document-Based Proposition Synthesis
- Collaborative Research Platform
RECAPS is a cutting-edge research copilot designed to revolutionize the way researchers approach complex questions and collaborate on projects. It leverages Large Language Models, advanced algorithms, prompting techniques, and natural language processing techniques to generate a comprehensive and intuitive representation of research findings.
To install RECAPS, follow these steps:
- Clone the repository:
git clone https://github.com/ReLink-Inc/RECAPS.git - Install the required dependencies:
pip install -r requirements.txt
To begin, you'll need to input your research question into the RECAPS interface. The system will then break down the question into smaller, manageable sub-questions.
RECAPS intelligently breaks down research questions into smaller, manageable sub-questions, allowing for a more focused and efficient exploration of the problem space.
By analyzing the sub-questions, RECAPS proposes potential solutions, helping researchers identify promising avenues for further investigation.
The system organizes the propositions into a DAG, where each node represents an answer to a sub-research question. This visual representation provides a clear overview of the research landscape and helps identify connections between different aspects of the problem.
RECAPS can construct the DAG from both ends, either by recursively subdividing the research question or by cumulatively building propositions from the ground up. This flexibility allows researchers to approach the problem from multiple angles and gain a comprehensive understanding of the subject matter.
Given a set of documents relevant to the research question, RECAPS can extract and synthesize information to generate propositions. This feature enables researchers to leverage existing knowledge and incorporate it seamlessly into their research.
The DAG representation serves as a foundation for effective collaboration among researchers. By sharing and contributing to the same project, team members can work together to refine propositions, identify gaps in knowledge, and ultimately reach a well-supported conclusion.
For detailed information on the RECAPS API and its various endpoints, please refer to the API Reference.
We welcome contributions from the research community to enhance RECAPS and make it an even more powerful tool for research exploration and collaboration. If you'd like to contribute, please follow our contribution guidelines and submit a pull request.
RECAPS is released under the MIT License.