Kiroku
K
Kiroku
Overview :
Kiroku is a multi-agent system designed to assist users in organizing and writing documents. It simulates the interaction between students and advisors during the PhD dissertation writing process, allowing writers to assume the advisor's role while the multi-agent system takes on the student’s role. This approach enables the rapid generation of sequences of paragraphs and improves communication methods through iterative evaluation of information, leveraging large language models (LLMs) to discuss complex topics. Kiroku requires an OPENAI_API_KEY and TAVILY_API_KEY to operate and supports Python versions 3.7 to 3.11.
Target Users :
Kiroku is designed for researchers, scholars, and professionals who need to write technical documents or academic papers. By simulating the academic writing process, Kiroku helps users efficiently organize their thoughts and draft documents, especially those requiring complex information processing and iterative revisions.
Total Visits: 474.6M
Top Region: US(19.34%)
Website Views : 52.4K
Use Cases
Researchers use Kiroku to write academic papers, rapidly constructing drafts through system-generated paragraph sequences.
Scholars leverage Kiroku's iterative evaluation features to undergo multiple revisions of their papers, enhancing their quality.
Technical writers utilize Kiroku to generate titles and citations for technical documents, streamlining their writing process.
Features
- Thought organization: Quickly generate sequences of paragraphs to optimize thought organization.
- Iterative evaluation: Optimize communication through repeated assessment of information.
- Discussion of complex topics: Utilize LLMs to discuss and process intricate subjects.
- Technical writing assistance: Particularly suitable for writing technical documents and research papers.
- Title and citation generation: Create titles and citations based on user-provided information.
- Multi-round revisions: Conduct multiple rounds of document revisions based on feedback.
- Temperature control: Adjust the LLM's temperature to control the creativity of the output.
- YAML configuration: Enable detailed configuration through YAML files, including document types and paragraph counts.
How to Use
1. Obtain your OPENAI_API_KEY and TAVILY_API_KEY.
2. Set up a Python virtual environment and install the necessary dependencies.
3. Prepare a YAML configuration file to define the document structure and writing parameters.
4. Place the YAML file and any related images in the specified directory.
5. Run Kiroku and open the designated localhost port in your browser.
6. Interact with Kiroku through the Gradio interface by providing writing instructions.
7. Adjust the YAML configuration and writing instructions based on feedback to refine the document.
8. Generate the final document that meets your needs.
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