🧠 Adaptive Graph of Thoughts
What is Adaptive Graph of Thoughts?
Adaptive Graph of Thoughts is an AI reasoning framework designed for scientific research, utilizing graph structures to enhance the way AI systems approach complex reasoning tasks.
How to use Adaptive Graph of Thoughts?
To use the framework, set up a Neo4j graph database with the required APOC library, configure the application settings, and run the server either locally or via Docker. You can interact with the API to perform scientific queries.
Key features of Adaptive Graph of Thoughts?
- Utilizes Neo4j for advanced graph-based reasoning.
- Implements the Model Context Protocol (MCP) for integration with AI applications.
- Supports dynamic confidence scoring and multi-dimensional evaluations.
- Dockerized for easy deployment and modular design for customization.
Use cases of Adaptive Graph of Thoughts?
- Analyzing complex scientific relationships and queries.
- Integrating with AI clients for enhanced reasoning capabilities.
- Supporting research tasks that require sophisticated data processing and analysis.
FAQ from Adaptive Graph of Thoughts?
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What is the required environment for running the project?
You need a running Neo4j instance with the APOC library installed, along with Python 3.11+ and Docker for deployment.
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Can I contribute to the project?
Yes! Contributions are welcome, and guidelines are available in the documentation.
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Is there a roadmap for future features?
Yes, the project has a roadmap that includes plans for enhanced graph visualization and integration with more data sources.