Overview
1. Overview of the Stores Function
In Casibase, the Stores function is one of its core modules, which allows users to integrate storage, modelling, and embedding service providers for knowledge base data storage, text vector conversion, and interaction with chatbots. With the Stores feature, users can build an efficient, flexible and powerful AI knowledge management system.
2.Advantages of Stores
2.1 Multi-model integration
Casibase's Stores feature supports multiple mainstream AI language models, including OpenAI (e.g., GPT-3.5, GPT-4), Azure OpenAI, HuggingFace, Google Gemini, and so on. This multi-model support allows users to choose the most suitable AI model for their specific needs and find a balance between performance, cost and features.
2.2 Multiple storage and embedding options
Users are free to choose storage and embedding service providers to meet different data storage and processing needs. This flexibility enables users to configure the most appropriate storage and embedding solution based on their technology stack and business requirements.
2.3 Multi-Store Mode
Casibase supports a multi-Store model that allows users to use different models, storage and embedding services in different Stores to provide customised services for different scenarios and users. This feature enables users to flexibly configure and switch Stores according to different business requirements.
3.Summary
Casibase's Stores feature provides users with a powerful knowledge management tool that enables them to flexibly build and manage knowledge bases by integrating multiple AI models, stores and embedded services. Its multi-Store model and enterprise-level features further enhance the flexibility and security of the system, which is suitable for a variety of application scenarios.
Casibase is an open source AI knowledge base system designed to provide efficient and flexible knowledge management and dialogue solutions for enterprises. One of its core features is Providers, which allows users to integrate multiple AI models and storage services to enhance the functionality and performance of the system.Providers are divided into three main categories: Model Providers, Embedding Provides and Storage Providers, which are responsible for handling AI models and data storage, respectively.