Last updated:2023-11-02


GPTBots.ai seamlessly connects LLM with enterprise data and service capabilities to efficiently build AI Bot services. It is easy to deeply integrate AI Bot capabilities into the actual business of the enterprise, allowing AI to drive business growth and improve efficiency.

GPTBots.ai have the following advantages and features:

  • LLM
    • Support out-of-the-box mainstream commercial large models, support access to open source large models and privatized deployment services;
    • No need to spend a lot of energy on LLM deployment, fine-tuning, etc., allowing developers to focus more on the core business of the enterprise;
    • Regardless of commercial or open source models, the data required for model fine-tuning can be quickly generated based on knowledge base data and user dialogue data for model fine-tuning.
  • Knowledges Base
    • Support various types of knowledge data such as doc/docx, pdf, txt, markdown, csv, xls/xlsx, webpage and Q&A, etc;
    • For different types of data, use different data analysis and segmentation schemes to improve data quality and integrity;
    • Support editing and management of knowledge paragraphs, and integrate NLP + vector solutions to improve search accuracy.
  • Plugin
    • Faced with the needs of specific fields, developers can get very good solutions through plugin (such as: investment analysis, output files, product recommendations, service bookings, etc.);
    • Developers can achieve seamless connection with enterprise data and service capabilities through plugins, while ensuring enterprise data security;
    • GPTBots not only provides official plugins, but also supports third-party developers to publicly release plugins based on their own service capabilities.
  • Flow-Bot
    • When faced with complex requirements and problems, developers can use Flow to realize the visual orchestration workflow of multiple LLMs;
    • Define a "Specific LLM" with a single function and clear output to improve quality and stability;
    • Multiple "Professional LLMs" and "Functional Components" work serially or in parallel through Flow to solve complex problems.
  • Bot Training
    • Chat records support quality ratings, keywords, topic summaries, etc., making it easier for developers to gain insight into what users care about;
    • Supports summarization, induction and classification of user problems, helping developers understand users' high-frequency problems, and optimize and supplement relevant knowledge in a targeted manner;
    • Bot training mode supports real-time correction of "conversation content", and continuously trains Bots to achieve better responses.