Controllable LLMs Integration with RAG for Diverse Businesses

Have you encountered the following problems with your LLM application?

AI response content is uncontrollable and cannot achieve strict quality and boundary control.
AI does not understand customer professional domain issues, nor can it effectively execute tasks.
A single LLM cannot solve complex problems and often answers incorrectly.

Controllable LLM is a prerequisite for business services

The authenticity, accuracy, and topic boundaries of AI responses are one of the core service values that GPTBots provides to enterprise users.

Reinforced identity prompts

Clear and effective identity prompt information can not only build the capabilities of LLM, but also effectively alleviate the illusions of LLM.

RAG makes knowledge more accurate

By configuring the RAG knowledge base and Plugins for LLM, more accurate and effective knowledge data can be obtained, thereby reducing the illusions of large models.

Data orchestration and emphasis

Visually orchestrate Prompts, support the annotation and emphasis of different types of data to help LLM understand the data structure, thereby improving the quality of AI responses.

Process orchestration and dedicated use

By configuring the RAG knowledge base and Plugins for LLM, more accurate and effective knowledge data can be obtained, thereby reducing the illusions of large models.

Support for custom sensitive words

Support for third-party security monitoring

Support for withdrawal of abnormal Q&A content

Make AI Bot more suitable for business

Provide various components to truly empower LLMs and Plugins, while making LLMs controllable and stable.

LLM fine-tuning, integrating LLM deeply into the business

It is very simple to fine-tune LLM at present, but GPTBots can use the Bot training results based on real user questions as the corpus data for fine-tuning LLM.

Natural language calls Plugin

Plugins for LLM can help enterprises seamlessly connect business APIs with LLM, providing enterprise services to users in natural language. This has revolutionized the way services are provided to users and brought more opportunities.

Flexible Flow is more in line with business

Flow orchestration can apply LLM to any link in complex problems, making the process of problem handling full of wisdom.

Strengthen memory for LLM

In addition to long and short memory, it also supports user attributes and user tasks as permanent memory of LLM.

Make LLM more powerful

Equip LLM with Tools Python library, MySQL database, code generation and execution capabilities, and continuously expand the capability boundaries of LLM.