简体中文 | English
-
Semantic Kernel: It uses advanced natural language processing technology to accurately understand, process and respond to complex semantic queries, and provides users with accurate information retrieval and recommendation services.
-
Kernel Memory: It has the ability to continuously learn and store knowledge points. AntSK has a long-term memory function to accumulate experience and provide a more personalized interactive experience.
-
Knowledge base: Knowledge base documents can be created by importing knowledge base documents (Word, PDF, Excel, Txt, Markdown, Json, PPT) and other forms.
-
API plug-in system: an open API plug-in system that allows third-party developers or service providers to easily integrate their services into AntSK and continuously enhance application functions.
-
Online search: AntSK can obtain the latest information in real time to ensure that the information received by users is always the most timely and relevant.
-
GPTs generation: This platform supports the creation of personalized GPT models and attempts to build your own GPT models.
-
API interface publishing: internal functions are provided externally in the form of API, so that developers can easily translate Xzy AntSK KnowledgeBase is integrated into other applications to enhance application intelligence.
AntSK is applicable to a variety of business scenarios, such as:
-
Enterprise level knowledge management system
-
Automatic customer service and chat robot
-
Enterprise Search Engine
-
Personalized recommendation system
-
Intelligent assisted writing
-
Education and online learning platform
-
Other interesting AI Apps
First, you need to create a knowledge base
In the knowledge base, you can use documents or urls to import
Click View to view the document slicing of the knowledge base
Then we need to create applications, which can create dialog applications and knowledge bases.
The application of knowledge base needs to select the existing knowledge base, which can be multiple
Then you can ask questions about the knowledge base documents in the dialogue
In addition, we can also create dialogue applications, and configure prompt word templates in corresponding applications
Let's see the effect
Login is the default login account and password
Here I use Postgres as data storage and vector storage, because both the Semantic Kernel and Kernel Memory support it. Of course, you can switch to other ones.
The model supports openai by default. If you need to use azure openai and need to adjust the dependency injection of SK, you can also use one api for integration.
The following configuration files need to be configured
"ConnectionStrings":{
"Postgres": "Host=; Port=; Database=antsk; Username=; Password="
},
"OpenAIOption":{
"EndPoint": "",
"Key": "",
"Model": "",
"Embedding Model": """""
},
Postgres:{
"ConnectionString": "Host=; Port=; Database=antsk; Username=; Password=",
"TableNamePrefix": "km -"
},
"Login": {
"User": "admin",
"Password": "xuzeyu"
}
I use CodeFirst mode. As long as the database link is configured, the table structure is automatically created
To learn more or start usingAntSK, you can follow my public account and join the exchange group.
If you have any questions or suggestions, please follow my public account through the following ways, and send a message to me. We also have an exchange group, which can send messages such as joining the group, and then I will bring you into the exchange group
We appreciate your interest inAntSKand look forward to working with you to create an intelligent future!