Xata is a data platform that offers seamless integration with OpenAI’s ChatGPT, allowing users to create interactive Q&A bots. This integration enhances the way users interact with their documentation, applications, and knowledge bases by enabling natural language queries. With Xata, organizations can improve user experience and accessibility to information.
The primary feature of Xata is its ability to integrate ChatGPT, which empowers users to build intelligent Q&A bots. These bots can effectively respond to user inquiries, making it easier to navigate through extensive documentation and resources.
Xata supports two types of search methods: keyword search and vector search. The choice between these methods depends on the specific needs of the user. Keyword search is straightforward and easy to implement, but it may introduce some latency. On the other hand, vector search offers more precise results, although it requires additional setup and tuning.
To set up a ChatGPT-based Q&A bot, users can utilize the `/ask/` endpoint provided by Xata. This endpoint allows users to define specific rules for how the bot should respond to various questions. For example, users can create rules that redirect certain inquiries about pricing to a dedicated page or ensure that examples provided are contextually relevant.
Here is a practical example of how to use the `/ask/` endpoint:
const result = await xata.db.Docs.ask(
'How do I install Xata?',
{
rules: [
'Do not answer questions about pricing or the free tier. Respond that Xata has several options available, please check https://xata.io/pricing for more information.',
'When you give an example, this example must exist exactly in the context given.'
],
searchType: 'keyword',
search: {
fuzziness: 2,
prefix: 'phrase',
target: [{ column: 'title', weight: 4 }, 'content', { column: 'keywords', weight: 4 }]
}
}
);
This code snippet illustrates how to query a specific table (`Docs`) with a question while defining rules for the response.
Integrating Xata with ChatGPT significantly enhances the usability of documentation. Users can pose questions in natural language and receive context-specific answers, making information retrieval more intuitive. This integration also allows documentation to be portable, enabling access across various platforms, which is particularly beneficial for organizations with diverse user bases.
Xata provides a range of resources to assist users in integrating ChatGPT into their data systems. These include a sample application built with Next.js and Chakra UI, as well as a starter repository featuring examples related to Pokémon. Additionally, users can find instructional videos that explain the integration process and its technical aspects.
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