Document Vector Database

Overview

The Document Vector Database Connected System enables Large Language Models (LLMs) to answer user submitted questions based on Appian Knowledge Center Documents. By uploading documents to this connected system, users can perform semantic searches to pinpoint the most pertinent content related to their questions. The Connected System also boasts Client APIs tailored for the AI Knowledge Assistant Component. This allows the AI Knowledge Assistant Component to deliver AI generated answers to user inquiries sourced from documents stored in the database, as well as general questions.

Key Features & Functionality

Upload Document - Uploads and stores the documents and its vector in the database.
List Documents - Provides us the list of documents uploaded in the database.
Database Operations
1. Delete Documents - Enables us to delete the documents that are uploaded in the database.
2. Sync Documents - Updates the existing documents in the database with the latest version of the document available in the Appian Knowledge Center.
3. Change Database Password - Changes Database password.
Query Documents - Get relevant pieces of content from documents for the given prompt.
Generate Response - Perform search in the given documents and generate ChatGPT response for the given prompt.
Client APIs for AI Knowledge Assistant component for fetching document details, chat completions, document querying, and uploading new documents to the database.

Notes:

Download the AI Knowledge Assistant, a sophisticated chatbot designed to perform semantic searches across your documents and provide precise answers to your queries.
This plugin is not supported for HA environments.

Parents

Appian AppMarket 10 months ago
v3.0.0 Release Notes
- Scalability Enhancements
- We have significantly enhanced the vector database’s scalability to allow multiple users to interact with the chatbot concurrently. Please note that query speeds may vary depending on the length of the documents, the amount of documents queried, the number of concurrent users, and hardware configurations.
- Query Performance
- There has been a substantial increase in query performance. Documents that are queried are now temporarily cached in-memory, resulting in a slight latency during the initial query but followed by nearly instantaneous responses for subsequent questions. This update markedly improves the speed and efficiency of our query processing.
IMPORTANT NOTE: If you are using this plugin in production, open a support case and ask to increase Heap Max for app server by 1GB. This will increase query performance and allow the plugin to handle a larger number of concurrent users.
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Appian AppMarket 10 months ago
v3.0.0 Release Notes
- Scalability Enhancements
- We have significantly enhanced the vector database’s scalability to allow multiple users to interact with the chatbot concurrently. Please note that query speeds may vary depending on the length of the documents, the amount of documents queried, the number of concurrent users, and hardware configurations.
- Query Performance
- There has been a substantial increase in query performance. Documents that are queried are now temporarily cached in-memory, resulting in a slight latency during the initial query but followed by nearly instantaneous responses for subsequent questions. This update markedly improves the speed and efficiency of our query processing.
IMPORTANT NOTE: If you are using this plugin in production, open a support case and ask to increase Heap Max for app server by 1GB. This will increase query performance and allow the plugin to handle a larger number of concurrent users.
- Cancel
- Up 0 Down
- Reply
- More
- Cancel

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