The Semantic Workbench service consists of several key components that interact to provide a seamless user experience:
Workbench Service: A backend Python service that handles state management, user interactions, and assists in broker functionalities.
Workbench App: A single-page web application written in TypeScript and React, compiled into static HTML that runs in the user’s browser.
FastAPI Framework: Utilized for the HTTP API, providing endpoints and continuous communication between the Workbench and assistants.
Assistants: Independently developed units that connect to the Workbench Service through a RESTful API. Assistants can manage their own state and handle connections to various language models.
The communication between the Workbench and Assistants is managed through HTTP requests:
- Initialization: Assistants notify the Workbench about their presence and provide a callback URL.
- Message Handling: Both the Workbench and Assistants can send HTTP requests to each other as needed.
- Events: There are several types of events (e.g.,
message created) that are handled through designated HTTP endpoints.
Each assistant (or agent) is registered and maintains its connection through continuous ping requests to the Workbench. This ensures that the state information and response handling remain synchronized.
The Semantic Workbench service is a Python service that provides the backend functionality of the Semantic Workbench.
Follow the setup guide to install the development tools.
In the workbench-service directory
makeIf this fails in Windows, try running a vanilla instance of cmd or powershell and not within Cmder or another shell that may have modified the environment.
To run and/or debug in VS Code, View->Run, "service: semantic-workbench-service"
In the workbench-service directory
uv run start-service