# Description of Changes
- Use pool for postgres connections
- Add ability to require user ID to be set on API calls to the engine
- Add process-wide concurrency cap on AI access (in addition to existing
user caps)
- Allow number of workers (threads) to be specified for stirling engine
- Update env var names to reflect that the DB is not just for RAG
# Description of Changes
Redesign AI engine so that it autogenerates the `tool_models.py` file
from the OpenAPI spec so the Python has access to the Java API
parameters and the full list of Java tools that it can run. CI ensures
that whenever someone modifies a tool endpoint that the AI enigne tool
models get updated as well (the dev gets told to run `task
engine:tool-models`).
There's loads of advantages to having the Java be the one that actually
executes the tools, rather than the frontend as it was previously set up
to theoretically use:
- The AI gets much better descriptions of the params from the API docs
- It'll be usable headless in the future so a Java daemon could run to
execute ops on files in a folder without the need for the UI to run
- The Java already has all the logic it needs to execute the tools
- We don't need to parse the TypeScript to find the API (which is hard
because the TS wasn't designed to be computer-read to extract the API)
I've also hooked up the prototype frontend to ensure it's working
properly, and have built it in a way that all the tool names can be
translated properly, which was always an issue with previous prototypes
of this.
---------
Co-authored-by: Anthony Stirling <[email protected]>
Co-authored-by: EthanHealy01 <[email protected]>
# Description of Changes
Add Java orchestration layer which can connect and go back and forth
with the AI engine to get results for the user. It's expected that the
AI engine will not be publicly available and this Java layer will always
be in front of it, to manage sessions and auth etc.
# Description of Changes
Redesign the Python AI engine to be properly agentic and make use of
`pydantic-ai` instead of `langchain` for correctness and ergonomics.
This should be a good foundation for us to build our AI engine on going
forwards.
James BruntonandGitHub
Anthony StirlingandGitHub
