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@fluid-experimental/ai-collab
Advanced tools
Experimental package to simplify integrating AI into Fluid-based applications
Utilities for using SharedTree with LLMs. This package aims to assist SharedTree-based apps that want to leverage LLMs.
The next steps in LLM/AI-based collaborative experiences with applications involves allowing LLMs to propose updates to application state directly.
The classic LLM dev experience involves crafting a prompt for an an LLM with some information about the app, then having the LLM response in a parseable format.
From here the developer needs to:
Newer LLM developer tooling has solved issue #1 in a variety of ways, getting the LLM to respond with a format that you can merge into your application and ensuring that the JSON response schema is valid. However, problems 3-4 still exist and the current landscape requires bespoke, per-app solutions for dealing with this. This library simplifies these issues.
These are the platform requirements for the current version of Fluid Framework Client Packages. These requirements err on the side of being too strict since within a major version they can be relaxed over time, but not made stricter. For Long Term Support (LTS) versions this can require supporting these platforms for several years.
It is likely that other configurations will work, but they are not supported: if they stop working, we do not consider that a bug. If you would benefit from support for something not listed here, file an issue and the product team will evaluate your request. When making such a request please include if the configuration already works (and thus the request is just that it becomes officially supported), or if changes are required to get it working.
strict
options are supported.strictNullChecks
is required.exactOptionalPropertyTypes
is currently not fully supported.
If used, narrowing members of Fluid Framework types types using in
, Reflect.has
, Object.hasOwn
or Object.prototype.hasOwnProperty
should be avoided as they may incorrectly exclude undefined
from the possible values in some cases.Node16
, NodeNext
, or Bundler
resolution should be used with TypeScript compilerOptions to follow the Node.js v12+ ESM Resolution and Loading algorithm.
Node10 resolution is not supported as it does not support Fluid Framework's API structuring pattern that is used to distinguish stable APIs from those that are in development.
ES Modules: ES Modules are the preferred way to consume our client packages (including in NodeJs) and consuming our client packages from ES Modules is fully supported.
CommonJs: Consuming our client packages as CommonJs is supported only in NodeJS and only for the cases listed below. This is done to accommodate some workflows without good ES Module support. If you have a workflow you would like included in this list, file an issue. Once this list of workflows motivating CommonJS support is empty, we may drop support for CommonJS one year after notice of the change is posted here.
There are many ways to contribute to Fluid.
Detailed instructions for working in the repo can be found in the Wiki.
This project has adopted the Microsoft Open Source Code of Conduct. For more information see the Code of Conduct FAQ or contact opencode@microsoft.com with any additional questions or comments.
This project may contain Microsoft trademarks or logos for Microsoft projects, products, or services. Use of these trademarks or logos must follow Microsoft’s Trademark & Brand Guidelines. Use of Microsoft trademarks or logos in modified versions of this project must not cause confusion or imply Microsoft sponsorship.
Not finding what you're looking for in this README? Check out fluidframework.com.
Still not finding what you're looking for? Please file an issue.
Thank you!
This project may contain Microsoft trademarks or logos for Microsoft projects, products, or services.
Use of these trademarks or logos must follow Microsoft's Trademark & Brand Guidelines.
Use of Microsoft trademarks or logos in modified versions of this project must not cause confusion or imply Microsoft sponsorship.
FAQs
Experimental package to simplify integrating AI into Fluid-based applications
We found that @fluid-experimental/ai-collab demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 0 open source maintainers collaborating on the project.
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