Shape the future of IBM watsonx Orchestrate
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Although I have not tested flow option, by opting OpenAPI spec is its being possible. As we just get endpoints after ML model deployment, this idea will have the potential to reduce the manual effort to manually write OpenAPI spec and use this as a tool. Please suggest your view on this.
Today are you able to achieve this within our flows experience by adding an openapi spec as a tool, or defining a python script as a tool for the same?
We have a project(client0) where we are trying to implement a concept called Talk to Model, where models can be accessible from skills(gen1), ai agents in IBM WatsonX. Orchestrate.
- Created agents which collects data for model inference.
- Automatically routing happens whenever user needs specific trained conventional model(specific dataset) to get the inference.
- Used OpenAPI spec to generate integrate models as tools.
- In orchestrate gen1 we had such options where we used to add extrenal services and used to add models (watsonx.ai)decision models. to create a skill.
- Similar features will definitely help and if we can give a button(Use this model as a tool) in watsonx.ai after model deployment that would also be awesome.
To add to the request, is the problem you're trying to solve here optimizing a response by essentially routing to the ideal model based on the type of ask? When would we expect to invoke these differnet models, or is the idea that they are tools we can describe and specifically control when they are utilized?