Feature Overview (mandatory - Complete while in New status)
An elevator pitch (value statement) that describes the Feature in a clear, concise way. ie: Executive Summary of the user goal or problem that is being solved, why does this matter to the user? The “What & Why”... 

With multiple model support (for inference, student, teacher) and to enable the end-to-end InstructLab workflow with Llama-Stack, we will have to ensure that: 

1. Our RHEL AI Providers are initialized with default models
2. llama-stack (server) CLI users are able to change these defaults to customize which models they want to use as student/teacher/inference models
3. llama-stack(server) CLI users are able to understand clearly which models are supported as teacher models, student models, and inference-only.
4. llama-stack-client CLI users know which models are available for each provider upon running 'llama-stack-client model list' and know how to invoke those commands (especially if there are more than one models available at an endpoint, like inference) 

Goals (mandatory - Complete while in New status)
Provide high-level goal statement, providing user context and expected user outcome(s) for this Feature

• Who benefits from this Feature, and how? 
• What is the difference between today’s current state and a world with this Feature?

<your text here>

Requirements (mandatory -_ Complete while in Refinement status):
A list of specific needs, capabilities, or objectives that a Feature must deliver to satisfy the Feature. Some requirements will be flagged as MVP. If an MVP gets shifted, the Feature shifts. If a non MVP requirement slips, it does not shift the feature.

Done - Acceptance Criteria (mandatory - Complete while in Refinement status):
Acceptance Criteria articulates and defines the value proposition - what is required to meet the goal and intent of this Feature. The Acceptance Criteria provides a detailed definition of scope and the expected outcomes - from a users point of view
…
<your text here>

Use Cases - i.e. User Experience & Workflow: (Initial completion while in Refinement status):
Include use case diagrams, main success scenarios, alternative flow scenarios.
<your text here>

Out of Scope __(Initial completion while in Refinement status):
High-level list of items or persona’s that are out of scope.
1. Client CLI also has a workflow to 'register' models - I think it's ok to call that workflow not supported since that will mean a client CLI change will have to force system restart. 

Documentation Considerations __(Initial completion while in Refinement status):
Provide information that needs to be considered and planned so that documentation will meet customer needs. If the feature extends existing functionality, provide a link to its current documentation..
<your text here>

Questions to Answer __(Initial completion while in Refinement status):
Include a list of refinement / architectural questions that may need to be answered before coding can begin. 

1. vLLM and Model Management?
2. RHEL AI Inference Provider? 
3. Do we download models on the llama-stack (server) side?
4. How do we deal with model 'register' in the short-term? 
5. Artifact management 
6. Where can models be pulled from? HF, OCI, S3, local, on server/filesystem? And, how?
7. CLI vs SDK workflow

Background and Strategic Fit (Initial completion while in Refinement status):
Provide any additional context is needed to frame the feature.

Today, on the Llama-Stack (server) CLI, 

This is an example of how 'available' models are listed upon Llama-Stack server CLI setup: 

• metadata: {}

  model_id: meta-llama/Meta-Llama-3.1-8B-Instruct-Turbo

  model_type: !!python/object/apply:llama_stack.apis.models.models.ModelType

  - llm

  provider_id: together

  provider_model_id: meta-llama/Meta-Llama-3.1-8B-Instruct-Turbo

(All supported models with a particular distribution stack are listed like this) 

Customer Considerations __(Initial completion while in Refinement status):
Provide any additional customer-specific considerations that must be made when designing and delivering the Feature.
<your text here>

Team Sign Off (Completion while in Planning status)

• All required Epics (known at the time) are linked to the this Feature
• All required Stories, Tasks (known at the time) for the most immediate Epics have been created and estimated
• Add - Reviewers name, Team Name
• Acceptance == Feature as “Ready” - well understood and scope is clear - Acceptance Criteria (scope) is elaborated, well defined, and understood
• Note: Only set FixVersion/s: on a Feature if the delivery team agrees they have the capacity and have committed that capability for that milestone

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