model-selection

1# Model Selection
2 
3Guides the user through selecting a base model based on their use case.
4 
5## When to Use
6 
7- User asks which model to use
8- User wants to select or change their base model
9- User mentions a model name or family (e.g., "Llama", "Mistral", "Nova") — the exact Hub model ID still needs to be resolved
10- User wants to evaluate a base model before deciding whether to finetune
11 
12## Prerequisites
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14- A `use_case_spec.md` file exists. If not, activate the use-case-specification skill to generate it first.
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16## Workflow
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18### Step 1: Check Region
19 
20Run:
21 
22```
23python -c "import boto3; print(boto3.session.Session().region_name)"
24```
25 
26- `None` → STOP. Tell user: "Set your region via `export AWS_DEFAULT_REGION=us-west-2` or `aws configure`."
27- Set → store REGION in context, continue.
28 
29### Step 2: Discover Hub
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311. List all available SageMaker Hubs in the user's region by calling the SageMaker `ListHubs` API using the `aws___call_aws` tool.
322. From the results, filter out any hub whose `HubDescription` contains "AI Registry" — these do not contain JumpStart models.
333. The remaining hubs are eligible (e.g., `SageMakerPublicHub` and any private hubs).
344. If exactly one eligible hub exists, use it automatically — do not ask the user.
355. If multiple eligible hubs exist, present them to the user and ask which one to use. Example:
36 
37   ```
38   I found the following model hubs:
39   - SageMakerPublicHub — SageMaker Public Hub
40   - Private-Hub-XYZ — Private Hub models
41…