Enable sane naming of registered objects with defaults (#429)

# What does this PR do? 

This is a follow-up to #425. That PR allows for specifying models in the
registry, but each entry needs to look like:

```yaml
- identifier: ...
  provider_id: ...
  provider_resource_identifier: ...
```

This is headache-inducing.

The current PR makes this situation better by adopting the shape of our
APIs. Namely, we need the user to only specify `model-id`. The rest
should be optional and figured out by the Stack. You can always override
it.

Here's what example `ollama` "full stack" registry looks like (we still
need to kill or simplify shield_type crap):
```yaml
models:
- model_id: Llama3.2-3B-Instruct
- model_id: Llama-Guard-3-1B
shields:
- shield_id: llama_guard
  shield_type: llama_guard
```

## Test Plan

See test plan for #425. Re-ran it.
This commit is contained in:
Ashwin Bharambe 2024-11-12 11:18:05 -08:00 committed by GitHub
parent d9d271a684
commit 09269e2a44
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17 changed files with 295 additions and 207 deletions

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@ -9,7 +9,7 @@ import tempfile
import pytest
import pytest_asyncio
from llama_stack.apis.models import Model
from llama_stack.apis.models import ModelInput
from llama_stack.distribution.datatypes import Api, Provider
from llama_stack.providers.inline.agents.meta_reference import (
@ -71,13 +71,9 @@ async def agents_stack(request, inference_model, safety_model):
if fixture.provider_data:
provider_data.update(fixture.provider_data)
inf_provider_id = providers["inference"][0].provider_id
safety_provider_id = providers["safety"][0].provider_id
shield = get_shield_to_register(
providers["safety"][0].provider_type, safety_provider_id, safety_model
shield_input = get_shield_to_register(
providers["safety"][0].provider_type, safety_model
)
inference_models = (
inference_model if isinstance(inference_model, list) else [inference_model]
)
@ -86,13 +82,11 @@ async def agents_stack(request, inference_model, safety_model):
providers,
provider_data,
models=[
Model(
identifier=model,
provider_id=inf_provider_id,
provider_resource_id=model,
ModelInput(
model_id=model,
)
for model in inference_models
],
shields=[shield],
shields=[shield_input],
)
return impls[Api.agents], impls[Api.memory]