llama-stack-mirror/llama_stack/providers/remote/inference/anthropic/models.py
Sébastien Han ac5fd57387
chore: remove nested imports (#2515)
# What does this PR do?

* Given that our API packages use "import *" in `__init.py__` we don't
need to do `from llama_stack.apis.models.models` but simply from
llama_stack.apis.models. The decision to use `import *` is debatable and
should probably be revisited at one point.

* Remove unneeded Ruff F401 rule
* Consolidate Ruff F403 rule in the pyprojectfrom
llama_stack.apis.models.models

Signed-off-by: Sébastien Han <seb@redhat.com>
2025-06-26 08:01:05 +05:30

35 lines
1.1 KiB
Python

# Copyright (c) Meta Platforms, Inc. and affiliates.
# All rights reserved.
#
# This source code is licensed under the terms described in the LICENSE file in
# the root directory of this source tree.
from llama_stack.apis.models import ModelType
from llama_stack.providers.utils.inference.model_registry import (
ProviderModelEntry,
)
LLM_MODEL_IDS = [
"anthropic/claude-3-5-sonnet-latest",
"anthropic/claude-3-7-sonnet-latest",
"anthropic/claude-3-5-haiku-latest",
]
MODEL_ENTRIES = [ProviderModelEntry(provider_model_id=m) for m in LLM_MODEL_IDS] + [
ProviderModelEntry(
provider_model_id="anthropic/voyage-3",
model_type=ModelType.embedding,
metadata={"embedding_dimension": 1024, "context_length": 32000},
),
ProviderModelEntry(
provider_model_id="anthropic/voyage-3-lite",
model_type=ModelType.embedding,
metadata={"embedding_dimension": 512, "context_length": 32000},
),
ProviderModelEntry(
provider_model_id="anthropic/voyage-code-3",
model_type=ModelType.embedding,
metadata={"embedding_dimension": 1024, "context_length": 32000},
),
]