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feat: register embedding models for ollama, together, fireworks (#1190)

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# What does this PR do?

We have support for embeddings in our Inference providers, but so far we
haven't done the final step of actually registering the known embedding
models and making sure they are extremely easy to use. This is one step
towards that.

## Test Plan

Run existing inference tests.

```bash

$ cd llama_stack/providers/tests/inference
$ pytest -s -v -k fireworks test_embeddings.py \
   --inference-model nomic-ai/nomic-embed-text-v1.5 --env EMBEDDING_DIMENSION=784
$  pytest -s -v -k together test_embeddings.py \
   --inference-model togethercomputer/m2-bert-80M-8k-retrieval --env EMBEDDING_DIMENSION=784
$ pytest -s -v -k ollama test_embeddings.py \
   --inference-model all-minilm:latest --env EMBEDDING_DIMENSION=784
```

The value of the EMBEDDING_DIMENSION isn't actually used in these tests,
it is merely used by the test fixtures to check if the model is an LLM
or Embedding.
This commit is contained in:
Ashwin Bharambe 2025-02-20 15:39:08 -08:00 • committed by GitHub
parent 736560ceba
commit 9436dd570d
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18 changed files with 214 additions and 105 deletions
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4
llama_stack/providers/tests/inference/fixtures.py
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@ -20,7 +20,7 @@ from llama_stack.providers.remote.inference.cerebras import CerebrasImplConfig
from llama_stack.providers.remote.inference.fireworks import FireworksImplConfig
from llama_stack.providers.remote.inference.groq import GroqConfig
from llama_stack.providers.remote.inference.nvidia import NVIDIAConfig
from llama_stack.providers.remote.inference.ollama import OllamaImplConfig
from llama_stack.providers.remote.inference.ollama import DEFAULT_OLLAMA_URL, OllamaImplConfig
from llama_stack.providers.remote.inference.sambanova import SambaNovaImplConfig
from llama_stack.providers.remote.inference.tgi import TGIImplConfig
from llama_stack.providers.remote.inference.together import TogetherImplConfig
@ -89,7 +89,7 @@ def inference_ollama() -> ProviderFixture:
Provider(
provider_id="ollama",
provider_type="remote::ollama",
config=OllamaImplConfig(url=get_env_or_fail("OLLAMA_URL")).model_dump(),
config=OllamaImplConfig(url=os.getenv("OLLAMA_URL", DEFAULT_OLLAMA_URL)).model_dump(),
)
],
)