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# What does this PR do? This PR adds OpenAI compatibility for Ollama embeddings. Closes https://github.com/meta-llama/llama-stack/issues/2428 Summary of changes: - `llama_stack/providers/remote/inference/ollama/ollama.py` - Implements the OpenAI embeddings endpoint for Ollama, replacing the NotImplementedError with a full function that validates the model, prepares parameters, calls the client, encodes embedding data (optionally in base64), and returns a correctly structured response. - Updates import statements to include the new embedding response utilities. - `llama_stack/providers/utils/inference/litellm_openai_mixin.py` - Refactors the embedding data encoding logic to use a new shared utility (`b64_encode_openai_embeddings_response`) instead of inline base64 encoding and packing logic. - Cleans up imports accordingly. - `llama_stack/providers/utils/inference/openai_compat.py` - Adds `b64_encode_openai_embeddings_response` to handle encoding OpenAI embedding outputs (including base64 support) in a reusable way. - Adds `prepare_openai_embeddings_params` utility for standardizing embedding parameter preparation. - Updates imports to include the new embedding data class. - `tests/integration/inference/test_openai_embeddings.py` - Removes `"remote::ollama"` from the list of providers that skip OpenAI embeddings tests, since support is now implemented. ## Note There was one minor issue, which required me to override the `OpenAIEmbeddingsResponse.model` name with `self._get_model(model).identifier` name, which is very unsatisfying. ## Test Plan Unit Tests and integration tests --------- Signed-off-by: Francisco Javier Arceo <farceo@redhat.com> |
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| .. | ||
| bedrock | ||
| common | ||
| datasetio | ||
| inference | ||
| kvstore | ||
| memory | ||
| responses | ||
| scoring | ||
| sqlstore | ||
| telemetry | ||
| tools | ||
| __init__.py | ||
| pagination.py | ||
| scheduler.py | ||