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feat: Adding OpenAI Compatible Prompts API

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Signed-off-by: Francisco Javier Arceo <farceo@redhat.com>
This commit is contained in:
Francisco Javier Arceo 2025-09-03 14:14:54 -04:00
parent 30117dea22
commit 8b00883abd
181 changed files with 21356 additions and 10332 deletions
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15
tests/unit/providers/vector_io/test_qdrant.py
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@ -11,7 +11,8 @@ from unittest.mock import AsyncMock, MagicMock, patch
import pytest
from llama_stack.apis.inference import EmbeddingsResponse, Inference
from llama_stack.apis.inference import Inference
from llama_stack.apis.inference.inference import OpenAIEmbeddingData, OpenAIEmbeddingsResponse, OpenAIEmbeddingUsage
from llama_stack.apis.vector_io import (
QueryChunksResponse,
VectorDB,
@ -53,7 +54,9 @@ def mock_vector_db(vector_db_id) -> MagicMock:
mock_vector_db.identifier = vector_db_id
mock_vector_db.embedding_dimension = 384
mock_vector_db.model_dump_json.return_value = (
'{"identifier": "' + vector_db_id + '", "embedding_model": "embedding_model", "embedding_dimension": 384}'
'{"identifier": "'
+ vector_db_id
+ '", "provider_id": "qdrant", "embedding_model": "embedding_model", "embedding_dimension": 384}'
)
return mock_vector_db
@ -68,7 +71,13 @@ def mock_vector_db_store(mock_vector_db) -> MagicMock:
@pytest.fixture
def mock_api_service(sample_embeddings):
mock_api_service = MagicMock(spec=Inference)
mock_api_service.embeddings = AsyncMock(return_value=EmbeddingsResponse(embeddings=sample_embeddings))
mock_api_service.openai_embeddings = AsyncMock(
return_value=OpenAIEmbeddingsResponse(
model="mock-embedding-model",
data=[OpenAIEmbeddingData(embedding=sample, index=i) for i, sample in enumerate(sample_embeddings)],
usage=OpenAIEmbeddingUsage(prompt_tokens=10, total_tokens=10),
)
)
return mock_api_service