wip

runner/app/routes/embeddings.py

@@ -5,30 +5,14 @@
 from fastapi import APIRouter, Depends, status
 from fastapi.responses import JSONResponse
 from fastapi.security import HTTPAuthorizationCredentials, HTTPBearer
-from pydantic import BaseModel, Field
 from app.dependencies import get_pipeline
 from app.pipelines.base import Pipeline
 from app.routes.utils import HTTPError, http_error
+from app.routes.utils import EmbeddingRequest, EmbeddingResponse
 
 router = APIRouter()
 logger = logging.getLogger(__name__)
 
-
-class EmbeddingRequest(BaseModel):
-    input: Union[str, List[str]] = Field(..., description="Text to embed")
-    model: str = Field("", description="Model to use")
-    instruction: Optional[str] = Field(
-        None, description="Instruction for instructor models")
-    normalize: bool = Field(True, description="Whether to normalize embeddings")
-
-
-class EmbeddingResponse(BaseModel):
-    object: str
-    data: List[Dict[str, Union[List[float], int]]]
-    model: str
-    usage: Dict[str, int]
-
-
 RESPONSES = {
     status.HTTP_200_OK: {"model": EmbeddingResponse},
     status.HTTP_400_BAD_REQUEST: {"model": HTTPError},

runner/app/routes/utils.py

@@ -95,6 +95,21 @@ class LLMResponse(BaseModel):
     created: int
 
 
+class EmbeddingRequest(BaseModel):
+    input: Union[str, List[str]] = Field(..., description="Text to embed")
+    model: str = Field("", description="Model to use")
+    instruction: Optional[str] = Field(
+        None, description="Instruction for instructor models")
+    normalize: bool = Field(True, description="Whether to normalize embeddings")
+
+
+class EmbeddingResponse(BaseModel):
+    object: str
+    data: List[Dict[str, Union[List[float], int]]]
+    model: str
+    usage: Dict[str, int]
+
+
 class ImageToTextResponse(BaseModel):
     """Response model for text generation."""