1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
|
from typing import Any, Optional, TypeVar
from uuid import UUID
from pydantic import BaseModel, Field
from shared.api.models.base import PaginatedR2RResult, R2RResults
T = TypeVar("T")
class IngestionResponse(BaseModel):
message: str = Field(
...,
description="A message describing the result of the ingestion request.",
)
task_id: Optional[UUID] = Field(
None,
description="The task ID of the ingestion request.",
)
document_id: UUID = Field(
...,
description="The ID of the document that was ingested.",
)
class Config:
json_schema_extra = {
"example": {
"message": "Ingestion task queued successfully.",
"task_id": "c68dc72e-fc23-5452-8f49-d7bd46088a96",
"document_id": "9fbe403b-c11c-5aae-8ade-ef22980c3ad1",
}
}
class UpdateResponse(BaseModel):
message: str = Field(
...,
description="A message describing the result of the ingestion request.",
)
task_id: Optional[UUID] = Field(
None,
description="The task ID of the ingestion request.",
)
document_ids: list[UUID] = Field(
...,
description="The ID of the document that was ingested.",
)
class Config:
json_schema_extra = {
"example": {
"message": "Update task queued successfully.",
"task_id": "c68dc72e-fc23-5452-8f49-d7bd46088a96",
"document_ids": ["9fbe403b-c11c-5aae-8ade-ef22980c3ad1"],
}
}
class VectorIndexResponse(BaseModel):
index: dict[str, Any]
class VectorIndicesResponse(BaseModel):
indices: list[VectorIndexResponse]
WrappedIngestionResponse = R2RResults[IngestionResponse]
WrappedMetadataUpdateResponse = R2RResults[IngestionResponse]
WrappedUpdateResponse = R2RResults[UpdateResponse]
WrappedVectorIndexResponse = R2RResults[VectorIndexResponse]
WrappedVectorIndicesResponse = PaginatedR2RResult[VectorIndicesResponse]
|
