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|
import json
from typing import Any, Optional
from uuid import UUID
from shared.api.models import (
WrappedBooleanResponse,
WrappedChunkResponse,
WrappedChunksResponse,
WrappedVectorSearchResponse,
)
from ..models import SearchSettings
class ChunksSDK:
"""SDK for interacting with chunks in the v3 API."""
def __init__(self, client):
self.client = client
def update(
self,
chunk: dict[str, str],
) -> WrappedChunkResponse:
"""Update an existing chunk.
Args:
chunk (dict[str, str]): Chunk to update. Should contain:
- id: UUID of the chunk
- metadata: Dictionary of metadata
Returns:
WrappedChunkResponse
"""
response_dict = self.client._make_request(
"POST",
f"chunks/{str(chunk['id'])}",
json=chunk,
version="v3",
)
return WrappedChunkResponse(**response_dict)
def retrieve(
self,
id: str | UUID,
) -> WrappedChunkResponse:
"""Get a specific chunk.
Args:
id (str | UUID): Chunk ID to retrieve
Returns:
WrappedChunkResponse
"""
response_dict = self.client._make_request(
"GET",
f"chunks/{id}",
version="v3",
)
return WrappedChunkResponse(**response_dict)
# FIXME: Is this the most appropriate name for this method?
def list_by_document(
self,
document_id: str | UUID,
metadata_filter: Optional[dict] = None,
offset: Optional[int] = 0,
limit: Optional[int] = 100,
) -> WrappedChunksResponse:
"""List chunks for a specific document.
Args:
document_id (str | UUID): Document ID to get chunks for
metadata_filter (Optional[dict]): Filter chunks by metadata
offset (int, optional): Specifies the number of objects to skip. Defaults to 0.
limit (int, optional): Specifies a limit on the number of objects to return, ranging between 1 and 100. Defaults to 100.
Returns:
WrappedChunksResponse
"""
params: dict = {
"offset": offset,
"limit": limit,
}
if metadata_filter:
params["metadata_filter"] = json.dumps(metadata_filter)
response_dict = self.client._make_request(
"GET",
f"documents/{str(document_id)}/chunks",
params=params,
version="v3",
)
return WrappedChunksResponse(**response_dict)
def delete(
self,
id: str | UUID,
) -> WrappedBooleanResponse:
"""Delete a specific chunk.
Args:
id (str | UUID): ID of chunk to delete
Returns:
WrappedBooleanResponse
"""
response_dict = self.client._make_request(
"DELETE",
f"chunks/{str(id)}",
version="v3",
)
return WrappedBooleanResponse(**response_dict)
def list(
self,
include_vectors: bool = False,
metadata_filter: Optional[dict] = None,
offset: Optional[int] = 0,
limit: Optional[int] = 100,
filters: Optional[dict] = None,
) -> WrappedChunksResponse:
"""List chunks with pagination support.
Args:
include_vectors (bool, optional): Include vector data in response. Defaults to False.
metadata_filter (Optional[dict], optional): Filter by metadata. Defaults to None.
offset (int, optional): Specifies the number of objects to skip. Defaults to 0.
limit (int, optional): Specifies a limit on the number of objects to return, ranging between 1 and 100. Defaults to 100.
Returns:
WrappedChunksResponse
"""
params: dict = {
"offset": offset,
"limit": limit,
"include_vectors": include_vectors,
}
if filters:
params["filters"] = json.dumps(filters)
if metadata_filter:
params["metadata_filter"] = json.dumps(metadata_filter)
response_dict = self.client._make_request(
"GET",
"chunks",
params=params,
version="v3",
)
return WrappedChunksResponse(**response_dict)
def search(
self,
query: str,
search_settings: Optional[dict | SearchSettings] = None,
) -> WrappedVectorSearchResponse:
"""Conduct a vector and/or graph search.
Args:
query (str): The query to search for.
search_settings (Optional[dict, SearchSettings]]): Vector search settings.
Returns:
WrappedVectorSearchResponse
"""
if search_settings and not isinstance(search_settings, dict):
search_settings = search_settings.model_dump()
data: dict[str, Any] = {
"query": query,
"search_settings": search_settings,
}
response_dict = self.client._make_request(
"POST",
"chunks/search",
json=data,
version="v3",
)
return WrappedVectorSearchResponse(**response_dict)
|
