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Feat: destination vector db add option for embedding without field names #91

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6 changes: 6 additions & 0 deletions airbyte_cdk/destinations/vector_db_based/config.py
Original file line number Diff line number Diff line change
Expand Up @@ -108,6 +108,12 @@ class ProcessingConfigModel(BaseModel):
always_show=True,
examples=["text", "user.name", "users.*.name"],
)
omit_field_names_from_embeddings: bool = Field(
default=False,
title="Omit field names from embeddings",
description="Do not include the field names in the text that gets embedded. By default field names are embedded e.g 'user: name, user.email: [email protected]'. If set to true, only the values are embedded e.g. 'name, [email protected]'.",
always_show=True,
)
metadata_fields: Optional[List[str]] = Field(
default=[],
title="Fields to store as metadata",
Expand Down
16 changes: 14 additions & 2 deletions airbyte_cdk/destinations/vector_db_based/document_processor.py
Original file line number Diff line number Diff line change
Expand Up @@ -5,7 +5,7 @@
import json
import logging
from dataclasses import dataclass
from typing import Any, Dict, List, Mapping, Optional, Tuple
from typing import Any, Dict, List, Mapping, Optional, Tuple, Union

import dpath
from airbyte_cdk.destinations.vector_db_based.config import (
Expand Down Expand Up @@ -125,6 +125,7 @@ def __init__(self, config: ProcessingConfigModel, catalog: ConfiguredAirbyteCata
self.text_fields = config.text_fields
self.metadata_fields = config.metadata_fields
self.field_name_mappings = config.field_name_mappings
self.omit_field_names_from_embeddings = config.omit_field_names_from_embeddings
self.logger = logging.getLogger("airbyte.document_processor")

def process(self, record: AirbyteRecordMessage) -> Tuple[List[Chunk], Optional[str]]:
Expand Down Expand Up @@ -162,10 +163,21 @@ def _generate_document(self, record: AirbyteRecordMessage) -> Optional[Document]
relevant_fields = self._extract_relevant_fields(record, self.text_fields)
if len(relevant_fields) == 0:
return None
text = stringify_dict(relevant_fields)
if not self.omit_field_names_from_embeddings:
text = stringify_dict(relevant_fields)
else:
text = self._extract_values_from_dict(relevant_fields)
metadata = self._extract_metadata(record)
return Document(page_content=text, metadata=metadata)

def _extract_values_from_dict(self, data: Union[dict, list, Any]) -> str:
if isinstance(data, dict):
return "\n".join(self._extract_values_from_dict(value) for value in data.values())
elif isinstance(data, list):
return "\n".join(self._extract_values_from_dict(item) for item in data)
else:
return str(data)

def _extract_relevant_fields(
self, record: AirbyteRecordMessage, fields: Optional[List[str]]
) -> Dict[str, Any]:
Expand Down
7 changes: 7 additions & 0 deletions unit_tests/destinations/vector_db_based/config_test.py
Original file line number Diff line number Diff line change
Expand Up @@ -242,6 +242,13 @@ def test_json_schema_generation():
"type": "array",
"items": {"type": "string"},
},
"omit_field_names_from_embeddings": {
"title": "Omit field names from embeddings",
"description": "Do not include the field names in the text that gets embedded. By default field names are embedded e.g 'user: name, user.email: [email protected]'. If set to true, only the values are embedded e.g. 'name, [email protected]'.",
"default": False,
"always_show": True,
"type": "boolean",
},
"metadata_fields": {
"title": "Fields to store as metadata",
"description": "List of fields in the record that should be stored as metadata. The field list is applied to all streams in the same way and non-existing fields are ignored. If none are defined, all fields are considered metadata fields. When specifying text fields, you can access nested fields in the record by using dot notation, e.g. `user.name` will access the `name` field in the `user` object. It's also possible to use wildcards to access all fields in an object, e.g. `users.*.name` will access all `names` fields in all entries of the `users` array. When specifying nested paths, all matching values are flattened into an array set to a field named by the path.",
Expand Down
51 changes: 51 additions & 0 deletions unit_tests/destinations/vector_db_based/document_processor_test.py
Original file line number Diff line number Diff line change
Expand Up @@ -193,6 +193,7 @@ def test_complex_text_fields():
"non.*.existing",
]
processor.metadata_fields = ["non_text", "non_text_2", "id"]
processor.omit_field_names_from_embeddings = False

chunks, _ = processor.process(record)

Expand All @@ -213,6 +214,56 @@ def test_complex_text_fields():
}


def test_complex_text_fields_omit_field_names():
processor = initialize_processor()

record = AirbyteRecordMessage(
stream="stream1",
namespace="namespace1",
data={
"id": 1,
"nested": {
"texts": [
{"text": "This is the text"},
{"text": "And another"},
]
},
"non_text": "a",
"non_text_2": 1,
"text": "This is the regular text",
"other_nested": {"non_text": {"a": "xyz", "b": "abc"}},
},
emitted_at=1234,
)

processor.text_fields = [
"nested.texts.*.text",
"text",
"other_nested.non_text",
"non.*.existing",
]
processor.metadata_fields = ["non_text", "non_text_2", "id"]
processor.omit_field_names_from_embeddings = True

chunks, _ = processor.process(record)

assert len(chunks) == 1
assert (
chunks[0].page_content
== """This is the text
And another
This is the regular text
xyz
abc"""
)
assert chunks[0].metadata == {
"id": 1,
"non_text": "a",
"non_text_2": 1,
"_ab_stream": "namespace1_stream1",
}


def test_no_text_fields():
processor = initialize_processor()

Expand Down
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