admin/dify
1
0
Fork 0
Code Issues Pull Requests Actions 1 Packages Projects Releases Wiki Activity

remove .value (#26633)

Browse Source 
Co-authored-by: autofix-ci[bot] <114827586+autofix-ci[bot]@users.noreply.github.com>
Co-authored-by: gemini-code-assist[bot] <176961590+gemini-code-assist[bot]@users.noreply.github.com>
This commit is contained in:
Asuka Minato
2025-10-11 10:08:29 +09:00
committed by GitHub
parent bb6a331490
commit 1bd621f819
138 changed files with 613 additions and 633 deletions
Download Patch File Download Diff File Expand all files Collapse all files

28
api/core/rag/datasource/vdb/huawei/huawei_cloud_vector.py
View File

@@ -67,9 +67,9 @@ class HuaweiCloudVector(BaseVector):
index=self._collection_name,
id=uuids[i],
document={
Field.CONTENT_KEY.value: documents[i].page_content,
Field.VECTOR.value: embeddings[i] or None,
Field.METADATA_KEY.value: documents[i].metadata or {},
Field.CONTENT_KEY: documents[i].page_content,
Field.VECTOR: embeddings[i] or None,
Field.METADATA_KEY: documents[i].metadata or {},
},
)
self._client.indices.refresh(index=self._collection_name)
@@ -101,7 +101,7 @@ class HuaweiCloudVector(BaseVector):
"size": top_k,
"query": {
"vector": {
Field.VECTOR.value: {
Field.VECTOR: {
"vector": query_vector,
"topk": top_k,
}
@@ -116,9 +116,9 @@ class HuaweiCloudVector(BaseVector):
docs_and_scores.append(
(
Document(
page_content=hit["_source"][Field.CONTENT_KEY.value],
vector=hit["_source"][Field.VECTOR.value],
metadata=hit["_source"][Field.METADATA_KEY.value],
page_content=hit["_source"][Field.CONTENT_KEY],
vector=hit["_source"][Field.VECTOR],
metadata=hit["_source"][Field.METADATA_KEY],
),
hit["_score"],
)
@@ -135,15 +135,15 @@ class HuaweiCloudVector(BaseVector):
return docs
def search_by_full_text(self, query: str, **kwargs: Any) -> list[Document]:
query_str = {"match": {Field.CONTENT_KEY.value: query}}
query_str = {"match": {Field.CONTENT_KEY: query}}
results = self._client.search(index=self._collection_name, query=query_str, size=kwargs.get("top_k", 4))
docs = []
for hit in results["hits"]["hits"]:
docs.append(
Document(
page_content=hit["_source"][Field.CONTENT_KEY.value],
vector=hit["_source"][Field.VECTOR.value],
metadata=hit["_source"][Field.METADATA_KEY.value],
page_content=hit["_source"][Field.CONTENT_KEY],
vector=hit["_source"][Field.VECTOR],
metadata=hit["_source"][Field.METADATA_KEY],
)
)
@@ -171,8 +171,8 @@ class HuaweiCloudVector(BaseVector):
dim = len(embeddings[0])
mappings = {
"properties": {
Field.CONTENT_KEY.value: {"type": "text"},
Field.VECTOR.value: { # Make sure the dimension is correct here
Field.CONTENT_KEY: {"type": "text"},
Field.VECTOR: { # Make sure the dimension is correct here
"type": "vector",
"dimension": dim,
"indexing": True,
@@ -181,7 +181,7 @@ class HuaweiCloudVector(BaseVector):
"neighbors": 32,
"efc": 128,
},
Field.METADATA_KEY.value: {
Field.METADATA_KEY: {
"type": "object",
"properties": {
"doc_id": {"type": "keyword"} # Map doc_id to keyword type