klas/t6_mem0
1
0
Fork 0
Code Issues Pull Requests Actions Packages Projects Releases Wiki Activity

Formatting and Client changes (#2247)

Browse Source
This commit is contained in:
Dev Khant
2025-02-23 00:39:26 +05:30
committed by GitHub
parent 17887b5959
commit c42934b7fb
9 changed files with 50 additions and 100 deletions
Download Patch File Download Diff File Expand all files Collapse all files

75
mem0/vector_stores/elasticsearch.py
View File

@@ -49,30 +49,14 @@ class ElasticsearchDB(VectorStoreBase):
def create_index(self) -> None:
"""Create Elasticsearch index with proper mappings if it doesn't exist"""
index_settings = {
"settings": {
"index": {
"number_of_replicas": 1,
"number_of_shards": 5,
"refresh_interval": "1s"
}
},
"settings": {"index": {"number_of_replicas": 1, "number_of_shards": 5, "refresh_interval": "1s"}},
"mappings": {
"properties": {
"text": {"type": "text"},
"vector": {
"type": "dense_vector",
"dims": self.vector_dim,
"index": True,
"similarity": "cosine"
},
"metadata": {
"type": "object",
"properties": {
"user_id": {"type": "keyword"}
}
}
"vector": {"type": "dense_vector", "dims": self.vector_dim, "index": True, "similarity": "cosine"},
"metadata": {"type": "object", "properties": {"user_id": {"type": "keyword"}}},
}
}
},
}
if not self.client.indices.exists(index=self.collection_name):
@@ -114,8 +98,8 @@ class ElasticsearchDB(VectorStoreBase):
"_id": id_,
"_source": {
"vector": vec,
"metadata": payloads[i] # Store all metadata in the metadata field
}
"metadata": payloads[i], # Store all metadata in the metadata field
},
}
actions.append(action)
@@ -127,7 +111,7 @@ class ElasticsearchDB(VectorStoreBase):
OutputData(
id=id_,
score=1.0, # Default score for inserts
payload=payloads[i]
payload=payloads[i],
)
)
return results
@@ -136,35 +120,20 @@ class ElasticsearchDB(VectorStoreBase):
"""Search for similar vectors using KNN search with pre-filtering."""
if not filters:
# If no filters, just do KNN search
search_query = {
"knn": {
"field": "vector",
"query_vector": query,
"k": limit,
"num_candidates": limit * 2
}
}
search_query = {"knn": {"field": "vector", "query_vector": query, "k": limit, "num_candidates": limit * 2}}
else:
# If filters exist, apply them with KNN search
filter_conditions = []
for key, value in filters.items():
filter_conditions.append({
"term": {
f"metadata.{key}": value
}
})
filter_conditions.append({"term": {f"metadata.{key}": value}})
search_query = {
"knn": {
"field": "vector",
"query_vector": query,
"k": limit,
"num_candidates": limit * 2,
"filter": {
"bool": {
"must": filter_conditions
}
}
"filter": {"bool": {"must": filter_conditions}},
}
}
@@ -173,11 +142,7 @@ class ElasticsearchDB(VectorStoreBase):
results = []
for hit in response["hits"]["hits"]:
results.append(
OutputData(
id=hit["_id"],
score=hit["_score"],
payload=hit.get("_source", {}).get("metadata", {})
)
OutputData(id=hit["_id"], score=hit["_score"], payload=hit.get("_source", {}).get("metadata", {}))
)
return results
@@ -203,7 +168,7 @@ class ElasticsearchDB(VectorStoreBase):
return OutputData(
id=response["_id"],
score=1.0, # Default score for direct get
payload=response["_source"].get("metadata", {})
payload=response["_source"].get("metadata", {}),
)
except KeyError as e:
logger.warning(f"Missing key in Elasticsearch response: {e}")
@@ -234,16 +199,8 @@ class ElasticsearchDB(VectorStoreBase):
if filters:
filter_conditions = []
for key, value in filters.items():
filter_conditions.append({
"term": {
f"metadata.{key}": value
}
})
query["query"] = {
"bool": {
"must": filter_conditions
}
}
filter_conditions.append({"term": {f"metadata.{key}": value}})
query["query"] = {"bool": {"must": filter_conditions}}
if limit:
query["size"] = limit
@@ -256,7 +213,7 @@ class ElasticsearchDB(VectorStoreBase):
OutputData(
id=hit["_id"],
score=1.0, # Default score for list operation
payload=hit.get("_source", {}).get("metadata", {})
payload=hit.get("_source", {}).get("metadata", {}),
)
)