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Get Milvus to use ANN

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This commit is contained in:
Cyber MacGeddon 2025-09-30 23:02:18 +01:00
parent 1d634df25a
commit 6b360dfc55
2 changed files with 6 additions and 18 deletions
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13
trustgraph-flow/trustgraph/direct/milvus_doc_embeddings.py
View file

@ -120,6 +120,8 @@ class DocVectors:
dim = len(embeds)
print("INSERT VEC", dim, flush=True)
if (dim, user, collection) not in self.collections:
self.init_collection(dim, user, collection)
@ -144,14 +146,6 @@ class DocVectors:
coll = self.collections[(dim, user, collection)]
search_params = {
"metric_type": "COSINE",
"params": {
"radius": 0.1,
"range_filter": 0.8
}
}
logger.debug("Loading...")
self.client.load_collection(
collection_name=coll,
@ -161,10 +155,11 @@ class DocVectors:
res = self.client.search(
collection_name=coll,
anns_field="vector",
data=[embeds],
limit=limit,
output_fields=fields,
search_params=search_params,
search_params={ "metric_type": "COSINE" },
)[0]

11
trustgraph-flow/trustgraph/direct/milvus_graph_embeddings.py
View file

@ -144,14 +144,6 @@ class EntityVectors:
coll = self.collections[(dim, user, collection)]
search_params = {
"metric_type": "COSINE",
"params": {
"radius": 0.1,
"range_filter": 0.8
}
}
logger.debug("Loading...")
self.client.load_collection(
collection_name=coll,
@ -161,10 +153,11 @@ class EntityVectors:
res = self.client.search(
collection_name=coll,
anns_field="vector",
data=[embeds],
limit=limit,
output_fields=fields,
search_params=search_params,
search_params={ "metric_type": "COSINE" },
)[0]