summaryrefslogtreecommitdiff
path: root/rag/db/vectors.py
diff options
context:
space:
mode:
authorGustaf Rydholm <gustaf.rydholm@gmail.com>2024-04-06 01:21:52 +0200
committerGustaf Rydholm <gustaf.rydholm@gmail.com>2024-04-06 01:21:52 +0200
commit13ac875b2269756045834d7a64e7b35acb9ce0b4 (patch)
treeab05dc7ba966de66e15cc8249ec2d772a2a4d34d /rag/db/vectors.py
parent59c77c93c39755526e3d7649660780584b1c090d (diff)
Rename dbs
Diffstat (limited to 'rag/db/vectors.py')
-rw-r--r--rag/db/vectors.py53
1 files changed, 0 insertions, 53 deletions
diff --git a/rag/db/vectors.py b/rag/db/vectors.py
deleted file mode 100644
index 9e8becb..0000000
--- a/rag/db/vectors.py
+++ /dev/null
@@ -1,53 +0,0 @@
-import os
-from dataclasses import dataclass
-from typing import Dict, List
-
-from qdrant_client import QdrantClient
-from qdrant_client.http.models import StrictFloat
-from qdrant_client.models import Distance, ScoredPoint, VectorParams, PointStruct
-from loguru import logger as log
-
-
-@dataclass
-class Point:
- id: str
- vector: List[StrictFloat]
- payload: Dict[str, str]
-
-
-class Vectors:
- def __init__(self):
- self.dim = int(os.environ["EMBEDDING_DIM"])
- self.collection_name = os.environ["QDRANT_COLLECTION_NAME"]
- self.client = QdrantClient(url=os.environ["QDRANT_URL"])
- self.__configure()
-
- def __configure(self):
- collections = list(map(lambda col: col.name, self.client.get_collections()))
- if self.collection_name not in collections:
- log.debug(f"Configuring collection {self.collection_name}...")
- self.client.create_collection(
- collection_name=self.collection_name,
- vectors_config=VectorParams(size=self.dim, distance=Distance.COSINE),
- )
- else:
- log.debug(f"Collection {self.collection_name} already exists...")
-
- def add(self, points: List[Point]):
- log.debug(f"Inserting {len(points)} vectors into the vector db...")
- self.client.upload_points(
- collection_name=self.collection_name,
- points=[
- PointStruct(id=point.id, vector=point.vector, payload=point.payload)
- for point in points
- ],
- parallel=4,
- max_retries=3,
- )
-
- def search(self, query: List[float], limit: int = 4) -> List[ScoredPoint]:
- log.debug("Searching for vectors...")
- hits = self.client.search(
- collection_name=self.collection_name, query_vector=query, limit=limit
- )
- return hits