DAN-81 Improve search round 2 (#82)

Includes:
- Multi vector indexing/search
- Ensemble model reranking
- Keyword Search backend

backend/scripts/reset_indexes.py

@@ -0,0 +1,39 @@
+# This file is purely for development use, not included in any builds
+from danswer.configs.model_configs import DOC_EMBEDDING_DIM
+from danswer.datastores.typesense.store import create_typesense_collection
+from danswer.utils.clients import get_qdrant_client
+from danswer.utils.clients import get_typesense_client
+from danswer.utils.logging import setup_logger
+from qdrant_client.http.models import Distance
+from qdrant_client.http.models import VectorParams
+from typesense.exceptions import ObjectNotFound  # type: ignore
+
+logger = setup_logger()
+
+
+def recreate_qdrant_collection(
+    collection_name: str, embedding_dim: int = DOC_EMBEDDING_DIM
+) -> None:
+    logger.info(f"Attempting to recreate Qdrant collection {collection_name}")
+    result = get_qdrant_client().recreate_collection(
+        collection_name=collection_name,
+        vectors_config=VectorParams(size=embedding_dim, distance=Distance.COSINE),
+    )
+    if not result:
+        raise RuntimeError("Could not create Qdrant collection")
+
+
+def recreate_typesense_collection(collection_name: str) -> None:
+    logger.info(f"Attempting to recreate Typesense collection {collection_name}")
+    ts_client = get_typesense_client()
+    try:
+        ts_client.collections[collection_name].delete()
+    except ObjectNotFound:
+        logger.debug(f"Collection {collection_name} does not already exist")
+
+    create_typesense_collection(collection_name)
+
+
+if __name__ == "__main__":
+    recreate_qdrant_collection("danswer_index")
+    recreate_typesense_collection("danswer_index")