---

name: local-mode description: "Use qdrant-client local in-memory and persistent stores for safe prototyping, local vector tests, filtering, sparse/named/multivector queries, persistence, locks, and migration boundaries." disable-model-invocation: true metadata: disco-role: operating license: Apache 2.0

local-mode

Use this sub-skill when the task is about running Qdrant through qdrant-client without a Qdrant server: QdrantClient(":memory:") for ephemeral tests or QdrantClient(path=...) for a persistent local store.

Route Here For

• Local in-memory examples, fixtures, notebooks, and deterministic smoke tests.
• Persistent local storage that can be closed and reopened with the same collection data.
• Local dense, sparse, named-vector, multivector, payload-filter, and fusion-query behavior.
• Local-only limits: exclusive persistent-path locks, closed-instance errors, raw REST/gRPC client unavailability, and large-data warnings.
• Deciding when a prototype should move from local mode to a Qdrant server or Qdrant Cloud.

Route Elsewhere

• Use ../client-operations/ for general collection, point, query, scroll, delete, batch, and CRUD method coverage that applies to both local and remote clients.
• Use ../connection-and-transport/ for server URLs, Cloud API keys, REST/gRPC transport, compatibility checks, TLS, timeouts, and raw transport clients.
• Use ../async-client/ for AsyncQdrantClient(":memory:") or async local usage.
• Use ../inference/ for FastEmbed, local model downloads, models.Document, GPU inference extras, and Cloud inference.

Quick Start

from qdrant_client import QdrantClient, models

client = QdrantClient(":memory:")
client.create_collection(
    "demo",
    vectors_config=models.VectorParams(size=4, distance=models.Distance.COSINE),
)
client.upsert(
    "demo",
    points=[models.PointStruct(id=1, vector=[1.0, 0.0, 0.0, 0.0], payload={"tag": "local"})],
)
hits = client.query_points("demo", query=[1.0, 0.0, 0.0, 0.0], limit=1).points
assert hits[0].id == 1
client.close()

For a deterministic validation script after installing qdrant-client, run:

python sub-skills/local-mode/scripts/local_mode_smoke.py --mode memory
python sub-skills/local-mode/scripts/local_mode_smoke.py --mode persistent

Read Next

• references/local-mode.md for in-memory and persistent recipes, named dense/sparse/multivector examples, payload filtering, score thresholds, and migration guidance.
• references/troubleshooting.md for lock errors, large local collections, unsupported local raw clients, closed instances, vector mismatches, and persistence surprises.
• scripts/local_mode_smoke.py for a safe smoke helper that exercises local dense, sparse, multivector, fusion, filtering, persistence, and locking behavior.