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pyqql-edge

Local QQL for Python: qdrant-edge + FastEmbed, zero remote Qdrant.

Proposition

Same QQL language as pyqql, but storage and (optionally) embeddings run in-process (qdrant-edge 0.8). Ideal for demos, CI, air-gapped tools. Cluster-only features (GROUP BY, custom SHARD, ACORN, SHOW QUOTAS / SET QUOTA, …) fail with stable QQL-EDGE-UNSUPPORTED-* codes. Sparse PARAMS (idf = …) is supported offline.

Install

pip install pyqql-edge

Python 3.8+. Wheels: Linux x64, macOS arm64, Windows x64 (not macOS Intel — ONNX).

Quick start

import pyqql_edge

client = pyqql_edge.local_executor(
    "./qdrant_data",
    on_disk_payload=False,
    model="bge-small-en-v1.5",
)

client.execute("CREATE COLLECTION docs HYBRID")
client.execute(
    'UPSERT INTO docs VALUES {id: 1, text: "hello from edge"}'
)
report = client.execute("QUERY TEXT 'hello' FROM docs USING dense LIMIT 10")
print(report)

stmt = pyqql_edge.parse("QUERY TEXT 'hello' FROM docs USING dense LIMIT 10")[0]
pyqql_edge.inject_filter(stmt, "org_id", "=", "acme")
# Edge has no custom SHARD routing — use remote Qdrant for SHARD / CREATE SHARD KEY

client.close()

API

Export Role
local_executor(data_dir, …) FastEmbed + edge storage
http_executor(data_dir, url, …) Edge storage + remote HTTP embedder
list_embedding_models() Dense ONNX catalog
parse / parse_json / is_valid / tokenize Frontend
inject_filter Isolation
Stmt.shard_key Property exists for AST parity; edge rejects SHARD at execute
compile_query / explain / execute Plan / run

Edge gotchas

Topic Reality
Point IDs Integers or UUIDs only
HYBRID queries Specify USING dense / USING sparse / hybrid forms
GROUP BY, SHARD, ACORN, quotas Unsupported offline — use remote Qdrant (QQL-EDGE-UNSUPPORTED-*)
Sparse idf Supported (qdrant-edge 0.8)
Models Locked at executor construction
Lifetime Call close() before deleting data_dir

Docs

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