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. Ideal for demos, CI, air-gapped tools. Cluster-only features (GROUP BY, custom SHARD, ACORN, …) fail with stable QQL-EDGE-UNSUPPORTED-* codes.

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	Unsupported offline — use remote Qdrant
Models	Locked at executor construction
Lifetime	Call `close()` before deleting `data_dir`

Docs

qql-edge · Gaps · Syntax

Development Status
- 3 - Alpha
Programming Language
- Python :: 3
- Rust
Typing
- Typed

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