DashVector Vector Search

---

name: alicloud-ai-search-dashvector

description: Build vector retrieval with DashVector using the Python SDK. Use when creating collections, upserting docs, and running similarity search with filters in Claude Code/Codex.

version: 1.0.0

---

Category: provider

# DashVector Vector Search

Use DashVector to manage collections and perform vector similarity search with optional filters and sparse vectors.

Prerequisites

python3 -m venv .venv
. .venv/bin/activate
python -m pip install dashvector

- `DASHVECTOR_API_KEY`

- `DASHVECTOR_ENDPOINT` (cluster endpoint)

Normalized operations

Create collection

Upsert docs

Query docs

Quickstart (Python SDK)

import os
import dashvector
from dashvector import Doc

client = dashvector.Client(
    api_key=os.getenv("DASHVECTOR_API_KEY"),
    endpoint=os.getenv("DASHVECTOR_ENDPOINT"),
)

# 1) Create a collection
ret = client.create(
    name="docs",
    dimension=768,
    metric="cosine",
    fields_schema={"title": str, "source": str, "chunk": int},
)
assert ret

# 2) Upsert docs
collection = client.get(name="docs")
ret = collection.upsert(
    [
        Doc(id="1", vector=[0.01] * 768, fields={"title": "Intro", "source": "kb", "chunk": 0}),
        Doc(id="2", vector=[0.02] * 768, fields={"title": "FAQ", "source": "kb", "chunk": 1}),
    ]
)
assert ret

# 3) Query
ret = collection.query(
    vector=[0.01] * 768,
    topk=5,
    filter="source = 'kb' AND chunk >= 0",
    output_fields=["title", "source", "chunk"],
    include_vector=False,
)
for doc in ret:
    print(doc.id, doc.fields)

Script quickstart

python skills/ai/search/alicloud-ai-search-dashvector/scripts/quickstart.py

Environment variables:

Optional args: `--collection`, `--dimension`, `--topk`, `--filter`.

Notes for Claude Code/Codex

Error handling

Validation

mkdir -p output/alicloud-ai-search-dashvector
for f in skills/ai/search/alicloud-ai-search-dashvector/scripts/*.py; do
  python3 -m py_compile "$f"
done
echo "py_compile_ok" > output/alicloud-ai-search-dashvector/validate.txt

Pass criteria: command exits 0 and `output/alicloud-ai-search-dashvector/validate.txt` is generated.

Output And Evidence

Workflow

1) Confirm user intent, region, identifiers, and whether the operation is read-only or mutating.

2) Run one minimal read-only query first to verify connectivity and permissions.

3) Execute the target operation with explicit parameters and bounded scope.

4) Verify results and save output/evidence files.

References