/claim #273

Summary

• Add a dependency-free Qdrant REST client under the existing JS SDK vector-db package.
• Export Qdrant and TypeScript types alongside Supabase.
• Support collection creation, insertVectorData/upsert, getDataFromQuery/search, getData/scroll, getDataById, updateById, and deleteById.
• Add mocked Vitest coverage for REST request shapes and result handling.
• Add a runnable dry-run example under JS/edgechains/examples/qdrant-vector-db.

Requirement Checklist

• Qdrant support added to JavaScript SDK vector database package: yes
• Qdrant REST API used directly: yes
• No Qdrant npm package introduced: yes
• EdgeChains classes/types exported from vector-db: yes
• Tests included: yes
• Runnable example included: yes
• Short demo included in this PR: yes
• CLA signed and CI passing: yes

Validation

• npx vitest run src/vector-db/src/tests/qdrant/qdrant.test.ts
• npm run build
• npm start from JS/edgechains/examples/qdrant-vector-db

Demo

Short demo GIF:

The example uses a mock HTTP client and prints the Qdrant REST requests it would send for collection creation, vector upsert, and search. It does not use any Qdrant npm package.

Full demo transcript, included so the output remains reviewable even if GitHub clips the embedded media:

EdgeChains #273 demo: Qdrant vector database client
Dry-run example; no Qdrant server or Qdrant npm package required.

$ cd JS/edgechains/examples/qdrant-vector-db
$ npm start

Creating collection:
PUT /collections/edgechains_docs
vectors.size = 3
vectors.distance = Cosine

Upserting vectors:
PUT /collections/edgechains_docs/points
points[0].id = doc-1
points[0].payload.text = EdgeChains supports direct Qdrant REST calls.

Searching:
POST /collections/edgechains_docs/points/search
vector = [0.12, 0.25, 0.87]
limit = 3

Search results:
doc-1 score=0.98 text="EdgeChains supports direct Qdrant REST calls."

✓ npx vitest run src/vector-db/src/tests/qdrant/qdrant.test.ts