Qdrant-client

- fix `search_batch` with sparse vectors in grpc 484 by agourlay
- align `close` method signature between `QdrantClient` and `QdrantRemote` 477 by joein

Bugfix release 💊

- fix parallel and bugs with implicit ids in `upload_collection`, `upload_records`, `upload_points` 460
- fix setting `grpc_options` with `https` in `sync` mode, and with `http+api-key` in `async` mode 467
- fix extend json validation in local mode to fix backward compatibility issue with types like `datetime` and `uuid` 462

Changelog

---
Features 🪄
- exposed _gRPC_ options 401
- support setting custom shard key in `upload_collection` and `upload_points` 396
- unlocked python dependency upper cup 419
- unlocked `urllib3` v2 418
- ease access to `fastembed` models 412
- extend access for `fastembed` configuration 416

---
Fixes 🪛
- replaced `httpx` _data_ with _content_ 426
- forbid having _NaN_ in payload in `local mode` 397
- fix python warning which was sometimes emitted on garbage collection in `local mode` 398 421
- fix division by zero error in cosine similarity in `local mode` 425
- add `wait` parameter to `upload_records` in `migrate` to avoid false-positive asserts 428
- fix operations with _sparse vectors_ with unsorted indices in _local mode_ 442
- restrict inserting points with non-configured vectors in _local mode_ 432
- fix reading collections with unnamed dense and named sparse vectors in _local mode_ 433
- forbid to `migrate` from collections with custom shard keys 447
- align `timeout` param types in `QdrantClient` and its methods


Deprecation ⏳
- `upload_records` has been deprecated in favour of `upload_points` 447

Thanks to the devs who contributed to this release

generall shivas1516 praveen-palanisamy joein

Changelog

---
Features

* Add Discovery API ([docs](https://qdrant.tech/documentation/concepts/explore/#discovery-api)) - https://github.com/qdrant/qdrant-client/pull/368 by coszio
- **Discovery search**: Uses a target and context pairs to limit the search space during the search
- **Context search**: Using only the context pairs, get the points that live in the best zone
* Add Sparse vectors support ([docs](https://qdrant.tech/documentation/concepts/collections/#collection-with-sparse-vectors)) - https://github.com/qdrant/qdrant-client/pull/378 by agourlay
- Combine the dense and sparse vectors to build hybrid search
* Add Manhattan distance support - https://github.com/qdrant/qdrant-client/pull/391 by generall
* Add custom shard key API ([docs](https://qdrant.tech/documentation/guides/distributed_deployment/#user-defined-sharding)) - https://github.com/qdrant/qdrant-client/pull/391 by generall
- Configure how to distribute points among shards

---
Fixes

* https://github.com/qdrant/qdrant-client/pull/337 - Add `wait` parameter to snapshots API by joein

Changelog

* Missing fix form previous release: https://github.com/qdrant/qdrant-client/pull/338 - add missing parameters in recommend batch API

Changelog

Features

* Proper support for Async client - https://github.com/qdrant/qdrant-client/pull/319
* Now all methods of regular qdrant client are available in async version.
* All method names, parameters and return types are preserved.
* Both gRPC and REST version are available.

* Improvements of [fastembed](https://github.com/qdrant/fastembed) integration:
* Support the latest v0.1.x version of fastembed: https://github.com/qdrant/fastembed/releases/tag/0.1.0
* Support for encoding of iterators in `add` API, useful for lazy reading of large dataset
* Support for data-level parallelism of the encoding operations


Fixes

* https://github.com/qdrant/qdrant-client/pull/337 - fix: convert score to float in local mode for pydantic

---

Async Qdrant client usage example:

python
from qdrant_client import AsyncQdrantClient, models
import numpy as np
import asyncio

async def main():
client = AsyncQdrantClient(url="http://localhost:6333")

res = await client.search(
collection_name="my_collection",
query_vector=np.random.rand(10).tolist(), type: ignore
limit=10,
)

print(res)

asyncio.run(main())