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joeingenerallcoszio
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Update models 1.17 (#1154)
* new: update models, add conversions, add conversion tests * new: add list shard keys, add get_optimizations * new: add weights to rrf * new: add cluster telemetry * new: add update_mode usage * fix: fix mypy * fix: populate inspection cache * use RRF ranking as in the core * timeouts propagation * gen async clients * implement score threshold for formular * new: add tests for update mode * fix: fix test skip comment * Relevance feedback local mode (#1152) * AI: implement local computation prompt: Considering the implementation in the server, make the local python implementation of the same scores calculation in this file: [@distances.py](...), consider that the local mode calculates for all points at once, while the server does it point by point. Server impl: ``` ... ``` * use constant for MARGIN * relevance feedback integration and test * do not exclude relevance context from result * Revert "do not exclude relevance context from result" This reverts commit 9c2a5ce. --------- Co-authored-by: generall <andrey@vasnetsov.com> * fix: fix conversion test --------- Co-authored-by: generall <andrey@vasnetsov.com> Co-authored-by: Luis Cossío <luis.cossio@qdrant.com>
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‎qdrant_client/async_client_base.py‎

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@@ -378,3 +378,16 @@ async def recover_current_peer(self) -> bool:
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async def remove_peer(self, peer_id: int, **kwargs: Any) -> bool:
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raise NotImplementedError()
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async def get_optimizations(
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self, collection_name: str, **kwargs: Any
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) -> types.OptimizationsResponse:
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raise NotImplementedError()
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async def list_shard_keys(
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self, collection_name: str, **kwargs: Any
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) -> types.ShardKeysResponse:
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raise NotImplementedError()
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async def cluster_telemetry(self, **kwargs: Any) -> types.DistributedTelemetryData:
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raise NotImplementedError()

‎qdrant_client/async_qdrant_client.py‎

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‎qdrant_client/async_qdrant_remote.py‎

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‎qdrant_client/client_base.py‎

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@@ -408,3 +408,23 @@ def recover_current_peer(self) -> bool:
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def remove_peer(self, peer_id: int, **kwargs: Any) -> bool:
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raise NotImplementedError()
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def get_optimizations(
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self,
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collection_name: str,
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**kwargs: Any,
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) -> types.OptimizationsResponse:
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raise NotImplementedError()
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def list_shard_keys(
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self,
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collection_name: str,
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**kwargs: Any,
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) -> types.ShardKeysResponse:
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raise NotImplementedError()
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def cluster_telemetry(
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self,
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**kwargs: Any,
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) -> types.DistributedTelemetryData:
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raise NotImplementedError()

‎qdrant_client/conversions/common_types.py‎

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Image: TypeAlias = rest.Image
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InferenceObject: TypeAlias = rest.InferenceObject
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StrictModeConfig: TypeAlias = rest.StrictModeConfig
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UpdateMode: TypeAlias = rest.UpdateMode
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QueryRequest: TypeAlias = rest.QueryRequest
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ClusterOperations: TypeAlias = rest.ClusterOperations
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ClusterStatus: TypeAlias = rest.ClusterStatus
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CollectionClusterInfo: TypeAlias = rest.CollectionClusterInfo
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OptimizationsResponse: TypeAlias = rest.OptimizationsResponse
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ShardKeysResponse: TypeAlias = rest.ShardKeysResponse
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DistributedTelemetryData: TypeAlias = rest.DistributedTelemetryData
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# we can't use `nptyping` package due to numpy/python-version incompatibilities
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# thus we need to define precise type annotations while we support python3.7

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