mirror of
https://github.com/qdrant/qdrant-client.git
synced 2026-07-26 20:51:09 -05:00
63f69540a6
* 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 9c2a5cedc0.
---------
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>
118 lines
2.9 KiB
Python
118 lines
2.9 KiB
Python
# flake8: noqa E501
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from typing import TYPE_CHECKING, Any, Dict, Set, TypeVar, Union
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from pydantic import BaseModel
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from pydantic.main import BaseModel
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from pydantic.version import VERSION as PYDANTIC_VERSION
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from qdrant_client.http.models import *
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from qdrant_client.http.models import models as m
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PYDANTIC_V2 = PYDANTIC_VERSION.startswith("2.")
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Model = TypeVar("Model", bound="BaseModel")
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SetIntStr = Set[Union[int, str]]
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DictIntStrAny = Dict[Union[int, str], Any]
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file = None
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def to_json(model: BaseModel, *args: Any, **kwargs: Any) -> str:
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if PYDANTIC_V2:
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return model.model_dump_json(*args, **kwargs)
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else:
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return model.json(*args, **kwargs)
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def jsonable_encoder(
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obj: Any,
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include: Union[SetIntStr, DictIntStrAny] = None,
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exclude=None,
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by_alias: bool = True,
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skip_defaults: bool = None,
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exclude_unset: bool = True,
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exclude_none: bool = True,
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):
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if hasattr(obj, "json") or hasattr(obj, "model_dump_json"):
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return to_json(
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obj,
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include=include,
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exclude=exclude,
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by_alias=by_alias,
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exclude_unset=bool(exclude_unset or skip_defaults),
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exclude_none=exclude_none,
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)
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return obj
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if TYPE_CHECKING:
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from qdrant_client.http.api_client import ApiClient
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class _BetaApi:
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def __init__(self, api_client: "Union[ApiClient, AsyncApiClient]"):
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self.api_client = api_client
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def _build_for_clear_issues(
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self,
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):
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"""
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Removes all issues reported so far
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"""
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headers = {}
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return self.api_client.request(
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type_=m.InlineResponse2001,
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method="DELETE",
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url="/issues",
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headers=headers if headers else None,
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)
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def _build_for_get_issues(
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self,
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):
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"""
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Get a report of performance issues and configuration suggestions
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"""
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headers = {}
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return self.api_client.request(
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type_=object,
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method="GET",
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url="/issues",
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headers=headers if headers else None,
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)
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class AsyncBetaApi(_BetaApi):
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async def clear_issues(
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self,
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) -> m.InlineResponse2001:
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"""
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Removes all issues reported so far
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"""
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return await self._build_for_clear_issues()
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async def get_issues(
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self,
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) -> object:
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"""
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Get a report of performance issues and configuration suggestions
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"""
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return await self._build_for_get_issues()
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class SyncBetaApi(_BetaApi):
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def clear_issues(
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self,
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) -> m.InlineResponse2001:
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"""
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Removes all issues reported so far
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"""
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return self._build_for_clear_issues()
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def get_issues(
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self,
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) -> object:
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"""
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Get a report of performance issues and configuration suggestions
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"""
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return self._build_for_get_issues()
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