mirror of
https://github.com/qdrant/qdrant-client.git
synced 2026-07-30 14:41:03 -05:00
b4ae703d1b
* wip: add draft implementation of batch processing * fix: embed dict and list of docs, remove redundant code * new: regen async, small refactor * refactor: add docstrings, rename methods * Upload points local inference (#881) * new: separate single and plural model embeddings * fix: fix lazy embed models * new: add inference object inspections to upload methods * wip: local inference upload parallel * new: add local inference to upload points and upload collection, refactor mixin * fix: remove redundant code * redundant import * tests: check is query for query points batch * refactor: refactor semi ordered map * tests: add test for local inference with batches with docs and vectors * tests: check the order of dict processing * new: distinguish models by options * fix: fix typing * fix: fix types * new: embed batches with different options * tests: add tests for batch with different options * fix: ignore ide incorrect type inspection * tests: wait for points to be inserted * fix: set threads to 1 in parallel inference * new: adjust max internal batch size * fix: fix type hints * function to get embeddings size (#892) * function to get embeddings size * async client * keep sync * new: extend embedding size to support image and late interaction models --------- Co-authored-by: George Panchuk <george.panchuk@qdrant.tech> * new: add local inference batch size (#894) --------- Co-authored-by: Andrey Vasnetsov <andrey@vasnetsov.com>
79 lines
2.8 KiB
Python
79 lines
2.8 KiB
Python
import inspect
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from typing import Optional
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from tools.async_client_generator.async_client_base import AsyncQdrantBase
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from tools.async_client_generator.base_generator import BaseGenerator
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from tools.async_client_generator.transformers import (
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ClassDefTransformer,
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ImportFromTransformer,
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ImportTransformer,
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)
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from tools.async_client_generator.transformers.fastembed import (
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FastembedCallTransformer,
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FastembedFunctionDefTransformer,
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)
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class FastembedGenerator(BaseGenerator):
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def __init__(
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self,
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keep_sync: Optional[list[str]] = None,
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class_replace_map: Optional[dict[str, str]] = None,
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import_replace_map: Optional[dict[str, str]] = None,
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):
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super().__init__()
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self._async_methods: Optional[list[str]] = None
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self.transformers.append(FastembedCallTransformer(async_methods=self.async_methods))
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self.transformers.append(ClassDefTransformer(class_replace_map=class_replace_map))
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self.transformers.append(ImportTransformer(import_replace_map=import_replace_map))
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self.transformers.append(ImportFromTransformer(import_replace_map=import_replace_map))
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self.transformers.append(FastembedFunctionDefTransformer(keep_sync=keep_sync))
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@property
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def async_methods(self) -> list[str]:
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if self._async_methods is None:
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self._async_methods = self.get_async_methods(AsyncQdrantBase)
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return self._async_methods
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@staticmethod
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def get_async_methods(class_obj: type) -> list[str]:
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async_methods = []
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for name, method in inspect.getmembers(class_obj):
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if inspect.iscoroutinefunction(method):
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async_methods.append(name)
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return async_methods
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if __name__ == "__main__":
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from tools.async_client_generator.config import CLIENT_DIR, CODE_DIR
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with open(CLIENT_DIR / "qdrant_fastembed.py", "r") as source_file:
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code = source_file.read()
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generator = FastembedGenerator(
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keep_sync=[
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"__init__",
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"set_model",
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"set_sparse_model",
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"get_vector_field_name",
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"get_sparse_vector_field_name",
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"get_embedding_size",
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"get_fastembed_vector_params",
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"get_fastembed_sparse_vector_params",
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"embedding_model_name",
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"sparse_embedding_model_name",
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],
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class_replace_map={
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"QdrantBase": "AsyncQdrantBase",
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"QdrantFastembedMixin": "AsyncQdrantFastembedMixin",
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},
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import_replace_map={
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"qdrant_client.client_base": "qdrant_client.async_client_base",
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"QdrantBase": "AsyncQdrantBase",
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},
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)
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modified_code = generator.generate(code)
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with open(CODE_DIR / "async_qdrant_fastembed.py", "w") as target_file:
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target_file.write(modified_code)
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