重排器概述

在信息检索和生成式人工智能领域，重排序器是优化初始搜索结果排序的重要工具。重排器与传统的嵌入模型不同，它将查询和文档作为输入，直接返回相似度得分，而不是嵌入得分。该分数表示输入查询和文档之间的相关性。

Reranker 通常在第一阶段检索后使用，一般通过向量近似近邻（ANN）技术完成。虽然 ANN 检索能高效地获取大量潜在相关结果，但它们可能并不总是根据与查询的实际语义相关性来确定结果的优先级。在这种情况下，reerankers 通常利用先进的机器学习模型（如 BERT 或其他基于 Transformer 的模型），通过更深入的上下文分析来优化结果顺序。通过这样做，rerankers 可以显著提高最终呈现给用户的结果的准确性和相关性。

PyMilvus 模型库集成了 rerank 函数，用于优化初始搜索返回结果的顺序。从 Milvus 获取最近嵌入后，您可以利用这些重排工具来完善搜索结果，从而提高搜索结果的精确度。

重新排名功能	应用程序接口或开源
BGE	开源
交叉编码器	开源
航海	应用程序接口
Cohere	应用程序接口
Jina AI	API

示例 1：使用 BGE rerank 函数根据查询对文档进行重排

在本例中，我们将演示如何使用BGE reranker根据特定查询对搜索结果进行重新排序。

要使用带有PyMilvus 模型库的重排器，首先要安装 PyMilvus 模型库以及包含所有必要重排实用程序的模型子包：

pip install pymilvus[model]
# or pip install "pymilvus[model]" for zsh.

要使用 BGE reranker，首先要导入BGERerankFunction 类：

from pymilvus.model.reranker import BGERerankFunction

然后，创建一个BGERerankFunction 实例用于重排：

bge_rf = BGERerankFunction(
    model_name="BAAI/bge-reranker-v2-m3",  # Specify the model name. Defaults to `BAAI/bge-reranker-v2-m3`.
    device="cpu" # Specify the device to use, e.g., 'cpu' or 'cuda:0'
)

要根据查询对文档进行排序，请使用以下代码：

query = "What event in 1956 marked the official birth of artificial intelligence as a discipline?"

documents = [
    "In 1950, Alan Turing published his seminal paper, 'Computing Machinery and Intelligence,' proposing the Turing Test as a criterion of intelligence, a foundational concept in the philosophy and development of artificial intelligence.",
    "The Dartmouth Conference in 1956 is considered the birthplace of artificial intelligence as a field; here, John McCarthy and others coined the term 'artificial intelligence' and laid out its basic goals.",
    "In 1951, British mathematician and computer scientist Alan Turing also developed the first program designed to play chess, demonstrating an early example of AI in game strategy.",
    "The invention of the Logic Theorist by Allen Newell, Herbert A. Simon, and Cliff Shaw in 1955 marked the creation of the first true AI program, which was capable of solving logic problems, akin to proving mathematical theorems."
]

bge_rf(query, documents)

预期输出结果类似于下图：

[RerankResult(text="The Dartmouth Conference in 1956 is considered the birthplace of artificial intelligence as a field; here, John McCarthy and others coined the term 'artificial intelligence' and laid out its basic goals.", score=0.9911615761470803, index=1),
 RerankResult(text="In 1950, Alan Turing published his seminal paper, 'Computing Machinery and Intelligence,' proposing the Turing Test as a criterion of intelligence, a foundational concept in the philosophy and development of artificial intelligence.", score=0.0326971950177779, index=0),
 RerankResult(text='The invention of the Logic Theorist by Allen Newell, Herbert A. Simon, and Cliff Shaw in 1955 marked the creation of the first true AI program, which was capable of solving logic problems, akin to proving mathematical theorems.', score=0.006514905766152258, index=3),
 RerankResult(text='In 1951, British mathematician and computer scientist Alan Turing also developed the first program designed to play chess, demonstrating an early example of AI in game strategy.', score=0.0042116724917325935, index=2)]

例 2：使用排序器提高搜索结果的相关性

在本指南中，我们将探讨如何利用 PyMilvus 中的search() 方法进行相似性搜索，以及如何使用重排序器增强搜索结果的相关性。我们将使用以下数据集进行演示：

entities = [
    {'doc_id': 0, 'doc_vector': [-0.0372721,0.0101959,...,-0.114994], 'doc_text': "In 1950, Alan Turing published his seminal paper, 'Computing Machinery and Intelligence,' proposing the Turing Test as a criterion of intelligence, a foundational concept in the philosophy and development of artificial intelligence."}, 
    {'doc_id': 1, 'doc_vector': [-0.00308882,-0.0219905,...,-0.00795811], 'doc_text': "The Dartmouth Conference in 1956 is considered the birthplace of artificial intelligence as a field; here, John McCarthy and others coined the term 'artificial intelligence' and laid out its basic goals."}, 
    {'doc_id': 2, 'doc_vector': [0.00945078,0.00397605,...,-0.0286199], 'doc_text': 'In 1951, British mathematician and computer scientist Alan Turing also developed the first program designed to play chess, demonstrating an early example of AI in game strategy.'}, 
    {'doc_id': 3, 'doc_vector': [-0.0391119,-0.00880096,...,-0.0109257], 'doc_text': 'The invention of the Logic Theorist by Allen Newell, Herbert A. Simon, and Cliff Shaw in 1955 marked the creation of the first true AI program, which was capable of solving logic problems, akin to proving mathematical theorems.'}
]

数据集组件

• doc_id:每个文档的唯一标识符。
• doc_vector:代表文档的向量嵌入。有关生成嵌入的指导，请参阅嵌入。
• doc_text:文档的文本内容。

准备工作

在启动相似性搜索之前，您需要与 Milvus 建立连接，创建一个数据集，并准备和插入数据到该数据集中。以下代码片段说明了这些初步步骤。

from pymilvus import MilvusClient, DataType

client = MilvusClient(
    uri="http://10.102.6.214:19530" # replace with your own Milvus server address
)

client.drop_collection('test_collection')

# define schema

schema = client.create_schema(auto_id=False, enabel_dynamic_field=True)

schema.add_field(field_name="doc_id", datatype=DataType.INT64, is_primary=True, description="document id")
schema.add_field(field_name="doc_vector", datatype=DataType.FLOAT_VECTOR, dim=384, description="document vector")
schema.add_field(field_name="doc_text", datatype=DataType.VARCHAR, max_length=65535, description="document text")

# define index params

index_params = client.prepare_index_params()

index_params.add_index(field_name="doc_vector", index_type="IVF_FLAT", metric_type="IP", params={"nlist": 128})

# create collection

client.create_collection(collection_name="test_collection", schema=schema, index_params=index_params)

# insert data into collection

client.insert(collection_name="test_collection", data=entities)

# Output:
# {'insert_count': 4, 'ids': [0, 1, 2, 3]}

进行相似性搜索

插入数据后，使用search 方法执行相似性搜索。

# search results based on our query

res = client.search(
    collection_name="test_collection",
    data=[[-0.045217834, 0.035171617, ..., -0.025117004]], # replace with your query vector
    limit=3,
    output_fields=["doc_id", "doc_text"]
)

for i in res[0]:
    print(f'distance: {i["distance"]}')
    print(f'doc_text: {i["entity"]["doc_text"]}')

预期输出类似于下面的内容：

distance: 0.7235960960388184
doc_text: The Dartmouth Conference in 1956 is considered the birthplace of artificial intelligence as a field; here, John McCarthy and others coined the term 'artificial intelligence' and laid out its basic goals.
distance: 0.6269873976707458
doc_text: In 1950, Alan Turing published his seminal paper, 'Computing Machinery and Intelligence,' proposing the Turing Test as a criterion of intelligence, a foundational concept in the philosophy and development of artificial intelligence.
distance: 0.5340118408203125
doc_text: The invention of the Logic Theorist by Allen Newell, Herbert A. Simon, and Cliff Shaw in 1955 marked the creation of the first true AI program, which was capable of solving logic problems, akin to proving mathematical theorems.

使用检索器增强搜索结果

然后，通过重新排序步骤提高搜索结果的相关性。在本例中，我们使用 PyMilvus 内置的CrossEncoderRerankFunction 对结果进行重排，以提高准确性。

# use reranker to rerank search results

from pymilvus.model.reranker import CrossEncoderRerankFunction

ce_rf = CrossEncoderRerankFunction(
    model_name="cross-encoder/ms-marco-MiniLM-L-6-v2",  # Specify the model name.
    device="cpu" # Specify the device to use, e.g., 'cpu' or 'cuda:0'
)

reranked_results = ce_rf(
    query='What event in 1956 marked the official birth of artificial intelligence as a discipline?',
    documents=[
        "In 1950, Alan Turing published his seminal paper, 'Computing Machinery and Intelligence,' proposing the Turing Test as a criterion of intelligence, a foundational concept in the philosophy and development of artificial intelligence.",
        "The Dartmouth Conference in 1956 is considered the birthplace of artificial intelligence as a field; here, John McCarthy and others coined the term 'artificial intelligence' and laid out its basic goals.",
        "In 1951, British mathematician and computer scientist Alan Turing also developed the first program designed to play chess, demonstrating an early example of AI in game strategy.",
        "The invention of the Logic Theorist by Allen Newell, Herbert A. Simon, and Cliff Shaw in 1955 marked the creation of the first true AI program, which was capable of solving logic problems, akin to proving mathematical theorems."
    ],
    top_k=3
)

# print the reranked results
for result in reranked_results:
    print(f'score: {result.score}')
    print(f'doc_text: {result.text}')

预期的输出结果类似于下图：

score: 6.250532627105713
doc_text: The Dartmouth Conference in 1956 is considered the birthplace of artificial intelligence as a field; here, John McCarthy and others coined the term 'artificial intelligence' and laid out its basic goals.
score: -2.9546022415161133
doc_text: In 1950, Alan Turing published his seminal paper, 'Computing Machinery and Intelligence,' proposing the Turing Test as a criterion of intelligence, a foundational concept in the philosophy and development of artificial intelligence.
score: -4.771512031555176
doc_text: The invention of the Logic Theorist by Allen Newell, Herbert A. Simon, and Cliff Shaw in 1955 marked the creation of the first true AI program, which was capable of solving logic problems, akin to proving mathematical theorems.