如何重新排序检索结果以缓解“中间丢失”效应

随着检索到的文档数量的增加（例如，超过十个），RAG 应用程序中出现了记录在案的重大性能下降。简而言之：模型容易错过长上下文中间的相关信息。

相比之下，针对向量存储的查询通常会按相关性降序返回文档（例如，按嵌入的余弦相似度衡量）。

为了缓解“中间丢失”效应，您可以在检索后重新排序文档，以便最相关的文档位于极值（例如，上下文的开头和结尾），而最不相关的文档位于中间。在某些情况下，这可以帮助向 LLM 提供最相关的信息。

LongContextReorder 文档转换器实现了此重新排序过程。下面我们演示一个示例。

%pip install --upgrade --quiet  sentence-transformers langchain-chroma langchain langchain-openai langchain-huggingface > /dev/null

首先，我们将一些人工文档嵌入并将其索引到 (内存中) Chroma 向量存储中。我们将使用 Hugging Face 嵌入，但任何 LangChain 向量存储或嵌入模型都可以。

from langchain_chroma import Chroma
from langchain_huggingface import HuggingFaceEmbeddings

# Get embeddings.
embeddings = HuggingFaceEmbeddings(model_name="all-MiniLM-L6-v2")

texts = [
    "Basquetball is a great sport.",
    "Fly me to the moon is one of my favourite songs.",
    "The Celtics are my favourite team.",
    "This is a document about the Boston Celtics",
    "I simply love going to the movies",
    "The Boston Celtics won the game by 20 points",
    "This is just a random text.",
    "Elden Ring is one of the best games in the last 15 years.",
    "L. Kornet is one of the best Celtics players.",
    "Larry Bird was an iconic NBA player.",
]

# Create a retriever
retriever = Chroma.from_texts(texts, embedding=embeddings).as_retriever(
    search_kwargs={"k": 10}
)
query = "What can you tell me about the Celtics?"

# Get relevant documents ordered by relevance score
docs = retriever.invoke(query)
docs

API 参考：HuggingFaceEmbeddings

[Document(page_content='This is a document about the Boston Celtics'),
 Document(page_content='The Celtics are my favourite team.'),
 Document(page_content='L. Kornet is one of the best Celtics players.'),
 Document(page_content='The Boston Celtics won the game by 20 points'),
 Document(page_content='Larry Bird was an iconic NBA player.'),
 Document(page_content='Elden Ring is one of the best games in the last 15 years.'),
 Document(page_content='Basquetball is a great sport.'),
 Document(page_content='I simply love going to the movies'),
 Document(page_content='Fly me to the moon is one of my favourite songs.'),
 Document(page_content='This is just a random text.')]

请注意，文档按与查询的相关性降序返回。LongContextReorder 文档转换器将实现上面描述的重新排序

from langchain_community.document_transformers import LongContextReorder

# Reorder the documents:
# Less relevant document will be at the middle of the list and more
# relevant elements at beginning / end.
reordering = LongContextReorder()
reordered_docs = reordering.transform_documents(docs)

# Confirm that the 4 relevant documents are at beginning and end.
reordered_docs

API 参考：LongContextReorder

[Document(page_content='The Celtics are my favourite team.'),
 Document(page_content='The Boston Celtics won the game by 20 points'),
 Document(page_content='Elden Ring is one of the best games in the last 15 years.'),
 Document(page_content='I simply love going to the movies'),
 Document(page_content='This is just a random text.'),
 Document(page_content='Fly me to the moon is one of my favourite songs.'),
 Document(page_content='Basquetball is a great sport.'),
 Document(page_content='Larry Bird was an iconic NBA player.'),
 Document(page_content='L. Kornet is one of the best Celtics players.'),
 Document(page_content='This is a document about the Boston Celtics')]

下面，我们将展示如何将重新排序后的文档整合到一个简单的问答链中。

from langchain.chains.combine_documents import create_stuff_documents_chain
from langchain_core.prompts import PromptTemplate
from langchain_openai import OpenAI

llm = OpenAI()

prompt_template = """
Given these texts:
-----
{context}
-----
Please answer the following question:
{query}
"""

prompt = PromptTemplate(
    template=prompt_template,
    input_variables=["context", "query"],
)

# Create and invoke the chain:
chain = create_stuff_documents_chain(llm, prompt)
response = chain.invoke({"context": reordered_docs, "query": query})
print(response)

API 参考：create_stuff_documents_chain | PromptTemplate | OpenAI

The Celtics are a professional basketball team and one of the most iconic franchises in the NBA. They are highly regarded and have a large fan base. The team has had many successful seasons and is often considered one of the top teams in the league. They have a strong history and have produced many great players, such as Larry Bird and L. Kornet. The team is based in Boston and is often referred to as the Boston Celtics.