Zep

从聊天记录中回忆、理解和提取数据。增强个性化 AI 体验。

Zep 是一种用于 AI 助手应用程序的长期记忆服务。使用 Zep，您可以为 AI 助手提供回忆过去对话的能力，无论对话有多久远，同时还能减少幻觉、延迟和成本。

有兴趣了解 Zep Cloud？请参阅Zep Cloud 安装指南和Zep Cloud 向量存储示例

开源安装和设置

Zep 开源项目：https://github.com/getzep/zep
Zep 开源文档：https://docs.getzep.com/

您需要使用 pip install -qU langchain-community 安装 langchain-community 才能使用此集成。

用法

在下面的示例中，我们使用 Zep 的自动嵌入功能，该功能使用低延迟嵌入模型自动在 Zep 服务器上嵌入文档。

注意

这些示例使用 Zep 的异步接口。通过从方法名称中删除 a 前缀来调用同步接口。
如果您传入 Embeddings 实例，Zep 将使用它来嵌入文档，而不是自动嵌入它们。您还必须将文档集合设置为 isAutoEmbedded === false。
如果您将集合设置为 isAutoEmbedded === false，则必须传入 Embeddings 实例。

从文档加载或创建集合

from uuid import uuid4

from langchain_community.document_loaders import WebBaseLoader
from langchain_community.vectorstores import ZepVectorStore
from langchain_community.vectorstores.zep import CollectionConfig
from langchain_text_splitters import RecursiveCharacterTextSplitter

ZEP_API_URL = "http://localhost:8000"  # this is the API url of your Zep instance
ZEP_API_KEY = "<optional_key>"  # optional API Key for your Zep instance
collection_name = f"babbage{uuid4().hex}"  # a unique collection name. alphanum only

# Collection config is needed if we're creating a new Zep Collection
config = CollectionConfig(
    name=collection_name,
    description="<optional description>",
    metadata={"optional_metadata": "associated with the collection"},
    is_auto_embedded=True,  # we'll have Zep embed our documents using its low-latency embedder
    embedding_dimensions=1536,  # this should match the model you've configured Zep to use.
)

# load the document
article_url = "https://www.gutenberg.org/cache/epub/71292/pg71292.txt"
loader = WebBaseLoader(article_url)
documents = loader.load()

# split it into chunks
text_splitter = RecursiveCharacterTextSplitter(chunk_size=500, chunk_overlap=0)
docs = text_splitter.split_documents(documents)

# Instantiate the VectorStore. Since the collection does not already exist in Zep,
# it will be created and populated with the documents we pass in.
vs = ZepVectorStore.from_documents(
    docs,
    collection_name=collection_name,
    config=config,
    api_url=ZEP_API_URL,
    api_key=ZEP_API_KEY,
    embedding=None,  # we'll have Zep embed our documents using its low-latency embedder
)

API 参考：WebBaseLoader | ZepVectorStore | CollectionConfig | RecursiveCharacterTextSplitter

# wait for the collection embedding to complete


async def wait_for_ready(collection_name: str) -> None:
    import time

    from zep_python import ZepClient

    client = ZepClient(ZEP_API_URL, ZEP_API_KEY)

    while True:
        c = await client.document.aget_collection(collection_name)
        print(
            "Embedding status: "
            f"{c.document_embedded_count}/{c.document_count} documents embedded"
        )
        time.sleep(1)
        if c.status == "ready":
            break


await wait_for_ready(collection_name)

Embedding status: 0/401 documents embedded
Embedding status: 0/401 documents embedded
Embedding status: 0/401 documents embedded
Embedding status: 0/401 documents embedded
Embedding status: 0/401 documents embedded
Embedding status: 0/401 documents embedded
Embedding status: 401/401 documents embedded

对集合进行相似性搜索查询

# query it
query = "what is the structure of our solar system?"
docs_scores = await vs.asimilarity_search_with_relevance_scores(query, k=3)

# print results
for d, s in docs_scores:
    print(d.page_content, " -> ", s, "\n====\n")

the positions of the two principal planets, (and these the most
necessary for the navigator,) Jupiter and Saturn, require each not less
than one hundred and sixteen tables. Yet it is not only necessary to
predict the position of these bodies, but it is likewise expedient to
tabulate the motions of the four satellites of Jupiter, to predict the
exact times at which they enter his shadow, and at which their shadows
cross his disc, as well as the times at which they are interposed  ->  0.9003241539387915 
====

furnish more than a small fraction of that aid to navigation (in the
large sense of that term), which, with greater facility, expedition, and
economy in the calculation and printing of tables, it might be made to
supply.

Tables necessary to determine the places of the planets are not less
necessary than those for the sun, moon, and stars. Some notion of the
number and complexity of these tables may be formed, when we state that  ->  0.8911165633479508 
====

the scheme of notation thus applied, immediately suggested the
advantages which must attend it as an instrument for expressing the
structure, operation, and circulation of the animal system; and we
entertain no doubt of its adequacy for that purpose. Not only the
mechanical connexion of the solid members of the bodies of men and
animals, but likewise the structure and operation of the softer parts,
including the muscles, integuments, membranes, &c. the nature, motion,  ->  0.8899750214770481 
====

通过 MMR 对集合进行重排序的搜索

Zep 提供了对搜索结果进行本地硬件加速的 MMR 重排序。

query = "what is the structure of our solar system?"
docs = await vs.asearch(query, search_type="mmr", k=3)

for d in docs:
    print(d.page_content, "\n====\n")

the positions of the two principal planets, (and these the most
necessary for the navigator,) Jupiter and Saturn, require each not less
than one hundred and sixteen tables. Yet it is not only necessary to
predict the position of these bodies, but it is likewise expedient to
tabulate the motions of the four satellites of Jupiter, to predict the
exact times at which they enter his shadow, and at which their shadows
cross his disc, as well as the times at which they are interposed 
====

the scheme of notation thus applied, immediately suggested the
advantages which must attend it as an instrument for expressing the
structure, operation, and circulation of the animal system; and we
entertain no doubt of its adequacy for that purpose. Not only the
mechanical connexion of the solid members of the bodies of men and
animals, but likewise the structure and operation of the softer parts,
including the muscles, integuments, membranes, &c. the nature, motion, 
====

resistance, economizing time, harmonizing the mechanism, and giving to
the whole mechanical action the utmost practical perfection.

The system of mechanical contrivances by which the results, here
attempted to be described, are attained, form only one order of
expedients adopted in this machinery;--although such is the perfection
of their action, that in any ordinary case they would be regarded as
having attained the ends in view with an almost superfluous degree of 
====

按元数据筛选

使用元数据过滤器缩小结果范围。首先，加载另一本书：“夏洛克·福尔摩斯的冒险”

# Let's add more content to the existing Collection
article_url = "https://www.gutenberg.org/files/48320/48320-0.txt"
loader = WebBaseLoader(article_url)
documents = loader.load()

# split it into chunks
text_splitter = RecursiveCharacterTextSplitter(chunk_size=500, chunk_overlap=0)
docs = text_splitter.split_documents(documents)

await vs.aadd_documents(docs)

await wait_for_ready(collection_name)

Embedding status: 401/1691 documents embedded
Embedding status: 401/1691 documents embedded
Embedding status: 401/1691 documents embedded
Embedding status: 401/1691 documents embedded
Embedding status: 401/1691 documents embedded
Embedding status: 401/1691 documents embedded
Embedding status: 901/1691 documents embedded
Embedding status: 901/1691 documents embedded
Embedding status: 901/1691 documents embedded
Embedding status: 901/1691 documents embedded
Embedding status: 901/1691 documents embedded
Embedding status: 901/1691 documents embedded
Embedding status: 1401/1691 documents embedded
Embedding status: 1401/1691 documents embedded
Embedding status: 1401/1691 documents embedded
Embedding status: 1401/1691 documents embedded
Embedding status: 1691/1691 documents embedded

我们看到了两本书的结果。请注意 source 元数据

query = "Was he interested in astronomy?"
docs = await vs.asearch(query, search_type="similarity", k=3)

for d in docs:
    print(d.page_content, " -> ", d.metadata, "\n====\n")

or remotely, for this purpose. But in addition to these, a great number
of tables, exclusively astronomical, are likewise indispensable. The
predictions of the astronomer, with respect to the positions and motions
of the bodies of the firmament, are the means, and the only means, which
enable the mariner to prosecute his art. By these he is enabled to
discover the distance of his ship from the Line, and the extent of his  ->  {'source': 'https://www.gutenberg.org/cache/epub/71292/pg71292.txt'} 
====

possess all knowledge which is likely to be useful to him in his work,
and this I have endeavored in my case to do. If I remember rightly, you
on one occasion, in the early days of our friendship, defined my limits
in a very precise fashion.”

“Yes,” I answered, laughing. “It was a singular document. Philosophy,
astronomy, and politics were marked at zero, I remember. Botany
variable, geology profound as regards the mud-stains from any region  ->  {'source': 'https://www.gutenberg.org/files/48320/48320-0.txt'} 
====

of astronomy, and its kindred sciences, with the various arts dependent
on them. In none are computations more operose than those which
astronomy in particular requires;--in none are preparatory facilities
more needful;--in none is error more detrimental. The practical
astronomer is interrupted in his pursuit, and diverted from his task of
observation by the irksome labours of computation, or his diligence in
observing becomes ineffectual for want of yet greater industry of  ->  {'source': 'https://www.gutenberg.org/cache/epub/71292/pg71292.txt'} 
====

现在，我们设置一个过滤器

filter = {
    "where": {
        "jsonpath": (
            "$[*] ? (@.source == 'https://www.gutenberg.org/files/48320/48320-0.txt')"
        )
    },
}

docs = await vs.asearch(query, search_type="similarity", metadata=filter, k=3)

for d in docs:
    print(d.page_content, " -> ", d.metadata, "\n====\n")

possess all knowledge which is likely to be useful to him in his work,
and this I have endeavored in my case to do. If I remember rightly, you
on one occasion, in the early days of our friendship, defined my limits
in a very precise fashion.”

“Yes,” I answered, laughing. “It was a singular document. Philosophy,
astronomy, and politics were marked at zero, I remember. Botany
variable, geology profound as regards the mud-stains from any region  ->  {'source': 'https://www.gutenberg.org/files/48320/48320-0.txt'} 
====

the light shining upon his strong-set aquiline features. So he sat as I
dropped off to sleep, and so he sat when a sudden ejaculation caused me
to wake up, and I found the summer sun shining into the apartment. The
pipe was still between his lips, the smoke still curled upward, and the
room was full of a dense tobacco haze, but nothing remained of the heap
of shag which I had seen upon the previous night.

“Awake, Watson?” he asked.

“Yes.”

“Game for a morning drive?”  ->  {'source': 'https://www.gutenberg.org/files/48320/48320-0.txt'} 
====

“I glanced at the books upon the table, and in spite of my ignorance
of German I could see that two of them were treatises on science, the
others being volumes of poetry. Then I walked across to the window,
hoping that I might catch some glimpse of the country-side, but an oak
shutter, heavily barred, was folded across it. It was a wonderfully
silent house. There was an old clock ticking loudly somewhere in the
passage, but otherwise everything was deadly still. A vague feeling of  ->  {'source': 'https://www.gutenberg.org/files/48320/48320-0.txt'} 
====

向量存储概念指南
向量存储操作指南

Zep

开源安装和设置

用法

注意

从文档加载或创建集合

对集合进行相似性搜索查询

通过 MMR 对集合进行重排序的搜索

按元数据筛选

此页面是否有帮助？

您还可以留下详细的反馈在 GitHub 上.

Zep

开源安装和设置​

用法​

注意​

从文档加载或创建集合​

对集合进行相似性搜索查询​

通过 MMR 对集合进行重排序的搜索​

按元数据筛选

相关​

此页面是否有帮助？

您还可以留下详细的反馈 在 GitHub 上.

开源安装和设置

用法

注意

从文档加载或创建集合

对集合进行相似性搜索查询

通过 MMR 对集合进行重排序的搜索

相关

您还可以留下详细的反馈在 GitHub 上.