Recall, understand, and extract data from chat histories. Power personalized AI experiences.
Zep is a long-term memory service for AI Assistant apps. With Zep, you can provide AI assistants with the ability to recall past conversations, no matter how distant, while also reducing hallucinations, latency, and cost.
Interested in Zep Cloud? See Zep Cloud Installation Guide and Zep Cloud Vector Store example
Open Source Installation and Setup
Zep Open Source project: https://github.com/getzep/zep Zep Open Source Docs: https://docs.getzep.com/You’ll need to install
langchain-community
with pip install -qU langchain-community
to use this integration Usage
In the examples below, we’re using Zep’s auto-embedding feature which automatically embeds documents on the Zep server using low-latency embedding models.Note
- These examples use Zep’s async interfaces. Call sync interfaces by removing the
a
prefix from the method names. - If you pass in an
Embeddings
instance Zep will use this to embed documents rather than auto-embed them. You must also set your document collection toisAutoEmbedded === false
. - If you set your collection to
isAutoEmbedded === false
, you must pass in anEmbeddings
instance.
Load or create a Collection from documents
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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 )
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# 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)
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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
Simarility Search Query over the Collection
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# 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")
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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 ====
Search over Collection Re-ranked by MMR
Zep offers native, hardware-accelerated MMR re-ranking of search results.Copy
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")
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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 ====
Filter by Metadata
Use a metadata filter to narrow down results. First, load another book: “Adventures of Sherlock Holmes”Copy
# 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)
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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
source
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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")
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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'} ====
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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")
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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'} ====