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Zep 云

从聊天记录中回忆、理解和提取数据。增强个性化的 AI 体验。

Zep 是一个用于 AI 助手应用程序的长期记忆服务。借助 Zep,您可以为 AI 助手提供回忆过去对话的能力,无论对话时间间隔多长,同时减少幻觉、延迟和成本。

参见 Zep Cloud 安装指南

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在 Zep 服务器上自动嵌入文档。

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。

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 ZepCloudVectorStore
from langchain_text_splitters import RecursiveCharacterTextSplitter

ZEP_API_KEY = "<your zep project key>" # You can generate your zep project key from the Zep dashboard
collection_name = f"babbage{uuid4().hex}" # a unique collection name. alphanum only

# 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 = ZepCloudVectorStore.from_documents(
docs,
embedding=None,
collection_name=collection_name,
api_key=ZEP_API_KEY,
)
# wait for the collection embedding to complete


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

from zep_cloud.client import AsyncZep

client = AsyncZep(api_key=ZEP_API_KEY)

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


await wait_for_ready(collection_name)
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 -> 0.78691166639328
====

are reduced to a system of wheel-work. We are, nevertheless, not without
hopes of conveying, even to readers unskilled in mathematics, some
satisfactory notions of a general nature on this subject.

_Thirdly_, To explain the actual state of the machinery at the present
time; what progress has been made towards its completion; and what are
the probable causes of those delays in its progress, which must be a
subject of regret to all friends of science. We shall indicate what -> 0.7853284478187561
====

from the improved state of astronomy, he found it necessary to recompute
these tables in 1821.

Although it is now about thirty years since the discovery of the four
new planets, Ceres, Pallas, Juno, and Vesta, it was not till recently
that tables of their motions were published. They have lately appeared
in Encke's Ephemeris.

We have thus attempted to convey some notion (though necessarily a very
inadequate one) of the immense extent of numerical tables which it has -> 0.7840130925178528
====

通过 MMR 对集合进行重新排序后的搜索

Zep 提供对搜索结果的原生硬件加速 MMR 重新排序功能。

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
====

are reduced to a system of wheel-work. We are, nevertheless, not without
hopes of conveying, even to readers unskilled in mathematics, some
satisfactory notions of a general nature on this subject.

_Thirdly_, To explain the actual state of the machinery at the present
time; what progress has been made towards its completion; and what are
the probable causes of those delays in its progress, which must be a
subject of regret to all friends of science. We shall indicate what
====

general commerce. But the science in which, above all others, the most
extensive and accurate tables are indispensable, is Astronomy; with the
improvement and perfection of which is inseparably connected that of the
kindred art of Navigation. We scarcely dare hope to convey to the
general reader any thing approaching to an adequate notion of the
multiplicity and complexity of the tables necessary for the purposes of
the astronomer and navigator. We feel, nevertheless, that the truly
====

按元数据筛选

使用元数据筛选器缩小结果范围。首先,加载另一本书:“福尔摩斯探案集”。

# 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)
Adding documents
generated documents 1290
added documents ['ddec2883-5776-47be-a7bc-23e851e969a9', '19d2a5ce-0a36-4d32-b522-2a54a69970e8', '5e6d8ed2-4527-4515-9557-f178b2682df8', 'ad2b04d9-e1f1-4d90-9920-ab6d95c63dd7', '19871eb4-b624-49d1-a160-a24487298ac6', '19e9e04b-6b3f-4a91-9717-1565a5065642', '0e9a6411-a6a6-4453-a655-2a251519a1fa', '51de5926-dbb1-4d58-b6d4-47c8e5988042', '244dc860-2bf0-41a1-aa3c-e170c0209c5a', '175e8811-70cd-499c-a35f-2502749bff2e', '5298951a-1087-45f4-afff-3466032301fc', 'd87f4495-95c9-4152-bf1b-90f73652e639', '638f6b85-1e05-462f-8c75-4c642a309d88', '92f7f430-9ffc-4ca5-ac92-953793a4a7b0', '5ce532f2-86b0-4953-8815-96b7fb0da046', '8187857a-02b6-4faa-80b3-ca6d64b0ae59', '599d479c-7c2e-4ad9-b5e4-651fced1f38c', 'e0869e51-92a5-4c87-ba35-a977c3fe43d2', 'bed376d9-3785-4fa3-a986-4d069e817a0e', '31e8e7b1-164b-4872-8a21-0a417d9c2793', '87f96ecb-c78a-4aaf-a976-557a76adecf1', '8f0e7eb2-fb67-4010-bec4-70f1ea319d22', '5d280424-00cc-475c-8334-3ac1dbda84c9', 'a27876c9-68c2-460c-bce1-43cbc734885a', '492fe1fc-0dc8-45ee-a343-3fc514014298', '964a4887-0a21-442b-8677-9568c8ea5b4a', '87b82a96-c981-454e-87f6-171cbaa90e20', '14014728-1617-4ff5-8f56-b2cbcdf08bcf', 'af95852d-e7ce-4db7-9b47-3cfbffcfd81b', '1f6526bf-f5a9-4a1a-9a9f-42e6d175d9d5', '0a214058-d318-4f75-a413-140a4bdbc55f', '0eee06d6-d7e0-4097-8231-af823635f786', '7e74bdc5-f42f-474e-8c3d-0a346227f1e6', 'c8959f06-5282-47e8-92fe-16a90bb20132', 'd895bdcb-b7d1-40fe-a9a8-92647630688a', 'ebb30286-4eba-4733-94c7-f2e92cfcd0a3', '02c87eb9-031d-44bc-ad9a-c3b07b6d879c', '5338e6e3-ebfd-42b9-ba71-4eb728a9aba0', 'b372dba5-f1e7-4cff-9ba2-17132b51423d', 'bad22837-aba8-4431-a742-e1642abdc1d3', 'e73f3146-9ac1-4517-8905-45ba31de1551', '6903a3cb-acb1-42cd-9653-b208487368e9', '92600304-7eb9-4a6f-9a27-ba14a28fc636', '44e720af-efcf-477a-a655-08967ff3159a', '61565e97-7aa5-4c8c-a330-86ba265824d6', 'de10ad67-1992-4c85-8112-c1a2cd93edc0', '103d4a40-789a-4797-ad86-e50b2efe93e8', 'a5940a28-a9db-435c-b3c2-3485fafba55a', '637475cc-9a54-4ced-ab03-4a5dddb1e152', 'b209df0d-6513-4a74-b0ea-7bb2b2e01c4b', 'e6ee7511-eec8-4b20-94b1-e338093c9760', 'ef4ceb0d-a990-4cc2-91ed-320e1552c98d', '8058b68a-7ce5-4fb9-9f89-ed1c9e04b60e', 'ddebdfe0-87c1-4c4f-9d1f-fdc32b6bd5e2', '5211afd6-3076-40ec-b964-8c4a165b6e3d', 'ac5e9a17-ff57-4885-b3b7-4229d09a2077', 'fcea3094-7d86-4c05-9780-5c894197b65a', '81b0bdd9-5be6-4b95-89db-fe737446512a', '68f42964-0c21-4409-8356-067bbc5eddb0', '28b3dbc4-3b5f-4a7e-9906-b34a30832384', '83a15ca3-b54b-449a-813b-76db3e1f11ea', '1fd0d950-e1e3-4c5a-b62c-487ed11e06ac', '70253ef9-e4c3-4f9e-aa51-18b2b067d2d5', 'f5538e25-1e4e-438f-b1ef-ebc359085df8', '643e6f1e-b5dd-4630-9e30-f323abff5261', 'ef370f62-6a99-4116-9843-ad3f36ca0779', '915d4b2b-5467-4398-ab65-369250ca1245', '830c873a-eb80-40f9-9f6b-92f3b7be4f19', 'a965a589-8717-43d0-9419-7e8fefda070d', 'd686b00b-f91c-4d80-ae4d-5e2b6c227c86', '264951a6-5788-4a22-b925-758bcf0c499e', '32227ea1-1aa6-470c-9148-911c3fdda203', '97474d19-ef5d-4f14-8ffd-09d68bf5960a', '71fc221f-0048-4fbd-a68e-7c40885e091c', 'ef7a0a8c-16fd-4a2a-8d70-0fbf086b312e', 'fae9bea0-9815-4495-87a6-72700c728e71', '3cafc749-c648-477f-9b3d-33eacddc42aa', '31756e9d-993d-4653-b521-ef5cd653ab3a', '6c9b28ad-adde-4055-87f4-e34c387ab607', 'dfddcef4-9229-4c2c-9deb-6533f6c87bfe', '0511f770-041c-405d-a9f0-5e9a2c62563e', 'e9e8f9b2-1879-4528-bc72-1318bd026f53', 'dbcc7682-cf0e-49db-998c-d581df5cc0b9', '95c3a979-92fd-4268-9b1f-36f526fb1115', 'fb602a32-87c2-4fa1-9e15-8d69fd780baf', '163489b5-20a9-4eba-a9cc-660c7d5c0d21', 'beef4aaa-7eed-4dec-a953-de40a20efc9e', 'c61782a0-184b-43c7-a232-772087bdafa1', 'acf045d9-c43d-4e16-87d1-93b142bd3c3a', 'bb014519-b473-4329-8045-7dbe33200c34', 'ecb12661-86b1-47f7-a4e8-6854beedbe46', 'c2450f1b-593f-4b8f-ba80-ec56bcf802ae', 'bc47a6b4-8a4b-4e0a-9fd2-a9999d0c6c74', '3f2581c2-1c91-4e57-830b-a08cd7b09f9f', '4441431d-d3be-49f5-bf07-d415baced24d', 'bcd90088-0313-4647-a83d-673e470565a0', '3949bacf-8bb5-451d-81f4-f902f2fe8aca', '7925ac14-5ce2-4717-afcb-86da4ec6f933', 'ddbb242d-c914-4608-97c0-d3c5ae817a15', '7c351dfc-8f19-4a49-9a65-b79b5ed8aa07', '65db2c1b-36e1-4b38-8d28-554c37f1c897', '5674788e-a430-4706-9801-cae72ce45763', 'd59612f3-2a65-489a-87fd-27123d8258c0', 'd62368e3-7e43-454d-b5fb-b4e2f37badab', '55a71614-29b6-44ba-ba64-b6444bbb432a', 'f03f605b-3770-48d8-8e96-6b3fb7915ea5', 'a51f8dd4-883a-4bbd-92b2-34581756f341', '6993ea75-5ebe-4aff-be14-3efb9107f616', '99501367-dc36-4589-97a0-0cc9e066c042', '7a5e56c8-48d6-42ee-8a8e-431b31669d98', 'b5394c35-0112-4fc5-9336-3c614d2326d4', '8be29e49-a2c3-4a0a-bc3e-99b74000f834', 'b714564c-8f18-4d0d-b530-cdc593dc4914', '0c93f74d-b20e-41b6-a9dc-709717bfe168', '51ce05f9-40c4-4d12-96ac-9245402a49c8', 'c18e4c15-edbe-4a78-98d2-2979d69b1ebf', 'c3dc5265-f1c2-4057-8408-a3a2ee71f77f', '9dc4d84e-6f47-4516-8173-3dded3aad48a', '36b19b4c-c846-456b-b7ce-76aee21c3783', '74a69f64-0b90-439a-82e8-245063711c13', '11ef7bc0-ac49-4368-ba83-6126d3eae999', '60afad3c-4c1f-4968-800d-6493338be615', '3d44d417-d82c-44e3-aae7-431f920974d9', '2448df31-e100-494f-abea-5815adf0fa5a', 'f654ee44-45b2-48c3-b1d7-5b80420d680f', '454bd226-0d6b-40a2-b0a0-a2de2a6aa8d4', 'd728840f-8f90-4c83-9329-268921bc92b4', '404234bb-5592-425e-b3c5-d391bcdc5f15', '9cab7401-f7b6-4379-81d0-100aa1cd4ab2', 'adde751f-d319-4534-9100-c8a1c4f04729', '54b173cb-80f0-46c8-bdcc-4d56fd38a6fe', 'bc3555da-1e7b-4248-bf4d-2229520b75f5', 'cf8fa6c5-63cf-43e2-a577-c6eb083c1f81', 'bf1f2c37-9c67-4478-83be-952611c14771', 'ea2d5b80-7dfd-4655-b1a8-0f6f235ac818', '6837c567-092c-4568-bb33-6f8b0a1acfd0', 'cb834e5e-222b-45ed-b2e7-339803e8825c', '37e9723d-263f-47d7-8ce3-27fabba84c7e', 'b63e0f9d-c463-4d03-84e4-66abf9e2f2ed', '2b57cad2-795d-47c6-be27-9566fa63794d', '81807f59-2354-48f8-b78c-296b20cf5586', '15459589-637e-44a5-b2a4-cbb94f2b4176', '29dd752c-2802-4806-8f97-2518fae5bcc5', '424c81bc-f21a-4646-a3fa-12f5694d828e', '398253e5-c4b3-4784-a60a-010e8b289d59', 'e43dd183-64b5-4821-b0f0-e5f759d3e974', '09bdc512-544b-42ef-80a9-2122d217bf8e', '27117536-c539-4eb5-8c67-f090a230f0c3', 'd68e3696-4a01-43ea-b763-d592eed48152', '8c771c9d-6596-479d-9572-0bf5141496f1', 'df39063a-62ad-4331-96fc-c1f064042bf8', 'a4357878-5a22-4b48-bbf0-ba9b19d6003e', '054a4f9c-6237-4624-ba55-a6d4dde70f33', '5ffdfff1-8379-4187-9ab3-8e33367855c2', '57f51416-cec0-437c-8e75-8c53b16a1e1d', 'ad030ad5-0b65-4160-8f7f-4d4aa04df8bb', '2350031c-86db-4926-baef-4337fdf0f501', '194a3bdd-5f37-4056-877f-e3a9f14e717b', 'c5ce3142-2dbc-4284-9a1b-6a82f17496b0', 'e86823b9-bdb3-4d1a-b929-8ec5ea69fb3a', '5c2913ed-c4e2-4fe0-81ff-406bb9b452ad', 'b2c7b0b9-5288-4000-89d7-43c1c21179bf', 'bd1e3aac-bf70-45c0-a519-91556bdeb3ec', '3b63324c-96ed-4d6d-bac7-a611fdbe4eef', '670050eb-6956-47a2-8fc0-a297c1cc5cb0', '53874ec0-1513-4603-a805-23433947b10a', 'd31c0999-46ea-4d4f-a60b-b3290931efe6', '39d99205-5de0-4234-b846-9758e67eb02b', 'aae705a4-9398-4068-90f5-59ae5569894f', '2d4e003e-ab3d-4759-b5bc-681d5b082f92', '67cd305c-7f2d-4847-8e0f-5cfb6708db8b', 'b5314a0a-57ea-4e7a-a47f-eccf626c2370', 'a5e7a9a7-824b-4622-8b55-8cbdfd5a0d00', '818cd68e-6f21-431c-9bb6-c7e03aa07327', 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'cc14bfda-e671-45cd-92f9-726e3af73a75', 'f6a2bbb2-41aa-4535-98ef-fa2bc6690553', '0af5f6ba-88a0-429e-ab34-eda507ab7b2b', 'b50a6077-62dd-4370-838d-4504e756ec76', '4e46ecc8-95f4-4e71-8546-7eff67aa9674', 'f9cc3e05-a4e0-47d8-8f85-c536944550dd', '76cf6789-64f3-440e-83d3-ea3a785a5f18', '1ff7f628-9d32-4da8-ad05-5157f21941b4', '819f5622-c337-499d-a5fd-09a6645a0bac', 'c20836de-ba7b-4848-b301-02f9ee73c2c4', '654a3768-44be-4085-97b3-b0c81c5b1e25', '6078246d-c76f-473b-aa53-aa9811d85202', 'e39365be-501f-4175-8b96-7bc21822038b', '92d48f92-0ab0-4295-b566-020041776d81', '3ef430ae-20ea-4b90-b4e4-7a147feb538e', 'f0eaf582-15e0-4f4c-ad11-a238903e3398', '72fac284-ba6a-49fd-9c64-360e7916882f', 'd27abf6f-ba69-499f-b16d-aaf4977976c9', 'b647b47c-7ce3-4d07-ac00-04f19aeb813f', 'c870e45e-e8cf-4428-94e8-a6e445da34c9', '711f7051-020c-480c-8eb1-3e134684a53a', '0eb793d1-1ba9-4bd7-8266-e25a5293b290', '370765bb-1578-4b2d-a525-9b68eacb5d3d', '2b7f2ba9-d96b-4929-afc3-aca3d6815ff4', 'a017a9e9-7486-466d-be7f-86204f271ac6', '049f12de-f88b-4053-8f33-b0d2de666717', '8f465387-28a7-484d-bf80-63678548df43', 'a253ed92-8cce-4781-a737-25713b56d0f6', '6dbf6270-19ad-44d8-adb5-2afacbef528c', 'b75162b1-6df6-4307-ae15-5cd999c3f293', '4317f253-649d-4453-a2e2-33cc114b8d20', '45570cc0-6b65-4920-9cc0-2c8cc404cfd8', '84d7db8a-7bf4-4c5a-97a1-92079a5d3827', '2060d9f8-f893-44bf-8b10-1147abdd770e', '20b67577-5a56-44a4-8cd7-ca222f3ffe1e', '98f5e175-ea55-4f9a-a8e3-57f5e72c2b99', 'bdfd2ff2-bdaf-4b2a-93f9-f6059c48543d', '0931c0f2-a490-44e7-94e9-e697a8f14a25', '0c415312-f2c7-4cb7-8b0c-610e6022cebe', 'e99e6197-c87d-4997-9c1a-a7a773cd16a6', '7cb530a2-6707-44d4-8230-f6350eec6633', '662fc59e-1650-4f10-af4e-f517069299af', '68301a90-9ca9-4e35-b650-89e40cd83381', 'bd31a7c5-dc58-491f-9d46-a7e33df609a0', '2af17dee-840b-48b7-97ce-58ee3c30c636', '6b750930-cb18-4f47-b973-b3ae83a5670d', 'ac5a81a2-b1e7-48f7-8660-11d2ee4a8155', 'b5f8fdeb-b540-4698-9e80-5465aaa457dd', '78722194-4664-4d77-8049-55ab29c52019', 'ea956d74-6d2d-4c13-92d8-bc6dbbfb99b6', '1ebb6bce-9e77-43dc-ac99-25f473684dea', '3164e884-dbd6-4997-bc1f-7d7021d18621', '05a75e45-2205-4c6b-8848-de79593dd773', 'ce158a73-2efe-4176-925b-7cb31ee29eb1', 'e8aac383-e775-4c8f-9e71-dc83f1fdba72', '25a69d4e-393b-434e-8c31-595d65fb5ffa', '7cbe17cd-26e6-4b22-824c-7f8847fb66be', '7237c5fd-7944-4cee-b348-f66a7e4dc37f', '1f865aa0-f115-4746-8930-a96f43a9c940', '8f52221b-96de-4b55-aa3b-c8d8be25f227', '03b8eda4-0eaa-4f28-bbde-b43937177567', '3c793dca-6bb1-4a7e-ae2e-0211e901783e', '1fa9bc1a-dce7-4053-89d5-b15d561a4684', '622e7fb9-11eb-4391-a4bf-de7ac21c1318', '3ed2d80f-9191-48e5-8cd6-762b474cbb46', '5c297f97-ab24-4b4d-9fc0-91731eb53c47']
Embedding status: 401/1691 documents embedded
Embedding status: 571/1691 documents embedded
Embedding status: 741/1691 documents embedded
Embedding status: 941/1691 documents embedded
Embedding status: 1211/1691 documents embedded
Embedding status: 1431/1691 documents embedded
Embedding status: 1691/1691 documents embedded

我们看到两本书的结果。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")
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'}
====

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'}
====

easily admitted, that an assembly of eminent naturalists and physicians,
with a sprinkling of astronomers, and one or two abstract
mathematicians, were not precisely the persons best qualified to
appreciate such an instrument of mechanical investigation as we have
here described. We shall not therefore be understood as intending the
slightest disrespect for these distinguished persons, when we express
our regret, that a discovery of such paramount practical value, in a -> {'source': 'https://www.gutenberg.org/cache/epub/71292/pg71292.txt'}
====

现在,我们设置一个筛选器

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 evening than in the daylight, for he said that he hated to be
conspicuous. Very retiring and gentlemanly he was. Even his voice was
gentle. He’d had the quinsy and swollen glands when he was young, he
told me, and it had left him with a weak throat, and a hesitating,
whispering fashion of speech. He was always well dressed, very neat and
plain, but his eyes were weak, just as mine are, and he wore tinted
glasses against the glare.” -> {'source': 'https://www.gutenberg.org/files/48320/48320-0.txt'}
====

which was characteristic of him. “It is perhaps less suggestive than
it might have been,” he remarked, “and yet there are a few inferences
which are very distinct, and a few others which represent at least a
strong balance of probability. That the man was highly intellectual
is of course obvious upon the face of it, and also that he was fairly
well-to-do within the last three years, although he has now fallen upon
evil days. He had foresight, but has less now than formerly, pointing -> {'source': 'https://www.gutenberg.org/files/48320/48320-0.txt'}
====

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