Tencent Cloud VectorDB

!pip3 install tcvectordb langchain-community

from langchain_community.document_loaders import TextLoader
from langchain_community.embeddings.fake import FakeEmbeddings
from langchain_community.vectorstores import TencentVectorDB
from langchain_community.vectorstores.tencentvectordb import ConnectionParams
from langchain_text_splitters import CharacterTextSplitter

loader = TextLoader("../../how_to/state_of_the_union.txt")
documents = loader.load()
text_splitter = CharacterTextSplitter(chunk_size=1000, chunk_overlap=0)
docs = text_splitter.split_documents(documents)

##  you can use a LangChain Embeddings model, like OpenAIEmbeddings:

# from langchain_community.embeddings.openai import OpenAIEmbeddings
#
# embeddings = OpenAIEmbeddings()
# t_vdb_embedding = None

## Or you can use a Tencent Embedding model, like `bge-base-zh`:

t_vdb_embedding = "bge-base-zh"  # bge-base-zh is the default model
embeddings = None

conn_params = ConnectionParams(
    url="http://10.0.X.X",
    key="eC4bLRy2va******************************",
    username="root",
    timeout=20,
)

vector_db = TencentVectorDB.from_documents(
    docs, embeddings, connection_params=conn_params, t_vdb_embedding=t_vdb_embedding
)

query = "What did the president say about Ketanji Brown Jackson"
docs = vector_db.similarity_search(query)
docs[0].page_content

'Tonight. I call on the Senate to: Pass the Freedom to Vote Act. Pass the John Lewis Voting Rights Act. And while you’re at it, pass the Disclose Act so Americans can know who is funding our elections. \n\nTonight, I’d like to honor someone who has dedicated his life to serve this country: Justice Stephen Breyer—an Army veteran, Constitutional scholar, and retiring Justice of the United States Supreme Court. Justice Breyer, thank you for your service. \n\nOne of the most serious constitutional responsibilities a President has is nominating someone to serve on the United States Supreme Court. \n\nAnd I did that 4 days ago, when I nominated Circuit Court of Appeals Judge Ketanji Brown Jackson. One of our nation’s top legal minds, who will continue Justice Breyer’s legacy of excellence.'

vector_db = TencentVectorDB(embeddings, conn_params)

vector_db.add_texts(["Ankush went to Princeton"])
query = "Where did Ankush go to college?"
docs = vector_db.max_marginal_relevance_search(query)
docs[0].page_content

'Ankush went to Princeton'

from langchain_community.vectorstores.tencentvectordb import (
    META_FIELD_TYPE_STRING,
    META_FIELD_TYPE_UINT64,
    ConnectionParams,
    MetaField,
    TencentVectorDB,
)
from langchain_core.documents import Document

meta_fields = [
    MetaField(name="year", data_type=META_FIELD_TYPE_UINT64, index=True),
    MetaField(name="rating", data_type=META_FIELD_TYPE_STRING, index=False),
    MetaField(name="genre", data_type=META_FIELD_TYPE_STRING, index=True),
    MetaField(name="director", data_type=META_FIELD_TYPE_STRING, index=True),
]

docs = [
    Document(
        page_content="The Shawshank Redemption is a 1994 American drama film written and directed by Frank Darabont.",
        metadata={
            "year": 1994,
            "rating": "9.3",
            "genre": "drama",
            "director": "Frank Darabont",
        },
    ),
    Document(
        page_content="The Godfather is a 1972 American crime film directed by Francis Ford Coppola.",
        metadata={
            "year": 1972,
            "rating": "9.2",
            "genre": "crime",
            "director": "Francis Ford Coppola",
        },
    ),
    Document(
        page_content="The Dark Knight is a 2008 superhero film directed by Christopher Nolan.",
        metadata={
            "year": 2008,
            "rating": "9.0",
            "genre": "superhero",
            "director": "Christopher Nolan",
        },
    ),
    Document(
        page_content="Inception is a 2010 science fiction action film written and directed by Christopher Nolan.",
        metadata={
            "year": 2010,
            "rating": "8.8",
            "genre": "science fiction",
            "director": "Christopher Nolan",
        },
    ),
]

vector_db = TencentVectorDB.from_documents(
    docs,
    None,
    connection_params=ConnectionParams(
        url="http://10.0.X.X",
        key="eC4bLRy2va******************************",
        username="root",
        timeout=20,
    ),
    collection_name="movies",
    meta_fields=meta_fields,
)

query = "film about dream by Christopher Nolan"

# you can use the tencentvectordb filtering syntax with the `expr` parameter:
result = vector_db.similarity_search(query, expr='director="Christopher Nolan"')

# you can either use the langchain filtering syntax with the `filter` parameter:
# result = vector_db.similarity_search(query, filter='eq("director", "Christopher Nolan")')

result

[Document(page_content='The Dark Knight is a 2008 superhero film directed by Christopher Nolan.', metadata={'year': 2008, 'rating': '9.0', 'genre': 'superhero', 'director': 'Christopher Nolan'}),
 Document(page_content='The Dark Knight is a 2008 superhero film directed by Christopher Nolan.', metadata={'year': 2008, 'rating': '9.0', 'genre': 'superhero', 'director': 'Christopher Nolan'}),
 Document(page_content='The Dark Knight is a 2008 superhero film directed by Christopher Nolan.', metadata={'year': 2008, 'rating': '9.0', 'genre': 'superhero', 'director': 'Christopher Nolan'}),
 Document(page_content='Inception is a 2010 science fiction action film written and directed by Christopher Nolan.', metadata={'year': 2010, 'rating': '8.8', 'genre': 'science fiction', 'director': 'Christopher Nolan'})]