如果您在 Colab 上打开此 Notebook，您可能需要安装 LlamaIndex 🦙。

输入 [ ]

已复制！

%pip install llama-index-vector-stores-faiss

%pip install llama-index-vector-stores-faiss
!pip install llama-index

已复制！

%pip install llama-index-vector-stores-faiss

!pip install llama-index
创建 Faiss 索引¶

import logging import sys logging.basicConfig(stream=sys.stdout, level=logging.INFO) logging.getLogger().addHandler(logging.StreamHandler(stream=sys.stdout))

已复制！

%pip install llama-index-vector-stores-faiss

import logging
import sys

logging.basicConfig(stream=sys.stdout, level=logging.INFO)
logging.getLogger().addHandler(logging.StreamHandler(stream=sys.stdout))
import faiss # text-ada-embedding-002 的维度 d = 1536 faiss_index = faiss.IndexFlatL2(d)

已复制！

%pip install llama-index-vector-stores-faiss

import faiss

# dimensions of text-ada-embedding-002
d = 1536
faiss_index = faiss.IndexFlatL2(d)
加载文档，构建 VectorStoreIndex¶

from llama_index.core import ( SimpleDirectoryReader, load_index_from_storage, VectorStoreIndex, StorageContext, ) from llama_index.vector_stores.faiss import FaissVectorStore from IPython.display import Markdown, display

已复制！

%pip install llama-index-vector-stores-faiss





from llama_index.core import (
    SimpleDirectoryReader,
    load_index_from_storage,
    VectorStoreIndex,
    StorageContext,
)
from llama_index.vector_stores.faiss import FaissVectorStore
from IPython.display import Markdown, display
下载数据

!mkdir -p 'data/paul_graham/' !wget 'https://raw.githubusercontent.com/run-llama/llama_index/main/docs/docs/examples/data/paul_graham/paul_graham_essay.txt' -O 'data/paul_graham/paul_graham_essay.txt'

已复制！

%pip install llama-index-vector-stores-faiss

!mkdir -p 'data/paul_graham/'
!wget 'https://raw.githubusercontent.com/run-llama/llama_index/main/docs/docs/examples/data/paul_graham/paul_graham_essay.txt' -O 'data/paul_graham/paul_graham_essay.txt'
# 加载文档 documents = SimpleDirectoryReader("./data/paul_graham/").load_data()

已复制！

%pip install llama-index-vector-stores-faiss

# load documents
documents = SimpleDirectoryReader("./data/paul_graham/").load_data()
vector_store = FaissVectorStore(faiss_index=faiss_index) storage_context = StorageContext.from_defaults(vector_store=vector_store) index = VectorStoreIndex.from_documents( documents, storage_context=storage_context )

已复制！

%pip install llama-index-vector-stores-faiss

vector_store = FaissVectorStore(faiss_index=faiss_index)
storage_context = StorageContext.from_defaults(vector_store=vector_store)
index = VectorStoreIndex.from_documents(
    documents, storage_context=storage_context
)
# 将索引保存到磁盘 index.storage_context.persist()

已复制！

%pip install llama-index-vector-stores-faiss

# save index to disk
index.storage_context.persist()
# 从磁盘加载索引 vector_store = FaissVectorStore.from_persist_dir("./storage") storage_context = StorageContext.from_defaults( vector_store=vector_store, persist_dir="./storage" ) index = load_index_from_storage(storage_context=storage_context)

已复制！

%pip install llama-index-vector-stores-faiss





# load index from disk
vector_store = FaissVectorStore.from_persist_dir("./storage")
storage_context = StorageContext.from_defaults(
    vector_store=vector_store, persist_dir="./storage"
)
index = load_index_from_storage(storage_context=storage_context)
查询索引¶

# 将日志级别设置为 DEBUG 以获得更详细的输出 query_engine = index.as_query_engine() response = query_engine.query("What did the author do growing up?")

已复制！

%pip install llama-index-vector-stores-faiss

# set Logging to DEBUG for more detailed outputs
query_engine = index.as_query_engine()
response = query_engine.query("What did the author do growing up?")
display(Markdown(f"{response}"))

已复制！

%pip install llama-index-vector-stores-faiss

display(Markdown(f"<b>{response}</b>"))
# 将日志级别设置为 DEBUG 以获得更详细的输出 query_engine = index.as_query_engine() response = query_engine.query( "What did the author do after his time at Y Combinator?" )

已复制！

%pip install llama-index-vector-stores-faiss

# set Logging to DEBUG for more detailed outputs
query_engine = index.as_query_engine()
response = query_engine.query(
    "What did the author do after his time at Y Combinator?"
)
回到顶部

已复制！

%pip install llama-index-vector-stores-faiss

display(Markdown(f"<b>{response}</b>"))
# 将日志级别设置为 DEBUG 以获得更详细的输出 query_engine = index.as_query_engine() response = query_engine.query( "What did the author do after his time at Y Combinator?" )