流式传输¶

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

输入 [ ]

!pip install llama-index

!pip install llama-index

输入 [ ]

import logging
import sys

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

from llama_index.core import VectorStoreIndex, SimpleDirectoryReader

import logging import sys logging.basicConfig(stream=sys.stdout, level=logging.INFO) logging.getLogger().addHandler(logging.StreamHandler(stream=sys.stdout)) from llama_index.core import VectorStoreIndex, SimpleDirectoryReader

INFO:numexpr.utils:Note: NumExpr detected 12 cores but "NUMEXPR_MAX_THREADS" not set, so enforcing safe limit of 8.
Note: NumExpr detected 12 cores but "NUMEXPR_MAX_THREADS" not set, so enforcing safe limit of 8.
INFO:numexpr.utils:NumExpr defaulting to 8 threads.
NumExpr defaulting to 8 threads.

/Users/suo/miniconda3/envs/llama/lib/python3.9/site-packages/deeplake/util/check_latest_version.py:32: UserWarning: A newer version of deeplake (3.6.7) is available. It's recommended that you update to the latest version using `pip install -U deeplake`.
  warnings.warn(

下载数据¶

输入 [ ]

!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'

!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，构建向量存储索引¶

输入 [ ]

# load documents
documents = SimpleDirectoryReader("./data/paul_graham").load_data()

# 加载文档 documents = SimpleDirectoryReader("./data/paul_graham").load_data()

输入 [ ]

index = VectorStoreIndex.from_documents(documents)

index = VectorStoreIndex.from_documents(documents)

查询索引¶

输入 [ ]

# set Logging to DEBUG for more detailed outputs
query_engine = index.as_query_engine(streaming=True, similarity_top_k=1)
response_stream = query_engine.query(
    "What did the author do growing up?",
)

# 将日志级别设置为 DEBUG 以获得更详细的输出 query_engine = index.as_query_engine(streaming=True, similarity_top_k=1) response_stream = query_engine.query( "What did the author do growing up?", )

输入 [ ]

response_stream.print_response_stream()

response_stream.print_response_stream()

The author grew up writing short stories and programming on an IBM 1401. He also nagged his father to buy him a TRS-80 microcomputer, on which he wrote simple games, a program to predict how high his model rockets would fly, and a word processor. He eventually went to college to study philosophy, but found it boring and switched to AI.