llamaindex openai api key的进一步展开说明

连接外部数据与OpenAI GPT3的方法

在本教程中，我们将向您展现怎样使用LlamaIndex将外部数据与OpenAI GPT3连接起来。以路易斯·卡罗尔（Lewis Carroll）的《爱丽丝漫游奇境记》为例，通过将该书与OpenAI GPT3连接，我们可以提出与书籍内容相关的问题并取得答案。

安装和设置

使用pip命令可以安装LlamaIndex库：

“`
pip install llama-index
“`

另外，您还需要将OpenAI API密钥添加到名为OPENAI_API_KEY的环境变量中，或您可以通过以下方式传递：

“`
# My OpenAI Key
import os
os.environ[‘OPENAI_API_KEY’] = “INSERT OPENAI KEY”
“`

LlamaIndex使用模式

LlamaIndex的一般使用模式以下：

• 加载文档（可以手动加载或通过数据加载器加载）
• 构建索引（从节点或文档中）
• 查询索引

第一项任务是加载文档。该书以.txt格式存储在data文件夹下，我们可以通过以下命令加载文档：

“`
from llama_index import SimpleDirectoryReader
documents = SimpleDirectoryReader(‘data’).load_data()
“`

索引构建

我们可以按以下方式对这一文档构建索引：

“`
from llama_index import GPTVectorStoreIndex
index = GPTVectorStoreIndex.from_documents(documents)
“`

保存和加载索引

索引被保存在内存中，如果我们希望将其保存到磁盘上，可以运行以下命令：

“`
from llama_index import StorageContext, load_index_from_storage
index.storage_context.persist(persist_dir=’./storage’) # 重建存储上下文
storage_context = StorageContext.from_defaults(persist_dir=’./storage’) # 加载索引
index = load_index_from_storage(storage_context)
“`

查询索引

高级API

现在，我们可使用高级API提出问题并得到答案。例如，让我们询问书的情节：

“`
query_engine = index.as_query_engine()
response = query_engine.query(“What is the plot of the book?”)
print(response.response)
“`

输出：

The book follows Alice, a young girl, as she falls down a rabbit hole and embarks on a series of strange and surreal adventures. Along the way, she meets a variety of strange creatures, including a talking caterpillar, a dodo, a Cheshire cat, and a mad hatter. She also participates in a variety of activities, such as a caucus race, a croquet game, and a tea party. Throughout her journey, Alice must use her wit and courage to solve puzzles and overcome obstacles in order to find her way home.

让我们再试试另外一个问题：

“`
response = query_engine.query(“Give me a summary of the book”)
print(response.response)
“`

输出：

Alice is a young girl who falls down a rabbit hole and finds herself in a strange world. She meets a variety of characters, including a Dodo, a Mouse, a King, a Queen, and a Knave. The Dodo organizes a race, but when it is over, no one knows who has won. Alice gives out comfits as prizes and the Mouse asks her to tell her story. Alice then tells the story of how she ended up in the strange world. The King and Queen then ask Alice to explain a poem, but she is unable to do so. The Queen then orders Alice’s head to be cut off, but Alice wakes up to find herself back in her sister’s lap.

最后，让我们试试另外一个问题：

“`
response = query_engine.query(“””Give me a brief description of all characters of the book.
I want the format to be Character –> Description”””)
print(response.response)
“`

输出：

Alice –> A young girl who falls down a rabbit hole and embarks on a fantastical journey through Wonderland. White Rabbit –> A talking rabbit who Alice follows down the rabbit hole. He is always in a hurry and is late for important appointments. Mock Turtle –> A talking turtle who Alice meets in Wonderland. He is sad and tells Alice stories about his past. Duchess –> A character Alice meets in Wonderland who is rude and mean. She is accompanied by a Cheshire Cat. Cheshire Cat –> A mysterious talking cat who appears and disappears at will. He is mischievous and often gives Alice cryptic advice. Queen of Hearts –> The ruler of Wonderland who is always angry and orders people to be executed for the slightest offense.

低级API

LlamaIndex还提供了与低级API相关的选项，以便在需要自定义查询时使用。例如：

“`
from llama_index import (
GPTVectorStoreIndex,
ResponseSynthesizer,
)
from llama_index.retrievers import VectorIndexRetriever
from llama_index.query_engine import RetrieverQueryEngine
from llama_index.indices.postprocessor import SimilarityPostprocessor

# 构建索引
index = GPTVectorStoreIndex.from_documents(documents)

# 配置检索器
retriever = VectorIndexRetriever(
index=index,
similarity_top_k=2,
)

# 配置响应合成器
response_synthesizer = ResponseSynthesizer.from_args(
node_postprocessors=[
SimilarityPostprocessor(similarity_cutoff=0.7)
]
)

# 组装查询引擎
query_engine = RetrieverQueryEngine(
retriever=retriever,
response_synthesizer=response_synthesizer,
)

# 查询
response = query_engine.query(“Give me a brief description of all characters of the book. I want the format to be Character –> Description”)
print(response.response)
“`

输出：

Alice –> A young girl who falls down a rabbit hole and embarks on a fantastical journey through Wonderland. The White Rabbit –> A talking rabbit who Alice follows down the rabbit hole. He is always in a hurry and is late for important appointments. The Duchess –> A rude and unpleasant woman who Alice meets in Wonderland. She is accompanied by a baby and a cook. The Cheshire Cat –> A mysterious talking cat who appears and disappears at will. He is known for his mischievous grin and his wise advice. The Mad Hatter –> A strange character who hosts a tea party for Alice. He is known for his nonsensical riddles and his odd behavior. The March Hare –> A hare who attends the Mad Hatter’s tea party. He is known for his erratic behavior and his love of tea. The Queen of Hearts –> The ruler of Wonderland. She is known for her temper and her love of executing people. The King of Hearts –> The Queen’s husband and the ruler of Wonderland. He is known for his meekness and his inability to stand up to the Queen.

索引列表

请记住，我们还可以创建索引列表。当我们需要要求摘要等任务时，这很有帮助。让我们再次要求提供该书的摘要，以作比较。

“`
from llama_index import GPTListIndex

index = GPTListIndex.from_documents(documents)

query_engine = index.as_query_engine(response_mode=”tree_summarize”)
response = query_engine.query(“Give me a summary of the book”)
print(response.response)
“`

输出：

Alice’s Adventures in Wonderland is a classic children’s novel by Lewis Carroll. The story follows Alice, a young girl who falls down a rabbit hole into a fantastical world populated by talking animals and other strange creatures. Through her adventures, Alice meets a variety of characters, including the White Rabbit, the Cheshire Cat, the Mad Hatter, the Queen of Hearts, and the Mock Turtle. She embarks on a series of adventures, during which she grows and shrinks in size, meets a variety of characters, and solves puzzles. Along the way, she learns valuable lessons about life and discovers her own identity. In the end, Alice wakes up from her dream and returns to reality, but she never forgets the wonderful experiences she had in Wonderland.

结语

借助LlamaIndex，我们能够通过连接定制数据来释放LLM的强大潜力。这些数据可以采取区别的格式，如txt、pdf、html等，也能够来自Notion、Slack、Twitter、LinkedIn等区别的来源。另外，数据还可以来自客户的评论或论坛。

在下一篇教程中，我们将向您展现怎样使用LangChain库连接客户数据以构建聊天机器人。敬请关注！

llamaindex openai api key的常见问答Q&A