聊天引擎 - OpenAI Agent 模式¶

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

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%pip install llama-index-llms-openai

%pip install llama-index-llms-openai

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!pip install llama-index

!pip install llama-index

下载数据¶

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!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'

--2023-11-20 14:52:58--  https://raw.githubusercontent.com/run-llama/llama_index/main/docs/docs/examples/data/paul_graham/paul_graham_essay.txt
Resolving raw.githubusercontent.com (raw.githubusercontent.com)... 185.199.110.133, 185.199.108.133, 185.199.109.133, ...
Connecting to raw.githubusercontent.com (raw.githubusercontent.com)|185.199.110.133|:443... connected.
HTTP request sent, awaiting response... 200 OK
Length: 75042 (73K) [text/plain]
Saving to: ‘data/paul_graham/paul_graham_essay.txt’

data/paul_graham/pa 100%[===================>]  73.28K  --.-KB/s    in 0.02s   

2023-11-20 14:52:58 (2.86 MB/s) - ‘data/paul_graham/paul_graham_essay.txt’ saved [75042/75042]

5 行代码快速开始¶

加载数据并构建索引

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from llama_index.core import VectorStoreIndex, SimpleDirectoryReader
from llama_index.llms.openai import OpenAI

# Necessary to use the latest OpenAI models that support function calling API
llm = OpenAI(model="gpt-3.5-turbo-0613")
data = SimpleDirectoryReader(input_dir="../data/paul_graham/").load_data()
index = VectorStoreIndex.from_documents(data)

from llama_index.core import VectorStoreIndex, SimpleDirectoryReader from llama_index.llms.openai import OpenAI # Necessary to use the latest OpenAI models that support function calling API llm = OpenAI(model="gpt-3.5-turbo-0613") data = SimpleDirectoryReader(input_dir="../data/paul_graham/").load_data() index = VectorStoreIndex.from_documents(data)

配置聊天引擎

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chat_engine = index.as_chat_engine(chat_mode="openai", llm=llm, verbose=True)

chat_engine = index.as_chat_engine(chat_mode="openai", llm=llm, verbose=True)

与您的数据聊天

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response = chat_engine.chat("Hi")
print(response)

response = chat_engine.chat("Hi") print(response)

STARTING TURN 1
---------------

Hello! How can I assist you today?

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response = chat_engine.chat(
    "Use the tool to answer: Who did Paul Graham hand over YC to?"
)
print(response)

response = chat_engine.chat( "Use the tool to answer: Who did Paul Graham hand over YC to?" ) print(response)

STARTING TURN 1
---------------

=== Calling Function ===
Calling function: query_engine_tool with args: {
  "input": "Who did Paul Graham hand over YC to?"
}
Got output: Paul Graham handed over YC to Sam Altman.
========================

STARTING TURN 2
---------------

Paul Graham handed over Y Combinator (YC) to Sam Altman.

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response = chat_engine.stream_chat(
    "Use the tool to answer: Who did Paul Graham hand over YC to?"
)
print(response)

response = chat_engine.stream_chat( "Use the tool to answer: Who did Paul Graham hand over YC to?" ) print(response)

STARTING TURN 1
---------------

=== Calling Function ===
Calling function: query_engine_tool with args: {
  "input": "Who did Paul Graham hand over YC to?"
}
Got output: Paul Graham handed over YC to Sam Altman.
========================

STARTING TURN 2
---------------

强制聊天引擎查询索引¶

注意：这是“openai”聊天模式（底层使用 `OpenAIAgent`）特有的功能。

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response = chat_engine.chat(
    "What did Paul Graham do growing up?", tool_choice="query_engine_tool"
)

response = chat_engine.chat( "What did Paul Graham do growing up?", tool_choice="query_engine_tool" )

STARTING TURN 1
---------------

=== Calling Function ===
Calling function: query_engine_tool with args: {
  "input": "What did Paul Graham do growing up?"
}
Got output: Growing up, Paul Graham worked on writing and programming. He wrote short stories and also tried his hand at programming on the IBM 1401 computer that his school district had. He later got a microcomputer, a TRS-80, and started programming more extensively, writing simple games and even a word processor.
========================

STARTING TURN 2
---------------

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print(response)

print(response)

Growing up, Paul Graham worked on writing and programming. He wrote short stories and also tried his hand at programming on the IBM 1401 computer that his school district had. He later got a microcomputer, a TRS-80, and started programming more extensively, writing simple games and even a word processor.