May 2025
Intermediate to advanced
382 pages
10h 33m
Chinese
Content preview from 图解大模型 : 生成式AI 原理与实战
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182
｜
第
7
章
提炼摘要的过程由另一个
LLM
完成：该模型接收完整对话历史作为输入，并负责生成简
明的摘要。使用外部
LLM
的显著优势在于，对话系统无须局限于单一模型。如图
7-12
所
示，该流程通过两阶段处理实现。
LLM
The answer to 1 + 1 is...
(drumroll) ...2.
Hi! I’m Maarten.
What is 1 + 1?
对话历史
提示词
What is my name?
<|user|><s>
Conversation history:
总结
Maarten asked what 1 + 1 is
and I told him 2.
<|end|>What is my name?
<|assistant|>
提示词模板
图 7-12：我们并未直接将对话历史传递给提示词模板，而是先通过另一个 LLM 提炼摘要
这意味着每次向主
LLM
发起查询时，系统会执行两次模型调用：
•
用户提示词处理
•
摘要提示词生成
要在
LangChain
中实现此功能，首先需要准备用于摘要的专用提示词模板：
# 创建摘要提示词模板
summary_prompt_template = """<s><|user|>Summarize the conversations and update
with the new lines.
Current summary:
{summary}
new lines of conversation:
{new_lines}
New summary:<|end|>
<|assistant|>""" ...
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