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机器翻译

本页由英文原文机器翻译而来，尚未经过母语审校，欢迎在 GitHub 上提出修改。内容如有出入，以英文原文为准。

任务： 一个根据商店的政策文档回答问题的页面，并显示每个回答来自哪份文档。

yaml

# Recipe: answers from your own documents, with the sources they came from.
paths:
  components: ./components

# The model server is Ollama at http://localhost:11434 unless
# QUANTUM_LLM_BASE_URL says otherwise; the model is this one unless
# QUANTUM_LLM_DEFAULT_MODEL says otherwise.
llm:
  model: phi3

knowledge/ 中的三个 Markdown 文件：

# Returns

Returns are accepted within 30 days of delivery, with the receipt. The refund
goes back to the card used for the order.

q:knowledge 读取这个文件夹，把它拆分成文本块并计算嵌入。q:llm knowledge="docs" 检索与问题最接近的文本块，编号后发送给模型，并指示它只根据这些文本块回答、像 [1] 这样引用它们。answer_result.sources 列出检索到的内容；answer_result.grounded 说明回答是否引用了其中任何一项。

xml

<q:component name="Ask">
  <!-- The documents in knowledge/, split into chunks and embedded when the
       page runs. persist="false" keeps the index in memory; without it, it is
       stored in ./.quantum/knowledge and reused until a document changes. -->
  <q:knowledge name="docs" persist="false" chunkSize="300" chunkOverlap="30">
    <q:source type="directory" path="knowledge" pattern="*.md" />
  </q:knowledge>

  <q:set name="question" value="{query.q}" default="" />

  <q:if condition="question">
    <!-- The question retrieves the closest chunks; they reach the model
         numbered, with the instruction to answer only from them and cite
         them like [1]. -->
    <q:llm name="answer" knowledge="docs" top="2">
      <q:message role="user">{question}</q:message>
    </q:llm>
  </q:if>

  <ui:window title="Ask the store">
    <ui:form>
      <ui:input bind="q" value="{question}" placeholder="Your question" />
      <ui:button variant="primary">Ask</ui:button>
    </ui:form>
    <q:if condition="question">
      <ui:text>{answer}</ui:text>
      <q:if condition="answer_result.grounded">
        <ui:text>Sources:</ui:text>
        <q:loop items="{answer_result.sources}" var="s">
          <ui:text>[{s.n}] {s.name}</ui:text>
        </q:loop>
        <q:else>
          <ui:alert variant="warning">This answer cites none of the documents.</ui:alert>
        </q:else>
      </q:if>
    </q:if>
  </ui:window>
</q:component>

xml

<!-- Structural checks, never the model's exact words: the same tests run
     against a real model before every release. -->
<q:test name="the answer comes with the document it is from" page="/">
  <test:visit q="How many days do I have to return an order?" />
  <test:expect text="Sources:" />
  <test:expect text="[1] returns.md" />
</q:test>

<q:test name="another question, another document" page="/">
  <test:visit q="Is shipping free for my order?" />
  <test:expect text="[1] shipping.md" />
</q:test>

<q:test name="no question, no model call" page="/">
  <test:visit />
  <test:expect no-text="Sources:" />
</q:test>

text

tests/ask.test.q
  PASS  the answer comes with the document it is from
  PASS  another question, another document
  PASS  no question, no model call
3 passed, 0 failed

已测试： 在 CI 中，这些测试针对一个替身模型服务器运行，它根据收到的第一个来源作答；每次发布前，它们针对真实模型运行（tests/live_ai/test_cookbook_ai.py）。因此它们检查的是结构——哪个来源、哪个工具、失败时页面显示什么——而从不检查模型的措辞。

参见 IA-2、IA-6 和 AI 指南（英文）。

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