zengli
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coding-agent


			
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  <h1>6.2 融合FAQ 和知识库查询（优化版）</h1>

<h2 id="_1">学习目标：<a class="headerlink" href="#_1" title="Permanent link">¶</a></h2>
<ul>
<li>深入理解优化后的智能问答系统，掌握端到端工作流程。</li>
<li>学习如何通过对话历史和流式输出提升用户交互体验。</li>
<li>掌握 MySQL FAQ 和 RAG 系统的集成，以及健壮的错误处理和日志记录。</li>
</ul>
<h2 id="_2">一、查询流程图<a class="headerlink" href="#_2" title="Permanent link">¶</a></h2>
<p><code>new_main.py</code> 是对 <code>old_main.py</code> 的优化版本，新增了对话历史管理和流式输出功能，增强了交互性和实时性。系统整合了 MySQL 的 FAQ 精确匹配、RAG 的知识库检索、MySQL 对话历史存储，以及流式答案生成，适用于知识库场景下的实时问答需求。</p>
<p>以下是优化后的智能问答系统查询流程图，展示用户输入到答案输出的处理逻辑，包括对话历史和流式输出。</p>
<div align="center"><img src="../img/lc_002.png" style="zoom:80%"><img></div>

<h2 id="_3">二、流程说明<a class="headerlink" href="#_3" title="Permanent link">¶</a></h2>
<ol>
<li><strong>输入处理</strong>：用户提供查询 (<code>query</code>)、会话 ID (<code>session_id</code>) 和可选的知识域过滤 (<code>source_filter</code>)。</li>
<li><strong>会话管理</strong>：若提供 <code>session_id</code>，从 MySQL 获取最近 5 轮对话历史；否则生成新的 UUID。</li>
<li><strong>BM25 搜索</strong>：使用 BM25 算法搜索 MySQL 知识库，设置相似度阈值 0.85。</li>
<li><strong>答案判断</strong>：</li>
<li>若找到可靠答案（相似度 &gt; 0.85），一次性返回。</li>
<li>若无可靠答案且需要 RAG，调用 RAG 系统以流式方式生成答案。</li>
<li>若无需 RAG，返回“未找到答案”。</li>
<li><strong>历史更新</strong>：将查询和答案存入 MySQL 的 <code>conversations</code> 表，保留最近 5 轮对话。</li>
<li><strong>输出</strong>：通过流式输出（RAG）或一次性输出（MySQL）返回答案，并展示对话历史。</li>
</ol>
<h2 id="_4">三、代码介绍<a class="headerlink" href="#_4" title="Permanent link">¶</a></h2>
<p>以下是 <code>new_main.py</code> 的完整代码，包含逐行注释，详细解析功能与实现逻辑。</p>
<h3 id="1">1 导入必备的工具包<a class="headerlink" href="#1" title="Permanent link">¶</a></h3>
<div class="highlight"><pre><span></span><code><span class="c1"># 导入 MySQL 系统组件，用于数据库操作和搜索</span>
<span class="kn">from</span><span class="w"> </span><span class="nn">mysql_qa.cache.redis_client</span><span class="w"> </span><span class="kn">import</span> <span class="n">RedisClient</span>
<span class="kn">from</span><span class="w"> </span><span class="nn">mysql_qa.db.mysql_client</span><span class="w"> </span><span class="kn">import</span> <span class="n">MySQLClient</span>
<span class="kn">from</span><span class="w"> </span><span class="nn">mysql_qa.retrieval.bm25_search</span><span class="w"> </span><span class="kn">import</span> <span class="n">BM25Search</span>
<span class="c1"># 导入 RAG 系统组件，用于知识库检索和答案生成</span>
<span class="kn">from</span><span class="w"> </span><span class="nn">rag_qa.core.vector_store</span><span class="w"> </span><span class="kn">import</span> <span class="n">VectorStore</span>
<span class="kn">from</span><span class="w"> </span><span class="nn">rag_qa.core.new_rag_system</span><span class="w"> </span><span class="kn">import</span> <span class="n">RAGSystem</span>
<span class="c1"># 导入配置和日志工具，用于系统配置和日志记录</span>
<span class="kn">from</span><span class="w"> </span><span class="nn">base.config</span><span class="w"> </span><span class="kn">import</span> <span class="n">config</span>
<span class="kn">from</span><span class="w"> </span><span class="nn">base.logger</span><span class="w"> </span><span class="kn">import</span> <span class="n">logger</span>
<span class="c1"># 导入 OpenAI 客户端，用于调用 DashScope API</span>
<span class="kn">from</span><span class="w"> </span><span class="nn">openai</span><span class="w"> </span><span class="kn">import</span> <span class="n">OpenAI</span>
<span class="c1"># 导入时间库，用于记录处理时间</span>
<span class="kn">import</span><span class="w"> </span><span class="nn">time</span>
<span class="kn">import</span><span class="w"> </span><span class="nn">pymysql</span>
<span class="kn">import</span><span class="w"> </span><span class="nn">uuid</span>
</code></pre></div>
<h3 id="2">2 系统初始化<a class="headerlink" href="#2" title="Permanent link">¶</a></h3>
<ul>
<li>(<code>__init__</code>) 初始化方法</li>
<li><strong>功能</strong>：初始化日志、配置、数据库客户端、搜索模块、向量存储、RAG 系统和对话历史表。</li>
<li><strong>关键点</strong>：通过 Config 管理 API 密钥和模型参数，异常处理确保 OpenAI 客户端初始化成功。</li>
</ul>
<div class="highlight"><pre><span></span><code><span class="k">class</span><span class="w"> </span><span class="nc">IntegratedQASystem</span><span class="p">:</span>
    <span class="k">def</span><span class="w"> </span><span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
        <span class="c1"># 初始化日志工具，用于记录系统运行信息</span>
        <span class="bp">self</span><span class="o">.</span><span class="n">logger</span> <span class="o">=</span> <span class="n">logger</span>
        <span class="bp">self</span><span class="o">.</span><span class="n">config</span> <span class="o">=</span> <span class="n">config</span>
        <span class="c1"># 初始化 MySQL 客户端，用于数据库操作</span>
        <span class="bp">self</span><span class="o">.</span><span class="n">mysql_client</span> <span class="o">=</span> <span class="n">MySQLClient</span><span class="p">()</span>
        <span class="c1"># 初始化 Redis 客户端，用于缓存管理</span>
        <span class="bp">self</span><span class="o">.</span><span class="n">redis_client</span> <span class="o">=</span> <span class="n">RedisClient</span><span class="p">()</span>
        <span class="c1"># 初始化 BM25 搜索模块，结合 MySQL 和 Redis</span>
        <span class="bp">self</span><span class="o">.</span><span class="n">bm25_search</span> <span class="o">=</span> <span class="n">BM25Search</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">redis_client</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">mysql_client</span><span class="p">)</span>
        <span class="k">try</span><span class="p">:</span>
            <span class="c1"># 初始化 OpenAI 客户端，连接 DashScope API</span>
            <span class="bp">self</span><span class="o">.</span><span class="n">client</span> <span class="o">=</span> <span class="n">OpenAI</span><span class="p">(</span><span class="n">api_key</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">config</span><span class="o">.</span><span class="n">DASHSCOPE_API_KEY</span><span class="p">,</span>
                                 <span class="n">base_url</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">config</span><span class="o">.</span><span class="n">DASHSCOPE_BASE_URL</span><span class="p">)</span>
        <span class="k">except</span> <span class="ne">Exception</span> <span class="k">as</span> <span class="n">e</span><span class="p">:</span>
            <span class="c1"># 记录 OpenAI 初始化失败的错误日志</span>
            <span class="bp">self</span><span class="o">.</span><span class="n">logger</span><span class="o">.</span><span class="n">error</span><span class="p">(</span><span class="sa">f</span><span class="s2">"OpenAI 客户端初始化失败: </span><span class="si">{</span><span class="n">e</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
            <span class="c1"># 抛出异常，终止初始化</span>
            <span class="k">raise</span>
        <span class="c1"># 初始化向量存储，用于 RAG 系统的知识库管理</span>
        <span class="bp">self</span><span class="o">.</span><span class="n">vector_store</span> <span class="o">=</span> <span class="n">VectorStore</span><span class="p">()</span>
        <span class="c1"># 初始化 RAG 系统，传入向量存储和 DashScope API 调用函数</span>
        <span class="bp">self</span><span class="o">.</span><span class="n">rag_system</span> <span class="o">=</span> <span class="n">RAGSystem</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">vector_store</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">call_dashscope</span><span class="p">)</span>
        <span class="c1"># 初始化对话历史表，用于存储会话记录</span>
        <span class="bp">self</span><span class="o">.</span><span class="n">init_conversation_table</span><span class="p">()</span>
</code></pre></div>
<h3 id="3">3 对话历史表初始化<a class="headerlink" href="#3" title="Permanent link">¶</a></h3>
<ul>
<li>(<code>init_conversation_table</code>) 方法</li>
<li><strong>功能</strong>：在 MySQL 中创建 <code>conversations</code> 表，存储会话 ID、问题、答案和时间戳，添加索引优化查询。</li>
<li><strong>关键点</strong>：使用 <code>IF NOT EXISTS</code> 避免重复创建，异常处理确保健壮性。</li>
</ul>
<div class="highlight"><pre><span></span><code>    <span class="k">def</span><span class="w"> </span><span class="nf">init_conversation_table</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="w">        </span><span class="sd">"""初始化MySQL中的conversations表，用于存储对话历史"""</span>
        <span class="k">try</span><span class="p">:</span>
            <span class="c1"># 创建 conversations 表，包含会话 ID、问题、答案和时间戳</span>
            <span class="bp">self</span><span class="o">.</span><span class="n">mysql_client</span><span class="o">.</span><span class="n">cursor</span><span class="o">.</span><span class="n">execute</span><span class="p">(</span><span class="s2">"""</span>
<span class="s2">                CREATE TABLE IF NOT EXISTS conversations (</span>
<span class="s2">                    id INT AUTO_INCREMENT PRIMARY KEY,</span>
<span class="s2">                    session_id VARCHAR(36) NOT NULL,</span>
<span class="s2">                    question TEXT NOT NULL,</span>
<span class="s2">                    answer TEXT NOT NULL,</span>
<span class="s2">                    timestamp DATETIME NOT NULL,</span>
<span class="s2">                    INDEX idx_session_id (session_id)</span>
<span class="s2">                )</span>
<span class="s2">            """</span><span class="p">)</span>
            <span class="c1"># 提交数据库事务</span>
            <span class="bp">self</span><span class="o">.</span><span class="n">mysql_client</span><span class="o">.</span><span class="n">connection</span><span class="o">.</span><span class="n">commit</span><span class="p">()</span>
            <span class="c1"># 记录表初始化成功的日志</span>
            <span class="bp">self</span><span class="o">.</span><span class="n">logger</span><span class="o">.</span><span class="n">info</span><span class="p">(</span><span class="s2">"对话历史表初始化成功"</span><span class="p">)</span>
        <span class="k">except</span> <span class="n">pymysql</span><span class="o">.</span><span class="n">MySQLError</span> <span class="k">as</span> <span class="n">e</span><span class="p">:</span>
            <span class="c1"># 记录表初始化失败的错误日志</span>
            <span class="bp">self</span><span class="o">.</span><span class="n">logger</span><span class="o">.</span><span class="n">error</span><span class="p">(</span><span class="sa">f</span><span class="s2">"初始化对话历史表失败: </span><span class="si">{</span><span class="n">e</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
            <span class="c1"># 抛出异常，终止初始化</span>
            <span class="k">raise</span>
</code></pre></div>
<h3 id="4-dashscope-api">4 调用 DashScope API<a class="headerlink" href="#4-dashscope-api" title="Permanent link">¶</a></h3>
<ul>
<li>(<code>call_dashscope</code>) 方法</li>
<li><strong>功能</strong>：通过 OpenAI 客户端调用 DashScope API，支持流式输出，逐 token 返回答案。</li>
<li><strong>关键点</strong>：启用 <code>stream=True</code> 实现流式输出，异常处理捕获 API 调用失败，支持前端实时显示。</li>
</ul>
<div class="highlight"><pre><span></span><code>    <span class="k">def</span><span class="w"> </span><span class="nf">call_dashscope</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">prompt</span><span class="p">):</span>
<span class="w">        </span><span class="sd">"""调用DashScope API生成答案（流式输出）"""</span>
        <span class="k">try</span><span class="p">:</span>
            <span class="c1"># 创建聊天完成请求，启用流式输出</span>
            <span class="n">completion</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">client</span><span class="o">.</span><span class="n">chat</span><span class="o">.</span><span class="n">completions</span><span class="o">.</span><span class="n">create</span><span class="p">(</span>
                <span class="n">model</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">config</span><span class="o">.</span><span class="n">LLM_MODEL</span><span class="p">,</span>  <span class="c1"># 使用配置中的语言模型</span>
                <span class="n">messages</span><span class="o">=</span><span class="p">[</span>
                    <span class="p">{</span><span class="s2">"role"</span><span class="p">:</span> <span class="s2">"system"</span><span class="p">,</span> <span class="s2">"content"</span><span class="p">:</span> <span class="s2">"你是一个有用的助手。"</span><span class="p">},</span>  <span class="c1"># 系统提示</span>
                    <span class="p">{</span><span class="s2">"role"</span><span class="p">:</span> <span class="s2">"user"</span><span class="p">,</span> <span class="s2">"content"</span><span class="p">:</span> <span class="n">prompt</span><span class="p">},</span>  <span class="c1"># 用户输入的提示</span>
                <span class="p">],</span>
                <span class="n">timeout</span><span class="o">=</span><span class="mi">30</span><span class="p">,</span>  <span class="c1"># 设置 30 秒超时</span>
                <span class="n">stream</span><span class="o">=</span><span class="kc">True</span>  <span class="c1"># 启用流式输出</span>
            <span class="p">)</span>
            <span class="c1"># 初始化收集流式输出的字符串</span>
            <span class="n">collected_content</span> <span class="o">=</span> <span class="s2">""</span>
            <span class="c1"># 遍历流式输出的每个 chunk</span>
            <span class="k">for</span> <span class="n">chunk</span> <span class="ow">in</span> <span class="n">completion</span><span class="p">:</span>
                <span class="k">if</span> <span class="n">chunk</span><span class="o">.</span><span class="n">choices</span> <span class="ow">and</span> <span class="n">chunk</span><span class="o">.</span><span class="n">choices</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="o">.</span><span class="n">delta</span><span class="o">.</span><span class="n">content</span><span class="p">:</span>
                    <span class="c1"># 获取当前 chunk 的内容</span>
                    <span class="n">content</span> <span class="o">=</span> <span class="n">chunk</span><span class="o">.</span><span class="n">choices</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="o">.</span><span class="n">delta</span><span class="o">.</span><span class="n">content</span>
                    <span class="c1"># 累积内容</span>
                    <span class="n">collected_content</span> <span class="o">+=</span> <span class="n">content</span>
                    <span class="c1"># 逐 token 返回，供前端实时显示</span>
                    <span class="k">yield</span> <span class="n">content</span>
            <span class="c1"># 返回完整答案</span>
            <span class="k">return</span> <span class="n">collected_content</span>
        <span class="k">except</span> <span class="ne">Exception</span> <span class="k">as</span> <span class="n">e</span><span class="p">:</span>
            <span class="c1"># 记录 API 调用失败的错误日志</span>
            <span class="bp">self</span><span class="o">.</span><span class="n">logger</span><span class="o">.</span><span class="n">error</span><span class="p">(</span><span class="sa">f</span><span class="s2">"LLM调用失败: </span><span class="si">{</span><span class="n">e</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
            <span class="c1"># 返回错误信息</span>
            <span class="k">return</span> <span class="sa">f</span><span class="s2">"错误：LLM调用失败 - </span><span class="si">{</span><span class="n">e</span><span class="si">}</span><span class="s2">"</span>
</code></pre></div>
<h3 id="5">5 获取最近对话历史<a class="headerlink" href="#5" title="Permanent link">¶</a></h3>
<ul>
<li>(<code>_fetch_recent_history</code>) 方法</li>
<li><strong>功能</strong>：从 MySQL 的 <code>conversations</code> 表获取指定 <code>session_id</code> 的最近 5 轮对话历史。</li>
<li><strong>关键点</strong>：使用参数化查询防止 SQL 注入，返回结果按时间正序，异常处理确保健壮性。</li>
</ul>
<div class="highlight"><pre><span></span><code>    <span class="k">def</span><span class="w"> </span><span class="nf">_fetch_recent_history</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">session_id</span><span class="p">:</span> <span class="nb">str</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">list</span><span class="p">:</span>
<span class="w">        </span><span class="sd">"""获取最近5轮对话历史"""</span>
        <span class="k">try</span><span class="p">:</span>
            <span class="c1"># 执行 SQL 查询，获取最近 5 轮对话</span>
            <span class="bp">self</span><span class="o">.</span><span class="n">mysql_client</span><span class="o">.</span><span class="n">cursor</span><span class="o">.</span><span class="n">execute</span><span class="p">(</span><span class="s2">"""</span>
<span class="s2">                SELECT question, answer</span>
<span class="s2">                FROM conversations</span>
<span class="s2">                WHERE session_id = </span><span class="si">%s</span>
<span class="s2">                ORDER BY timestamp DESC</span>
<span class="s2">                LIMIT </span><span class="si">%s</span>
<span class="s2">            """</span><span class="p">,</span> <span class="p">(</span><span class="n">session_id</span><span class="p">,</span> <span class="mi">5</span><span class="p">))</span>
            <span class="c1"># 将查询结果转换为字典列表</span>
            <span class="n">history</span> <span class="o">=</span> <span class="p">[{</span><span class="s2">"question"</span><span class="p">:</span> <span class="n">row</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="s2">"answer"</span><span class="p">:</span> <span class="n">row</span><span class="p">[</span><span class="mi">1</span><span class="p">]}</span> <span class="k">for</span> <span class="n">row</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">mysql_client</span><span class="o">.</span><span class="n">cursor</span><span class="o">.</span><span class="n">fetchall</span><span class="p">()]</span>
            <span class="c1"># 反转结果，按时间正序返回</span>
            <span class="k">return</span> <span class="n">history</span><span class="p">[::</span><span class="o">-</span><span class="mi">1</span><span class="p">]</span>
        <span class="k">except</span> <span class="n">pymysql</span><span class="o">.</span><span class="n">MySQLError</span> <span class="k">as</span> <span class="n">e</span><span class="p">:</span>
            <span class="c1"># 记录查询失败的错误日志</span>
            <span class="bp">self</span><span class="o">.</span><span class="n">logger</span><span class="o">.</span><span class="n">error</span><span class="p">(</span><span class="sa">f</span><span class="s2">"获取对话历史失败: </span><span class="si">{</span><span class="n">e</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
            <span class="c1"># 返回空列表</span>
            <span class="k">return</span> <span class="p">[]</span>
</code></pre></div>
<h3 id="6">6 更新会话历史<a class="headerlink" href="#6" title="Permanent link">¶</a></h3>
<ul>
<li>(<code>update_session_history</code>) 方法</li>
<li><strong>功能</strong>：将新问题和答案插入 <code>conversations</code> 表，保留最近 5 轮对话，删除旧记录。</li>
<li><strong>关键点</strong>：使用事务确保数据一致性，子查询删除超出限制的记录，日志记录操作结果。</li>
</ul>
<div class="highlight"><pre><span></span><code>    <span class="k">def</span><span class="w"> </span><span class="nf">update_session_history</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">session_id</span><span class="p">:</span> <span class="nb">str</span><span class="p">,</span> <span class="n">question</span><span class="p">:</span> <span class="nb">str</span><span class="p">,</span> <span class="n">answer</span><span class="p">:</span> <span class="nb">str</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">list</span><span class="p">:</span>
<span class="w">        </span><span class="sd">"""更新会话历史到MySQL，保留最近5轮对话"""</span>
        <span class="k">try</span><span class="p">:</span>
            <span class="c1"># 插入新的对话记录</span>
            <span class="bp">self</span><span class="o">.</span><span class="n">mysql_client</span><span class="o">.</span><span class="n">cursor</span><span class="o">.</span><span class="n">execute</span><span class="p">(</span><span class="s2">"""</span>
<span class="s2">                INSERT INTO conversations (session_id, question, answer, timestamp)</span>
<span class="s2">                VALUES (</span><span class="si">%s</span><span class="s2">, </span><span class="si">%s</span><span class="s2">, </span><span class="si">%s</span><span class="s2">, NOW())</span>
<span class="s2">            """</span><span class="p">,</span> <span class="p">(</span><span class="n">session_id</span><span class="p">,</span> <span class="n">question</span><span class="p">,</span> <span class="n">answer</span><span class="p">))</span>
            <span class="c1"># 获取更新后的对话历史</span>
            <span class="n">history</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">_fetch_recent_history</span><span class="p">(</span><span class="n">session_id</span><span class="p">)</span>
            <span class="c1"># 删除超出 5 轮的旧记录</span>
            <span class="bp">self</span><span class="o">.</span><span class="n">mysql_client</span><span class="o">.</span><span class="n">cursor</span><span class="o">.</span><span class="n">execute</span><span class="p">(</span><span class="s2">"""</span>
<span class="s2">                DELETE FROM conversations</span>
<span class="s2">                WHERE session_id = </span><span class="si">%s</span><span class="s2"> AND id NOT IN (</span>
<span class="s2">                    SELECT id FROM (</span>
<span class="s2">                        SELECT id</span>
<span class="s2">                        FROM conversations</span>
<span class="s2">                        WHERE session_id = </span><span class="si">%s</span>
<span class="s2">                        ORDER BY timestamp DESC</span>
<span class="s2">                        LIMIT </span><span class="si">%s</span>
<span class="s2">                    ) AS sub</span>
<span class="s2">                )</span>
<span class="s2">            """</span><span class="p">,</span> <span class="p">(</span><span class="n">session_id</span><span class="p">,</span> <span class="n">session_id</span><span class="p">,</span> <span class="mi">5</span><span class="p">))</span>
            <span class="c1"># 提交事务</span>
            <span class="bp">self</span><span class="o">.</span><span class="n">mysql_client</span><span class="o">.</span><span class="n">connection</span><span class="o">.</span><span class="n">commit</span><span class="p">()</span>
            <span class="c1"># 记录更新成功的日志</span>
            <span class="bp">self</span><span class="o">.</span><span class="n">logger</span><span class="o">.</span><span class="n">info</span><span class="p">(</span><span class="sa">f</span><span class="s2">"会话 </span><span class="si">{</span><span class="n">session_id</span><span class="si">}</span><span class="s2"> 历史更新成功"</span><span class="p">)</span>
            <span class="c1"># 返回更新后的历史</span>
            <span class="k">return</span> <span class="n">history</span>
        <span class="k">except</span> <span class="n">pymysql</span><span class="o">.</span><span class="n">MySQLError</span> <span class="k">as</span> <span class="n">e</span><span class="p">:</span>
            <span class="c1"># 记录数据库操作失败的错误日志</span>
            <span class="bp">self</span><span class="o">.</span><span class="n">logger</span><span class="o">.</span><span class="n">error</span><span class="p">(</span><span class="sa">f</span><span class="s2">"更新会话历史失败: </span><span class="si">{</span><span class="n">e</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
            <span class="c1"># 回滚事务</span>
            <span class="bp">self</span><span class="o">.</span><span class="n">mysql_client</span><span class="o">.</span><span class="n">connection</span><span class="o">.</span><span class="n">rollback</span><span class="p">()</span>
            <span class="c1"># 抛出异常</span>
            <span class="k">raise</span>
        <span class="k">except</span> <span class="ne">Exception</span> <span class="k">as</span> <span class="n">e</span><span class="p">:</span>
            <span class="c1"># 记录意外错误的日志</span>
            <span class="bp">self</span><span class="o">.</span><span class="n">logger</span><span class="o">.</span><span class="n">error</span><span class="p">(</span><span class="sa">f</span><span class="s2">"更新会话历史意外错误: </span><span class="si">{</span><span class="n">e</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
            <span class="c1"># 回滚事务</span>
            <span class="bp">self</span><span class="o">.</span><span class="n">mysql_client</span><span class="o">.</span><span class="n">connection</span><span class="o">.</span><span class="n">rollback</span><span class="p">()</span>
            <span class="c1"># 抛出异常</span>
            <span class="k">raise</span>
</code></pre></div>
<h3 id="7">7 获取会话历史<a class="headerlink" href="#7" title="Permanent link">¶</a></h3>
<ul>
<li>(<code>get_session_history</code>) 方法</li>
<li><strong>功能</strong>：从 MySQL 获取指定 <code>session_id</code> 的对话历史，复用 <code>_fetch_recent_history</code>。</li>
<li><strong>关键点</strong>：保持代码简洁，适合外部调用（如 API 或界面展示）。</li>
</ul>
<div class="highlight"><pre><span></span><code>    <span class="k">def</span><span class="w"> </span><span class="nf">get_session_history</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">session_id</span><span class="p">:</span> <span class="nb">str</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">list</span><span class="p">:</span>
<span class="w">        </span><span class="sd">"""从MySQL获取会话历史"""</span>
        <span class="c1"># 调用 _fetch_recent_history 获取对话历史</span>
        <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">_fetch_recent_history</span><span class="p">(</span><span class="n">session_id</span><span class="p">)</span>
</code></pre></div>
<h3 id="8">8 清除会话历史<a class="headerlink" href="#8" title="Permanent link">¶</a></h3>
<ul>
<li>(<code>clear_session_history</code>) 方法</li>
<li><strong>功能</strong>：删除指定 <code>session_id</code> 的所有对话历史记录。</li>
<li><strong>关键点</strong>：使用参数化查询防止 SQL 注入，事务管理确保操作原子性，返回布尔值表示成功或失败。</li>
</ul>
<div class="highlight"><pre><span></span><code>    <span class="k">def</span><span class="w"> </span><span class="nf">clear_session_history</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">session_id</span><span class="p">:</span> <span class="nb">str</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">bool</span><span class="p">:</span>
<span class="w">        </span><span class="sd">"""清除指定会话历史"""</span>
        <span class="k">try</span><span class="p">:</span>
            <span class="c1"># 删除指定 session_id 的所有对话记录</span>
            <span class="bp">self</span><span class="o">.</span><span class="n">mysql_client</span><span class="o">.</span><span class="n">cursor</span><span class="o">.</span><span class="n">execute</span><span class="p">(</span><span class="s2">"""</span>
<span class="s2">                DELETE FROM conversations</span>
<span class="s2">                WHERE session_id = </span><span class="si">%s</span>
<span class="s2">            """</span><span class="p">,</span> <span class="p">(</span><span class="n">session_id</span><span class="p">,))</span>
            <span class="c1"># 提交事务</span>
            <span class="bp">self</span><span class="o">.</span><span class="n">mysql_client</span><span class="o">.</span><span class="n">connection</span><span class="o">.</span><span class="n">commit</span><span class="p">()</span>
            <span class="c1"># 记录清除成功的日志</span>
            <span class="bp">self</span><span class="o">.</span><span class="n">logger</span><span class="o">.</span><span class="n">info</span><span class="p">(</span><span class="sa">f</span><span class="s2">"会话 </span><span class="si">{</span><span class="n">session_id</span><span class="si">}</span><span class="s2"> 历史已清除"</span><span class="p">)</span>
            <span class="c1"># 返回 True 表示成功</span>
            <span class="k">return</span> <span class="kc">True</span>
        <span class="k">except</span> <span class="n">pymysql</span><span class="o">.</span><span class="n">MySQLError</span> <span class="k">as</span> <span class="n">e</span><span class="p">:</span>
            <span class="c1"># 记录清除失败的错误日志</span>
            <span class="bp">self</span><span class="o">.</span><span class="n">logger</span><span class="o">.</span><span class="n">error</span><span class="p">(</span><span class="sa">f</span><span class="s2">"清除会话历史失败: </span><span class="si">{</span><span class="n">e</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
            <span class="c1"># 回滚事务</span>
            <span class="bp">self</span><span class="o">.</span><span class="n">mysql_client</span><span class="o">.</span><span class="n">connection</span><span class="o">.</span><span class="n">rollback</span><span class="p">()</span>
            <span class="c1"># 返回 False 表示失败</span>
            <span class="k">return</span> <span class="kc">False</span>
</code></pre></div>
<h3 id="9">9 查询处理<a class="headerlink" href="#9" title="Permanent link">¶</a></h3>
<ul>
<li>
<p>(<code>query</code>) 方法</p>
</li>
<li>
<p><strong>功能</strong>：处理用户查询，优先使用 BM25 搜索 MySQL，若无可靠答案则回退到 RAG，支持流式输出和对话历史。</p>
</li>
<li>
<p><strong>关键点</strong>：通过生成器逐 token 返回 RAG 答案，记录处理时间，支持知识域过滤。</p>
</li>
<li>
<blockquote>
<p>注意：1.修改generate_answer方法添加history参数，2.修改rag_prompt方法的提示词</p>
</blockquote>
</li>
</ul>
<div class="highlight"><pre><span></span><code>    <span class="k">def</span><span class="w"> </span><span class="nf">query</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">query</span><span class="p">,</span> <span class="n">source_filter</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">session_id</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span>
<span class="w">        </span><span class="sd">"""查询集成系统，支持对话历史和流式输出"""</span>
        <span class="n">start_time</span> <span class="o">=</span> <span class="n">time</span><span class="o">.</span><span class="n">time</span><span class="p">()</span>  <span class="c1"># 记录查询开始时间</span>
        <span class="c1"># 记录查询信息到日志</span>
        <span class="bp">self</span><span class="o">.</span><span class="n">logger</span><span class="o">.</span><span class="n">info</span><span class="p">(</span><span class="sa">f</span><span class="s2">"处理查询: '</span><span class="si">{</span><span class="n">query</span><span class="si">}</span><span class="s2">' (会话ID: </span><span class="si">{</span><span class="n">session_id</span><span class="si">}</span><span class="s2">)"</span><span class="p">)</span>
        <span class="c1"># 获取对话历史，若无 session_id 则返回空列表</span>
        <span class="n">history</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">get_session_history</span><span class="p">(</span><span class="n">session_id</span><span class="p">)</span> <span class="k">if</span> <span class="n">session_id</span> <span class="k">else</span> <span class="p">[]</span>
        <span class="c1"># 执行 BM25 搜索，获取答案和是否需要 RAG 的标志</span>
        <span class="n">answer</span><span class="p">,</span> <span class="n">need_rag</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">bm25_search</span><span class="o">.</span><span class="n">search</span><span class="p">(</span><span class="n">query</span><span class="p">,</span> <span class="n">threshold</span><span class="o">=</span><span class="mf">0.85</span><span class="p">)</span>
        <span class="k">if</span> <span class="n">answer</span><span class="p">:</span>
            <span class="c1"># 如果找到可靠答案，记录答案到日志</span>
            <span class="bp">self</span><span class="o">.</span><span class="n">logger</span><span class="o">.</span><span class="n">info</span><span class="p">(</span><span class="sa">f</span><span class="s2">"MySQL答案: </span><span class="si">{</span><span class="n">answer</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
            <span class="k">if</span> <span class="n">session_id</span><span class="p">:</span>
                <span class="c1"># 更新对话历史</span>
                <span class="bp">self</span><span class="o">.</span><span class="n">update_session_history</span><span class="p">(</span><span class="n">session_id</span><span class="p">,</span> <span class="n">query</span><span class="p">,</span> <span class="n">answer</span><span class="p">)</span>
            <span class="c1"># 计算处理时间</span>
            <span class="n">processing_time</span> <span class="o">=</span> <span class="n">time</span><span class="o">.</span><span class="n">time</span><span class="p">()</span> <span class="o">-</span> <span class="n">start_time</span>
            <span class="c1"># 记录处理时间到日志</span>
            <span class="bp">self</span><span class="o">.</span><span class="n">logger</span><span class="o">.</span><span class="n">info</span><span class="p">(</span><span class="sa">f</span><span class="s2">"查询处理耗时 </span><span class="si">{</span><span class="n">processing_time</span><span class="si">:</span><span class="s2">.2f</span><span class="si">}</span><span class="s2">秒"</span><span class="p">)</span>
            <span class="c1"># 一次性返回答案，标记为完整</span>
            <span class="k">yield</span> <span class="n">answer</span><span class="p">,</span> <span class="kc">True</span>
        <span class="k">elif</span> <span class="n">need_rag</span><span class="p">:</span>
            <span class="c1"># 如果需要 RAG，记录回退信息到日志</span>
            <span class="bp">self</span><span class="o">.</span><span class="n">logger</span><span class="o">.</span><span class="n">info</span><span class="p">(</span><span class="s2">"无可靠MySQL答案，回退到RAG"</span><span class="p">)</span>
            <span class="c1"># 初始化收集完整答案的字符串</span>
            <span class="n">collected_answer</span> <span class="o">=</span> <span class="s2">""</span>
            <span class="c1"># 从 RAG 系统获取流式输出</span>
            <span class="k">for</span> <span class="n">token</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">rag_system</span><span class="o">.</span><span class="n">generate_answer</span><span class="p">(</span><span class="n">query</span><span class="p">,</span> <span class="n">source_filter</span><span class="o">=</span><span class="n">source_filter</span><span class="p">,</span> <span class="n">history</span><span class="o">=</span><span class="n">history</span><span class="p">):</span>
                <span class="c1"># 累积答案</span>
                <span class="n">collected_answer</span> <span class="o">+=</span> <span class="n">token</span>
                <span class="c1"># 逐 token 返回，标记为部分答案</span>
                <span class="k">yield</span> <span class="n">token</span><span class="p">,</span> <span class="kc">False</span>
            <span class="k">if</span> <span class="n">session_id</span><span class="p">:</span>
                <span class="c1"># 更新对话历史，存储完整答案</span>
                <span class="bp">self</span><span class="o">.</span><span class="n">update_session_history</span><span class="p">(</span><span class="n">session_id</span><span class="p">,</span> <span class="n">query</span><span class="p">,</span> <span class="n">collected_answer</span><span class="p">)</span>
            <span class="c1"># 计算处理时间</span>
            <span class="n">processing_time</span> <span class="o">=</span> <span class="n">time</span><span class="o">.</span><span class="n">time</span><span class="p">()</span> <span class="o">-</span> <span class="n">start_time</span>
            <span class="c1"># 记录处理时间到日志</span>
            <span class="bp">self</span><span class="o">.</span><span class="n">logger</span><span class="o">.</span><span class="n">info</span><span class="p">(</span><span class="sa">f</span><span class="s2">"查询处理耗时 </span><span class="si">{</span><span class="n">processing_time</span><span class="si">:</span><span class="s2">.2f</span><span class="si">}</span><span class="s2">秒"</span><span class="p">)</span>
            <span class="c1"># 返回空字符串，标记流结束</span>
            <span class="k">yield</span> <span class="s2">""</span><span class="p">,</span> <span class="kc">True</span>
        <span class="k">else</span><span class="p">:</span>
            <span class="c1"># 如果无答案，记录信息到日志</span>
            <span class="bp">self</span><span class="o">.</span><span class="n">logger</span><span class="o">.</span><span class="n">info</span><span class="p">(</span><span class="s2">"未找到答案"</span><span class="p">)</span>
            <span class="c1"># 计算处理时间</span>
            <span class="n">processing_time</span> <span class="o">=</span> <span class="n">time</span><span class="o">.</span><span class="n">time</span><span class="p">()</span> <span class="o">-</span> <span class="n">start_time</span>
            <span class="c1"># 记录处理时间到日志</span>
            <span class="bp">self</span><span class="o">.</span><span class="n">logger</span><span class="o">.</span><span class="n">info</span><span class="p">(</span><span class="sa">f</span><span class="s2">"查询处理耗时 </span><span class="si">{</span><span class="n">processing_time</span><span class="si">:</span><span class="s2">.2f</span><span class="si">}</span><span class="s2">秒"</span><span class="p">)</span>
            <span class="c1"># 一次性返回默认答案，标记为完整</span>
            <span class="k">yield</span> <span class="s2">"未找到答案"</span><span class="p">,</span> <span class="kc">True</span>
</code></pre></div>
<h3 id="10-rag_system">10 改造rag_system<a class="headerlink" href="#10-rag_system" title="Permanent link">¶</a></h3>
<p>上述代码中我们构建了一个RAGSystem，传入了历史对话变量，并进行查询，很明显原来的功能无法支持。</p>
<p>我们这里新建一个new_rag_system，重写查询相关逻辑。</p>
<p>在修改rag_system之前，我们首先需要做的是在Augment的提示词模板中加入history部分，目前只有context和query，修改后如下：</p>
<div class="highlight"><pre><span></span><code><span class="c1"># core/prompts.py</span>
<span class="c1"># 定义 RAGPrompts 类，用于管理所有 Prompt 模板</span>
<span class="k">class</span><span class="w"> </span><span class="nc">RAGPrompts</span><span class="p">:</span>
    <span class="c1"># 定义 RAG 提示模板</span>
    <span class="nd">@staticmethod</span>
    <span class="k">def</span><span class="w"> </span><span class="nf">rag_prompt</span><span class="p">():</span>
        <span class="c1"># 创建并返回 PromptTemplate 对象</span>
        <span class="k">return</span> <span class="n">PromptTemplate</span><span class="p">(</span>
            <span class="n">template</span><span class="o">=</span><span class="s2">"""  </span>
<span class="s2">            你是一个智能助手，帮助用户回答问题。请参考用户的助手的对话历史和上下文回答问题。</span>
<span class="s2">            如果提供了上下文，请基于上下文回答；如果没有上下文，请直接根据你的知识回答。  </span>
<span class="s2">            如果答案来源于检索到的文档，请在回答中说明。</span>

<span class="s2">            对话历史: </span><span class="si">{history}</span>
<span class="s2">            上下文: </span><span class="si">{context}</span><span class="s2">  </span>
<span class="s2">            问题: </span><span class="si">{question}</span><span class="s2">  </span>

<span class="s2">            如果无法回答，请回复：“信息不足，无法回答，请联系人工客服，电话：</span><span class="si">{phone}</span><span class="s2">。”  </span>
<span class="s2">            回答:  </span>
<span class="s2">            """</span><span class="p">,</span>
            <span class="c1">#   定义输入变量</span>
            <span class="n">input_variables</span><span class="o">=</span><span class="p">[</span><span class="s2">"context"</span><span class="p">,</span> <span class="s2">"history"</span><span class="p">,</span> <span class="s2">"question"</span><span class="p">,</span> <span class="s2">"phone"</span><span class="p">],</span>
        <span class="p">)</span>
</code></pre></div>
<p>然后创建新的类<code>rag_qa/core/new_rag_system.py</code>，并支持hitsory。因前面我们已经详细讲过rag_system的源码，这里我们直接把修改后的代码展现：</p>
<div class="highlight"><pre><span></span><code><span class="kn">from</span><span class="w"> </span><span class="nn">rag_qa.core.prompts</span><span class="w"> </span><span class="kn">import</span> <span class="n">RAGPrompts</span>
<span class="c1">#   导入 time 模块，用于计算时间</span>
<span class="kn">import</span><span class="w"> </span><span class="nn">time</span>
<span class="kn">from</span><span class="w"> </span><span class="nn">base.config</span><span class="w"> </span><span class="kn">import</span> <span class="n">config</span>
<span class="kn">from</span><span class="w"> </span><span class="nn">base.logger</span><span class="w"> </span><span class="kn">import</span> <span class="n">logger</span>
<span class="kn">from</span><span class="w"> </span><span class="nn">rag_qa.core.query_classifier</span><span class="w"> </span><span class="kn">import</span> <span class="n">QueryClassifier</span>  <span class="c1"># 导入查询分类器</span>
<span class="kn">from</span><span class="w"> </span><span class="nn">rag_qa.core.strategy_selector</span><span class="w"> </span><span class="kn">import</span> <span class="n">StrategySelector</span>  <span class="c1"># 导入策略选择器</span>


<span class="k">class</span><span class="w"> </span><span class="nc">RAGSystem</span><span class="p">:</span>

    <span class="k">def</span><span class="w"> </span><span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">vector_store</span><span class="p">,</span> <span class="n">llm</span><span class="p">):</span>
        <span class="c1">#   设置向量数据库对象</span>
        <span class="bp">self</span><span class="o">.</span><span class="n">vector_store</span> <span class="o">=</span> <span class="n">vector_store</span>
        <span class="c1">#   设置大语言模型调用函数</span>
        <span class="bp">self</span><span class="o">.</span><span class="n">llm</span> <span class="o">=</span> <span class="n">llm</span>
        <span class="c1">#   获取 RAG 提示模板</span>
        <span class="bp">self</span><span class="o">.</span><span class="n">rag_prompt</span> <span class="o">=</span> <span class="n">RAGPrompts</span><span class="o">.</span><span class="n">rag_prompt</span><span class="p">()</span>
        <span class="c1">#   初始化查询分类器</span>
        <span class="kn">from</span><span class="w"> </span><span class="nn">base.config</span><span class="w"> </span><span class="kn">import</span> <span class="n">config</span>
        <span class="bp">self</span><span class="o">.</span><span class="n">query_classifier</span> <span class="o">=</span> <span class="n">QueryClassifier</span><span class="p">(</span>
            <span class="n">model_path</span><span class="o">=</span><span class="sa">f</span><span class="s1">'</span><span class="si">{</span><span class="n">config</span><span class="o">.</span><span class="n">MODELS_DIR</span><span class="si">}</span><span class="s1">/bert_query_classifier'</span><span class="p">)</span>
        <span class="c1">#   初始化策略选择器</span>
        <span class="bp">self</span><span class="o">.</span><span class="n">strategy_selector</span> <span class="o">=</span> <span class="n">StrategySelector</span><span class="p">()</span>

    <span class="k">def</span><span class="w"> </span><span class="nf">_retrieve_with_hyde</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">query</span><span class="p">):</span>
        <span class="n">logger</span><span class="o">.</span><span class="n">info</span><span class="p">(</span><span class="sa">f</span><span class="s2">"使用 HyDE 策略进行检索 (查询: '</span><span class="si">{</span><span class="n">query</span><span class="si">}</span><span class="s2">')"</span><span class="p">)</span>
        <span class="c1">#   获取假设问题生成的 Prompt 模板</span>
        <span class="n">hyde_prompt_template</span> <span class="o">=</span> <span class="n">RAGPrompts</span><span class="o">.</span><span class="n">hyde_prompt</span><span class="p">()</span>  <span class="c1"># 使用 template 后缀区分</span>
        <span class="c1">#   调用大语言模型生成假设答案</span>
        <span class="k">try</span><span class="p">:</span>
            <span class="n">hypo_answer</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">llm</span><span class="p">(</span><span class="n">hyde_prompt_template</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">query</span><span class="o">=</span><span class="n">query</span><span class="p">))</span>
            <span class="n">logger</span><span class="o">.</span><span class="n">info</span><span class="p">(</span><span class="sa">f</span><span class="s2">"HyDE 生成的假设答案: '</span><span class="si">{</span><span class="n">hypo_answer</span><span class="si">}</span><span class="s2">'"</span><span class="p">)</span>
            <span class="c1">#   使用假设答案进行检索，并返回检索结果</span>
            <span class="c1">#   注意：HyDE 通常只用于生成检索向量，不一定需要 rerank 这一步，但这里复用了</span>
            <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">vector_store</span><span class="o">.</span><span class="n">hybrid_search_with_rerank</span><span class="p">(</span>
                <span class="n">hypo_answer</span><span class="p">,</span> <span class="n">k</span><span class="o">=</span><span class="n">config</span><span class="o">.</span><span class="n">RETRIEVAL_K</span>  <span class="c1"># 使用 K 而非 M</span>
            <span class="p">)</span>
        <span class="k">except</span> <span class="ne">Exception</span> <span class="k">as</span> <span class="n">e</span><span class="p">:</span>
            <span class="n">logger</span><span class="o">.</span><span class="n">error</span><span class="p">(</span><span class="sa">f</span><span class="s2">"HyDE 策略执行失败: </span><span class="si">{</span><span class="n">e</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
            <span class="k">return</span> <span class="p">[]</span>

    <span class="k">def</span><span class="w"> </span><span class="nf">_retrieve_with_subqueries</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">query</span><span class="p">):</span>
        <span class="n">logger</span><span class="o">.</span><span class="n">info</span><span class="p">(</span><span class="sa">f</span><span class="s2">"使用子查询策略进行检索 (查询: '</span><span class="si">{</span><span class="n">query</span><span class="si">}</span><span class="s2">')"</span><span class="p">)</span>
        <span class="c1">#   获取子查询生成的 Prompt 模板</span>
        <span class="n">subquery_prompt_template</span> <span class="o">=</span> <span class="n">RAGPrompts</span><span class="o">.</span><span class="n">subquery_prompt</span><span class="p">()</span>  <span class="c1"># 使用 template 后缀区分</span>
        <span class="k">try</span><span class="p">:</span>
            <span class="c1">#   调用大语言模型生成子查询列表</span>
            <span class="n">subqueries_text</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">llm</span><span class="p">(</span><span class="n">subquery_prompt_template</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">query</span><span class="o">=</span><span class="n">query</span><span class="p">))</span>
            <span class="n">subqueries</span> <span class="o">=</span> <span class="p">[</span><span class="n">q</span><span class="o">.</span><span class="n">strip</span><span class="p">()</span> <span class="k">for</span> <span class="n">q</span> <span class="ow">in</span> <span class="n">subqueries_text</span><span class="o">.</span><span class="n">split</span><span class="p">(</span><span class="s2">"</span><span class="se">\n</span><span class="s2">"</span><span class="p">)</span> <span class="k">if</span> <span class="n">q</span><span class="o">.</span><span class="n">strip</span><span class="p">()]</span>
            <span class="n">logger</span><span class="o">.</span><span class="n">info</span><span class="p">(</span><span class="sa">f</span><span class="s2">"生成的子查询: </span><span class="si">{</span><span class="n">subqueries</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
            <span class="k">if</span> <span class="ow">not</span> <span class="n">subqueries</span><span class="p">:</span>
                <span class="n">logger</span><span class="o">.</span><span class="n">warning</span><span class="p">(</span><span class="s2">"未能生成有效的子查询"</span><span class="p">)</span>
                <span class="k">return</span> <span class="p">[]</span>

            <span class="c1">#   初始化空列表，用于存储所有子查询的检索结果</span>
            <span class="n">all_docs</span> <span class="o">=</span> <span class="p">[]</span>
            <span class="c1">#   遍历每个子查询</span>
            <span class="k">for</span> <span class="n">sub_q</span> <span class="ow">in</span> <span class="n">subqueries</span><span class="p">:</span>
                <span class="c1">#   使用子查询进行检索，并将结果添加到列表中</span>
                <span class="c1">#   这里对每个子查询都执行了 hybrid search + rerank，开销可能较大</span>
                <span class="n">docs</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">vector_store</span><span class="o">.</span><span class="n">hybrid_search_with_rerank</span><span class="p">(</span>
                    <span class="n">sub_q</span><span class="p">,</span> <span class="n">k</span><span class="o">=</span><span class="n">config</span><span class="o">.</span><span class="n">RETRIEVAL_K</span>  <span class="c1"># 使用 K</span>
                <span class="p">)</span>
                <span class="n">all_docs</span><span class="o">.</span><span class="n">extend</span><span class="p">(</span><span class="n">docs</span><span class="p">)</span>
                <span class="n">logger</span><span class="o">.</span><span class="n">info</span><span class="p">(</span><span class="sa">f</span><span class="s2">"子查询 '</span><span class="si">{</span><span class="n">sub_q</span><span class="si">}</span><span class="s2">' 检索到 </span><span class="si">{</span><span class="nb">len</span><span class="p">(</span><span class="n">docs</span><span class="p">)</span><span class="si">}</span><span class="s2"> 个文档"</span><span class="p">)</span>

            <span class="c1">#   对所有检索结果进行去重 (基于对象内存地址，如果 Document 内容相同但对象不同则无法去重)</span>
            <span class="c1">#   更可靠的去重方式是基于文档内容或 ID</span>
            <span class="n">unique_docs_dict</span> <span class="o">=</span> <span class="p">{</span><span class="n">doc</span><span class="o">.</span><span class="n">page_content</span><span class="p">:</span> <span class="n">doc</span> <span class="k">for</span> <span class="n">doc</span> <span class="ow">in</span> <span class="n">all_docs</span><span class="p">}</span>  <span class="c1"># 基于内容去重</span>
            <span class="n">unique_docs</span> <span class="o">=</span> <span class="nb">list</span><span class="p">(</span><span class="n">unique_docs_dict</span><span class="o">.</span><span class="n">values</span><span class="p">())</span>

            <span class="n">logger</span><span class="o">.</span><span class="n">info</span><span class="p">(</span><span class="sa">f</span><span class="s2">"所有子查询共检索到 </span><span class="si">{</span><span class="nb">len</span><span class="p">(</span><span class="n">all_docs</span><span class="p">)</span><span class="si">}</span><span class="s2"> 个文档, 去重后剩 </span><span class="si">{</span><span class="nb">len</span><span class="p">(</span><span class="n">unique_docs</span><span class="p">)</span><span class="si">}</span><span class="s2"> 个"</span><span class="p">)</span>
            <span class="c1">#   返回去重后的文档，限制数量 (是否需要在此处限制? retrieve_and_merge 末尾会限制)</span>
            <span class="c1"># return unique_docs[: Config.CANDIDATE_M]</span>
            <span class="k">return</span> <span class="n">unique_docs</span>  <span class="c1"># 返回所有唯一文档，让 retrieve_and_merge 处理数量</span>

        <span class="k">except</span> <span class="ne">Exception</span> <span class="k">as</span> <span class="n">e</span><span class="p">:</span>
            <span class="n">logger</span><span class="o">.</span><span class="n">error</span><span class="p">(</span><span class="sa">f</span><span class="s2">"子查询策略执行失败: </span><span class="si">{</span><span class="n">e</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
            <span class="k">return</span> <span class="p">[]</span>
   <span class="k">def</span><span class="w"> </span><span class="nf">_retrieve_with_backtracking</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">query</span><span class="p">):</span>
        <span class="n">logger</span><span class="o">.</span><span class="n">info</span><span class="p">(</span><span class="sa">f</span><span class="s2">"使用回溯问题策略进行检索 (查询: '</span><span class="si">{</span><span class="n">query</span><span class="si">}</span><span class="s2">')"</span><span class="p">)</span>
        <span class="c1">#   获取回溯问题生成的 Prompt 模板</span>
        <span class="n">backtrack_prompt_template</span> <span class="o">=</span> <span class="n">RAGPrompts</span><span class="o">.</span><span class="n">backtracking_prompt</span><span class="p">()</span>  <span class="c1"># 使用 template 后缀区分</span>
        <span class="k">try</span><span class="p">:</span>
            <span class="c1">#   调用大语言模型生成回溯问题</span>
            <span class="n">simplified_query</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">llm</span><span class="p">(</span><span class="n">backtrack_prompt_template</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">query</span><span class="o">=</span><span class="n">query</span><span class="p">))</span><span class="o">.</span><span class="n">strip</span><span class="p">()</span>
            <span class="n">logger</span><span class="o">.</span><span class="n">info</span><span class="p">(</span><span class="sa">f</span><span class="s2">"生成的回溯问题: '</span><span class="si">{</span><span class="n">simplified_query</span><span class="si">}</span><span class="s2">'"</span><span class="p">)</span>
            <span class="c1">#   使用回溯问题进行检索，并返回检索结果</span>
            <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">vector_store</span><span class="o">.</span><span class="n">hybrid_search_with_rerank</span><span class="p">(</span>
                <span class="n">simplified_query</span><span class="p">,</span> <span class="n">k</span><span class="o">=</span><span class="n">config</span><span class="o">.</span><span class="n">RETRIEVAL_K</span>  <span class="c1"># 使用 K</span>
            <span class="p">)</span>
        <span class="k">except</span> <span class="ne">Exception</span> <span class="k">as</span> <span class="n">e</span><span class="p">:</span>
            <span class="n">logger</span><span class="o">.</span><span class="n">error</span><span class="p">(</span><span class="sa">f</span><span class="s2">"回溯问题策略执行失败: </span><span class="si">{</span><span class="n">e</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
            <span class="k">return</span> <span class="p">[]</span>

    <span class="k">def</span><span class="w"> </span><span class="nf">retrieve_and_merge</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">query</span><span class="p">,</span> <span class="n">source_filter</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">strategy</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span>  <span class="c1"># 新增 strategy 参数</span>
        <span class="c1">#   如果未指定检索策略，则使用策略选择器选择</span>
        <span class="k">if</span> <span class="ow">not</span> <span class="n">strategy</span><span class="p">:</span>
            <span class="n">strategy</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">strategy_selector</span><span class="o">.</span><span class="n">select_strategy</span><span class="p">(</span><span class="n">query</span><span class="p">)</span>

        <span class="c1">#   根据检索策略选择不同的检索方式</span>
        <span class="n">ranked_sub_chunks</span> <span class="o">=</span> <span class="p">[]</span>  <span class="c1"># 初始化</span>
        <span class="k">if</span> <span class="n">strategy</span> <span class="o">==</span> <span class="s2">"回溯问题检索"</span><span class="p">:</span>
            <span class="n">ranked_sub_chunks</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">_retrieve_with_backtracking</span><span class="p">(</span><span class="n">query</span><span class="p">)</span>
        <span class="k">elif</span> <span class="n">strategy</span> <span class="o">==</span> <span class="s2">"子查询检索"</span><span class="p">:</span>
            <span class="n">ranked_sub_chunks</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">_retrieve_with_subqueries</span><span class="p">(</span><span class="n">query</span><span class="p">)</span>  <span class="c1"># 返回的是唯一文档列表</span>
            <span class="c1"># 注意：子查询返回的是已 rerank 过的父文档或子块列表，后续合并逻辑可能需要调整</span>
            <span class="c1"># 当前实现中，子查询返回的是初步检索（可能已rerank）的块，再进行合并</span>
        <span class="k">elif</span> <span class="n">strategy</span> <span class="o">==</span> <span class="s2">"假设问题检索"</span><span class="p">:</span>
            <span class="n">ranked_sub_chunks</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">_retrieve_with_hyde</span><span class="p">(</span><span class="n">query</span><span class="p">)</span>
        <span class="k">else</span><span class="p">:</span>  <span class="c1"># 默认或“直接检索”</span>
            <span class="n">logger</span><span class="o">.</span><span class="n">info</span><span class="p">(</span><span class="sa">f</span><span class="s2">"使用直接检索策略 (查询: '</span><span class="si">{</span><span class="n">query</span><span class="si">}</span><span class="s2">')"</span><span class="p">)</span>
            <span class="n">ranked_sub_chunks</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">vector_store</span><span class="o">.</span><span class="n">hybrid_search_with_rerank</span><span class="p">(</span>
                <span class="n">query</span><span class="p">,</span> <span class="n">k</span><span class="o">=</span><span class="n">config</span><span class="o">.</span><span class="n">RETRIEVAL_K</span><span class="p">,</span> <span class="n">source_filter</span><span class="o">=</span><span class="n">source_filter</span>
            <span class="p">)</span>  <span class="c1"># 注意 hybrid_search_with_rerank 返回的是 rerank 后的父文档</span>

        <span class="n">logger</span><span class="o">.</span><span class="n">info</span><span class="p">(</span><span class="sa">f</span><span class="s2">"策略 '</span><span class="si">{</span><span class="n">strategy</span><span class="si">}</span><span class="s2">' 检索到 </span><span class="si">{</span><span class="nb">len</span><span class="p">(</span><span class="n">ranked_sub_chunks</span><span class="p">)</span><span class="si">}</span><span class="s2"> 个候选文档 (可能已是父文档)"</span><span class="p">)</span>
        <span class="n">final_context_docs</span> <span class="o">=</span> <span class="n">ranked_sub_chunks</span><span class="p">[:</span><span class="n">config</span><span class="o">.</span><span class="n">CANDIDATE_M</span><span class="p">]</span>
        <span class="n">logger</span><span class="o">.</span><span class="n">info</span><span class="p">(</span><span class="sa">f</span><span class="s2">"最终选取 </span><span class="si">{</span><span class="nb">len</span><span class="p">(</span><span class="n">final_context_docs</span><span class="p">)</span><span class="si">}</span><span class="s2"> 个文档作为上下文"</span><span class="p">)</span>
        <span class="k">return</span> <span class="n">final_context_docs</span>

    <span class="k">def</span><span class="w"> </span><span class="nf">generate_answer</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">query</span><span class="p">,</span> <span class="n">source_filter</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">history</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span>
<span class="w">        </span><span class="sd">"""生成答案，支持对话历史，限制提示长度，并支持流式输出"""</span>
        <span class="n">start_time</span> <span class="o">=</span> <span class="n">time</span><span class="o">.</span><span class="n">time</span><span class="p">()</span>
        <span class="n">logger</span><span class="o">.</span><span class="n">info</span><span class="p">(</span><span class="sa">f</span><span class="s2">"开始处理查询: '</span><span class="si">{</span><span class="n">query</span><span class="si">}</span><span class="s2">', 知识域过滤: </span><span class="si">{</span><span class="n">source_filter</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>

        <span class="c1"># 验证历史格式</span>
        <span class="c1"># [{}]</span>
        <span class="k">if</span> <span class="n">history</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span> <span class="ow">and</span> <span class="ow">not</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">history</span><span class="p">,</span> <span class="nb">list</span><span class="p">):</span>
            <span class="n">logger</span><span class="o">.</span><span class="n">warning</span><span class="p">(</span><span class="sa">f</span><span class="s2">"无效的历史格式: </span><span class="si">{</span><span class="nb">type</span><span class="p">(</span><span class="n">history</span><span class="p">)</span><span class="si">}</span><span class="s2">，忽略历史"</span><span class="p">)</span>
            <span class="n">history</span> <span class="o">=</span> <span class="p">[]</span>
        <span class="k">elif</span> <span class="n">history</span><span class="p">:</span>
            <span class="n">history</span> <span class="o">=</span> <span class="n">history</span><span class="p">[</span><span class="o">-</span><span class="mi">5</span><span class="p">:]</span>  <span class="c1"># 限制最多5轮</span>
            <span class="k">for</span> <span class="n">h</span> <span class="ow">in</span> <span class="n">history</span><span class="p">:</span>
                <span class="k">if</span> <span class="ow">not</span> <span class="p">(</span><span class="nb">isinstance</span><span class="p">(</span><span class="n">h</span><span class="p">,</span> <span class="nb">dict</span><span class="p">)</span> <span class="ow">and</span> <span class="s2">"question"</span> <span class="ow">in</span> <span class="n">h</span> <span class="ow">and</span> <span class="s2">"answer"</span> <span class="ow">in</span> <span class="n">h</span><span class="p">):</span>
                    <span class="n">logger</span><span class="o">.</span><span class="n">warning</span><span class="p">(</span><span class="sa">f</span><span class="s2">"无效的历史条目: </span><span class="si">{</span><span class="n">h</span><span class="si">}</span><span class="s2">，忽略历史"</span><span class="p">)</span>
                    <span class="n">history</span> <span class="o">=</span> <span class="p">[]</span>
                    <span class="k">break</span>

        <span class="c1"># 构造历史上下文</span>
        <span class="c1"># TODO 这里构造了上下文</span>
        <span class="n">history_context</span> <span class="o">=</span> <span class="s2">""</span>
        <span class="k">if</span> <span class="n">history</span><span class="p">:</span>
            <span class="n">history_context</span> <span class="o">=</span> <span class="s2">"</span><span class="se">\n</span><span class="s2">"</span><span class="o">.</span><span class="n">join</span><span class="p">(</span>
                <span class="p">[</span><span class="sa">f</span><span class="s2">"Q: </span><span class="si">{</span><span class="n">h</span><span class="p">[</span><span class="s1">'question'</span><span class="p">]</span><span class="si">}</span><span class="se">\n</span><span class="s2">A: </span><span class="si">{</span><span class="n">h</span><span class="p">[</span><span class="s1">'answer'</span><span class="p">]</span><span class="si">}</span><span class="s2">"</span> <span class="k">for</span> <span class="n">h</span> <span class="ow">in</span> <span class="n">history</span><span class="p">]</span>
            <span class="p">)</span>
            <span class="n">logger</span><span class="o">.</span><span class="n">info</span><span class="p">(</span><span class="sa">f</span><span class="s2">"使用对话历史: </span><span class="si">{</span><span class="n">history_context</span><span class="p">[:</span><span class="mi">100</span><span class="p">]</span><span class="si">}</span><span class="s2">..."</span><span class="p">)</span>

        <span class="c1">#   判断查询类型</span>
        <span class="n">query_category</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">query_classifier</span><span class="o">.</span><span class="n">predict_category</span><span class="p">(</span><span class="n">query</span><span class="p">)</span>
        <span class="n">logger</span><span class="o">.</span><span class="n">info</span><span class="p">(</span><span class="sa">f</span><span class="s2">"查询分类结果：</span><span class="si">{</span><span class="n">query_category</span><span class="si">}</span><span class="s2"> (查询: '</span><span class="si">{</span><span class="n">query</span><span class="si">}</span><span class="s2">')"</span><span class="p">)</span>

        <span class="c1">#   如果查询属于“通用知识”类别，则直接使用 LLM 回答</span>
        <span class="k">if</span> <span class="n">query_category</span> <span class="o">==</span> <span class="s2">"通用知识"</span><span class="p">:</span>
            <span class="n">logger</span><span class="o">.</span><span class="n">info</span><span class="p">(</span><span class="s2">"查询为通用知识，直接调用 LLM"</span><span class="p">)</span>
            <span class="n">prompt_input</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">rag_prompt</span><span class="o">.</span><span class="n">format</span><span class="p">(</span>
                <span class="n">context</span><span class="o">=</span><span class="s2">""</span><span class="p">,</span> <span class="n">history</span><span class="o">=</span><span class="n">history_context</span><span class="p">,</span> <span class="n">question</span><span class="o">=</span><span class="n">query</span><span class="p">,</span> <span class="n">phone</span><span class="o">=</span><span class="n">config</span><span class="o">.</span><span class="n">CUSTOMER_SERVICE_PHONE</span>
            <span class="p">)</span>  <span class="c1"># 不使用上下文</span>
            <span class="k">try</span><span class="p">:</span>
                <span class="n">answer</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">llm</span><span class="p">(</span><span class="n">prompt_input</span><span class="p">)</span>
            <span class="k">except</span> <span class="ne">Exception</span> <span class="k">as</span> <span class="n">e</span><span class="p">:</span>
                <span class="n">logger</span><span class="o">.</span><span class="n">error</span><span class="p">(</span><span class="sa">f</span><span class="s2">"直接调用 LLM 失败: </span><span class="si">{</span><span class="n">e</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
                <span class="n">answer</span> <span class="o">=</span> <span class="sa">f</span><span class="s2">"抱歉，处理您的通用知识问题时出错。请联系人工客服：</span><span class="si">{</span><span class="n">config</span><span class="o">.</span><span class="n">CUSTOMER_SERVICE_PHONE</span><span class="si">}</span><span class="s2">"</span>
            <span class="n">processing_time</span> <span class="o">=</span> <span class="n">time</span><span class="o">.</span><span class="n">time</span><span class="p">()</span> <span class="o">-</span> <span class="n">start_time</span>
            <span class="n">logger</span><span class="o">.</span><span class="n">info</span><span class="p">(</span>
                <span class="sa">f</span><span class="s2">"通用知识查询处理完成 (耗时: </span><span class="si">{</span><span class="n">processing_time</span><span class="si">:</span><span class="s2">.2f</span><span class="si">}</span><span class="s2">s, 查询: '</span><span class="si">{</span><span class="n">query</span><span class="si">}</span><span class="s2">')"</span>
            <span class="p">)</span>
            <span class="k">return</span> <span class="n">answer</span>

        <span class="c1">#   否则，进行 RAG 检索并生成答案</span>
        <span class="n">logger</span><span class="o">.</span><span class="n">info</span><span class="p">(</span><span class="s2">"查询为企业知识，执行 RAG 流程"</span><span class="p">)</span>
        <span class="c1">#   选择检索策略</span>
        <span class="n">strategy</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">strategy_selector</span><span class="o">.</span><span class="n">select_strategy</span><span class="p">(</span><span class="n">query</span><span class="p">)</span>

        <span class="c1">#   检索相关文档</span>
        <span class="n">context_docs</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">retrieve_and_merge</span><span class="p">(</span>
            <span class="n">query</span><span class="p">,</span> <span class="n">source_filter</span><span class="o">=</span><span class="n">source_filter</span><span class="p">,</span> <span class="n">strategy</span><span class="o">=</span><span class="n">strategy</span>
        <span class="p">)</span>  <span class="c1"># 传递 strategy</span>

        <span class="c1">#   准备上下文</span>
        <span class="k">if</span> <span class="n">context_docs</span><span class="p">:</span>
            <span class="n">context</span> <span class="o">=</span> <span class="s2">"</span><span class="se">\n\n</span><span class="s2">"</span><span class="o">.</span><span class="n">join</span><span class="p">([</span><span class="n">doc</span><span class="o">.</span><span class="n">page_content</span> <span class="k">for</span> <span class="n">doc</span> <span class="ow">in</span> <span class="n">context_docs</span><span class="p">])</span>  <span class="c1"># 使用换行符分隔文档</span>
            <span class="n">logger</span><span class="o">.</span><span class="n">info</span><span class="p">(</span><span class="sa">f</span><span class="s2">"构建上下文完成，包含 </span><span class="si">{</span><span class="nb">len</span><span class="p">(</span><span class="n">context_docs</span><span class="p">)</span><span class="si">}</span><span class="s2"> 个文档块"</span><span class="p">)</span>
            <span class="c1"># logger.debug(f"上下文内容:\n{context[:500]}...") # Debug 日志可以打印部分上下文</span>
        <span class="k">else</span><span class="p">:</span>
            <span class="n">context</span> <span class="o">=</span> <span class="s2">""</span>
            <span class="n">logger</span><span class="o">.</span><span class="n">info</span><span class="p">(</span><span class="s2">"未检索到相关文档，上下文为空"</span><span class="p">)</span>

        <span class="c1">#   构造 Prompt，调用大语言模型生成答案</span>

        <span class="c1"># 构造提示</span>
        <span class="c1"># TODO generate阶段，放到了提示词里面，让大模型进行整合</span>
        <span class="n">prompt_input</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">rag_prompt</span><span class="o">.</span><span class="n">format</span><span class="p">(</span>
            <span class="n">context</span><span class="o">=</span><span class="n">context</span><span class="p">,</span>
            <span class="n">history</span><span class="o">=</span><span class="n">history_context</span><span class="p">,</span>
            <span class="n">question</span><span class="o">=</span><span class="n">query</span><span class="p">,</span>
            <span class="n">phone</span><span class="o">=</span><span class="n">config</span><span class="o">.</span><span class="n">CUSTOMER_SERVICE_PHONE</span>
        <span class="p">)</span>
        <span class="c1"># logger.debug(f"最终生成的 Prompt:\n{prompt_input}") # Debug 日志</span>

        <span class="k">try</span><span class="p">:</span>
            <span class="n">answer</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">llm</span><span class="p">(</span><span class="n">prompt_input</span><span class="p">)</span>
        <span class="k">except</span> <span class="ne">Exception</span> <span class="k">as</span> <span class="n">e</span><span class="p">:</span>
            <span class="n">logger</span><span class="o">.</span><span class="n">error</span><span class="p">(</span><span class="sa">f</span><span class="s2">"调用 LLM 生成最终答案失败: </span><span class="si">{</span><span class="n">e</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
            <span class="n">answer</span> <span class="o">=</span> <span class="sa">f</span><span class="s2">"抱歉，处理您的企业知识问题时出错。请联系人工客服：</span><span class="si">{</span><span class="n">config</span><span class="o">.</span><span class="n">CUSTOMER_SERVICE_PHONE</span><span class="si">}</span><span class="s2">"</span>

        <span class="c1">#   记录查询处理完成的日志</span>
        <span class="n">processing_time</span> <span class="o">=</span> <span class="n">time</span><span class="o">.</span><span class="n">time</span><span class="p">()</span> <span class="o">-</span> <span class="n">start_time</span>
        <span class="n">logger</span><span class="o">.</span><span class="n">info</span><span class="p">(</span><span class="sa">f</span><span class="s2">"查询处理完成 (耗时: </span><span class="si">{</span><span class="n">processing_time</span><span class="si">:</span><span class="s2">.2f</span><span class="si">}</span><span class="s2">s, 查询: '</span><span class="si">{</span><span class="n">query</span><span class="si">}</span><span class="s2">')"</span><span class="p">)</span>
        <span class="k">return</span> <span class="n">answer</span>
</code></pre></div>
<h3 id="11">11 命令行交互<a class="headerlink" href="#11" title="Permanent link">¶</a></h3>
<ul>
<li>(<code>main</code>) 函数</li>
<li><strong>功能</strong>：提供交互式命令行界面，生成唯一会话 ID，接受用户查询和知识域过滤，流式显示答案并展示对话历史。</li>
<li><strong>关键点</strong>：支持流式输出，验证知识域过滤有效性，异常处理和资源清理确保系统健壮。</li>
</ul>
<div class="highlight"><pre><span></span><code><span class="k">def</span><span class="w"> </span><span class="nf">main</span><span class="p">():</span>
    <span class="c1"># 定义主函数，提供命令行交互界面</span>
    <span class="n">qa_system</span> <span class="o">=</span> <span class="n">IntegratedQASystem</span><span class="p">()</span>  <span class="c1"># 初始化问答系统</span>
    <span class="c1"># 生成唯一会话 ID</span>
    <span class="n">session_id</span> <span class="o">=</span> <span class="nb">str</span><span class="p">(</span><span class="n">uuid</span><span class="o">.</span><span class="n">uuid4</span><span class="p">())</span>
    <span class="c1"># 打印欢迎信息</span>
    <span class="nb">print</span><span class="p">(</span><span class="s2">"</span><span class="se">\n</span><span class="s2">欢迎使用集成问答系统！"</span><span class="p">)</span>
    <span class="c1"># 打印会话 ID</span>
    <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"会话ID: </span><span class="si">{</span><span class="n">session_id</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
    <span class="c1"># 打印支持的知识域</span>
    <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"支持的知识域：</span><span class="si">{</span><span class="n">qa_system</span><span class="o">.</span><span class="n">config</span><span class="o">.</span><span class="n">VALID_SOURCES</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
    <span class="c1"># 提示用户输入查询或退出</span>
    <span class="nb">print</span><span class="p">(</span><span class="s2">"输入查询进行问答，输入 'exit' 退出。"</span><span class="p">)</span>
    <span class="k">try</span><span class="p">:</span>
        <span class="k">while</span> <span class="kc">True</span><span class="p">:</span>
            <span class="c1"># 获取用户输入的查询</span>
            <span class="n">query</span> <span class="o">=</span> <span class="nb">input</span><span class="p">(</span><span class="s2">"</span><span class="se">\n</span><span class="s2">输入查询: "</span><span class="p">)</span><span class="o">.</span><span class="n">strip</span><span class="p">()</span>
            <span class="k">if</span> <span class="n">query</span><span class="o">.</span><span class="n">lower</span><span class="p">()</span> <span class="o">==</span> <span class="s2">"exit"</span><span class="p">:</span>
                <span class="c1"># 如果用户输入 exit，记录退出日志</span>
                <span class="n">logger</span><span class="o">.</span><span class="n">info</span><span class="p">(</span><span class="s2">"退出系统"</span><span class="p">)</span>
                <span class="c1"># 打印退出信息</span>
                <span class="nb">print</span><span class="p">(</span><span class="s2">"再见！"</span><span class="p">)</span>
                <span class="c1"># 退出循环</span>
                <span class="k">break</span>
            <span class="c1"># 获取用户输入的知识域过滤</span>
            <span class="n">source_filter</span> <span class="o">=</span> <span class="nb">input</span><span class="p">(</span><span class="sa">f</span><span class="s2">"请输入知识域 (</span><span class="si">{</span><span class="s1">'/'</span><span class="o">.</span><span class="n">join</span><span class="p">(</span><span class="n">qa_system</span><span class="o">.</span><span class="n">config</span><span class="o">.</span><span class="n">VALID_SOURCES</span><span class="p">)</span><span class="si">}</span><span class="s2">) (直接回车默认不过滤): "</span><span class="p">)</span><span class="o">.</span><span class="n">strip</span><span class="p">()</span>
            <span class="k">if</span> <span class="n">source_filter</span> <span class="ow">and</span> <span class="n">source_filter</span> <span class="ow">not</span> <span class="ow">in</span> <span class="n">qa_system</span><span class="o">.</span><span class="n">config</span><span class="o">.</span><span class="n">VALID_SOURCES</span><span class="p">:</span>
                <span class="c1"># 如果知识域过滤无效，记录警告日志</span>
                <span class="n">logger</span><span class="o">.</span><span class="n">warning</span><span class="p">(</span><span class="sa">f</span><span class="s2">"无效的知识域 '</span><span class="si">{</span><span class="n">source_filter</span><span class="si">}</span><span class="s2">'，将不过滤"</span><span class="p">)</span>
                <span class="c1"># 设置为空，忽略过滤</span>
                <span class="n">source_filter</span> <span class="o">=</span> <span class="kc">None</span>
            <span class="c1"># 打印答案提示</span>
            <span class="nb">print</span><span class="p">(</span><span class="s2">"</span><span class="se">\n</span><span class="s2">答案: "</span><span class="p">,</span> <span class="n">end</span><span class="o">=</span><span class="s2">""</span><span class="p">,</span> <span class="n">flush</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
            <span class="c1"># 初始化累积答案的字符串</span>
            <span class="n">answer</span> <span class="o">=</span> <span class="s2">""</span>
            <span class="c1"># 迭代 query 方法的生成器</span>
            <span class="k">for</span> <span class="n">token</span><span class="p">,</span> <span class="n">is_complete</span> <span class="ow">in</span> <span class="n">qa_system</span><span class="o">.</span><span class="n">query</span><span class="p">(</span><span class="n">query</span><span class="p">,</span> <span class="n">source_filter</span><span class="o">=</span><span class="n">source_filter</span><span class="p">,</span> <span class="n">session_id</span><span class="o">=</span><span class="n">session_id</span><span class="p">):</span>
                <span class="k">if</span> <span class="n">token</span><span class="p">:</span>
                    <span class="c1"># 仅当 token 非空时打印</span>
                    <span class="nb">print</span><span class="p">(</span><span class="n">token</span><span class="p">,</span> <span class="n">end</span><span class="o">=</span><span class="s2">""</span><span class="p">,</span> <span class="n">flush</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
                    <span class="c1"># 累积答案</span>
                    <span class="n">answer</span> <span class="o">+=</span> <span class="n">token</span>
                <span class="k">if</span> <span class="n">is_complete</span><span class="p">:</span>
                    <span class="c1"># 如果是完整答案或流结束，换行并退出循环</span>
                    <span class="nb">print</span><span class="p">()</span>
                    <span class="k">break</span>
            <span class="c1"># 打印对话历史</span>
            <span class="n">history</span> <span class="o">=</span> <span class="n">qa_system</span><span class="o">.</span><span class="n">get_session_history</span><span class="p">(</span><span class="n">session_id</span><span class="p">)</span>
            <span class="nb">print</span><span class="p">(</span><span class="s2">"</span><span class="se">\n</span><span class="s2">最近对话历史:"</span><span class="p">)</span>
            <span class="k">for</span> <span class="n">idx</span><span class="p">,</span> <span class="n">entry</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="n">history</span><span class="p">,</span> <span class="mi">1</span><span class="p">):</span>
                <span class="c1"># 按顺序打印历史记录</span>
                <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"</span><span class="si">{</span><span class="n">idx</span><span class="si">}</span><span class="s2">. 问: </span><span class="si">{</span><span class="n">entry</span><span class="p">[</span><span class="s1">'question'</span><span class="p">]</span><span class="si">}</span><span class="se">\n</span><span class="s2">   答: </span><span class="si">{</span><span class="n">entry</span><span class="p">[</span><span class="s1">'answer'</span><span class="p">]</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
    <span class="k">except</span> <span class="ne">Exception</span> <span class="k">as</span> <span class="n">e</span><span class="p">:</span>
        <span class="c1"># 记录系统错误日志</span>
        <span class="n">logger</span><span class="o">.</span><span class="n">error</span><span class="p">(</span><span class="sa">f</span><span class="s2">"系统错误: </span><span class="si">{</span><span class="n">e</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
        <span class="c1"># 打印错误信息</span>
        <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"发生错误: </span><span class="si">{</span><span class="n">e</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
    <span class="k">finally</span><span class="p">:</span>
        <span class="c1"># 关闭 MySQL 连接</span>
        <span class="n">qa_system</span><span class="o">.</span><span class="n">mysql_client</span><span class="o">.</span><span class="n">close</span><span class="p">()</span>

<span class="k">if</span> <span class="vm">__name__</span> <span class="o">==</span> <span class="s2">"__main__"</span><span class="p">:</span>
    <span class="c1"># 如果脚本作为主程序运行，调用 main 函数</span>
    <span class="n">main</span><span class="p">()</span>
</code></pre></div>
<h2 id="_5">章节小结<a class="headerlink" href="#_5" title="Permanent link">¶</a></h2>
<p>本章展示了优化后的 <code>new_main.py</code>，通过新增对话历史管理和流式输出功能，显著提升了交互性和实时性。系统结合 MySQL FAQ 的快速匹配、RAG 系统的复杂查询处理、MySQL 的历史存储，以及流式答案生成，配备健壮的日志记录和错误处理，适合知识库场景下的实时问答需求</p>


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