agent功能开发增加MCP后端
This commit is contained in:
174
mcp_server.py
174
mcp_server.py
@@ -1473,7 +1473,7 @@ class MCPAgentIntegrated:
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# 发送开始事件
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yield self._format_sse("status", {"stage": "start", "message": "开始处理查询"})
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# 阶段1: Kimi 制定计划（流式）
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# 阶段1: Kimi 制定计划（流式，带 DeepMoney 备选）
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yield self._format_sse("status", {"stage": "planning", "message": "正在制定执行计划..."})
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messages = [
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@@ -1481,40 +1481,81 @@ class MCPAgentIntegrated:
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{"role": "user", "content": user_query},
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]
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# 使用流式 API 调用 Kimi
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stream = self.kimi_client.chat.completions.create(
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model=self.kimi_model,
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messages=messages,
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temperature=1.0,
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max_tokens=16000,
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stream=True, # 启用流式输出
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)
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reasoning_content = ""
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plan_content = ""
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use_fallback = False
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# 逐块接收 Kimi 的响应
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for chunk in stream:
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if chunk.choices[0].delta.content:
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content_chunk = chunk.choices[0].delta.content
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plan_content += content_chunk
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try:
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# 尝试使用 Kimi 流式 API
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stream = self.kimi_client.chat.completions.create(
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model=self.kimi_model,
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messages=messages,
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temperature=1.0,
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max_tokens=16000,
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stream=True, # 启用流式输出
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)
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# 发送思考过程片段
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yield self._format_sse("thinking", {
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"content": content_chunk,
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"stage": "planning"
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# 逐块接收 Kimi 的响应
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for chunk in stream:
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if chunk.choices[0].delta.content:
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content_chunk = chunk.choices[0].delta.content
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plan_content += content_chunk
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# 发送思考过程片段
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yield self._format_sse("thinking", {
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"content": content_chunk,
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"stage": "planning"
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})
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# 提取 reasoning_content（如果有）
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if hasattr(chunk.choices[0], 'delta') and hasattr(chunk.choices[0].delta, 'reasoning_content'):
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reasoning_chunk = chunk.choices[0].delta.reasoning_content
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if reasoning_chunk:
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reasoning_content += reasoning_chunk
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# 发送推理过程片段
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yield self._format_sse("reasoning", {
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"content": reasoning_chunk
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})
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except Exception as kimi_error:
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# 检查是否是内容风控错误（400）
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error_str = str(kimi_error)
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if "400" in error_str and ("content_filter" in error_str or "high risk" in error_str):
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logger.warning(f"[Planning] Kimi 内容风控拒绝，切换到 DeepMoney: {error_str}")
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use_fallback = True
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yield self._format_sse("status", {
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"stage": "planning",
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"message": "切换到备用模型制定计划..."
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})
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# 提取 reasoning_content（如果有）
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if hasattr(chunk.choices[0], 'delta') and hasattr(chunk.choices[0].delta, 'reasoning_content'):
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reasoning_chunk = chunk.choices[0].delta.reasoning_content
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if reasoning_chunk:
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reasoning_content += reasoning_chunk
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# 发送推理过程片段
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yield self._format_sse("reasoning", {
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"content": reasoning_chunk
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try:
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# 使用 DeepMoney 备选方案（非流式，因为 DeepMoney 可能不支持流式）
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fallback_response = self.deepmoney_client.chat.completions.create(
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model=self.deepmoney_model,
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messages=messages,
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temperature=0.7,
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max_tokens=16000,
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)
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plan_content = fallback_response.choices[0].message.content
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# 发送完整的计划内容（一次性）
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yield self._format_sse("thinking", {
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"content": plan_content,
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"stage": "planning"
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})
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logger.info(f"[Planning] DeepMoney 备选方案成功")
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except Exception as fallback_error:
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logger.error(f"[Planning] DeepMoney 备选方案也失败: {fallback_error}")
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raise Exception(f"Kimi 和 DeepMoney 都无法生成计划: {kimi_error}, {fallback_error}")
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else:
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# 不是内容风控错误，直接抛出
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logger.error(f"[Planning] Kimi 调用失败（非风控原因）: {kimi_error}")
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raise
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# 解析完整的计划
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plan_json = plan_content.strip()
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@@ -1682,29 +1723,72 @@ class MCPAgentIntegrated:
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},
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]
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# 使用流式 API 生成总结
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summary_stream = self.kimi_client.chat.completions.create(
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model="kimi-k2-turbo-preview",
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messages=messages,
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temperature=0.7,
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max_tokens=2000,
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stream=True, # 启用流式输出
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)
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# 使用流式 API 生成总结（带 DeepMoney 备选）
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final_summary = ""
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# 逐块发送总结内容
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for chunk in summary_stream:
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if chunk.choices[0].delta.content:
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content_chunk = chunk.choices[0].delta.content
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final_summary += content_chunk
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try:
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summary_stream = self.kimi_client.chat.completions.create(
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model="kimi-k2-turbo-preview",
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messages=messages,
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temperature=0.7,
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max_tokens=2000,
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stream=True, # 启用流式输出
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)
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# 发送总结片段
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yield self._format_sse("summary_chunk", {
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"content": content_chunk
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# 逐块发送总结内容
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for chunk in summary_stream:
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if chunk.choices[0].delta.content:
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content_chunk = chunk.choices[0].delta.content
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final_summary += content_chunk
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# 发送总结片段
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yield self._format_sse("summary_chunk", {
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"content": content_chunk
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})
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logger.info("[Summary] 流式总结完成")
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except Exception as kimi_error:
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# 检查是否是内容风控错误（400）
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error_str = str(kimi_error)
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if "400" in error_str and ("content_filter" in error_str or "high risk" in error_str):
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logger.warning(f"[Summary] Kimi 内容风控拒绝，切换到 DeepMoney: {error_str}")
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yield self._format_sse("status", {
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"stage": "summarizing",
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"message": "切换到备用模型生成总结..."
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})
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logger.info("[Summary] 流式总结完成")
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try:
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# 使用 DeepMoney 备选方案（非流式）
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fallback_response = self.deepmoney_client.chat.completions.create(
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model=self.deepmoney_model,
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messages=messages,
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temperature=0.7,
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max_tokens=2000,
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)
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final_summary = fallback_response.choices[0].message.content
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# 发送完整的总结内容（一次性）
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yield self._format_sse("summary_chunk", {
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"content": final_summary
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})
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logger.info(f"[Summary] DeepMoney 备选方案成功")
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except Exception as fallback_error:
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logger.error(f"[Summary] DeepMoney 备选方案也失败: {fallback_error}")
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# 使用降级方案：简单拼接执行结果
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final_summary = f"执行了 {len(plan.steps)} 个步骤，其中 {len(successful_results)} 个成功。\n\n执行结果：\n{results_text[:500]}..."
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yield self._format_sse("summary_chunk", {
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"content": final_summary
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})
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logger.warning("[Summary] 使用降级方案（简单拼接）")
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else:
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# 不是内容风控错误，直接抛出
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logger.error(f"[Summary] Kimi 调用失败（非风控原因）: {kimi_error}")
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raise
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# 发送完整的总结和元数据
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yield self._format_sse("summary", {
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