feat(agent): Opening remarks and document citation function

api/app/services/app_chat_service.py

@@ -82,6 +82,12 @@ class AppChatService:
             )
             system_prompt = system_prompt_rendered.get_text_content() or system_prompt
 
+        # opening_statement：首轮对话注入开场白
+        is_new_conversation = not self.conversation_service.get_messages(conversation_id, limit=1)
+        system_prompt = self.agent_service._inject_opening_statement(
+            features_config, system_prompt, is_new_conversation
+        )
+
         # 准备工具列表
         tools = []
 
@@ -93,7 +99,8 @@ class AppChatService:
         tools.extend(skill_tools)
         if skill_prompts:
             system_prompt = f"{system_prompt}\n\n{skill_prompts}"
-        tools.extend(self.agent_service.load_knowledge_retrieval_config(config.knowledge_retrieval, user_id))
+        kb_tools, citations_collector = self.agent_service.load_knowledge_retrieval_config(config.knowledge_retrieval, user_id)
+        tools.extend(kb_tools)
         memory_flag = False
         if memory:
             memory_tools, memory_flag = self.agent_service.load_memory_config(
@@ -230,7 +237,7 @@ class AppChatService:
             }),
             "elapsed_time": elapsed_time,
             "suggested_questions": suggested_questions,
-            "citations": self.agent_service._filter_citations(features_config, result.get("citations", [])),
+            "citations": self.agent_service._filter_citations(features_config, citations_collector),
             "audio_url": audio_url,
             "audio_status": "pending"
         }
@@ -283,6 +290,12 @@ class AppChatService:
                 )
                 system_prompt = system_prompt_rendered.get_text_content() or system_prompt
 
+            # opening_statement：首轮对话注入开场白
+            is_new_conversation = not self.conversation_service.get_messages(conversation_id, limit=1)
+            system_prompt = self.agent_service._inject_opening_statement(
+                features_config, system_prompt, is_new_conversation
+            )
+
             # 准备工具列表
             tools = []
 
@@ -295,7 +308,8 @@ class AppChatService:
             tools.extend(skill_tools)
             if skill_prompts:
                 system_prompt = f"{system_prompt}\n\n{skill_prompts}"
-            tools.extend(self.agent_service.load_knowledge_retrieval_config(config.knowledge_retrieval, user_id))
+            kb_tools, citations_collector = self.agent_service.load_knowledge_retrieval_config(config.knowledge_retrieval, user_id)
+            tools.extend(kb_tools)
             # 添加长期记忆工具
             memory_flag = False
             if memory:
@@ -409,7 +423,7 @@ class AppChatService:
                     logger.warning(f"TTS任务异常: {e}")
                     audio_status = "failed"
             end_data["audio_status"] = audio_status if stream_audio_url else None
-            end_data["citations"] = self.agent_service._filter_citations(features_config, [])
+            end_data["citations"] = self.agent_service._filter_citations(features_config, citations_collector)
 
             # 保存消息
             human_meta = {

api/app/services/draft_run_service.py

@@ -190,13 +190,14 @@ def create_web_search_tool(web_search_config: Dict[str, Any]):
     return web_search_tool
 
 
-def create_knowledge_retrieval_tool(kb_config, kb_ids, user_id):
+def create_knowledge_retrieval_tool(kb_config, kb_ids, user_id, citations_collector: list = None):
     """从知识库中检索相关信息。当用户的问题需要参考知识库、文档或历史记录时，使用此工具进行检索。
 
     Args:
         kb_config: 知识库配置
         kb_ids: 知识库ID列表
         user_id: 用户ID
+        citations_collector: 用于收集引用信息的列表（由外部传入，tool 执行时填充）
 
     Returns:
         检索到的相关知识内容
@@ -229,6 +230,21 @@ def create_knowledge_retrieval_tool(kb_config, kb_ids, user_id):
                     }
                 )
 
+                # 收集引用信息
+                if citations_collector is not None:
+                    seen_doc_ids = {c.get("document_id") for c in citations_collector}
+                    for chunk in retrieve_chunks_result:
+                        meta = chunk.metadata or {}
+                        doc_id = meta.get("document_id") or meta.get("doc_id")
+                        if doc_id and doc_id not in seen_doc_ids:
+                            seen_doc_ids.add(doc_id)
+                            citations_collector.append({
+                                "document_id": doc_id,
+                                "file_name": meta.get("file_name", ""),
+                                "knowledge_id": str(meta.get("knowledge_id", "")),
+                                "score": meta.get("score", 0),
+                            })
+
                 return f"检索到以下相关信息：\n\n{context}"
             else:
                 logger.warning("知识库检索未找到结果")
@@ -320,26 +336,26 @@ class AgentRunService:
             self,
             knowledge_retrieval_config: dict | None,
             user_id
-    ) -> list:
+    ) -> tuple[list, list]:
+        """返回 (tools, citations_collector)"""
         if not knowledge_retrieval_config:
-            return []
+            return [], []
 
+        citations_collector = []
         tools = []
         knowledge_bases = knowledge_retrieval_config.get("knowledge_bases", [])
         kb_ids = bool(knowledge_bases and knowledge_bases[0].get("kb_id"))
         if kb_ids:
-            # 创建知识库检索工具
-            kb_tool = create_knowledge_retrieval_tool(knowledge_retrieval_config, kb_ids, user_id)
+            kb_tool = create_knowledge_retrieval_tool(
+                knowledge_retrieval_config, kb_ids, user_id,
+                citations_collector=citations_collector
+            )
             tools.append(kb_tool)
-
             logger.debug(
                 "已添加知识库检索工具",
-                extra={
-                    "kb_ids": kb_ids,
-                    "tool_count": len(tools)
-                }
+                extra={"kb_ids": kb_ids, "tool_count": len(tools)}
             )
-        return tools
+        return tools, citations_collector
 
     def load_memory_config(
             self,
@@ -549,7 +565,8 @@ class AgentRunService:
             tools.extend(skill_tools)
             if skill_prompts:
                 system_prompt = f"{system_prompt}\n\n{skill_prompts}"
-            tools.extend(self.load_knowledge_retrieval_config(knowledge_retrieval_config, user_id))
+            kb_tools, citations_collector = self.load_knowledge_retrieval_config(knowledge_retrieval_config, user_id)
+            tools.extend(kb_tools)
             # 添加长期记忆工具
             memory_flag = False
             if memory:
@@ -680,7 +697,7 @@ class AgentRunService:
                 "suggested_questions": await self._generate_suggested_questions(
                     features_config, result["content"], api_key_config, effective_params
                 ) if not sub_agent else [],
-                "citations": self._filter_citations(features_config, result.get("citations", [])),
+                "citations": self._filter_citations(features_config, citations_collector),
                 "audio_url": audio_url,
                 "audio_status": "pending"
             }
@@ -790,7 +807,8 @@ class AgentRunService:
             tools.extend(skill_tools)
             if skill_prompts:
                 system_prompt = f"{system_prompt}\n\n{skill_prompts}"
-            tools.extend(self.load_knowledge_retrieval_config(knowledge_retrieval_config, user_id))
+            kb_tools, citations_collector = self.load_knowledge_retrieval_config(knowledge_retrieval_config, user_id)
+            tools.extend(kb_tools)
 
             # 添加长期记忆工具
             memory_flag = False
@@ -943,7 +961,7 @@ class AgentRunService:
                         logger.warning(f"TTS任务异常: {e}")
                         audio_status = "failed"
                 end_data["audio_status"] = audio_status if stream_audio_url else None
-                end_data["citations"] = self._filter_citations(features_config, [])
+                end_data["citations"] = self._filter_citations(features_config, citations_collector)
             yield self._format_sse_event("end", end_data)
 
             logger.info(