rebase main

agent/core/runner.py

@@ -113,8 +113,6 @@ class RunConfig:
 
     # --- 框架层参数 ---
     agent_type: str = "default"
-    # Agent 实例标识（用于知识 owner 兜底）；为空时回退到 uid
-    agent_id: Optional[str] = None
     uid: Optional[str] = None
     system_prompt: Optional[str] = None        # None = 从 skills 自动构建
     skills: Optional[List[str]] = None         # 注入 system prompt 的 skill 名称列表；None = 按 preset 决定
@@ -1109,7 +1107,6 @@ class AgentRunner:
 
                 if not has_context_call:
                     # 手动添加 get_current_context 工具调用
-                    import uuid
                     context_call_id = f"call_context_{uuid.uuid4().hex[:8]}"
                     tool_calls.append({
                         "id": context_call_id,
@@ -1346,23 +1343,6 @@ class AgentRunner:
                     elif tool_args is None:
                         tool_args = {}
 
-                    # 注入知识管理工具的默认字段
-                    if tool_name == "knowledge_save":
-                        run_agent_id = config.agent_id or config.uid or "agent"
-                        tool_args.setdefault("owner", config.knowledge.get_owner(run_agent_id))
-                        if config.knowledge.default_tags:
-                            existing_tags = tool_args.get("tags") or {}
-                            merged_tags = {**config.knowledge.default_tags, **existing_tags}
-                            tool_args["tags"] = merged_tags
-                        if config.knowledge.default_scopes:
-                            existing_scopes = tool_args.get("scopes") or []
-                            tool_args["scopes"] = existing_scopes + config.knowledge.default_scopes
-                    elif tool_name == "knowledge_search":
-                        if config.knowledge.default_search_types and "types" not in tool_args:
-                            tool_args["types"] = config.knowledge.default_search_types
-                        if config.knowledge.default_search_owner and "owner" not in tool_args:
-                            tool_args["owner"] = config.knowledge.default_search_owner
-
                     # 记录工具调用（INFO 级别，显示参数）
                     args_str = json.dumps(tool_args, ensure_ascii=False)
                     args_display = args_str[:100] + "..." if len(args_str) > 100 else args_str
@@ -1593,69 +1573,7 @@ class AgentRunner:
                 preview = str(content)
             logger.info(f"  {label}后[{idx}] {role}: {preview}")
 
-<<<<<<< HEAD
         return new_history
-=======
-            tool_calls = reflect_result.get("tool_calls") or []
-            if not tool_calls:
-                logger.info("反思阶段无经验保存 (source=%s)", source_name)
-                return
-
-            saved_count = 0
-            for tc in tool_calls:
-                tool_name = tc.get("function", {}).get("name")
-                if tool_name != "knowledge_save":
-                    continue
-
-                tool_args = tc.get("function", {}).get("arguments") or {}
-                if isinstance(tool_args, str):
-                    tool_args = json.loads(tool_args) if tool_args.strip() else {}
-
-                # 注入来源信息（LLM 不需要填写这些字段）
-                tool_args.setdefault("source_name", source_name)
-                tool_args.setdefault("source_category", "exp")
-                tool_args.setdefault("message_id", trace_id)
-
-                # 注入知识管理默认字段
-                run_agent_id = config.agent_id or config.uid or "agent"
-                tool_args.setdefault("owner", config.knowledge.get_owner(run_agent_id))
-                if config.knowledge.default_tags:
-                    existing_tags = tool_args.get("tags") or {}
-                    merged_tags = {**config.knowledge.default_tags, **existing_tags}
-                    tool_args["tags"] = merged_tags
-                if config.knowledge.default_scopes:
-                    tool_args.setdefault("scopes", config.knowledge.default_scopes)
-
-                try:
-                    await self.tools.execute(
-                        "knowledge_save",
-                        tool_args,
-                        uid=config.uid or "",
-                        context={"store": self.trace_store, "trace_id": trace_id},
-                    )
-                    saved_count += 1
-                except Exception as e:
-                    logger.warning("保存经验失败: %s", e)
-
-            logger.info("已提取并保存 %d 条经验 (source=%s)", saved_count, source_name)
-
-        except Exception as e:
-            logger.error("知识反思提取失败 (source=%s): %s", source_name, e)
-
-    async def _extract_knowledge_on_completion(
-        self,
-        trace_id: str,
-        history: List[Dict],
-        config: RunConfig,
-    ) -> None:
-        """任务完成后执行全局复盘，提取经验保存到知识库。"""
-        logger.info("任务完成后复盘提取: trace=%s", trace_id)
-        await self._run_reflect(
-            trace_id, history, config,
-            reflect_prompt=config.knowledge.get_completion_reflect_prompt(),
-            source_name="completion_reflection",
-        )
->>>>>>> 0a8d3f1 (修改远程库地址和新流程)
 
     # ===== 回溯（Rewind）=====
 
@@ -1906,7 +1824,8 @@ class AgentRunner:
         goal_tree: Optional[GoalTree],
     ) -> str:
         """构建周期性注入的上下文（GoalTree + Active Collaborators + Focus 提醒）"""
-        parts = []
+        from datetime import datetime
+        parts = [f"## Current Time\n\n{datetime.now().strftime('%Y-%m-%d %H:%M:%S')}"]
 
         # GoalTree
         if goal_tree and goal_tree.goals:

agent/tools/builtin/knowledge.py

@@ -15,8 +15,8 @@ from agent.core.prompts import build_reflect_prompt, COMPLETION_REFLECT_PROMPT
 
 logger = logging.getLogger(__name__)
 
-# KnowHub Server API 地址
-KNOWHUB_API = os.getenv("KNOWHUB_API", "http://43.106.118.91:9999")
+# KnowHub Server API 地址（去除末尾斜杠）
+KNOWHUB_API = os.getenv("KNOWHUB_API", "http://localhost:8000").rstrip("/")
 
 
 # ===== 知识管理配置 =====