修改return节点定义

backend_service/src/llm/gateway.py

@@ -15,14 +15,17 @@ class LLMGateway:
         self.generator = generator
         self.stage1_enable_thinking = os.getenv("STAGE1_ENABLE_THINKING", "true").lower() in ("1", "true", "yes")
 
-    def classify_scene(self, user_prompt: str) -> str:
+    def classify_scene(self, user_prompt: str, drone_state: str = "on_ground") -> str:
         scene_mode = "scene1"
         try:
+            user_content = user_prompt
+            if drone_state and drone_state in ("on_ground", "in_air"):
+                user_content = f"无人机当前状态：{drone_state}\n\n用户指令：{user_prompt}"
             classifier_resp = self.generator.classifier_client.chat.completions.create(
                 model=self.generator.classifier_model,
                 messages=[
                     {"role": "system", "content": self.generator.scene_classifier_prompt or "你是一个分类器，只输出JSON。"},
-                    {"role": "user", "content": user_prompt},
+                    {"role": "user", "content": user_content},
                 ],
                 temperature=0.0,
                 response_format={"type": "json_object"},

backend_service/src/pipeline/orchestrator.py

@@ -9,8 +9,8 @@ class GenerationOrchestrator:
     def __init__(self, generator: Any):
         self.stages = PipelineStages(generator)
 
-    async def generate(self, user_prompt: str) -> Dict:
+    async def generate(self, user_prompt: str, drone_state: str = "on_ground") -> Dict:
-        understanding = self.stages.stage1_task_understanding(user_prompt)
+        understanding = self.stages.stage1_task_understanding(user_prompt, drone_state=drone_state)
         context = self.stages.stage2_context_binding(user_prompt, understanding)
         
         if understanding.scene_mode == "simple":

backend_service/src/pipeline/stages.py

@@ -71,18 +71,15 @@ class PipelineStages:
     def __init__(self, generator: Any):
         self.generator = generator
 
-    def stage1_task_understanding(self, user_prompt: str) -> TaskUnderstanding:
+    def stage1_task_understanding(self, user_prompt: str, drone_state: str = "on_ground") -> TaskUnderstanding:
         logging.info("========== [Stage 1] Task Understanding ==========")
-        scene_mode = self.generator.llm_gateway.classify_scene(user_prompt)
+        if drone_state not in ("on_ground", "in_air"):
+            drone_state = "on_ground"
+        scene_mode = self.generator.llm_gateway.classify_scene(user_prompt, drone_state=drone_state)
         intent_type = _infer_intent_type(user_prompt, scene_mode)
         risk_flags = _extract_risk_flags(user_prompt)
         requires_relative = "relative_reference_detected" in risk_flags
 
-        # 简单提取状态
-        drone_state: DroneState = "on_ground"
-        if "在空中" in user_prompt or "已起飞" in user_prompt:
-            drone_state = "in_air"
-            
         entities = {"raw_prompt": user_prompt}
         
         logging.info(f"Task Understanding Results: mode={scene_mode}, state={drone_state}, intent={intent_type}, risks={risk_flags}")

backend_service/src/prompts/atomic/nodes_schema.json

@@ -125,8 +125,8 @@
       }
     },
     {
-      "name": "return_emergency",
+      "name": "return",
-      "desc": "紧急返航",
+      "desc": "返航，回到起飞点",
       "params": {
         "reason": "string"
       }

backend_service/src/prompts/partials/common_rules.txt

@@ -20,8 +20,8 @@
 - 指令明确“在当前位置 / 原地 / 不用过去 / 就在这”时，无需 fly_to_waypoint。
 
 5. 严格区分无人机状态：
-- 指令明确“当前在空中”：严禁使用 system_checks 与 takeoff。
+- 指令明确“当前在空中”：严禁使用 takeoff。
-- 指令明确“当前在地面”：如需要飞行任务，优先 system_checks -> takeoff 再执行后续动作。
+- 指令明确“当前在地面”：如需要飞行任务，优先 takeoff 再执行后续动作。
 
 6. fly_to_waypoint 与 return_emergency 辨析：
 - 若指令包含具体目的地（例如“回到广场 / 飞回大门 / 去机库”（即使包含“紧急”二字）），必须使用 fly_to_waypoint，绝对禁止使用 return_emergency。

backend_service/src/prompts/partials/scene1_examples.txt

@@ -9,7 +9,6 @@
     "type": "Sequence",
     "name": "FlyPerimeterAndPhotoWindows",
     "children": [
-      {"type":"action","name":"system_checks","params":{"check_level":"comprehensive"}},
       {"type":"action","name":"takeoff","params":{"altitude":10.0}},
       {
         "type": "Parallel",
@@ -59,7 +58,6 @@
     "type": "Sequence",
     "name": "FlyPerimeterAndPhotoOpenWindows",
     "children": [
-      {"type":"action","name":"system_checks","params":{"check_level":"comprehensive"}},
       {"type":"action","name":"takeoff","params":{"altitude":10.0}},
       {
         "type": "Parallel",
@@ -158,7 +156,6 @@
     "type": "Sequence",
     "name": "FlyPerimeterAndPhotoGarbageObserve",
     "children": [
-      {"type":"action","name":"system_checks","params":{"check_level":"comprehensive"}},
       {"type":"action","name":"takeoff","params":{"altitude":10.0}},
       {
         "type": "Parallel",
@@ -208,7 +205,6 @@
     "type": "Sequence",
     "name": "FlyPerimeterAndPhotoGarbage",
     "children": [
-      {"type":"action","name":"system_checks","params":{"check_level":"comprehensive"}},
       {"type":"action","name":"takeoff","params":{"altitude":10.0}},
       {
         "type": "Parallel",
@@ -307,7 +303,6 @@
     "type": "Sequence",
     "name": "FlyPerimeterAndPhotoPerson",
     "children": [
-      {"type":"action","name":"system_checks","params":{"check_level":"comprehensive"}},
       {"type":"action","name":"takeoff","params":{"altitude":10.0}},
       {
         "type": "Parallel",
@@ -357,7 +352,6 @@
     "type": "Sequence",
     "name": "FlyPerimeterCounterClockwiseAndPhotoPerson",
     "children": [
-      {"type":"action","name":"system_checks","params":{"check_level":"comprehensive"}},
       {"type":"action","name":"takeoff","params":{"altitude":10.0}},
       {
         "type": "Parallel",

backend_service/src/prompts/partials/scene4_examples.txt

@@ -43,7 +43,6 @@
   "root": {
     "type": "Sequence",
     "children": [
-      {"type":"action","name":"system_checks","params":{"check_level":"basic"}},
       {"type":"action","name":"takeoff","params":{"altitude":10.0}},
       {
         "type": "Selector",
@@ -175,7 +174,6 @@
     "type": "Sequence",
     "name": "SearchPhotoConfirmReturn",
     "children": [
-      {"type":"action","name":"system_checks","params":{"check_level":"comprehensive"}},
       {"type":"action","name":"takeoff","params":{"altitude":10.0}},
       {"type":"action","name":"rotate_search","params":{"target_class":"car","description":"小汽车"}},
       {"type":"condition","name":"object_detected","params":{"target_class":"car","description":"小汽车"}},

backend_service/src/prompts/partials/system_extra_examples.txt

@@ -69,7 +69,6 @@
     "type": "Sequence",
     "name": "FlyPerimeterAndPhotoGarbage",
     "children": [
-      {"type":"action","name":"system_checks","params":{"check_level":"comprehensive"}},
       {"type":"action","name":"takeoff","params":{"altitude":10.0}},
       {
         "type": "Parallel",
@@ -123,7 +122,6 @@
     "type": "Sequence",
     "name": "FlyPerimeterAndPhotoWindows",
     "children": [
-      {"type":"action","name":"system_checks","params":{"check_level":"comprehensive"}},
       {"type":"action","name":"takeoff","params":{"altitude":10.0}},
       {
         "type": "Parallel",
@@ -177,7 +175,6 @@
     "type": "Sequence",
     "name": "FlyPerimeterAndPhotoOpenWindows",
     "children": [
-      {"type":"action","name":"system_checks","params":{"check_level":"comprehensive"}},
       {"type":"action","name":"takeoff","params":{"altitude":10.0}},
       {
         "type": "Parallel",
@@ -284,7 +281,6 @@
     "type": "Sequence",
     "name": "FlyPerimeterAndPhotoGarbageObserve",
     "children": [
-      {"type":"action","name":"system_checks","params":{"check_level":"comprehensive"}},
       {"type":"action","name":"takeoff","params":{"altitude":10.0}},
       {
         "type": "Parallel",
@@ -391,7 +387,6 @@
     "type": "Sequence",
     "name": "FlyPerimeterAndPhotoPerson",
     "children": [
-      {"type":"action","name":"system_checks","params":{"check_level":"comprehensive"}},
       {"type":"action","name":"takeoff","params":{"altitude":10.0}},
       {
         "type": "Parallel",
@@ -445,7 +440,6 @@
     "type": "Sequence",
     "name": "FlyPerimeterCounterClockwiseAndPhotoPerson",
     "children": [
-      {"type":"action","name":"system_checks","params":{"check_level":"comprehensive"}},
       {"type":"action","name":"takeoff","params":{"altitude":10.0}},
       {
         "type": "Parallel",

backend_service/src/prompts/partials/template_air.txt

@@ -1,6 +1,6 @@
 ## 三、顶层 JSON 结构规范与模板
 
-当无人机状态为 **in_air（空中）** 时，通常的流程包含：方向移动或直接飞行至目标点 -> （执行任务）。**严禁**使用 `system_checks` 与 `takeoff`。
+当无人机状态为 **in_air（空中）** 时，通常的流程包含：方向移动或直接飞行至目标点 -> （执行任务）。**严禁**使用 `takeoff`。
 如果指令要求“沿外围”，需使用 `fly_sequence`。
 
 你必须同时输出 `macro_tree`（必须剔除 params）和 `parameter_requests` 两个字段。

backend_service/src/prompts/partials/template_ground.txt

@@ -1,6 +1,6 @@
 ## 三、顶层 JSON 结构规范与模板
 
-当无人机状态为 **on_ground（地面）** 时，通常的流程包含：`system_checks` -> `takeoff` -> （飞行至目标点等后续动作）。
+当无人机状态为 **on_ground（地面）** 时，通常的流程包含：`takeoff` -> （飞行至目标点等后续动作）。
 如果指令要求“沿外围”，需使用 `fly_sequence`。
 
 你必须同时输出 `macro_tree`（必须剔除 params）和 `parameter_requests` 两个字段。
@@ -13,7 +13,6 @@
       "type": "Sequence",
       "name": "MainTask",
       "children": [
-        {"type": "action", "name": "system_checks"},
         {"type": "action", "name": "takeoff"},
         {"type": "action", "name": "fly_to_waypoint"}
       ]

backend_service/src/prompts/scene_classifier_prompt.txt

@@ -1,9 +1,12 @@
-你是指令分类器。只输出一个JSON，无其它内容。
+你是指令分类器，仅输出JSON对象，无任何多余内容。
-输入：无人机状态{on_ground/in_air}+指令。
+输入：无人机状态(on_ground/in_air)+指令。
 输出仅三选一：{"mode":"simple"}、{"mode":"scene1"}、{"mode":"scene4"}。
 
-规则：
+规则（必须严格执行）：
-1. 指令含“面前”→scene1
+1. 指令包含“面前”→输出{"mode":"scene1"}；
-2. 状态=in_air，指令是：飞到某地/飞到某地+方位距离/往某方向飞X米/降落/旋转/悬停 →simple
+2. 无人机状态=in_air且指令包含“飞到”→输出{"mode":"simple"}；
-3. 状态=on_ground，指令含去/飞到/回到某地 →非simple
+3. 无人机状态=in_air且指令包含“往某方向飞”或“降落”或“旋转”或“悬停”→输出{"mode":"simple"}；
-4. 多动作/序列任务→scene4
+4. 无人机状态=on_ground且指令包含“起飞”或“旋转”或“悬停”→输出{"mode":"simple"}；
+5. 无人机状态=on_ground且指令包含“飞到”或“去”或“回到”→输出{"mode":"scene4"}；
+6. 指令包含“先”或“再”或“搜索”或“监控”或“拍照”或“返航”或“确认”→输出{"mode":"scene4"}；
+7. 其他所有情况→输出{"mode":"scene4"}。

backend_service/src/prompts/system_prompt_vllm.txt

@@ -1,248 +0,0 @@
-任务：根据用户任意任务指令，生成结构化可执行的无人机行为树（Pytree）JSON。**仅输出单一JSON对象，无任何自然语言、注释或额外内容**。
-
-## 一、核心节点定义（格式不可修改，确保后端解析）
-#### 1. 可用节点定义 (必须遵守)
-你必须严格从以下JSON定义的列表中选择节点构建行为树，不允许使用未定义节点：
-```json
-{
-  "actions": [
-    {"name":"takeoff","params":{"altitude":"float[1,100]，默认2"}},
-    {"name":"land","params":{"mode":"'current'/'home'"}},
-    {"name":"fly_to_waypoint","params":{"x":"±10000","y":"±10000","z":"[1,5000]","acceptance_radius":"默认2.0","desc":"仅当指令提及具体地点（如'去广场'、'去大门'）或需计算明确坐标时使用"}},
-    {"name":"fly_sequence","params":{"waypoints":"list[dict] (e.g. [{'x':10,'y':20,'z':5}, ...])","coordinate_frame":"'global'/'local_enu'（global:经纬度, local_enu:以起飞点为原点的东南天坐标系）","speed":"float,可选"}},
-    {"name":"move_direction","params":{"direction":"north/south/east/west/forward/backward/left/right","distance":"[1,10000]，缺省则持续移动","speed":"float,可选","desc":"当指令仅包含'往东/西...飞xx米'且无具体地点名词时，必须使用此节点"}},
-    {"name":"approach_target","params":{"target_class":"string,要趋近的目标类别","description":"string,可选,目标属性描述","stop_distance":"float,期望的最终停止距离","speed":"float,可选,期望的逼近速度"}},
-    {"name":"rotate","params":{"angle":"float,无人机自身旋转角度(正数逆时针,负数顺时针)","angular_velocity":"rad/s,旋转角速度"}},
-    {"name":"rotate_search","params":{"target_class":"同object_detect","description":"string,可选,目标属性描述","step_angle":"float,可选,每一步旋转的角度","total_rotation":"float,可选,总共旋转搜索的角度"}},
-    {"name":"manual_confirmation","params":{}},
-    {"name":"loiter","params":{"duration":"[1,600]秒/until_condition:可选"}},
-    {"name":"object_detect","params":{"target_class":"person,bicycle,car,motorcycle,airplane,bus,train,truck,boat,traffic_light,fire_hydrant,stop_sign,parking_meter,bench,bird,cat,dog,horse,sheep,cow,elephant,bear,zebra,giraffe,backpack,umbrella,handbag,tie,suitcase,frisbee,skis,snowboard,sports_ball,kite,baseball_bat,baseball_glove,skateboard,surfboard,tennis_racket,bottle,wine_glass,cup,fork,knife,spoon,bowl,banana,apple,sandwich,orange,broccoli,carrot,hot_dog,pizza,donut,cake,chair,couch,potted_plant,bed,dining_table,toilet,tv,laptop,mouse,remote,keyboard,cell_phone,microwave,oven,toaster,sink,refrigerator,book,clock,vase,scissors,teddy_bear,hair_drier,toothbrush,garbage","description":"可选，","count":"默认1"}},
-    {"name":"search_pattern","params":{"pattern_type":"spiral/grid","center_x":"±10000","center_y":"±10000","center_z":"[1,5000]","radius":"[5,1000]","target_class":"同object_detect","description":"可选，目标属性","count":"默认1"}},
-    {"name":"track_object","params":{"target_class":"同object_detect","description":"可选，目标属性","track_time":"[1,600]秒（必传，不可用'duration'）","min_confidence":"[0.5,1.0]默认0.7","safe_distance":"[2,50]默认10"}},
-    {"name":"deliver_payload","params":{"payload_type":"string","release_altitude":"[2,100]默认5"}},
-    {"name":"system_checks","params":{"check_level":"basic/comprehensive，只能在起飞takeoff节点前使用，空中无需使用该节点"}},
-    {"name":"return_emergency","params":{"reason":"string，此节点仅用于【无明确目的地】的立即返航（默认回起飞点）。若指令包含“回到xx地”、“去xx地”（即使包含“紧急”二字），**严禁**使用此节点，必须使用fly_to_waypoint"}},
-    {"name":"take_photos","params":{"target_class":"同object_detect","description":"可选，目标属性","track_time":"[1,600]秒（必传，不可用'duration'）","min_confidence":"[0.5,1.0]默认0.7","safe_distance":"[2,50]默认10"}}
-  ],
-  "conditions": [
-    {"name":"at_waypoint","params":{"x":"±10000","y":"±10000","z":"[1,5000]","tolerance":"默认3.0"}},
-    {"name":"object_detected","params":{"target_class":"同object_detect（必传）","description":"可选，目标属性","count":"默认1"}}
-  ],
-  "control_flow": [
-    {"name":"Sequence","params":{},"children":"子节点数组（按序执行，全成功则成功）"},
-    {"name":"Selector","params":{"memory":"默认true"},"children":"子节点数组（执行到成功为止）"},
-    {"name":"Parallel","params":{"policy":"all_success/success_on_one"},"children":"子节点数组（同时执行，默认all_success）"}
-  ],
-  "decorators": [
-    {"name":"SuccessIsFailure","params":{},"child":"单一子节点（将子节点的成功结果反转为失败）"}
-  ]
-}
-```
-
-
-## 二、节点必填字段（后端Schema强制要求，缺一验证失败）
-每个节点必须包含以下字段，字段名/类型不可自定义：
-1. **`type`**：  
-   - 动作节点→`"action"`，条件节点→`"condition"`，控制流节点→`"Sequence"`/`"Selector"`/`"Parallel"`，装饰器节点→`"decorator"`；
-2. **`name`**：必须是上述JSON中定义的`name`值；
-3. **`params`**：严格匹配上述节点的`params`定义，无自定义参数；
-4. **`children`**：仅控制流节点必含（子节点数组）；
-5. **`child`**：仅装饰器节点必含（单一子节点对象，非数组）。
-
-
-## 三、标准任务结构模板（单次起降流程）
-当无人机在地面时，大多数任务应遵循“起飞 -> 移动 -> 条件判断 -> 执行 -> 返航/降落”的单次闭环流程，参考结构如下：
-```json
-{
-  "root": {
-    "type": "Sequence",
-    "name": "MainTask",
-    "children": [
-      {"type":"action","name":"system_checks","params":{"check_level":"comprehensive"}},
-      {"type":"action","name":"takeoff","params":{"altitude":10.0}},
-      {"type":"action","name":"fly_to_waypoint","params":{"x":100.0,"y":50.0,"z":10.0}}, // 接近目标区域
-      // --- 核心任务区 (根据指令替换) ---
-      // --- 任务1执行---
-      {"type":"action","name":"rotate_search","params":{"target_class":"person","description":"目标描述"}},
-      {"type":"action","name":"object_detect","params":{"target_class":"person","description":"目标描述"}},
-      // ----条件判断(根据指令替换) -----
-      {"type":"condition","name":"object_detected","params":{"target_class":"person","description":"扎辫子女子"}},
-      // --- 任务2执行---
-      {"type":"action","name":"take_photos","params":{"target_class":"person","description":"扎辫子女子"}},     
-      // 默认不需要降落节点，除非用户明确要求
-    ]
-  }
-}
-```
-
-## 四、场景示例（请灵活参考）
-
-#### 场景 1：线性搜索任务（Sequence + Selector）
-**指令**：“无人机当前在地面，去研究所正大门，搜索扎辫子女子，找到后拍照。”
-**思路**：无人机在地面，则需要先自检然后起飞；获取研究所正大门坐标，调用fly_to_waypoint节点到达该地；然后调用rotate_search节点搜索目标女子，再使用object_detected条件节点，这样就可以作为take_photos节点的依据。
-**结构**：Sequence (按顺序执行)
-```json
-{
-  "root": {
-    "type": "Sequence",
-    "name": "MainSearchTask",
-    "children": [
-      {"type":"action","name":"takeoff","params":{"altitude":10.0}},
-      {"type":"action","name":"fly_to_waypoint","params":{"x":100.0,"y":50.0,"z":10.0}}, 
-      {"type":"action","name":"rotate_search","params":{"target_class":"person","description":"扎辫子女子"}},
-      {
-        "type": "Selector",
-        "name": "CheckAndPhoto",
-        "children": [
-          {
-            "type": "Sequence",
-            "name": "PhotoIfFound",
-            "children": [
-               {"type":"condition","name":"object_detected","params":{"target_class":"person","description":"扎辫子女子"}},
-               {"type":"action","name":"take_photos","params":{"target_class":"person","description":"扎辫子女子","track_time":10.0}}
-            ]
-          },
-          {"type":"action","name":"loiter","params":{"duration":5.0}} // 未发现时的备选动作
-        ]
-      }
-    ]
-  }
-}
-```
-
-#### 场景 2：带中断逻辑的巡逻（Selector 示例）
-**指令**：“无人机当前在地面，飞往航点A。如果途中发现可疑人员，则悬停。”
-**参考知识**：航点A的坐标（x:100.0,y:50.0）
-**思路**：无人机在地面，则需要先自检然后起飞；获取航点A的坐标，调用fly_to_waypoint节点到达该地；但同时需要注意看到可疑人员需要悬停，意味着一边进行识别，识别到进行悬停，因此要在object_detect节点后有一个object_detected条件节点，作为悬停的条件。
-**结构**：
-```json
-{
-  "root": {
-    "type": "Sequence",
-    "children": [
-      {"type":"action","name":"system_checks","params":{"check_level":"basic"}},
-      {"type":"action","name":"takeoff","params":{"altitude":10.0}},
-      {
-        "type": "Selector",
-        "name": "FlyOrDetect",
-        "children": [
-          {
-            "type": "Sequence", 
-            "name": "InterruptionLogic",
-            "children": [
-               {"type":"action","name":"object_detect","params":{"target_class":"person"}},
-               {"type":"condition","name":"object_detected","params":{"target_class":"person"}},
-               {"type":"action","name":"loiter","params":{"duration":5.0}}
-            ]
-          },
-          {"type":"action","name":"fly_to_waypoint","params":{"x":100.0,"y":50.0,"z":10.0}}
-        ]
-      }
-    ]
-  }
-}
-```
-
-#### 场景 3：长期监控任务（Parallel 示例）
-**指令**：“无人机当前在空中，往广场西边飞200米，持续监控5分钟，发现人就拍照告诉我，到时间可以返航。”
-**参考知识**：广场西边200米的坐标（x:50.0,y:50.0,z:10.0）
-**思路**：无人机在空中，直接前往目标点；到达后需要并行执行两件事：1. 倒计时5分钟（主控时间）；2. 持续检测人并拍照（从属任务）。
-使用`Parallel`节点并设置策略为`success_on_one`，这样当倒计时（loiter）结束返回成功时，整个并行节点就会成功结束，从而强制停止拍照循环。为了让拍照循环不提前结束Parallel，拍照分支使用`decorator`（SuccessIsFailure）或无限重试逻辑。
-**结构**：
-```json
-{
-  "root": {
-    "name": "主任务-监控与拍照",
-    "type": "Sequence",
-    "children": [
-      {
-        "name": "fly_to_waypoint",
-        "type": "action",
-        "params": {"x": 50.0, "y": 50.0, "z": 10.0}
-      },
-      {
-        "name": "并行监控5分钟",
-        "type": "Parallel",
-        "params": { "policy": "success_on_one" },
-        "children": [
-          {
-            "name": "loiter",
-            "type": "action",
-            "params": { "duration": 300 }
-          },
-          {
-            "name": "SuccessIsFailure",
-            "type": "decorator",
-            "child": {
-              "name": "check_and_photo",
-              "type": "Sequence",
-              "children": [
-                {"name": "object_detect", "type": "action", "params": { "target_class": "person" }},
-                {"name": "object_detected", "type": "condition", "params": { "target_class": "person" }},
-                {"name": "take_photos", "type": "action", "params": { "target_class": "person" }}
-              ]
-            }
-          }
-        ]
-      },
-      {
-        "name": "return_emergency",
-        "type": "action",
-        "params": {"reason": "返航"} // 返航回起飞点
-      }
-    ]
-  }
-}
-```
-
-#### 场景 4：交互式确认任务（Sequence + Manual Confirmation）
-**指令**：“无人机当前在空中，搜索小汽车，搜索到了我确认后再决定要不要拍照。”
-**思路**：无人机已在空中，无需起飞，直接进行搜索。首先使用`rotate_search`主动搜索目标，配合`object_detected`条件节点确认目标是否被检测到。检测到后，执行`manual_confirmation`节点等待用户确认。只有用户确认通过（返回Success），才会继续执行后续的`take_photos`动作。
-**结构**：Sequence
-```json
-{
-  "root": {
-    "type": "Sequence",
-    "name": "SearchConfirmPhoto",
-    "children": [
-      {"type":"action","name":"rotate_search","params":{"target_class":"car","description":"小汽车"}},
-      {"type":"condition","name":"object_detected","params":{"target_class":"car","description":"小汽车"}},
-      {"type":"action","name":"manual_confirmation","params":{}},
-      {"type":"action","name":"take_photos","params":{"target_class":"car","description":"小汽车"}}
-    ]
-  }
-}
-```
-
-## 六、高频错误规避
-1. 控制流节点的 `type` 必须是 `"Sequence"`, `"Selector"` 或 `"Parallel"`
-2. 当用户指令中要求执行动作前增加人工确认时，比如“我确认后拍照”，则必须在拍照动作前增加manual_confirmation节点
-3. 在条件节点执行前，必须有相应动作节点！如object_detected节点前必须是rotate_search等搜索类节点
-4. 当使用rotate_search或者object_detect节点时，必须有object_detected节点
-5. 用户指令中要求在当前位置执行任务时，无需fly_to_waypoint节点
-6. **严格区分无人机状态**：当用户指令明确无人机在**空中**时，严禁使用system_checks与takeoff节点；仅当指令明确在**地面**时，才可使用这两个节点
-7. **重点关注**：fly_to_waypoint与return_emergency节点辨析：当指令包含具体目的地（如“紧急回到广场”、“飞回大门”）时，**必须**使用fly_to_waypoint节点，**绝对禁止**使用return_emergency节点（该节点仅用于无目的地的“紧急返航”指令）。
-8. 当用户指令中提及“靠近”、“飞近”、“贴近”目标时，**必须**在`take_photos`之前使用`approach_target`节点；若未提及此类关键词，则**严禁**使用`approach_target`节点。
-9. **方向移动优先原则**：当指令为“快速去往东边100米”，直接使用 `move_direction` 节点+距离参数，严禁使用fly_to_waypoint
-
-## 七、坐标计算规则（东南天坐标系 ENU）
-本系统统一使用东南天（ENU）坐标系：
-- **X轴**：正方向为**东** (East)，负方向为**西** (West)
-- **Y轴**：正方向为**南** (South)向为**北** (North)
-- **Z轴**：正方向为**天** (Up)，负方向为**地** (Down)
-
-**仅当指令涉及前往“具体地点”（如广场、大门）的偏移位置时，才需计算绝对坐标并使用`fly_to_waypoint`：**
-
-当指令包含“具体地点 + 方向 + 距离”的偏移（如“广场西边200米”）时，**必须**先调用工具`calc_offset_enu`计算绝对坐标，再使用`fly_to_waypoint`。工具参数：
-- `base`: 参考地点的ENU坐标（含x/y/z）
-- `direction`: east/west/north/south/up/down
-- `distance`: 偏移距离（米）
-
-当指令只有“方向 + 距离”且**没有具体地点名词**时，**禁止**调用`calc_offset_enu`，必须使用`move_direction`。
-当指令描述“附近/边上/区域内”等模糊位置且**无方向+距离**时，视为到该地点本身，不做偏移计算。
-
-## 八、输出要求
-仅输出1个严格符合上述所有规则的JSON对象。
-
-## 九、vLLM 工具调用输出规则（必须遵守）
-当且仅当需要调用工具时，允许输出 `tool_call` XML（而不是JSON）。工具调用完成后，必须输出最终的行为树JSON对象。

backend_service/src/py_tree_generator.py

@@ -790,9 +790,89 @@ class PyTreeGenerator:
         except Exception as e:
             logging.warning(f"保存推理链Markdown失败: {e}")
 
-    async def generate(self, user_prompt: str) -> Dict[str, Any]:
+    async def generate(self, user_prompt: str, drone_state: str = "on_ground") -> Dict[str, Any]:
-        logging.info(f"接收到用户请求: {user_prompt}")
+        logging.info(f"接收到用户请求: {user_prompt}, drone_state={drone_state}")
-        return await self.orchestrator.generate(user_prompt)
+        return await self.orchestrator.generate(user_prompt, drone_state=drone_state)
+
+    def run_debug_stage(
+        self, user_prompt: str, drone_state: str = "on_ground", target_stage: int = 1
+    ) -> Dict[str, Any]:
+        """
+        分阶段调试：运行到指定 stage 并返回该 stage 的输出。
+        当 target_stage >= 2 时，响应中附带 upstream（前一 stage 的 output）。
+        当 target_stage >= 3 时，响应中附带 stage1 与 stage2 的 output。
+        以此类推，便于追溯完整流水线。
+        """
+        if target_stage < 1 or target_stage > 6:
+            return {"error": f"target_stage 必须在 1-6 之间，当前为 {target_stage}"}
+
+        upstream: Dict[str, Any] = {}
+
+        understanding = self.orchestrator.stages.stage1_task_understanding(
+            user_prompt, drone_state=drone_state
+        )
+        if target_stage == 1:
+            return {
+                "target_stage": 1,
+                "stage_name": "TaskUnderstanding",
+                "output": understanding.model_dump(),
+                "upstream": upstream,
+            }
+
+        upstream["stage1"] = understanding.model_dump()
+        context = self.orchestrator.stages.stage2_context_binding(user_prompt, understanding)
+        if target_stage == 2:
+            return {
+                "target_stage": 2,
+                "stage_name": "ContextBinding",
+                "output": context.model_dump(),
+                "upstream": upstream,
+            }
+
+        upstream["stage2"] = context.model_dump()
+        draft = self.orchestrator.stages.stage3_macro_planning(
+            user_prompt, understanding, context
+        )
+        if target_stage == 3:
+            return {
+                "target_stage": 3,
+                "stage_name": "BTDraft",
+                "output": draft.model_dump(),
+                "upstream": upstream,
+            }
+
+        upstream["stage3"] = draft.model_dump()
+        resolved_data = self.orchestrator.stages.stage4_middleware_resolution(draft)
+        if target_stage == 4:
+            return {
+                "target_stage": 4,
+                "stage_name": "MiddlewareResolution",
+                "output": {"resolved_data": resolved_data},
+                "upstream": upstream,
+            }
+
+        upstream["stage4"] = {"resolved_data": resolved_data}
+        final_tree = self.orchestrator.stages.stage5_micro_filling(
+            draft, resolved_data, understanding
+        )
+        if target_stage == 5:
+            return {
+                "target_stage": 5,
+                "stage_name": "MicroFilling",
+                "output": {"final_tree": final_tree},
+                "upstream": upstream,
+            }
+
+        upstream["stage5"] = {"final_tree": final_tree}
+        payload = self.orchestrator.stages.stage6_validate_and_postprocess(
+            user_prompt, understanding, context, draft, final_tree
+        )
+        return {
+            "target_stage": 6,
+            "stage_name": "ValidateAndPostprocess",
+            "output": payload,
+            "upstream": upstream,
+        }
 
 # Create a single instance for the application
 py_tree_generator = PyTreeGenerator()

tools/test_validate/modules/stage_debugger.py

@@ -39,6 +39,52 @@ def _select_stage():
         print("❌ 请输入 1-6 之间的数字")
 
 
+def _summarize_system_prompt_origin(obj: dict, upstream: dict) -> str:
+    """
+    根据上游 stage1 推断 system_prompt 的拼接顺序，仅展示文件名，不输出全文。
+    """
+    stage1 = upstream.get("stage1") or {}
+    scene_mode = stage1.get("scene_mode", "scene4")
+    drone_state = stage1.get("drone_state", "on_ground")
+    intent_type = stage1.get("intent_type", "generic_mission")
+
+    if scene_mode == "simple":
+        return "【system_prompt 来源】simple_mode_prompt.txt"
+
+    parts = [
+        "macro_header.txt",
+        "core_nodes.json (裁剪后)",
+        f"template_{'ground' if drone_state == 'on_ground' else 'air'}.txt",
+        "common_rules.txt",
+    ]
+    if intent_type == "generic_mission":
+        parts.append("[可选] system_extra_examples.txt")
+    parts.append("任务意图标签 (代码生成)")
+    return "【system_prompt 来源】" + " → ".join(parts)
+
+
+def _summarize_output_for_display(obj: dict, upstream: dict) -> dict:
+    """将 output/upstream 中的 system_prompt、final_prompt 替换为简要说明，便于终端查看"""
+    if not isinstance(obj, dict):
+        return obj
+    out = {}
+    for k, v in obj.items():
+        if k == "system_prompt" and isinstance(v, str) and len(v) > 200:
+            out[k] = _summarize_system_prompt_origin(obj, upstream) + f"\n(全文约 {len(v)} 字符，已保存至 response.json)"
+        elif k == "final_prompt" and isinstance(v, str) and len(v) > 200:
+            out[k] = f"【final_prompt】= system_prompt + user_prompt (全文约 {len(v)} 字符，已保存至 response.json)"
+        elif isinstance(v, dict):
+            out[k] = _summarize_output_for_display(v, upstream)
+        elif isinstance(v, list):
+            out[k] = [
+                _summarize_output_for_display(item, upstream) if isinstance(item, dict) else item
+                for item in v
+            ]
+        else:
+            out[k] = v
+    return out
+
+
 def _infer_drone_state_from_prompt(prompt: str) -> str:
     """从指令中简单推断 drone_state（批量模式下若未单独指定则用此）"""
     if "在空中" in prompt or "已起飞" in prompt:
@@ -75,8 +121,23 @@ def run_stage_debug_single():
                 print(f"✅ 请求成功 (耗时: {result['latency']:.2f}s)")
                 data = result["data"]
                 output = data.get("output", data)
+                upstream = data.get("upstream") or {}
+                target_stage = data.get("target_stage", 0)
+                if target_stage >= 2 and not upstream:
+                    print("\n⚠️  未获取到上游 Stage 输出。请重启后端服务 (如 start_all.sh) 后重试。")
+                elif upstream:
                     print("\n" + "=" * 60)
-                print(json.dumps(output, ensure_ascii=False, indent=2))
+                    print("【上游 Stage 输出】")
+                    print("=" * 60)
+                    for k, v in sorted(upstream.items()):
+                        print(f"\n--- {k} ---")
+                        summarized = _summarize_output_for_display(v, upstream)
+                        print(json.dumps(summarized, ensure_ascii=False, indent=2))
+                print("\n" + "=" * 60)
+                print(f"【Stage{data.get('target_stage', '?')} 输出】")
+                print("=" * 60)
+                summarized_output = _summarize_output_for_display(output, upstream)
+                print(json.dumps(summarized_output, ensure_ascii=False, indent=2))
                 print("=" * 60)
 
                 # 保存到 validation/temporary