diff --git a/backend_service/src/__pycache__/__init__.cpython-313.pyc b/backend_service/src/__pycache__/__init__.cpython-313.pyc index 440180f5..3a3bc7d5 100644 Binary files a/backend_service/src/__pycache__/__init__.cpython-313.pyc and b/backend_service/src/__pycache__/__init__.cpython-313.pyc differ diff --git a/backend_service/src/__pycache__/main.cpython-313.pyc b/backend_service/src/__pycache__/main.cpython-313.pyc index 049ce475..176b615d 100644 Binary files a/backend_service/src/__pycache__/main.cpython-313.pyc and b/backend_service/src/__pycache__/main.cpython-313.pyc differ diff --git a/backend_service/src/__pycache__/models.cpython-313.pyc b/backend_service/src/__pycache__/models.cpython-313.pyc index 8ce9945c..92238477 100644 Binary files a/backend_service/src/__pycache__/models.cpython-313.pyc and b/backend_service/src/__pycache__/models.cpython-313.pyc differ diff --git a/backend_service/src/__pycache__/py_tree_generator.cpython-313.pyc b/backend_service/src/__pycache__/py_tree_generator.cpython-313.pyc index c5e37492..e976244b 100644 Binary files a/backend_service/src/__pycache__/py_tree_generator.cpython-313.pyc and b/backend_service/src/__pycache__/py_tree_generator.cpython-313.pyc differ diff --git a/backend_service/src/__pycache__/websocket_manager.cpython-313.pyc b/backend_service/src/__pycache__/websocket_manager.cpython-313.pyc index 847b63c4..939083a5 100644 Binary files a/backend_service/src/__pycache__/websocket_manager.cpython-313.pyc and b/backend_service/src/__pycache__/websocket_manager.cpython-313.pyc differ diff --git a/backend_service/src/prompts/simple_mode_prompt.txt b/backend_service/src/prompts/simple_mode_prompt.txt index 525fa5fc..a3e38bb6 100644 --- a/backend_service/src/prompts/simple_mode_prompt.txt +++ b/backend_service/src/prompts/simple_mode_prompt.txt @@ -18,7 +18,11 @@ {"name": "takeoff", "description": "无人机从当前位置垂直起飞到指定的海拔高度。", "params": {"altitude": "float, 目标海拔高度(米)，范围[1, 100]，默认为2"}}, {"name": "land", "description": "降落无人机。可选择当前位置或返航点降落。", "params": {"mode": "string, 可选值: 'current'（当前位置）, 'home'（返航点）"}}, {"name": "fly_to_waypoint", "description": "导航至一个指定坐标点。使用相对坐标系（x,y,z），单位为米。", "params": {"x": "float", "y": "float", "z": "float", "acceptance_radius": "float, 可选，默认2.0"}}, - {"name": "move_direction", "description": "按指定方向直线移动。方向可为绝对方位或相对机体朝向。", "params": {"direction": "string: north|south|east|west|forward|backward|left|right", "distance": "float[1,10000], 可选, 不指定则持续移动"}}, + {"name": "move_direction", "description": "按指定方向直线移动。方向可为绝对方位或相对机体朝向。", "params": {"direction": "string: north|south|east|west|forward|backward|left|right", "distance": "float[1,10000], 可选, 不指定则持续移动", "speed": "float, 可选"}}, + {"name": "approach_target", "description": "快速趋近目标至固定距离。", "params": {"target_class": "string, 要趋近的目标类别", "description": "string, 可选", "stop_distance": "float, 期望的最终停止距离", "speed": "float, 可选"}}, + {"name": "rotate", "description": "旋转固定角度。", "params": {"angle": "float, 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", "description": "原地旋转搜索目标。", "params": {"target_class": "string, 要搜寻的目标类别", "description": "string, 可选", "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", "description": "前端弹窗是否继续执行后续任务。", "params": {}}, {"name": "orbit_around_point", "description": "以给定中心点为中心，等速圆周飞行指定圈数。", "params": {"center_x": "float", "center_y": "float", "center_z": "float", "radius": "float[5,1000]", "laps": "int[1,20]", "clockwise": "boolean, 可选, 默认true", "speed_mps": "float[0.5,15], 可选", "gimbal_lock": "boolean, 可选, 默认true"}}, {"name": "orbit_around_target", "description": "以目标为中心，等速圆周飞行指定圈数（需已有目标）。", "params": {"target_class": "string, 取值同object_detect列表", "description": "string, 可选", "radius": "float[5,1000]", "laps": "int[1,20]", "clockwise": "boolean, 可选, 默认true", "speed_mps": "float[0.5,15], 可选", "gimbal_lock": "boolean, 可选, 默认true"}}, {"name": "loiter", "description": "在当前位置上空悬停一段时间或直到条件触发。", "params": {"duration": "float, 可选[1,600]", "until_condition": "string, 可选"}}, @@ -32,7 +36,6 @@ {"name": "emergency_return", "description": "执行紧急返航程序。", "params": {"reason": "string"}} ], "conditions": [ - {"name": "battery_above", "description": "电池电量高于阈值。", "params": {"threshold": "float[0.0,1.0]"}}, {"name": "at_waypoint", "description": "在指定坐标容差范围内。", "params": {"x": "float", "y": "float", "z": "float", "tolerance": "float, 可选, 默认3.0"}}, {"name": "object_detected", "description": "检测到特定目标。", "params": {"target_class": "string", "description": "string, 可选", "count": "int, 可选, 默认1"}}, {"name": "target_destroyed", "description": "目标已被摧毁。", "params": {"target_class": "string", "description": "string, 可选", "confidence": "float[0.5-1.0], 默认0.8"}}, @@ -58,4 +61,4 @@ - “环绕X米Y圈” → 若有目标上下文则使用 `orbit_around_target`，否则根据是否给出中心坐标选择 `orbit_around_point`；`radius=X`，`laps=Y`，默认 `clockwise=true`，`gimbal_lock=true` - “顺时针/逆时针” → `clockwise=true/false` - “等速” → 若未给速度则 `speed_mps` 采用默认值（例如3.0）；若口令指明速度，裁剪到[0.5,15] -- “以(x,y,z)为中心”/“当前位置为中心” → 选择 `orbit_around_point` 并填充 `center_x/center_y/center_z` \ No newline at end of file +- “以(x,y,z)为中心”/“当前位置为中心” → 选择 `orbit_around_point` 并填充 `center_x/center_y/center_z` diff --git a/backend_service/src/prompts/system_prompt.txt b/backend_service/src/prompts/system_prompt.txt index a52410a8..bbf2c9fd 100644 --- a/backend_service/src/prompts/system_prompt.txt +++ b/backend_service/src/prompts/system_prompt.txt @@ -9,7 +9,11 @@ {"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"}}, - {"name":"move_direction","params":{"direction":"north/south/east/west/forward/backward/left/right","distance":"[1,10000]，缺省持续移动"}}, + {"name":"move_direction","params":{"direction":"north/south/east/west/forward/backward/left/right","distance":"[1,10000]，缺省持续移动","speed":"float,可选"}}, + {"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,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":"string,要搜寻的目标类别","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":"orbit_around_point","params":{"center_x":"±10000","center_y":"±10000","center_z":"[1,5000]","radius":"[5,1000]","laps":"[1,20]","clockwise":"默认true","speed_mps":"[0.5,15]","gimbal_lock":"默认true"}}, {"name":"orbit_around_target","params":{"target_class":"见object_detect列表","description":"可选，目标属性","radius":"[5,1000]","laps":"[1,20]","clockwise":"默认true","speed_mps":"[0.5,15]","gimbal_lock":"默认true"}}, {"name":"loiter","params":{"duration":"[1,600]秒/until_condition:可选"}}, @@ -20,10 +24,10 @@ {"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":"preflight_checks","params":{"check_level":"basic/comprehensive"}}, - {"name":"emergency_return","params":{"reason":"string"}} + {"name":"emergency_return","params":{"reason":"string"}}, + {"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":"battery_above","params":{"threshold":"[0.0,1.0]，必传"}}, {"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"}}, {"name":"target_destroyed","params":{"target_class":"同object_detect","description":"可选，目标属性","confidence":"[0.5,1.0]默认0.8"}}, @@ -34,6 +38,9 @@ {"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"},"children":"子节点数组（同时执行，严禁用'one_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）"} ] } ``` @@ -42,53 +49,91 @@ ## 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"`（与`name`字段值完全一致）； -2. **`name`**：必须是上述JSON中`actions`/`conditions`/`control_flow`下的`name`值（如“gps_status”不可错写为“gps_check”）； -3. **`params`**：严格匹配上述节点的`params`定义，无自定义参数（如优先级排序不可加“priority”字段，仅用`description`）； -4. **`children`**：仅控制流节点必含（子节点数组），动作/条件节点无此字段。 + - 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、行为树固定结构（通用不变，确保安全验证） -根节点必须是`Parallel`，`children`含`MainTask`（Sequence）和`SafetyMonitor`（Selector），结构不随任务类型（含优先级排序）修改： +## 三、标准任务结构模板（单次起降流程） +大多数任务应遵循“起飞 -> 接近 -> 执行 -> 返航/降落”的单次闭环流程，参考结构如下： ```json { "root": { - "type": "Parallel", - "name": "MissionWithSafety", - "params": {"policy": "all_success"}, + "type": "Sequence", + "name": "MainTask", "children": [ - { - "type": "Sequence", - "name": "MainTask", - "params": {}, - "children": [ - // 通用主任务步骤（含优先级排序任务示例，需按用户指令替换）： - {"type":"action","name":"preflight_checks","params":{"check_level":"comprehensive"}}, - {"type":"action","name":"takeoff","params":{"altitude":10.0}}, - {"type":"action","name":"fly_to_waypoint","params":{"x":200.0,"y":150.0,"z":10.0}}, // 搜索区坐标（用户未给时填合理值） - {"type":"action","name":"search_pattern","params":{"pattern_type":"grid","center_x":200.0,"center_y":150.0,"center_z":10.0,"radius":50.0,"target_class":"balloon","description":"红色"}}, - {"type":"condition","name":"object_detected","params":{"target_class":"balloon","description":"红色"}}, // 确认高优先级目标 - {"type":"action","name":"track_object","params":{"target_class":"balloon","description":"红色","track_time":30.0}}, - {"type":"action","name":"strike_target","params":{"target_class":"balloon","description":"红色"}}, - {"type":"action","name":"land","params":{"mode":"home"}} - ] - }, + {"type":"action","name":"preflight_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) --- + {"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"}}, + // ------------------------------- + {"type":"action","name":"land","params":{"mode":"home"}} + ] + } +} +``` + +## 四、场景示例（请灵活参考） + +#### 场景 1：线性搜索任务（Sequence + Selector） +**指令**：“去研究所正大门，搜索扎辫子女子并拍照。” +**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": "SafetyMonitor", - "params": {"memory": true}, + "name": "CheckAndPhoto", "children": [ - {"type":"condition","name":"battery_above","params":{"threshold":0.3}}, - {"type":"condition","name":"gps_status","params":{"min_satellites":8}}, { - "type":"Sequence", - "name":"EmergencyHandler", - "params": {}, + "type": "Sequence", + "name": "PhotoIfFound", "children": [ - {"type":"action","name":"emergency_return","params":{"reason":"safety_breach"}}, - {"type":"action","name":"land","params":{"mode":"home"}} + {"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 + ] + }, + {"type":"action","name":"land","params":{"mode":"home"}} + ] + } +} +``` + +#### 场景 2：带中断逻辑的巡逻（Selector 示例） +**指令**：“飞往航点A。如果途中发现可疑人员，则悬停。” +**结构**： +```json +{ + "root": { + "type": "Sequence", + "children": [ + {"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":"action","name":"loiter","params":{"duration":5.0}} + ] + }, + {"type":"action","name":"fly_to_waypoint","params":{"x":100.0,"y":50.0,"z":10.0}} ] } ] @@ -96,22 +141,20 @@ } ``` +## 五、优先级排序任务通用示例 +当用户指令中明确提出有多个待考察且具有优先级关系的物体时，节点描述须为优先级关系。 +| 用户指令场景 | `target_class` | `description` | +|-----------------------------|-----------------|-------------------------| +| 红气球＞蓝气球＞绿气球 | `balloon` | `（红＞蓝＞绿）` | +| 军用卡车＞民用卡车＞面包车 | `truck` | `（军用卡车＞民用卡车＞面包车）` | -## 四、优先级排序任务通用示例 -当用户指令中明确提出有多个待考察且具有优先级关系的物体时，节点描述须为优先级关系。比如当指令为已知有三个气球，危险级关系为红色气球大于蓝色气球大于绿色气球，要求优先跟踪最危险的气球时，节点的描述参考下表情形。 -| 用户指令场景 | `target_class` | `description` | 核心节点示例（search_pattern） | -|-----------------------------|-----------------|-------------------------|------------------------------------------------------------------------------------------------| -| 红气球＞蓝气球＞绿气球 | `balloon` | `（红＞蓝＞绿）` | `{"type":"action","name":"search_pattern","params":{"pattern_type":"grid","center_x":200,"center_y":150,"center_z":10,"radius":50,"target_class":"balloon","description":"（红＞蓝＞绿）"}}` | -| 军用卡车＞民用卡车＞面包车 | `truck` | `（军用卡车＞民用卡车＞面包车）` | `{"type":"action","name":"object_detect","params":{"target_class":"truck","description":"（军用卡车＞民用卡车＞面包车）"}}` | +## 六、高频错误规避 +1. 优先级排序不可修改`target_class`，仅用`description`填排序规则； +2. `track_object`必传`track_time`； +3. `gps_status`的`min_satellites`必须在6-15之间； +4. 严禁输出 markdown 代码块标记，直接输出 JSON 纯文本； +5. 控制流节点的 `type` 必须是 `"Sequence"`, `"Selector"` 或 `"Parallel"`； +6. 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 - -## 五、高频错误规避（确保验证通过） -1. 优先级排序不可修改`target_class`：如“民用卡车、面包车与军用卡车中，军用卡车优先”，`target_class`仍为`truck`，仅用`description`填排序规则； -2. 在没有明确指出物体之间的优先级关系情况下，`description`字段只描述物体属性本身，严禁与用户指令中不存在的物体进行排序； -3. `track_object`必传`track_time`：不可用`duration`替代（如跟踪30秒填`"track_time":30.0`）； -4. `gps_status`的`min_satellites`必须在6-15之间（如8，不可缺省）； -5. 无自定义节点：“锁定高优先级目标”需通过`object_detect`+`object_detected`实现，不可用“lock_high_risk_target”。 - - -## 六、输出要求 -仅输出1个严格符合上述所有规则的JSON对象，**确保：1. 优先级排序逻辑正确填入`description`；2. `target_class`匹配预定义列表；3. 行为树结构不变；4. 后端解析与Schema验证无错误**，无任何冗余内容。 +## 七、输出要求 +仅输出1个严格符合上述所有规则的JSON对象。 diff --git a/backend_service/src/py_tree_generator.py b/backend_service/src/py_tree_generator.py index dc405e4e..fb7e2e78 100644 --- a/backend_service/src/py_tree_generator.py +++ b/backend_service/src/py_tree_generator.py @@ -52,7 +52,7 @@ def _parse_allowed_nodes_from_prompt(prompt_text: str) -> tuple[Set[str], Set[st """ try: # 使用更精确的正则表达式匹配节点定义部分 - node_section_pattern = r"#### 2\. 可用节点定义.*?```json\s*({.*?})\s*```" + node_section_pattern = r"#### 1\. 可用节点定义.*?```json\s*({.*?})\s*```" match = re.search(node_section_pattern, prompt_text, re.DOTALL | re.IGNORECASE) if not match: @@ -144,51 +144,12 @@ def _fallback_parse_nodes(prompt_text: str) -> tuple[Set[str], Set[str]]: logging.error("在所有JSON代码块中都没有找到有效的节点定义结构。") return set(), set() -def _find_nodes_by_name(node: Dict, target_name: str) -> List[Dict]: - """递归查找所有指定名称的节点""" - nodes_found = [] - - if node.get("name") == target_name: - nodes_found.append(node) - - # 递归搜索子节点 - for child in node.get("children", []): - nodes_found.extend(_find_nodes_by_name(child, target_name)) - - return nodes_found - -def _validate_safety_monitoring(pytree_instance: dict) -> bool: - """验证行为树是否包含必要的安全监控""" - root_node = pytree_instance.get("root", {}) - - # 查找所有电池监控节点 - battery_nodes = _find_nodes_by_name(root_node, "battery_above") - - # 检查是否包含安全监控结构 - safety_monitors = _find_nodes_by_name(root_node, "SafetyMonitor") - - if not battery_nodes and not safety_monitors: - logging.warning("⚠️ 安全警告: 行为树中没有发现电池监控节点或安全监控器") - return False - - # 检查电池阈值设置是否合理 - for battery_node in battery_nodes: - threshold = battery_node.get("params", {}).get("threshold") - if threshold is not None: - if threshold < 0.25: - logging.warning(f"⚠️ 安全警告: 电池阈值设置过低 ({threshold})，建议不低于0.25") - elif threshold > 0.5: - logging.warning(f"⚠️ 安全警告: 电池阈值设置过高 ({threshold})，可能影响任务执行") - - logging.info("✅ 安全监控验证通过") - return True - def _generate_pytree_schema(allowed_actions: set, allowed_conditions: set) -> dict: """ 根据允许的行动和条件节点，动态生成一个JSON Schema。 """ # 所有可能的节点类型 - node_types = ["action", "condition", "Sequence", "Selector", "Parallel"] + node_types = ["action", "condition", "Sequence", "Selector", "Parallel", "decorator"] # 目标检测相关的类别枚举 target_classes = [ @@ -201,38 +162,44 @@ def _generate_pytree_schema(allowed_actions: set, allowed_conditions: set) -> di "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","balloon" + "clock", "vase", "scissors", "teddy_bear", "hair_drier", "toothbrush","balloon","trash","window" ] # 递归节点定义 node_definition = { "type": "object", "properties": { - "type": {"type": "string", "enum": node_types}, + # 修改：手动构造不区分大小写的正则，避免使用不支持的 (?i) 标志 + # 匹配: action, condition, sequence, selector, parallel, decorator (忽略大小写) + "type": { + "type": "string", + "pattern": "^([Aa][Cc][Tt][Ii][Oo][Nn]|[Cc][Oo][Nn][Dd][Ii][Tt][Ii][Oo][Nn]|[Ss][Ee][Qq][Uu][Ee][Nn][Cc][Ee]|[Ss][Ee][Ll][Ee][Cc][Tt][Oo][Rr]|[Pp][Aa][Rr][Aa][Ll][Ll][Ee][Ll]|[Dd][Ee][Cc][Oo][Rr][Aa][Tt][Oo][Rr])$" + }, "name": {"type": "string"}, "params": {"type": "object"}, "children": { "type": "array", "items": {"$ref": "#/definitions/node"} - } + }, + "child": {"$ref": "#/definitions/node"} }, "required": ["type", "name"], "allOf": [ - # 动作节点验证 + # 动作节点验证 (忽略大小写) { - "if": {"properties": {"type": {"const": "action"}}}, + "if": {"properties": {"type": {"pattern": "^[Aa][Cc][Tt][Ii][Oo][Nn]$"}}}, "then": {"properties": {"name": {"enum": sorted(list(allowed_actions))}}} }, - # 条件节点验证 + # 条件节点验证 (忽略大小写) { - "if": {"properties": {"type": {"const": "condition"}}}, + "if": {"properties": {"type": {"pattern": "^[Cc][Oo][Nn][Dd][Ii][Tt][Ii][Oo][Nn]$"}}}, "then": {"properties": {"name": {"enum": sorted(list(allowed_conditions))}}} }, - # 目标检测动作节点的参数验证 + # 目标检测动作节点的参数验证 (忽略大小写) { "if": { "properties": { - "type": {"const": "action"}, + "type": {"pattern": "^[Aa][Cc][Tt][Ii][Oo][Nn]$"}, "name": {"const": "object_detect"} } }, @@ -251,11 +218,11 @@ def _generate_pytree_schema(allowed_actions: set, allowed_conditions: set) -> di } } }, - # 目标检测条件节点的参数验证 + # 目标检测条件节点的参数验证 (忽略大小写) { "if": { "properties": { - "type": {"const": "condition"}, + "type": {"pattern": "^[Cc][Oo][Nn][Dd][Ii][Tt][Ii][Oo][Nn]$"}, "name": {"const": "object_detected"} } }, @@ -274,11 +241,11 @@ def _generate_pytree_schema(allowed_actions: set, allowed_conditions: set) -> di } } }, - # 电池监控节点的参数验证 + # 电池监控节点的参数验证 (忽略大小写) { "if": { "properties": { - "type": {"const": "condition"}, + "type": {"pattern": "^[Cc][Oo][Nn][Dd][Ii][Tt][Ii][Oo][Nn]$"}, "name": {"const": "battery_above"} } }, @@ -295,11 +262,11 @@ def _generate_pytree_schema(allowed_actions: set, allowed_conditions: set) -> di } } }, - # GPS状态节点的参数验证 + # GPS状态节点的参数验证 (忽略大小写) { "if": { "properties": { - "type": {"const": "condition"}, + "type": {"pattern": "^[Cc][Oo][Nn][Dd][Ii][Tt][Ii][Oo][Nn]$"}, "name": {"const": "gps_status"} } }, @@ -372,10 +339,7 @@ def _validate_pytree_with_schema(pytree_instance: dict, schema: dict) -> bool: jsonschema.validate(instance=pytree_instance, schema=schema) logging.info("✅ JSON Schema验证成功") - # 额外验证安全监控 - safety_valid = _validate_safety_monitoring(pytree_instance) - - return True and safety_valid + return True except jsonschema.ValidationError as e: logging.warning("❌ Pytree验证失败") logging.warning(f"错误信息: {e.message}") @@ -503,6 +467,10 @@ def _add_nodes_and_edges(node: dict, dot, parent_id: str | None = None) -> str: shape = 'ellipse' style = 'filled' fillcolor = '#e1d5e7' # 紫色 + elif node_type == 'decorator': + shape = 'doubleoctagon' + style = 'filled' + fillcolor = '#f8cecc' # 浅红 # 特别标记安全相关节点 if node.get('name') in ['battery_above', 'gps_status', 'SafetyMonitor']: @@ -515,28 +483,28 @@ def _add_nodes_and_edges(node: dict, dot, parent_id: str | None = None) -> str: if parent_id: dot.edge(parent_id, current_id) - # 递归处理子节点 + # 递归处理子节点 (Sequence, Selector, Parallel 等) children = node.get("children", []) - if not children: - return current_id - - # 记录所有子节点的ID - child_ids = [] - - # 正确的递归连接：每个子节点都连接到当前节点 - for child in children: - child_id = _add_nodes_and_edges(child, dot, current_id) - child_ids.append(child_id) - - # 子节点同级排列（横向排布，更直观地表现同层） - if len(child_ids) > 1: - with dot.subgraph(name=f"rank_{current_id}") as s: - s.attr(rank='same') - for cid in child_ids: - s.node(cid) - - # 行为树中，所有类型的节点都只是父连子，不需要子节点间的额外连接 - # Sequence、Selector、Parallel 的执行逻辑由行为树引擎处理，不需要在可视化中体现 + if children: + # 记录所有子节点的ID + child_ids = [] + + # 正确的递归连接：每个子节点都连接到当前节点 + for child in children: + child_id = _add_nodes_and_edges(child, dot, current_id) + child_ids.append(child_id) + + # 子节点同级排列（横向排布，更直观地表现同层） + if len(child_ids) > 1: + with dot.subgraph(name=f"rank_{current_id}") as s: + s.attr(rank='same') + for cid in child_ids: + s.node(cid) + + # 递归处理单子节点 (Decorator) + child = node.get("child") + if child: + _add_nodes_and_edges(child, dot, current_id) return current_id @@ -588,7 +556,7 @@ class PyTreeGenerator: self.complex_llm_client = openai.OpenAI(api_key=self.api_key, base_url=self.complex_base_url) # --- ChromaDB Client Setup --- - vector_store_path = os.path.abspath(os.path.join(self.base_dir, '..', '..', 'tools', 'vector_store')) + vector_store_path = os.path.abspath(os.path.join(self.base_dir, '..', '..', 'tools', 'rag','vector_store')) self.chroma_client = chromadb.PersistentClient(path=vector_store_path) # Explicitly use the remote embedding function for queries @@ -725,7 +693,7 @@ class PyTreeGenerator: pytree_str = combined_text if combined_text else (msg_content or "") raw_full_text_for_logging = pytree_str # 保存完整原文（含 ）以便失败时完整打印 - # 提取 推理链内容（若存在） + # 提取 推理链内容（若有） reasoning_text = None try: think_match = re.search(r"([\s\S]*?)", pytree_str) @@ -827,49 +795,7 @@ class PyTreeGenerator: pytree_dict['final_prompt'] = final_prompt return pytree_dict - # 复杂模式回退：若模型误返回简单结构（root是单个action），则自动包装为含安全监控的行为树 - if mode == "complex" and isinstance(pytree_dict, dict) and 'root' in pytree_dict: - root_node = pytree_dict.get('root', {}) - # 检查是否是简单结构（root是单个action节点，没有children） - if (root_node.get('type') == 'action' and - ('children' not in root_node or not root_node.get('children'))): - try: - jsonschema.validate(instance=pytree_dict, schema=self.simple_schema) - logging.warning("⚠️ 复杂模式生成了简单结构（单个action），触发自动包装为完整行为树的回退逻辑。") - action_name = root_node.get('name') - action_params = root_node.get('params') if isinstance(root_node.get('params'), dict) else {} - - safety_selector = { - "type": "Selector", - "name": "SafetyMonitor", - "params": {"memory": True}, - "children": [ - {"type": "condition", "name": "battery_above", "params": {"threshold": 0.3}}, - {"type": "condition", "name": "gps_status", "params": {"min_satellites": 8}}, - {"type": "Sequence", "name": "EmergencyHandler", "children": [ - {"type": "action", "name": "emergency_return", "params": {"reason": "safety_breach"}}, - {"type": "action", "name": "land", "params": {"mode": "home"}} - ]} - ] - } - - main_children = [{"type": "action", "name": action_name, "params": action_params}] - if action_name != "land": - main_children.append({"type": "action", "name": "land", "params": {"mode": "home"}}) - - root_parallel = { - "type": "Parallel", - "name": "MissionWithSafety", - "params": {"policy": "all_success"}, - "children": [ - {"type": "Sequence", "name": "MainTask", "children": main_children}, - safety_selector - ] - } - pytree_dict = {"root": root_parallel} - except jsonschema.ValidationError: - # 不符合简单结构，按正常复杂验证继续 - pass + # 验证生成的复杂行为树 if _validate_pytree_with_schema(pytree_dict, self.schema): logging.info("✅ 成功生成并验证了Pytree") plan_id = str(uuid.uuid4()) diff --git a/tools/rag/README.md b/tools/rag/README.md new file mode 100644 index 00000000..4fe96cfe --- /dev/null +++ b/tools/rag/README.md @@ -0,0 +1,39 @@ +# RAG & Map Tools + +该目录包含了地图构建、知识库生成和向量数据库管理的相关工具。 + +## 目录结构 + +- **knowledge_base/**: 存放源文档数据。 + - 支持格式: `.txt`, `.md`, `.pdf` + - 生成格式: `.json`, `.ndjson` (由 `build_knowledge_base.py` 生成) + +- **map/**: 存放地图原始数据。 + - `.osm` (OpenStreetMap 数据) + - `.world` (Gazebo 仿真环境数据) + +- **vector_store/**: ChromaDB 向量数据库的持久化存储目录。 + +## 脚本说明 + +### 1. `build_knowledge_base.py` +**功能**: 处理 `map/` 目录下的地图文件，提取地理信息和语义描述，生成知识库文件到 `knowledge_base/` 目录。 +**使用方法**: +```bash +python build_knowledge_base.py +``` + +### 2. `ingest.py` +**功能**: 读取 `knowledge_base/` 中的所有文档，调用嵌入模型（Embedding Model）将其向量化，并存入 `vector_store/` 中的 ChromaDB 数据库。 +**使用方法**: +```bash +python ingest.py +``` +**依赖**: 需要确保后端嵌入服务（如 `llama-server`）已启动，或者配置正确的 `ORIN_IP` 环境变量。 + +## 工作流 +1. 将地图文件放入 `map/`。 +2. 运行 `build_knowledge_base.py` 生成文本描述。 +3. 将其他补充文档放入 `knowledge_base/`。 +4. 运行 `ingest.py` 构建向量索引。 + diff --git a/tools/rag/build_knowledge_base.py b/tools/rag/build_knowledge_base.py new file mode 100644 index 00000000..19ffaba3 --- /dev/null +++ b/tools/rag/build_knowledge_base.py @@ -0,0 +1,157 @@ +import xml.etree.ElementTree as ET +import json +from pathlib import Path +import logging +import os + +# --- 配置日志 --- +logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(levelname)s - %(message)s') + +def process_osm_json(input_path: Path) -> list[str]: + """ + 处理OpenStreetMap的JSON文件，返回描述性句子列表。 + """ + logging.info(f"正在以OSM JSON格式处理文件: {input_path.name}") + descriptions = [] + try: + with open(input_path, 'r', encoding='utf-8') as f: + data = json.load(f) + except (json.JSONDecodeError, IOError) as e: + logging.error(f"读取或解析 {input_path.name} 时出错: {e}") + return [] + + elements = data.get('elements', []) + if not elements: + return [] + + nodes_map = {node['id']: node for node in elements if node.get('type') == 'node'} + ways = [elem for elem in elements if elem.get('type') == 'way'] + + for way in ways: + tags = way.get('tags', {}) + if 'name' not in tags: + continue + + way_name = tags.get('name') + way_nodes_ids = way.get('nodes', []) + if not way_nodes_ids: + continue + + total_lat, total_lon, node_count = 0, 0, 0 + for node_id in way_nodes_ids: + node_info = nodes_map.get(node_id) + if node_info: + total_lat += node_info.get('lat', 0) + total_lon += node_info.get('lon', 0) + node_count += 1 + + if node_count == 0: + continue + + center_lat = total_lat / node_count + center_lon = total_lon / node_count + + sentence = f"在地图上有一个名为 '{way_name}' 的地点或区域" + other_tags = {k: v for k, v in tags.items() if k != 'name'} + if other_tags: + tag_descs = [f"{key}是'{value}'" for key, value in other_tags.items()] + sentence += f"，它的{ '、'.join(tag_descs) }" + sentence += f"，其中心位置坐标大约在 ({center_lat:.6f}, {center_lon:.6f})。" + descriptions.append(sentence) + + logging.info(f"从 {input_path.name} 提取了 {len(descriptions)} 条位置描述。") + return descriptions + + +def process_gazebo_world(input_path: Path) -> list[str]: + """ + 处理Gazebo的.world文件，返回描述性句子列表。 + """ + logging.info(f"正在以Gazebo World格式处理文件: {input_path.name}") + descriptions = [] + try: + tree = ET.parse(input_path) + root = tree.getroot() + except ET.ParseError as e: + logging.error(f"解析XML文件 {input_path.name} 失败: {e}") + return [] + + models = root.findall('.//model') + for model in models: + model_name = model.get('name') + pose_element = model.find('pose') + + if model_name and pose_element is not None and pose_element.text: + try: + pose_values = [float(p) for p in pose_element.text.strip().split()] + sentence = ( + f"仿真环境中有一个名为 '{model_name}' 的物体，" + f"其位置和姿态(x, y, z, roll, pitch, yaw)为: {pose_values}。" + ) + descriptions.append(sentence) + except (ValueError, IndexError): + logging.warning(f"跳过模型 '{model_name}'，因其pose格式不正确。") + + logging.info(f"从 {input_path.name} 提取了 {len(descriptions)} 个物体信息。") + return descriptions + + +def main(): + """ + 主函数，扫描源数据目录，为每个文件生成独立的NDJSON知识库。 + """ + script_dir = Path(__file__).resolve().parent + # 输入源: tools/map/ + source_data_dir = script_dir / 'map' + # 输出目录: tools/knowledge_base/ + output_knowledge_base_dir = script_dir / 'knowledge_base' + + if not source_data_dir.exists(): + logging.error(f"源数据目录不存在: {source_data_dir}") + return + + # 确保输出目录存在 + output_knowledge_base_dir.mkdir(parents=True, exist_ok=True) + + total_files_processed = 0 + logging.info(f"--- 开始扫描源数据目录: {source_data_dir} ---") + + for file_path in source_data_dir.iterdir(): + if not file_path.is_file(): + continue + + descriptions = [] + if file_path.suffix == '.json': + descriptions = process_osm_json(file_path) + elif file_path.suffix == '.world': + descriptions = process_gazebo_world(file_path) + else: + logging.warning(f"跳过不支持的文件类型: {file_path.name}") + continue + + if not descriptions: + logging.warning(f"未能从 {file_path.name} 提取有效信息，跳过生成文件。") + continue + + output_filename = file_path.stem + '_knowledge.ndjson' + output_path = output_knowledge_base_dir / output_filename + + try: + with open(output_path, 'w', encoding='utf-8') as f: + for sentence in descriptions: + json_record = {"text": sentence} + f.write(json.dumps(json_record, ensure_ascii=False) + '\n') + logging.info(f"成功为 '{file_path.name}' 生成知识库文件: {output_path.name}") + total_files_processed += 1 + except IOError as e: + logging.error(f"写入输出文件 '{output_path.name}' 失败: {e}") + + logging.info("--- 数据处理完成 ---") + if total_files_processed > 0: + logging.info(f"共为 {total_files_processed} 个源文件生成了知识库。") + else: + logging.warning("未生成任何知识库文件。") + + +if __name__ == "__main__": + main() \ No newline at end of file diff --git a/tools/rag/ingest.py b/tools/rag/ingest.py new file mode 100644 index 00000000..476a3ece --- /dev/null +++ b/tools/rag/ingest.py @@ -0,0 +1,194 @@ +# 该代码用于将本地知识库中的文档导入到ChromaDB中，并使用远程嵌入模型进行向量化 +import os +from pathlib import Path +import chromadb +# from chromadb.utils import embedding_functions - 不再需要 +from chromadb.api.types import Documents, EmbeddingFunction, Embeddings, Embeddable +from unstructured.partition.auto import partition +from rich.progress import track +import logging +import requests # 导入requests +import json # 导入json模块 + +# 配置日志 +logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(levelname)s - %(message)s') + +# --- 配置 --- +# 获取脚本所在目录，确保路径的正确性 +SCRIPT_DIR = Path(__file__).resolve().parent +KNOWLEDGE_BASE_DIR = SCRIPT_DIR / "knowledge_base" +VECTOR_STORE_DIR = SCRIPT_DIR / "vector_store" +COLLECTION_NAME = "drone_docs" +# EMBEDDING_MODEL_NAME = "bge-small-zh-v1.5" # 不再需要，模型名在函数内部处理 + +# --- 自定义远程嵌入函数 --- +class RemoteEmbeddingFunction(EmbeddingFunction[Embeddable]): + """ + 一个使用远程、兼容OpenAI API的嵌入服务的嵌入函数。 + """ + def __init__(self, api_url: str): + self._api_url = api_url + logging.info(f"自定义嵌入函数已初始化，将连接到: {self._api_url}") + + def __call__(self, input: Embeddable) -> Embeddings: + """ + 对输入的文档进行嵌入。 + """ + # 我们的服务只能处理文本，所以检查输入是否为字符串列表 + if not isinstance(input, list) or not all(isinstance(doc, str) for doc in input): + logging.error("此嵌入函数仅支持字符串列表（文档）作为输入。") + return [] + + try: + # 移除 "model" 参数，因为embedding服务可能不需要它 + response = requests.post( + self._api_url, + json={"input": input}, + headers={"Content-Type": "application/json"} + ) + response.raise_for_status() # 如果请求失败则抛出HTTPError + + # 按照OpenAI API的格式解析返回的嵌入向量 + data = response.json().get("data", []) + if not data: + raise ValueError("API响应中没有找到'data'字段或'data'为空") + + embeddings = [item['embedding'] for item in data] + return embeddings + + except requests.RequestException as e: + logging.error(f"调用嵌入API失败: {e}") + # 返回一个空列表或根据需要处理错误 + return [] + except (ValueError, KeyError) as e: + logging.error(f"解析API响应失败: {e}") + logging.error(f"收到的响应内容: {response.text}") + return [] + + +def get_documents(directory: Path): + """从知识库目录加载所有文档并进行切分""" + documents = [] + logging.info(f"从 '{directory}' 加载文档...") + for file_path in directory.rglob("*"): + if file_path.is_file() and not file_path.name.startswith('.'): + try: + # 对简单文本文件直接读取 + if file_path.suffix in ['.txt', '.md']: + text = file_path.read_text(encoding='utf-8') + documents.append({ + "text": text, + "metadata": {"source": str(file_path.name)} + }) + logging.info(f"成功处理文本文件: {file_path.name}") + # 特别处理常规的JSON文件 + elif file_path.suffix == '.json': + with open(file_path, 'r', encoding='utf-8') as f: + data = json.load(f) + if 'elements' in data and isinstance(data['elements'], list): + for element in data['elements']: + documents.append({ + "text": json.dumps(element, ensure_ascii=False), + "metadata": {"source": str(file_path.name)} + }) + logging.info(f"成功处理JSON文件: {file_path.name}, 提取了 {len(data['elements'])} 个元素。") + else: + documents.append({ + "text": json.dumps(data, ensure_ascii=False), + "metadata": {"source": str(file_path.name)} + }) + logging.info(f"成功处理JSON文件: {file_path.name} (作为单个文档)") + # 新增：专门处理我们生成的 NDJSON 文件 + elif file_path.suffix == '.ndjson': + with open(file_path, 'r', encoding='utf-8') as f: + count = 0 + for line in f: + try: + record = json.loads(line) + if 'text' in record and isinstance(record['text'], str): + documents.append({ + "text": record['text'], + "metadata": {"source": str(file_path.name)} + }) + count += 1 + except json.JSONDecodeError: + logging.warning(f"跳过无效的JSON行: {line.strip()}") + if count > 0: + logging.info(f"成功处理NDJSON文件: {file_path.name}, 提取了 {count} 个文档。") + # 对其他所有文件类型，使用unstructured + else: + elements = partition(filename=str(file_path)) + for element in elements: + documents.append({ + "text": element.text, + "metadata": {"source": str(file_path.name)} + }) + logging.info(f"成功处理文件: {file_path.name} (使用unstructured)") + except Exception as e: + logging.error(f"处理文件 {file_path.name} 失败: {e}") + return documents + + +def main(): + """主函数，执行文档入库流程""" + if not KNOWLEDGE_BASE_DIR.exists(): + KNOWLEDGE_BASE_DIR.mkdir(parents=True) + logging.warning(f"知识库目录不存在，已自动创建: {KNOWLEDGE_BASE_DIR}") + logging.warning("请向该目录中添加您的知识文件(如 .txt, .pdf, .md)。") + return + + # 1. 加载并切分文档 + docs_to_ingest = get_documents(KNOWLEDGE_BASE_DIR) + if not docs_to_ingest: + logging.warning("在知识库中未找到可处理的文档。") + return + + # 2. 初始化ChromaDB客户端和远程嵌入函数 + orin_ip = os.getenv("ORIN_IP", "localhost") + embedding_api_url = f"http://{orin_ip}:8090/v1/embeddings" + + logging.info(f"正在初始化远程嵌入函数，目标服务地址: {embedding_api_url}") + embedding_func = RemoteEmbeddingFunction(api_url=embedding_api_url) + + client = chromadb.PersistentClient(path=str(VECTOR_STORE_DIR)) + + # 3. 创建或获取集合 + logging.info(f"正在访问ChromaDB集合: {COLLECTION_NAME}") + collection = client.get_or_create_collection( + name=COLLECTION_NAME, + embedding_function=embedding_func + ) + + # 4. 将文档向量化并存入数据库 + logging.info(f"开始将 {len(docs_to_ingest)} 个文档块入库...") + + # 为了避免重复添加，可以先检查 + # (这里为了简单，我们每次都重新添加，生产环境需要更复杂的逻辑) + + doc_texts = [doc['text'] for doc in docs_to_ingest] + metadatas = [doc['metadata'] for doc in docs_to_ingest] + ids = [f"doc_{KNOWLEDGE_BASE_DIR.name}_{i}" for i in range(len(doc_texts))] + + try: + # ChromaDB的add方法会自动处理嵌入 + collection.add( + documents=doc_texts, + metadatas=metadatas, + ids=ids + ) + logging.info("所有文档块已成功入库！") + except Exception as e: + logging.error(f"向ChromaDB添加文档时出错: {e}") + + + # 验证一下 + count = collection.count() + logging.info(f"数据库中现在有 {count} 个条目。") + + print("\n✅ 数据入库完成！") + print(f"知识库位于: {KNOWLEDGE_BASE_DIR}") + print(f"向量数据库位于: {VECTOR_STORE_DIR}") + + +if __name__ == "__main__": + main() \ No newline at end of file diff --git a/tools/rag/knowledge_base/export_knowledge.ndjson b/tools/rag/knowledge_base/export_knowledge.ndjson new file mode 100644 index 00000000..5169b6be --- /dev/null +++ b/tools/rag/knowledge_base/export_knowledge.ndjson @@ -0,0 +1,6 @@ +{"text": "在地图上有一个名为 '跷跷板' 的地点或区域，它的leisure是'playground'，其中心位置坐标大约在 (x:15, y:-8.5, z:1.2)。"} +{"text": "在地图上有一个名为 'A地' 的地点或区域，它的building是'commercial'，其中心位置坐标大约在 (x:10, y:-10, z:2)。"} +{"text": "在地图上有一个名为 '学生宿舍' 的地点或区域，它的building是'dormitory'，其中心位置坐标大约在 (x:5, y:3, z:2)。"} +{"text": "地点：'研究所正大门'。别名：'大门'、'入口'。坐标：(x:-23.8, y:292.8, z:14)。建议悬停高度：14米。适合任务：定点侦察、拍照。"} +{"text": "地点：'研究所广场'。属性：开阔区域。坐标：(x:-24.0, y:241.8, z:14)。建议搜索半径：30米。适合任务：寻找人员、旋转搜索。"} +{"text": "路线：'研究所外围巡逻'。关键航点序列：[(x:-24.0, y:241.8), (x:-107.8, y:289.8), (x:-106.5, y:241.3), (x:-23.80, y:292.80)]。高度：14米。适合环绕侦察任务。"} diff --git a/tools/rag/map/export.json b/tools/rag/map/export.json new file mode 100644 index 00000000..fd4b0d2b --- /dev/null +++ b/tools/rag/map/export.json @@ -0,0 +1,70349 @@ +{ + "version": 0.6, + "generator": "Overpass API 0.7.62.7 375dc00a", + "osm3s": { + "timestamp_osm_base": "2025-07-16T07:03:51Z", + "copyright": "The data included in this document is from www.openstreetmap.org. 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b/tools/rag/vector_store/chroma.sqlite3 new file mode 100644 index 00000000..0de942cb Binary files /dev/null and b/tools/rag/vector_store/chroma.sqlite3 differ diff --git a/tools/test_validate/README.md b/tools/test_validate/README.md new file mode 100644 index 00000000..1fc98126 --- /dev/null +++ b/tools/test_validate/README.md @@ -0,0 +1,57 @@ +# Test & Validation Tools (Unified) + +该目录包含用于测试无人机规划系统、API 接口及 LLM 服务的集成验证工具集。 + +## 🚀 快速开始 + +使用统一入口脚本启动交互式菜单： + +```bash +python run_tests.py +``` + +## 🛠️ 测试模式 + +### 1. 交互式单次测试 (Mode 1) +- **场景**: 快速验证单条指令，调试 Prompt。 +- **操作**: 在终端输入自然语言指令，即时获取结果。 +- **输出**: `validation/temporary/{指令名}/` + - `response.json`: 完整 API 响应 + - `plan.png`: 可视化任务树 + - `process.log`: 请求与响应日志 + +### 2. 批量/场景测试 (Mode 2) +- **场景**: + - **场景测试**: 验证一组预定义指令的正确性（默认运行 1 次）。 + - **稳定性测试**: 对同一组指令进行高频重复测试（如运行 10 次），检测成功率和延迟抖动。 +- **操作**: + 1. 选择指令文件（位于 `instructions/` 目录）。 + 2. 输入每条指令的运行次数（默认 1）。 +- **输出**: `validation/{时间戳}/` + - `test_summary.csv`: 统计摘要（成功率、平均耗时） + - `test_details.csv`: 每次运行的详细记录 + - `instructions_backup.txt`: 本次测试使用的指令备份 + - `{指令名}/`: 包含所有运行的 `.json` 和 `.png` 产物 + +## 📂 目录结构 + +```text +tools/test_validate/ +├── instructions/ # 指令集文件 (.txt) +├── modules/ # 功能模块 +│ ├── api_client.py # API 客户端核心 +│ ├── interactive_test.py # 交互式测试逻辑 +│ ├── batch_runner.py # 批量测试逻辑 +│ ├── visualizer.py # 可视化工具库 +│ ├── llm_tester.py # LLM 连接测试 +│ └── drone_uploader.py # 任务上传工具 +├── validation/ # 测试产物输出 +│ ├── temporary/ # 交互式测试结果 +│ └── {时间戳}/ # 批量测试结果 +└── run_tests.py # 主程序入口 +``` + +## 📄 配置文件 + +- **instructions/validate_instructions.txt**: 默认的预定义场景指令集。 +- 您可以在 `instructions/` 下添加任意 `.txt` 文件，测试时会在菜单中自动列出供选择。 diff --git a/tools/test_validate/instructions/validate_instructions.txt b/tools/test_validate/instructions/validate_instructions.txt new file mode 100644 index 00000000..1ac9c029 --- /dev/null +++ b/tools/test_validate/instructions/validate_instructions.txt @@ -0,0 +1,5 @@ +去研究所正大门，搜索扎辫子女子并拍照。 +查找戴帽子的女子，找到后近距离拍照。 +到研究所广场，对长发可疑男子进行拍照。 +到研究所广场，寻找黄色衣服男子，我确认后再对其拍照。 +立即返航。 \ No newline at end of file diff --git a/tools/test_validate/modules/__pycache__/api_client.cpython-313.pyc b/tools/test_validate/modules/__pycache__/api_client.cpython-313.pyc new file mode 100644 index 00000000..ffc32d47 Binary files /dev/null and b/tools/test_validate/modules/__pycache__/api_client.cpython-313.pyc differ diff --git a/tools/test_validate/modules/__pycache__/batch_runner.cpython-313.pyc b/tools/test_validate/modules/__pycache__/batch_runner.cpython-313.pyc new file mode 100644 index 00000000..de2182f3 Binary files /dev/null and b/tools/test_validate/modules/__pycache__/batch_runner.cpython-313.pyc differ diff --git a/tools/test_validate/modules/__pycache__/interactive_test.cpython-313.pyc b/tools/test_validate/modules/__pycache__/interactive_test.cpython-313.pyc new file mode 100644 index 00000000..1021179f Binary files /dev/null and b/tools/test_validate/modules/__pycache__/interactive_test.cpython-313.pyc differ diff --git a/tools/test_validate/modules/__pycache__/visualizer.cpython-313.pyc b/tools/test_validate/modules/__pycache__/visualizer.cpython-313.pyc new file mode 100644 index 00000000..5ebcf156 Binary files /dev/null and b/tools/test_validate/modules/__pycache__/visualizer.cpython-313.pyc differ diff --git a/tools/test_validate/modules/api_client.py b/tools/test_validate/modules/api_client.py new file mode 100644 index 00000000..2f5881b2 --- /dev/null +++ b/tools/test_validate/modules/api_client.py @@ -0,0 +1,60 @@ +import requests +import time +import json + +class APIClient: + def __init__(self, base_url="http://127.0.0.1:8000"): + self.base_url = base_url + self.endpoint = "/generate_plan" + + def send_request(self, prompt, timeout=60): + """ + Sends a request to the API and returns a structured result. + Returns: + dict: { + "success": bool, + "data": dict or None, + "latency": float (seconds), + "error": str or None, + "http_status": int or None + } + """ + url = f"{self.base_url}{self.endpoint}" + payload = {"user_prompt": prompt} + headers = {"Content-Type": "application/json"} + + start_time = time.time() + try: + response = requests.post(url, json=payload, headers=headers, timeout=timeout) + latency = time.time() - start_time + + response.raise_for_status() + + try: + data = response.json() + return { + "success": True, + "data": data, + "latency": latency, + "error": None, + "http_status": response.status_code + } + except json.JSONDecodeError: + return { + "success": False, + "data": None, + "latency": latency, + "error": f"Invalid JSON response: {response.text[:200]}", + "http_status": response.status_code + } + + except requests.exceptions.RequestException as e: + latency = time.time() - start_time + return { + "success": False, + "data": None, + "latency": latency, + "error": str(e), + "http_status": getattr(e.response, 'status_code', None) + } + diff --git a/tools/test_validate/modules/batch_runner.py b/tools/test_validate/modules/batch_runner.py new file mode 100644 index 00000000..f3f99b01 --- /dev/null +++ b/tools/test_validate/modules/batch_runner.py @@ -0,0 +1,129 @@ +import os +import json +import time +import csv +import shutil +from datetime import datetime +from .api_client import APIClient +from .visualizer import generate_visualization, sanitize_filename + +def run_batch_test(): + # 1. 选择指令文件 + base_dir = os.path.dirname(os.path.dirname(__file__)) + instr_dir = os.path.join(base_dir, "instructions") + files = [f for f in os.listdir(instr_dir) if f.endswith('.txt')] + + if not files: + print("❌ 未在 instructions 目录下找到 .txt 文件") + return + + print("\n请选择测试指令文件:") + for i, f in enumerate(files): + print(f"{i+1}. {f}") + + try: + idx = int(input("请输入序号: ").strip()) - 1 + if idx < 0 or idx >= len(files): + print("❌ 无效序号") + return + selected_file = os.path.join(instr_dir, files[idx]) + except ValueError: + print("❌ 输入无效") + return + + # 2. 配置参数 + try: + iterations = int(input("请输入每条指令的测试次数 (默认1): ").strip() or "1") + except ValueError: + iterations = 1 + + # 3. 准备输出目录 + timestamp = datetime.now().strftime("%Y%m%d%H%M%S") + output_dir = os.path.join(base_dir, "validation", timestamp) + os.makedirs(output_dir, exist_ok=True) + + # 备份指令文件 + shutil.copy(selected_file, os.path.join(output_dir, "instructions_backup.txt")) + + # 读取指令 + with open(selected_file, 'r', encoding='utf-8') as f: + instructions = [line.strip() for line in f if line.strip() and not line.startswith('#')] + + print(f"\n🚀 开始批量测试 (共 {len(instructions)} 条指令, 每条 {iterations} 次)") + print(f"📂 输出目录: {output_dir}\n") + + client = APIClient() + detailed_results = [] + summary_stats = {} + + for i, prompt in enumerate(instructions, 1): + print(f"[{i}/{len(instructions)}] 测试指令: {prompt[:30]}...") + safe_name = sanitize_filename(prompt) + instr_out_dir = os.path.join(output_dir, safe_name) + os.makedirs(instr_out_dir, exist_ok=True) + + success_count = 0 + total_latency = 0 + + for k in range(1, iterations + 1): + print(f" - 第 {k} 次...", end="", flush=True) + result = client.send_request(prompt) + + # 记录详情 + detailed_results.append({ + "instruction": prompt, + "run_id": k, + "success": result['success'], + "latency": result['latency'], + "error": result['error'] or "" + }) + + # 保存产物 + if result['success']: + print(f" ✅ ({result['latency']:.2f}s)") + success_count += 1 + total_latency += result['latency'] + + # 保存JSON + with open(os.path.join(instr_out_dir, f"{k}.json"), 'w', encoding='utf-8') as f: + json.dump(result['data'], f, indent=2, ensure_ascii=False) + + # 保存图片 + if result['data'] and 'root' in result['data']: + generate_visualization(result['data']['root'], os.path.join(instr_out_dir, f"{k}.png")) + else: + print(f" ❌ {result['error']}") + + time.sleep(0.5) # 避免过快请求 + + # 统计单条指令 + avg_lat = total_latency / success_count if success_count > 0 else 0 + summary_stats[prompt] = { + "total_runs": iterations, + "success_runs": success_count, + "success_rate": f"{(success_count/iterations)*100:.1f}%", + "avg_latency": f"{avg_lat:.2f}s" + } + + # 4. 生成报告 + # 详细报告 + with open(os.path.join(output_dir, "test_details.csv"), 'w', newline='', encoding='utf-8') as f: + writer = csv.DictWriter(f, fieldnames=["instruction", "run_id", "success", "latency", "error"]) + writer.writeheader() + writer.writerows(detailed_results) + + # 摘要报告 + with open(os.path.join(output_dir, "test_summary.csv"), 'w', newline='', encoding='utf-8') as f: + writer = csv.writer(f) + writer.writerow(["Instruction", "Total Runs", "Success Runs", "Success Rate", "Avg Latency"]) + for prompt, stats in summary_stats.items(): + writer.writerow([ + prompt, + stats["total_runs"], + stats["success_runs"], + stats["success_rate"], + stats["avg_latency"] + ]) + + print(f"\n✅ 测试完成! 统计报告已保存至 {output_dir}") + diff --git a/tools/test_validate/modules/drone_uploader.py b/tools/test_validate/modules/drone_uploader.py new file mode 100644 index 00000000..682b5171 --- /dev/null +++ b/tools/test_validate/modules/drone_uploader.py @@ -0,0 +1,37 @@ +import requests +import os +import sys + +def upload_mission(drone_ip, file_path): + """上传一个JSON任务文件到无人机""" + if not os.path.exists(file_path): + print(f"Error: File not found at {file_path}") + return + + url = f"http://{drone_ip}:5000/missions" + print(f"正在上传 {file_path} 到 {url} ...") + + try: + with open(file_path, 'rb') as f: + files = {'file': (os.path.basename(file_path), f, 'application/json')} + response = requests.post(url, files=files, timeout=10) + + # 检查HTTP响应状态码 + response.raise_for_status() + + print("上传成功!") + print("无人机端响应:", response.json()) + + except requests.exceptions.RequestException as e: + print(f"上传过程中发生错误: {e}") + +if __name__ == '__main__': + if len(sys.argv) < 3: + print("用法: python ground_station_client.py [无人机IP地址] [JSON文件路径]") + print("示例: python ground_station_client.py 192.168.1.10 ./missions/rescue_mission.json") + sys.exit(1) + + drone_ip_address = sys.argv[1] + mission_file_path = sys.argv[2] + + upload_mission(drone_ip_address, mission_file_path) diff --git a/tools/test_validate/modules/interactive_test.py b/tools/test_validate/modules/interactive_test.py new file mode 100644 index 00000000..918f807d --- /dev/null +++ b/tools/test_validate/modules/interactive_test.py @@ -0,0 +1,87 @@ +import os +import json +import logging +from .api_client import APIClient +from .visualizer import generate_visualization, sanitize_filename + +# 配置日志 +logging.basicConfig(level=logging.INFO, format='%(message)s') + +def run_interactive_test(): + client = APIClient() + print("\n🚀 进入交互式测试模式 (输入 'exit' 或 'q' 退出)") + + while True: + try: + prompt = input("\n请输入测试指令: ").strip() + if prompt.lower() in ['exit', 'q']: + break + if not prompt: + continue + + print("⏳ 正在请求后端 API...") + result = client.send_request(prompt) + + if result['success']: + print(f"✅ 请求成功 (耗时: {result['latency']:.2f}s)") + + # 创建输出目录 + sanitized_name = sanitize_filename(prompt) + output_dir = os.path.join( + os.path.dirname(os.path.dirname(__file__)), + "validation", + "temporary", + sanitized_name + ) + os.makedirs(output_dir, exist_ok=True) + + # 保存 JSON + json_path = os.path.join(output_dir, "response.json") + with open(json_path, 'w', encoding='utf-8') as f: + json.dump(result['data'], f, indent=2, ensure_ascii=False) + + # 保存日志 + log_path = os.path.join(output_dir, "process.log") + with open(log_path, 'w', encoding='utf-8') as f: + f.write(f"Prompt: {prompt}\n") + f.write(f"Status: {result['http_status']}\n") + f.write(f"Latency: {result['latency']}\n") + f.write(f"Response: {json.dumps(result['data'], ensure_ascii=False)}\n") + + # 生成图片 + if result['data'] and 'root' in result['data']: + png_path = os.path.join(output_dir, "plan.png") + if generate_visualization(result['data']['root'], png_path): + print(f"🖼️ 可视化图已生成: {png_path}") + else: + print("⚠️ 可视化生成失败") + + print(f"📂 结果已保存至: {output_dir}") + else: + print(f"❌ 请求失败: {result['error']}") + + # 即使失败也保存日志，以便排查 + sanitized_name = sanitize_filename(prompt) + output_dir = os.path.join( + os.path.dirname(os.path.dirname(__file__)), + "validation", + "temporary", + sanitized_name + ) + os.makedirs(output_dir, exist_ok=True) + + log_path = os.path.join(output_dir, "process.log") + with open(log_path, 'w', encoding='utf-8') as f: + f.write(f"Prompt: {prompt}\n") + f.write(f"Status: {result['http_status']}\n") + f.write(f"Latency: {result['latency']}\n") + f.write(f"Error: {result['error']}\n") + # 如果有部分数据，也记录下来 + if result['data']: + f.write(f"Partial Response: {json.dumps(result['data'], ensure_ascii=False)}\n") + print(f"⚠️ 错误日志已保存至: {log_path}") + + except KeyboardInterrupt: + print("\n已取消") + break + diff --git a/tools/test_validate/modules/llm_tester.py b/tools/test_validate/modules/llm_tester.py new file mode 100644 index 00000000..af75b2c7 --- /dev/null +++ b/tools/test_validate/modules/llm_tester.py @@ -0,0 +1,174 @@ +#!/usr/bin/env python3 +# -*- coding: utf-8 -*- + +import os +import sys +import json +import argparse +from typing import Any, Dict + +import requests + + +def build_args() -> argparse.Namespace: + parser = argparse.ArgumentParser( + description="调用本地 llama-server (OpenAI兼容) 进行推理，支持自定义系统/用户提示词" + ) + parser.add_argument( + "--base-url", + default=os.getenv("SIMPLE_BASE_URL", "http://127.0.0.1:8081/v1"), + help="llama-server 的基础URL（默认: http://127.0.0.1:8081/v1，或环境变量 SIMPLE_BASE_URL）", + ) + parser.add_argument( + "--model", + default=os.getenv("SIMPLE_MODEL", "local-model"), + help="模型名称（默认: local-model，或环境变量 SIMPLE_MODEL）", + ) + parser.add_argument( + "--system", + default="You are a helpful assistant.", + help="系统提示词（system role）", + ) + parser.add_argument( + "--system-file", + default=None, + help="系统提示词文件路径（txt）；若提供，则覆盖 --system 的字符串", + ) + parser.add_argument( + "--user", + default=None, + help="用户提示词（user role）；若不传则从交互式输入读取", + ) + parser.add_argument( + "--temperature", + type=float, + default=0.2, + help="采样温度（默认: 0.2）", + ) + parser.add_argument( + "--max-tokens", + type=int, + default=4096, + help="最大生成Token数（默认: 4096）", + ) + parser.add_argument( + "--timeout", + type=float, + default=120.0, + help="HTTP超时时间秒（默认: 120）", + ) + parser.add_argument( + "--verbose", + action="store_true", + help="打印完整返回JSON", + ) + return parser.parse_args() + + +def call_llama_server( + base_url: str, + model: str, + system_prompt: str, + user_prompt: str, + temperature: float, + max_tokens: int, + timeout: float, +) -> Dict[str, Any]: + endpoint = base_url.rstrip("/") + "/chat/completions" + headers: Dict[str, str] = {"Content-Type": "application/json"} + + # 兼容需要API Key的代理/服务（llama-server通常不强制） + api_key = os.getenv("OPENAI_API_KEY") + if api_key: + headers["Authorization"] = f"Bearer {api_key}" + + payload: Dict[str, Any] = { + "model": model, + "messages": [ + {"role": "system", "content": system_prompt}, + {"role": "user", "content": user_prompt}, + ], + "temperature": temperature, + "max_tokens": max_tokens, + } + + resp = requests.post(endpoint, headers=headers, data=json.dumps(payload), timeout=timeout) + resp.raise_for_status() + return resp.json() + + +def main() -> None: + args = build_args() + + user_prompt = args.user + if not user_prompt: + try: + user_prompt = input("请输入用户提示词: ") + except KeyboardInterrupt: + print("\n已取消。") + sys.exit(1) + + # 解析系统提示词：优先使用 --system-file + system_prompt = args.system + if args.system_file: + try: + with open(args.system_file, "r", encoding="utf-8") as f: + system_prompt = f.read() + except Exception as e: + print("\n❌ 读取系统提示词文件失败：") + print(str(e)) + sys.exit(1) + + try: + print("--- llama-server 推理 ---") + print(f"Base URL: {args.base_url}") + print(f"Model: {args.model}") + if args.system_file: + print(f"System(from file): {args.system_file}") + else: + print(f"System: {system_prompt}") + print(f"User: {user_prompt}") + + data = call_llama_server( + base_url=args.base_url, + model=args.model, + system_prompt=system_prompt, + user_prompt=user_prompt, + temperature=args.temperature, + max_tokens=args.max_tokens, + timeout=args.timeout, + ) + + if args.verbose: + print("\n完整返回JSON:") + print(json.dumps(data, ensure_ascii=False, indent=2)) + + # 尝试按OpenAI兼容格式提取assistant内容 + content = None + try: + content = data["choices"][0]["message"]["content"] + except Exception: + pass + + if content is not None: + print("\n模型输出:") + print(content) + else: + # 兜底打印 + print("\n无法按OpenAI兼容字段解析内容，原始返回如下：") + print(json.dumps(data, ensure_ascii=False)) + + except requests.exceptions.RequestException as e: + print("\n❌ 请求失败：请确认 llama-server 已在 8081 端口启动并可访问。") + print(f"详情: {e}") + sys.exit(2) + except Exception as e: + print("\n❌ 发生未预期的错误：") + print(str(e)) + sys.exit(3) + + +if __name__ == "__main__": + main() + + diff --git a/tools/test_validate/modules/visualizer.py b/tools/test_validate/modules/visualizer.py new file mode 100644 index 00000000..95f1ee73 --- /dev/null +++ b/tools/test_validate/modules/visualizer.py @@ -0,0 +1,287 @@ +#!/usr/bin/env python3 +# -*- coding: utf-8 -*- +""" +从API测试日志中提取JSON响应并批量可视化 +""" +import json +import os +import re +import logging +import platform +import random +import html +from typing import Dict, List, Tuple +from collections import defaultdict + +# 配置日志 +logging.basicConfig( + level=logging.INFO, + format='%(asctime)s - %(levelname)s - %(message)s' +) + +def sanitize_filename(text: str) -> str: + """将文本转换为安全的文件名""" + # 移除或替换不安全的字符 + text = re.sub(r'[<>:"/\\|?*]', '_', text) + # 限制长度 + if len(text) > 100: + text = text[:100] + return text + +def _pick_zh_font(): + """选择合适的中文字体""" + sys = platform.system() + if sys == "Windows": + return "Microsoft YaHei" + elif sys == "Darwin": + return "PingFang SC" + else: + return "Noto Sans CJK SC" + +def _add_nodes_and_edges(node: dict, dot, parent_id: str | None = None) -> str: + """递归辅助函数，用于添加节点和边。""" + try: + from graphviz import Digraph + except ImportError: + logging.critical("错误：未安装graphviz库。请运行: pip install graphviz") + return "" + + current_id = f"{id(node)}_{random.randint(1000, 9999)}" + + # 准备节点标签（HTML-like，正确换行与转义） + name = html.escape(str(node.get('name', ''))) + ntype = html.escape(str(node.get('type', ''))) + label_parts = [f"{name} ({ntype})"] + + # 格式化参数显示 + params = node.get('params') or {} + if params: + params_lines = [] + for key, value in params.items(): + k = html.escape(str(key)) + if isinstance(value, float): + value_str = f"{value:.2f}".rstrip('0').rstrip('.') + else: + value_str = str(value) + v = html.escape(value_str) + params_lines.append(f"{k}: {v}") + params_text = "
".join(params_lines) + label_parts.append(f"{params_text}") + + node_label = f"<{'
'.join(label_parts)}>" + + # 根据类型设置节点样式和颜色 + node_type = (node.get('type') or '').lower() + shape = 'ellipse' + style = 'filled' + fillcolor = '#e6e6e6' # 默认灰色填充 + border_color = '#666666' # 默认描边色 + + if node_type == 'action': + shape = 'box' + style = 'rounded,filled' + fillcolor = "#cde4ff" # 浅蓝 + elif node_type == 'condition': + shape = 'diamond' + style = 'filled' + fillcolor = "#fff2cc" # 浅黄 + elif node_type == 'sequence': + shape = 'ellipse' + style = 'filled' + fillcolor = '#d5e8d4' # 绿色 + elif node_type == 'selector': + shape = 'ellipse' + style = 'filled' + fillcolor = '#ffe6cc' # 橙色 + elif node_type == 'parallel': + shape = 'ellipse' + style = 'filled' + fillcolor = '#e1d5e7' # 紫色 + + # 特别标记安全相关节点 + if node.get('name') in ['battery_above', 'gps_status', 'SafetyMonitor']: + border_color = '#ff0000' # 红色边框突出显示安全节点 + style = 'filled,bold' # 加粗 + + dot.node(current_id, label=node_label, shape=shape, style=style, fillcolor=fillcolor, color=border_color) + + # 连接父节点 + if parent_id: + dot.edge(parent_id, current_id) + + # 递归处理子节点 + children = node.get("children", []) + if not children: + return current_id + + # 记录所有子节点的ID + child_ids = [] + + # 正确的递归连接：每个子节点都连接到当前节点 + for child in children: + child_id = _add_nodes_and_edges(child, dot, current_id) + child_ids.append(child_id) + + # 子节点同级排列（横向排布，更直观地表现同层） + if len(child_ids) > 1: + with dot.subgraph(name=f"rank_{current_id}") as s: + s.attr(rank='same') + for cid in child_ids: + s.node(cid) + + return current_id + +def generate_visualization(node: Dict, file_path: str): + """ + 使用Graphviz将Pytree字典可视化，并保存到指定路径。 + """ + try: + from graphviz import Digraph + except ImportError: + logging.critical("错误：未安装graphviz库。请运行: pip install graphviz") + return False + + fontname = _pick_zh_font() + + dot = Digraph('Pytree', comment='Drone Mission Plan') + dot.attr(rankdir='TB', label='Drone Mission Plan', fontsize='20', fontname=fontname) + dot.attr('node', shape='box', style='rounded,filled', fontname=fontname) + dot.attr('edge', fontname=fontname) + + _add_nodes_and_edges(node, dot) + + try: + # 确保输出目录存在 + base_path, ext = os.path.splitext(file_path) + render_path = base_path if ext.lower() == '.png' else file_path + + out_dir = os.path.dirname(render_path) + if out_dir and not os.path.exists(out_dir): + os.makedirs(out_dir, exist_ok=True) + + # 保存为 .png 文件，并自动删除源码 .gv 文件 + dot.render(render_path, format='png', cleanup=True, view=False) + return True + except Exception as e: + logging.error(f"❌ 生成可视化图形失败: {e}") + return False + +# 保留旧的函数以兼容（如果有其他脚本引用） +def _visualize_pytree(node: Dict, file_path: str): + return generate_visualization(node, file_path) + +def parse_log_file(log_file_path: str) -> Dict[str, List[Dict]]: + """ + 解析日志文件，提取原始指令和完整API响应JSON + 返回: {原始指令: [JSON响应列表]} + """ + with open(log_file_path, 'r', encoding='utf-8') as f: + content = f.read() + + # 按分隔符分割条目 + entries = re.split(r'={80,}', content) + + results = defaultdict(list) + + for entry in entries: + if not entry.strip(): + continue + + # 提取原始指令 + instruction_match = re.search(r'原始指令:\s*(.+)', entry) + if not instruction_match: + continue + + original_instruction = instruction_match.group(1).strip() + + # 提取完整API响应JSON + json_match = re.search(r'完整API响应:\s*\n(\{.*\})', entry, re.DOTALL) + if not json_match: + logging.warning(f"未找到指令 '{original_instruction}' 的JSON响应") + continue + + json_str = json_match.group(1).strip() + + try: + json_obj = json.loads(json_str) + results[original_instruction].append(json_obj) + logging.info(f"成功提取指令 '{original_instruction}' 的JSON响应") + except json.JSONDecodeError as e: + logging.error(f"解析指令 '{original_instruction}' 的JSON失败: {e}") + continue + + return results + +def process_and_visualize(log_file_path: str, output_dir: str): + """ + 处理日志文件并批量可视化 + """ + # 创建输出目录 + os.makedirs(output_dir, exist_ok=True) + + # 解析日志文件 + logging.info(f"开始解析日志文件: {log_file_path}") + instruction_responses = parse_log_file(log_file_path) + + logging.info(f"共找到 {len(instruction_responses)} 个不同的原始指令") + + # 处理每个指令的所有响应 + for instruction, responses in instruction_responses.items(): + logging.info(f"\n处理指令: {instruction} (共 {len(responses)} 个响应)") + + # 创建指令目录（使用安全的文件名） + safe_instruction_name = sanitize_filename(instruction) + instruction_dir = os.path.join(output_dir, safe_instruction_name) + os.makedirs(instruction_dir, exist_ok=True) + + # 处理每个响应 + for idx, response in enumerate(responses, 1): + try: + # 提取root节点 + root_node = response.get('root') + if not root_node: + logging.warning(f"响应 #{idx} 没有root节点，跳过") + continue + + # 生成文件名 + json_filename = f"response_{idx}.json" + png_filename = f"response_{idx}.png" + + json_path = os.path.join(instruction_dir, json_filename) + png_path = os.path.join(instruction_dir, png_filename) + + # 保存JSON文件 + with open(json_path, 'w', encoding='utf-8') as f: + json.dump(response, f, ensure_ascii=False, indent=2) + + logging.info(f" 保存JSON: {json_filename}") + + # 生成可视化 + generate_visualization(root_node, png_path) + logging.info(f" 生成可视化: {png_filename}") + + except Exception as e: + logging.error(f"处理响应 #{idx} 时出错: {e}") + continue + + logging.info(f"\n✅ 所有处理完成！结果保存在: {output_dir}") + +if __name__ == "__main__": + import argparse + + parser = argparse.ArgumentParser(description="批量可视化API测试日志") + parser.add_argument("--log", default=os.path.join(os.path.dirname(os.path.dirname(__file__)), "api_test_log.txt"), help="日志文件路径") + parser.add_argument("--out", default=os.path.join(os.path.dirname(os.path.dirname(__file__)), "validation"), help="输出目录") + + args = parser.parse_args() + + log_file = args.log + output_directory = args.out + + print(f"日志文件: {log_file}") + print(f"输出目录: {output_directory}") + + if os.path.exists(log_file): + process_and_visualize(log_file, output_directory) + else: + print(f"错误: 找不到日志文件 {log_file}") \ No newline at end of file diff --git a/tools/test_validate/run_tests.py b/tools/test_validate/run_tests.py new file mode 100755 index 00000000..5fc2dcfb --- /dev/null +++ b/tools/test_validate/run_tests.py @@ -0,0 +1,118 @@ +#!/usr/bin/env python3 +# -*- coding: utf-8 -*- + +import os +import sys +import time +import subprocess + +# Add current directory to path so modules can be imported +sys.path.append(os.path.dirname(os.path.abspath(__file__))) + +from modules.interactive_test import run_interactive_test +from modules.batch_runner import run_batch_test + +def clear_screen(): + os.system('cls' if os.name == 'nt' else 'clear') + +def print_header(): + clear_screen() + print("=" * 60) + print(" Drone Planning 系统测试工具箱 (Unified)") + print("=" * 60) + print(f"当前工作目录: {os.getcwd()}") + print("-" * 60) + +def run_legacy_module(module_name, args=None): + """运行旧的独立 Python 脚本 (用于 LLM 测试和上传工具)""" + script_path = os.path.join(os.path.dirname(__file__), "modules", module_name) + + if not os.path.exists(script_path): + print(f"❌ 错误: 找不到脚本 {script_path}") + input("\n按回车键继续...") + return + + cmd = [sys.executable, script_path] + if args: + cmd.extend(args) + + print(f"\n🚀 正在启动: {module_name} ...\n") + try: + # 保持当前环境变量 + env = os.environ.copy() + # 确保 PYTHONPATH 包含当前目录 + env["PYTHONPATH"] = os.path.dirname(__file__) + os.pathsep + env.get("PYTHONPATH", "") + subprocess.run(cmd, env=env, check=False) + except KeyboardInterrupt: + print("\n\n⚠️ 操作已取消") + except Exception as e: + print(f"\n❌ 运行出错: {e}") + + input("\n按回车键返回菜单...") + +def menu_drone_upload(): + print("\n[3] 上传任务到无人机") + print("说明: 将生成的任务文件上传到无人机 (Ground Station Client)。") + + ip = input("\n请输入无人机 IP 地址 (默认: 127.0.0.1): ").strip() or "127.0.0.1" + file_path = input("请输入任务文件路径 (.json): ").strip() + + if not file_path: + print("❌ 必须提供文件路径！") + time.sleep(1) + return + + if not os.path.exists(file_path): + print(f"❌ 文件不存在: {file_path}") + time.sleep(1) + return + + run_legacy_module("drone_uploader.py", [ip, file_path]) + +def main(): + # 切换到脚本所在目录 + os.chdir(os.path.dirname(os.path.abspath(__file__))) + + while True: + print_header() + print("请选择测试模式:") + print("1. 交互式单次测试 (Interactive Single Test)") + print(" - 手动输入指令，即时查看结果和可视化") + print("2. 批量/场景测试 (Batch/Scenario Test)") + print(" - 读取指令文件，支持多轮压力测试，生成统计报告") + print("3. 上传任务到无人机 (Drone Uploader)") + print("4. LLM 服务连通性测试 (LLM Tester)") + print("0. 退出") + print("-" * 60) + + choice = input("请输入选项 [0-4]: ").strip() + + if choice == '1': + try: + run_interactive_test() + except Exception as e: + print(f"❌ 运行出错: {e}") + input("\n按回车键返回菜单...") + + elif choice == '2': + try: + run_batch_test() + except Exception as e: + print(f"❌ 运行出错: {e}") + input("\n按回车键返回菜单...") + + elif choice == '3': + menu_drone_upload() + + elif choice == '4': + run_legacy_module("llm_tester.py") + + elif choice == '0': + print("\n👋 再见！") + break + else: + print("\n❌ 无效选项，请重试") + time.sleep(1) + +if __name__ == "__main__": + main()