diff --git a/.gitattributes b/.gitattributes
index c7d9f3332a950355d5a77d85000f05e6f45435ea..3fa076007ed129a1a3f024d2f17146ba12fe027d 100644
--- a/.gitattributes
+++ b/.gitattributes
@@ -32,3 +32,6 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
*.zip filter=lfs diff=lfs merge=lfs -text
*.zst filter=lfs diff=lfs merge=lfs -text
*tfevents* filter=lfs diff=lfs merge=lfs -text
+DI-sheep/service/ckpt_best.pth.tar filter=lfs diff=lfs merge=lfs -text
+DI-sheep/ui/public/demo.gif filter=lfs diff=lfs merge=lfs -text
+DI-sheep/ui/public/sound-disco.mp3 filter=lfs diff=lfs merge=lfs -text
diff --git a/DI-sheep/LICENSE b/DI-sheep/LICENSE
new file mode 100644
index 0000000000000000000000000000000000000000..afdfe50e72e0e63f3b2bd373e6147a170277ffdc
--- /dev/null
+++ b/DI-sheep/LICENSE
@@ -0,0 +1,202 @@
+
+ Apache License
+ Version 2.0, January 2004
+ http://www.apache.org/licenses/
+
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diff --git a/DI-sheep/README.md b/DI-sheep/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..39dc4440d952fe2cb421218170f104c7dea5bb5e
--- /dev/null
+++ b/DI-sheep/README.md
@@ -0,0 +1,103 @@
+# DI-sheep：深度强化学习 + 羊了个羊
+
+当 AI 技术的明珠——深度强化学习，遇到号称“通关率只有0.01%”的游戏“羊了个羊”，会碰撞出哪些奇思妙想呢？
+
+P.S. 路过记得点个 star  ，持续更新ing。
+
+P.S.S. 想了解更多深度强化学习相关知识？快来 [DI-engine](https://github.com/opendilab/DI-engine) 训练自己的智能体。
+
+
+
+
+
+# News
+- [bilibili] [羊群加不进去？那就来加猫群叭！深度强化学习版的羊了个羊来了](https://www.bilibili.com/video/BV1N24y1o7Lw/?spm_id_from=333.999.0.0)
+- [WeChat] [万事开头难？喵小DI玩“羊了个羊”可不难](https://mp.weixin.qq.com/s/4Z3WtkcWRp6x4x60RVELfQ)
+
+# 使用指南
+
+## 算法原理解析
+
+
+## 快速上手
+
+- 如果想**在线试玩** --> [在线网页（改进中）](https://opendilab.net/sheep)
+- 如果想**本地部署/测试**
+ - 服务端（Python）
+ ```shell
+ # 预先安装好 Python3
+ cd service
+ pip install -r requirement.txt
+ FLASK_APP=app.py flask run # 玩家试玩
+ # FLASK_APP=agent_app.py flask run # 玩家 + AI 试玩
+ ```
+ - 客户端（react）
+ ```shell
+ # 预先安装好 node.js 和 react
+ cd ui
+ npm run build
+ npm run preview
+ ```
+ 然后在网页中打开对应链接即可
+- 如果想进行完整的深度强化学习训练
+ ```shell
+ # 预先安装好 Python3
+ cd service
+ pip install -r requirement-train.txt
+ python3 -u sheep_ppo_main.py
+ ```
+- 如果想使用定义好的 gym 羊了个羊环境 --> 点个 star 之后直接暴力 CTRL C+V 拿走 `service/sheep_env.py` 尽情魔改
+- 如果想获得训练好的深度强化学习模型 --> 访问 [OpenDILab官网下载链接](https://opendilab.net/download/DI-sheep/) （目前提供了两种试玩模型，但智能体仍有很多进步空间）
+- 如果想了解更多深度强化学习相关知识 --> 欢迎参阅 [DI-engine](https://github.com/opendilab/DI-engine) 和[相关文档](https://di-engine-docs.readthedocs.io/zh_CN/latest/)
+- 如果想了解未来的更新计划 --> 请参阅[更新计划](#更新计划)
+- 如果有其他问题或想法 --> 欢迎 github ISSUE 区讨论，或是贡献 Pull requests
+
+## 项目结构
+```text
+.
+├── LICENSE
+├── ui --> react 网页前端
+└── service --> Python 核心模块（算法和服务端）
+ ├── app.py --> flask 服务 app (仅人类操作)
+ ├── agent_app.py --> flask 服务 app（人类+AI操作）
+ ├── requirement.txt --> Python 依赖库列表
+ ├── sheep_env.py --> gym 格式环境
+ ├── sheep_model.py --> 基于 PyTorch 的 Actor-Critic 神经网络模型
+ ├── sheep_ppo_main.py --> 基于 DI-engine 的深度强化学习训练主函数
+ ├── test_sheep_env.py --> gym 格式环境的单元测试
+ └── test_sheep_model.py --> 神经网络模型的单元测试
+```
+
+
+
+# 更新计划
+
+## 算法
+
+- [ ] 强化学习训练参数调整和算法微调
+- [ ] 提供可供本地试玩的模型权重
+- [ ] 详细的神经网络和强化学习算法设计文档
+- [ ] model-based RL 和 planning 算法
+- [ ] 神经网络压缩（用于部署）
+
+## 环境
+- [ ] 添加原类型游戏（比如3tiles）中的各种道具
+- [ ] 牌的层数问题如何定义
+- [ ] 结合 JAX 优化环境运行速度
+- [ ] 更多结合 AI 的玩法设计
+
+
+## 应用
+- [x] 更多自定义主题和 BGM
+- [x] 在线网页端部署
+- [x] 样例神经网络权重下载
+- [ ] 更多 AI 训练时的行为分析
+- [ ] 移动端应用（欢迎Android/IOS开发者支持）
+
+
+# 致谢
+- react 前端部分主要参考 https://github.com/StreakingMan/solvable-sheep-game ，请大家也多多支持这个 repo
+
+
+# License
+DI-sheep is released under the Apache 2.0 license.
diff --git a/DI-sheep/service/agent_app.py b/DI-sheep/service/agent_app.py
new file mode 100644
index 0000000000000000000000000000000000000000..397a4960e5b3bec55c0ac35fc5d1f80dc03acefa
--- /dev/null
+++ b/DI-sheep/service/agent_app.py
@@ -0,0 +1,161 @@
+import time
+import numpy as np
+import torch
+from flask import Flask, request, jsonify, make_response
+from flask_restplus import Api, Resource, fields
+from threading import Thread
+from sheep_env import SheepEnv
+from sheep_model import SheepModel
+
+flask_app = Flask(__name__)
+app = Api(
+ app=flask_app,
+ version="0.0.1",
+ title="DI-sheep App",
+ description="Play Sheep with Deep Reinforcement Learning, Powered by OpenDILab"
+)
+
+name_space = app.namespace('DI-sheep', description='DI-sheep APIs')
+model = app.model(
+ 'DI-sheep params', {
+ 'command': fields.String(required=False, description="Command Field", help="reset, step"),
+ 'argument': fields.Integer(required=False, description="Argument Field", help="reset->level, step->action"),
+ }
+)
+MAX_ENV_NUM = 50
+ENV_TIMEOUT_SECOND = 60
+envs = {}
+model = SheepModel(item_obs_size=80, item_num=30, global_obs_size=19)
+ckpt = torch.load('ckpt_best.pth.tar', map_location='cpu')['model']
+ckpt = {'item_encoder.encoder' + k.split('item_encoder')[-1] if 'item_encoder' in k else k: v for k, v in ckpt.items()} # compatibility for v1 and v2 model
+model.load_state_dict(ckpt)
+
+
+def random_action(obs, env):
+ action_mask = obs['action_mask']
+ action = np.random.choice(len(action_mask), p=action_mask / action_mask.sum())
+ return action
+
+
+def env_monitor():
+ while True:
+ cur_time = time.time()
+ pop_keys = []
+ for k, v in envs.items():
+ if cur_time - v['update_time'] >= ENV_TIMEOUT_SECOND:
+ pop_keys.append(k)
+ for k in pop_keys:
+ envs.pop(k)
+ time.sleep(1)
+
+
+app.env_thread = Thread(target=env_monitor, daemon=True)
+app.env_thread.start()
+
+
+@name_space.route("/")
+class MainClass(Resource):
+
+ def options(self):
+ response = make_response()
+ response.headers.add("Access-Control-Allow-Origin", "*")
+ response.headers.add('Access-Control-Allow-Headers', "*")
+ response.headers.add('Access-Control-Allow-Methods', "*")
+ return response
+
+ @app.expect(model)
+ def post(self):
+ try:
+ t_start = time.time()
+ data = request.json
+ cmd, arg, uid = data['command'], data['argument'], data['uid']
+ ip = request.remote_addr + uid
+
+ if ip not in envs:
+ if cmd == 'reset':
+ if len(envs) >= MAX_ENV_NUM:
+ response = jsonify(
+ {
+ "statusCode": 501,
+ "status": "No enough env resource, please wait a moment",
+ }
+ )
+ response.headers.add('Access-Control-Allow-Origin', '*')
+ return response
+ else:
+ env = SheepEnv(1, agent=True, max_padding=True)
+ env.seed(0)
+ envs[ip] = {'env': env, 'update_time': time.time()}
+ else:
+ response = jsonify(
+ {
+ "statusCode": 501,
+ "status": "No response for too long time, please reset the game",
+ }
+ )
+ response.headers.add('Access-Control-Allow-Origin', '*')
+ return response
+ else:
+ env = envs[ip]['env']
+ envs[ip]['update_time'] = time.time()
+
+ if cmd == 'reset':
+ obs = env.reset(arg)
+ action = model.compute_action(obs)
+ # action = random_action(obs, env)
+ scene = [item.to_json() for item in env.scene if item is not None]
+ response = jsonify(
+ {
+ "statusCode": 200,
+ "status": "Execution action",
+ "result": {
+ "scene": scene,
+ "max_item_num": env.total_item_num,
+ "action": action,
+ }
+ }
+ )
+ elif cmd == 'step':
+ obs, _, done, _ = env.step(arg)
+ action = model.compute_action(obs)
+ # action = random_action(obs, env)
+ scene = [item.to_json() for item in env.scene if item is not None]
+ bucket = [item.to_json() for item in env.bucket]
+ response = jsonify(
+ {
+ "statusCode": 200,
+ "status": "Execution action",
+ "result": {
+ "scene": scene,
+ "bucket": bucket,
+ "done": done,
+ "action": action,
+ }
+ }
+ )
+ else:
+ response = jsonify({
+ "statusCode": 500,
+ "status": "Invalid command: {}".format(cmd),
+ })
+ response.headers.add('Access-Control-Allow-Origin', '*')
+ return response
+ print('backend process time: {}'.format(time.time() - t_start))
+ print('current env number: {}'.format(len(envs)))
+ response.headers.add('Access-Control-Allow-Origin', '*')
+ return response
+ except Exception as e:
+ import traceback
+ print(repr(e))
+ print(traceback.format_exc())
+ response = jsonify({
+ "statusCode": 500,
+ "status": "Could not execute action",
+ })
+ response.headers.add('Access-Control-Allow-Origin', '*')
+ return response
+
+if __name__ == "__main__":
+ flask_app.run(host='0.0.0.0')
+
+
diff --git a/DI-sheep/service/app.py b/DI-sheep/service/app.py
new file mode 100644
index 0000000000000000000000000000000000000000..4ef18e6b99ccb80cb2b0d4b86ff8970367c7ff30
--- /dev/null
+++ b/DI-sheep/service/app.py
@@ -0,0 +1,142 @@
+import time
+from flask import Flask, request, jsonify, make_response
+from flask_restplus import Api, Resource, fields
+from threading import Thread
+from sheep_env import SheepEnv
+
+flask_app = Flask(__name__)
+app = Api(
+ app=flask_app,
+ version="0.0.1",
+ title="DI-sheep App",
+ description="Play Sheep with Deep Reinforcement Learning, Powered by OpenDILab"
+)
+
+name_space = app.namespace('DI-sheep', description='DI-sheep APIs')
+model = app.model(
+ 'DI-sheep params', {
+ 'command': fields.String(required=False, description="Command Field", help="reset, step"),
+ 'argument': fields.Integer(required=False, description="Argument Field", help="reset->level, step->action"),
+ }
+)
+MAX_ENV_NUM = 50
+ENV_TIMEOUT_SECOND = 60
+envs = {}
+
+
+def env_monitor():
+ while True:
+ cur_time = time.time()
+ pop_keys = []
+ for k, v in envs.items():
+ if cur_time - v['update_time'] >= ENV_TIMEOUT_SECOND:
+ pop_keys.append(k)
+ for k in pop_keys:
+ envs.pop(k)
+ time.sleep(1)
+
+
+app.env_thread = Thread(target=env_monitor, daemon=True)
+app.env_thread.start()
+
+
+@name_space.route("/")
+class MainClass(Resource):
+
+ def options(self):
+ response = make_response()
+ response.headers.add("Access-Control-Allow-Origin", "*")
+ response.headers.add('Access-Control-Allow-Headers', "*")
+ response.headers.add('Access-Control-Allow-Methods', "*")
+ return response
+
+ @app.expect(model)
+ def post(self):
+ try:
+ t_start = time.time()
+ data = request.json
+ cmd, arg, uid = data['command'], data['argument'], data['uid']
+ ip = request.remote_addr
+ ip = str(ip) + str(uid)
+
+ if ip not in envs:
+ if cmd == 'reset':
+ if len(envs) >= MAX_ENV_NUM:
+ response = jsonify(
+ {
+ "statusCode": 501,
+ "status": "No enough env resource, please wait a moment",
+ }
+ )
+ response.headers.add('Access-Control-Allow-Origin', '*')
+ return response
+ else:
+ env = SheepEnv(1, agent=False)
+ envs[ip] = {'env': env, 'update_time': time.time()}
+ else:
+ response = jsonify(
+ {
+ "statusCode": 501,
+ "status": "No response for too long time, please reset the game",
+ }
+ )
+ response.headers.add('Access-Control-Allow-Origin', '*')
+ return response
+ else:
+ env = envs[ip]['env']
+ envs[ip]['update_time'] = time.time()
+ if cmd == 'reset':
+ env.reset(arg)
+ scene = [item.to_json() for item in env.scene if item is not None]
+ response = jsonify(
+ {
+ "statusCode": 200,
+ "status": "Execution action",
+ "result": {
+ "scene": scene,
+ "max_item_num": env.total_item_num,
+ }
+ }
+ )
+ elif cmd == 'step':
+ _, _, done, _ = env.step(arg)
+ scene = [item.to_json() for item in env.scene if item is not None]
+ bucket = [item.to_json() for item in env.bucket]
+ response = jsonify(
+ {
+ "statusCode": 200,
+ "status": "Execution action",
+ "result": {
+ "scene": scene,
+ "bucket": bucket,
+ "done": done,
+ }
+ }
+ )
+ else:
+ response = jsonify({
+ "statusCode": 500,
+ "status": "Invalid command: {}".format(cmd),
+ })
+ response.headers.add('Access-Control-Allow-Origin', '*')
+ return response
+ print('backend process time: {}'.format(time.time() - t_start))
+ print('current env number: {}'.format(len(envs)))
+ response.headers.add('Access-Control-Allow-Origin', '*')
+ return response
+ except Exception as e:
+ import traceback
+ print(repr(e))
+ print(traceback.format_exc())
+ response = jsonify({
+ "statusCode": 500,
+ "status": "Could not execute action",
+ })
+ response.headers.add('Access-Control-Allow-Origin', '*')
+ return response
+
+if __name__ == "__main__":
+ flask_app.run(host='0.0.0.0')
+
+
+
diff --git a/DI-sheep/service/ckpt_best.pth.tar b/DI-sheep/service/ckpt_best.pth.tar
new file mode 100644
index 0000000000000000000000000000000000000000..09b6bb91d0a2a2920795e225ee6245bc0499320c
--- /dev/null
+++ b/DI-sheep/service/ckpt_best.pth.tar
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:6fda262054a2d69e44b9a2189c82be0203f412f432a37a7e9ec9b93dd0416e18
+size 3403809
diff --git a/DI-sheep/service/requirement-train.txt b/DI-sheep/service/requirement-train.txt
new file mode 100644
index 0000000000000000000000000000000000000000..ad09fe5a687c8acdb6edd9636e7a1398b32cf09d
--- /dev/null
+++ b/DI-sheep/service/requirement-train.txt
@@ -0,0 +1 @@
+DI-engine>=0.4.5
diff --git a/DI-sheep/service/requirement.txt b/DI-sheep/service/requirement.txt
new file mode 100644
index 0000000000000000000000000000000000000000..4642d2371ce593ec1aa7c650ee5be9ae815b4ff7
--- /dev/null
+++ b/DI-sheep/service/requirement.txt
@@ -0,0 +1,8 @@
+flask==1.1.2
+flask-restplus==0.13.0
+werkzeug==0.16.0
+jinja2==3.0.3
+markupsafe==2.0.1
+itsdangerous==2.0.1
+numpy
+gym
diff --git a/DI-sheep/service/sheep_env.py b/DI-sheep/service/sheep_env.py
new file mode 100644
index 0000000000000000000000000000000000000000..2654b41e5d467620da91d20ae9bb8f5cd30c72f3
--- /dev/null
+++ b/DI-sheep/service/sheep_env.py
@@ -0,0 +1,248 @@
+from typing import Tuple, Optional, Dict
+from collections import deque
+import copy
+import gym
+import json
+import uuid
+import numpy as np
+
+
+class Item:
+
+ def __init__(self, icon, offset, row, column):
+ self.icon = icon
+ self.offset = offset
+ self.row = row
+ self.column = column
+ self.uid = str(uuid.uuid4())
+ self.x = column * 100 + offset
+ self.y = row * 100 + offset
+ self.grid_x = self.x % 25
+ self.grid_y = self.y % 25
+ self.accessible = 1
+ self.visible = 1
+
+ def __repr__(self) -> str:
+ return 'icon({})'.format(self.icon)
+
+ def to_json(self):
+ return json.dumps(self, default=lambda o: o.__dict__ if hasattr(o, '__dict__') else int(o) if isinstance(o,np.int64) else "", sort_keys=True, indent=2)
+
+
+class SheepEnv(gym.Env):
+ max_level = 10
+ R = 10
+ icons = [i for i in range(10)]
+ ranges = [
+ [2, 6],
+ [1, 6],
+ [1, 7],
+ [0, 7],
+ [0, 8],
+ ]
+
+ def __init__(self, level: int, bucket_length: int = 7, agent: bool = True, max_padding: bool = False) -> None:
+ self.level = level
+ assert 1 <= self.level <= self.max_level
+ self.bucket_length = bucket_length
+ self.agent = agent
+ self.max_padding = max_padding
+ self._make_game()
+
+ def seed(self, seed: int) -> None:
+ self._seed = seed
+ np.random.seed(self._seed)
+
+ def _make_game(self) -> None:
+ # TODO wash scene
+ self.icon_pool = self.icons[:2 * self.level]
+ self.offset_pool = [0, 25, 50, 75][:1 + self.level]
+ self.selected_range = self.ranges[min(4, self.level - 1)]
+ self.max_item_per_icon = 9
+ self.max_level_item_num = len(self.icons) * self.max_item_per_icon + 2
+ if self.level >= 10:
+ self.item_per_icon = 6 + (self.level - 5 + 1) // 2
+ # add non-divisible items
+ self.item_non_div = 2
+ else:
+ self.item_per_icon = 6
+ self.item_non_div = 0
+ self.total_item_num = len(self.icon_pool) * self.item_per_icon + self.item_non_div
+
+ self.scene = []
+ self.bucket = deque(maxlen=self.bucket_length)
+
+ N = self.selected_range[1] - self.selected_range[0] - 1
+ for i in range(len(self.icon_pool)):
+ for j in range(self.item_per_icon):
+ row = self.selected_range[0] + np.int64(N * np.random.random())
+ column = self.selected_range[0] + np.int64(N * np.random.random())
+ offset = self.offset_pool[np.int64(np.random.random() * len(self.offset_pool))]
+ item = Item(self.icon_pool[i], offset, row, column)
+ self.scene.append(item)
+ if self.item_non_div > 0:
+ for icon in np.random.choice(self.icon_pool, size=self.item_non_div, replace=False):
+ row = self.selected_range[0] + np.int64(N * np.random.random())
+ column = self.selected_range[0] + np.int64(N * np.random.random())
+ offset = self.offset_pool[np.int64(np.random.random() * len(self.offset_pool))]
+ item = Item(int(icon), offset, row, column)
+ self.scene.append(item)
+
+ self.cur_item_num = len(self.scene)
+ self.reward_3tiles = self.R * 0.5 / (len(self.scene) // 3)
+
+ self._update_visible_accessible()
+ self._set_space()
+
+ def _update_visible_accessible(self) -> None:
+ for i in range(self.total_item_num):
+ covered_items = []
+ item1 = self.scene[i]
+ if item1 is None:
+ continue
+ item1.accessible = 1
+ for j in range(i + 1, self.total_item_num):
+ item2 = self.scene[j]
+ if item2 is None:
+ continue
+ if not (item2.x + 100 <= item1.x or item2.x >= item1.x + 100 or item2.y + 100 <= item1.y
+ or item2.y >= item1.y + 100):
+ item1.accessible = 0
+ if not self.agent:
+ break
+ covered_items.append(item2)
+ if self.agent and len(covered_items) > 0:
+ flag = np.zeros((2, 2)).astype(np.int64) # core offset 50x50 is visible
+ core_x, core_y = item1.x + 25, item1.y + 25
+ for item in covered_items:
+ min_x = max(core_x, item.x)
+ max_x = min(core_x + 50, item.x + 100)
+ min_y = max(core_y, item.y)
+ max_y = min(core_y + 50, item.y + 100)
+ if min_x < max_x or min_y < max_y:
+ # top left: (max_x, max_y)
+ # bottom right: (min_x, min_y)
+ flag[(min_x - core_x) // 25:(max_x - core_x) // 25,
+ (min_y - core_y) // 25:(max_y - core_y) // 25] = 1
+ if flag.sum() == 4:
+ break
+ item1.visible = int(flag.sum() < 4)
+ else:
+ item1.visible = 1
+
+ def _execute_action(self, action: int) -> float:
+ action_item = copy.deepcopy(self.scene[action])
+ assert action_item is not None, action
+ self.scene[action] = None
+ self.cur_item_num -= 1
+ same_items = []
+ for i in range(len(self.bucket)):
+ item = self.bucket[i]
+ if item.icon == action_item.icon:
+ same_items.append(item)
+
+ if len(same_items) == 2:
+ for item in same_items:
+ self.bucket.remove(item)
+ return copy.deepcopy(self.reward_3tiles) # necessary deepcopy
+ else:
+ self.bucket.append(action_item)
+ return 0.
+
+ def reset(self, level: Optional[int] = None) -> Dict:
+ if level is not None:
+ self.level = level
+ assert 1 <= self.level <= self.max_level
+ self._make_game()
+ self._set_space()
+ return self._get_obs()
+
+ def close(self) -> None:
+ pass
+
+ # usually overwritten methods
+
+ def step(self, action: int) -> Tuple:
+ rew = self._execute_action(action)
+ self._update_visible_accessible()
+
+ obs = self._get_obs()
+ if self.cur_item_num == 0:
+ rew += self.R
+ done = True
+ elif len(self.bucket) == self.bucket_length:
+ rew -= self.R
+ done = True
+ else:
+ done = False
+ info = {}
+ return obs, rew, done, info
+
+ def _get_obs(self) -> Dict:
+ item_obs = np.zeros((self.total_item_num, self.item_size))
+ action_mask = np.zeros(self.total_item_num).astype(np.uint8)
+
+ L, N = self.L, self.N
+ p1, p2, p3 = L + N, L + N + N, L + N + N + 2
+ for i in range(len(self.scene)):
+ item = self.scene[i]
+ if item is None:
+ item_obs[i][L - 1] = 1
+ else:
+ item_obs[i][L + item.grid_x] = 1
+ item_obs[i][p1 + item.grid_y] = 1
+ item_obs[i][p3 + item.visible] = 1
+ if item.visible:
+ item_obs[i][item.icon] = 1
+ item_obs[i][p2 + item.accessible] = 1
+ else:
+ item_obs[i][L - 2] = 1
+ if item.accessible:
+ action_mask[i] = 1
+
+ bucket_obs = np.zeros(3 * len(self.icons))
+ bucket_icon_stat = [0 for _ in range(len(self.icons))]
+ for item in self.bucket:
+ bucket_icon_stat[item.icon] += 1
+ for i in range(len(bucket_icon_stat)):
+ bucket_obs[i * 3 + bucket_icon_stat[i]] = 1
+
+ global_obs = np.zeros(self.global_size)
+ if self.max_padding:
+ global_obs[self.cur_item_num // self.max_item_per_icon] = 1
+ else:
+ global_obs[self.cur_item_num // self.item_per_icon] = 1
+ global_obs[self.global_size - self.bucket_length - 1 + len(self.bucket)] = 1
+
+ return {
+ 'item_obs': item_obs,
+ 'bucket_obs': bucket_obs,
+ 'global_obs': global_obs,
+ 'action_mask': action_mask,
+ }
+
+ def _set_space(self) -> None:
+ if self.max_padding:
+ N = self.ranges[-1][1] - self.ranges[-1][0]
+ # icon + x + y + accessible + visible
+ L = len(self.icons) + 2 # +2 for not visible and move out
+ else:
+ N = self.selected_range[1] - self.selected_range[0]
+ # icon + x + y + accessible + visible
+ L = len(self.icon_pool) + 2 # +2 for not visible and move out
+ self.L, self.N = L, N
+ self.item_size = L + 4 * N * 2 + 2 + 2
+ if self.max_padding:
+ self.global_size = self.max_level_item_num // self.max_item_per_icon + 1 + self.bucket_length + 1
+ else:
+ self.global_size = self.total_item_num // self.item_per_icon + 1 + self.bucket_length + 1
+ self.observation_space = gym.spaces.Dict(
+ {
+ 'item_obs': gym.spaces.Box(0, 1, dtype=np.float32, shape=(self.total_item_num, self.item_size)),
+ 'bucket_obs': gym.spaces.Box(0, 1, dtype=np.float32, shape=(3 * len(self.icons), )),
+ 'global_obs': gym.spaces.Box(0, 1, dtype=np.float32, shape=(self.global_size, )),
+ 'action_mask': gym.spaces.Box(0, 1, dtype=np.float32, shape=(self.total_item_num, )) # TODO
+ }
+ )
+ self.action_space = gym.spaces.Discrete(self.total_item_num)
+ self.reward_space = gym.spaces.Box(-self.R * 1.5, self.R * 1.5, dtype=np.float32)
diff --git a/DI-sheep/service/sheep_model.py b/DI-sheep/service/sheep_model.py
new file mode 100644
index 0000000000000000000000000000000000000000..bbf29ba438d74245eb602bdfe2e43218af63397d
--- /dev/null
+++ b/DI-sheep/service/sheep_model.py
@@ -0,0 +1,126 @@
+import torch
+import torch.nn as nn
+import treetensor.torch as ttorch
+from ding.torch_utils import Transformer, MLP, unsqueeze, to_tensor
+
+
+class ItemEncoder(nn.Module):
+ encoder_type = ['TF', 'MLP', 'two_stage_MLP']
+
+ def __init__(self, item_obs_size=60, item_num=30, item_encoder_type='TF', hidden_size=64, activation=nn.ReLU()):
+ super(ItemEncoder, self).__init__()
+ assert item_encoder_type in self.encoder_type, "not support item encoder type: {}/{}".format(item_encoder_type, self.encoder_type)
+ self.item_encoder_type = item_encoder_type
+ self.item_num = item_num
+ self.hidden_size = hidden_size
+
+ if self.item_encoder_type == 'TF':
+ self.encoder = Transformer(
+ item_obs_size,
+ hidden_dim=2 * hidden_size,
+ output_dim=hidden_size,
+ activation=activation
+ )
+ elif self.item_encoder_type == 'MLP':
+ self.encoder = MLP(
+ item_obs_size,
+ hidden_size,
+ hidden_size,
+ layer_num=3,
+ activation=activation
+ )
+ elif self.item_encoder_type == 'two_stage_MLP':
+ self.trans_len = 16
+ self.encoder_1 = MLP(
+ item_obs_size,
+ hidden_size,
+ self.trans_len,
+ layer_num=3,
+ activation=activation
+ )
+ self.encoder_2 = MLP(
+ self.trans_len*self.item_num,
+ hidden_size,
+ self.item_num*hidden_size,
+ layer_num=2,
+ activation=activation
+ )
+
+ def forward(self, item_obs):
+ if self.item_encoder_type == 'two_stage_MLP':
+ item_embedding_1 = self.encoder_1(item_obs) # (B, M, L)
+ item_embedding_2 = torch.reshape(item_embedding_1, [-1, self.trans_len*self.item_num])
+ item_embedding = self.encoder_2(item_embedding_2)
+ item_embedding = torch.reshape(item_embedding, [-1, self.item_num, self.hidden_size])
+ else:
+ item_embedding = self.encoder(item_obs)
+ return item_embedding
+
+
+class SheepModel(nn.Module):
+ mode = ['compute_actor', 'compute_critic', 'compute_actor_critic']
+
+ def __init__(self, item_obs_size=60, item_num=30, item_encoder_type='TF', bucket_obs_size=30, global_obs_size=17, hidden_size=64, activation=nn.ReLU(), ttorch_return=False):
+ super(SheepModel, self).__init__()
+ self.item_encoder = ItemEncoder(item_obs_size, item_num, item_encoder_type, hidden_size, activation=activation)
+ self.bucket_encoder = MLP(bucket_obs_size, hidden_size, hidden_size, layer_num=3, activation=activation)
+ self.global_encoder = MLP(global_obs_size, hidden_size, hidden_size, layer_num=2, activation=activation)
+ self.value_head = nn.Sequential(
+ MLP(hidden_size, hidden_size, hidden_size, layer_num=2, activation=activation), nn.Linear(hidden_size, 1)
+ )
+ self.ttorch_return = ttorch_return
+
+ def compute_actor(self, x):
+ item_embedding = self.item_encoder(x['item_obs'])
+ bucket_embedding = self.bucket_encoder(x['bucket_obs'])
+ global_embedding = self.global_encoder(x['global_obs'])
+
+ key = item_embedding
+ query = bucket_embedding + global_embedding
+ query = query.unsqueeze(1)
+ logit = (key * query).sum(2)
+ logit.masked_fill_(~x['action_mask'].bool(), value=-1e9)
+ if self.ttorch_return:
+ return logit
+ else:
+ return {'logit': logit}
+
+ def compute_critic(self, x):
+ item_embedding = self.item_encoder(x['item_obs'])
+ bucket_embedding = self.bucket_encoder(x['bucket_obs'])
+ global_embedding = self.global_encoder(x['global_obs'])
+
+ embedding = item_embedding.mean(1) + bucket_embedding + global_embedding
+ value = self.value_head(embedding)
+ if self.ttorch_return:
+ return value.squeeze(1)
+ else:
+ return {'value': value.squeeze(1)}
+
+ def compute_actor_critic(self, x):
+ item_embedding = self.item_encoder(x['item_obs'])
+ bucket_embedding = self.bucket_encoder(x['bucket_obs'])
+ global_embedding = self.global_encoder(x['global_obs'])
+
+ key = item_embedding
+ query = bucket_embedding + global_embedding
+ query = query.unsqueeze(1)
+ logit = (key * query).sum(2)
+ logit.masked_fill_(~x['action_mask'].bool(), value=-1e9)
+
+ embedding = item_embedding.mean(1) + bucket_embedding + global_embedding
+ value = self.value_head(embedding)
+ if self.ttorch_return:
+ return ttorch.as_tensor({'logit': logit, 'value': value.squeeze(1)})
+ else:
+ return {'logit': logit, 'value': value.squeeze(1)}
+
+ def forward(self, x, mode):
+ assert mode in self.mode, "not support forward mode: {}/{}".format(mode, self.mode)
+ return getattr(self, mode)(x)
+
+ def compute_action(self, x):
+ x = unsqueeze(to_tensor(x))
+ with torch.no_grad():
+ logit = self.compute_actor(x)['logit']
+ return logit.argmax(dim=-1)[0].item()
diff --git a/DI-sheep/service/sheep_ppo_level9_main.py b/DI-sheep/service/sheep_ppo_level9_main.py
new file mode 100644
index 0000000000000000000000000000000000000000..71b16d2ff8acf2f99cdf2269bc144a0ff7e27551
--- /dev/null
+++ b/DI-sheep/service/sheep_ppo_level9_main.py
@@ -0,0 +1,123 @@
+import os
+from easydict import EasyDict
+from tensorboardX import SummaryWriter
+from ding.config import compile_config
+from ding.envs import create_env_manager, DingEnvWrapper, EvalEpisodeReturnEnv
+from ding.policy import PPOPolicy
+from ding.worker import BaseLearner, create_serial_collector, InteractionSerialEvaluator
+from ding.utils import set_pkg_seed
+
+from sheep_env import SheepEnv
+from sheep_model import SheepModel
+
+sheep_ppo_config = dict(
+ exp_name='level9/sheep_ppo_MLP_1M_seed0',
+ env=dict(
+ env_id='Sheep-v0',
+ level=10,
+ collector_env_num=8,
+ evaluator_env_num=10,
+ n_evaluator_episode=10,
+ # stop_value=15,
+ stop_value=1e6, # to run fixed env step
+ ),
+ policy=dict(
+ cuda=True,
+ recompute_adv=True,
+ action_space='discrete',
+ model=dict(),
+ learn=dict(
+ epoch_per_collect=10,
+ batch_size=320,
+ learning_rate=3e-4,
+ value_weight=0.5,
+ entropy_weight=0.001,
+ clip_ratio=0.2,
+ adv_norm=False,
+ value_norm=True,
+ ),
+ collect=dict(
+ n_sample=3200,
+ discount_factor=0.99,
+ gae_lambda=0.95,
+ ),
+ eval=dict(evaluator=dict(eval_freq=500, )),
+ ),
+)
+sheep_ppo_config = EasyDict(sheep_ppo_config)
+main_config = sheep_ppo_config
+
+sheep_ppo_create_config = dict(
+ env=dict(
+ type='mujoco',
+ import_names=['dizoo.mujoco.envs.mujoco_env'],
+ ),
+ env_manager=dict(type='subprocess'),
+ policy=dict(type='ppo', ),
+)
+sheep_ppo_create_config = EasyDict(sheep_ppo_create_config)
+create_config = sheep_ppo_create_config
+
+
+def sheep_env_fn(level):
+ return DingEnvWrapper(
+ SheepEnv(level), cfg={'env_wrapper': [
+ lambda env: EvalEpisodeReturnEnv(env),
+ ]}
+ )
+
+
+def main(input_cfg, seed, max_env_step=int(1e6), max_train_iter=int(1e6)):
+ cfg, create_cfg = input_cfg
+ cfg = compile_config(cfg, seed=seed, auto=True, create_cfg=create_cfg)
+ collector_env = create_env_manager(
+ cfg.env.manager, [lambda: sheep_env_fn(cfg.env.level) for _ in range(cfg.env.collector_env_num)]
+ )
+ evaluator_env = create_env_manager(
+ cfg.env.manager, [lambda: sheep_env_fn(cfg.env.level) for _ in range(cfg.env.evaluator_env_num)]
+ )
+ collector_env.seed(cfg.seed, dynamic_seed=False)
+ evaluator_env.seed(cfg.seed, dynamic_seed=False)
+ set_pkg_seed(cfg.seed, use_cuda=cfg.policy.cuda)
+
+ obs_space = collector_env._env_ref.observation_space
+ model = SheepModel(
+ obs_space['item_obs'].shape[1],
+ obs_space['item_obs'].shape[0],
+ 'TF',
+ obs_space['bucket_obs'].shape[0],
+ obs_space['global_obs'].shape[0]
+ )
+ policy = PPOPolicy(cfg.policy, model=model, enable_field=['learn', 'collect', 'eval'])
+
+ tb_logger = SummaryWriter(os.path.join('./{}/log/'.format(cfg.exp_name), 'serial'))
+ learner = BaseLearner(cfg.policy.learn.learner, policy.learn_mode, tb_logger, exp_name=cfg.exp_name)
+ collector = create_serial_collector(
+ cfg.policy.collect.collector,
+ env=collector_env,
+ policy=policy.collect_mode,
+ tb_logger=tb_logger,
+ exp_name=cfg.exp_name
+ )
+ evaluator = InteractionSerialEvaluator(
+ cfg.policy.eval.evaluator, evaluator_env, policy.eval_mode, tb_logger, exp_name=cfg.exp_name
+ )
+
+ learner.call_hook('before_run')
+
+ while True:
+ if evaluator.should_eval(learner.train_iter):
+ stop, reward = evaluator.eval(learner.save_checkpoint, learner.train_iter, collector.envstep)
+ if stop:
+ break
+ new_data = collector.collect(train_iter=learner.train_iter)
+
+ learner.train(new_data, collector.envstep)
+ if collector.envstep >= max_env_step or learner.train_iter >= max_train_iter:
+ break
+
+ learner.call_hook('after_run')
+
+
+if __name__ == "__main__":
+ main([main_config, create_config], seed=0)
diff --git a/DI-sheep/service/sheep_ppo_main.py b/DI-sheep/service/sheep_ppo_main.py
new file mode 100644
index 0000000000000000000000000000000000000000..9704beb1c8fbea5fa9b2264016e1eb633f0150e0
--- /dev/null
+++ b/DI-sheep/service/sheep_ppo_main.py
@@ -0,0 +1,122 @@
+import os
+from easydict import EasyDict
+from tensorboardX import SummaryWriter
+from ding.config import compile_config
+from ding.envs import create_env_manager, DingEnvWrapper, EvalEpisodeReturnEnv
+from ding.policy import PPOPolicy
+from ding.worker import BaseLearner, create_serial_collector, InteractionSerialEvaluator
+from ding.utils import set_pkg_seed
+
+from sheep_env import SheepEnv
+from sheep_model import SheepModel
+
+sheep_ppo_config = dict(
+ exp_name='sheep_ppo_seed0',
+ env=dict(
+ env_id='Sheep-v0',
+ level=2,
+ collector_env_num=8,
+ evaluator_env_num=10,
+ n_evaluator_episode=10,
+ stop_value=15,
+ ),
+ policy=dict(
+ cuda=True,
+ recompute_adv=True,
+ action_space='discrete',
+ model=dict(),
+ learn=dict(
+ epoch_per_collect=10,
+ batch_size=320,
+ learning_rate=3e-4,
+ value_weight=0.5,
+ entropy_weight=0.001,
+ clip_ratio=0.2,
+ adv_norm=False,
+ value_norm=True,
+ ),
+ collect=dict(
+ n_sample=3200,
+ discount_factor=0.99,
+ gae_lambda=0.95,
+ ),
+ eval=dict(evaluator=dict(eval_freq=500, )),
+ ),
+)
+sheep_ppo_config = EasyDict(sheep_ppo_config)
+main_config = sheep_ppo_config
+
+sheep_ppo_create_config = dict(
+ env=dict(
+ type='mujoco',
+ import_names=['dizoo.mujoco.envs.mujoco_env'],
+ ),
+ env_manager=dict(type='subprocess'),
+ policy=dict(type='ppo', ),
+)
+sheep_ppo_create_config = EasyDict(sheep_ppo_create_config)
+create_config = sheep_ppo_create_config
+
+
+def sheep_env_fn(level):
+ return DingEnvWrapper(
+ SheepEnv(level), cfg={'env_wrapper': [
+ lambda env: EvalEpisodeReturnEnv(env),
+ ]}
+ )
+
+
+def main(input_cfg, seed, max_env_step=int(1e7), max_train_iter=int(1e7)):
+ cfg, create_cfg = input_cfg
+ cfg = compile_config(cfg, seed=seed, auto=True, create_cfg=create_cfg)
+ collector_env = create_env_manager(
+ cfg.env.manager, [lambda: sheep_env_fn(cfg.env.level) for _ in range(cfg.env.collector_env_num)]
+ )
+ evaluator_env = create_env_manager(
+ cfg.env.manager, [lambda: sheep_env_fn(cfg.env.level) for _ in range(cfg.env.evaluator_env_num)]
+ )
+ collector_env.seed(cfg.seed, dynamic_seed=False)
+ evaluator_env.seed(cfg.seed, dynamic_seed=False)
+ set_pkg_seed(cfg.seed, use_cuda=cfg.policy.cuda)
+
+ obs_space = collector_env._env_ref.observation_space
+ model = SheepModel(
+ obs_space['item_obs'].shape[1],
+ obs_space['item_obs'].shape[0],
+ 'TF',
+ obs_space['bucket_obs'].shape[0],
+ obs_space['global_obs'].shape[0]
+ )
+ policy = PPOPolicy(cfg.policy, model=model, enable_field=['learn', 'collect', 'eval'])
+
+ tb_logger = SummaryWriter(os.path.join('./{}/log/'.format(cfg.exp_name), 'serial'))
+ learner = BaseLearner(cfg.policy.learn.learner, policy.learn_mode, tb_logger, exp_name=cfg.exp_name)
+ collector = create_serial_collector(
+ cfg.policy.collect.collector,
+ env=collector_env,
+ policy=policy.collect_mode,
+ tb_logger=tb_logger,
+ exp_name=cfg.exp_name
+ )
+ evaluator = InteractionSerialEvaluator(
+ cfg.policy.eval.evaluator, evaluator_env, policy.eval_mode, tb_logger, exp_name=cfg.exp_name
+ )
+
+ learner.call_hook('before_run')
+
+ while True:
+ if evaluator.should_eval(learner.train_iter):
+ stop, reward = evaluator.eval(learner.save_checkpoint, learner.train_iter, collector.envstep)
+ if stop:
+ break
+ new_data = collector.collect(train_iter=learner.train_iter)
+
+ learner.train(new_data, collector.envstep)
+ if collector.envstep >= max_env_step or learner.train_iter >= max_train_iter:
+ break
+
+ learner.call_hook('after_run')
+
+
+if __name__ == "__main__":
+ main([main_config, create_config], seed=0)
\ No newline at end of file
diff --git a/DI-sheep/service/test_sheep_env.py b/DI-sheep/service/test_sheep_env.py
new file mode 100644
index 0000000000000000000000000000000000000000..66c66d16e28f82957abbeacb40b1bcef394c0798
--- /dev/null
+++ b/DI-sheep/service/test_sheep_env.py
@@ -0,0 +1,23 @@
+import pytest
+import numpy as np
+from sheep_env import SheepEnv
+
+
+@pytest.mark.unittest
+def test_naive():
+ env = SheepEnv(level=9)
+ obs = env.reset()
+ print(env.observation_space)
+
+ while True:
+ action_mask = obs['action_mask']
+ action = np.random.choice(len(action_mask), p=action_mask / action_mask.sum())
+ obs, rew, done, info = env.step(action)
+ print(env.bucket, rew, done)
+ assert isinstance(obs, dict)
+ assert set(obs.keys()) == set(['item_obs', 'bucket_obs', 'global_obs', 'action_mask'])
+ assert np.isscalar(rew)
+ assert isinstance(done, bool)
+ assert isinstance(info, dict)
+ if done:
+ break
diff --git a/DI-sheep/service/test_sheep_model.py b/DI-sheep/service/test_sheep_model.py
new file mode 100644
index 0000000000000000000000000000000000000000..40eaf4bf8d632312383aea064b37f8b15b5b5285
--- /dev/null
+++ b/DI-sheep/service/test_sheep_model.py
@@ -0,0 +1,19 @@
+import pytest
+import torch
+from sheep_model import SheepModel
+
+
+@pytest.mark.unittest
+def test_naive():
+ B, M = 3, 30
+ model = SheepModel(item_num=30, item_encoder_type='two_stage_MLP')
+ data = {
+ 'item_obs': torch.randn(B, M, 60),
+ 'bucket_obs': torch.randn(B, 30),
+ 'global_obs': torch.randn(B, 17),
+ 'action_mask': torch.randint(0, 2, size=(M, )).bool()
+ }
+
+ output = model.forward(data, mode='compute_actor_critic')
+ assert output['logit'].shape == (B, M)
+ assert output['value'].shape == (B, )
diff --git a/DI-sheep/ui/.commitlintrc.cjs b/DI-sheep/ui/.commitlintrc.cjs
new file mode 100644
index 0000000000000000000000000000000000000000..eb86589cb4bddb2001e802b779a8509f5d6f60b9
--- /dev/null
+++ b/DI-sheep/ui/.commitlintrc.cjs
@@ -0,0 +1,9 @@
+/**
+ * commitlint config
+ * @ref http://commitlint.js.org/
+ * @desc generated at 9/15/2022, 12:52:11 PM by streakingman-cli@1.9.2
+ */
+
+module.exports = {
+ extends: ['@commitlint/config-conventional'],
+};
diff --git a/DI-sheep/ui/.editorconfig b/DI-sheep/ui/.editorconfig
new file mode 100644
index 0000000000000000000000000000000000000000..7a57064d0bd82da8a3636818f88ad596b87e371b
--- /dev/null
+++ b/DI-sheep/ui/.editorconfig
@@ -0,0 +1,15 @@
+# https://editorconfig.org/
+# generated at 9/15/2022, 12:52:15 PM by streakingman-cli@1.9.2
+# 该配置文件是给webstorm使用的
+root = true
+
+[*]
+indent_style = space
+indent_size = 4
+end_of_line = lf
+charset = utf-8
+trim_trailing_whitespace = true
+insert_final_newline = true
+
+[*.md]
+trim_trailing_whitespace = false
diff --git a/DI-sheep/ui/.eslintignore b/DI-sheep/ui/.eslintignore
new file mode 100644
index 0000000000000000000000000000000000000000..a8d80d3b7a772dd05dcac0584994bc99ca06d852
--- /dev/null
+++ b/DI-sheep/ui/.eslintignore
@@ -0,0 +1,9 @@
+# generated at 9/15/2022, 12:51:49 PM by streakingman-cli@1.9.2
+
+node_modules
+dist
+
+!.eslintrc.js
+!.prettierrc.js
+!.commitlintrc.js
+!.lintstagedrc.js
diff --git a/DI-sheep/ui/.eslintrc.cjs b/DI-sheep/ui/.eslintrc.cjs
new file mode 100644
index 0000000000000000000000000000000000000000..c25475d0d349d34cb1b370e6738256b5758ee876
--- /dev/null
+++ b/DI-sheep/ui/.eslintrc.cjs
@@ -0,0 +1,28 @@
+/**
+ * eslint config
+ * @ref http://eslint.cn/
+ * @desc generated at 9/15/2022, 12:51:49 PM by streakingman-cli@1.9.2
+ */
+
+module.exports = {
+ root: true,
+ parser: '@typescript-eslint/parser',
+ parserOptions: {
+ sourceType: 'module',
+ ecmaVersion: 11,
+ },
+ env: {
+ es6: true,
+ node: true,
+ },
+ plugins: ['eslint-plugin-prettier', '@typescript-eslint'],
+ extends: [
+ 'eslint:recommended',
+ 'plugin:react/recommended',
+ 'plugin:@typescript-eslint/recommended',
+ 'plugin:prettier/recommended',
+ ],
+ rules: {
+ 'prettier/prettier': 'error',
+ },
+};
diff --git a/DI-sheep/ui/.gitignore b/DI-sheep/ui/.gitignore
new file mode 100644
index 0000000000000000000000000000000000000000..cf7ff2f72ee15f3de472fcf0e28bf41840cfc779
--- /dev/null
+++ b/DI-sheep/ui/.gitignore
@@ -0,0 +1,24 @@
+# Logs
+logs
+*.log
+npm-debug.log*
+yarn-debug.log*
+yarn-error.log*
+pnpm-debug.log*
+lerna-debug.log*
+
+node_modules
+# dist
+dist-ssr
+*.local
+
+# Editor directories and files
+.vscode/*
+!.vscode/extensions.json
+.idea
+.DS_Store
+*.suo
+*.ntvs*
+*.njsproj
+*.sln
+*.sw?
diff --git a/DI-sheep/ui/.husky/commit-msg b/DI-sheep/ui/.husky/commit-msg
new file mode 100755
index 0000000000000000000000000000000000000000..7241764b9e0b44b13fdfcc6bf87671d29fb56cf0
--- /dev/null
+++ b/DI-sheep/ui/.husky/commit-msg
@@ -0,0 +1,4 @@
+#!/usr/bin/env sh
+. "$(dirname -- "$0")/_/husky.sh"
+
+npx --no-install commitlint --edit
diff --git a/DI-sheep/ui/.husky/pre-commit b/DI-sheep/ui/.husky/pre-commit
new file mode 100755
index 0000000000000000000000000000000000000000..d24fdfc601b9ffe8ccc3fca5d3b873109dc56c4a
--- /dev/null
+++ b/DI-sheep/ui/.husky/pre-commit
@@ -0,0 +1,4 @@
+#!/usr/bin/env sh
+. "$(dirname -- "$0")/_/husky.sh"
+
+npx lint-staged
diff --git a/DI-sheep/ui/.lintstagedrc.cjs b/DI-sheep/ui/.lintstagedrc.cjs
new file mode 100644
index 0000000000000000000000000000000000000000..86547443f0777cd44de7569146046ee4c0429175
--- /dev/null
+++ b/DI-sheep/ui/.lintstagedrc.cjs
@@ -0,0 +1,11 @@
+/**
+ * lint-staged config
+ * @ref https://www.npmjs.com/package/lint-staged
+ * @desc generated at 9/15/2022, 12:52:11 PM by streakingman-cli@1.9.2
+ */
+
+module.exports = {
+ '!(dist/**/*)*.{[tj]s,[tj]sx,[cm]js}': ['eslint --fix'],
+ '!(dist/**/*)*.json': ['prettier --write'],
+ '!(dist/**/*)*.{css,scss}': ['stylelint --fix'],
+};
diff --git a/DI-sheep/ui/.prettierrc.cjs b/DI-sheep/ui/.prettierrc.cjs
new file mode 100644
index 0000000000000000000000000000000000000000..f7d06a97f96c65cf94d192c0e66100bebe27814c
--- /dev/null
+++ b/DI-sheep/ui/.prettierrc.cjs
@@ -0,0 +1,12 @@
+/**
+ * prettier config
+ * @ref https://prettier.io/
+ * @desc generated at 9/15/2022, 12:51:48 PM by streakingman-cli@1.9.2
+ */
+
+module.exports = {
+ tabWidth: 4,
+ singleQuote: true,
+ htmlWhitespaceSensitivity: 'css',
+ endOfLine: 'lf'
+}
diff --git a/DI-sheep/ui/.stylelintrc.cjs b/DI-sheep/ui/.stylelintrc.cjs
new file mode 100644
index 0000000000000000000000000000000000000000..16bbc13557d938c9947a0d17bcb6f52ca0a2ccbe
--- /dev/null
+++ b/DI-sheep/ui/.stylelintrc.cjs
@@ -0,0 +1,12 @@
+/**
+ * stylelint config
+ * @ref https://stylelint.io/
+ * @desc generated at 9/15/2022, 12:51:58 PM by streakingman-cli@1.9.2
+ */
+
+module.exports = {
+ extends: [
+ 'stylelint-config-standard-scss',
+ 'stylelint-config-prettier-scss',
+ ],
+};
diff --git a/DI-sheep/ui/.versionrc.cjs b/DI-sheep/ui/.versionrc.cjs
new file mode 100644
index 0000000000000000000000000000000000000000..7027a521261d0044892a2c3c4b0ee0e2fcaab53d
--- /dev/null
+++ b/DI-sheep/ui/.versionrc.cjs
@@ -0,0 +1,5 @@
+module.exports = {
+ scripts: {
+ postbump: 'yarn build && git add dist/*',
+ },
+};
diff --git a/DI-sheep/ui/LICENSE.md b/DI-sheep/ui/LICENSE.md
new file mode 100644
index 0000000000000000000000000000000000000000..f288702d2fa16d3cdf0035b15a9fcbc552cd88e7
--- /dev/null
+++ b/DI-sheep/ui/LICENSE.md
@@ -0,0 +1,674 @@
+ GNU GENERAL PUBLIC LICENSE
+ Version 3, 29 June 2007
+
+ Copyright (C) 2007 Free Software Foundation, Inc.
+ Everyone is permitted to copy and distribute verbatim copies
+ of this license document, but changing it is not allowed.
+
+ Preamble
+
+ The GNU General Public License is a free, copyleft license for
+software and other kinds of works.
+
+ The licenses for most software and other practical works are designed
+to take away your freedom to share and change the works. By contrast,
+the GNU General Public License is intended to guarantee your freedom to
+share and change all versions of a program--to make sure it remains free
+software for all its users. We, the Free Software Foundation, use the
+GNU General Public License for most of our software; it applies also to
+any other work released this way by its authors. You can apply it to
+your programs, too.
+
+ When we speak of free software, we are referring to freedom, not
+price. Our General Public Licenses are designed to make sure that you
+have the freedom to distribute copies of free software (and charge for
+them if you wish), that you receive source code or can get it if you
+want it, that you can change the software or use pieces of it in new
+free programs, and that you know you can do these things.
+
+ To protect your rights, we need to prevent others from denying you
+these rights or asking you to surrender the rights. Therefore, you have
+certain responsibilities if you distribute copies of the software, or if
+you modify it: responsibilities to respect the freedom of others.
+
+ For example, if you distribute copies of such a program, whether
+gratis or for a fee, you must pass on to the recipients the same
+freedoms that you received. You must make sure that they, too, receive
+or can get the source code. And you must show them these terms so they
+know their rights.
+
+ Developers that use the GNU GPL protect your rights with two steps:
+(1) assert copyright on the software, and (2) offer you this License
+giving you legal permission to copy, distribute and/or modify it.
+
+ For the developers' and authors' protection, the GPL clearly explains
+that there is no warranty for this free software. For both users' and
+authors' sake, the GPL requires that modified versions be marked as
+changed, so that their problems will not be attributed erroneously to
+authors of previous versions.
+
+ Some devices are designed to deny users access to install or run
+modified versions of the software inside them, although the manufacturer
+can do so. This is fundamentally incompatible with the aim of
+protecting users' freedom to change the software. The systematic
+pattern of such abuse occurs in the area of products for individuals to
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+have designed this version of the GPL to prohibit the practice for those
+products. If such problems arise substantially in other domains, we
+stand ready to extend this provision to those domains in future versions
+of the GPL, as needed to protect the freedom of users.
+
+ Finally, every program is threatened constantly by software patents.
+States should not allow patents to restrict development and use of
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+avoid the special danger that patents applied to a free program could
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+patents cannot be used to render the program non-free.
+
+ The precise terms and conditions for copying, distribution and
+modification follow.
+
+ TERMS AND CONDITIONS
+
+ 0. Definitions.
+
+ "This License" refers to version 3 of the GNU General Public License.
+
+ "Copyright" also means copyright-like laws that apply to other kinds of
+works, such as semiconductor masks.
+
+ "The Program" refers to any copyrightable work licensed under this
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+
+ A "covered work" means either the unmodified Program or a work based
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+
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+ To "convey" a work means any kind of propagation that enables other
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+
+ e) Convey the object code using peer-to-peer transmission, provided
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+ Source of the work are being offered to the general public at no
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+
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+included in conveying the object code work.
+
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+ 7. Additional Terms.
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+ "Additional permissions" are terms that supplement the terms of this
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+Additional permissions that are applicable to the entire Program shall
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+that they are valid under applicable law. If additional permissions
+apply only to part of the Program, that part may be used separately
+under those permissions, but the entire Program remains governed by
+this License without regard to the additional permissions.
+
+ When you convey a copy of a covered work, you may at your option
+remove any additional permissions from that copy, or from any part of
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+ All other non-permissive additional terms are considered "further
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+ You may not propagate or modify a covered work except as expressly
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+this License (including any patent licenses granted under the third
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+ However, if you cease all violation of this License, then your
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+ Moreover, your license from a particular copyright holder is
+reinstated permanently if the copyright holder notifies you of the
+violation by some reasonable means, this is the first time you have
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+your receipt of the notice.
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+ Termination of your rights under this section does not terminate the
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+reinstated, you do not qualify to receive new licenses for the same
+material under section 10.
+
+ 9. Acceptance Not Required for Having Copies.
+
+ You are not required to accept this License in order to receive or
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+ 10. Automatic Licensing of Downstream Recipients.
+
+ Each time you convey a covered work, the recipient automatically
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+ You may not impose any further restrictions on the exercise of the
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+any patent claim is infringed by making, using, selling, offering for
+sale, or importing the Program or any portion of it.
+
+ 11. Patents.
+
+ A "contributor" is a copyright holder who authorizes use under this
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+
+ A contributor's "essential patent claims" are all patent claims
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+but do not include claims that would be infringed only as a
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+patent license under the contributor's essential patent claims, to
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+
+ In the following three paragraphs, a "patent license" is any express
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+(such as an express permission to practice a patent or covenant not to
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+party means to make such an agreement or commitment not to enforce a
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+
+ If you convey a covered work, knowingly relying on a patent license,
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+then you must either (1) cause the Corresponding Source to be so
+available, or (2) arrange to deprive yourself of the benefit of the
+patent license for this particular work, or (3) arrange, in a manner
+consistent with the requirements of this License, to extend the patent
+license to downstream recipients. "Knowingly relying" means you have
+actual knowledge that, but for the patent license, your conveying the
+covered work in a country, or your recipient's use of the covered work
+in a country, would infringe one or more identifiable patents in that
+country that you have reason to believe are valid.
+
+ If, pursuant to or in connection with a single transaction or
+arrangement, you convey, or propagate by procuring conveyance of, a
+covered work, and grant a patent license to some of the parties
+receiving the covered work authorizing them to use, propagate, modify
+or convey a specific copy of the covered work, then the patent license
+you grant is automatically extended to all recipients of the covered
+work and works based on it.
+
+ A patent license is "discriminatory" if it does not include within
+the scope of its coverage, prohibits the exercise of, or is
+conditioned on the non-exercise of one or more of the rights that are
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+for and in connection with specific products or compilations that
+contain the covered work, unless you entered into that arrangement,
+or that patent license was granted, prior to 28 March 2007.
+
+ Nothing in this License shall be construed as excluding or limiting
+any implied license or other defenses to infringement that may
+otherwise be available to you under applicable patent law.
+
+ 12. No Surrender of Others' Freedom.
+
+ If conditions are imposed on you (whether by court order, agreement or
+otherwise) that contradict the conditions of this License, they do not
+excuse you from the conditions of this License. If you cannot convey a
+covered work so as to satisfy simultaneously your obligations under this
+License and any other pertinent obligations, then as a consequence you may
+not convey it at all. For example, if you agree to terms that obligate you
+to collect a royalty for further conveying from those to whom you convey
+the Program, the only way you could satisfy both those terms and this
+License would be to refrain entirely from conveying the Program.
+
+ 13. Use with the GNU Affero General Public License.
+
+ Notwithstanding any other provision of this License, you have
+permission to link or combine any covered work with a work licensed
+under version 3 of the GNU Affero General Public License into a single
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+License will continue to apply to the part which is the covered work,
+but the special requirements of the GNU Affero General Public License,
+section 13, concerning interaction through a network will apply to the
+combination as such.
+
+ 14. Revised Versions of this License.
+
+ The Free Software Foundation may publish revised and/or new versions of
+the GNU General Public License from time to time. Such new versions will
+be similar in spirit to the present version, but may differ in detail to
+address new problems or concerns.
+
+ Each version is given a distinguishing version number. If the
+Program specifies that a certain numbered version of the GNU General
+Public License "or any later version" applies to it, you have the
+option of following the terms and conditions either of that numbered
+version or of any later version published by the Free Software
+Foundation. If the Program does not specify a version number of the
+GNU General Public License, you may choose any version ever published
+by the Free Software Foundation.
+
+ If the Program specifies that a proxy can decide which future
+versions of the GNU General Public License can be used, that proxy's
+public statement of acceptance of a version permanently authorizes you
+to choose that version for the Program.
+
+ Later license versions may give you additional or different
+permissions. However, no additional obligations are imposed on any
+author or copyright holder as a result of your choosing to follow a
+later version.
+
+ 15. Disclaimer of Warranty.
+
+ THERE IS NO WARRANTY FOR THE PROGRAM, TO THE EXTENT PERMITTED BY
+APPLICABLE LAW. EXCEPT WHEN OTHERWISE STATED IN WRITING THE COPYRIGHT
+HOLDERS AND/OR OTHER PARTIES PROVIDE THE PROGRAM "AS IS" WITHOUT WARRANTY
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+THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
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+IS WITH YOU. SHOULD THE PROGRAM PROVE DEFECTIVE, YOU ASSUME THE COST OF
+ALL NECESSARY SERVICING, REPAIR OR CORRECTION.
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+ 16. Limitation of Liability.
+
+ IN NO EVENT UNLESS REQUIRED BY APPLICABLE LAW OR AGREED TO IN WRITING
+WILL ANY COPYRIGHT HOLDER, OR ANY OTHER PARTY WHO MODIFIES AND/OR CONVEYS
+THE PROGRAM AS PERMITTED ABOVE, BE LIABLE TO YOU FOR DAMAGES, INCLUDING ANY
+GENERAL, SPECIAL, INCIDENTAL OR CONSEQUENTIAL DAMAGES ARISING OUT OF THE
+USE OR INABILITY TO USE THE PROGRAM (INCLUDING BUT NOT LIMITED TO LOSS OF
+DATA OR DATA BEING RENDERED INACCURATE OR LOSSES SUSTAINED BY YOU OR THIRD
+PARTIES OR A FAILURE OF THE PROGRAM TO OPERATE WITH ANY OTHER PROGRAMS),
+EVEN IF SUCH HOLDER OR OTHER PARTY HAS BEEN ADVISED OF THE POSSIBILITY OF
+SUCH DAMAGES.
+
+ 17. Interpretation of Sections 15 and 16.
+
+ If the disclaimer of warranty and limitation of liability provided
+above cannot be given local legal effect according to their terms,
+reviewing courts shall apply local law that most closely approximates
+an absolute waiver of all civil liability in connection with the
+Program, unless a warranty or assumption of liability accompanies a
+copy of the Program in return for a fee.
+
+ END OF TERMS AND CONDITIONS
+
+ How to Apply These Terms to Your New Programs
+
+ If you develop a new program, and you want it to be of the greatest
+possible use to the public, the best way to achieve this is to make it
+free software which everyone can redistribute and change under these terms.
+
+ To do so, attach the following notices to the program. It is safest
+to attach them to the start of each source file to most effectively
+state the exclusion of warranty; and each file should have at least
+the "copyright" line and a pointer to where the full notice is found.
+
+
+ Copyright (C)
+
+ This program is free software: you can redistribute it and/or modify
+ it under the terms of the GNU General Public License as published by
+ the Free Software Foundation, either version 3 of the License, or
+ (at your option) any later version.
+
+ This program is distributed in the hope that it will be useful,
+ but WITHOUT ANY WARRANTY; without even the implied warranty of
+ MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
+ GNU General Public License for more details.
+
+ You should have received a copy of the GNU General Public License
+ along with this program. If not, see .
+
+Also add information on how to contact you by electronic and paper mail.
+
+ If the program does terminal interaction, make it output a short
+notice like this when it starts in an interactive mode:
+
+ Copyright (C)
+ This program comes with ABSOLUTELY NO WARRANTY; for details type `show w'.
+ This is free software, and you are welcome to redistribute it
+ under certain conditions; type `show c' for details.
+
+The hypothetical commands `show w' and `show c' should show the appropriate
+parts of the General Public License. Of course, your program's commands
+might be different; for a GUI interface, you would use an "about box".
+
+ You should also get your employer (if you work as a programmer) or school,
+if any, to sign a "copyright disclaimer" for the program, if necessary.
+For more information on this, and how to apply and follow the GNU GPL, see
+.
+
+ The GNU General Public License does not permit incorporating your program
+into proprietary programs. If your program is a subroutine library, you
+may consider it more useful to permit linking proprietary applications with
+the library. If this is what you want to do, use the GNU Lesser General
+Public License instead of this License. But first, please read
+.
diff --git a/DI-sheep/ui/README.md b/DI-sheep/ui/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..9e2eb9614bde34e2e7b6238dffa1076af597334e
--- /dev/null
+++ b/DI-sheep/ui/README.md
@@ -0,0 +1,3 @@
+# react 网页前端
+
+主要参考 https://github.com/StreakingMan/solvable-sheep-game ，请大家也多多支持这个 repo
diff --git a/DI-sheep/ui/index.html b/DI-sheep/ui/index.html
new file mode 100644
index 0000000000000000000000000000000000000000..ba7c22afa6d04d54dbabcb34ebc9fdab9d2983d2
--- /dev/null
+++ b/DI-sheep/ui/index.html
@@ -0,0 +1,31 @@
+
+
+
+
+
+
+
+ DI-sheep
+
+
+
+
+
+
+
+
diff --git a/DI-sheep/ui/package.json b/DI-sheep/ui/package.json
new file mode 100644
index 0000000000000000000000000000000000000000..f5c60032a410c18d381c1935e65a7dfe4f0abffd
--- /dev/null
+++ b/DI-sheep/ui/package.json
@@ -0,0 +1,41 @@
+{
+ "name": "DI-sheep-ui",
+ "private": false,
+ "version": "0.0.1",
+ "type": "module",
+ "scripts": {
+ "dev": "vite",
+ "build": "tsc && vite build",
+ "preview": "vite preview",
+ "prepare": "husky install",
+ "release:first": "standard-version -- --first-release",
+ "release": "standard-version --commit-all"
+ },
+ "dependencies": {
+ "react": "^18.2.0",
+ "react-dom": "^18.2.0"
+ },
+ "devDependencies": {
+ "@commitlint/cli": "^17.1.2",
+ "@commitlint/config-conventional": "^17.1.0",
+ "@types/react": "^18.0.20",
+ "@types/react-dom": "^18.0.6",
+ "@typescript-eslint/eslint-plugin": "^5.37.0",
+ "@typescript-eslint/parser": "^5.37.0",
+ "@vitejs/plugin-react": "^2.1.0",
+ "eslint": "^8.23.1",
+ "eslint-config-prettier": "^8.5.0",
+ "eslint-plugin-prettier": "^4.2.1",
+ "eslint-plugin-react": "^7.31.8",
+ "husky": "^8.0.1",
+ "lint-staged": "^13.0.3",
+ "prettier": "^2.7.1",
+ "standard-version": "^9.5.0",
+ "stylelint": "^14.11.0",
+ "stylelint-config-prettier-scss": "^0.0.1",
+ "stylelint-config-standard-scss": "^5.0.0",
+ "typescript": "^4.6.4",
+ "vite": "^3.1.0"
+ },
+ "license": "SEE LICENSE IN LICENSE.md"
+}
diff --git a/DI-sheep/ui/preview.png b/DI-sheep/ui/preview.png
new file mode 100644
index 0000000000000000000000000000000000000000..99f7e61254558ffdfc985ad6cf697a4736f54406
Binary files /dev/null and b/DI-sheep/ui/preview.png differ
diff --git a/DI-sheep/ui/public/demo.gif b/DI-sheep/ui/public/demo.gif
new file mode 100644
index 0000000000000000000000000000000000000000..943a19b675cb621f3dfc8cfb4deb0b7aa582235b
--- /dev/null
+++ b/DI-sheep/ui/public/demo.gif
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:08ccf0d041f155cf2cc9c8fbb3712e7cb5982ac886c8e2277289ba78743175e7
+size 4697925
diff --git a/DI-sheep/ui/public/favicon.ico b/DI-sheep/ui/public/favicon.ico
new file mode 100644
index 0000000000000000000000000000000000000000..3ab5292509d3c8ce693266953ba2ea00317f6249
Binary files /dev/null and b/DI-sheep/ui/public/favicon.ico differ
diff --git a/DI-sheep/ui/public/github.svg b/DI-sheep/ui/public/github.svg
new file mode 100644
index 0000000000000000000000000000000000000000..e75ce135311040a3f7923cc85c468ee24f2b06b8
--- /dev/null
+++ b/DI-sheep/ui/public/github.svg
@@ -0,0 +1,5 @@
+
diff --git a/DI-sheep/ui/public/song_of_kedaya.mp3 b/DI-sheep/ui/public/song_of_kedaya.mp3
new file mode 100644
index 0000000000000000000000000000000000000000..6f6486064ea3638ff266402e9ae1fed2777eaeb4
Binary files /dev/null and b/DI-sheep/ui/public/song_of_kedaya.mp3 differ
diff --git a/DI-sheep/ui/public/sound-disco.mp3 b/DI-sheep/ui/public/sound-disco.mp3
new file mode 100644
index 0000000000000000000000000000000000000000..7313de839a22ddac9111a50e1ad8a1c6b942023c
--- /dev/null
+++ b/DI-sheep/ui/public/sound-disco.mp3
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:62b6f7960a64624890e0c59a9e8a8fb02a95c6449091b98d1fa4817c288f638c
+size 8299694
diff --git a/DI-sheep/ui/qrcode.png b/DI-sheep/ui/qrcode.png
new file mode 100644
index 0000000000000000000000000000000000000000..038180fc438ca2f4442e122a76a114bea3ae43ad
Binary files /dev/null and b/DI-sheep/ui/qrcode.png differ
diff --git a/DI-sheep/ui/src/App.css b/DI-sheep/ui/src/App.css
new file mode 100644
index 0000000000000000000000000000000000000000..e8cea4e7f87da1022b7e4ea3c4373e7a886c9e29
--- /dev/null
+++ b/DI-sheep/ui/src/App.css
@@ -0,0 +1,110 @@
+#root {
+ text-align: center;
+ width: 100%;
+ max-width: 500px;
+ margin: 0 auto;
+}
+
+.app {
+ width: 100%;
+ margin: 0 auto;
+}
+
+.scene-container {
+ width: 100%;
+ padding-bottom: 100%;
+ position: relative;
+ margin: 10% 0;
+}
+
+.scene-inner {
+ position: absolute;
+ left: 0;
+ right: 0;
+ bottom: 0;
+ top: 0;
+ overflow: visible;
+ font-size: 28px;
+}
+
+.symbol {
+ width: 12.5%;
+ padding-bottom: 12.5%;
+ position: absolute;
+ transition: 150ms;
+ left: 0;
+ top: 0;
+ border-radius: 8px;
+}
+
+.symbol-inner {
+ position: absolute;
+ left: 0;
+ right: 0;
+ bottom: 0;
+ top: 0;
+ display: flex;
+ justify-content: center;
+ align-items: center;
+ border-radius: 8px;
+ border: 2px solid #444;
+ transition: 0.3s;
+ overflow: hidden;
+ user-select: none;
+}
+
+.symbol-inner img {
+ width: 100%;
+ height: 100%;
+ object-fit: contain;
+}
+
+.queue-container {
+ border-radius: 8px;
+ width: 100%;
+ padding-bottom: 15%;
+ border: 2px solid gray;
+ margin-bottom: 16px;
+}
+
+.flex-container {
+ display: flex;
+ gap: 8px;
+}
+
+.flex-center {
+ justify-content: center;
+ align-items: center;
+}
+
+.flex-grow {
+ flex-grow: 1;
+}
+
+.flex-between {
+ justify-content: space-between;
+ align-items: center;
+}
+
+.modal {
+ position: fixed;
+ width: 100vw;
+ height: 100vh;
+ display: flex;
+ flex-direction: column;
+ align-items: center;
+ justify-content: center;
+ backdrop-filter: blur(10px);
+ background-color: rgb(255 255 255 / 40%);
+ top: 0;
+ left: 0;
+}
+
+.bgm-button {
+ position: fixed;
+ left: 0;
+ top: 0;
+ padding: 4px;
+ width: 36px;
+ height: 36px;
+}
diff --git a/DI-sheep/ui/src/App.tsx b/DI-sheep/ui/src/App.tsx
new file mode 100644
index 0000000000000000000000000000000000000000..f6f89cc566a86cd6e852d0375c9bdab73d1fb07b
--- /dev/null
+++ b/DI-sheep/ui/src/App.tsx
@@ -0,0 +1,449 @@
+import React, {
+ FC,
+ MouseEventHandler,
+ useEffect,
+ useRef,
+ useState,
+} from 'react';
+
+import './App.css';
+import { GithubIcon } from './GithubIcon';
+import { randomString, waitTimeout } from './utils';
+import { defaultTheme } from './themes/default';
+import { Icon, Theme } from './themes/interface';
+import { fishermanTheme } from './themes/fisherman';
+import { diTheme } from './themes/di';
+import { mhlTheme } from './themes/mhl';
+import { yhdTheme } from './themes/yhd';
+
+const themes = [defaultTheme, fishermanTheme, diTheme, mhlTheme, yhdTheme];
+
+const maxLevel = 10;
+const target_url = 'http://localhost:5002/DI-sheep/';
+
+interface MySymbol {
+ id: string;
+ status: number; // 0->1->2
+ isCover: boolean;
+ isAgentTarget: boolean;
+ x: number;
+ y: number;
+ icon: Icon;
+}
+
+type Scene = MySymbol[];
+
+// 8*8 grid with factor 4 (32x32)
+const makeScene: (level: number, icons: Icon[], new_scene_data: string[], agent_action: number) => Scene = (level, icons, new_scene_data, agent_action) => {
+ const curLevel = Math.min(maxLevel, level);
+ const iconPool = icons.slice(0, 2 * curLevel);
+
+ const scene: Scene = [];
+
+ for (const raw_data of new_scene_data) {
+ const data = JSON.parse(raw_data);
+
+ const count = scene.length;
+ scene.push({
+ isCover: !data.accessible,
+ // isCover: !data.visible, // for viz debug
+ isAgentTarget: count === agent_action,
+ status: 0,
+ icon: iconPool[data.icon],
+ id: data.uid,
+ x: data.x,
+ y: data.y,
+ });
+ }
+ return scene;
+};
+
+
+interface SymbolProps extends MySymbol {
+ onClick: MouseEventHandler;
+}
+
+const Symbol: FC = ({ x, y, icon, isCover, isAgentTarget, status, onClick }) => {
+ return (
+
+