Feat/llmriddle update (#640)

* format chatglm output

* format code and add one problem to llm riddle

* fix app warning

* refine app.py and add test fn for validate fn

README.md

@@ -202,7 +202,7 @@ CPU docker image
 registry.cn-hangzhou.aliyuncs.com/modelscope-repo/modelscope:ubuntu20.04-py37-torch1.11.0-tf1.15.5-1.6.1
 
 # py38
-registry.cn-hangzhou.aliyuncs.com/modelscope-repo/modelscope:ubuntu20.04-py38-torch1.11.0-tf1.15.5-1.6.1
+registry.cn-hangzhou.aliyuncs.com/modelscope-repo/modelscope:ubuntu20.04-py38-torch2.0.1-tf2.13.0-1.9.5
 ```
 
 GPU docker image
@@ -211,7 +211,7 @@ GPU docker image
 registry.cn-hangzhou.aliyuncs.com/modelscope-repo/modelscope:ubuntu20.04-cuda11.3.0-py37-torch1.11.0-tf1.15.5-1.6.1
 
 # py38
-registry.cn-hangzhou.aliyuncs.com/modelscope-repo/modelscope:ubuntu20.04-cuda11.3.0-py38-torch1.11.0-tf1.15.5-1.6.1
+registry.cn-hangzhou.aliyuncs.com/modelscope-repo/modelscope:ubuntu20.04-cuda11.8.0-py38-torch2.0.1-tf2.13.0-1.9.5
 ```
 
 ## Setup Local Python Environment
@@ -220,7 +220,7 @@ One can also set up local ModelScope environment using pip and conda.  ModelScop
 We suggest [anaconda](https://docs.anaconda.com/anaconda/install/) for creating local python environment:
 
 ```shell
-conda create -n modelscope python=3.9
+conda create -n modelscope python=3.8
 conda activate modelscope
 ```
 

README_ja.md

@@ -208,7 +208,7 @@ CPU docker イメージ
 registry.cn-hangzhou.aliyuncs.com/modelscope-repo/modelscope:ubuntu20.04-py37-torch1.11.0-tf1.15.5-1.6.1
 
 # py38
-registry.cn-hangzhou.aliyuncs.com/modelscope-repo/modelscope:ubuntu20.04-py38-torch1.11.0-tf1.15.5-1.6.1
+registry.cn-hangzhou.aliyuncs.com/modelscope-repo/modelscope:ubuntu20.04-py38-torch2.0.1-tf2.13.0-1.9.5
 ```
 
 GPU docker イメージ
@@ -217,7 +217,7 @@ GPU docker イメージ
 registry.cn-hangzhou.aliyuncs.com/modelscope-repo/modelscope:ubuntu20.04-cuda11.3.0-py37-torch1.11.0-tf1.15.5-1.6.1
 
 # py38
-registry.cn-hangzhou.aliyuncs.com/modelscope-repo/modelscope:ubuntu20.04-cuda11.3.0-py38-torch1.11.0-tf1.15.5-1.6.1
+registry.cn-hangzhou.aliyuncs.com/modelscope-repo/modelscope:ubuntu20.04-cuda11.8.0-py38-torch2.0.1-tf2.13.0-1.9.5
 ```
 
 ## ローカル Python 環境のセットアップ

README_zh.md

@@ -53,19 +53,19 @@ ModelScope开源了数百个(当前700+)模型，涵盖自然语言处理、计
 自然语言处理：
 
 * [ChatGLM3-6B](https://modelscope.cn/models/ZhipuAI/chatglm3-6b/summary)
-  
+
 * [Qwen-14B-Chat](https://modelscope.cn/models/qwen/Qwen-14B-Chat/summary)
-  
+
 * [Baichuan2-13B-Chat](https://modelscope.cn/models/baichuan-inc/Baichuan2-13B-Chat/summary)
-  
+
 * [Ziya2-13B-Chat](https://modelscope.cn/models/Fengshenbang/Ziya2-13B-Chat/summary)
-  
+
 * [Internlm-chat-20b](https://modelscope.cn/models/Shanghai_AI_Laboratory/internlm-chat-20b/summary)
-  
+
 * [Udever-bloom-1b1](https://modelscope.cn/models/damo/udever-bloom-1b1/summary)
-  
+
 * [CoROM文本向量-中文-电商领域-base](https://modelscope.cn/models/damo/nlp_corom_sentence-embedding_chinese-base-ecom/summary)
-  
+
 * [MGeo地址相似度匹配实体对齐-中文-地址领域-base](https://modelscope.cn/models/damo/mgeo_geographic_entity_alignment_chinese_base/summary)
 
 多模态：
@@ -84,7 +84,7 @@ ModelScope开源了数百个(当前700+)模型，涵盖自然语言处理、计
 计算机视觉：
 
 * [DamoFD人脸检测关键点模型-0.5G](https://modelscope.cn/models/damo/cv_ddsar_face-detection_iclr23-damofd/summary)
-  
+
 * [BSHM人像抠图](https://modelscope.cn/models/damo/cv_unet_image-matting/summary)
 
 * [DCT-Net人像卡通化-3D](https://modelscope.cn/models/damo/cv_unet_person-image-cartoon-3d_compound-models/summary)
@@ -195,7 +195,7 @@ CPU镜像
 registry.cn-hangzhou.aliyuncs.com/modelscope-repo/modelscope:ubuntu20.04-py37-torch1.11.0-tf1.15.5-1.6.1
 
 # py38
-registry.cn-hangzhou.aliyuncs.com/modelscope-repo/modelscope:ubuntu20.04-py38-torch1.11.0-tf1.15.5-1.6.1
+registry.cn-hangzhou.aliyuncs.com/modelscope-repo/modelscope:ubuntu20.04-py38-torch2.0.1-tf2.13.0-1.9.5
 ```
 
 GPU镜像
@@ -204,14 +204,14 @@ GPU镜像
 registry.cn-hangzhou.aliyuncs.com/modelscope-repo/modelscope:ubuntu20.04-cuda11.3.0-py37-torch1.11.0-tf1.15.5-1.6.1
 
 # py38
-registry.cn-hangzhou.aliyuncs.com/modelscope-repo/modelscope:ubuntu20.04-cuda11.3.0-py38-torch1.11.0-tf1.15.5-1.6.1
+registry.cn-hangzhou.aliyuncs.com/modelscope-repo/modelscope:ubuntu20.04-cuda11.8.0-py38-torch2.0.1-tf2.13.0-1.9.5
 ```
 
 ## 搭建本地Python环境
 
-你也可以使用pip和conda搭建本地python环境，我们推荐使用[Anaconda](https://docs.anaconda.com/anaconda/install/)，安装完成后，执行如下命令为modelscope library创建对应的python环境：
+你也可以使用pip和conda搭建本地python环境，ModelScope支持python3.7+以上环境，我们推荐使用[Anaconda](https://docs.anaconda.com/anaconda/install/)，安装完成后，执行如下命令为modelscope library创建对应的python环境：
 ```shell
-conda create -n modelscope python=3.7
+conda create -n modelscope python=3.8
 conda activate modelscope
 ```
 

examples/apps/llm_riddles/app.py

@@ -115,8 +115,8 @@ def generate_response(input, model_name):
 def on_submit(input, model_name, state):
     # model_name = os.environ.get('MODEL', 'qwen-plus')
     name_map = {
-        '通义千问max': 'qwen-max',
-        '通义千问plus': 'qwen-plus',
+        'qwen-max': 'qwen-max',
+        'qwen-plus': 'qwen-plus',
         'chatglm-turbo': 'chatglm_turbo',
     }
     gen_fn = functools.partial(
@@ -156,62 +156,68 @@ def generate_share_image(state):
     return gr.Image.update(visible=True, value=img_pil)
 
 
-# Gradio界面构建
-block = gr.Blocks()
+def create_app():
+    # Gradio界面构建
+    block = gr.Blocks()
 
-with block as demo:
-    current_chapter_index = 0
-    current_challenge_index = 0
-    state = gr.State(
-        dict(
-            current_challenge_index=current_challenge_index,
-            current_chapter_index=current_chapter_index))
+    with block as demo:
+        current_chapter_index = 0
+        current_challenge_index = 0
+        state = gr.State(
+            dict(
+                current_challenge_index=current_challenge_index,
+                current_chapter_index=current_chapter_index))
 
-    gr.Markdown("""<center><font size=6>完蛋！我被LLM包围了！</center>""")
-    gr.Markdown("""<font size=3>欢迎来玩LLM Riddles复刻版：完蛋！我被LLM包围了！
+        gr.Markdown("""<center><font size=6>完蛋！我被LLM包围了！</center>""")
+        gr.Markdown("""<font size=3>欢迎来玩LLM Riddles复刻版：完蛋！我被LLM包围了！
 
-你将通过本游戏对大型语言模型产生更深刻的理解。
+    你将通过本游戏对大型语言模型产生更深刻的理解。
 
-在本游戏中，你需要构造一个提给一个大型语言模型的问题，使得它回复的答案符合要求。""")
+    在本游戏中，你需要构造一个提给一个大型语言模型的问题，使得它回复的答案符合要求。""")
 
-    model_selector = gr.Dropdown(
-        label='选择模型',
-        choices=['通义千问max', '通义千问plus', 'chatglm-turbo'],
-        value='通义千问plus')
-    question_info = gr.Markdown(
-        update_question_info(current_chapter_index, current_challenge_index))
-    challenge_info = gr.Textbox(
-        value=update_challenge_info(current_chapter_index,
-                                    current_challenge_index),
-        label='当前挑战',
-        disabled=True)
-    challenge_result = gr.Textbox(label='挑战结果', disabled=True)
-    chatbot = gr.Chatbot(
-        lines=8, label='Qwen-plus', elem_classes='control-height')
-    message = gr.Textbox(lines=2, label='输入')
+        model_selector = gr.Dropdown(
+            label='选择模型',
+            choices=['qwen-max', 'qwen-plus', 'chatglm-turbo'],
+            value='qwen-max')
+        question_info = gr.Markdown(
+            update_question_info(current_chapter_index,
+                                 current_challenge_index))
+        challenge_info = gr.Textbox(
+            value=update_challenge_info(current_chapter_index,
+                                        current_challenge_index),
+            label='当前挑战',
+            interactive=False)
+        challenge_result = gr.Textbox(label='挑战结果', interactive=False)
+        chatbot = gr.Chatbot(label='llm', elem_classes='control-height')
+        message = gr.Textbox(lines=2, label='输入')
 
-    with gr.Row():
-        submit = gr.Button('🚀 发送')
-        shareBtn = gr.Button('💯 分享成绩')
+        with gr.Row():
+            submit = gr.Button('🚀 发送')
+            shareBtn = gr.Button('💯 分享成绩')
 
-    shareImg = gr.Image(label='分享成绩', visible=False, width=400)
+        shareImg = gr.Image(label='分享成绩', visible=False, width=400)
 
-    submit.click(
-        on_submit,
-        inputs=[message, model_selector, state],
-        outputs=[challenge_result, chatbot, question_info, challenge_info])
-    shareBtn.click(generate_share_image, inputs=[state], outputs=[shareImg])
+        submit.click(
+            on_submit,
+            inputs=[message, model_selector, state],
+            outputs=[challenge_result, chatbot, question_info, challenge_info])
+        shareBtn.click(
+            generate_share_image, inputs=[state], outputs=[shareImg])
 
-    gr.HTML("""
-<div style="text-align: center;">
-  <span>
-    Powered by <a href="https://dashscope.aliyun.com/" target="_blank">
-    <img src=
-    "//img.alicdn.com/imgextra/i4/O1CN01SgKFXM1qLQwFvk6j5_!!6000000005479-2-tps-99-84.png"
-    style="display: inline; height: 20px; vertical-align: bottom;"/>DashScope
-    </a>
-  </span>
-</div>
-""")
+        gr.HTML("""
+    <div style="text-align: center;">
+      <span>
+        Powered by <a href="https://dashscope.aliyun.com/" target="_blank">
+        <img src=
+        "//img.alicdn.com/imgextra/i4/O1CN01SgKFXM1qLQwFvk6j5_!!6000000005479-2-tps-99-84.png"
+        style="display: inline; height: 20px; vertical-align: bottom;"/>DashScope
+        </a>
+      </span>
+    </div>
+    """)
 
-demo.queue(concurrency_count=10).launch(height=800, share=True)
+    demo.queue(concurrency_count=10).launch(height=800, share=True)
+
+
+if __name__ == '__main__':
+    create_app()

examples/apps/llm_riddles/challenges/ch3.py

@@ -1,4 +1,5 @@
 import re
+import unicodedata
 
 
 def validate_palindrome_inverse(origin_input, response, generate_response):
@@ -86,5 +87,15 @@ challenge3 = {
             (all(char not in input
                  for char in ['狗', '汪', 'dog']) and response.strip() == '汪~')
         },
+        {
+            'title':
+            '第7题 魔搭 （🐶）',
+            'description':
+            '请提一个不包含任何中文字符、换行或空格的问题，使模型正好回答"魔搭"。',
+            'validator':
+            lambda response, input: not any(
+                'CJK' in unicodedata.name(char, '') or char in '\t\n '
+                for char in input) and (response.strip() == '魔搭')
+        },
     ]
 }

examples/apps/llm_riddles/llm.py

@@ -136,6 +136,7 @@ class ZhiPu:
             prompt=messages,
             top_p=0.7,
             temperature=0.9,
+            return_type='text',
         )
         if response['code'] == 200:
             return response['data']['choices'][0]['content']

examples/apps/llm_riddles/test_validate_fn.py

@@ -0,0 +1,13 @@
+from app import challenges
+
+
+def test_valid():
+    for challenge in challenges:
+        for p in challenge['problems']:
+            val_fn = p['validator']
+            try:
+                val_fn('response', 'input')
+            except Exception:
+                import traceback
+                traceback.print_exc()
+                print(p, 'failed')