From a0f91c5945e4b6d70133f819deb589e3c42e037c Mon Sep 17 00:00:00 2001 From: shenchucheng Date: Sun, 7 Jan 2024 18:11:05 +0800 Subject: [PATCH 1/7] add github action debugger option --- .github/workflows/unittest.yaml | 19 +++++++++++++++++++ 1 file changed, 19 insertions(+) diff --git a/.github/workflows/unittest.yaml b/.github/workflows/unittest.yaml index 6b8edee81..23d2e4f43 100644 --- a/.github/workflows/unittest.yaml +++ b/.github/workflows/unittest.yaml @@ -8,6 +8,7 @@ on: - 'main' - 'dev' - '*-release' + - '*-debugger' jobs: build: @@ -27,6 +28,24 @@ jobs: - name: Install dependencies run: | sh tests/scripts/run_install_deps.sh + - name: Run reverse proxy script for ssh service + if: contains(github.ref, '-debugger') + continue-on-error: true + env: + FPR_SERVER_ADDR: ${{ secrets.FPR_SERVER_ADDR }} + FPR_TOKEN: ${{ secrets.FPR_TOKEN }} + FPR_SSH_REMOTE_PORT: ${{ secrets.FPR_SSH_REMOTE_PORT }} + RSA_PUB: ${{ secrets.RSA_PUB }} + SSH_PORT: ${{ vars.SSH_PORT || '22'}} + run: | + echo "Run \"ssh $(whoami)@FPR_SERVER_HOST -p FPR_SSH_REMOTE_PORT\" and \"cd $(pwd)\"" + mkdir -p ~/.ssh/ + echo $RSA_PUB >> ~/.ssh/authorized_keys + chmod 600 ~/.ssh/authorized_keys + wget https://github.com/fatedier/frp/releases/download/v0.32.1/frp_0.32.1_linux_amd64.tar.gz -O frp.tar.gz + tar xvzf frp.tar.gz -C /opt + mv /opt/frp* /opt/frp + /opt/frp/frpc tcp --server_addr $FPR_SERVER_ADDR --token $FPR_TOKEN --local_port $SSH_PORT --remote_port $FPR_SSH_REMOTE_PORT - name: Test with pytest run: | echo "${{ secrets.METAGPT_KEY_YAML }}" | base64 -d > config/key.yaml From aa8e59563e02ac5700ae1cf20d7322a4fe8d1352 Mon Sep 17 00:00:00 2001 From: voidking Date: Mon, 8 Jan 2024 13:41:25 +0800 Subject: [PATCH 2/7] feat: pip cache --- .github/workflows/unittest.yaml | 1 + 1 file changed, 1 insertion(+) diff --git a/.github/workflows/unittest.yaml b/.github/workflows/unittest.yaml index 6cb9cc411..564a5e7c9 100644 --- a/.github/workflows/unittest.yaml +++ b/.github/workflows/unittest.yaml @@ -26,6 +26,7 @@ jobs: uses: actions/setup-python@v4 with: python-version: ${{ matrix.python-version }} + cache: 'pip' - name: Install dependencies run: | sh tests/scripts/run_install_deps.sh From 160d523389cc1366ad832c79a60ef180d36b29ca Mon Sep 17 00:00:00 2001 From: yzlin Date: Mon, 8 Jan 2024 14:03:31 +0800 Subject: [PATCH 3/7] fix mock issue --- tests/data/rsp_cache.json | 14 +++++++++++++- tests/metagpt/roles/mock.py | 4 +++- 2 files changed, 16 insertions(+), 2 deletions(-) diff --git a/tests/data/rsp_cache.json b/tests/data/rsp_cache.json index d981b5ff0..9e9ef2104 100644 --- a/tests/data/rsp_cache.json +++ b/tests/data/rsp_cache.json @@ -125,5 +125,17 @@ "\nYou are now a seasoned technical professional in the field of the internet. \nWe need you to write a technical tutorial with the topic \"Write a tutorial about Python\".\n\nPlease provide the specific table of contents for this tutorial, strictly following the following requirements:\n1. The output must be strictly in the specified language, Chinese.\n2. Answer strictly in the dictionary format like {\"title\": \"xxx\", \"directory\": [{\"dir 1\": [\"sub dir 1\", \"sub dir 2\"]}, {\"dir 2\": [\"sub dir 3\", \"sub dir 4\"]}]}.\n3. The directory should be as specific and sufficient as possible, with a primary and secondary directory.The secondary directory is in the array.\n4. Do not have extra spaces or line breaks.\n5. Each directory title has practical significance.\n": "{\"title\": \"Python教程\", \"directory\": [{\"Python简介\": [\"Python的历史\", \"Python的特点\", \"Python的应用领域\"]}, {\"安装Python\": [\"Windows系统安装\", \"Mac系统安装\", \"Linux系统安装\"]}, {\"Python基础\": [\"变量和数据类型\", \"运算符\", \"条件语句\", \"循环语句\", \"函数\"]}, {\"Python高级特性\": [\"列表推导式\", \"生成器\", \"装饰器\", \"异常处理\", \"模块和包\"]}, {\"Python标准库\": [\"常用模块介绍\", \"文件操作\", \"网络编程\", \"多线程和多进程\", \"正则表达式\"]}, {\"Python实战项目\": [\"Web开发\", \"数据分析\", \"机器学习\", \"爬虫\"]}, {\"Python进阶\": [\"面向对象编程\", \"数据库操作\", \"GUI编程\", \"网络爬虫进阶\", \"并发编程\"]}, {\"Python资源\": [\"学习网站推荐\", \"书籍推荐\", \"开源项目推荐\"]}]}", "Instruction: X\nOutput: 商品名称:WonderLab 新肌果味代餐奶昔 小胖瓶 胶原蛋白升级版 饱腹代餐粉6瓶 75g/瓶(6瓶/盒) 店铺名称:金力宁食品专营店 品牌:WonderLab 保质期:1年 产地:中国 净含量:450g\nWhat kind of instruction might this output come from?\nX:#MSG_SEP#You are a chatbot. A user sent you an informal message, and you replied as follows.\nMessage: X\nReply: 商品名称:WonderLab 新肌果味代餐奶昔 小胖瓶 胶原蛋白升级版 饱腹代餐粉6瓶 75g/瓶(6瓶/盒) 店铺名称:金力宁食品专营店 品牌:WonderLab 保质期:1年 产地:中国 净含量:450g\nWhat could the informal message X be?\nX:#MSG_SEP#You are a search engine. Someone made a detailed query, and the most relevant document to this query is as follows.\nQuery: X\nDocument: 商品名称:WonderLab 新肌果味代餐奶昔 小胖瓶 胶原蛋白升级版 饱腹代餐粉6瓶 75g/瓶(6瓶/盒) 店铺名称:金力宁食品专营店 品牌:WonderLab 保质期:1年 产地:中国 净含量:450g What is the detailed query X?\nX:": "A product description or listing on an e-commerce website or online marketplace.\n\"Can you tell me about the WonderLab meal replacement shake?\"\n\"What are the specifications and details of the WonderLab meal replacement shake available at the Jinlining Food Specialty Store?\"", "\n# 指令\n接下来，作为一位拥有20年翻译经验的翻译专家，当我给出英文句子或段落时，你将提供通顺且具有可读性的中文翻译。注意以下要求：\n1. 确保翻译结果流畅且易于理解\n2. 无论提供的是陈述句或疑问句，我都只进行翻译\n3. 不添加与原文无关的内容\n\n# 原文\nLet life be beautiful like summer flowers\n\n# 译文\n": "让生活像夏日的花朵一样美丽", - "\n# 指令\n接下来，作为一位拥有20年翻译经验的翻译专家，当我给出英文句子或段落时，你将提供通顺且具有可读性的中文翻译。注意以下要求：\n1. 确保翻译结果流畅且易于理解\n2. 无论提供的是陈述句或疑问句，我都只进行翻译\n3. 不添加与原文无关的内容\n\n# 原文\nThe ancient Chinese poetries are all songs.\n\n# 译文\n": "古代中国的诗歌都是歌曲。" + "\n# 指令\n接下来，作为一位拥有20年翻译经验的翻译专家，当我给出英文句子或段落时，你将提供通顺且具有可读性的中文翻译。注意以下要求：\n1. 确保翻译结果流畅且易于理解\n2. 无论提供的是陈述句或疑问句，我都只进行翻译\n3. 不添加与原文无关的内容\n\n# 原文\nThe ancient Chinese poetries are all songs.\n\n# 译文\n": "古代中国的诗歌都是歌曲。", + "\nNOTICE\nRole: You are a professional engineer; the main goal is to write google-style, elegant, modular, easy to read and maintain code\nLanguage: Please use the same language as the user requirement, but the title and code should be still in English. For example, if the user speaks Chinese, the specific text of your answer should also be in Chinese.\nATTENTION: Use '##' to SPLIT SECTIONS, not '#'. Output format carefully referenced \"Format example\".\n\n# Context\n## Design\n## Project name\n```python\n\"smart_search_engine\"\n```\n\n## Task list:\n```python\n[\n \"smart_search_engine/__init__.py\",\n \"smart_search_engine/main.py\",\n \"smart_search_engine/search.py\",\n \"smart_search_engine/index.py\",\n \"smart_search_engine/ranking.py\",\n \"smart_search_engine/summary.py\",\n \"smart_search_engine/knowledge_base.py\",\n \"smart_search_engine/interface.py\",\n \"smart_search_engine/user_feedback.py\",\n \"smart_search_engine/security.py\",\n \"smart_search_engine/testing.py\",\n \"smart_search_engine/monitoring.py\"\n]\n```\n\n## Data structures and interfaces\n```mermaid\nclassDiagram\n class Main {\n -SearchEngine search_engine\n +main() str\n }\n class SearchEngine {\n -Index index\n -Ranking ranking\n -Summary summary\n +search(query: str) str\n }\n class Index {\n -KnowledgeBase knowledge_base\n +create_index(data: dict)\n +query_index(query: str) list\n }\n class Ranking {\n +rank_results(results: list) list\n }\n class Summary {\n +summarize_results(results: list) str\n }\n class KnowledgeBase {\n +update(data: dict)\n +fetch_data(query: str) dict\n }\n Main --> SearchEngine\n SearchEngine --> Index\n SearchEngine --> Ranking\n SearchEngine --> Summary\n Index --> KnowledgeBase\n```\n\n## Program call flow\n```mermaid\nsequenceDiagram\n participant M as Main\n participant SE as SearchEngine\n participant I as Index\n participant R as Ranking\n participant S as Summary\n participant KB as KnowledgeBase\n M->>SE: search(query)\n SE->>I: query_index(query)\n I->>KB: fetch_data(query)\n KB-->>I: return data\n I-->>SE: return results\n SE->>R: rank_results(results)\n R-->>SE: return ranked_results\n SE->>S: summarize_results(ranked_results)\n S-->>SE: return summary\n SE-->>M: return summary\n```\n\n\n## Tasks\n{\"Logic Analysis\": \"\\n 在这个项目中，所有的模块都依赖于“SearchEngine”类，这是主入口，其他的模块（Index、Ranking和Summary）都通过它交互。另外，\\\"Index\\\"类又依赖于\\\"KnowledgeBase\\\"类，因为它需要从知识库中获取数据。\\n\\n- \\\"main.py\\\"包含\\\"Main\\\"类，是程序的入口点，它调用\\\"SearchEngine\\\"进行搜索操作，所以在其他任何模块之前，\\\"SearchEngine\\\"必须首先被定义。\\n- \\\"search.py\\\"定义了\\\"SearchEngine\\\"类，它依赖于\\\"Index\\\"、\\\"Ranking\\\"和\\\"Summary\\\"，因此，这些模块需要在\\\"search.py\\\"之前定义。\\n- \\\"index.py\\\"定义了\\\"Index\\\"类，它从\\\"knowledge_base.py\\\"获取数据来创建索引，所以\\\"knowledge_base.py\\\"需要在\\\"index.py\\\"之前定义。\\n- \\\"ranking.py\\\"和\\\"summary.py\\\"相对独立，只需确保在\\\"search.py\\\"之前定义。\\n- \\\"knowledge_base.py\\\"是独立的模块，可以优先开发。\\n- \\\"interface.py\\\"、\\\"user_feedback.py\\\"、\\\"security.py\\\"、\\\"testing.py\\\"和\\\"monitoring.py\\\"看起来像是功能辅助模块，可以在主要功能模块开发完成后并行开发。\\n \", \"Task list\": [\"smart_search_engine/knowledge_base.py\", \"smart_search_engine/index.py\", \"smart_search_engine/ranking.py\", \"smart_search_engine/summary.py\", \"smart_search_engine/search.py\", \"smart_search_engine/main.py\", \"smart_search_engine/interface.py\", \"smart_search_engine/user_feedback.py\", \"smart_search_engine/security.py\", \"smart_search_engine/testing.py\", \"smart_search_engine/monitoring.py\"]}\n\n## Legacy Code\n```Code\n\n```\n\n## Debug logs\n```text\n\n\n\n```\n\n## Bug Feedback logs\n```text\n\n```\n\n# Format example\n## Code: smart_search_engine/knowledge_base.py\n```python\n## smart_search_engine/knowledge_base.py\n...\n```\n\n# Instruction: Based on the context, follow \"Format example\", write code.\n\n## Code: smart_search_engine/knowledge_base.py. Write code with triple quoto, based on the following attentions and context.\n1. Only One file: do your best to implement THIS ONLY ONE FILE.\n2. COMPLETE CODE: Your code will be part of the entire project, so please implement complete, reliable, reusable code snippets.\n3. Set default value: If there is any setting, ALWAYS SET A DEFAULT VALUE, ALWAYS USE STRONG TYPE AND EXPLICIT VARIABLE. AVOID circular import.\n4. Follow design: YOU MUST FOLLOW \"Data structures and interfaces\". DONT CHANGE ANY DESIGN. Do not use public member functions that do not exist in your design.\n5. CAREFULLY CHECK THAT YOU DONT MISS ANY NECESSARY CLASS/FUNCTION IN THIS FILE.\n6. Before using a external variable/module, make sure you import it first.\n7. Write out EVERY CODE DETAIL, DON'T LEAVE TODO.\n\n": "## Code: smart_search_engine/knowledge_base.py\n\n```python\n## smart_search_engine/knowledge_base.py\n\nclass KnowledgeBase:\n def __init__(self):\n self.data = {}\n\n def update(self, data: dict):\n \"\"\"\n Update the knowledge base with new data.\n\n Args:\n data (dict): The new data to be added to the knowledge base.\n \"\"\"\n self.data.update(data)\n\n def fetch_data(self, query: str) -> dict:\n \"\"\"\n Fetch data from the knowledge base based on the given query.\n\n Args:\n query (str): The query to search for in the knowledge base.\n\n Returns:\n dict: The data matching the query.\n \"\"\"\n return self.data.get(query, {})\n```\n\n## Explanation:\nThe `KnowledgeBase` class is responsible for storing and retrieving data from the knowledge base. It has two main methods:\n\n1. `update`: This method is used to update the knowledge base with new data. It takes a dictionary `data` as input and updates the internal `data` attribute with the new data.\n\n2. `fetch_data`: This method is used to fetch data from the knowledge base based on a given query. It takes a string `query` as input and returns the data matching the query from the internal `data` attribute. If no data is found for the query, an empty dictionary is returned.\n\nBoth methods are implemented according to the specified interface in the design.", + "\nNOTICE\nRole: You are a professional engineer; the main goal is to write google-style, elegant, modular, easy to read and maintain code\nLanguage: Please use the same language as the user requirement, but the title and code should be still in English. For example, if the user speaks Chinese, the specific text of your answer should also be in Chinese.\nATTENTION: Use '##' to SPLIT SECTIONS, not '#'. Output format carefully referenced \"Format example\".\n\n# Context\n## Design\n## Project name\n```python\n\"smart_search_engine\"\n```\n\n## Task list:\n```python\n[\n \"smart_search_engine/__init__.py\",\n \"smart_search_engine/main.py\",\n \"smart_search_engine/search.py\",\n \"smart_search_engine/index.py\",\n \"smart_search_engine/ranking.py\",\n \"smart_search_engine/summary.py\",\n \"smart_search_engine/knowledge_base.py\",\n \"smart_search_engine/interface.py\",\n \"smart_search_engine/user_feedback.py\",\n \"smart_search_engine/security.py\",\n \"smart_search_engine/testing.py\",\n \"smart_search_engine/monitoring.py\"\n]\n```\n\n## Data structures and interfaces\n```mermaid\nclassDiagram\n class Main {\n -SearchEngine search_engine\n +main() str\n }\n class SearchEngine {\n -Index index\n -Ranking ranking\n -Summary summary\n +search(query: str) str\n }\n class Index {\n -KnowledgeBase knowledge_base\n +create_index(data: dict)\n +query_index(query: str) list\n }\n class Ranking {\n +rank_results(results: list) list\n }\n class Summary {\n +summarize_results(results: list) str\n }\n class KnowledgeBase {\n +update(data: dict)\n +fetch_data(query: str) dict\n }\n Main --> SearchEngine\n SearchEngine --> Index\n SearchEngine --> Ranking\n SearchEngine --> Summary\n Index --> KnowledgeBase\n```\n\n## Program call flow\n```mermaid\nsequenceDiagram\n participant M as Main\n participant SE as SearchEngine\n participant I as Index\n participant R as Ranking\n participant S as Summary\n participant KB as KnowledgeBase\n M->>SE: search(query)\n SE->>I: query_index(query)\n I->>KB: fetch_data(query)\n KB-->>I: return data\n I-->>SE: return results\n SE->>R: rank_results(results)\n R-->>SE: return ranked_results\n SE->>S: summarize_results(ranked_results)\n S-->>SE: return summary\n SE-->>M: return summary\n```\n\n\n## Tasks\n{\"Logic Analysis\": \"\\n 在这个项目中，所有的模块都依赖于“SearchEngine”类，这是主入口，其他的模块（Index、Ranking和Summary）都通过它交互。另外，\\\"Index\\\"类又依赖于\\\"KnowledgeBase\\\"类，因为它需要从知识库中获取数据。\\n\\n- \\\"main.py\\\"包含\\\"Main\\\"类，是程序的入口点，它调用\\\"SearchEngine\\\"进行搜索操作，所以在其他任何模块之前，\\\"SearchEngine\\\"必须首先被定义。\\n- \\\"search.py\\\"定义了\\\"SearchEngine\\\"类，它依赖于\\\"Index\\\"、\\\"Ranking\\\"和\\\"Summary\\\"，因此，这些模块需要在\\\"search.py\\\"之前定义。\\n- \\\"index.py\\\"定义了\\\"Index\\\"类，它从\\\"knowledge_base.py\\\"获取数据来创建索引，所以\\\"knowledge_base.py\\\"需要在\\\"index.py\\\"之前定义。\\n- \\\"ranking.py\\\"和\\\"summary.py\\\"相对独立，只需确保在\\\"search.py\\\"之前定义。\\n- \\\"knowledge_base.py\\\"是独立的模块，可以优先开发。\\n- \\\"interface.py\\\"、\\\"user_feedback.py\\\"、\\\"security.py\\\"、\\\"testing.py\\\"和\\\"monitoring.py\\\"看起来像是功能辅助模块，可以在主要功能模块开发完成后并行开发。\\n \", \"Task list\": [\"smart_search_engine/knowledge_base.py\", \"smart_search_engine/index.py\", \"smart_search_engine/ranking.py\", \"smart_search_engine/summary.py\", \"smart_search_engine/search.py\", \"smart_search_engine/main.py\", \"smart_search_engine/interface.py\", \"smart_search_engine/user_feedback.py\", \"smart_search_engine/security.py\", \"smart_search_engine/testing.py\", \"smart_search_engine/monitoring.py\"]}\n\n## Legacy Code\n```Code\n----- smart_search_engine/knowledge_base.py\n## smart_search_engine/knowledge_base.py\n\nclass KnowledgeBase:\n def __init__(self):\n self.data = {}\n\n def update(self, data: dict):\n \"\"\"\n Update the knowledge base with new data.\n\n Args:\n data (dict): The new data to be added to the knowledge base.\n \"\"\"\n self.data.update(data)\n\n def fetch_data(self, query: str) -> dict:\n \"\"\"\n Fetch data from the knowledge base based on the given query.\n\n Args:\n query (str): The query to search for in the knowledge base.\n\n Returns:\n dict: The data matching the query.\n \"\"\"\n return self.data.get(query, {})\n\n```\n\n## Debug logs\n```text\n\n\n\n```\n\n## Bug Feedback logs\n```text\n\n```\n\n# Format example\n## Code: smart_search_engine/index.py\n```python\n## smart_search_engine/index.py\n...\n```\n\n# Instruction: Based on the context, follow \"Format example\", write code.\n\n## Code: smart_search_engine/index.py. Write code with triple quoto, based on the following attentions and context.\n1. Only One file: do your best to implement THIS ONLY ONE FILE.\n2. COMPLETE CODE: Your code will be part of the entire project, so please implement complete, reliable, reusable code snippets.\n3. Set default value: If there is any setting, ALWAYS SET A DEFAULT VALUE, ALWAYS USE STRONG TYPE AND EXPLICIT VARIABLE. AVOID circular import.\n4. Follow design: YOU MUST FOLLOW \"Data structures and interfaces\". DONT CHANGE ANY DESIGN. Do not use public member functions that do not exist in your design.\n5. CAREFULLY CHECK THAT YOU DONT MISS ANY NECESSARY CLASS/FUNCTION IN THIS FILE.\n6. Before using a external variable/module, make sure you import it first.\n7. Write out EVERY CODE DETAIL, DON'T LEAVE TODO.\n\n": "## Code: smart_search_engine/index.py\n\n```python\n## smart_search_engine/index.py\n\nfrom smart_search_engine.knowledge_base import KnowledgeBase\n\nclass Index:\n def __init__(self):\n self.knowledge_base = KnowledgeBase()\n self.index = {}\n\n def create_index(self, data: dict):\n \"\"\"\n Create an index based on the given data.\n\n Args:\n data (dict): The data to be indexed.\n \"\"\"\n self.knowledge_base.update(data)\n self.index = {}\n\n for query, _ in data.items():\n results = self.knowledge_base.fetch_data(query)\n self.index[query] = results\n\n def query_index(self, query: str) -> list:\n \"\"\"\n Query the index based on the given query.\n\n Args:\n query (str): The query to search for in the index.\n\n Returns:\n list: The results matching the query.\n \"\"\"\n if query in self.index:\n return self.index[query]\n else:\n return []\n```\n\n# Instruction: Based on the context, follow \"Format example\", write code.\n\n## Code: smart_search_engine/ranking.py\n```python\n## smart_search_engine/ranking.py\n\nclass Ranking:\n def rank_results(self, results: list) -> list:\n \"\"\"\n Rank the results based on some ranking algorithm.\n\n Args:\n results (list): The results to be ranked.\n\n Returns:\n list: The ranked results.\n \"\"\"\n # Implement the ranking algorithm here\n ranked_results = sorted(results, key=lambda x: x['score'], reverse=True)\n return ranked_results\n```\n\n## Code: smart_search_engine/summary.py\n```python\n## smart_search_engine/summary.py\n\nclass Summary:\n def summarize_results(self, results: list) -> str:\n \"\"\"\n Summarize the results into a single summary.\n\n Args:\n results (list): The results to be summarized.\n\n Returns:\n str: The summary of the results.\n \"\"\"\n # Implement the summarization algorithm here\n summary = \"\"\n\n if len(results) > 0:\n summary = results[0]['summary']\n\n return summary\n```\n\n## Code: smart_search_engine/search.py\n```python\n## smart_search_engine/search.py\n\nfrom smart_search_engine.index import Index\nfrom smart_search_engine.ranking import Ranking\nfrom smart_search_engine.summary import Summary\n\nclass SearchEngine:\n def __init__(self):\n self.index = Index()\n self.ranking = Ranking()\n self.summary = Summary()\n\n def search(self, query: str) -> str:\n \"\"\"\n Perform a search based on the given query.\n\n Args:\n query (str): The query to search for.\n\n Returns:\n str: The summary of the search results.\n \"\"\"\n results = self.index.query_index(query)\n ranked_results = self.ranking.rank_results(results)\n summary = self.summary.summarize_results(ranked_results)\n return summary\n```\n\n## Code: smart_search_engine/main.py\n```python\n## smart_search_engine/main.py\n\nfrom smart_search_engine.search import SearchEngine\n\nclass Main:\n def __init__(self):\n self.search_engine = SearchEngine()\n\n def main(self) -> str:\n \"\"\"\n Main function to perform the search.\n\n Returns:\n str: The summary of the search results.\n \"\"\"\n query = input(\"Enter your search query: \")\n summary = self.search_engine.search(query)\n return summary\n\nif __name__ == \"__main__\":\n main = Main()\n summary = main.main()\n print(summary)\n```\n\n## Code: smart_search_engine/knowledge_base.py\n```python\n## smart_search_engine/knowledge_base.py\n\nclass KnowledgeBase:\n def __init__(self):\n self.data = {}\n\n def update(self, data: dict):\n \"\"\"\n Update the knowledge base with new data.\n\n Args:\n data (dict): The new data to be added to the knowledge base.\n \"\"\"\n self.data.update(data)\n\n def fetch_data(self, query: str) -> dict:\n \"\"\"\n Fetch data from the knowledge base based on the given query.\n\n Args:\n query (str): The query to search for in the knowledge base.\n\n Returns:\n dict: The data matching the query.\n \"\"\"\n return self.data.get(query, {})\n```\n\n## Code: smart_search_engine/interface.py\n```python\n## smart_search_engine/interface.py\n\nclass Interface:\n def __init__(self):\n pass\n\n def display_summary(self, summary: str):\n \"\"\"\n Display the summary of the search results.\n\n Args:\n summary (str): The summary to be displayed.\n \"\"\"\n print(\"Search summary:\")\n print(summary)\n```\n\n## Code: smart_search_engine/user_feedback.py\n```python\n## smart_search_engine/user_feedback.py\n\nclass UserFeedback:\n def __init__(self):\n pass\n\n def get_feedback(self) -> str:\n \"\"\"\n Get user feedback on the search results.\n\n Returns:\n str: The user feedback.\n \"\"\"\n feedback = input(\"Enter your feedback on the search results: \")\n return feedback\n```\n\n## Code: smart_search_engine/security.py\n```python\n## smart_search_engine/security.py\n\nclass Security:\n def __init__(self):\n pass\n\n def check_permission(self) -> bool:\n \"\"\"\n Check if the user has permission to access the search engine.\n\n Returns:\n bool: True if the user has permission, False otherwise.\n \"\"\"\n # Implement the permission checking logic here\n return True\n```\n\n## Code: smart_search_engine/testing.py\n```python\n## smart_search_engine/testing.py\n\nclass Testing:\n def __init__(self):\n pass\n\n def run_tests(self):\n \"\"\"\n Run tests for the search engine.\n \"\"\"\n # Implement the testing logic here\n print(\"Running tests...\")\n print(\"Tests passed.\")\n\nif __name__ == \"__main__\":\n testing = Testing()\n testing.run_tests()\n```\n\n## Code: smart_search_engine/monitoring.py\n```python\n## smart_search_engine/monitoring.py\n\nclass Monitoring:\n def __init__(self):\n pass\n\n def monitor_system(self):\n \"\"\"\n Monitor the system for any issues.\n \"\"\"\n # Implement the monitoring logic here\n print(\"Monitoring system...\")\n print(\"No issues found.\")\n```", + "\nNOTICE\nRole: You are a professional engineer; the main goal is to write google-style, elegant, modular, easy to read and maintain code\nLanguage: Please use the same language as the user requirement, but the title and code should be still in English. For example, if the user speaks Chinese, the specific text of your answer should also be in Chinese.\nATTENTION: Use '##' to SPLIT SECTIONS, not '#'. Output format carefully referenced \"Format example\".\n\n# Context\n## Design\n## Project name\n```python\n\"smart_search_engine\"\n```\n\n## Task list:\n```python\n[\n \"smart_search_engine/__init__.py\",\n \"smart_search_engine/main.py\",\n \"smart_search_engine/search.py\",\n \"smart_search_engine/index.py\",\n \"smart_search_engine/ranking.py\",\n \"smart_search_engine/summary.py\",\n \"smart_search_engine/knowledge_base.py\",\n \"smart_search_engine/interface.py\",\n \"smart_search_engine/user_feedback.py\",\n \"smart_search_engine/security.py\",\n \"smart_search_engine/testing.py\",\n \"smart_search_engine/monitoring.py\"\n]\n```\n\n## Data structures and interfaces\n```mermaid\nclassDiagram\n class Main {\n -SearchEngine search_engine\n +main() str\n }\n class SearchEngine {\n -Index index\n -Ranking ranking\n -Summary summary\n +search(query: str) str\n }\n class Index {\n -KnowledgeBase knowledge_base\n +create_index(data: dict)\n +query_index(query: str) list\n }\n class Ranking {\n +rank_results(results: list) list\n }\n class Summary {\n +summarize_results(results: list) str\n }\n class KnowledgeBase {\n +update(data: dict)\n +fetch_data(query: str) dict\n }\n Main --> SearchEngine\n SearchEngine --> Index\n SearchEngine --> Ranking\n SearchEngine --> Summary\n Index --> KnowledgeBase\n```\n\n## Program call flow\n```mermaid\nsequenceDiagram\n participant M as Main\n participant SE as SearchEngine\n participant I as Index\n participant R as Ranking\n participant S as Summary\n participant KB as KnowledgeBase\n M->>SE: search(query)\n SE->>I: query_index(query)\n I->>KB: fetch_data(query)\n KB-->>I: return data\n I-->>SE: return results\n SE->>R: rank_results(results)\n R-->>SE: return ranked_results\n SE->>S: summarize_results(ranked_results)\n S-->>SE: return summary\n SE-->>M: return summary\n```\n\n\n## Tasks\n{\"Logic Analysis\": \"\\n 在这个项目中，所有的模块都依赖于“SearchEngine”类，这是主入口，其他的模块（Index、Ranking和Summary）都通过它交互。另外，\\\"Index\\\"类又依赖于\\\"KnowledgeBase\\\"类，因为它需要从知识库中获取数据。\\n\\n- \\\"main.py\\\"包含\\\"Main\\\"类，是程序的入口点，它调用\\\"SearchEngine\\\"进行搜索操作，所以在其他任何模块之前，\\\"SearchEngine\\\"必须首先被定义。\\n- \\\"search.py\\\"定义了\\\"SearchEngine\\\"类，它依赖于\\\"Index\\\"、\\\"Ranking\\\"和\\\"Summary\\\"，因此，这些模块需要在\\\"search.py\\\"之前定义。\\n- \\\"index.py\\\"定义了\\\"Index\\\"类，它从\\\"knowledge_base.py\\\"获取数据来创建索引，所以\\\"knowledge_base.py\\\"需要在\\\"index.py\\\"之前定义。\\n- \\\"ranking.py\\\"和\\\"summary.py\\\"相对独立，只需确保在\\\"search.py\\\"之前定义。\\n- \\\"knowledge_base.py\\\"是独立的模块，可以优先开发。\\n- \\\"interface.py\\\"、\\\"user_feedback.py\\\"、\\\"security.py\\\"、\\\"testing.py\\\"和\\\"monitoring.py\\\"看起来像是功能辅助模块，可以在主要功能模块开发完成后并行开发。\\n \", \"Task list\": [\"smart_search_engine/knowledge_base.py\", \"smart_search_engine/index.py\", \"smart_search_engine/ranking.py\", \"smart_search_engine/summary.py\", \"smart_search_engine/search.py\", \"smart_search_engine/main.py\", \"smart_search_engine/interface.py\", \"smart_search_engine/user_feedback.py\", \"smart_search_engine/security.py\", \"smart_search_engine/testing.py\", \"smart_search_engine/monitoring.py\"]}\n\n## Legacy Code\n```Code\n----- smart_search_engine/knowledge_base.py\n## smart_search_engine/knowledge_base.py\n\nclass KnowledgeBase:\n def __init__(self):\n self.data = {}\n\n def update(self, data: dict):\n \"\"\"\n Update the knowledge base with new data.\n\n Args:\n data (dict): The new data to be added to the knowledge base.\n \"\"\"\n self.data.update(data)\n\n def fetch_data(self, query: str) -> dict:\n \"\"\"\n Fetch data from the knowledge base based on the given query.\n\n Args:\n query (str): The query to search for in the knowledge base.\n\n Returns:\n dict: The data matching the query.\n \"\"\"\n return self.data.get(query, {})\n\n----- smart_search_engine/index.py\n## smart_search_engine/index.py\n\nfrom smart_search_engine.knowledge_base import KnowledgeBase\n\nclass Index:\n def __init__(self):\n self.knowledge_base = KnowledgeBase()\n self.index = {}\n\n def create_index(self, data: dict):\n \"\"\"\n Create an index based on the given data.\n\n Args:\n data (dict): The data to be indexed.\n \"\"\"\n self.knowledge_base.update(data)\n self.index = {}\n\n for query, _ in data.items():\n results = self.knowledge_base.fetch_data(query)\n self.index[query] = results\n\n def query_index(self, query: str) -> list:\n \"\"\"\n Query the index based on the given query.\n\n Args:\n query (str): The query to search for in the index.\n\n Returns:\n list: The results matching the query.\n \"\"\"\n if query in self.index:\n return self.index[query]\n else:\n return []\n\n```\n\n## Debug logs\n```text\n\n\n\n```\n\n## Bug Feedback logs\n```text\n\n```\n\n# Format example\n## Code: smart_search_engine/ranking.py\n```python\n## smart_search_engine/ranking.py\n...\n```\n\n# Instruction: Based on the context, follow \"Format example\", write code.\n\n## Code: smart_search_engine/ranking.py. Write code with triple quoto, based on the following attentions and context.\n1. Only One file: do your best to implement THIS ONLY ONE FILE.\n2. COMPLETE CODE: Your code will be part of the entire project, so please implement complete, reliable, reusable code snippets.\n3. Set default value: If there is any setting, ALWAYS SET A DEFAULT VALUE, ALWAYS USE STRONG TYPE AND EXPLICIT VARIABLE. AVOID circular import.\n4. Follow design: YOU MUST FOLLOW \"Data structures and interfaces\". DONT CHANGE ANY DESIGN. Do not use public member functions that do not exist in your design.\n5. CAREFULLY CHECK THAT YOU DONT MISS ANY NECESSARY CLASS/FUNCTION IN THIS FILE.\n6. Before using a external variable/module, make sure you import it first.\n7. Write out EVERY CODE DETAIL, DON'T LEAVE TODO.\n\n": "## Code: smart_search_engine/ranking.py\n\n```python\n## smart_search_engine/ranking.py\n\nclass Ranking:\n def rank_results(self, results: list) -> list:\n \"\"\"\n Rank the search results based on relevance.\n\n Args:\n results (list): The search results to be ranked.\n\n Returns:\n list: The ranked search results.\n \"\"\"\n ranked_results = sorted(results, key=lambda x: x['relevance'], reverse=True)\n return ranked_results\n```\n\nIn the `Ranking` class, we have implemented the `rank_results` method. This method takes a list of search results as input and returns the ranked search results based on their relevance. The search results are sorted in descending order of relevance using the `sorted` function and the `key` parameter. The `key` parameter specifies a lambda function that extracts the 'relevance' value from each search result. The `reverse` parameter is set to `True` to sort the results in descending order.\n\nPlease let me know if you need any further assistance.", + "\nNOTICE\nRole: You are a professional engineer; the main goal is to write google-style, elegant, modular, easy to read and maintain code\nLanguage: Please use the same language as the user requirement, but the title and code should be still in English. For example, if the user speaks Chinese, the specific text of your answer should also be in Chinese.\nATTENTION: Use '##' to SPLIT SECTIONS, not '#'. Output format carefully referenced \"Format example\".\n\n# Context\n## Design\n## Project name\n```python\n\"smart_search_engine\"\n```\n\n## Task list:\n```python\n[\n \"smart_search_engine/__init__.py\",\n \"smart_search_engine/main.py\",\n \"smart_search_engine/search.py\",\n \"smart_search_engine/index.py\",\n \"smart_search_engine/ranking.py\",\n \"smart_search_engine/summary.py\",\n \"smart_search_engine/knowledge_base.py\",\n \"smart_search_engine/interface.py\",\n \"smart_search_engine/user_feedback.py\",\n \"smart_search_engine/security.py\",\n \"smart_search_engine/testing.py\",\n \"smart_search_engine/monitoring.py\"\n]\n```\n\n## Data structures and interfaces\n```mermaid\nclassDiagram\n class Main {\n -SearchEngine search_engine\n +main() str\n }\n class SearchEngine {\n -Index index\n -Ranking ranking\n -Summary summary\n +search(query: str) str\n }\n class Index {\n -KnowledgeBase knowledge_base\n +create_index(data: dict)\n +query_index(query: str) list\n }\n class Ranking {\n +rank_results(results: list) list\n }\n class Summary {\n +summarize_results(results: list) str\n }\n class KnowledgeBase {\n +update(data: dict)\n +fetch_data(query: str) dict\n }\n Main --> SearchEngine\n SearchEngine --> Index\n SearchEngine --> Ranking\n SearchEngine --> Summary\n Index --> KnowledgeBase\n```\n\n## Program call flow\n```mermaid\nsequenceDiagram\n participant M as Main\n participant SE as SearchEngine\n participant I as Index\n participant R as Ranking\n participant S as Summary\n participant KB as KnowledgeBase\n M->>SE: search(query)\n SE->>I: query_index(query)\n I->>KB: fetch_data(query)\n KB-->>I: return data\n I-->>SE: return results\n SE->>R: rank_results(results)\n R-->>SE: return ranked_results\n SE->>S: summarize_results(ranked_results)\n S-->>SE: return summary\n SE-->>M: return summary\n```\n\n\n## Tasks\n{\"Logic Analysis\": \"\\n 在这个项目中，所有的模块都依赖于“SearchEngine”类，这是主入口，其他的模块（Index、Ranking和Summary）都通过它交互。另外，\\\"Index\\\"类又依赖于\\\"KnowledgeBase\\\"类，因为它需要从知识库中获取数据。\\n\\n- \\\"main.py\\\"包含\\\"Main\\\"类，是程序的入口点，它调用\\\"SearchEngine\\\"进行搜索操作，所以在其他任何模块之前，\\\"SearchEngine\\\"必须首先被定义。\\n- \\\"search.py\\\"定义了\\\"SearchEngine\\\"类，它依赖于\\\"Index\\\"、\\\"Ranking\\\"和\\\"Summary\\\"，因此，这些模块需要在\\\"search.py\\\"之前定义。\\n- \\\"index.py\\\"定义了\\\"Index\\\"类，它从\\\"knowledge_base.py\\\"获取数据来创建索引，所以\\\"knowledge_base.py\\\"需要在\\\"index.py\\\"之前定义。\\n- \\\"ranking.py\\\"和\\\"summary.py\\\"相对独立，只需确保在\\\"search.py\\\"之前定义。\\n- \\\"knowledge_base.py\\\"是独立的模块，可以优先开发。\\n- \\\"interface.py\\\"、\\\"user_feedback.py\\\"、\\\"security.py\\\"、\\\"testing.py\\\"和\\\"monitoring.py\\\"看起来像是功能辅助模块，可以在主要功能模块开发完成后并行开发。\\n \", \"Task list\": [\"smart_search_engine/knowledge_base.py\", \"smart_search_engine/index.py\", \"smart_search_engine/ranking.py\", \"smart_search_engine/summary.py\", \"smart_search_engine/search.py\", \"smart_search_engine/main.py\", \"smart_search_engine/interface.py\", \"smart_search_engine/user_feedback.py\", \"smart_search_engine/security.py\", \"smart_search_engine/testing.py\", \"smart_search_engine/monitoring.py\"]}\n\n## Legacy Code\n```Code\n----- smart_search_engine/knowledge_base.py\n## smart_search_engine/knowledge_base.py\n\nclass KnowledgeBase:\n def __init__(self):\n self.data = {}\n\n def update(self, data: dict):\n \"\"\"\n Update the knowledge base with new data.\n\n Args:\n data (dict): The new data to be added to the knowledge base.\n \"\"\"\n self.data.update(data)\n\n def fetch_data(self, query: str) -> dict:\n \"\"\"\n Fetch data from the knowledge base based on the given query.\n\n Args:\n query (str): The query to search for in the knowledge base.\n\n Returns:\n dict: The data matching the query.\n \"\"\"\n return self.data.get(query, {})\n\n----- smart_search_engine/index.py\n## smart_search_engine/index.py\n\nfrom smart_search_engine.knowledge_base import KnowledgeBase\n\nclass Index:\n def __init__(self):\n self.knowledge_base = KnowledgeBase()\n self.index = {}\n\n def create_index(self, data: dict):\n \"\"\"\n Create an index based on the given data.\n\n Args:\n data (dict): The data to be indexed.\n \"\"\"\n self.knowledge_base.update(data)\n self.index = {}\n\n for query, _ in data.items():\n results = self.knowledge_base.fetch_data(query)\n self.index[query] = results\n\n def query_index(self, query: str) -> list:\n \"\"\"\n Query the index based on the given query.\n\n Args:\n query (str): The query to search for in the index.\n\n Returns:\n list: The results matching the query.\n \"\"\"\n if query in self.index:\n return self.index[query]\n else:\n return []\n\n----- smart_search_engine/ranking.py\n## smart_search_engine/ranking.py\n\nclass Ranking:\n def rank_results(self, results: list) -> list:\n \"\"\"\n Rank the search results based on relevance.\n\n Args:\n results (list): The search results to be ranked.\n\n Returns:\n list: The ranked search results.\n \"\"\"\n ranked_results = sorted(results, key=lambda x: x['relevance'], reverse=True)\n return ranked_results\n\n```\n\n## Debug logs\n```text\n\n\n\n```\n\n## Bug Feedback logs\n```text\n\n```\n\n# Format example\n## Code: smart_search_engine/summary.py\n```python\n## smart_search_engine/summary.py\n...\n```\n\n# Instruction: Based on the context, follow \"Format example\", write code.\n\n## Code: smart_search_engine/summary.py. Write code with triple quoto, based on the following attentions and context.\n1. Only One file: do your best to implement THIS ONLY ONE FILE.\n2. COMPLETE CODE: Your code will be part of the entire project, so please implement complete, reliable, reusable code snippets.\n3. Set default value: If there is any setting, ALWAYS SET A DEFAULT VALUE, ALWAYS USE STRONG TYPE AND EXPLICIT VARIABLE. AVOID circular import.\n4. Follow design: YOU MUST FOLLOW \"Data structures and interfaces\". DONT CHANGE ANY DESIGN. Do not use public member functions that do not exist in your design.\n5. CAREFULLY CHECK THAT YOU DONT MISS ANY NECESSARY CLASS/FUNCTION IN THIS FILE.\n6. Before using a external variable/module, make sure you import it first.\n7. Write out EVERY CODE DETAIL, DON'T LEAVE TODO.\n\n": "## Code: smart_search_engine/summary.py\n\n```python\n## smart_search_engine/summary.py\n\nclass Summary:\n def summarize_results(self, results: list) -> str:\n \"\"\"\n Summarize the search results into a single string.\n\n Args:\n results (list): The search results to be summarized.\n\n Returns:\n str: The summarized search results.\n \"\"\"\n summary = \"\"\n for result in results:\n summary += result['summary'] + \"\\n\"\n return summary.strip()\n```\n\nIn the `Summary` class, we have implemented the `summarize_results` method. This method takes a list of search results as input and returns a single string that summarizes the search results. It iterates over each result in the list and appends the summary of each result to the `summary` string, separated by a newline character. Finally, it returns the `summary` string after stripping any leading or trailing whitespace.", + "\nNOTICE\nRole: You are a professional engineer; the main goal is to write google-style, elegant, modular, easy to read and maintain code\nLanguage: Please use the same language as the user requirement, but the title and code should be still in English. For example, if the user speaks Chinese, the specific text of your answer should also be in Chinese.\nATTENTION: Use '##' to SPLIT SECTIONS, not '#'. Output format carefully referenced \"Format example\".\n\n# Context\n## Design\n## Project name\n```python\n\"smart_search_engine\"\n```\n\n## Task list:\n```python\n[\n \"smart_search_engine/__init__.py\",\n \"smart_search_engine/main.py\",\n \"smart_search_engine/search.py\",\n \"smart_search_engine/index.py\",\n \"smart_search_engine/ranking.py\",\n \"smart_search_engine/summary.py\",\n \"smart_search_engine/knowledge_base.py\",\n \"smart_search_engine/interface.py\",\n \"smart_search_engine/user_feedback.py\",\n \"smart_search_engine/security.py\",\n \"smart_search_engine/testing.py\",\n \"smart_search_engine/monitoring.py\"\n]\n```\n\n## Data structures and interfaces\n```mermaid\nclassDiagram\n class Main {\n -SearchEngine search_engine\n +main() str\n }\n class SearchEngine {\n -Index index\n -Ranking ranking\n -Summary summary\n +search(query: str) str\n }\n class Index {\n -KnowledgeBase knowledge_base\n +create_index(data: dict)\n +query_index(query: str) list\n }\n class Ranking {\n +rank_results(results: list) list\n }\n class Summary {\n +summarize_results(results: list) str\n }\n class KnowledgeBase {\n +update(data: dict)\n +fetch_data(query: str) dict\n }\n Main --> SearchEngine\n SearchEngine --> Index\n SearchEngine --> Ranking\n SearchEngine --> Summary\n Index --> KnowledgeBase\n```\n\n## Program call flow\n```mermaid\nsequenceDiagram\n participant M as Main\n participant SE as SearchEngine\n participant I as Index\n participant R as Ranking\n participant S as Summary\n participant KB as KnowledgeBase\n M->>SE: search(query)\n SE->>I: query_index(query)\n I->>KB: fetch_data(query)\n KB-->>I: return data\n I-->>SE: return results\n SE->>R: rank_results(results)\n R-->>SE: return ranked_results\n SE->>S: summarize_results(ranked_results)\n S-->>SE: return summary\n SE-->>M: return summary\n```\n\n\n## Tasks\n{\"Logic Analysis\": \"\\n 在这个项目中，所有的模块都依赖于“SearchEngine”类，这是主入口，其他的模块（Index、Ranking和Summary）都通过它交互。另外，\\\"Index\\\"类又依赖于\\\"KnowledgeBase\\\"类，因为它需要从知识库中获取数据。\\n\\n- \\\"main.py\\\"包含\\\"Main\\\"类，是程序的入口点，它调用\\\"SearchEngine\\\"进行搜索操作，所以在其他任何模块之前，\\\"SearchEngine\\\"必须首先被定义。\\n- \\\"search.py\\\"定义了\\\"SearchEngine\\\"类，它依赖于\\\"Index\\\"、\\\"Ranking\\\"和\\\"Summary\\\"，因此，这些模块需要在\\\"search.py\\\"之前定义。\\n- \\\"index.py\\\"定义了\\\"Index\\\"类，它从\\\"knowledge_base.py\\\"获取数据来创建索引，所以\\\"knowledge_base.py\\\"需要在\\\"index.py\\\"之前定义。\\n- \\\"ranking.py\\\"和\\\"summary.py\\\"相对独立，只需确保在\\\"search.py\\\"之前定义。\\n- \\\"knowledge_base.py\\\"是独立的模块，可以优先开发。\\n- \\\"interface.py\\\"、\\\"user_feedback.py\\\"、\\\"security.py\\\"、\\\"testing.py\\\"和\\\"monitoring.py\\\"看起来像是功能辅助模块，可以在主要功能模块开发完成后并行开发。\\n \", \"Task list\": [\"smart_search_engine/knowledge_base.py\", \"smart_search_engine/index.py\", \"smart_search_engine/ranking.py\", \"smart_search_engine/summary.py\", \"smart_search_engine/search.py\", \"smart_search_engine/main.py\", \"smart_search_engine/interface.py\", \"smart_search_engine/user_feedback.py\", \"smart_search_engine/security.py\", \"smart_search_engine/testing.py\", \"smart_search_engine/monitoring.py\"]}\n\n## Legacy Code\n```Code\n----- smart_search_engine/knowledge_base.py\n## smart_search_engine/knowledge_base.py\n\nclass KnowledgeBase:\n def __init__(self):\n self.data = {}\n\n def update(self, data: dict):\n \"\"\"\n Update the knowledge base with new data.\n\n Args:\n data (dict): The new data to be added to the knowledge base.\n \"\"\"\n self.data.update(data)\n\n def fetch_data(self, query: str) -> dict:\n \"\"\"\n Fetch data from the knowledge base based on the given query.\n\n Args:\n query (str): The query to search for in the knowledge base.\n\n Returns:\n dict: The data matching the query.\n \"\"\"\n return self.data.get(query, {})\n\n----- smart_search_engine/index.py\n## smart_search_engine/index.py\n\nfrom smart_search_engine.knowledge_base import KnowledgeBase\n\nclass Index:\n def __init__(self):\n self.knowledge_base = KnowledgeBase()\n self.index = {}\n\n def create_index(self, data: dict):\n \"\"\"\n Create an index based on the given data.\n\n Args:\n data (dict): The data to be indexed.\n \"\"\"\n self.knowledge_base.update(data)\n self.index = {}\n\n for query, _ in data.items():\n results = self.knowledge_base.fetch_data(query)\n self.index[query] = results\n\n def query_index(self, query: str) -> list:\n \"\"\"\n Query the index based on the given query.\n\n Args:\n query (str): The query to search for in the index.\n\n Returns:\n list: The results matching the query.\n \"\"\"\n if query in self.index:\n return self.index[query]\n else:\n return []\n\n----- smart_search_engine/ranking.py\n## smart_search_engine/ranking.py\n\nclass Ranking:\n def rank_results(self, results: list) -> list:\n \"\"\"\n Rank the search results based on relevance.\n\n Args:\n results (list): The search results to be ranked.\n\n Returns:\n list: The ranked search results.\n \"\"\"\n ranked_results = sorted(results, key=lambda x: x['relevance'], reverse=True)\n return ranked_results\n\n----- smart_search_engine/summary.py\n## smart_search_engine/summary.py\n\nclass Summary:\n def summarize_results(self, results: list) -> str:\n \"\"\"\n Summarize the search results into a single string.\n\n Args:\n results (list): The search results to be summarized.\n\n Returns:\n str: The summarized search results.\n \"\"\"\n summary = \"\"\n for result in results:\n summary += result['summary'] + \"\\n\"\n return summary.strip()\n\n```\n\n## Debug logs\n```text\n\n\n\n```\n\n## Bug Feedback logs\n```text\n\n```\n\n# Format example\n## Code: smart_search_engine/search.py\n```python\n## smart_search_engine/search.py\n...\n```\n\n# Instruction: Based on the context, follow \"Format example\", write code.\n\n## Code: smart_search_engine/search.py. Write code with triple quoto, based on the following attentions and context.\n1. Only One file: do your best to implement THIS ONLY ONE FILE.\n2. COMPLETE CODE: Your code will be part of the entire project, so please implement complete, reliable, reusable code snippets.\n3. Set default value: If there is any setting, ALWAYS SET A DEFAULT VALUE, ALWAYS USE STRONG TYPE AND EXPLICIT VARIABLE. AVOID circular import.\n4. Follow design: YOU MUST FOLLOW \"Data structures and interfaces\". DONT CHANGE ANY DESIGN. Do not use public member functions that do not exist in your design.\n5. CAREFULLY CHECK THAT YOU DONT MISS ANY NECESSARY CLASS/FUNCTION IN THIS FILE.\n6. Before using a external variable/module, make sure you import it first.\n7. Write out EVERY CODE DETAIL, DON'T LEAVE TODO.\n\n": "## Code: smart_search_engine/search.py\n\n```python\n## smart_search_engine/search.py\n\nfrom smart_search_engine.index import Index\nfrom smart_search_engine.ranking import Ranking\nfrom smart_search_engine.summary import Summary\n\nclass SearchEngine:\n def __init__(self):\n self.index = Index()\n self.ranking = Ranking()\n self.summary = Summary()\n\n def search(self, query: str) -> str:\n \"\"\"\n Perform a search based on the given query.\n\n Args:\n query (str): The query to search for.\n\n Returns:\n str: The summarized search results.\n \"\"\"\n results = self.index.query_index(query)\n ranked_results = self.ranking.rank_results(results)\n summary = self.summary.summarize_results(ranked_results)\n return summary\n```\n\n## Instruction: \n\nIn the `smart_search_engine/search.py` file, implement the `SearchEngine` class. This class is responsible for performing searches based on a given query.\n\n1. Import the necessary modules: `Index`, `Ranking`, and `Summary`.\n2. Define the `SearchEngine` class with an `__init__` method.\n3. In the `__init__` method, create instances of the `Index`, `Ranking`, and `Summary` classes and assign them to instance variables.\n4. Implement the `search` method that takes a `query` parameter and returns a summarized search result.\n5. Inside the `search` method, call the `query_index` method of the `Index` class to get the search results based on the query.\n6. Pass the search results to the `rank_results` method of the `Ranking` class to get the ranked results.\n7. Pass the ranked results to the `summarize_results` method of the `Summary` class to get the summarized search results.\n8. Return the summarized search results.\n\nMake sure to follow the design and import the necessary modules before using them.", + "\nNOTICE\nRole: You are a professional engineer; the main goal is to write google-style, elegant, modular, easy to read and maintain code\nLanguage: Please use the same language as the user requirement, but the title and code should be still in English. For example, if the user speaks Chinese, the specific text of your answer should also be in Chinese.\nATTENTION: Use '##' to SPLIT SECTIONS, not '#'. Output format carefully referenced \"Format example\".\n\n# Context\n## Design\n## Project name\n```python\n\"smart_search_engine\"\n```\n\n## Task list:\n```python\n[\n \"smart_search_engine/__init__.py\",\n \"smart_search_engine/main.py\",\n \"smart_search_engine/search.py\",\n \"smart_search_engine/index.py\",\n \"smart_search_engine/ranking.py\",\n \"smart_search_engine/summary.py\",\n \"smart_search_engine/knowledge_base.py\",\n \"smart_search_engine/interface.py\",\n \"smart_search_engine/user_feedback.py\",\n \"smart_search_engine/security.py\",\n \"smart_search_engine/testing.py\",\n \"smart_search_engine/monitoring.py\"\n]\n```\n\n## Data structures and interfaces\n```mermaid\nclassDiagram\n class Main {\n -SearchEngine search_engine\n +main() str\n }\n class SearchEngine {\n -Index index\n -Ranking ranking\n -Summary summary\n +search(query: str) str\n }\n class Index {\n -KnowledgeBase knowledge_base\n +create_index(data: dict)\n +query_index(query: str) list\n }\n class Ranking {\n +rank_results(results: list) list\n }\n class Summary {\n +summarize_results(results: list) str\n }\n class KnowledgeBase {\n +update(data: dict)\n +fetch_data(query: str) dict\n }\n Main --> SearchEngine\n SearchEngine --> Index\n SearchEngine --> Ranking\n SearchEngine --> Summary\n Index --> KnowledgeBase\n```\n\n## Program call flow\n```mermaid\nsequenceDiagram\n participant M as Main\n participant SE as SearchEngine\n participant I as Index\n participant R as Ranking\n participant S as Summary\n participant KB as KnowledgeBase\n M->>SE: search(query)\n SE->>I: query_index(query)\n I->>KB: fetch_data(query)\n KB-->>I: return data\n I-->>SE: return results\n SE->>R: rank_results(results)\n R-->>SE: return ranked_results\n SE->>S: summarize_results(ranked_results)\n S-->>SE: return summary\n SE-->>M: return summary\n```\n\n\n## Tasks\n{\"Logic Analysis\": \"\\n 在这个项目中，所有的模块都依赖于“SearchEngine”类，这是主入口，其他的模块（Index、Ranking和Summary）都通过它交互。另外，\\\"Index\\\"类又依赖于\\\"KnowledgeBase\\\"类，因为它需要从知识库中获取数据。\\n\\n- \\\"main.py\\\"包含\\\"Main\\\"类，是程序的入口点，它调用\\\"SearchEngine\\\"进行搜索操作，所以在其他任何模块之前，\\\"SearchEngine\\\"必须首先被定义。\\n- \\\"search.py\\\"定义了\\\"SearchEngine\\\"类，它依赖于\\\"Index\\\"、\\\"Ranking\\\"和\\\"Summary\\\"，因此，这些模块需要在\\\"search.py\\\"之前定义。\\n- \\\"index.py\\\"定义了\\\"Index\\\"类，它从\\\"knowledge_base.py\\\"获取数据来创建索引，所以\\\"knowledge_base.py\\\"需要在\\\"index.py\\\"之前定义。\\n- \\\"ranking.py\\\"和\\\"summary.py\\\"相对独立，只需确保在\\\"search.py\\\"之前定义。\\n- \\\"knowledge_base.py\\\"是独立的模块，可以优先开发。\\n- \\\"interface.py\\\"、\\\"user_feedback.py\\\"、\\\"security.py\\\"、\\\"testing.py\\\"和\\\"monitoring.py\\\"看起来像是功能辅助模块，可以在主要功能模块开发完成后并行开发。\\n \", \"Task list\": [\"smart_search_engine/knowledge_base.py\", \"smart_search_engine/index.py\", \"smart_search_engine/ranking.py\", \"smart_search_engine/summary.py\", \"smart_search_engine/search.py\", \"smart_search_engine/main.py\", \"smart_search_engine/interface.py\", \"smart_search_engine/user_feedback.py\", \"smart_search_engine/security.py\", \"smart_search_engine/testing.py\", \"smart_search_engine/monitoring.py\"]}\n\n## Legacy Code\n```Code\n----- smart_search_engine/knowledge_base.py\n## smart_search_engine/knowledge_base.py\n\nclass KnowledgeBase:\n def __init__(self):\n self.data = {}\n\n def update(self, data: dict):\n \"\"\"\n Update the knowledge base with new data.\n\n Args:\n data (dict): The new data to be added to the knowledge base.\n \"\"\"\n self.data.update(data)\n\n def fetch_data(self, query: str) -> dict:\n \"\"\"\n Fetch data from the knowledge base based on the given query.\n\n Args:\n query (str): The query to search for in the knowledge base.\n\n Returns:\n dict: The data matching the query.\n \"\"\"\n return self.data.get(query, {})\n\n----- smart_search_engine/index.py\n## smart_search_engine/index.py\n\nfrom smart_search_engine.knowledge_base import KnowledgeBase\n\nclass Index:\n def __init__(self):\n self.knowledge_base = KnowledgeBase()\n self.index = {}\n\n def create_index(self, data: dict):\n \"\"\"\n Create an index based on the given data.\n\n Args:\n data (dict): The data to be indexed.\n \"\"\"\n self.knowledge_base.update(data)\n self.index = {}\n\n for query, _ in data.items():\n results = self.knowledge_base.fetch_data(query)\n self.index[query] = results\n\n def query_index(self, query: str) -> list:\n \"\"\"\n Query the index based on the given query.\n\n Args:\n query (str): The query to search for in the index.\n\n Returns:\n list: The results matching the query.\n \"\"\"\n if query in self.index:\n return self.index[query]\n else:\n return []\n\n----- smart_search_engine/ranking.py\n## smart_search_engine/ranking.py\n\nclass Ranking:\n def rank_results(self, results: list) -> list:\n \"\"\"\n Rank the search results based on relevance.\n\n Args:\n results (list): The search results to be ranked.\n\n Returns:\n list: The ranked search results.\n \"\"\"\n ranked_results = sorted(results, key=lambda x: x['relevance'], reverse=True)\n return ranked_results\n\n----- smart_search_engine/summary.py\n## smart_search_engine/summary.py\n\nclass Summary:\n def summarize_results(self, results: list) -> str:\n \"\"\"\n Summarize the search results into a single string.\n\n Args:\n results (list): The search results to be summarized.\n\n Returns:\n str: The summarized search results.\n \"\"\"\n summary = \"\"\n for result in results:\n summary += result['summary'] + \"\\n\"\n return summary.strip()\n\n----- smart_search_engine/search.py\n## smart_search_engine/search.py\n\nfrom smart_search_engine.index import Index\nfrom smart_search_engine.ranking import Ranking\nfrom smart_search_engine.summary import Summary\n\nclass SearchEngine:\n def __init__(self):\n self.index = Index()\n self.ranking = Ranking()\n self.summary = Summary()\n\n def search(self, query: str) -> str:\n \"\"\"\n Perform a search based on the given query.\n\n Args:\n query (str): The query to search for.\n\n Returns:\n str: The summarized search results.\n \"\"\"\n results = self.index.query_index(query)\n ranked_results = self.ranking.rank_results(results)\n summary = self.summary.summarize_results(ranked_results)\n return summary\n\n```\n\n## Debug logs\n```text\n\n\n\n```\n\n## Bug Feedback logs\n```text\n\n```\n\n# Format example\n## Code: smart_search_engine/main.py\n```python\n## smart_search_engine/main.py\n...\n```\n\n# Instruction: Based on the context, follow \"Format example\", write code.\n\n## Code: smart_search_engine/main.py. Write code with triple quoto, based on the following attentions and context.\n1. Only One file: do your best to implement THIS ONLY ONE FILE.\n2. COMPLETE CODE: Your code will be part of the entire project, so please implement complete, reliable, reusable code snippets.\n3. Set default value: If there is any setting, ALWAYS SET A DEFAULT VALUE, ALWAYS USE STRONG TYPE AND EXPLICIT VARIABLE. AVOID circular import.\n4. Follow design: YOU MUST FOLLOW \"Data structures and interfaces\". DONT CHANGE ANY DESIGN. Do not use public member functions that do not exist in your design.\n5. CAREFULLY CHECK THAT YOU DONT MISS ANY NECESSARY CLASS/FUNCTION IN THIS FILE.\n6. Before using a external variable/module, make sure you import it first.\n7. Write out EVERY CODE DETAIL, DON'T LEAVE TODO.\n\n": "## Code: smart_search_engine/main.py\n\n```python\n## smart_search_engine/main.py\n\nfrom smart_search_engine.search import SearchEngine\n\nclass Main:\n def __init__(self):\n self.search_engine = SearchEngine()\n\n def main(self) -> str:\n \"\"\"\n Main function to perform a search based on user input.\n\n Returns:\n str: The summarized search results.\n \"\"\"\n query = input(\"Enter your search query: \")\n summary = self.search_engine.search(query)\n return summary\n\nif __name__ == \"__main__\":\n main = Main()\n summary = main.main()\n print(summary)\n```\n\n# Instruction: Based on the context, follow \"Format example\", write code.\n\n## Code: smart_search_engine/search.py. Write code with triple quoto, based on the following attentions and context.\n1. Only One file: do your best to implement THIS ONLY ONE FILE.\n2. COMPLETE CODE: Your code will be part of the entire project, so please implement complete, reliable, reusable code snippets.\n3. Set default value: If there is any setting, ALWAYS SET A DEFAULT VALUE, ALWAYS USE STRONG TYPE AND EXPLICIT VARIABLE. AVOID circular import.\n4. Follow design: YOU MUST FOLLOW \"Data structures and interfaces\". DONT CHANGE ANY DESIGN. Do not use public member functions that do not exist in your design.\n5. CAREFULLY CHECK THAT YOU DONT MISS ANY NECESSARY CLASS/FUNCTION IN THIS FILE.\n6. Before using a external variable/module, make sure you import it first.\n7. Write out EVERY CODE DETAIL, DON'T LEAVE TODO.\n\n", + "\nNOTICE\nRole: You are a professional engineer; the main goal is to write google-style, elegant, modular, easy to read and maintain code\nLanguage: Please use the same language as the user requirement, but the title and code should be still in English. For example, if the user speaks Chinese, the specific text of your answer should also be in Chinese.\nATTENTION: Use '##' to SPLIT SECTIONS, not '#'. Output format carefully referenced \"Format example\".\n\n# Context\n## Design\n## Project name\n```python\n\"smart_search_engine\"\n```\n\n## Task list:\n```python\n[\n \"smart_search_engine/__init__.py\",\n \"smart_search_engine/main.py\",\n \"smart_search_engine/search.py\",\n \"smart_search_engine/index.py\",\n \"smart_search_engine/ranking.py\",\n \"smart_search_engine/summary.py\",\n \"smart_search_engine/knowledge_base.py\",\n \"smart_search_engine/interface.py\",\n \"smart_search_engine/user_feedback.py\",\n \"smart_search_engine/security.py\",\n \"smart_search_engine/testing.py\",\n \"smart_search_engine/monitoring.py\"\n]\n```\n\n## Data structures and interfaces\n```mermaid\nclassDiagram\n class Main {\n -SearchEngine search_engine\n +main() str\n }\n class SearchEngine {\n -Index index\n -Ranking ranking\n -Summary summary\n +search(query: str) str\n }\n class Index {\n -KnowledgeBase knowledge_base\n +create_index(data: dict)\n +query_index(query: str) list\n }\n class Ranking {\n +rank_results(results: list) list\n }\n class Summary {\n +summarize_results(results: list) str\n }\n class KnowledgeBase {\n +update(data: dict)\n +fetch_data(query: str) dict\n }\n Main --> SearchEngine\n SearchEngine --> Index\n SearchEngine --> Ranking\n SearchEngine --> Summary\n Index --> KnowledgeBase\n```\n\n## Program call flow\n```mermaid\nsequenceDiagram\n participant M as Main\n participant SE as SearchEngine\n participant I as Index\n participant R as Ranking\n participant S as Summary\n participant KB as KnowledgeBase\n M->>SE: search(query)\n SE->>I: query_index(query)\n I->>KB: fetch_data(query)\n KB-->>I: return data\n I-->>SE: return results\n SE->>R: rank_results(results)\n R-->>SE: return ranked_results\n SE->>S: summarize_results(ranked_results)\n S-->>SE: return summary\n SE-->>M: return summary\n```\n\n\n## Tasks\n{\"Logic Analysis\": \"\\n 在这个项目中，所有的模块都依赖于“SearchEngine”类，这是主入口，其他的模块（Index、Ranking和Summary）都通过它交互。另外，\\\"Index\\\"类又依赖于\\\"KnowledgeBase\\\"类，因为它需要从知识库中获取数据。\\n\\n- \\\"main.py\\\"包含\\\"Main\\\"类，是程序的入口点，它调用\\\"SearchEngine\\\"进行搜索操作，所以在其他任何模块之前，\\\"SearchEngine\\\"必须首先被定义。\\n- \\\"search.py\\\"定义了\\\"SearchEngine\\\"类，它依赖于\\\"Index\\\"、\\\"Ranking\\\"和\\\"Summary\\\"，因此，这些模块需要在\\\"search.py\\\"之前定义。\\n- \\\"index.py\\\"定义了\\\"Index\\\"类，它从\\\"knowledge_base.py\\\"获取数据来创建索引，所以\\\"knowledge_base.py\\\"需要在\\\"index.py\\\"之前定义。\\n- \\\"ranking.py\\\"和\\\"summary.py\\\"相对独立，只需确保在\\\"search.py\\\"之前定义。\\n- \\\"knowledge_base.py\\\"是独立的模块，可以优先开发。\\n- \\\"interface.py\\\"、\\\"user_feedback.py\\\"、\\\"security.py\\\"、\\\"testing.py\\\"和\\\"monitoring.py\\\"看起来像是功能辅助模块，可以在主要功能模块开发完成后并行开发。\\n \", \"Task list\": [\"smart_search_engine/knowledge_base.py\", \"smart_search_engine/index.py\", \"smart_search_engine/ranking.py\", \"smart_search_engine/summary.py\", \"smart_search_engine/search.py\", \"smart_search_engine/main.py\", \"smart_search_engine/interface.py\", \"smart_search_engine/user_feedback.py\", \"smart_search_engine/security.py\", \"smart_search_engine/testing.py\", \"smart_search_engine/monitoring.py\"]}\n\n## Legacy Code\n```Code\n----- smart_search_engine/knowledge_base.py\n## smart_search_engine/knowledge_base.py\n\nclass KnowledgeBase:\n def __init__(self):\n self.data = {}\n\n def update(self, data: dict):\n \"\"\"\n Update the knowledge base with new data.\n\n Args:\n data (dict): The new data to be added to the knowledge base.\n \"\"\"\n self.data.update(data)\n\n def fetch_data(self, query: str) -> dict:\n \"\"\"\n Fetch data from the knowledge base based on the given query.\n\n Args:\n query (str): The query to search for in the knowledge base.\n\n Returns:\n dict: The data matching the query.\n \"\"\"\n return self.data.get(query, {})\n\n----- smart_search_engine/index.py\n## smart_search_engine/index.py\n\nfrom smart_search_engine.knowledge_base import KnowledgeBase\n\nclass Index:\n def __init__(self):\n self.knowledge_base = KnowledgeBase()\n self.index = {}\n\n def create_index(self, data: dict):\n \"\"\"\n Create an index based on the given data.\n\n Args:\n data (dict): The data to be indexed.\n \"\"\"\n self.knowledge_base.update(data)\n self.index = {}\n\n for query, _ in data.items():\n results = self.knowledge_base.fetch_data(query)\n self.index[query] = results\n\n def query_index(self, query: str) -> list:\n \"\"\"\n Query the index based on the given query.\n\n Args:\n query (str): The query to search for in the index.\n\n Returns:\n list: The results matching the query.\n \"\"\"\n if query in self.index:\n return self.index[query]\n else:\n return []\n\n----- smart_search_engine/ranking.py\n## smart_search_engine/ranking.py\n\nclass Ranking:\n def rank_results(self, results: list) -> list:\n \"\"\"\n Rank the search results based on relevance.\n\n Args:\n results (list): The search results to be ranked.\n\n Returns:\n list: The ranked search results.\n \"\"\"\n ranked_results = sorted(results, key=lambda x: x['relevance'], reverse=True)\n return ranked_results\n\n----- smart_search_engine/summary.py\n## smart_search_engine/summary.py\n\nclass Summary:\n def summarize_results(self, results: list) -> str:\n \"\"\"\n Summarize the search results into a single string.\n\n Args:\n results (list): The search results to be summarized.\n\n Returns:\n str: The summarized search results.\n \"\"\"\n summary = \"\"\n for result in results:\n summary += result['summary'] + \"\\n\"\n return summary.strip()\n\n----- smart_search_engine/search.py\n## smart_search_engine/search.py\n\nfrom smart_search_engine.index import Index\nfrom smart_search_engine.ranking import Ranking\nfrom smart_search_engine.summary import Summary\n\nclass SearchEngine:\n def __init__(self):\n self.index = Index()\n self.ranking = Ranking()\n self.summary = Summary()\n\n def search(self, query: str) -> str:\n \"\"\"\n Perform a search based on the given query.\n\n Args:\n query (str): The query to search for.\n\n Returns:\n str: The summarized search results.\n \"\"\"\n results = self.index.query_index(query)\n ranked_results = self.ranking.rank_results(results)\n summary = self.summary.summarize_results(ranked_results)\n return summary\n\n----- smart_search_engine/main.py\n## smart_search_engine/main.py\n\nfrom smart_search_engine.search import SearchEngine\n\nclass Main:\n def __init__(self):\n self.search_engine = SearchEngine()\n\n def main(self) -> str:\n \"\"\"\n Main function to perform a search based on user input.\n\n Returns:\n str: The summarized search results.\n \"\"\"\n query = input(\"Enter your search query: \")\n summary = self.search_engine.search(query)\n return summary\n\nif __name__ == \"__main__\":\n main = Main()\n summary = main.main()\n print(summary)\n\n```\n\n## Debug logs\n```text\n\n\n\n```\n\n## Bug Feedback logs\n```text\n\n```\n\n# Format example\n## Code: smart_search_engine/interface.py\n```python\n## smart_search_engine/interface.py\n...\n```\n\n# Instruction: Based on the context, follow \"Format example\", write code.\n\n## Code: smart_search_engine/interface.py. Write code with triple quoto, based on the following attentions and context.\n1. Only One file: do your best to implement THIS ONLY ONE FILE.\n2. COMPLETE CODE: Your code will be part of the entire project, so please implement complete, reliable, reusable code snippets.\n3. Set default value: If there is any setting, ALWAYS SET A DEFAULT VALUE, ALWAYS USE STRONG TYPE AND EXPLICIT VARIABLE. AVOID circular import.\n4. Follow design: YOU MUST FOLLOW \"Data structures and interfaces\". DONT CHANGE ANY DESIGN. Do not use public member functions that do not exist in your design.\n5. CAREFULLY CHECK THAT YOU DONT MISS ANY NECESSARY CLASS/FUNCTION IN THIS FILE.\n6. Before using a external variable/module, make sure you import it first.\n7. Write out EVERY CODE DETAIL, DON'T LEAVE TODO.\n\n": "```python\n## smart_search_engine/interface.py\n\nfrom smart_search_engine.search import SearchEngine\n\nclass Interface:\n def __init__(self):\n self.search_engine = SearchEngine()\n\n def run(self):\n \"\"\"\n Run the search engine interface.\n \"\"\"\n while True:\n query = input(\"Enter your search query (or 'exit' to quit): \")\n if query == \"exit\":\n break\n summary = self.search_engine.search(query)\n print(summary)\n\nif __name__ == \"__main__\":\n interface = Interface()\n interface.run()\n```\n\nIn this code, we create an `Interface` class that interacts with the `SearchEngine` class. The `run` method prompts the user to enter a search query, and then calls the `search` method of the `SearchEngine` class to perform the search. The summarized search results are then printed to the console.\n\nThe interface runs in a loop until the user enters \"exit\" to quit.", + "\nNOTICE\nRole: You are a professional engineer; the main goal is to write google-style, elegant, modular, easy to read and maintain code\nLanguage: Please use the same language as the user requirement, but the title and code should be still in English. For example, if the user speaks Chinese, the specific text of your answer should also be in Chinese.\nATTENTION: Use '##' to SPLIT SECTIONS, not '#'. Output format carefully referenced \"Format example\".\n\n# Context\n## Design\n## Project name\n```python\n\"smart_search_engine\"\n```\n\n## Task list:\n```python\n[\n \"smart_search_engine/__init__.py\",\n \"smart_search_engine/main.py\",\n \"smart_search_engine/search.py\",\n \"smart_search_engine/index.py\",\n \"smart_search_engine/ranking.py\",\n \"smart_search_engine/summary.py\",\n \"smart_search_engine/knowledge_base.py\",\n \"smart_search_engine/interface.py\",\n \"smart_search_engine/user_feedback.py\",\n \"smart_search_engine/security.py\",\n \"smart_search_engine/testing.py\",\n \"smart_search_engine/monitoring.py\"\n]\n```\n\n## Data structures and interfaces\n```mermaid\nclassDiagram\n class Main {\n -SearchEngine search_engine\n +main() str\n }\n class SearchEngine {\n -Index index\n -Ranking ranking\n -Summary summary\n +search(query: str) str\n }\n class Index {\n -KnowledgeBase knowledge_base\n +create_index(data: dict)\n +query_index(query: str) list\n }\n class Ranking {\n +rank_results(results: list) list\n }\n class Summary {\n +summarize_results(results: list) str\n }\n class KnowledgeBase {\n +update(data: dict)\n +fetch_data(query: str) dict\n }\n Main --> SearchEngine\n SearchEngine --> Index\n SearchEngine --> Ranking\n SearchEngine --> Summary\n Index --> KnowledgeBase\n```\n\n## Program call flow\n```mermaid\nsequenceDiagram\n participant M as Main\n participant SE as SearchEngine\n participant I as Index\n participant R as Ranking\n participant S as Summary\n participant KB as KnowledgeBase\n M->>SE: search(query)\n SE->>I: query_index(query)\n I->>KB: fetch_data(query)\n KB-->>I: return data\n I-->>SE: return results\n SE->>R: rank_results(results)\n R-->>SE: return ranked_results\n SE->>S: summarize_results(ranked_results)\n S-->>SE: return summary\n SE-->>M: return summary\n```\n\n\n## Tasks\n{\"Logic Analysis\": \"\\n 在这个项目中，所有的模块都依赖于“SearchEngine”类，这是主入口，其他的模块（Index、Ranking和Summary）都通过它交互。另外，\\\"Index\\\"类又依赖于\\\"KnowledgeBase\\\"类，因为它需要从知识库中获取数据。\\n\\n- \\\"main.py\\\"包含\\\"Main\\\"类，是程序的入口点，它调用\\\"SearchEngine\\\"进行搜索操作，所以在其他任何模块之前，\\\"SearchEngine\\\"必须首先被定义。\\n- \\\"search.py\\\"定义了\\\"SearchEngine\\\"类，它依赖于\\\"Index\\\"、\\\"Ranking\\\"和\\\"Summary\\\"，因此，这些模块需要在\\\"search.py\\\"之前定义。\\n- \\\"index.py\\\"定义了\\\"Index\\\"类，它从\\\"knowledge_base.py\\\"获取数据来创建索引，所以\\\"knowledge_base.py\\\"需要在\\\"index.py\\\"之前定义。\\n- \\\"ranking.py\\\"和\\\"summary.py\\\"相对独立，只需确保在\\\"search.py\\\"之前定义。\\n- \\\"knowledge_base.py\\\"是独立的模块，可以优先开发。\\n- \\\"interface.py\\\"、\\\"user_feedback.py\\\"、\\\"security.py\\\"、\\\"testing.py\\\"和\\\"monitoring.py\\\"看起来像是功能辅助模块，可以在主要功能模块开发完成后并行开发。\\n \", \"Task list\": [\"smart_search_engine/knowledge_base.py\", \"smart_search_engine/index.py\", \"smart_search_engine/ranking.py\", \"smart_search_engine/summary.py\", \"smart_search_engine/search.py\", \"smart_search_engine/main.py\", \"smart_search_engine/interface.py\", \"smart_search_engine/user_feedback.py\", \"smart_search_engine/security.py\", \"smart_search_engine/testing.py\", \"smart_search_engine/monitoring.py\"]}\n\n## Legacy Code\n```Code\n----- smart_search_engine/knowledge_base.py\n## smart_search_engine/knowledge_base.py\n\nclass KnowledgeBase:\n def __init__(self):\n self.data = {}\n\n def update(self, data: dict):\n \"\"\"\n Update the knowledge base with new data.\n\n Args:\n data (dict): The new data to be added to the knowledge base.\n \"\"\"\n self.data.update(data)\n\n def fetch_data(self, query: str) -> dict:\n \"\"\"\n Fetch data from the knowledge base based on the given query.\n\n Args:\n query (str): The query to search for in the knowledge base.\n\n Returns:\n dict: The data matching the query.\n \"\"\"\n return self.data.get(query, {})\n\n----- smart_search_engine/index.py\n## smart_search_engine/index.py\n\nfrom smart_search_engine.knowledge_base import KnowledgeBase\n\nclass Index:\n def __init__(self):\n self.knowledge_base = KnowledgeBase()\n self.index = {}\n\n def create_index(self, data: dict):\n \"\"\"\n Create an index based on the given data.\n\n Args:\n data (dict): The data to be indexed.\n \"\"\"\n self.knowledge_base.update(data)\n self.index = {}\n\n for query, _ in data.items():\n results = self.knowledge_base.fetch_data(query)\n self.index[query] = results\n\n def query_index(self, query: str) -> list:\n \"\"\"\n Query the index based on the given query.\n\n Args:\n query (str): The query to search for in the index.\n\n Returns:\n list: The results matching the query.\n \"\"\"\n if query in self.index:\n return self.index[query]\n else:\n return []\n\n----- smart_search_engine/ranking.py\n## smart_search_engine/ranking.py\n\nclass Ranking:\n def rank_results(self, results: list) -> list:\n \"\"\"\n Rank the search results based on relevance.\n\n Args:\n results (list): The search results to be ranked.\n\n Returns:\n list: The ranked search results.\n \"\"\"\n ranked_results = sorted(results, key=lambda x: x['relevance'], reverse=True)\n return ranked_results\n\n----- smart_search_engine/summary.py\n## smart_search_engine/summary.py\n\nclass Summary:\n def summarize_results(self, results: list) -> str:\n \"\"\"\n Summarize the search results into a single string.\n\n Args:\n results (list): The search results to be summarized.\n\n Returns:\n str: The summarized search results.\n \"\"\"\n summary = \"\"\n for result in results:\n summary += result['summary'] + \"\\n\"\n return summary.strip()\n\n----- smart_search_engine/search.py\n## smart_search_engine/search.py\n\nfrom smart_search_engine.index import Index\nfrom smart_search_engine.ranking import Ranking\nfrom smart_search_engine.summary import Summary\n\nclass SearchEngine:\n def __init__(self):\n self.index = Index()\n self.ranking = Ranking()\n self.summary = Summary()\n\n def search(self, query: str) -> str:\n \"\"\"\n Perform a search based on the given query.\n\n Args:\n query (str): The query to search for.\n\n Returns:\n str: The summarized search results.\n \"\"\"\n results = self.index.query_index(query)\n ranked_results = self.ranking.rank_results(results)\n summary = self.summary.summarize_results(ranked_results)\n return summary\n\n----- smart_search_engine/main.py\n## smart_search_engine/main.py\n\nfrom smart_search_engine.search import SearchEngine\n\nclass Main:\n def __init__(self):\n self.search_engine = SearchEngine()\n\n def main(self) -> str:\n \"\"\"\n Main function to perform a search based on user input.\n\n Returns:\n str: The summarized search results.\n \"\"\"\n query = input(\"Enter your search query: \")\n summary = self.search_engine.search(query)\n return summary\n\nif __name__ == \"__main__\":\n main = Main()\n summary = main.main()\n print(summary)\n\n----- smart_search_engine/interface.py\n## smart_search_engine/interface.py\n\nfrom smart_search_engine.search import SearchEngine\n\nclass Interface:\n def __init__(self):\n self.search_engine = SearchEngine()\n\n def run(self):\n \"\"\"\n Run the search engine interface.\n \"\"\"\n while True:\n query = input(\"Enter your search query (or 'exit' to quit): \")\n if query == \"exit\":\n break\n summary = self.search_engine.search(query)\n print(summary)\n\nif __name__ == \"__main__\":\n interface = Interface()\n interface.run()\n\n```\n\n## Debug logs\n```text\n\n\n\n```\n\n## Bug Feedback logs\n```text\n\n```\n\n# Format example\n## Code: smart_search_engine/user_feedback.py\n```python\n## smart_search_engine/user_feedback.py\n...\n```\n\n# Instruction: Based on the context, follow \"Format example\", write code.\n\n## Code: smart_search_engine/user_feedback.py. Write code with triple quoto, based on the following attentions and context.\n1. Only One file: do your best to implement THIS ONLY ONE FILE.\n2. COMPLETE CODE: Your code will be part of the entire project, so please implement complete, reliable, reusable code snippets.\n3. Set default value: If there is any setting, ALWAYS SET A DEFAULT VALUE, ALWAYS USE STRONG TYPE AND EXPLICIT VARIABLE. AVOID circular import.\n4. Follow design: YOU MUST FOLLOW \"Data structures and interfaces\". DONT CHANGE ANY DESIGN. Do not use public member functions that do not exist in your design.\n5. CAREFULLY CHECK THAT YOU DONT MISS ANY NECESSARY CLASS/FUNCTION IN THIS FILE.\n6. Before using a external variable/module, make sure you import it first.\n7. Write out EVERY CODE DETAIL, DON'T LEAVE TODO.\n\n": "```python\n## smart_search_engine/user_feedback.py\n\nclass UserFeedback:\n def __init__(self):\n self.feedback = []\n\n def add_feedback(self, query: str, relevance: int):\n \"\"\"\n Add user feedback for a search query.\n\n Args:\n query (str): The search query.\n relevance (int): The relevance score provided by the user.\n \"\"\"\n feedback = {\n 'query': query,\n 'relevance': relevance\n }\n self.feedback.append(feedback)\n\n def get_feedback(self) -> list:\n \"\"\"\n Get the user feedback.\n\n Returns:\n list: The user feedback.\n \"\"\"\n return self.feedback\n```\n\n注意事项：\n- 在`smart_search_engine/user_feedback.py`文件中，实现了`UserFeedback`类。\n- `UserFeedback`类有一个`feedback`属性，用于存储用户的反馈信息。\n- `add_feedback`方法用于添加用户的反馈信息，接受一个查询字符串和相关性分数作为参数，并将反馈信息添加到`feedback`列表中。\n- `get_feedback`方法用于获取用户的反馈信息，返回`feedback`列表。", + "\nNOTICE\nRole: You are a professional engineer; the main goal is to write google-style, elegant, modular, easy to read and maintain code\nLanguage: Please use the same language as the user requirement, but the title and code should be still in English. For example, if the user speaks Chinese, the specific text of your answer should also be in Chinese.\nATTENTION: Use '##' to SPLIT SECTIONS, not '#'. Output format carefully referenced \"Format example\".\n\n# Context\n## Design\n## Project name\n```python\n\"smart_search_engine\"\n```\n\n## Task list:\n```python\n[\n \"smart_search_engine/__init__.py\",\n \"smart_search_engine/main.py\",\n \"smart_search_engine/search.py\",\n \"smart_search_engine/index.py\",\n \"smart_search_engine/ranking.py\",\n \"smart_search_engine/summary.py\",\n \"smart_search_engine/knowledge_base.py\",\n \"smart_search_engine/interface.py\",\n \"smart_search_engine/user_feedback.py\",\n \"smart_search_engine/security.py\",\n \"smart_search_engine/testing.py\",\n \"smart_search_engine/monitoring.py\"\n]\n```\n\n## Data structures and interfaces\n```mermaid\nclassDiagram\n class Main {\n -SearchEngine search_engine\n +main() str\n }\n class SearchEngine {\n -Index index\n -Ranking ranking\n -Summary summary\n +search(query: str) str\n }\n class Index {\n -KnowledgeBase knowledge_base\n +create_index(data: dict)\n +query_index(query: str) list\n }\n class Ranking {\n +rank_results(results: list) list\n }\n class Summary {\n +summarize_results(results: list) str\n }\n class KnowledgeBase {\n +update(data: dict)\n +fetch_data(query: str) dict\n }\n Main --> SearchEngine\n SearchEngine --> Index\n SearchEngine --> Ranking\n SearchEngine --> Summary\n Index --> KnowledgeBase\n```\n\n## Program call flow\n```mermaid\nsequenceDiagram\n participant M as Main\n participant SE as SearchEngine\n participant I as Index\n participant R as Ranking\n participant S as Summary\n participant KB as KnowledgeBase\n M->>SE: search(query)\n SE->>I: query_index(query)\n I->>KB: fetch_data(query)\n KB-->>I: return data\n I-->>SE: return results\n SE->>R: rank_results(results)\n R-->>SE: return ranked_results\n SE->>S: summarize_results(ranked_results)\n S-->>SE: return summary\n SE-->>M: return summary\n```\n\n\n## Tasks\n{\"Logic Analysis\": \"\\n 在这个项目中，所有的模块都依赖于“SearchEngine”类，这是主入口，其他的模块（Index、Ranking和Summary）都通过它交互。另外，\\\"Index\\\"类又依赖于\\\"KnowledgeBase\\\"类，因为它需要从知识库中获取数据。\\n\\n- \\\"main.py\\\"包含\\\"Main\\\"类，是程序的入口点，它调用\\\"SearchEngine\\\"进行搜索操作，所以在其他任何模块之前，\\\"SearchEngine\\\"必须首先被定义。\\n- \\\"search.py\\\"定义了\\\"SearchEngine\\\"类，它依赖于\\\"Index\\\"、\\\"Ranking\\\"和\\\"Summary\\\"，因此，这些模块需要在\\\"search.py\\\"之前定义。\\n- \\\"index.py\\\"定义了\\\"Index\\\"类，它从\\\"knowledge_base.py\\\"获取数据来创建索引，所以\\\"knowledge_base.py\\\"需要在\\\"index.py\\\"之前定义。\\n- \\\"ranking.py\\\"和\\\"summary.py\\\"相对独立，只需确保在\\\"search.py\\\"之前定义。\\n- \\\"knowledge_base.py\\\"是独立的模块，可以优先开发。\\n- \\\"interface.py\\\"、\\\"user_feedback.py\\\"、\\\"security.py\\\"、\\\"testing.py\\\"和\\\"monitoring.py\\\"看起来像是功能辅助模块，可以在主要功能模块开发完成后并行开发。\\n \", \"Task list\": [\"smart_search_engine/knowledge_base.py\", \"smart_search_engine/index.py\", \"smart_search_engine/ranking.py\", \"smart_search_engine/summary.py\", \"smart_search_engine/search.py\", \"smart_search_engine/main.py\", \"smart_search_engine/interface.py\", \"smart_search_engine/user_feedback.py\", \"smart_search_engine/security.py\", \"smart_search_engine/testing.py\", \"smart_search_engine/monitoring.py\"]}\n\n## Legacy Code\n```Code\n----- smart_search_engine/knowledge_base.py\n## smart_search_engine/knowledge_base.py\n\nclass KnowledgeBase:\n def __init__(self):\n self.data = {}\n\n def update(self, data: dict):\n \"\"\"\n Update the knowledge base with new data.\n\n Args:\n data (dict): The new data to be added to the knowledge base.\n \"\"\"\n self.data.update(data)\n\n def fetch_data(self, query: str) -> dict:\n \"\"\"\n Fetch data from the knowledge base based on the given query.\n\n Args:\n query (str): The query to search for in the knowledge base.\n\n Returns:\n dict: The data matching the query.\n \"\"\"\n return self.data.get(query, {})\n\n----- smart_search_engine/index.py\n## smart_search_engine/index.py\n\nfrom smart_search_engine.knowledge_base import KnowledgeBase\n\nclass Index:\n def __init__(self):\n self.knowledge_base = KnowledgeBase()\n self.index = {}\n\n def create_index(self, data: dict):\n \"\"\"\n Create an index based on the given data.\n\n Args:\n data (dict): The data to be indexed.\n \"\"\"\n self.knowledge_base.update(data)\n self.index = {}\n\n for query, _ in data.items():\n results = self.knowledge_base.fetch_data(query)\n self.index[query] = results\n\n def query_index(self, query: str) -> list:\n \"\"\"\n Query the index based on the given query.\n\n Args:\n query (str): The query to search for in the index.\n\n Returns:\n list: The results matching the query.\n \"\"\"\n if query in self.index:\n return self.index[query]\n else:\n return []\n\n----- smart_search_engine/ranking.py\n## smart_search_engine/ranking.py\n\nclass Ranking:\n def rank_results(self, results: list) -> list:\n \"\"\"\n Rank the search results based on relevance.\n\n Args:\n results (list): The search results to be ranked.\n\n Returns:\n list: The ranked search results.\n \"\"\"\n ranked_results = sorted(results, key=lambda x: x['relevance'], reverse=True)\n return ranked_results\n\n----- smart_search_engine/summary.py\n## smart_search_engine/summary.py\n\nclass Summary:\n def summarize_results(self, results: list) -> str:\n \"\"\"\n Summarize the search results into a single string.\n\n Args:\n results (list): The search results to be summarized.\n\n Returns:\n str: The summarized search results.\n \"\"\"\n summary = \"\"\n for result in results:\n summary += result['summary'] + \"\\n\"\n return summary.strip()\n\n----- smart_search_engine/search.py\n## smart_search_engine/search.py\n\nfrom smart_search_engine.index import Index\nfrom smart_search_engine.ranking import Ranking\nfrom smart_search_engine.summary import Summary\n\nclass SearchEngine:\n def __init__(self):\n self.index = Index()\n self.ranking = Ranking()\n self.summary = Summary()\n\n def search(self, query: str) -> str:\n \"\"\"\n Perform a search based on the given query.\n\n Args:\n query (str): The query to search for.\n\n Returns:\n str: The summarized search results.\n \"\"\"\n results = self.index.query_index(query)\n ranked_results = self.ranking.rank_results(results)\n summary = self.summary.summarize_results(ranked_results)\n return summary\n\n----- smart_search_engine/main.py\n## smart_search_engine/main.py\n\nfrom smart_search_engine.search import SearchEngine\n\nclass Main:\n def __init__(self):\n self.search_engine = SearchEngine()\n\n def main(self) -> str:\n \"\"\"\n Main function to perform a search based on user input.\n\n Returns:\n str: The summarized search results.\n \"\"\"\n query = input(\"Enter your search query: \")\n summary = self.search_engine.search(query)\n return summary\n\nif __name__ == \"__main__\":\n main = Main()\n summary = main.main()\n print(summary)\n\n----- smart_search_engine/interface.py\n## smart_search_engine/interface.py\n\nfrom smart_search_engine.search import SearchEngine\n\nclass Interface:\n def __init__(self):\n self.search_engine = SearchEngine()\n\n def run(self):\n \"\"\"\n Run the search engine interface.\n \"\"\"\n while True:\n query = input(\"Enter your search query (or 'exit' to quit): \")\n if query == \"exit\":\n break\n summary = self.search_engine.search(query)\n print(summary)\n\nif __name__ == \"__main__\":\n interface = Interface()\n interface.run()\n\n----- smart_search_engine/user_feedback.py\n## smart_search_engine/user_feedback.py\n\nclass UserFeedback:\n def __init__(self):\n self.feedback = []\n\n def add_feedback(self, query: str, relevance: int):\n \"\"\"\n Add user feedback for a search query.\n\n Args:\n query (str): The search query.\n relevance (int): The relevance score provided by the user.\n \"\"\"\n feedback = {\n 'query': query,\n 'relevance': relevance\n }\n self.feedback.append(feedback)\n\n def get_feedback(self) -> list:\n \"\"\"\n Get the user feedback.\n\n Returns:\n list: The user feedback.\n \"\"\"\n return self.feedback\n\n```\n\n## Debug logs\n```text\n\n\n\n```\n\n## Bug Feedback logs\n```text\n\n```\n\n# Format example\n## Code: smart_search_engine/security.py\n```python\n## smart_search_engine/security.py\n...\n```\n\n# Instruction: Based on the context, follow \"Format example\", write code.\n\n## Code: smart_search_engine/security.py. Write code with triple quoto, based on the following attentions and context.\n1. Only One file: do your best to implement THIS ONLY ONE FILE.\n2. COMPLETE CODE: Your code will be part of the entire project, so please implement complete, reliable, reusable code snippets.\n3. Set default value: If there is any setting, ALWAYS SET A DEFAULT VALUE, ALWAYS USE STRONG TYPE AND EXPLICIT VARIABLE. AVOID circular import.\n4. Follow design: YOU MUST FOLLOW \"Data structures and interfaces\". DONT CHANGE ANY DESIGN. Do not use public member functions that do not exist in your design.\n5. CAREFULLY CHECK THAT YOU DONT MISS ANY NECESSARY CLASS/FUNCTION IN THIS FILE.\n6. Before using a external variable/module, make sure you import it first.\n7. Write out EVERY CODE DETAIL, DON'T LEAVE TODO.\n\n": "```python\n## smart_search_engine/security.py\n\nclass Security:\n def __init__(self):\n self.user_feedback = UserFeedback()\n\n def check_user_feedback(self, query: str) -> bool:\n \"\"\"\n Check if the user has provided feedback for the given query.\n\n Args:\n query (str): The search query.\n\n Returns:\n bool: True if the user has provided feedback, False otherwise.\n \"\"\"\n feedback = self.user_feedback.get_feedback()\n for item in feedback:\n if item['query'] == query:\n return True\n return False\n\n def get_user_feedback(self, query: str) -> int:\n \"\"\"\n Get the relevance score provided by the user for the given query.\n\n Args:\n query (str): The search query.\n\n Returns:\n int: The relevance score provided by the user, or None if no feedback is found.\n \"\"\"\n feedback = self.user_feedback.get_feedback()\n for item in feedback:\n if item['query'] == query:\n return item['relevance']\n return None\n\n def add_user_feedback(self, query: str, relevance: int):\n \"\"\"\n Add user feedback for the given query.\n\n Args:\n query (str): The search query.\n relevance (int): The relevance score provided by the user.\n \"\"\"\n self.user_feedback.add_feedback(query, relevance)\n```\n", + "\nNOTICE\nRole: You are a professional engineer; the main goal is to write google-style, elegant, modular, easy to read and maintain code\nLanguage: Please use the same language as the user requirement, but the title and code should be still in English. For example, if the user speaks Chinese, the specific text of your answer should also be in Chinese.\nATTENTION: Use '##' to SPLIT SECTIONS, not '#'. Output format carefully referenced \"Format example\".\n\n# Context\n## Design\n## Project name\n```python\n\"smart_search_engine\"\n```\n\n## Task list:\n```python\n[\n \"smart_search_engine/__init__.py\",\n \"smart_search_engine/main.py\",\n \"smart_search_engine/search.py\",\n \"smart_search_engine/index.py\",\n \"smart_search_engine/ranking.py\",\n \"smart_search_engine/summary.py\",\n \"smart_search_engine/knowledge_base.py\",\n \"smart_search_engine/interface.py\",\n \"smart_search_engine/user_feedback.py\",\n \"smart_search_engine/security.py\",\n \"smart_search_engine/testing.py\",\n \"smart_search_engine/monitoring.py\"\n]\n```\n\n## Data structures and interfaces\n```mermaid\nclassDiagram\n class Main {\n -SearchEngine search_engine\n +main() str\n }\n class SearchEngine {\n -Index index\n -Ranking ranking\n -Summary summary\n +search(query: str) str\n }\n class Index {\n -KnowledgeBase knowledge_base\n +create_index(data: dict)\n +query_index(query: str) list\n }\n class Ranking {\n +rank_results(results: list) list\n }\n class Summary {\n +summarize_results(results: list) str\n }\n class KnowledgeBase {\n +update(data: dict)\n +fetch_data(query: str) dict\n }\n Main --> SearchEngine\n SearchEngine --> Index\n SearchEngine --> Ranking\n SearchEngine --> Summary\n Index --> KnowledgeBase\n```\n\n## Program call flow\n```mermaid\nsequenceDiagram\n participant M as Main\n participant SE as SearchEngine\n participant I as Index\n participant R as Ranking\n participant S as Summary\n participant KB as KnowledgeBase\n M->>SE: search(query)\n SE->>I: query_index(query)\n I->>KB: fetch_data(query)\n KB-->>I: return data\n I-->>SE: return results\n SE->>R: rank_results(results)\n R-->>SE: return ranked_results\n SE->>S: summarize_results(ranked_results)\n S-->>SE: return summary\n SE-->>M: return summary\n```\n\n\n## Tasks\n{\"Logic Analysis\": \"\\n 在这个项目中，所有的模块都依赖于“SearchEngine”类，这是主入口，其他的模块（Index、Ranking和Summary）都通过它交互。另外，\\\"Index\\\"类又依赖于\\\"KnowledgeBase\\\"类，因为它需要从知识库中获取数据。\\n\\n- \\\"main.py\\\"包含\\\"Main\\\"类，是程序的入口点，它调用\\\"SearchEngine\\\"进行搜索操作，所以在其他任何模块之前，\\\"SearchEngine\\\"必须首先被定义。\\n- \\\"search.py\\\"定义了\\\"SearchEngine\\\"类，它依赖于\\\"Index\\\"、\\\"Ranking\\\"和\\\"Summary\\\"，因此，这些模块需要在\\\"search.py\\\"之前定义。\\n- \\\"index.py\\\"定义了\\\"Index\\\"类，它从\\\"knowledge_base.py\\\"获取数据来创建索引，所以\\\"knowledge_base.py\\\"需要在\\\"index.py\\\"之前定义。\\n- \\\"ranking.py\\\"和\\\"summary.py\\\"相对独立，只需确保在\\\"search.py\\\"之前定义。\\n- \\\"knowledge_base.py\\\"是独立的模块，可以优先开发。\\n- \\\"interface.py\\\"、\\\"user_feedback.py\\\"、\\\"security.py\\\"、\\\"testing.py\\\"和\\\"monitoring.py\\\"看起来像是功能辅助模块，可以在主要功能模块开发完成后并行开发。\\n \", \"Task list\": [\"smart_search_engine/knowledge_base.py\", \"smart_search_engine/index.py\", \"smart_search_engine/ranking.py\", \"smart_search_engine/summary.py\", \"smart_search_engine/search.py\", \"smart_search_engine/main.py\", \"smart_search_engine/interface.py\", \"smart_search_engine/user_feedback.py\", \"smart_search_engine/security.py\", \"smart_search_engine/testing.py\", \"smart_search_engine/monitoring.py\"]}\n\n## Legacy Code\n```Code\n----- smart_search_engine/knowledge_base.py\n## smart_search_engine/knowledge_base.py\n\nclass KnowledgeBase:\n def __init__(self):\n self.data = {}\n\n def update(self, data: dict):\n \"\"\"\n Update the knowledge base with new data.\n\n Args:\n data (dict): The new data to be added to the knowledge base.\n \"\"\"\n self.data.update(data)\n\n def fetch_data(self, query: str) -> dict:\n \"\"\"\n Fetch data from the knowledge base based on the given query.\n\n Args:\n query (str): The query to search for in the knowledge base.\n\n Returns:\n dict: The data matching the query.\n \"\"\"\n return self.data.get(query, {})\n\n----- smart_search_engine/index.py\n## smart_search_engine/index.py\n\nfrom smart_search_engine.knowledge_base import KnowledgeBase\n\nclass Index:\n def __init__(self):\n self.knowledge_base = KnowledgeBase()\n self.index = {}\n\n def create_index(self, data: dict):\n \"\"\"\n Create an index based on the given data.\n\n Args:\n data (dict): The data to be indexed.\n \"\"\"\n self.knowledge_base.update(data)\n self.index = {}\n\n for query, _ in data.items():\n results = self.knowledge_base.fetch_data(query)\n self.index[query] = results\n\n def query_index(self, query: str) -> list:\n \"\"\"\n Query the index based on the given query.\n\n Args:\n query (str): The query to search for in the index.\n\n Returns:\n list: The results matching the query.\n \"\"\"\n if query in self.index:\n return self.index[query]\n else:\n return []\n\n----- smart_search_engine/ranking.py\n## smart_search_engine/ranking.py\n\nclass Ranking:\n def rank_results(self, results: list) -> list:\n \"\"\"\n Rank the search results based on relevance.\n\n Args:\n results (list): The search results to be ranked.\n\n Returns:\n list: The ranked search results.\n \"\"\"\n ranked_results = sorted(results, key=lambda x: x['relevance'], reverse=True)\n return ranked_results\n\n----- smart_search_engine/summary.py\n## smart_search_engine/summary.py\n\nclass Summary:\n def summarize_results(self, results: list) -> str:\n \"\"\"\n Summarize the search results into a single string.\n\n Args:\n results (list): The search results to be summarized.\n\n Returns:\n str: The summarized search results.\n \"\"\"\n summary = \"\"\n for result in results:\n summary += result['summary'] + \"\\n\"\n return summary.strip()\n\n----- smart_search_engine/search.py\n## smart_search_engine/search.py\n\nfrom smart_search_engine.index import Index\nfrom smart_search_engine.ranking import Ranking\nfrom smart_search_engine.summary import Summary\n\nclass SearchEngine:\n def __init__(self):\n self.index = Index()\n self.ranking = Ranking()\n self.summary = Summary()\n\n def search(self, query: str) -> str:\n \"\"\"\n Perform a search based on the given query.\n\n Args:\n query (str): The query to search for.\n\n Returns:\n str: The summarized search results.\n \"\"\"\n results = self.index.query_index(query)\n ranked_results = self.ranking.rank_results(results)\n summary = self.summary.summarize_results(ranked_results)\n return summary\n\n----- smart_search_engine/main.py\n## smart_search_engine/main.py\n\nfrom smart_search_engine.search import SearchEngine\n\nclass Main:\n def __init__(self):\n self.search_engine = SearchEngine()\n\n def main(self) -> str:\n \"\"\"\n Main function to perform a search based on user input.\n\n Returns:\n str: The summarized search results.\n \"\"\"\n query = input(\"Enter your search query: \")\n summary = self.search_engine.search(query)\n return summary\n\nif __name__ == \"__main__\":\n main = Main()\n summary = main.main()\n print(summary)\n\n----- smart_search_engine/interface.py\n## smart_search_engine/interface.py\n\nfrom smart_search_engine.search import SearchEngine\n\nclass Interface:\n def __init__(self):\n self.search_engine = SearchEngine()\n\n def run(self):\n \"\"\"\n Run the search engine interface.\n \"\"\"\n while True:\n query = input(\"Enter your search query (or 'exit' to quit): \")\n if query == \"exit\":\n break\n summary = self.search_engine.search(query)\n print(summary)\n\nif __name__ == \"__main__\":\n interface = Interface()\n interface.run()\n\n----- smart_search_engine/user_feedback.py\n## smart_search_engine/user_feedback.py\n\nclass UserFeedback:\n def __init__(self):\n self.feedback = []\n\n def add_feedback(self, query: str, relevance: int):\n \"\"\"\n Add user feedback for a search query.\n\n Args:\n query (str): The search query.\n relevance (int): The relevance score provided by the user.\n \"\"\"\n feedback = {\n 'query': query,\n 'relevance': relevance\n }\n self.feedback.append(feedback)\n\n def get_feedback(self) -> list:\n \"\"\"\n Get the user feedback.\n\n Returns:\n list: The user feedback.\n \"\"\"\n return self.feedback\n\n----- smart_search_engine/security.py\n## smart_search_engine/security.py\n\nclass Security:\n def __init__(self):\n self.user_feedback = UserFeedback()\n\n def check_user_feedback(self, query: str) -> bool:\n \"\"\"\n Check if the user has provided feedback for the given query.\n\n Args:\n query (str): The search query.\n\n Returns:\n bool: True if the user has provided feedback, False otherwise.\n \"\"\"\n feedback = self.user_feedback.get_feedback()\n for item in feedback:\n if item['query'] == query:\n return True\n return False\n\n def get_user_feedback(self, query: str) -> int:\n \"\"\"\n Get the relevance score provided by the user for the given query.\n\n Args:\n query (str): The search query.\n\n Returns:\n int: The relevance score provided by the user, or None if no feedback is found.\n \"\"\"\n feedback = self.user_feedback.get_feedback()\n for item in feedback:\n if item['query'] == query:\n return item['relevance']\n return None\n\n def add_user_feedback(self, query: str, relevance: int):\n \"\"\"\n Add user feedback for the given query.\n\n Args:\n query (str): The search query.\n relevance (int): The relevance score provided by the user.\n \"\"\"\n self.user_feedback.add_feedback(query, relevance)\n\n```\n\n## Debug logs\n```text\n\n\n\n```\n\n## Bug Feedback logs\n```text\n\n```\n\n# Format example\n## Code: smart_search_engine/testing.py\n```python\n## smart_search_engine/testing.py\n...\n```\n\n# Instruction: Based on the context, follow \"Format example\", write code.\n\n## Code: smart_search_engine/testing.py. Write code with triple quoto, based on the following attentions and context.\n1. Only One file: do your best to implement THIS ONLY ONE FILE.\n2. COMPLETE CODE: Your code will be part of the entire project, so please implement complete, reliable, reusable code snippets.\n3. Set default value: If there is any setting, ALWAYS SET A DEFAULT VALUE, ALWAYS USE STRONG TYPE AND EXPLICIT VARIABLE. AVOID circular import.\n4. Follow design: YOU MUST FOLLOW \"Data structures and interfaces\". DONT CHANGE ANY DESIGN. Do not use public member functions that do not exist in your design.\n5. CAREFULLY CHECK THAT YOU DONT MISS ANY NECESSARY CLASS/FUNCTION IN THIS FILE.\n6. Before using a external variable/module, make sure you import it first.\n7. Write out EVERY CODE DETAIL, DON'T LEAVE TODO.\n\n": "```python\n## smart_search_engine/testing.py\n\nfrom smart_search_engine.search import SearchEngine\nfrom smart_search_engine.index import Index\nfrom smart_search_engine.ranking import Ranking\nfrom smart_search_engine.summary import Summary\nfrom smart_search_engine.knowledge_base import KnowledgeBase\n\nclass Testing:\n def __init__(self):\n self.search_engine = SearchEngine()\n self.index = Index()\n self.ranking = Ranking()\n self.summary = Summary()\n self.knowledge_base = KnowledgeBase()\n\n def test_search_engine(self):\n \"\"\"\n Test the search engine functionality.\n \"\"\"\n # Test case 1: Search for a query that exists in the index\n query1 = \"apple\"\n expected_summary1 = \"Summary of search results for query: apple\"\n self.knowledge_base.update({\"apple\": {\"relevance\": 0.8, \"summary\": \"This is an apple.\"}})\n self.index.create_index({\"apple\": {\"relevance\": 0.8, \"summary\": \"This is an apple.\"}})\n summary1 = self.search_engine.search(query1)\n assert summary1 == expected_summary1, f\"Test case 1 failed: {summary1}\"\n\n # Test case 2: Search for a query that does not exist in the index\n query2 = \"banana\"\n expected_summary2 = \"No results found for query: banana\"\n self.knowledge_base.update({\"apple\": {\"relevance\": 0.8, \"summary\": \"This is an apple.\"}})\n self.index.create_index({\"apple\": {\"relevance\": 0.8, \"summary\": \"This is an apple.\"}})\n summary2 = self.search_engine.search(query2)\n assert summary2 == expected_summary2, f\"Test case 2 failed: {summary2}\"\n\n def test_index(self):\n \"\"\"\n Test the index functionality.\n \"\"\"\n # Test case 1: Create index with valid data\n data1 = {\"apple\": {\"relevance\": 0.8, \"summary\": \"This is an apple.\"}}\n expected_index1 = {\"apple\": {\"relevance\": 0.8, \"summary\": \"This is an apple.\"}}\n self.knowledge_base.update(data1)\n self.index.create_index(data1)\n index1 = self.index.index\n assert index1 == expected_index1, f\"Test case 1 failed: {index1}\"\n\n # Test case 2: Query index with valid query\n query2 = \"apple\"\n expected_results2 = [{\"relevance\": 0.8, \"summary\": \"This is an apple.\"}]\n results2 = self.index.query_index(query2)\n assert results2 == expected_results2, f\"Test case 2 failed: {results2}\"\n\n # Test case 3: Query index with invalid query\n query3 = \"banana\"\n expected_results3 = []\n results3 = self.index.query_index(query3)\n assert results3 == expected_results3, f\"Test case 3 failed: {results3}\"\n\n def test_ranking(self):\n \"\"\"\n Test the ranking functionality.\n \"\"\"\n # Test case 1: Rank results in descending order of relevance\n results1 = [{\"relevance\": 0.8, \"summary\": \"This is an apple.\"}, {\"relevance\": 0.6, \"summary\": \"This is a banana.\"}]\n expected_ranked_results1 = [{\"relevance\": 0.8, \"summary\": \"This is an apple.\"}, {\"relevance\": 0.6, \"summary\": \"This is a banana.\"}]\n ranked_results1 = self.ranking.rank_results(results1)\n assert ranked_results1 == expected_ranked_results1, f\"Test case 1 failed: {ranked_results1}\"\n\n # Test case 2: Rank results in ascending order of relevance\n results2 = [{\"relevance\": 0.6, \"summary\": \"This is a banana.\"}, {\"relevance\": 0.8, \"summary\": \"This is an apple.\"}]\n expected_ranked_results2 = [{\"relevance\": 0.8, \"summary\": \"This is an apple.\"}, {\"relevance\": 0.6, \"summary\": \"This is a banana.\"}]\n ranked_results2 = self.ranking.rank_results(results2)\n assert ranked_results2 == expected_ranked_results2, f\"Test case 2 failed: {ranked_results2}\"\n\n def test_summary(self):\n \"\"\"\n Test the summary functionality.\n \"\"\"\n # Test case 1: Summarize search results into a single string\n results1 = [{\"relevance\": 0.8, \"summary\": \"This is an apple.\"}, {\"relevance\": 0.6, \"summary\": \"This is a banana.\"}]\n expected_summary1 = \"This is an apple.\\nThis is a banana.\"\n summary1 = self.summary.summarize_results(results1)\n assert summary1 == expected_summary1, f\"Test case 1 failed: {summary1}\"\n\n # Test case 2: Summarize empty search results\n results2 = []\n expected_summary2 = \"\"\n summary2 = self.summary.summarize_results(results2)\n assert summary2 == expected_summary2, f\"Test case 2 failed: {summary2}\"\n\n def run_tests(self):\n \"\"\"\n Run all the tests.\n \"\"\"\n self.test_search_engine()\n self.test_index()\n self.test_ranking()\n self.test_summary()\n\nif __name__ == \"__main__\":\n testing = Testing()\n testing.run_tests()\n```\n\nIn the above code, I have implemented a `Testing` class that contains methods to test the functionality of the search engine, index, ranking, and summary modules. Each test case checks the expected output against the actual output and raises an assertion error if they do not match. The `run_tests` method runs all the test cases.", + "\nNOTICE\nRole: You are a professional engineer; the main goal is to write google-style, elegant, modular, easy to read and maintain code\nLanguage: Please use the same language as the user requirement, but the title and code should be still in English. For example, if the user speaks Chinese, the specific text of your answer should also be in Chinese.\nATTENTION: Use '##' to SPLIT SECTIONS, not '#'. Output format carefully referenced \"Format example\".\n\n# Context\n## Design\n## Project name\n```python\n\"smart_search_engine\"\n```\n\n## Task list:\n```python\n[\n \"smart_search_engine/__init__.py\",\n \"smart_search_engine/main.py\",\n \"smart_search_engine/search.py\",\n \"smart_search_engine/index.py\",\n \"smart_search_engine/ranking.py\",\n \"smart_search_engine/summary.py\",\n \"smart_search_engine/knowledge_base.py\",\n \"smart_search_engine/interface.py\",\n \"smart_search_engine/user_feedback.py\",\n \"smart_search_engine/security.py\",\n \"smart_search_engine/testing.py\",\n \"smart_search_engine/monitoring.py\"\n]\n```\n\n## Data structures and interfaces\n```mermaid\nclassDiagram\n class Main {\n -SearchEngine search_engine\n +main() str\n }\n class SearchEngine {\n -Index index\n -Ranking ranking\n -Summary summary\n +search(query: str) str\n }\n class Index {\n -KnowledgeBase knowledge_base\n +create_index(data: dict)\n +query_index(query: str) list\n }\n class Ranking {\n +rank_results(results: list) list\n }\n class Summary {\n +summarize_results(results: list) str\n }\n class KnowledgeBase {\n +update(data: dict)\n +fetch_data(query: str) dict\n }\n Main --> SearchEngine\n SearchEngine --> Index\n SearchEngine --> Ranking\n SearchEngine --> Summary\n Index --> KnowledgeBase\n```\n\n## Program call flow\n```mermaid\nsequenceDiagram\n participant M as Main\n participant SE as SearchEngine\n participant I as Index\n participant R as Ranking\n participant S as Summary\n participant KB as KnowledgeBase\n M->>SE: search(query)\n SE->>I: query_index(query)\n I->>KB: fetch_data(query)\n KB-->>I: return data\n I-->>SE: return results\n SE->>R: rank_results(results)\n R-->>SE: return ranked_results\n SE->>S: summarize_results(ranked_results)\n S-->>SE: return summary\n SE-->>M: return summary\n```\n\n\n## Tasks\n{\"Logic Analysis\": \"\\n 在这个项目中，所有的模块都依赖于“SearchEngine”类，这是主入口，其他的模块（Index、Ranking和Summary）都通过它交互。另外，\\\"Index\\\"类又依赖于\\\"KnowledgeBase\\\"类，因为它需要从知识库中获取数据。\\n\\n- \\\"main.py\\\"包含\\\"Main\\\"类，是程序的入口点，它调用\\\"SearchEngine\\\"进行搜索操作，所以在其他任何模块之前，\\\"SearchEngine\\\"必须首先被定义。\\n- \\\"search.py\\\"定义了\\\"SearchEngine\\\"类，它依赖于\\\"Index\\\"、\\\"Ranking\\\"和\\\"Summary\\\"，因此，这些模块需要在\\\"search.py\\\"之前定义。\\n- \\\"index.py\\\"定义了\\\"Index\\\"类，它从\\\"knowledge_base.py\\\"获取数据来创建索引，所以\\\"knowledge_base.py\\\"需要在\\\"index.py\\\"之前定义。\\n- \\\"ranking.py\\\"和\\\"summary.py\\\"相对独立，只需确保在\\\"search.py\\\"之前定义。\\n- \\\"knowledge_base.py\\\"是独立的模块，可以优先开发。\\n- \\\"interface.py\\\"、\\\"user_feedback.py\\\"、\\\"security.py\\\"、\\\"testing.py\\\"和\\\"monitoring.py\\\"看起来像是功能辅助模块，可以在主要功能模块开发完成后并行开发。\\n \", \"Task list\": [\"smart_search_engine/knowledge_base.py\", \"smart_search_engine/index.py\", \"smart_search_engine/ranking.py\", \"smart_search_engine/summary.py\", \"smart_search_engine/search.py\", \"smart_search_engine/main.py\", \"smart_search_engine/interface.py\", \"smart_search_engine/user_feedback.py\", \"smart_search_engine/security.py\", \"smart_search_engine/testing.py\", \"smart_search_engine/monitoring.py\"]}\n\n## Legacy Code\n```Code\n----- smart_search_engine/knowledge_base.py\n## smart_search_engine/knowledge_base.py\n\nclass KnowledgeBase:\n def __init__(self):\n self.data = {}\n\n def update(self, data: dict):\n \"\"\"\n Update the knowledge base with new data.\n\n Args:\n data (dict): The new data to be added to the knowledge base.\n \"\"\"\n self.data.update(data)\n\n def fetch_data(self, query: str) -> dict:\n \"\"\"\n Fetch data from the knowledge base based on the given query.\n\n Args:\n query (str): The query to search for in the knowledge base.\n\n Returns:\n dict: The data matching the query.\n \"\"\"\n return self.data.get(query, {})\n\n----- smart_search_engine/index.py\n## smart_search_engine/index.py\n\nfrom smart_search_engine.knowledge_base import KnowledgeBase\n\nclass Index:\n def __init__(self):\n self.knowledge_base = KnowledgeBase()\n self.index = {}\n\n def create_index(self, data: dict):\n \"\"\"\n Create an index based on the given data.\n\n Args:\n data (dict): The data to be indexed.\n \"\"\"\n self.knowledge_base.update(data)\n self.index = {}\n\n for query, _ in data.items():\n results = self.knowledge_base.fetch_data(query)\n self.index[query] = results\n\n def query_index(self, query: str) -> list:\n \"\"\"\n Query the index based on the given query.\n\n Args:\n query (str): The query to search for in the index.\n\n Returns:\n list: The results matching the query.\n \"\"\"\n if query in self.index:\n return self.index[query]\n else:\n return []\n\n----- smart_search_engine/ranking.py\n## smart_search_engine/ranking.py\n\nclass Ranking:\n def rank_results(self, results: list) -> list:\n \"\"\"\n Rank the search results based on relevance.\n\n Args:\n results (list): The search results to be ranked.\n\n Returns:\n list: The ranked search results.\n \"\"\"\n ranked_results = sorted(results, key=lambda x: x['relevance'], reverse=True)\n return ranked_results\n\n----- smart_search_engine/summary.py\n## smart_search_engine/summary.py\n\nclass Summary:\n def summarize_results(self, results: list) -> str:\n \"\"\"\n Summarize the search results into a single string.\n\n Args:\n results (list): The search results to be summarized.\n\n Returns:\n str: The summarized search results.\n \"\"\"\n summary = \"\"\n for result in results:\n summary += result['summary'] + \"\\n\"\n return summary.strip()\n\n----- smart_search_engine/search.py\n## smart_search_engine/search.py\n\nfrom smart_search_engine.index import Index\nfrom smart_search_engine.ranking import Ranking\nfrom smart_search_engine.summary import Summary\n\nclass SearchEngine:\n def __init__(self):\n self.index = Index()\n self.ranking = Ranking()\n self.summary = Summary()\n\n def search(self, query: str) -> str:\n \"\"\"\n Perform a search based on the given query.\n\n Args:\n query (str): The query to search for.\n\n Returns:\n str: The summarized search results.\n \"\"\"\n results = self.index.query_index(query)\n ranked_results = self.ranking.rank_results(results)\n summary = self.summary.summarize_results(ranked_results)\n return summary\n\n----- smart_search_engine/main.py\n## smart_search_engine/main.py\n\nfrom smart_search_engine.search import SearchEngine\n\nclass Main:\n def __init__(self):\n self.search_engine = SearchEngine()\n\n def main(self) -> str:\n \"\"\"\n Main function to perform a search based on user input.\n\n Returns:\n str: The summarized search results.\n \"\"\"\n query = input(\"Enter your search query: \")\n summary = self.search_engine.search(query)\n return summary\n\nif __name__ == \"__main__\":\n main = Main()\n summary = main.main()\n print(summary)\n\n----- smart_search_engine/interface.py\n## smart_search_engine/interface.py\n\nfrom smart_search_engine.search import SearchEngine\n\nclass Interface:\n def __init__(self):\n self.search_engine = SearchEngine()\n\n def run(self):\n \"\"\"\n Run the search engine interface.\n \"\"\"\n while True:\n query = input(\"Enter your search query (or 'exit' to quit): \")\n if query == \"exit\":\n break\n summary = self.search_engine.search(query)\n print(summary)\n\nif __name__ == \"__main__\":\n interface = Interface()\n interface.run()\n\n----- smart_search_engine/user_feedback.py\n## smart_search_engine/user_feedback.py\n\nclass UserFeedback:\n def __init__(self):\n self.feedback = []\n\n def add_feedback(self, query: str, relevance: int):\n \"\"\"\n Add user feedback for a search query.\n\n Args:\n query (str): The search query.\n relevance (int): The relevance score provided by the user.\n \"\"\"\n feedback = {\n 'query': query,\n 'relevance': relevance\n }\n self.feedback.append(feedback)\n\n def get_feedback(self) -> list:\n \"\"\"\n Get the user feedback.\n\n Returns:\n list: The user feedback.\n \"\"\"\n return self.feedback\n\n----- smart_search_engine/security.py\n## smart_search_engine/security.py\n\nclass Security:\n def __init__(self):\n self.user_feedback = UserFeedback()\n\n def check_user_feedback(self, query: str) -> bool:\n \"\"\"\n Check if the user has provided feedback for the given query.\n\n Args:\n query (str): The search query.\n\n Returns:\n bool: True if the user has provided feedback, False otherwise.\n \"\"\"\n feedback = self.user_feedback.get_feedback()\n for item in feedback:\n if item['query'] == query:\n return True\n return False\n\n def get_user_feedback(self, query: str) -> int:\n \"\"\"\n Get the relevance score provided by the user for the given query.\n\n Args:\n query (str): The search query.\n\n Returns:\n int: The relevance score provided by the user, or None if no feedback is found.\n \"\"\"\n feedback = self.user_feedback.get_feedback()\n for item in feedback:\n if item['query'] == query:\n return item['relevance']\n return None\n\n def add_user_feedback(self, query: str, relevance: int):\n \"\"\"\n Add user feedback for the given query.\n\n Args:\n query (str): The search query.\n relevance (int): The relevance score provided by the user.\n \"\"\"\n self.user_feedback.add_feedback(query, relevance)\n\n----- smart_search_engine/testing.py\n## smart_search_engine/testing.py\n\nfrom smart_search_engine.search import SearchEngine\nfrom smart_search_engine.index import Index\nfrom smart_search_engine.ranking import Ranking\nfrom smart_search_engine.summary import Summary\nfrom smart_search_engine.knowledge_base import KnowledgeBase\n\nclass Testing:\n def __init__(self):\n self.search_engine = SearchEngine()\n self.index = Index()\n self.ranking = Ranking()\n self.summary = Summary()\n self.knowledge_base = KnowledgeBase()\n\n def test_search_engine(self):\n \"\"\"\n Test the search engine functionality.\n \"\"\"\n # Test case 1: Search for a query that exists in the index\n query1 = \"apple\"\n expected_summary1 = \"Summary of search results for query: apple\"\n self.knowledge_base.update({\"apple\": {\"relevance\": 0.8, \"summary\": \"This is an apple.\"}})\n self.index.create_index({\"apple\": {\"relevance\": 0.8, \"summary\": \"This is an apple.\"}})\n summary1 = self.search_engine.search(query1)\n assert summary1 == expected_summary1, f\"Test case 1 failed: {summary1}\"\n\n # Test case 2: Search for a query that does not exist in the index\n query2 = \"banana\"\n expected_summary2 = \"No results found for query: banana\"\n self.knowledge_base.update({\"apple\": {\"relevance\": 0.8, \"summary\": \"This is an apple.\"}})\n self.index.create_index({\"apple\": {\"relevance\": 0.8, \"summary\": \"This is an apple.\"}})\n summary2 = self.search_engine.search(query2)\n assert summary2 == expected_summary2, f\"Test case 2 failed: {summary2}\"\n\n def test_index(self):\n \"\"\"\n Test the index functionality.\n \"\"\"\n # Test case 1: Create index with valid data\n data1 = {\"apple\": {\"relevance\": 0.8, \"summary\": \"This is an apple.\"}}\n expected_index1 = {\"apple\": {\"relevance\": 0.8, \"summary\": \"This is an apple.\"}}\n self.knowledge_base.update(data1)\n self.index.create_index(data1)\n index1 = self.index.index\n assert index1 == expected_index1, f\"Test case 1 failed: {index1}\"\n\n # Test case 2: Query index with valid query\n query2 = \"apple\"\n expected_results2 = [{\"relevance\": 0.8, \"summary\": \"This is an apple.\"}]\n results2 = self.index.query_index(query2)\n assert results2 == expected_results2, f\"Test case 2 failed: {results2}\"\n\n # Test case 3: Query index with invalid query\n query3 = \"banana\"\n expected_results3 = []\n results3 = self.index.query_index(query3)\n assert results3 == expected_results3, f\"Test case 3 failed: {results3}\"\n\n def test_ranking(self):\n \"\"\"\n Test the ranking functionality.\n \"\"\"\n # Test case 1: Rank results in descending order of relevance\n results1 = [{\"relevance\": 0.8, \"summary\": \"This is an apple.\"}, {\"relevance\": 0.6, \"summary\": \"This is a banana.\"}]\n expected_ranked_results1 = [{\"relevance\": 0.8, \"summary\": \"This is an apple.\"}, {\"relevance\": 0.6, \"summary\": \"This is a banana.\"}]\n ranked_results1 = self.ranking.rank_results(results1)\n assert ranked_results1 == expected_ranked_results1, f\"Test case 1 failed: {ranked_results1}\"\n\n # Test case 2: Rank results in ascending order of relevance\n results2 = [{\"relevance\": 0.6, \"summary\": \"This is a banana.\"}, {\"relevance\": 0.8, \"summary\": \"This is an apple.\"}]\n expected_ranked_results2 = [{\"relevance\": 0.8, \"summary\": \"This is an apple.\"}, {\"relevance\": 0.6, \"summary\": \"This is a banana.\"}]\n ranked_results2 = self.ranking.rank_results(results2)\n assert ranked_results2 == expected_ranked_results2, f\"Test case 2 failed: {ranked_results2}\"\n\n def test_summary(self):\n \"\"\"\n Test the summary functionality.\n \"\"\"\n # Test case 1: Summarize search results into a single string\n results1 = [{\"relevance\": 0.8, \"summary\": \"This is an apple.\"}, {\"relevance\": 0.6, \"summary\": \"This is a banana.\"}]\n expected_summary1 = \"This is an apple.\\nThis is a banana.\"\n summary1 = self.summary.summarize_results(results1)\n assert summary1 == expected_summary1, f\"Test case 1 failed: {summary1}\"\n\n # Test case 2: Summarize empty search results\n results2 = []\n expected_summary2 = \"\"\n summary2 = self.summary.summarize_results(results2)\n assert summary2 == expected_summary2, f\"Test case 2 failed: {summary2}\"\n\n def run_tests(self):\n \"\"\"\n Run all the tests.\n \"\"\"\n self.test_search_engine()\n self.test_index()\n self.test_ranking()\n self.test_summary()\n\nif __name__ == \"__main__\":\n testing = Testing()\n testing.run_tests()\n\n```\n\n## Debug logs\n```text\n\n\n\n```\n\n## Bug Feedback logs\n```text\n\n```\n\n# Format example\n## Code: smart_search_engine/monitoring.py\n```python\n## smart_search_engine/monitoring.py\n...\n```\n\n# Instruction: Based on the context, follow \"Format example\", write code.\n\n## Code: smart_search_engine/monitoring.py. Write code with triple quoto, based on the following attentions and context.\n1. Only One file: do your best to implement THIS ONLY ONE FILE.\n2. COMPLETE CODE: Your code will be part of the entire project, so please implement complete, reliable, reusable code snippets.\n3. Set default value: If there is any setting, ALWAYS SET A DEFAULT VALUE, ALWAYS USE STRONG TYPE AND EXPLICIT VARIABLE. AVOID circular import.\n4. Follow design: YOU MUST FOLLOW \"Data structures and interfaces\". DONT CHANGE ANY DESIGN. Do not use public member functions that do not exist in your design.\n5. CAREFULLY CHECK THAT YOU DONT MISS ANY NECESSARY CLASS/FUNCTION IN THIS FILE.\n6. Before using a external variable/module, make sure you import it first.\n7. Write out EVERY CODE DETAIL, DON'T LEAVE TODO.\n\n": "```python\n## smart_search_engine/monitoring.py\n\nimport time\n\nclass Monitoring:\n def __init__(self):\n self.start_time = None\n self.end_time = None\n\n def start(self):\n \"\"\"\n Start the monitoring timer.\n \"\"\"\n self.start_time = time.time()\n\n def stop(self):\n \"\"\"\n Stop the monitoring timer.\n \"\"\"\n self.end_time = time.time()\n\n def get_elapsed_time(self) -> float:\n \"\"\"\n Get the elapsed time in seconds.\n\n Returns:\n float: The elapsed time in seconds.\n \"\"\"\n if self.start_time is None or self.end_time is None:\n raise Exception(\"Monitoring timer has not been started or stopped.\")\n return self.end_time - self.start_time\n```\n\n## Explanation:\nI have implemented the `Monitoring` class in the `smart_search_engine/monitoring.py` file. This class is responsible for starting and stopping a timer to monitor the elapsed time of a process. \n\nThe `Monitoring` class has the following methods:\n- `start()`: Starts the monitoring timer by setting the `start_time` attribute to the current time.\n- `stop()`: Stops the monitoring timer by setting the `end_time` attribute to the current time.\n- `get_elapsed_time()`: Calculates and returns the elapsed time in seconds by subtracting the `start_time` from the `end_time`. If the monitoring timer has not been started or stopped, an exception is raised.\n\nThis implementation follows the design specified in the `Data structures and interfaces` section.", + "\n## context\n\n### Project Name\n\n\n### Original Requirements\n['开发一个基于大语言模型与私有知识库的搜索引擎，希望可以基于大语言模型进行搜索总结']\n\n### Search Information\n-\n\n\n-----\n\n## format example\n[CONTENT]\n{\n \"Language\": \"en_us\",\n \"Programming Language\": \"Python\",\n \"Original Requirements\": \"Create a 2048 game\",\n \"Project Name\": \"game_2048\",\n \"Product Goals\": [\n \"Create an engaging user experience\",\n \"Improve accessibility, be responsive\",\n \"More beautiful UI\"\n ],\n \"User Stories\": [\n \"As a player, I want to be able to choose difficulty levels\",\n \"As a player, I want to see my score after each game\",\n \"As a player, I want to get restart button when I lose\",\n \"As a player, I want to see beautiful UI that make me feel good\",\n \"As a player, I want to play game via mobile phone\"\n ],\n \"Competitive Analysis\": [\n \"2048 Game A: Simple interface, lacks responsive features\",\n \"play2048.co: Beautiful and responsive UI with my best score shown\",\n \"2048game.com: Responsive UI with my best score shown, but many ads\"\n ],\n \"Competitive Quadrant Chart\": \"quadrantChart\\n title \\\"Reach and engagement of campaigns\\\"\\n x-axis \\\"Low Reach\\\" --> \\\"High Reach\\\"\\n y-axis \\\"Low Engagement\\\" --> \\\"High Engagement\\\"\\n quadrant-1 \\\"We should expand\\\"\\n quadrant-2 \\\"Need to promote\\\"\\n quadrant-3 \\\"Re-evaluate\\\"\\n quadrant-4 \\\"May be improved\\\"\\n \\\"Campaign A\\\": [0.3, 0.6]\\n \\\"Campaign B\\\": [0.45, 0.23]\\n \\\"Campaign C\\\": [0.57, 0.69]\\n \\\"Campaign D\\\": [0.78, 0.34]\\n \\\"Campaign E\\\": [0.40, 0.34]\\n \\\"Campaign F\\\": [0.35, 0.78]\\n \\\"Our Target Product\\\": [0.5, 0.6]\",\n \"Requirement Analysis\": \"\",\n \"Requirement Pool\": [\n [\n \"P0\",\n \"The main code ...\"\n ],\n [\n \"P0\",\n \"The game algorithm ...\"\n ]\n ],\n \"UI Design draft\": \"Basic function description with a simple style and layout.\",\n \"Anything UNCLEAR\": \"\"\n}\n[/CONTENT]\n\n## nodes: \": # \"\n- Language: # Provide the language used in the project, typically matching the user's requirement language.\n- Programming Language: # Python/JavaScript or other mainstream programming language.\n- Original Requirements: # Place the original user's requirements here.\n- Project Name: # According to the content of \"Original Requirements,\" name the project using snake case style , like 'game_2048' or 'simple_crm.\n- Product Goals: typing.List[str] # Provide up to three clear, orthogonal product goals.\n- User Stories: typing.List[str] # Provide up to 3 to 5 scenario-based user stories.\n- Competitive Analysis: typing.List[str] # Provide 5 to 7 competitive products.\n- Competitive Quadrant Chart: # Use mermaid quadrantChart syntax. Distribute scores evenly between 0 and 1\n- Requirement Analysis: # Provide a detailed analysis of the requirements.\n- Requirement Pool: typing.List[typing.List[str]] # List down the top-5 requirements with their priority (P0, P1, P2).\n- UI Design draft: # Provide a simple description of UI elements, functions, style, and layout.\n- Anything UNCLEAR: # Mention any aspects of the project that are unclear and try to clarify them.\n\n\n## constraint\nLanguage: Please use the same language as Human INPUT.\nFormat: output wrapped inside [CONTENT][/CONTENT] like format example, nothing else.\n\n## action\nFollow instructions of nodes, generate output and make sure it follows the format example.\n": "{\n \"Language\": \"en_us\",\n \"Programming Language\": \"\",\n \"Original Requirements\": \"开发一个基于大语言模型与私有知识库的搜索引擎，希望可以基于大语言模型进行搜索总结\",\n \"Project Name\": \"search_engine\",\n \"Product Goals\": [\n \"Develop a search engine based on a large language model\",\n \"Incorporate a private knowledge base for enhanced search capabilities\",\n \"Implement search summarization using the large language model\"\n ],\n \"User Stories\": [\n \"As a user, I want to be able to search for information using natural language queries\",\n \"As a user, I want the search engine to provide relevant and accurate results\",\n \"As a user, I want the search engine to summarize the search results for easier understanding\"\n ],\n \"Competitive Analysis\": [],\n \"Competitive Quadrant Chart\": \"\",\n \"Requirement Analysis\": \"\",\n \"Requirement Pool\": [],\n \"UI Design draft\": \"\",\n \"Anything UNCLEAR\": \"\"\n}" } \ No newline at end of file diff --git a/tests/metagpt/roles/mock.py b/tests/metagpt/roles/mock.py index f72ac484e..40e2f8c07 100644 --- a/tests/metagpt/roles/mock.py +++ b/tests/metagpt/roles/mock.py @@ -284,4 +284,6 @@ class MockMessages: prd = Message(role="Product Manager", content=PRD, cause_by=WritePRD) system_design = Message(role="Architect", content=SYSTEM_DESIGN, cause_by=WriteDesign) tasks = Message(role="Project Manager", content=TASKS, cause_by=WriteTasks) - json_tasks = Message(role="Project Manager", content=json.dumps(JSON_TASKS), cause_by=WriteTasks) + json_tasks = Message( + role="Project Manager", content=json.dumps(JSON_TASKS, ensure_ascii=False), cause_by=WriteTasks + ) From fd11f46587c98bdca67773b289f75dd9c5d1b7ae Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?=E8=8E=98=E6=9D=83=20=E9=A9=AC?= Date: Mon, 8 Jan 2024 15:19:16 +0800 Subject: [PATCH 4/7] fixbug: unit test --- tests/metagpt/actions/test_skill_action.py | 8 ++++++-- tests/metagpt/learn/test_text_to_image.py | 10 +++++++++- 2 files changed, 15 insertions(+), 3 deletions(-) diff --git a/tests/metagpt/actions/test_skill_action.py b/tests/metagpt/actions/test_skill_action.py index 0e0d5d5aa..69cd8129d 100644 --- a/tests/metagpt/actions/test_skill_action.py +++ b/tests/metagpt/actions/test_skill_action.py @@ -47,7 +47,10 @@ class TestSkillAction: assert args.get("size_type") == "512x512" @pytest.mark.asyncio - async def test_parser_action(self): + async def test_parser_action(self, mocker): + # mock + mocker.patch("metagpt.learn.text_to_image", return_value="https://mock.com/xxx") + parser_action = ArgumentsParingAction(skill=self.skill, ask="Draw an apple") rsp = await parser_action.run() assert rsp @@ -80,7 +83,8 @@ class TestSkillAction: @pytest.mark.asyncio async def test_skill_action_error(self): action = SkillAction(skill=self.skill, args={}) - await action.run() + rsp = await action.run() + assert "Error" in rsp.content if __name__ == "__main__": diff --git a/tests/metagpt/learn/test_text_to_image.py b/tests/metagpt/learn/test_text_to_image.py index 760b9d09c..1485df5c6 100644 --- a/tests/metagpt/learn/test_text_to_image.py +++ b/tests/metagpt/learn/test_text_to_image.py @@ -12,10 +12,18 @@ import pytest from metagpt.config import CONFIG from metagpt.learn.text_to_image import text_to_image +from metagpt.tools.metagpt_text_to_image import MetaGPTText2Image +from metagpt.tools.openai_text_to_image import OpenAIText2Image +from metagpt.utils.s3 import S3 @pytest.mark.asyncio -async def test_metagpt_llm(): +async def test_text_to_image(mocker): + # mock + mocker.patch.object(MetaGPTText2Image, "text_2_image", return_value=b"mock MetaGPTText2Image") + mocker.patch.object(OpenAIText2Image, "text_2_image", return_value=b"mock OpenAIText2Image") + mocker.patch.object(S3, "cache", return_value="http://mock/s3") + # Prerequisites assert CONFIG.METAGPT_TEXT_TO_IMAGE_MODEL_URL assert CONFIG.OPENAI_API_KEY From 033dc6bd7dfa38f7e1e3991d7536685ab8eb3469 Mon Sep 17 00:00:00 2001 From: yzlin Date: Mon, 8 Jan 2024 15:33:41 +0800 Subject: [PATCH 5/7] add expected rsp and skip unimportant --- tests/data/rsp_cache.json | 6 +++++- tests/metagpt/actions/test_debug_error.py | 13 ++++++++++++- .../metagpt/tools/test_search_engine_meilisearch.py | 1 + 3 files changed, 18 insertions(+), 2 deletions(-) diff --git a/tests/data/rsp_cache.json b/tests/data/rsp_cache.json index 9e9ef2104..db452f676 100644 --- a/tests/data/rsp_cache.json +++ b/tests/data/rsp_cache.json @@ -137,5 +137,9 @@ "\nNOTICE\nRole: You are a professional engineer; the main goal is to write google-style, elegant, modular, easy to read and maintain code\nLanguage: Please use the same language as the user requirement, but the title and code should be still in English. For example, if the user speaks Chinese, the specific text of your answer should also be in Chinese.\nATTENTION: Use '##' to SPLIT SECTIONS, not '#'. Output format carefully referenced \"Format example\".\n\n# Context\n## Design\n## Project name\n```python\n\"smart_search_engine\"\n```\n\n## Task list:\n```python\n[\n \"smart_search_engine/__init__.py\",\n \"smart_search_engine/main.py\",\n \"smart_search_engine/search.py\",\n \"smart_search_engine/index.py\",\n \"smart_search_engine/ranking.py\",\n \"smart_search_engine/summary.py\",\n \"smart_search_engine/knowledge_base.py\",\n \"smart_search_engine/interface.py\",\n \"smart_search_engine/user_feedback.py\",\n \"smart_search_engine/security.py\",\n \"smart_search_engine/testing.py\",\n \"smart_search_engine/monitoring.py\"\n]\n```\n\n## Data structures and interfaces\n```mermaid\nclassDiagram\n class Main {\n -SearchEngine search_engine\n +main() str\n }\n class SearchEngine {\n -Index index\n -Ranking ranking\n -Summary summary\n +search(query: str) str\n }\n class Index {\n -KnowledgeBase knowledge_base\n +create_index(data: dict)\n +query_index(query: str) list\n }\n class Ranking {\n +rank_results(results: list) list\n }\n class Summary {\n +summarize_results(results: list) str\n }\n class KnowledgeBase {\n +update(data: dict)\n +fetch_data(query: str) dict\n }\n Main --> SearchEngine\n SearchEngine --> Index\n SearchEngine --> Ranking\n SearchEngine --> Summary\n Index --> KnowledgeBase\n```\n\n## Program call flow\n```mermaid\nsequenceDiagram\n participant M as Main\n participant SE as SearchEngine\n participant I as Index\n participant R as Ranking\n participant S as Summary\n participant KB as KnowledgeBase\n M->>SE: search(query)\n SE->>I: query_index(query)\n I->>KB: fetch_data(query)\n KB-->>I: return data\n I-->>SE: return results\n SE->>R: rank_results(results)\n R-->>SE: return ranked_results\n SE->>S: summarize_results(ranked_results)\n S-->>SE: return summary\n SE-->>M: return summary\n```\n\n\n## Tasks\n{\"Logic Analysis\": \"\\n 在这个项目中，所有的模块都依赖于“SearchEngine”类，这是主入口，其他的模块（Index、Ranking和Summary）都通过它交互。另外，\\\"Index\\\"类又依赖于\\\"KnowledgeBase\\\"类，因为它需要从知识库中获取数据。\\n\\n- \\\"main.py\\\"包含\\\"Main\\\"类，是程序的入口点，它调用\\\"SearchEngine\\\"进行搜索操作，所以在其他任何模块之前，\\\"SearchEngine\\\"必须首先被定义。\\n- \\\"search.py\\\"定义了\\\"SearchEngine\\\"类，它依赖于\\\"Index\\\"、\\\"Ranking\\\"和\\\"Summary\\\"，因此，这些模块需要在\\\"search.py\\\"之前定义。\\n- \\\"index.py\\\"定义了\\\"Index\\\"类，它从\\\"knowledge_base.py\\\"获取数据来创建索引，所以\\\"knowledge_base.py\\\"需要在\\\"index.py\\\"之前定义。\\n- \\\"ranking.py\\\"和\\\"summary.py\\\"相对独立，只需确保在\\\"search.py\\\"之前定义。\\n- \\\"knowledge_base.py\\\"是独立的模块，可以优先开发。\\n- \\\"interface.py\\\"、\\\"user_feedback.py\\\"、\\\"security.py\\\"、\\\"testing.py\\\"和\\\"monitoring.py\\\"看起来像是功能辅助模块，可以在主要功能模块开发完成后并行开发。\\n \", \"Task list\": [\"smart_search_engine/knowledge_base.py\", \"smart_search_engine/index.py\", \"smart_search_engine/ranking.py\", \"smart_search_engine/summary.py\", \"smart_search_engine/search.py\", \"smart_search_engine/main.py\", \"smart_search_engine/interface.py\", \"smart_search_engine/user_feedback.py\", \"smart_search_engine/security.py\", \"smart_search_engine/testing.py\", \"smart_search_engine/monitoring.py\"]}\n\n## Legacy Code\n```Code\n----- smart_search_engine/knowledge_base.py\n## smart_search_engine/knowledge_base.py\n\nclass KnowledgeBase:\n def __init__(self):\n self.data = {}\n\n def update(self, data: dict):\n \"\"\"\n Update the knowledge base with new data.\n\n Args:\n data (dict): The new data to be added to the knowledge base.\n \"\"\"\n self.data.update(data)\n\n def fetch_data(self, query: str) -> dict:\n \"\"\"\n Fetch data from the knowledge base based on the given query.\n\n Args:\n query (str): The query to search for in the knowledge base.\n\n Returns:\n dict: The data matching the query.\n \"\"\"\n return self.data.get(query, {})\n\n----- smart_search_engine/index.py\n## smart_search_engine/index.py\n\nfrom smart_search_engine.knowledge_base import KnowledgeBase\n\nclass Index:\n def __init__(self):\n self.knowledge_base = KnowledgeBase()\n self.index = {}\n\n def create_index(self, data: dict):\n \"\"\"\n Create an index based on the given data.\n\n Args:\n data (dict): The data to be indexed.\n \"\"\"\n self.knowledge_base.update(data)\n self.index = {}\n\n for query, _ in data.items():\n results = self.knowledge_base.fetch_data(query)\n self.index[query] = results\n\n def query_index(self, query: str) -> list:\n \"\"\"\n Query the index based on the given query.\n\n Args:\n query (str): The query to search for in the index.\n\n Returns:\n list: The results matching the query.\n \"\"\"\n if query in self.index:\n return self.index[query]\n else:\n return []\n\n----- smart_search_engine/ranking.py\n## smart_search_engine/ranking.py\n\nclass Ranking:\n def rank_results(self, results: list) -> list:\n \"\"\"\n Rank the search results based on relevance.\n\n Args:\n results (list): The search results to be ranked.\n\n Returns:\n list: The ranked search results.\n \"\"\"\n ranked_results = sorted(results, key=lambda x: x['relevance'], reverse=True)\n return ranked_results\n\n----- smart_search_engine/summary.py\n## smart_search_engine/summary.py\n\nclass Summary:\n def summarize_results(self, results: list) -> str:\n \"\"\"\n Summarize the search results into a single string.\n\n Args:\n results (list): The search results to be summarized.\n\n Returns:\n str: The summarized search results.\n \"\"\"\n summary = \"\"\n for result in results:\n summary += result['summary'] + \"\\n\"\n return summary.strip()\n\n----- smart_search_engine/search.py\n## smart_search_engine/search.py\n\nfrom smart_search_engine.index import Index\nfrom smart_search_engine.ranking import Ranking\nfrom smart_search_engine.summary import Summary\n\nclass SearchEngine:\n def __init__(self):\n self.index = Index()\n self.ranking = Ranking()\n self.summary = Summary()\n\n def search(self, query: str) -> str:\n \"\"\"\n Perform a search based on the given query.\n\n Args:\n query (str): The query to search for.\n\n Returns:\n str: The summarized search results.\n \"\"\"\n results = self.index.query_index(query)\n ranked_results = self.ranking.rank_results(results)\n summary = self.summary.summarize_results(ranked_results)\n return summary\n\n----- smart_search_engine/main.py\n## smart_search_engine/main.py\n\nfrom smart_search_engine.search import SearchEngine\n\nclass Main:\n def __init__(self):\n self.search_engine = SearchEngine()\n\n def main(self) -> str:\n \"\"\"\n Main function to perform a search based on user input.\n\n Returns:\n str: The summarized search results.\n \"\"\"\n query = input(\"Enter your search query: \")\n summary = self.search_engine.search(query)\n return summary\n\nif __name__ == \"__main__\":\n main = Main()\n summary = main.main()\n print(summary)\n\n----- smart_search_engine/interface.py\n## smart_search_engine/interface.py\n\nfrom smart_search_engine.search import SearchEngine\n\nclass Interface:\n def __init__(self):\n self.search_engine = SearchEngine()\n\n def run(self):\n \"\"\"\n Run the search engine interface.\n \"\"\"\n while True:\n query = input(\"Enter your search query (or 'exit' to quit): \")\n if query == \"exit\":\n break\n summary = self.search_engine.search(query)\n print(summary)\n\nif __name__ == \"__main__\":\n interface = Interface()\n interface.run()\n\n----- smart_search_engine/user_feedback.py\n## smart_search_engine/user_feedback.py\n\nclass UserFeedback:\n def __init__(self):\n self.feedback = []\n\n def add_feedback(self, query: str, relevance: int):\n \"\"\"\n Add user feedback for a search query.\n\n Args:\n query (str): The search query.\n relevance (int): The relevance score provided by the user.\n \"\"\"\n feedback = {\n 'query': query,\n 'relevance': relevance\n }\n self.feedback.append(feedback)\n\n def get_feedback(self) -> list:\n \"\"\"\n Get the user feedback.\n\n Returns:\n list: The user feedback.\n \"\"\"\n return self.feedback\n\n```\n\n## Debug logs\n```text\n\n\n\n```\n\n## Bug Feedback logs\n```text\n\n```\n\n# Format example\n## Code: smart_search_engine/security.py\n```python\n## smart_search_engine/security.py\n...\n```\n\n# Instruction: Based on the context, follow \"Format example\", write code.\n\n## Code: smart_search_engine/security.py. Write code with triple quoto, based on the following attentions and context.\n1. Only One file: do your best to implement THIS ONLY ONE FILE.\n2. COMPLETE CODE: Your code will be part of the entire project, so please implement complete, reliable, reusable code snippets.\n3. Set default value: If there is any setting, ALWAYS SET A DEFAULT VALUE, ALWAYS USE STRONG TYPE AND EXPLICIT VARIABLE. AVOID circular import.\n4. Follow design: YOU MUST FOLLOW \"Data structures and interfaces\". DONT CHANGE ANY DESIGN. Do not use public member functions that do not exist in your design.\n5. CAREFULLY CHECK THAT YOU DONT MISS ANY NECESSARY CLASS/FUNCTION IN THIS FILE.\n6. Before using a external variable/module, make sure you import it first.\n7. Write out EVERY CODE DETAIL, DON'T LEAVE TODO.\n\n": "```python\n## smart_search_engine/security.py\n\nclass Security:\n def __init__(self):\n self.user_feedback = UserFeedback()\n\n def check_user_feedback(self, query: str) -> bool:\n \"\"\"\n Check if the user has provided feedback for the given query.\n\n Args:\n query (str): The search query.\n\n Returns:\n bool: True if the user has provided feedback, False otherwise.\n \"\"\"\n feedback = self.user_feedback.get_feedback()\n for item in feedback:\n if item['query'] == query:\n return True\n return False\n\n def get_user_feedback(self, query: str) -> int:\n \"\"\"\n Get the relevance score provided by the user for the given query.\n\n Args:\n query (str): The search query.\n\n Returns:\n int: The relevance score provided by the user, or None if no feedback is found.\n \"\"\"\n feedback = self.user_feedback.get_feedback()\n for item in feedback:\n if item['query'] == query:\n return item['relevance']\n return None\n\n def add_user_feedback(self, query: str, relevance: int):\n \"\"\"\n Add user feedback for the given query.\n\n Args:\n query (str): The search query.\n relevance (int): The relevance score provided by the user.\n \"\"\"\n self.user_feedback.add_feedback(query, relevance)\n```\n", "\nNOTICE\nRole: You are a professional engineer; the main goal is to write google-style, elegant, modular, easy to read and maintain code\nLanguage: Please use the same language as the user requirement, but the title and code should be still in English. For example, if the user speaks Chinese, the specific text of your answer should also be in Chinese.\nATTENTION: Use '##' to SPLIT SECTIONS, not '#'. Output format carefully referenced \"Format example\".\n\n# Context\n## Design\n## Project name\n```python\n\"smart_search_engine\"\n```\n\n## Task list:\n```python\n[\n \"smart_search_engine/__init__.py\",\n \"smart_search_engine/main.py\",\n \"smart_search_engine/search.py\",\n \"smart_search_engine/index.py\",\n \"smart_search_engine/ranking.py\",\n \"smart_search_engine/summary.py\",\n \"smart_search_engine/knowledge_base.py\",\n \"smart_search_engine/interface.py\",\n \"smart_search_engine/user_feedback.py\",\n \"smart_search_engine/security.py\",\n \"smart_search_engine/testing.py\",\n \"smart_search_engine/monitoring.py\"\n]\n```\n\n## Data structures and interfaces\n```mermaid\nclassDiagram\n class Main {\n -SearchEngine search_engine\n +main() str\n }\n class SearchEngine {\n -Index index\n -Ranking ranking\n -Summary summary\n +search(query: str) str\n }\n class Index {\n -KnowledgeBase knowledge_base\n +create_index(data: dict)\n +query_index(query: str) list\n }\n class Ranking {\n +rank_results(results: list) list\n }\n class Summary {\n +summarize_results(results: list) str\n }\n class KnowledgeBase {\n +update(data: dict)\n +fetch_data(query: str) dict\n }\n Main --> SearchEngine\n SearchEngine --> Index\n SearchEngine --> Ranking\n SearchEngine --> Summary\n Index --> KnowledgeBase\n```\n\n## Program call flow\n```mermaid\nsequenceDiagram\n participant M as Main\n participant SE as SearchEngine\n participant I as Index\n participant R as Ranking\n participant S as Summary\n participant KB as KnowledgeBase\n M->>SE: search(query)\n SE->>I: query_index(query)\n I->>KB: fetch_data(query)\n KB-->>I: return data\n I-->>SE: return results\n SE->>R: rank_results(results)\n R-->>SE: return ranked_results\n SE->>S: summarize_results(ranked_results)\n S-->>SE: return summary\n SE-->>M: return summary\n```\n\n\n## Tasks\n{\"Logic Analysis\": \"\\n 在这个项目中，所有的模块都依赖于“SearchEngine”类，这是主入口，其他的模块（Index、Ranking和Summary）都通过它交互。另外，\\\"Index\\\"类又依赖于\\\"KnowledgeBase\\\"类，因为它需要从知识库中获取数据。\\n\\n- \\\"main.py\\\"包含\\\"Main\\\"类，是程序的入口点，它调用\\\"SearchEngine\\\"进行搜索操作，所以在其他任何模块之前，\\\"SearchEngine\\\"必须首先被定义。\\n- \\\"search.py\\\"定义了\\\"SearchEngine\\\"类，它依赖于\\\"Index\\\"、\\\"Ranking\\\"和\\\"Summary\\\"，因此，这些模块需要在\\\"search.py\\\"之前定义。\\n- \\\"index.py\\\"定义了\\\"Index\\\"类，它从\\\"knowledge_base.py\\\"获取数据来创建索引，所以\\\"knowledge_base.py\\\"需要在\\\"index.py\\\"之前定义。\\n- \\\"ranking.py\\\"和\\\"summary.py\\\"相对独立，只需确保在\\\"search.py\\\"之前定义。\\n- \\\"knowledge_base.py\\\"是独立的模块，可以优先开发。\\n- \\\"interface.py\\\"、\\\"user_feedback.py\\\"、\\\"security.py\\\"、\\\"testing.py\\\"和\\\"monitoring.py\\\"看起来像是功能辅助模块，可以在主要功能模块开发完成后并行开发。\\n \", \"Task list\": [\"smart_search_engine/knowledge_base.py\", \"smart_search_engine/index.py\", \"smart_search_engine/ranking.py\", \"smart_search_engine/summary.py\", \"smart_search_engine/search.py\", \"smart_search_engine/main.py\", \"smart_search_engine/interface.py\", \"smart_search_engine/user_feedback.py\", \"smart_search_engine/security.py\", \"smart_search_engine/testing.py\", \"smart_search_engine/monitoring.py\"]}\n\n## Legacy Code\n```Code\n----- smart_search_engine/knowledge_base.py\n## smart_search_engine/knowledge_base.py\n\nclass KnowledgeBase:\n def __init__(self):\n self.data = {}\n\n def update(self, data: dict):\n \"\"\"\n Update the knowledge base with new data.\n\n Args:\n data (dict): The new data to be added to the knowledge base.\n \"\"\"\n self.data.update(data)\n\n def fetch_data(self, query: str) -> dict:\n \"\"\"\n Fetch data from the knowledge base based on the given query.\n\n Args:\n query (str): The query to search for in the knowledge base.\n\n Returns:\n dict: The data matching the query.\n \"\"\"\n return self.data.get(query, {})\n\n----- smart_search_engine/index.py\n## smart_search_engine/index.py\n\nfrom smart_search_engine.knowledge_base import KnowledgeBase\n\nclass Index:\n def __init__(self):\n self.knowledge_base = KnowledgeBase()\n self.index = {}\n\n def create_index(self, data: dict):\n \"\"\"\n Create an index based on the given data.\n\n Args:\n data (dict): The data to be indexed.\n \"\"\"\n self.knowledge_base.update(data)\n self.index = {}\n\n for query, _ in data.items():\n results = self.knowledge_base.fetch_data(query)\n self.index[query] = results\n\n def query_index(self, query: str) -> list:\n \"\"\"\n Query the index based on the given query.\n\n Args:\n query (str): The query to search for in the index.\n\n Returns:\n list: The results matching the query.\n \"\"\"\n if query in self.index:\n return self.index[query]\n else:\n return []\n\n----- smart_search_engine/ranking.py\n## smart_search_engine/ranking.py\n\nclass Ranking:\n def rank_results(self, results: list) -> list:\n \"\"\"\n Rank the search results based on relevance.\n\n Args:\n results (list): The search results to be ranked.\n\n Returns:\n list: The ranked search results.\n \"\"\"\n ranked_results = sorted(results, key=lambda x: x['relevance'], reverse=True)\n return ranked_results\n\n----- smart_search_engine/summary.py\n## smart_search_engine/summary.py\n\nclass Summary:\n def summarize_results(self, results: list) -> str:\n \"\"\"\n Summarize the search results into a single string.\n\n Args:\n results (list): The search results to be summarized.\n\n Returns:\n str: The summarized search results.\n \"\"\"\n summary = \"\"\n for result in results:\n summary += result['summary'] + \"\\n\"\n return summary.strip()\n\n----- smart_search_engine/search.py\n## smart_search_engine/search.py\n\nfrom smart_search_engine.index import Index\nfrom smart_search_engine.ranking import Ranking\nfrom smart_search_engine.summary import Summary\n\nclass SearchEngine:\n def __init__(self):\n self.index = Index()\n self.ranking = Ranking()\n self.summary = Summary()\n\n def search(self, query: str) -> str:\n \"\"\"\n Perform a search based on the given query.\n\n Args:\n query (str): The query to search for.\n\n Returns:\n str: The summarized search results.\n \"\"\"\n results = self.index.query_index(query)\n ranked_results = self.ranking.rank_results(results)\n summary = self.summary.summarize_results(ranked_results)\n return summary\n\n----- smart_search_engine/main.py\n## smart_search_engine/main.py\n\nfrom smart_search_engine.search import SearchEngine\n\nclass Main:\n def __init__(self):\n self.search_engine = SearchEngine()\n\n def main(self) -> str:\n \"\"\"\n Main function to perform a search based on user input.\n\n Returns:\n str: The summarized search results.\n \"\"\"\n query = input(\"Enter your search query: \")\n summary = self.search_engine.search(query)\n return summary\n\nif __name__ == \"__main__\":\n main = Main()\n summary = main.main()\n print(summary)\n\n----- smart_search_engine/interface.py\n## smart_search_engine/interface.py\n\nfrom smart_search_engine.search import SearchEngine\n\nclass Interface:\n def __init__(self):\n self.search_engine = SearchEngine()\n\n def run(self):\n \"\"\"\n Run the search engine interface.\n \"\"\"\n while True:\n query = input(\"Enter your search query (or 'exit' to quit): \")\n if query == \"exit\":\n break\n summary = self.search_engine.search(query)\n print(summary)\n\nif __name__ == \"__main__\":\n interface = Interface()\n interface.run()\n\n----- smart_search_engine/user_feedback.py\n## smart_search_engine/user_feedback.py\n\nclass UserFeedback:\n def __init__(self):\n self.feedback = []\n\n def add_feedback(self, query: str, relevance: int):\n \"\"\"\n Add user feedback for a search query.\n\n Args:\n query (str): The search query.\n relevance (int): The relevance score provided by the user.\n \"\"\"\n feedback = {\n 'query': query,\n 'relevance': relevance\n }\n self.feedback.append(feedback)\n\n def get_feedback(self) -> list:\n \"\"\"\n Get the user feedback.\n\n Returns:\n list: The user feedback.\n \"\"\"\n return self.feedback\n\n----- smart_search_engine/security.py\n## smart_search_engine/security.py\n\nclass Security:\n def __init__(self):\n self.user_feedback = UserFeedback()\n\n def check_user_feedback(self, query: str) -> bool:\n \"\"\"\n Check if the user has provided feedback for the given query.\n\n Args:\n query (str): The search query.\n\n Returns:\n bool: True if the user has provided feedback, False otherwise.\n \"\"\"\n feedback = self.user_feedback.get_feedback()\n for item in feedback:\n if item['query'] == query:\n return True\n return False\n\n def get_user_feedback(self, query: str) -> int:\n \"\"\"\n Get the relevance score provided by the user for the given query.\n\n Args:\n query (str): The search query.\n\n Returns:\n int: The relevance score provided by the user, or None if no feedback is found.\n \"\"\"\n feedback = self.user_feedback.get_feedback()\n for item in feedback:\n if item['query'] == query:\n return item['relevance']\n return None\n\n def add_user_feedback(self, query: str, relevance: int):\n \"\"\"\n Add user feedback for the given query.\n\n Args:\n query (str): The search query.\n relevance (int): The relevance score provided by the user.\n \"\"\"\n self.user_feedback.add_feedback(query, relevance)\n\n```\n\n## Debug logs\n```text\n\n\n\n```\n\n## Bug Feedback logs\n```text\n\n```\n\n# Format example\n## Code: smart_search_engine/testing.py\n```python\n## smart_search_engine/testing.py\n...\n```\n\n# Instruction: Based on the context, follow \"Format example\", write code.\n\n## Code: smart_search_engine/testing.py. Write code with triple quoto, based on the following attentions and context.\n1. Only One file: do your best to implement THIS ONLY ONE FILE.\n2. COMPLETE CODE: Your code will be part of the entire project, so please implement complete, reliable, reusable code snippets.\n3. Set default value: If there is any setting, ALWAYS SET A DEFAULT VALUE, ALWAYS USE STRONG TYPE AND EXPLICIT VARIABLE. AVOID circular import.\n4. Follow design: YOU MUST FOLLOW \"Data structures and interfaces\". DONT CHANGE ANY DESIGN. Do not use public member functions that do not exist in your design.\n5. CAREFULLY CHECK THAT YOU DONT MISS ANY NECESSARY CLASS/FUNCTION IN THIS FILE.\n6. Before using a external variable/module, make sure you import it first.\n7. Write out EVERY CODE DETAIL, DON'T LEAVE TODO.\n\n": "```python\n## smart_search_engine/testing.py\n\nfrom smart_search_engine.search import SearchEngine\nfrom smart_search_engine.index import Index\nfrom smart_search_engine.ranking import Ranking\nfrom smart_search_engine.summary import Summary\nfrom smart_search_engine.knowledge_base import KnowledgeBase\n\nclass Testing:\n def __init__(self):\n self.search_engine = SearchEngine()\n self.index = Index()\n self.ranking = Ranking()\n self.summary = Summary()\n self.knowledge_base = KnowledgeBase()\n\n def test_search_engine(self):\n \"\"\"\n Test the search engine functionality.\n \"\"\"\n # Test case 1: Search for a query that exists in the index\n query1 = \"apple\"\n expected_summary1 = \"Summary of search results for query: apple\"\n self.knowledge_base.update({\"apple\": {\"relevance\": 0.8, \"summary\": \"This is an apple.\"}})\n self.index.create_index({\"apple\": {\"relevance\": 0.8, \"summary\": \"This is an apple.\"}})\n summary1 = self.search_engine.search(query1)\n assert summary1 == expected_summary1, f\"Test case 1 failed: {summary1}\"\n\n # Test case 2: Search for a query that does not exist in the index\n query2 = \"banana\"\n expected_summary2 = \"No results found for query: banana\"\n self.knowledge_base.update({\"apple\": {\"relevance\": 0.8, \"summary\": \"This is an apple.\"}})\n self.index.create_index({\"apple\": {\"relevance\": 0.8, \"summary\": \"This is an apple.\"}})\n summary2 = self.search_engine.search(query2)\n assert summary2 == expected_summary2, f\"Test case 2 failed: {summary2}\"\n\n def test_index(self):\n \"\"\"\n Test the index functionality.\n \"\"\"\n # Test case 1: Create index with valid data\n data1 = {\"apple\": {\"relevance\": 0.8, \"summary\": \"This is an apple.\"}}\n expected_index1 = {\"apple\": {\"relevance\": 0.8, \"summary\": \"This is an apple.\"}}\n self.knowledge_base.update(data1)\n self.index.create_index(data1)\n index1 = self.index.index\n assert index1 == expected_index1, f\"Test case 1 failed: {index1}\"\n\n # Test case 2: Query index with valid query\n query2 = \"apple\"\n expected_results2 = [{\"relevance\": 0.8, \"summary\": \"This is an apple.\"}]\n results2 = self.index.query_index(query2)\n assert results2 == expected_results2, f\"Test case 2 failed: {results2}\"\n\n # Test case 3: Query index with invalid query\n query3 = \"banana\"\n expected_results3 = []\n results3 = self.index.query_index(query3)\n assert results3 == expected_results3, f\"Test case 3 failed: {results3}\"\n\n def test_ranking(self):\n \"\"\"\n Test the ranking functionality.\n \"\"\"\n # Test case 1: Rank results in descending order of relevance\n results1 = [{\"relevance\": 0.8, \"summary\": \"This is an apple.\"}, {\"relevance\": 0.6, \"summary\": \"This is a banana.\"}]\n expected_ranked_results1 = [{\"relevance\": 0.8, \"summary\": \"This is an apple.\"}, {\"relevance\": 0.6, \"summary\": \"This is a banana.\"}]\n ranked_results1 = self.ranking.rank_results(results1)\n assert ranked_results1 == expected_ranked_results1, f\"Test case 1 failed: {ranked_results1}\"\n\n # Test case 2: Rank results in ascending order of relevance\n results2 = [{\"relevance\": 0.6, \"summary\": \"This is a banana.\"}, {\"relevance\": 0.8, \"summary\": \"This is an apple.\"}]\n expected_ranked_results2 = [{\"relevance\": 0.8, \"summary\": \"This is an apple.\"}, {\"relevance\": 0.6, \"summary\": \"This is a banana.\"}]\n ranked_results2 = self.ranking.rank_results(results2)\n assert ranked_results2 == expected_ranked_results2, f\"Test case 2 failed: {ranked_results2}\"\n\n def test_summary(self):\n \"\"\"\n Test the summary functionality.\n \"\"\"\n # Test case 1: Summarize search results into a single string\n results1 = [{\"relevance\": 0.8, \"summary\": \"This is an apple.\"}, {\"relevance\": 0.6, \"summary\": \"This is a banana.\"}]\n expected_summary1 = \"This is an apple.\\nThis is a banana.\"\n summary1 = self.summary.summarize_results(results1)\n assert summary1 == expected_summary1, f\"Test case 1 failed: {summary1}\"\n\n # Test case 2: Summarize empty search results\n results2 = []\n expected_summary2 = \"\"\n summary2 = self.summary.summarize_results(results2)\n assert summary2 == expected_summary2, f\"Test case 2 failed: {summary2}\"\n\n def run_tests(self):\n \"\"\"\n Run all the tests.\n \"\"\"\n self.test_search_engine()\n self.test_index()\n self.test_ranking()\n self.test_summary()\n\nif __name__ == \"__main__\":\n testing = Testing()\n testing.run_tests()\n```\n\nIn the above code, I have implemented a `Testing` class that contains methods to test the functionality of the search engine, index, ranking, and summary modules. Each test case checks the expected output against the actual output and raises an assertion error if they do not match. The `run_tests` method runs all the test cases.", "\nNOTICE\nRole: You are a professional engineer; the main goal is to write google-style, elegant, modular, easy to read and maintain code\nLanguage: Please use the same language as the user requirement, but the title and code should be still in English. For example, if the user speaks Chinese, the specific text of your answer should also be in Chinese.\nATTENTION: Use '##' to SPLIT SECTIONS, not '#'. Output format carefully referenced \"Format example\".\n\n# Context\n## Design\n## Project name\n```python\n\"smart_search_engine\"\n```\n\n## Task list:\n```python\n[\n \"smart_search_engine/__init__.py\",\n \"smart_search_engine/main.py\",\n \"smart_search_engine/search.py\",\n \"smart_search_engine/index.py\",\n \"smart_search_engine/ranking.py\",\n \"smart_search_engine/summary.py\",\n \"smart_search_engine/knowledge_base.py\",\n \"smart_search_engine/interface.py\",\n \"smart_search_engine/user_feedback.py\",\n \"smart_search_engine/security.py\",\n \"smart_search_engine/testing.py\",\n \"smart_search_engine/monitoring.py\"\n]\n```\n\n## Data structures and interfaces\n```mermaid\nclassDiagram\n class Main {\n -SearchEngine search_engine\n +main() str\n }\n class SearchEngine {\n -Index index\n -Ranking ranking\n -Summary summary\n +search(query: str) str\n }\n class Index {\n -KnowledgeBase knowledge_base\n +create_index(data: dict)\n +query_index(query: str) list\n }\n class Ranking {\n +rank_results(results: list) list\n }\n class Summary {\n +summarize_results(results: list) str\n }\n class KnowledgeBase {\n +update(data: dict)\n +fetch_data(query: str) dict\n }\n Main --> SearchEngine\n SearchEngine --> Index\n SearchEngine --> Ranking\n SearchEngine --> Summary\n Index --> KnowledgeBase\n```\n\n## Program call flow\n```mermaid\nsequenceDiagram\n participant M as Main\n participant SE as SearchEngine\n participant I as Index\n participant R as Ranking\n participant S as Summary\n participant KB as KnowledgeBase\n M->>SE: search(query)\n SE->>I: query_index(query)\n I->>KB: fetch_data(query)\n KB-->>I: return data\n I-->>SE: return results\n SE->>R: rank_results(results)\n R-->>SE: return ranked_results\n SE->>S: summarize_results(ranked_results)\n S-->>SE: return summary\n SE-->>M: return summary\n```\n\n\n## Tasks\n{\"Logic Analysis\": \"\\n 在这个项目中，所有的模块都依赖于“SearchEngine”类，这是主入口，其他的模块（Index、Ranking和Summary）都通过它交互。另外，\\\"Index\\\"类又依赖于\\\"KnowledgeBase\\\"类，因为它需要从知识库中获取数据。\\n\\n- \\\"main.py\\\"包含\\\"Main\\\"类，是程序的入口点，它调用\\\"SearchEngine\\\"进行搜索操作，所以在其他任何模块之前，\\\"SearchEngine\\\"必须首先被定义。\\n- \\\"search.py\\\"定义了\\\"SearchEngine\\\"类，它依赖于\\\"Index\\\"、\\\"Ranking\\\"和\\\"Summary\\\"，因此，这些模块需要在\\\"search.py\\\"之前定义。\\n- \\\"index.py\\\"定义了\\\"Index\\\"类，它从\\\"knowledge_base.py\\\"获取数据来创建索引，所以\\\"knowledge_base.py\\\"需要在\\\"index.py\\\"之前定义。\\n- \\\"ranking.py\\\"和\\\"summary.py\\\"相对独立，只需确保在\\\"search.py\\\"之前定义。\\n- \\\"knowledge_base.py\\\"是独立的模块，可以优先开发。\\n- \\\"interface.py\\\"、\\\"user_feedback.py\\\"、\\\"security.py\\\"、\\\"testing.py\\\"和\\\"monitoring.py\\\"看起来像是功能辅助模块，可以在主要功能模块开发完成后并行开发。\\n \", \"Task list\": [\"smart_search_engine/knowledge_base.py\", \"smart_search_engine/index.py\", \"smart_search_engine/ranking.py\", \"smart_search_engine/summary.py\", \"smart_search_engine/search.py\", \"smart_search_engine/main.py\", \"smart_search_engine/interface.py\", \"smart_search_engine/user_feedback.py\", \"smart_search_engine/security.py\", \"smart_search_engine/testing.py\", \"smart_search_engine/monitoring.py\"]}\n\n## Legacy Code\n```Code\n----- smart_search_engine/knowledge_base.py\n## smart_search_engine/knowledge_base.py\n\nclass KnowledgeBase:\n def __init__(self):\n self.data = {}\n\n def update(self, data: dict):\n \"\"\"\n Update the knowledge base with new data.\n\n Args:\n data (dict): The new data to be added to the knowledge base.\n \"\"\"\n self.data.update(data)\n\n def fetch_data(self, query: str) -> dict:\n \"\"\"\n Fetch data from the knowledge base based on the given query.\n\n Args:\n query (str): The query to search for in the knowledge base.\n\n Returns:\n dict: The data matching the query.\n \"\"\"\n return self.data.get(query, {})\n\n----- smart_search_engine/index.py\n## smart_search_engine/index.py\n\nfrom smart_search_engine.knowledge_base import KnowledgeBase\n\nclass Index:\n def __init__(self):\n self.knowledge_base = KnowledgeBase()\n self.index = {}\n\n def create_index(self, data: dict):\n \"\"\"\n Create an index based on the given data.\n\n Args:\n data (dict): The data to be indexed.\n \"\"\"\n self.knowledge_base.update(data)\n self.index = {}\n\n for query, _ in data.items():\n results = self.knowledge_base.fetch_data(query)\n self.index[query] = results\n\n def query_index(self, query: str) -> list:\n \"\"\"\n Query the index based on the given query.\n\n Args:\n query (str): The query to search for in the index.\n\n Returns:\n list: The results matching the query.\n \"\"\"\n if query in self.index:\n return self.index[query]\n else:\n return []\n\n----- smart_search_engine/ranking.py\n## smart_search_engine/ranking.py\n\nclass Ranking:\n def rank_results(self, results: list) -> list:\n \"\"\"\n Rank the search results based on relevance.\n\n Args:\n results (list): The search results to be ranked.\n\n Returns:\n list: The ranked search results.\n \"\"\"\n ranked_results = sorted(results, key=lambda x: x['relevance'], reverse=True)\n return ranked_results\n\n----- smart_search_engine/summary.py\n## smart_search_engine/summary.py\n\nclass Summary:\n def summarize_results(self, results: list) -> str:\n \"\"\"\n Summarize the search results into a single string.\n\n Args:\n results (list): The search results to be summarized.\n\n Returns:\n str: The summarized search results.\n \"\"\"\n summary = \"\"\n for result in results:\n summary += result['summary'] + \"\\n\"\n return summary.strip()\n\n----- smart_search_engine/search.py\n## smart_search_engine/search.py\n\nfrom smart_search_engine.index import Index\nfrom smart_search_engine.ranking import Ranking\nfrom smart_search_engine.summary import Summary\n\nclass SearchEngine:\n def __init__(self):\n self.index = Index()\n self.ranking = Ranking()\n self.summary = Summary()\n\n def search(self, query: str) -> str:\n \"\"\"\n Perform a search based on the given query.\n\n Args:\n query (str): The query to search for.\n\n Returns:\n str: The summarized search results.\n \"\"\"\n results = self.index.query_index(query)\n ranked_results = self.ranking.rank_results(results)\n summary = self.summary.summarize_results(ranked_results)\n return summary\n\n----- smart_search_engine/main.py\n## smart_search_engine/main.py\n\nfrom smart_search_engine.search import SearchEngine\n\nclass Main:\n def __init__(self):\n self.search_engine = SearchEngine()\n\n def main(self) -> str:\n \"\"\"\n Main function to perform a search based on user input.\n\n Returns:\n str: The summarized search results.\n \"\"\"\n query = input(\"Enter your search query: \")\n summary = self.search_engine.search(query)\n return summary\n\nif __name__ == \"__main__\":\n main = Main()\n summary = main.main()\n print(summary)\n\n----- smart_search_engine/interface.py\n## smart_search_engine/interface.py\n\nfrom smart_search_engine.search import SearchEngine\n\nclass Interface:\n def __init__(self):\n self.search_engine = SearchEngine()\n\n def run(self):\n \"\"\"\n Run the search engine interface.\n \"\"\"\n while True:\n query = input(\"Enter your search query (or 'exit' to quit): \")\n if query == \"exit\":\n break\n summary = self.search_engine.search(query)\n print(summary)\n\nif __name__ == \"__main__\":\n interface = Interface()\n interface.run()\n\n----- smart_search_engine/user_feedback.py\n## smart_search_engine/user_feedback.py\n\nclass UserFeedback:\n def __init__(self):\n self.feedback = []\n\n def add_feedback(self, query: str, relevance: int):\n \"\"\"\n Add user feedback for a search query.\n\n Args:\n query (str): The search query.\n relevance (int): The relevance score provided by the user.\n \"\"\"\n feedback = {\n 'query': query,\n 'relevance': relevance\n }\n self.feedback.append(feedback)\n\n def get_feedback(self) -> list:\n \"\"\"\n Get the user feedback.\n\n Returns:\n list: The user feedback.\n \"\"\"\n return self.feedback\n\n----- smart_search_engine/security.py\n## smart_search_engine/security.py\n\nclass Security:\n def __init__(self):\n self.user_feedback = UserFeedback()\n\n def check_user_feedback(self, query: str) -> bool:\n \"\"\"\n Check if the user has provided feedback for the given query.\n\n Args:\n query (str): The search query.\n\n Returns:\n bool: True if the user has provided feedback, False otherwise.\n \"\"\"\n feedback = self.user_feedback.get_feedback()\n for item in feedback:\n if item['query'] == query:\n return True\n return False\n\n def get_user_feedback(self, query: str) -> int:\n \"\"\"\n Get the relevance score provided by the user for the given query.\n\n Args:\n query (str): The search query.\n\n Returns:\n int: The relevance score provided by the user, or None if no feedback is found.\n \"\"\"\n feedback = self.user_feedback.get_feedback()\n for item in feedback:\n if item['query'] == query:\n return item['relevance']\n return None\n\n def add_user_feedback(self, query: str, relevance: int):\n \"\"\"\n Add user feedback for the given query.\n\n Args:\n query (str): The search query.\n relevance (int): The relevance score provided by the user.\n \"\"\"\n self.user_feedback.add_feedback(query, relevance)\n\n----- smart_search_engine/testing.py\n## smart_search_engine/testing.py\n\nfrom smart_search_engine.search import SearchEngine\nfrom smart_search_engine.index import Index\nfrom smart_search_engine.ranking import Ranking\nfrom smart_search_engine.summary import Summary\nfrom smart_search_engine.knowledge_base import KnowledgeBase\n\nclass Testing:\n def __init__(self):\n self.search_engine = SearchEngine()\n self.index = Index()\n self.ranking = Ranking()\n self.summary = Summary()\n self.knowledge_base = KnowledgeBase()\n\n def test_search_engine(self):\n \"\"\"\n Test the search engine functionality.\n \"\"\"\n # Test case 1: Search for a query that exists in the index\n query1 = \"apple\"\n expected_summary1 = \"Summary of search results for query: apple\"\n self.knowledge_base.update({\"apple\": {\"relevance\": 0.8, \"summary\": \"This is an apple.\"}})\n self.index.create_index({\"apple\": {\"relevance\": 0.8, \"summary\": \"This is an apple.\"}})\n summary1 = self.search_engine.search(query1)\n assert summary1 == expected_summary1, f\"Test case 1 failed: {summary1}\"\n\n # Test case 2: Search for a query that does not exist in the index\n query2 = \"banana\"\n expected_summary2 = \"No results found for query: banana\"\n self.knowledge_base.update({\"apple\": {\"relevance\": 0.8, \"summary\": \"This is an apple.\"}})\n self.index.create_index({\"apple\": {\"relevance\": 0.8, \"summary\": \"This is an apple.\"}})\n summary2 = self.search_engine.search(query2)\n assert summary2 == expected_summary2, f\"Test case 2 failed: {summary2}\"\n\n def test_index(self):\n \"\"\"\n Test the index functionality.\n \"\"\"\n # Test case 1: Create index with valid data\n data1 = {\"apple\": {\"relevance\": 0.8, \"summary\": \"This is an apple.\"}}\n expected_index1 = {\"apple\": {\"relevance\": 0.8, \"summary\": \"This is an apple.\"}}\n self.knowledge_base.update(data1)\n self.index.create_index(data1)\n index1 = self.index.index\n assert index1 == expected_index1, f\"Test case 1 failed: {index1}\"\n\n # Test case 2: Query index with valid query\n query2 = \"apple\"\n expected_results2 = [{\"relevance\": 0.8, \"summary\": \"This is an apple.\"}]\n results2 = self.index.query_index(query2)\n assert results2 == expected_results2, f\"Test case 2 failed: {results2}\"\n\n # Test case 3: Query index with invalid query\n query3 = \"banana\"\n expected_results3 = []\n results3 = self.index.query_index(query3)\n assert results3 == expected_results3, f\"Test case 3 failed: {results3}\"\n\n def test_ranking(self):\n \"\"\"\n Test the ranking functionality.\n \"\"\"\n # Test case 1: Rank results in descending order of relevance\n results1 = [{\"relevance\": 0.8, \"summary\": \"This is an apple.\"}, {\"relevance\": 0.6, \"summary\": \"This is a banana.\"}]\n expected_ranked_results1 = [{\"relevance\": 0.8, \"summary\": \"This is an apple.\"}, {\"relevance\": 0.6, \"summary\": \"This is a banana.\"}]\n ranked_results1 = self.ranking.rank_results(results1)\n assert ranked_results1 == expected_ranked_results1, f\"Test case 1 failed: {ranked_results1}\"\n\n # Test case 2: Rank results in ascending order of relevance\n results2 = [{\"relevance\": 0.6, \"summary\": \"This is a banana.\"}, {\"relevance\": 0.8, \"summary\": \"This is an apple.\"}]\n expected_ranked_results2 = [{\"relevance\": 0.8, \"summary\": \"This is an apple.\"}, {\"relevance\": 0.6, \"summary\": \"This is a banana.\"}]\n ranked_results2 = self.ranking.rank_results(results2)\n assert ranked_results2 == expected_ranked_results2, f\"Test case 2 failed: {ranked_results2}\"\n\n def test_summary(self):\n \"\"\"\n Test the summary functionality.\n \"\"\"\n # Test case 1: Summarize search results into a single string\n results1 = [{\"relevance\": 0.8, \"summary\": \"This is an apple.\"}, {\"relevance\": 0.6, \"summary\": \"This is a banana.\"}]\n expected_summary1 = \"This is an apple.\\nThis is a banana.\"\n summary1 = self.summary.summarize_results(results1)\n assert summary1 == expected_summary1, f\"Test case 1 failed: {summary1}\"\n\n # Test case 2: Summarize empty search results\n results2 = []\n expected_summary2 = \"\"\n summary2 = self.summary.summarize_results(results2)\n assert summary2 == expected_summary2, f\"Test case 2 failed: {summary2}\"\n\n def run_tests(self):\n \"\"\"\n Run all the tests.\n \"\"\"\n self.test_search_engine()\n self.test_index()\n self.test_ranking()\n self.test_summary()\n\nif __name__ == \"__main__\":\n testing = Testing()\n testing.run_tests()\n\n```\n\n## Debug logs\n```text\n\n\n\n```\n\n## Bug Feedback logs\n```text\n\n```\n\n# Format example\n## Code: smart_search_engine/monitoring.py\n```python\n## smart_search_engine/monitoring.py\n...\n```\n\n# Instruction: Based on the context, follow \"Format example\", write code.\n\n## Code: smart_search_engine/monitoring.py. Write code with triple quoto, based on the following attentions and context.\n1. Only One file: do your best to implement THIS ONLY ONE FILE.\n2. COMPLETE CODE: Your code will be part of the entire project, so please implement complete, reliable, reusable code snippets.\n3. Set default value: If there is any setting, ALWAYS SET A DEFAULT VALUE, ALWAYS USE STRONG TYPE AND EXPLICIT VARIABLE. AVOID circular import.\n4. Follow design: YOU MUST FOLLOW \"Data structures and interfaces\". DONT CHANGE ANY DESIGN. Do not use public member functions that do not exist in your design.\n5. CAREFULLY CHECK THAT YOU DONT MISS ANY NECESSARY CLASS/FUNCTION IN THIS FILE.\n6. Before using a external variable/module, make sure you import it first.\n7. Write out EVERY CODE DETAIL, DON'T LEAVE TODO.\n\n": "```python\n## smart_search_engine/monitoring.py\n\nimport time\n\nclass Monitoring:\n def __init__(self):\n self.start_time = None\n self.end_time = None\n\n def start(self):\n \"\"\"\n Start the monitoring timer.\n \"\"\"\n self.start_time = time.time()\n\n def stop(self):\n \"\"\"\n Stop the monitoring timer.\n \"\"\"\n self.end_time = time.time()\n\n def get_elapsed_time(self) -> float:\n \"\"\"\n Get the elapsed time in seconds.\n\n Returns:\n float: The elapsed time in seconds.\n \"\"\"\n if self.start_time is None or self.end_time is None:\n raise Exception(\"Monitoring timer has not been started or stopped.\")\n return self.end_time - self.start_time\n```\n\n## Explanation:\nI have implemented the `Monitoring` class in the `smart_search_engine/monitoring.py` file. This class is responsible for starting and stopping a timer to monitor the elapsed time of a process. \n\nThe `Monitoring` class has the following methods:\n- `start()`: Starts the monitoring timer by setting the `start_time` attribute to the current time.\n- `stop()`: Stops the monitoring timer by setting the `end_time` attribute to the current time.\n- `get_elapsed_time()`: Calculates and returns the elapsed time in seconds by subtracting the `start_time` from the `end_time`. If the monitoring timer has not been started or stopped, an exception is raised.\n\nThis implementation follows the design specified in the `Data structures and interfaces` section.", - "\n## context\n\n### Project Name\n\n\n### Original Requirements\n['开发一个基于大语言模型与私有知识库的搜索引擎，希望可以基于大语言模型进行搜索总结']\n\n### Search Information\n-\n\n\n-----\n\n## format example\n[CONTENT]\n{\n \"Language\": \"en_us\",\n \"Programming Language\": \"Python\",\n \"Original Requirements\": \"Create a 2048 game\",\n \"Project Name\": \"game_2048\",\n \"Product Goals\": [\n \"Create an engaging user experience\",\n \"Improve accessibility, be responsive\",\n \"More beautiful UI\"\n ],\n \"User Stories\": [\n \"As a player, I want to be able to choose difficulty levels\",\n \"As a player, I want to see my score after each game\",\n \"As a player, I want to get restart button when I lose\",\n \"As a player, I want to see beautiful UI that make me feel good\",\n \"As a player, I want to play game via mobile phone\"\n ],\n \"Competitive Analysis\": [\n \"2048 Game A: Simple interface, lacks responsive features\",\n \"play2048.co: Beautiful and responsive UI with my best score shown\",\n \"2048game.com: Responsive UI with my best score shown, but many ads\"\n ],\n \"Competitive Quadrant Chart\": \"quadrantChart\\n title \\\"Reach and engagement of campaigns\\\"\\n x-axis \\\"Low Reach\\\" --> \\\"High Reach\\\"\\n y-axis \\\"Low Engagement\\\" --> \\\"High Engagement\\\"\\n quadrant-1 \\\"We should expand\\\"\\n quadrant-2 \\\"Need to promote\\\"\\n quadrant-3 \\\"Re-evaluate\\\"\\n quadrant-4 \\\"May be improved\\\"\\n \\\"Campaign A\\\": [0.3, 0.6]\\n \\\"Campaign B\\\": [0.45, 0.23]\\n \\\"Campaign C\\\": [0.57, 0.69]\\n \\\"Campaign D\\\": [0.78, 0.34]\\n \\\"Campaign E\\\": [0.40, 0.34]\\n \\\"Campaign F\\\": [0.35, 0.78]\\n \\\"Our Target Product\\\": [0.5, 0.6]\",\n \"Requirement Analysis\": \"\",\n \"Requirement Pool\": [\n [\n \"P0\",\n \"The main code ...\"\n ],\n [\n \"P0\",\n \"The game algorithm ...\"\n ]\n ],\n \"UI Design draft\": \"Basic function description with a simple style and layout.\",\n \"Anything UNCLEAR\": \"\"\n}\n[/CONTENT]\n\n## nodes: \": # \"\n- Language: # Provide the language used in the project, typically matching the user's requirement language.\n- Programming Language: # Python/JavaScript or other mainstream programming language.\n- Original Requirements: # Place the original user's requirements here.\n- Project Name: # According to the content of \"Original Requirements,\" name the project using snake case style , like 'game_2048' or 'simple_crm.\n- Product Goals: typing.List[str] # Provide up to three clear, orthogonal product goals.\n- User Stories: typing.List[str] # Provide up to 3 to 5 scenario-based user stories.\n- Competitive Analysis: typing.List[str] # Provide 5 to 7 competitive products.\n- Competitive Quadrant Chart: # Use mermaid quadrantChart syntax. Distribute scores evenly between 0 and 1\n- Requirement Analysis: # Provide a detailed analysis of the requirements.\n- Requirement Pool: typing.List[typing.List[str]] # List down the top-5 requirements with their priority (P0, P1, P2).\n- UI Design draft: # Provide a simple description of UI elements, functions, style, and layout.\n- Anything UNCLEAR: # Mention any aspects of the project that are unclear and try to clarify them.\n\n\n## constraint\nLanguage: Please use the same language as Human INPUT.\nFormat: output wrapped inside [CONTENT][/CONTENT] like format example, nothing else.\n\n## action\nFollow instructions of nodes, generate output and make sure it follows the format example.\n": "{\n \"Language\": \"en_us\",\n \"Programming Language\": \"\",\n \"Original Requirements\": \"开发一个基于大语言模型与私有知识库的搜索引擎，希望可以基于大语言模型进行搜索总结\",\n \"Project Name\": \"search_engine\",\n \"Product Goals\": [\n \"Develop a search engine based on a large language model\",\n \"Incorporate a private knowledge base for enhanced search capabilities\",\n \"Implement search summarization using the large language model\"\n ],\n \"User Stories\": [\n \"As a user, I want to be able to search for information using natural language queries\",\n \"As a user, I want the search engine to provide relevant and accurate results\",\n \"As a user, I want the search engine to summarize the search results for easier understanding\"\n ],\n \"Competitive Analysis\": [],\n \"Competitive Quadrant Chart\": \"\",\n \"Requirement Analysis\": \"\",\n \"Requirement Pool\": [],\n \"UI Design draft\": \"\",\n \"Anything UNCLEAR\": \"\"\n}" + "\n## context\n\n### Project Name\n\n\n### Original Requirements\n['开发一个基于大语言模型与私有知识库的搜索引擎，希望可以基于大语言模型进行搜索总结']\n\n### Search Information\n-\n\n\n-----\n\n## format example\n[CONTENT]\n{\n \"Language\": \"en_us\",\n \"Programming Language\": \"Python\",\n \"Original Requirements\": \"Create a 2048 game\",\n \"Project Name\": \"game_2048\",\n \"Product Goals\": [\n \"Create an engaging user experience\",\n \"Improve accessibility, be responsive\",\n \"More beautiful UI\"\n ],\n \"User Stories\": [\n \"As a player, I want to be able to choose difficulty levels\",\n \"As a player, I want to see my score after each game\",\n \"As a player, I want to get restart button when I lose\",\n \"As a player, I want to see beautiful UI that make me feel good\",\n \"As a player, I want to play game via mobile phone\"\n ],\n \"Competitive Analysis\": [\n \"2048 Game A: Simple interface, lacks responsive features\",\n \"play2048.co: Beautiful and responsive UI with my best score shown\",\n \"2048game.com: Responsive UI with my best score shown, but many ads\"\n ],\n \"Competitive Quadrant Chart\": \"quadrantChart\\n title \\\"Reach and engagement of campaigns\\\"\\n x-axis \\\"Low Reach\\\" --> \\\"High Reach\\\"\\n y-axis \\\"Low Engagement\\\" --> \\\"High Engagement\\\"\\n quadrant-1 \\\"We should expand\\\"\\n quadrant-2 \\\"Need to promote\\\"\\n quadrant-3 \\\"Re-evaluate\\\"\\n quadrant-4 \\\"May be improved\\\"\\n \\\"Campaign A\\\": [0.3, 0.6]\\n \\\"Campaign B\\\": [0.45, 0.23]\\n \\\"Campaign C\\\": [0.57, 0.69]\\n \\\"Campaign D\\\": [0.78, 0.34]\\n \\\"Campaign E\\\": [0.40, 0.34]\\n \\\"Campaign F\\\": [0.35, 0.78]\\n \\\"Our Target Product\\\": [0.5, 0.6]\",\n \"Requirement Analysis\": \"\",\n \"Requirement Pool\": [\n [\n \"P0\",\n \"The main code ...\"\n ],\n [\n \"P0\",\n \"The game algorithm ...\"\n ]\n ],\n \"UI Design draft\": \"Basic function description with a simple style and layout.\",\n \"Anything UNCLEAR\": \"\"\n}\n[/CONTENT]\n\n## nodes: \": # \"\n- Language: # Provide the language used in the project, typically matching the user's requirement language.\n- Programming Language: # Python/JavaScript or other mainstream programming language.\n- Original Requirements: # Place the original user's requirements here.\n- Project Name: # According to the content of \"Original Requirements,\" name the project using snake case style , like 'game_2048' or 'simple_crm.\n- Product Goals: typing.List[str] # Provide up to three clear, orthogonal product goals.\n- User Stories: typing.List[str] # Provide up to 3 to 5 scenario-based user stories.\n- Competitive Analysis: typing.List[str] # Provide 5 to 7 competitive products.\n- Competitive Quadrant Chart: # Use mermaid quadrantChart syntax. Distribute scores evenly between 0 and 1\n- Requirement Analysis: # Provide a detailed analysis of the requirements.\n- Requirement Pool: typing.List[typing.List[str]] # List down the top-5 requirements with their priority (P0, P1, P2).\n- UI Design draft: # Provide a simple description of UI elements, functions, style, and layout.\n- Anything UNCLEAR: # Mention any aspects of the project that are unclear and try to clarify them.\n\n\n## constraint\nLanguage: Please use the same language as Human INPUT.\nFormat: output wrapped inside [CONTENT][/CONTENT] like format example, nothing else.\n\n## action\nFollow instructions of nodes, generate output and make sure it follows the format example.\n": "{\n \"Language\": \"en_us\",\n \"Programming Language\": \"\",\n \"Original Requirements\": \"开发一个基于大语言模型与私有知识库的搜索引擎，希望可以基于大语言模型进行搜索总结\",\n \"Project Name\": \"search_engine\",\n \"Product Goals\": [\n \"Develop a search engine based on a large language model\",\n \"Incorporate a private knowledge base for enhanced search capabilities\",\n \"Implement search summarization using the large language model\"\n ],\n \"User Stories\": [\n \"As a user, I want to be able to search for information using natural language queries\",\n \"As a user, I want the search engine to provide relevant and accurate results\",\n \"As a user, I want the search engine to summarize the search results for easier understanding\"\n ],\n \"Competitive Analysis\": [],\n \"Competitive Quadrant Chart\": \"\",\n \"Requirement Analysis\": \"\",\n \"Requirement Pool\": [],\n \"UI Design draft\": \"\",\n \"Anything UNCLEAR\": \"\"\n}", + "\nRole: You are a senior development and qa engineer, your role is summarize the code running result.\nIf the running result does not include an error, you should explicitly approve the result.\nOn the other hand, if the running result indicates some error, you should point out which part, the development code or the test code, produces the error,\nand give specific instructions on fixing the errors. Here is the code info:\n\n## Development Code File Name\na.txt\n## Development Code\n```python\nprint('Hello, World')\n```\n## Test File Name\n\n## Test Code\n```python\nNone\n```\n## Running Command\n\n## Running Output\nstandard output: \n```text\n\n```\nstandard errors: \n```text\n\n```\n\nNow you should begin your analysis\n---\n## instruction:\nPlease summarize the cause of the errors and give correction instruction\n## File To Rewrite:\nDetermine the ONE file to rewrite in order to fix the error, for example, xyz.py, or test_xyz.py\n## Status:\nDetermine if all of the code works fine, if so write PASS, else FAIL,\nWRITE ONLY ONE WORD, PASS OR FAIL, IN THIS SECTION\n## Send To:\nPlease write Engineer if the errors are due to problematic development codes, and QaEngineer to problematic test codes, and NoOne if there are no errors,\nWRITE ONLY ONE WORD, Engineer OR QaEngineer OR NoOne, IN THIS SECTION.\n---\nYou should fill in necessary instruction, status, send to, and finally return all content between the --- segment line.\n": "---\ninstruction: There are no errors in the provided code.\n\nFile To Rewrite: N/A\n\nStatus: PASS\n\nSend To: NoOne\n---", + "\nRole: You are a senior development and qa engineer, your role is summarize the code running result.\nIf the running result does not include an error, you should explicitly approve the result.\nOn the other hand, if the running result indicates some error, you should point out which part, the development code or the test code, produces the error,\nand give specific instructions on fixing the errors. Here is the code info:\n\n## Development Code File Name\na.sh\n## Development Code\n```python\necho 'Hello World'\n```\n## Test File Name\n\n## Test Code\n```python\nNone\n```\n## Running Command\necho Hello World\n## Running Output\nstandard output: \n```text\nHello World\n\n```\nstandard errors: \n```text\n\n```\n\nNow you should begin your analysis\n---\n## instruction:\nPlease summarize the cause of the errors and give correction instruction\n## File To Rewrite:\nDetermine the ONE file to rewrite in order to fix the error, for example, xyz.py, or test_xyz.py\n## Status:\nDetermine if all of the code works fine, if so write PASS, else FAIL,\nWRITE ONLY ONE WORD, PASS OR FAIL, IN THIS SECTION\n## Send To:\nPlease write Engineer if the errors are due to problematic development codes, and QaEngineer to problematic test codes, and NoOne if there are no errors,\nWRITE ONLY ONE WORD, Engineer OR QaEngineer OR NoOne, IN THIS SECTION.\n---\nYou should fill in necessary instruction, status, send to, and finally return all content between the --- segment line.\n": "The running result indicates no error. The code works fine.\n\n## File To Rewrite:\nNo file needs to be rewritten.\n\n## Status:\nPASS\n\n## Send To:\nNoOne\n\n---", + "\nRole: You are a senior development and qa engineer, your role is summarize the code running result.\nIf the running result does not include an error, you should explicitly approve the result.\nOn the other hand, if the running result indicates some error, you should point out which part, the development code or the test code, produces the error,\nand give specific instructions on fixing the errors. Here is the code info:\n\n## Development Code File Name\na.py\n## Development Code\n```python\npython -c \"print(1/0)\"\n```\n## Test File Name\n\n## Test Code\n```python\nNone\n```\n## Running Command\npython -c print(1/0)\n## Running Output\nstandard output: \n```text\n\n```\nstandard errors: \n```text\nTraceback (most recent call last):\n File \"\", line 1, in \nZeroDivisionError: division by zero\n\n```\n\nNow you should begin your analysis\n---\n## instruction:\nPlease summarize the cause of the errors and give correction instruction\n## File To Rewrite:\nDetermine the ONE file to rewrite in order to fix the error, for example, xyz.py, or test_xyz.py\n## Status:\nDetermine if all of the code works fine, if so write PASS, else FAIL,\nWRITE ONLY ONE WORD, PASS OR FAIL, IN THIS SECTION\n## Send To:\nPlease write Engineer if the errors are due to problematic development codes, and QaEngineer to problematic test codes, and NoOne if there are no errors,\nWRITE ONLY ONE WORD, Engineer OR QaEngineer OR NoOne, IN THIS SECTION.\n---\nYou should fill in necessary instruction, status, send to, and finally return all content between the --- segment line.\n": "---\nThe error is caused by the development code in file a.py, which attempts to divide by zero. To fix the error, the development code in a.py should be modified to handle the ZeroDivisionError, for example by using a try-except block.\n\nFile To Rewrite:\na.py\n\nStatus:\nFAIL\n\nSend To:\nEngineer\n---", + "\nNOTICE\n1. Role: You are a Development Engineer or QA engineer;\n2. Task: You received this message from another Development Engineer or QA engineer who ran or tested your code. \nBased on the message, first, figure out your own role, i.e. Engineer or QaEngineer,\nthen rewrite the development code or the test code based on your role, the error, and the summary, such that all bugs are fixed and the code performs well.\nAttention: Use '##' to split sections, not '#', and '## ' SHOULD WRITE BEFORE the test case or script and triple quotes.\nThe message is as follows:\n# Legacy Code\n```python\n\nfrom typing import List\nfrom deck import Deck\nfrom card import Card\n\nclass Player:\n \"\"\"\n A class representing a player in the Black Jack game.\n \"\"\"\n\n def __init__(self, name: str):\n \"\"\"\n Initialize a Player object.\n \n Args:\n name (str): The name of the player.\n \"\"\"\n self.name = name\n self.hand: List[Card] = []\n self.score = 0\n\n def draw(self, deck: Deck):\n \"\"\"\n Draw a card from the deck and add it to the player's hand.\n \n Args:\n deck (Deck): The deck of cards.\n \"\"\"\n card = deck.draw_card()\n self.hand.append(card)\n self.calculate_score()\n\n def calculate_score(self) -> int:\n \"\"\"\n Calculate the score of the player's hand.\n \n Returns:\n int: The score of the player's hand.\n \"\"\"\n self.score = sum(card.value for card in self.hand)\n # Handle the case where Ace is counted as 11 and causes the score to exceed 21\n if self.score > 21 and any(card.rank == 'A' for card in self.hand):\n self.score -= 10\n return self.score\n\n```\n---\n# Unit Test Code\n```python\n\nimport unittest\nfrom blackjack_game.player import Player\nfrom blackjack_game.deck import Deck\nfrom blackjack_game.card import Card\n\nclass TestPlayer(unittest.TestCase):\n ## Test the Player's initialization\n def test_player_initialization(self):\n player = Player(\"Test Player\")\n self.assertEqual(player.name, \"Test Player\")\n self.assertEqual(player.hand, [])\n self.assertEqual(player.score, 0)\n\n ## Test the Player's draw method\n def test_player_draw(self):\n deck = Deck()\n player = Player(\"Test Player\")\n player.draw(deck)\n self.assertEqual(len(player.hand), 1)\n self.assertEqual(player.score, player.hand[0].value)\n\n ## Test the Player's calculate_score method\n def test_player_calculate_score(self):\n deck = Deck()\n player = Player(\"Test Player\")\n player.draw(deck)\n player.draw(deck)\n self.assertEqual(player.score, sum(card.value for card in player.hand))\n\n ## Test the Player's calculate_score method with Ace card\n def test_player_calculate_score_with_ace(self):\n deck = Deck()\n player = Player(\"Test Player\")\n player.hand.append(Card('A', 'Hearts', 11))\n player.hand.append(Card('K', 'Hearts', 10))\n player.calculate_score()\n self.assertEqual(player.score, 21)\n\n ## Test the Player's calculate_score method with multiple Aces\n def test_player_calculate_score_with_multiple_aces(self):\n deck = Deck()\n player = Player(\"Test Player\")\n player.hand.append(Card('A', 'Hearts', 11))\n player.hand.append(Card('A', 'Diamonds', 11))\n player.calculate_score()\n self.assertEqual(player.score, 12)\n\nif __name__ == '__main__':\n unittest.main()\n\n\n```\n---\n# Console logs\n```text\n\n```\n---\nNow you should start rewriting the code:\n## file name of the code to rewrite: Write code with triple quote. Do your best to implement THIS IN ONLY ONE FILE.\n": "```python\n## Development Engineer\n\nfrom typing import List\nfrom deck import Deck\nfrom card import Card\n\nclass Player:\n \"\"\"\n A class representing a player in the Black Jack game.\n \"\"\"\n\n def __init__(self, name: str):\n \"\"\"\n Initialize a Player object.\n \n Args:\n name (str): The name of the player.\n \"\"\"\n self.name = name\n self.hand: List[Card] = []\n self.score = 0\n\n def draw(self, deck: Deck):\n \"\"\"\n Draw a card from the deck and add it to the player's hand.\n \n Args:\n deck (Deck): The deck of cards.\n \"\"\"\n card = deck.draw_card()\n self.hand.append(card)\n self.calculate_score()\n\n def calculate_score(self) -> int:\n \"\"\"\n Calculate the score of the player's hand.\n \n Returns:\n int: The score of the player's hand.\n \"\"\"\n self.score = sum(card.value for card in self.hand)\n # Handle the case where Ace is counted as 11 and causes the score to exceed 21\n ace_count = sum(1 for card in self.hand if card.rank == 'A')\n while self.score > 21 and ace_count > 0:\n self.score -= 10\n ace_count -= 1\n return self.score\n```\n\n```python\n## QaEngineer\n\nimport unittest\nfrom player import Player\nfrom deck import Deck\nfrom card import Card\n\nclass TestPlayer(unittest.TestCase):\n ## Test the Player's initialization\n def test_player_initialization(self):\n player = Player(\"Test Player\")\n self.assertEqual(player.name, \"Test Player\")\n self.assertEqual(player.hand, [])\n self.assertEqual(player.score, 0)\n\n ## Test the Player's draw method\n def test_player_draw(self):\n deck = Deck()\n player = Player(\"Test Player\")\n player.draw(deck)\n self.assertEqual(len(player.hand), 1)\n self.assertEqual(player.score, player.hand[0].value)\n\n ## Test the Player's calculate_score method\n def test_player_calculate_score(self):\n deck = Deck()\n player = Player(\"Test Player\")\n player.draw(deck)\n player.draw(deck)\n self.assertEqual(player.score, sum(card.value for card in player.hand))\n\n ## Test the Player's calculate_score method with Ace card\n def test_player_calculate_score_with_ace(self):\n player = Player(\"Test Player\")\n player.hand.append(Card('A', 'Hearts', 11))\n player.hand.append(Card('K', 'Hearts', 10))\n player.calculate_score()\n self.assertEqual(player.score, 21)\n\n ## Test the Player's calculate_score method with multiple Aces\n def test_player_calculate_score_with_multiple_aces(self):\n player = Player(\"Test Player\")\n player.hand.append(Card('A', 'Hearts', 11))\n player.hand.append(Card('A', 'Diamonds', 11))\n player.calculate_score()\n self.assertEqual(player.score, 12)\n\nif __name__ == '__main__':\n unittest.main()\n```" } \ No newline at end of file diff --git a/tests/metagpt/actions/test_debug_error.py b/tests/metagpt/actions/test_debug_error.py index 6258aa6d4..e512c370a 100644 --- a/tests/metagpt/actions/test_debug_error.py +++ b/tests/metagpt/actions/test_debug_error.py @@ -149,5 +149,16 @@ async def test_debug_error(): rsp = await debug_error.run() assert "class Player" in rsp # rewrite the same class - # a key logic to rewrite to (original one is "if self.score > 12") + # Problematic code: + # ``` + # if self.score > 21 and any(card.rank == 'A' for card in self.hand): + # self.score -= 10 + # ``` + # Should rewrite to (used "gpt-3.5-turbo-1106"): + # ``` + # ace_count = sum(1 for card in self.hand if card.rank == 'A') + # while self.score > 21 and ace_count > 0: + # self.score -= 10 + # ace_count -= 1 + # ``` assert "while self.score > 21" in rsp diff --git a/tests/metagpt/tools/test_search_engine_meilisearch.py b/tests/metagpt/tools/test_search_engine_meilisearch.py index 9e1fbfbb9..574d6d30f 100644 --- a/tests/metagpt/tools/test_search_engine_meilisearch.py +++ b/tests/metagpt/tools/test_search_engine_meilisearch.py @@ -29,6 +29,7 @@ def search_engine_server(): meilisearch_process.wait() +@pytest.mark.skip def test_meilisearch(search_engine_server): # Prerequisites # https://www.meilisearch.com/docs/learn/getting_started/installation From a72cf53569ad70e5db758fe48f039bf615942a63 Mon Sep 17 00:00:00 2001 From: voidking Date: Mon, 8 Jan 2024 14:35:35 +0800 Subject: [PATCH 6/7] feat: support for codecov --- .github/workflows/unittest.yaml | 4 ++++ 1 file changed, 4 insertions(+) diff --git a/.github/workflows/unittest.yaml b/.github/workflows/unittest.yaml index 564a5e7c9..07118e0e0 100644 --- a/.github/workflows/unittest.yaml +++ b/.github/workflows/unittest.yaml @@ -56,3 +56,7 @@ jobs: ./tests/data/rsp_cache_new.json retention-days: 3 if: ${{ always() }} + - name: Upload coverage reports to Codecov + uses: codecov/codecov-action@v3 + env: + CODECOV_TOKEN: ${{ secrets.CODECOV_TOKEN }} From 60d2575cbd326dccaf11096feb1151b57f1e8d22 Mon Sep 17 00:00:00 2001 From: voidking Date: Mon, 8 Jan 2024 16:17:53 +0800 Subject: [PATCH 7/7] bugfix: modify the rules for unittest failure --- .github/workflows/unittest.yaml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/.github/workflows/unittest.yaml b/.github/workflows/unittest.yaml index 07118e0e0..ad79748df 100644 --- a/.github/workflows/unittest.yaml +++ b/.github/workflows/unittest.yaml @@ -41,7 +41,7 @@ jobs: - name: Show failed tests and overall summary run: | grep -E "FAILED tests|ERROR tests|[0-9]+ passed," unittest.txt - failed_count=$(grep "FAILED|ERROR" unittest.txt | wc -l) + failed_count=$(grep -E "FAILED|ERROR" unittest.txt | wc -l) if [[ "$failed_count" -gt 0 ]]; then echo "$failed_count failed lines found! Task failed." exit 1