Feature: Vector Search - Embedding Generation and Semantic Search
  As a user
  I want to use vector database to perform semantic search in my wiki
  So that I can find relevant content based on meaning rather than exact keywords

  Background:
    Given I add test ai settings

  @vectorSearch @mockOpenAI
  Scenario: Agent workflow - Create notes, update embeddings, then search
    Given I have started the mock OpenAI server
      | response                                                                                                                                                                                                        | stream | embedding   |
      | <tool_use name="wiki-operation">{"workspaceName":"wiki","operation":"wiki-add-tiddler","title":"AI Agent Guide","text":"智能体是一种可以执行任务的AI系统，它可以使用工具、搜索信息并与用户交互。"}</tool_use>   | false  |             |
      | 已成功在工作区 wiki 中创建条目 "AI Agent Guide"。                                                                                                                                                               | false  |             |
      | <tool_use name="wiki-operation">{"workspaceName":"wiki","operation":"wiki-add-tiddler","title":"Vector Database Tutorial","text":"向量数据库用于存储和检索高维向量数据，支持语义搜索和相似度匹配。"}</tool_use> | false  |             |
      | 已成功在工作区 wiki 中创建条目 "Vector Database Tutorial"。                                                                                                                                                     | false  |             |
      | <tool_use name="wiki-update-embeddings">{"workspaceName":"wiki","forceUpdate":false}</tool_use>                                                                                                                 | false  |             |
      |                                                                                                                                                                                                                 | false  | note1       |
      |                                                                                                                                                                                                                 | false  | note2       |
      | 已成功为工作区 wiki 生成向量嵌入索引。总计2个笔记，2个嵌入向量。                                                                                                                                                | false  |             |
      | <tool_use name="wiki-search">{"workspaceName":"wiki","searchType":"vector","query":"如何使用AI智能体","limit":5,"threshold":0.7}</tool_use>                                                                     | false  |             |
      |                                                                                                                                                                                                                 | false  | query-note1 |
      | 根据向量搜索结果，在工作区 wiki 中找到以下相关内容：\n\n**Tiddler: AI Agent Guide** (Similarity: 95.0%)\n这篇笔记介绍了AI智能体的基本概念和使用方法。                                                           | false  |             |
    # Launch application after mock server is ready
    Then I launch the TidGi application
    And I wait for the page to load completely
    And I should see a "page body" element with selector "body"
    # Ensure we are in the agent workspace (not wiki workspace) for agent interaction
    When I click on an "agent workspace button" element with selector "[data-testid='workspace-agent']"
    And I should see a "new tab button" element with selector "[data-tab-id='new-tab-button']"
    # Step 1: Open agent chat interface
    When I click on a "new tab button" element with selector "[data-tab-id='new-tab-button']"
    And I should see a "search interface" element with selector ".aa-Autocomplete"
    When I click on a "search input box" element with selector ".aa-Input"
    And I should see an "autocomplete panel" element with selector ".aa-Panel"
    When I click on an "agent suggestion" element with selector '[data-autocomplete-source-id="agentsSource"] .aa-ItemWrapper'
    # Step 2: Create first note
    When I click on a "message input textarea" element with selector "[data-testid='agent-message-input']"
    When I type "在 wiki 工作区创建一个名为 AI Agent Guide 的笔记，内容是：智能体是一种可以执行任务的AI系统，它可以使用工具、搜索信息并与用户交互。" in "chat input" element with selector "[data-testid='agent-message-input']"
    And I press "Enter" key
    Then I should see 4 messages in chat history
  # Step 3: Create second note
    When I click on a "message input textarea" element with selector "[data-testid='agent-message-input']"
    When I type "再创建一个名为 Vector Database Tutorial 的笔记，内容是：向量数据库用于存储和检索高维向量数据，支持语义搜索和相似度匹配。" in "chat input" element with selector "[data-testid='agent-message-input']"
    And I press "Enter" key
    Then I should see 8 messages in chat history
    # Step 4: Update vector embeddings using agent tool
    When I click on a "message input textarea" element with selector "[data-testid='agent-message-input']"
    When I type "为 wiki 工作区更新向量索引" in "chat input" element with selector "[data-testid='agent-message-input']"
    And I press "Enter" key
    Then I should see 12 messages in chat history
    # Step 5: Perform vector search
    When I click on a "message input textarea" element with selector "[data-testid='agent-message-input']"
    When I type "使用向量搜索在 wiki 中查找关于如何使用AI智能体的内容" in "chat input" element with selector "[data-testid='agent-message-input']"
    And I press "Enter" key
    Then I should see 16 messages in chat history
    # Verify the last message contains vector search results
    And I should see "search result in last message" elements with selectors:
      | element description        | selector                                                               |
      | search result in last message| [data-testid='message-bubble']:has-text('Tiddler: AI Agent Guide') |

  @vectorSearch @mockOpenAI
  Scenario: UI workflow - Generate embeddings via preferences, then search
    Given I have started the mock OpenAI server
      | response                                                                                                                                                                                                       | stream | embedding   |
      | <tool_use name="wiki-operation">{"workspaceName":"wiki","operation":"wiki-add-tiddler","title":"Machine Learning Basics","text":"机器学习是人工智能的一个分支，通过算法让计算机从数据中学习规律。"}</tool_use> | false  |             |
      | 已成功在工作区 wiki 中创建条目 "Machine Learning Basics"。                                                                                                                                                     | false  |             |
      |                                                                                                                                                                                                                | false  | note3       |
      | <tool_use name="wiki-search">{"workspaceName":"wiki","searchType":"vector","query":"机器学习","limit":5,"threshold":0.7}</tool_use>                                                                            | false  |             |
      |                                                                                                                                                                                                                | false  | query-note3 |
      | 根据向量搜索结果，在工作区 wiki 中找到以下相关内容：\n\n**Tiddler: Machine Learning Basics** (Similarity: 98.0%)\n这篇笔记介绍了机器学习的基本概念。                                                           | false  |             |
    # Launch application after mock server is ready
    Then I launch the TidGi application
    And I wait for the page to load completely
    And I should see a "page body" element with selector "body"
    # Ensure we are in the agent workspace (not wiki workspace) for agent interaction
    When I click on an "agent workspace button" element with selector "[data-testid='workspace-agent']"
    And I should see a "new tab button" element with selector "[data-tab-id='new-tab-button']"
    # Step 1: Create a test note via agent
    When I click on "new tab button and create default agent button" elements with selectors:
      | element description        | selector                                    |
      | new tab button             | [data-tab-id='new-tab-button']              |
      | create default agent button| [data-testid='create-default-agent-button'] |
    And I should see a "message input box" element with selector "[data-testid='agent-message-input']"
    When I click on a "message input textarea" element with selector "[data-testid='agent-message-input']"
    When I type "在 wiki 工作区创建一个名为 Machine Learning Basics 的笔记，内容是：机器学习是人工智能的一个分支，通过算法让计算机从数据中学习规律。" in "chat input" element with selector "[data-testid='agent-message-input']"
    And I press "Enter" key
    Then I should see 4 messages in chat history
    # Step 2: Open workspace settings and navigate to Search/Embedding section to generate embeddings
    When I open edit workspace window for workspace with name "wiki"
    And I switch to "editWorkspace" window
    When I click on a "search section" element with selector "[data-testid='preference-section-search']"
    When I click on a "generate embeddings button" element with selector "[data-testid^='generate-embeddings-button-']"
    Then I should see a "delete embeddings button after generation" element with selector "[data-testid^='delete-embeddings-button-']"
    # Close workspace settings
    When I close "editWorkspace" window
    And I switch to "main" window
    # Step 3: Perform vector search and verify results match agent workflow
    When I click on a "message input textarea" element with selector "[data-testid='agent-message-input']"
    When I type "使用向量搜索在 wiki 中查找关于机器学习的内容" in "chat input" element with selector "[data-testid='agent-message-input']"
    And I press "Enter" key
    Then I should see 8 messages in chat history
    # Verify the last message contains vector search results
    And I should see a "ML search result in last message" element with selector "[data-testid='message-bubble']:has-text('Tiddler: Machine Learning Basics')"

  @vectorSearch @mockOpenAI
  Scenario: Vector search with low similarity - No results below threshold, then lower threshold
    Given I have started the mock OpenAI server
      | response                                                                                                                                                       | stream | embedding |
      | <tool_use name="wiki-operation">{"workspaceName":"wiki","operation":"wiki-add-tiddler","title":"AI Technology","text":"人工智能技术正在改变世界。"}</tool_use> | false  |           |
      | 已成功在工作区 wiki 中创建条目 "AI Technology"。                                                                                                               | false  |           |
      | <tool_use name="wiki-operation">{"workspaceName":"wiki","operation":"wiki-add-tiddler","title":"Machine Learning","text":"机器学习算法和应用。"}</tool_use>    | false  |           |
      | 已成功在工作区 wiki 中创建条目 "Machine Learning"。                                                                                                            | false  |           |
      | <tool_use name="wiki-update-embeddings">{"workspaceName":"wiki","forceUpdate":false}</tool_use>                                                                | false  |           |
      |                                                                                                                                                                | false  | note4     |
      |                                                                                                                                                                | false  | note5     |
      | 已成功为工作区 wiki 生成向量嵌入索引。总计2个笔记，2个嵌入向量。                                                                                               | false  |           |
      | <tool_use name="wiki-search">{"workspaceName":"wiki","searchType":"vector","query":"天气预报","limit":5,"threshold":0.7}</tool_use>                            | false  |           |
      |                                                                                                                                                                | false  | unrelated |
      | 在Wiki工作空间"wiki"中未找到符合条件的向量搜索结果（相似度阈值：0.7）。                                                                                        | false  |           |
      | <tool_use name="wiki-search">{"workspaceName":"wiki","searchType":"vector","query":"天气预报","limit":5,"threshold":0.1}</tool_use>                            | false  |           |
      |                                                                                                                                                                | false  | unrelated |
      | 根据向量搜索结果，在工作区 wiki 中找到以下相关内容：\n\n**Tiddler: AI Technology** (Similarity: 15.0%)\n低相似度结果。                                         | false  |           |
    # Launch application after mock server is ready
    Then I launch the TidGi application
    And I wait for the page to load completely
    And I should see a "page body" element with selector "body"
    # Ensure we are in the agent workspace (not wiki workspace) for agent interaction
    When I click on an "agent workspace button" element with selector "[data-testid='workspace-agent']"
    And I should see a "new tab button" element with selector "[data-tab-id='new-tab-button']"
    # Step 1: Open agent chat interface
    When I click on "new tab button and create default agent button" elements with selectors:
      | element description        | selector                                    |
      | new tab button             | [data-tab-id='new-tab-button']              |
      | create default agent button| [data-testid='create-default-agent-button'] |
    And I should see a "message input box" element with selector "[data-testid='agent-message-input']"
    # Step 2: Create first note about AI
    When I click on a "message input textarea" element with selector "[data-testid='agent-message-input']"
    When I type "在 wiki 工作区创建一个名为 AI Technology 的笔记，内容是：人工智能技术正在改变世界。" in "chat input" element with selector "[data-testid='agent-message-input']"
    And I press "Enter" key
    Then I should see 4 messages in chat history
    # Step 3: Create second note about ML
    When I click on a "message input textarea" element with selector "[data-testid='agent-message-input']"
    When I type "再创建一个名为 Machine Learning 的笔记，内容是：机器学习算法和应用。" in "chat input" element with selector "[data-testid='agent-message-input']"
    And I press "Enter" key
    Then I should see 8 messages in chat history
    # Step 4: Update vector embeddings
    When I click on a "message input textarea" element with selector "[data-testid='agent-message-input']"
    When I type "为 wiki 工作区更新向量索引" in "chat input" element with selector "[data-testid='agent-message-input']"
    And I press "Enter" key
    Then I should see 12 messages in chat history
    # Step 5: Search for unrelated content with high threshold (should find nothing)
    When I click on a "message input textarea" element with selector "[data-testid='agent-message-input']"
    When I type "使用向量搜索在 wiki 中查找关于天气预报的内容，阈值设为0.7" in "chat input" element with selector "[data-testid='agent-message-input']"
    And I press "Enter" key
    Then I should see 16 messages in chat history
    # Verify the response contains "no results found" with threshold info
    Then I should see "no results and threshold 0.7" elements with selectors:
      | element description          | selector                                                                 |
      | no results message           | [data-testid='message-bubble']:has-text('未找到符合条件') |
      | threshold 0.7 message        | [data-testid='message-bubble']:has-text('0.7')            |
    # Step 6: Lower threshold and search again (should find low-similarity results)
    When I click on a "message input textarea" element with selector "[data-testid='agent-message-input']"
    When I type "再次搜索天气预报，但这次把阈值降低到0.1" in "chat input" element with selector "[data-testid='agent-message-input']"
    And I press "Enter" key
    Then I should see 20 messages in chat history
    # Verify the response contains low-similarity result
    Then I should see "AI Technology and low similarity" elements with selectors:
      | element description                    | selector                                                                 |
      | AI Technology message                  | [data-testid='message-bubble']:has-text('Tiddler: AI Technology') |
      | low similarity message                 | [data-testid='message-bubble']:has-text('15')             |