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https://github.com/tiddly-gittly/TidGi-Desktop.git
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02c610c3d7
- Implemented AgentSwitcher component with dropdown functionality for selecting agent definitions. - Integrated loading of agent definitions on dropdown open. - Added visual feedback for current selection and disabled state. feat: create ToolResultRenderer for generic tool result messages - Developed ToolResultRenderer to handle rendering of <functions_result> messages. - Included collapsible parameters and result display with error handling. - Added truncation for long results in collapsed view. test: add comprehensive tests for MessageRenderer components - Implemented tests for AskQuestionRenderer, ToolResultRenderer, ToolApprovalRenderer, and BaseMessageRenderer. - Ensured proper rendering and functionality for various message types and states. - Included pattern routing tests for MessageRenderer. feat: introduce TurnActionBar for action management in agent turns - Created TurnActionBar component for managing actions like rollback, retry, delete, and copy. - Integrated visual feedback for file changes and rollback status. - Added functionality for copying agent responses and full conversation to clipboard. feat: implement askQuestionPending for managing user responses - Developed infrastructure for handling pending ask-question requests. - Implemented promise-based blocking until user responds to agent questions. - Added timeout handling for ask-question requests.
185 lines
19 KiB
Gherkin
185 lines
19 KiB
Gherkin
Feature: Vector Search - Embedding Generation and Semantic Search
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As a user
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I want to use vector database to perform semantic search in my wiki
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So that I can find relevant content based on meaning rather than exact keywords
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Background:
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Given I add test ai settings
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@vectorSearch @mockOpenAI
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Scenario: Agent workflow - Create notes, update embeddings, then search
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Given I have started the mock OpenAI server
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| response | stream | embedding |
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| <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 | |
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| 已成功在工作区 wiki 中创建条目 "AI Agent Guide"。 | false | |
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| <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 | |
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| 已成功在工作区 wiki 中创建条目 "Vector Database Tutorial"。 | false | |
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| <tool_use name="wiki-update-embeddings">{"workspaceName":"wiki","forceUpdate":false}</tool_use> | false | |
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| | false | note1 |
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| | false | note2 |
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| 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 | |
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| <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 | |
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| | false | query-note1 |
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| 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 | |
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# Launch application after mock server is ready
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Then I launch the TidGi application
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And I wait for the page to load completely
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And I should see a "page body" element with selector "body"
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# Ensure we are in the agent workspace (not wiki workspace) for agent interaction
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When I click on an "agent workspace button" element with selector "[data-testid='workspace-agent']"
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And I should see a "new tab button" element with selector "[data-tab-id='new-tab-button']"
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# Step 1: Open agent chat interface
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When I click on a "new tab button" element with selector "[data-tab-id='new-tab-button']"
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And I should see a "search interface" element with selector ".aa-Autocomplete"
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When I click on a "search input box" element with selector ".aa-Input"
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And I should see an "autocomplete panel" element with selector ".aa-Panel"
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When I click on an "agent suggestion" element with selector '[data-autocomplete-source-id="agentsSource"] .aa-ItemWrapper'
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# Step 2: Create first note
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When I click on a "message input textarea" element with selector "[data-testid='agent-message-input']"
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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']"
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And I press "Enter" key
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Then I should see 4 messages in chat history
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# Step 3: Create second note
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When I click on a "message input textarea" element with selector "[data-testid='agent-message-input']"
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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']"
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And I press "Enter" key
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Then I should see 8 messages in chat history
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# Step 4: Update vector embeddings using agent tool
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When I click on a "message input textarea" element with selector "[data-testid='agent-message-input']"
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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']"
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And I press "Enter" key
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Then I should see 12 messages in chat history
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# Step 5: Perform vector search
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When I click on a "message input textarea" element with selector "[data-testid='agent-message-input']"
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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']"
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And I press "Enter" key
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Then I should see 16 messages in chat history
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# Verify the last message contains vector search results
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And I should see "search result in last message" elements with selectors:
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| element description | selector |
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| search result in last message| [data-testid='message-bubble']:has-text('Tiddler: AI Agent Guide') |
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@vectorSearch @mockOpenAI
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Scenario: UI workflow - Generate embeddings via preferences, then search
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Given I have started the mock OpenAI server
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| response | stream | embedding |
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| <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 | |
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| 已成功在工作区 wiki 中创建条目 "Machine Learning Basics"。 | false | |
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| | false | note3 |
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| <tool_use name="wiki-search">{"workspaceName":"wiki","searchType":"vector","query":"机器学习","limit":5,"threshold":0.7}</tool_use> | false | |
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| | false | query-note3 |
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| 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 | |
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# Launch application after mock server is ready
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Then I launch the TidGi application
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And I wait for the page to load completely
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And I should see a "page body" element with selector "body"
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# Ensure we are in the agent workspace (not wiki workspace) for agent interaction
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When I click on an "agent workspace button" element with selector "[data-testid='workspace-agent']"
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And I should see a "new tab button" element with selector "[data-tab-id='new-tab-button']"
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# Step 1: Create a test note via agent
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When I click on "new tab button and create default agent button" elements with selectors:
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| element description | selector |
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| new tab button | [data-tab-id='new-tab-button'] |
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| create default agent button| [data-testid='create-default-agent-button'] |
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And I should see a "message input box" element with selector "[data-testid='agent-message-input']"
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When I click on a "message input textarea" element with selector "[data-testid='agent-message-input']"
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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']"
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And I press "Enter" key
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Then I should see 4 messages in chat history
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# Step 2: Open preferences and navigate to Search section to generate embeddings
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When I click on a "settings button" element with selector "#open-preferences-button"
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When I switch to "preferences" window
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When I click on a "search section" element with selector "[data-testid='preference-section-search']"
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# Wait for workspace list to load
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# The Search.tsx renders workspace cards with name, status, and buttons
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And I should see a "wiki workspace card" element with selector "*:has-text('wiki')"
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# Click the generate button - use button text "生成" instead of data-testid
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# The button shows "生成" for initial generation, "更新嵌入" after generation
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When I click on a "generate button with text" element with selector "button:has-text('生成')"
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# Verify generation completed with detailed status information
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# Should show: workspace name, embedding count, note count, last updated time and action buttons
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Then I should see "workspace name in status and embedding count status and embedding word and last updated label and update button after generation and delete button after generation" elements with selectors:
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| element description | selector |
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| workspace name in status | *:has-text('wiki') |
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| embedding count status | *:has-text('个笔记') |
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| embedding word | *:has-text('嵌入') |
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| last updated label | *:has-text('最后更新') |
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| update button after generation | button:has-text('更新嵌入') |
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| delete button after generation | button:has-text('删除') |
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# Close preferences
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When I close "preferences" window
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And I switch to "main" window
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# Step 3: Perform vector search and verify results match agent workflow
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When I click on a "message input textarea" element with selector "[data-testid='agent-message-input']"
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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']"
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And I press "Enter" key
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Then I should see 8 messages in chat history
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# Verify the last message contains vector search results
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And I should see a "ML search result in last message" element with selector "[data-testid='message-bubble']:has-text('Tiddler: Machine Learning Basics')"
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@vectorSearch @mockOpenAI
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Scenario: Vector search with low similarity - No results below threshold, then lower threshold
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Given I have started the mock OpenAI server
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| response | stream | embedding |
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| <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 | |
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| 已成功在工作区 wiki 中创建条目 "AI Technology"。 | false | |
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| <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 | |
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| 已成功在工作区 wiki 中创建条目 "Machine Learning"。 | false | |
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| <tool_use name="wiki-update-embeddings">{"workspaceName":"wiki","forceUpdate":false}</tool_use> | false | |
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| | false | note4 |
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| | false | note5 |
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| 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 | |
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| <tool_use name="wiki-search">{"workspaceName":"wiki","searchType":"vector","query":"天气预报","limit":5,"threshold":0.7}</tool_use> | false | |
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| | false | unrelated |
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| 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 | |
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| <tool_use name="wiki-search">{"workspaceName":"wiki","searchType":"vector","query":"天气预报","limit":5,"threshold":0.1}</tool_use> | false | |
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| | false | unrelated |
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| 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 | |
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# Launch application after mock server is ready
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Then I launch the TidGi application
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And I wait for the page to load completely
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And I should see a "page body" element with selector "body"
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# Ensure we are in the agent workspace (not wiki workspace) for agent interaction
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When I click on an "agent workspace button" element with selector "[data-testid='workspace-agent']"
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And I should see a "new tab button" element with selector "[data-tab-id='new-tab-button']"
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# Step 1: Open agent chat interface
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When I click on "new tab button and create default agent button" elements with selectors:
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| element description | selector |
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| new tab button | [data-tab-id='new-tab-button'] |
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| create default agent button| [data-testid='create-default-agent-button'] |
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And I should see a "message input box" element with selector "[data-testid='agent-message-input']"
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# Step 2: Create first note about AI
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When I click on a "message input textarea" element with selector "[data-testid='agent-message-input']"
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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']"
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And I press "Enter" key
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Then I should see 4 messages in chat history
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# Step 3: Create second note about ML
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When I click on a "message input textarea" element with selector "[data-testid='agent-message-input']"
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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']"
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And I press "Enter" key
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Then I should see 8 messages in chat history
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# Step 4: Update vector embeddings
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When I click on a "message input textarea" element with selector "[data-testid='agent-message-input']"
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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']"
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And I press "Enter" key
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Then I should see 12 messages in chat history
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# Step 5: Search for unrelated content with high threshold (should find nothing)
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When I click on a "message input textarea" element with selector "[data-testid='agent-message-input']"
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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']"
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And I press "Enter" key
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Then I should see 16 messages in chat history
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# Verify the response contains "no results found" with threshold info
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Then I should see "no results and threshold 0.7" elements with selectors:
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| element description | selector |
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| no results message | [data-testid='message-bubble']:has-text('未找到符合条件') |
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| threshold 0.7 message | [data-testid='message-bubble']:has-text('0.7') |
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# Step 6: Lower threshold and search again (should find low-similarity results)
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When I click on a "message input textarea" element with selector "[data-testid='agent-message-input']"
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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']"
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And I press "Enter" key
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Then I should see 20 messages in chat history
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# Verify the response contains low-similarity result
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Then I should see "AI Technology and low similarity" elements with selectors:
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| element description | selector |
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| AI Technology message | [data-testid='message-bubble']:has-text('Tiddler: AI Technology') |
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| low similarity message | [data-testid='message-bubble']:has-text('15') |
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