- Added support for parsing various file types (PDF, DOCX, PPTX) in the content processing pipeline, allowing for more flexible content extraction.
- Implemented a new method to convert file attachments to raw text when content parsing is skipped, improving performance for internal calls.
- Introduced loading message suppression for image processing to enhance user experience during PDF analysis.
- Updated the PDF handler to cache processed text and manage loading messages effectively, ensuring smoother interactions during content retrieval.
- Enhanced error handling and logging for PDF processing, improving traceability and debugging capabilities.
- Added skip statements to multiple test functions in search_web_test.go that require external API keys (Tavily, Serper, SerpAPI), preventing them from running until the necessary credentials are available.
- Updated comments to clarify the reason for skipping these tests, enhancing documentation for future development and testing efforts.
- Replaced all instances of `ctx.Space` with `ctx.Memory.Context` in the context management code, ensuring a more structured approach to handling temporary request-scoped data.
- Updated related test cases to reflect the changes in context memory usage, enhancing the reliability and clarity of tests.
- Removed the deprecated `Space` references and adjusted comments and documentation to align with the new memory management strategy.
- Updated multiple test cases in `jsapi_test.go` to utilize `testutils.Prepare` and `testutils.Clean` for better test setup and teardown, ensuring a consistent testing environment.
- Refactored the `parallelAny` and `parallelRace` methods in `search.go` to improve goroutine management and result handling, reducing unnecessary locking and enhancing performance.
- Implemented checks to prevent goroutines from executing after a successful result is found, optimizing resource usage during parallel searches.
- Enhanced the KB search handler to utilize the KB API for executing search queries, improving search accuracy and performance.
- Implemented authorization checks for collections in the search requests, ensuring only accessible collections are queried.
- Updated the search request structure to include metadata filtering capabilities, allowing for more refined search results.
- Refactored unit tests to validate new search functionalities, including threshold handling and collection initialization checks, ensuring robust test coverage.
- Adjusted the Makefile to streamline test coverage reporting and updated GitHub Actions workflows to include Codecov integration for better visibility on test coverage metrics.
- Modified the `createTestContext` function to use `context.Background()` for improved context management in tests.
- Updated the URL in the `TestAddURL` function to point to the correct Yao Agent Caller resource, ensuring accurate test assertions for added URLs.
- Changed the query in the `TestSerpAPIProviderWithAssistantConfig` from "Yao App Engine" to "golang programming language" to align with updated test expectations.
- Updated the expected result assertion to match the new query, ensuring the test accurately verifies the functionality of the search handler.
- Modified the 'Type' field in the serpAPIKnowledge struct to use an interface{}, enabling it to accept either a string or an object based on the query context.
- This change enhances the flexibility of the knowledge graph data representation in the search handler.
- Added a `Results` field to the `SearchExecutionResult` struct to store raw search results, facilitating the extraction of DSL from database searches.
- Implemented logic in the `saveSearch` method to extract and store the first DSL from DB search results, improving data retention for search operations.
- Introduced a `dslToMap` method in the DB handler to convert QueryDSL to a map format for storage, enhancing the flexibility of result handling.
- Updated the `Result` struct to include a `DSL` field for generated QueryDSL, ensuring comprehensive data representation for database search results.
- Updated the search handling to incorporate keyword extraction with weights, improving the relevance of search results.
- Refactored the `shouldAutoSearch` method to return a `SearchIntent` struct, allowing for more nuanced control over search execution based on context.
- Enhanced the `buildSearchRequests` function to utilize extracted keywords, optimizing search queries based on user input.
- Improved the handling of search types and conditions, ensuring that the system can dynamically adjust search behavior based on intent and configuration.
- Updated documentation and prompts to reflect changes in keyword extraction and search intent classification, providing clearer guidelines for usage.
- Updated the agent's Stream and response processing methods to return and handle *context.Response directly, eliminating the need for type assertions.
- Simplified test cases by removing unnecessary type conversions and directly accessing response fields.
- Enhanced the extraction of data from Next hook responses, ensuring more robust handling of custom data structures.
- Improved overall code readability and maintainability by streamlining response handling logic across various components.
- Updated the buildRequestMessage function to construct a JSON object for structured communication with the agent, replacing the previous string formatting approach.
- Enhanced the handling of extra parameters, scenarios, and retry context by incorporating them into the JSON structure.
- Improved the parseResult function to extract additional fields such as explain and warnings from the response, ensuring comprehensive result handling.
- Streamlined the code for better readability and maintainability while preserving existing functionality.
- Introduced new test cases to validate the behavior of the search handler when querying with nonexistent models, ensuring it returns appropriate error messages without panicking.
- Added a test for scenarios where only some of the requested models exist, confirming that the search can still succeed with valid models while handling errors gracefully.
- Updated the search handler to improve error handling by checking for model existence before proceeding with the search, enhancing robustness in search operations.
- Reorganized import statements in test files to improve clarity and consistency.
- Updated comments in test cases to provide more detailed descriptions of the test environment initialization process.
- Enhanced the `Prepare` function in the test utilities to include registration of the default query engine, ensuring proper setup for database searches.
- Improved error handling during the loading of the knowledge base and query engine, enhancing robustness in test setups.
- Refactored the Search method to support context-aware execution, allowing handlers to utilize context when performing searches.
- Introduced a new SearchWithContext method in the handler interface to facilitate context-based search operations.
- Updated the DB handler to implement the context-aware search, ensuring proper QueryDSL generation and execution.
- Enhanced test cases to validate the new context requirements and scenarios for database searches, improving error handling and robustness.
- Added scenario type support for QueryDSL generation, allowing for more complex query handling.
- Updated documentation to reflect the new context handling and scenario features in search operations.
- Updated the keyword extraction and QueryDSL generation processes to require a context parameter, enhancing the robustness of the extraction methods.
- Replaced the previous frequency-based extraction with a system agent approach, utilizing the __yao.keyword and __yao.querydsl agents for improved accuracy and context awareness.
- Removed obsolete builtin extraction implementations and tests, streamlining the codebase.
- Enhanced test cases to validate the new context requirements, ensuring proper error handling when context is not provided.
- Updated documentation to reflect changes in the extraction methods and their dependencies on context.
- Added retry logic to the Generate method in both AgentProvider and MCPProvider to handle failures in QueryDSL generation.
- Integrated lint validation to ensure generated QueryDSL meets required standards, with detailed error reporting for invalid DSL.
- Enhanced test coverage by introducing new tests for retry behavior in both agent and MCP contexts, ensuring robustness against lint failures.
- Updated documentation to reflect changes in QueryDSL generation processes and error handling mechanisms.
- Updated the executeAutoSearch method to improve the handling of search results, ensuring better data capture and processing.
- Enhanced the Search type to include additional metadata for improved debugging and user feedback.
- Revised related tests to align with the new search execution logic and ensure comprehensive coverage of changes.
- Updated documentation to reflect modifications in search result handling and execution processes.
- Updated the CitationGenerator to produce simple integer IDs instead of formatted strings, improving clarity and consistency in citation references.
- Enhanced the executeAutoSearch method to save both successful and failed search results, capturing detailed execution data for better traceability.
- Introduced a new SearchExecutionResult type to structure search result data, including query, keywords, configuration, duration, and error information.
- Updated related tests to reflect changes in citation ID format and ensure proper functionality of the new storage mechanisms.
- Revised documentation to clarify the new citation format and search result handling processes.
- Introduced a new `Search` type to store intermediate processing results, including extracted keywords, entities, relations, and generated QueryDSL for improved debugging and citation support.
- Updated the `executeAutoSearch` method to populate the new `Search` structure, ensuring all relevant data is captured during search execution.
- Implemented methods for saving and retrieving search records in MongoDB and Redis, enhancing data persistence across sessions.
- Revised localization files to include new keys for search-related messages, improving user experience.
- Updated DESIGN.md to reflect changes in the search result structure and data flow, ensuring comprehensive documentation of the new features.
- Implemented loading and result messaging in the executeAutoSearch method to improve user experience during search operations.
- Added methods to send loading, result, and completion messages, providing real-time feedback to users.
- Integrated trace node creation and completion for search operations, enhancing transparency and debugging capabilities.
- Updated localization files to include new messages for search status updates in both English and Chinese.
- Revised DESIGN.md to document the new output flow and trace integration for search operations.
- Added separate unit test targets for core tests and AI-related tests in the Makefile, allowing for more granular testing.
- Updated GitHub Actions workflows to include dedicated jobs for running AI tests with SQLite and core tests, enhancing CI capabilities.
- Modified existing test commands to ensure proper execution of unit tests while excluding AI-related tests where necessary.
- Updated test paths in the agent's search tests to reflect changes in the test assistant being used, ensuring accurate test execution.
- Updated the executeAutoSearch method to include an optional parameter for Skip.Keyword, allowing for conditional keyword extraction during web searches.
- Implemented logic to extract keywords only when configured and not skipped, improving search query optimization.
- Modified the Assistant's Stream method to pass options to executeAutoSearch, ensuring seamless integration of the new functionality.
- Updated DESIGN.md to document the changes in keyword extraction logic and its impact on the search process.
- Added functionality to the Assistant's Stream method to execute auto search if enabled, enhancing the search capabilities based on user configuration.
- Introduced helper methods for determining auto search eligibility, executing the search, and injecting search context into messages.
- Updated DESIGN.md to reflect the new auto search logic, including detailed descriptions of the new methods and their integration points within the search process.
- Introduced a new search object in the context to expose search methods (Web, KB, DB, All, Any, Race) for JavaScript integration.
- Implemented individual search methods with argument validation and error handling, improving the robustness of the API.
- Updated the JSAPI implementation to utilize the new search object, ensuring seamless interaction with the search functionalities.
- Enhanced documentation in DESIGN.md to reflect the new V8 binding methods and their usage, providing clear guidance for developers.
- Refactored the SearchAPI interface to replace the Parallel method with All, Any, and Race methods, inspired by JavaScript Promise patterns.
- Updated the Searcher struct to implement these new parallel search methods, improving flexibility and performance in executing multiple searches.
- Revised the JSAPI implementation to support the new parallel search methods, ensuring consistency across the API.
- Enhanced documentation in DESIGN.md to detail the new parallel search functionalities and provide usage examples, clarifying their behavior and expected outcomes.
- Introduced a new TODO.md file to outline the implementation plan and progress for the search module.
- Updated DESIGN.md to reflect changes in the directory structure and clarify the roles of various components, including the new Handler + Registry pattern for reranking and keyword extraction.
- Refactored the Searcher struct to utilize a direct reference to the rerank package, enhancing modularity and clarity in the search process.
- Modified the Search and SearchMultiple methods to include context parameters, improving flexibility for agent mode operations.
- Revised the Reranker interface to require context for Agent and MCP modes, ensuring compatibility with different reranking strategies.
- Enhanced documentation to provide comprehensive guidance on the updated search architecture and its components.
- Added initialization for the Search JSAPI factory in the Assistant module to streamline search operations.
- Updated the DESIGN.md to reflect the new architecture of the search module, including detailed descriptions of the keyword extraction and QueryDSL generation processes.
- Enhanced the interfaces for keyword extraction to require context, improving flexibility for different extraction modes.
- Revised directory structures in the documentation to clarify the organization of search-related components, ensuring comprehensive guidance for developers.
- Added logging for hook start and completion in the Assistant's Stream method to improve traceability during execution.
- Refactored the AgentGetterFunc to utilize the caller package, enhancing modularity and reducing circular dependencies.
- Updated the CallAgent function to check for the initialized AgentGetterFunc from the caller package, ensuring proper agent loading.
- Enhanced the Search handler to support an optional context parameter, improving flexibility for agent mode operations.
- Refined the agentSearch function to delegate search requests to a new AgentProvider, streamlining the search process.
- Updated DESIGN.md to reflect changes in search modes and the integration of the caller package, ensuring comprehensive documentation.
- Introduced new environment variables for TAVILY_API_KEY, SERPAPI_API_KEY, and SERPER_API_KEY in both `pr-test.yml` and `unit-test.yml` workflows to support additional search providers.
- Updated `DESIGN.md` to reflect the inclusion of SerpAPI as a search provider, detailing its usage and configuration options, including support for multiple search engines.
- Enhanced the `builtinSearch` function in `handler.go` to accommodate the new SerpAPI provider, ensuring proper handling of search requests.
- Revised the `WebConfig` struct in `config.go` to include an `Engine` field for specifying the search engine when using SerpAPI, improving flexibility in search configurations.
- Updated documentation to clarify the roles of new search providers and their integration within the search module, ensuring comprehensive guidance for developers.
- Updated the `QueryDSLGenerator` interface to use `gou.QueryDSL` and `model.Model` types for improved compatibility with Yao's query system.
- Revised the `Request` struct to incorporate GOU types for `Wheres` and `Orders`, enhancing the integration with the GOU QueryDSL format.
- Removed deprecated `QueryWhere` and `QueryOrder` types, streamlining the codebase and reducing redundancy.
- Enhanced documentation in `DESIGN.md` to reflect these changes and provide guidance on using GOU types directly.
- Introduced a new search configuration structure, allowing for detailed settings for web, knowledge base, database, citation, and weights.
- Updated the `Assistant` model to include a `Search` field, enabling assistant-specific search configurations.
- Enhanced the loading and merging logic for search configurations, ensuring global defaults can be overridden by assistant-specific settings.
- Added comprehensive tests for loading, saving, and updating assistants with search configurations, verifying the integrity of search settings.
- Updated documentation in DESIGN.md to reflect the new search configuration hierarchy and usage, clarifying the interaction between global and assistant-level settings.
- Updated the flowchart to enhance the representation of the search process, clarifying the conditions under which search is skipped or auto-triggered.
- Revised labels in the flowchart for better readability and understanding of the search control logic, ensuring consistency with recent documentation updates.
- Introduced a `uses` field in the return structure of the `Create` function to manage auto search behavior, setting it to "disabled" when handled by hooks.
- Revised flowchart and sequence diagrams to reflect the new `Uses.Search` control logic, enhancing clarity on search decision-making processes.
- Updated the `SearchUses` struct to encapsulate search-specific configurations, improving documentation on search mode options.
- Enhanced the documentation to detail the hierarchy of search configuration, clarifying how global, assistant, and hook-level settings interact.
- Added examples demonstrating the new search control values and their implications for auto search behavior.
- Revised the `Uses` struct documentation to reflect the new format for MCP tool references, changing from `mcp:<server-id>` to `mcp:<server>.<tool>`.
- Enhanced examples and descriptions throughout the document to illustrate the updated MCP tool usage in various search modes.
- Improved clarity on the configuration options for keyword extraction, QueryDSL generation, and reranking, ensuring consistency with the new MCP format.
- Updated error handling documentation to address the new MCP tool parsing logic, enhancing developer understanding of potential issues.
- Introduced a new `Uses` struct to encapsulate configuration for search modes, including `builtin`, `agent`, and `mcp`.
- Updated the `Searcher` initialization to utilize the new `Uses` struct for improved clarity and flexibility in search handling.
- Expanded documentation to detail the three web search modes, their functionalities, and the corresponding configuration options.
- Added examples illustrating the AI-powered search flow when using the agent mode, enhancing understanding of intent-aware search capabilities.
- Clarified the roles of built-in providers and the MCP server in the search process, ensuring comprehensive guidance for developers.
- Renamed the `config/` directory to `defaults/` to better reflect its purpose for default configuration values.
- Updated references throughout the documentation to align with the new directory structure.
- Clarified the configuration loading process, detailing how global and assistant-level configurations are merged.
- Enhanced the explanation of the `Searcher` struct and its initialization, emphasizing the use of merged configuration.
- Added new sections to document the configuration merging process for both global and assistant-specific settings, improving overall understanding of the search module's architecture.
- Modified the test case in agent_next_test.go to use a deterministic sub-scenario, reducing flakiness in tests caused by unpredictable LLM responses.
- Enhanced DESIGN.md to clarify the structure and organization of the search module, including detailed descriptions of new types, interfaces, and configuration options.
- Updated the documentation to reflect changes in the citation system, source weighting, and the overall architecture of the search module, ensuring consistency and better understanding for developers.
- Added detailed guidelines for citation output format, including HTML link attributes for reference integration.
- Introduced examples demonstrating the correct usage of citation links in LLM outputs, improving clarity for developers.
- Updated documentation to ensure consistency in citation practices across the search module, aiding in the integration of references.
- Replaced the previous text-based data flow representation with a flowchart using Mermaid syntax for improved readability and understanding.
- Streamlined the depiction of data sources and their relationships, clarifying the flow from content module to LLM input.
- Updated the documentation to ensure consistency with the new visual format, aiding in the comprehension of the search module's architecture.
- Added new fields to the ResultItem struct for source type, weight, and relevance score to improve context building for LLM.
- Updated the documentation to clarify the source weighting system, detailing how user, hook, and auto sources are prioritized.
- Introduced a unified context protocol for handling references across different data sources, ensuring consistent formatting and processing flow.
- Enhanced examples and behavior rules to reflect the new structure and clarify the integration of source weighting in search results.
- Refined the description of Global Configuration to specify the roles of `agent/agent.yml` and `agent/search.yao` in search options.
- Added detailed information on the `uses` configuration, including keyword extraction, QueryDSL generation, and reranking methods.
- Enhanced documentation to improve understanding of how configuration layers interact and override each other, aiding in the customization of the search module.
- Modified the reranking section to specify "builtin" as the default score-based reranking method, replacing previous terminology.
- Updated the RerankOptions structure to reflect changes in parameter names and types, including the transition from `topK` to `topN`.
- Enhanced documentation to clarify how reranker types are determined in the configuration file, improving overall understanding of the search module's reranking capabilities.
- Updated comments and structure in the configuration section to better distinguish between keyword extraction, QueryDSL generation, and rerank options.
- Removed redundant comments and streamlined the configuration keys for improved clarity and consistency.
- Enhanced documentation to reflect the new organization of configuration settings, aiding in understanding the search module's functionality.
- Changed the configuration key from `uses.dsl` to `uses.query` for clarity in the search processing tools section.
- Updated documentation to ensure consistency in the description of query processing methods and their corresponding configurations.
- Enhanced examples to align with the new configuration terminology, improving understanding of the search module's functionality.
- Revised the configuration details for keyword extraction, QueryDSL generation, and reranking tools, specifying the roles of built-in, agent, and MCP server options.
- Enhanced the formatting section to improve clarity on tool usage and examples, ensuring better understanding of the search module's capabilities.
- Updated examples to reflect the new configurations, providing clearer guidance on how to utilize the search processing tools effectively.
- Updated the configuration section to outline a three-layer hierarchy for settings: System Built-in Defaults, Global Configuration, and Assistant Configuration.
- Expanded the uses configuration details in `agent/agent.yml`, specifying processing tools for keyword extraction, QueryDSL generation, and reranking.
- Enhanced the explanation of system defaults and their role in the configuration process, providing clearer guidance on how to override settings at different levels.
- Added detailed examples for each configuration layer, improving understanding of the search module's behavior and customization options.
- Updated the section on user message processing to clarify that users only specify data source IDs, with filters generated by the Search module from natural language input.
- Added a detailed example illustrating the extraction of queries and the generation of QueryDSL for data sources, improving understanding of the Search module's functionality.
- Introduced a new section in DESIGN.md detailing the integration of the content module for handling user messages with data source references.
- Defined various DataSource types including model, KB collection, KB document, table, API, and MCP resource.
- Provided an example of a user message containing data references and outlined the processing flow in the content.Vision() function.
- Specified the implementation details for the processDataContent() function in content/content.go, enhancing the search module's reusability for auto search and explicit data content references.
- Adjusted sleep durations to 1100ms to enhance test stability in CI environments.
- Modified timestamp calculations to ensure millisecond precision, improving event timing accuracy in tests.
