Add copilot instructions for AI agents

[ModerRAS]

This pull request adds a comprehensive Copilot instruction guide for the TelegramSearchBot project, aiming to help contributors quickly understand the architecture, configuration, and development best practices. The guide covers project structure, dependency injection, message processing, search/data management, scheduled tasks, AI/tool integration, build/test commands, developer tips, and common pitfalls.

Project architecture and configuration:

• Overview of solution structure, entry point (Program.cs), and unified configuration loading via Env.cs from %LOCALAPPDATA%/TelegramSearchBot/Config.json, with a note to avoid appsettings.json.
• Details on dependency injection, Scrutor scanning, and guidelines for adding new services to ensure proper DI registration.

Core processing and data management:

• Explanation of message processing pipeline, controller dependencies, and stateless controller design, emphasizing use of PipelineContext.PipelineCache for cross-controller data.
• Description of search/data layers, including EF Core, Lucene, Faiss vector search, and tight coupling between search controllers and services.

Scheduled tasks and AI integration:

• Instructions for implementing scheduled tasks, distributed locking/queues via Garnet/Redis, and heartbeat mechanisms to avoid task misclassification.
• Guidelines for integrating AI tools, LLM channels, and OCR/ASR/QR services, including

[Copilot]

Pull Request Overview

This PR adds comprehensive Copilot instructions to help AI assistants and contributors understand the TelegramSearchBot project architecture and development practices. The instructions provide essential guidance for working with the codebase, covering project structure, dependency injection, message processing, data management, and development workflows.

• Adds detailed project architecture overview including solution structure and configuration management
• Documents message processing pipeline, dependency injection patterns, and core development workflows
• Provides guidance on search/data layers, scheduled tasks, AI integration, and common development pitfalls

[claude]

Claude finished @ModerRAS's task —— View job

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Pull Request Review

Review Tasks:

• Read and analyze the new copilot-instructions.md file
• Evaluate code quality and best practices
• Check for potential bugs or issues
• Assess performance considerations
• Review security concerns
• analyze test coverage implications
• Provide comprehensive review feedback

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Code Quality and Best Practices ✅

Strengths:

• Comprehensive documentation covering the entire architecture
• Clear separation of concerns between controllers, services, and data layers
• Well-defined dependency injection patterns with Scrutor scanning
• Proper use of interfaces and service lifetimes
• Good emphasis on stateless controllers and service layer separation

Areas for improvement:

• Consider adding English translation for broader accessibility
• Some sections could benefit from code examples
• Missing information about error handling patterns

Potential Bugs or Issues ⚠️

Minor concerns identified:

• No mention of error handling for configuration file loading
• Missing guidance on handling database connection failures
• No documentation of fallback mechanisms for AI service failures
• Could add guidance on handling concurrent access to shared resources

Performance Considerations ⚠️

Well covered areas:

• Proper use of background services for long-running tasks
• Separate processes for OCR/ASR to prevent blocking
• Efficient use of Garnet/Redis for distributed operations
• Faiss vector indexing for semantic search

Additional recommendations:

• Consider adding guidance on memory management for large datasets
• Document any performance-critical paths or bottlenecks
• Add recommendations for monitoring and performance profiling

Security Concerns 🔒

Good practices documented:

• Proper configuration management (avoiding appsettings.json)
• Use of Windows JobObject for process isolation
• Separation of sensitive configuration to LOCALAPPDATA

Areas to enhance:

• Consider adding security best practices section
• Document any security-related configuration requirements
• Add guidance on handling user data privacy

Test Coverage 📝

Current state:

• Mentions vector testing with PowerShell script
• References xUnit test categories
• Covers basic build and test commands

Recommendations:

• Add more comprehensive testing guidance
• Document integration testing approaches
• Include guidance on testing AI service integrations
• Add performance testing recommendations

Overall Assessment ✅

This is a well-structured, comprehensive copilot instruction document that provides excellent guidance for developers working on the TelegramSearchBot project. The documentation effectively covers:

• Architecture clarity: Clear explanation of the multi-project structure and responsibilities
• Development workflow: Proper guidance on DI, controllers, and service patterns
• Operational considerations: Good coverage of background tasks, scheduling, and AI integration
• Configuration management: Proper emphasis on avoiding appsettings.json and using LOCALAPPDATA

Final recommendation: APPROVE - The documentation adds significant value to the project and follows good practices. Consider implementing the minor improvements suggested above in a follow-up update.

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[github-actions]

🔍 PR检查报告

📋 检查概览

• PR: Add copilot instructions for AI agents #163
• 分支: feature/add-copilot-instructions → master
• 触发事件: pull_request
• 提交: 0c2e465

🧪 测试结果

平台	状态	详情
Ubuntu	🔴 失败	测试结果不可用
Windows	🔴 失败	测试结果不可用

📊 代码质量

• ✅ 代码格式化检查
• ✅ 安全漏洞扫描
• ✅ 依赖包分析
• ✅ 代码覆盖率收集

📁 测试产物

• 测试结果文件已上传为artifacts
• 代码覆盖率已上传到Codecov

🔗 相关链接

• PR页面
• Actions日志

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