SkrOYC/better-context

AI Summary: This issue proposes refactoring the 'btca' (better-context) codebase to reduce over-engineering. The current architecture includes complex event systems, repository caching, and configuration management that increase maintenance burden without proportional value. The goal is to simplify these components, drawing inspiration from a simpler reference implementation, to preserve core features with significantly less complexity.

AI Summary: This issue aims to address several performance bottlenecks in the current implementation. Key areas of focus include optimizing server instance usage, introducing response caching, implementing parallel processing for sequential operations, and reducing redundant API calls. The goal is to improve overall efficiency and resource utilization.

AI Summary: This issue aims to enhance the type safety of SDK usage by strengthening type assertions, standardizing type definitions between the SDK and local code, and improving error and event handling with more robust typing. The goal is to reduce type-related bugs and improve overall code quality.

AI Summary: This issue aims to significantly improve the system's event processing capabilities by addressing manual filtering, memory issues with long streams, and the lack of backpressure handling. The proposed solution involves implementing robust buffering, backpressure mechanisms, event type-specific handlers with error isolation, and better memory management for long-running streams.

AI Summary: This issue proposes to significantly improve the application's configuration and validation processes. Key changes include shifting validation from runtime to startup, implementing caching for validation results to boost performance, and enabling dynamic configuration updates without requiring a service restart. The goal is to make configuration more robust, efficient, and user-friendly.

AI Summary: This issue aims to significantly improve concurrent session management by addressing manual port management, lack of resource coordination, and potential resource exhaustion. The proposed solution involves implementing session pooling, a coordination system for multiple instances, resource limits, monitoring, and exploring server instance sharing to optimize resource usage and prevent exhaustion.

AI Summary: This issue proposes enhancing the OpenCode SDK's error handling and resilience. It aims to implement sophisticated retry logic with exponential backoff, improve error propagation and user feedback, and develop more robust port exhaustion handling to prevent inconsistent session states and transient failures.

AI Summary: This issue addresses critical resource management problems within the OpenCode SDK, aiming to prevent orphaned processes, memory leaks, and ensure proper cleanup of server instances. The proposed solution involves implementing session timeouts, graceful shutdown procedures, and robust process monitoring to enhance stability and reliability.

AI Summary: This issue proposes a comprehensive overhaul of how the Opencode SDK is used within the Better Context codebase. Key areas for improvement include robust resource management, enhanced error handling with retry mechanisms, efficient concurrent session management, optimized configuration and validation, and improved event processing with backpressure handling. The goal is to increase reliability, performance, and maintainability.

AI Summary: This epic aims to simplify the btca tool by removing its TUI, server, and background instance functionalities, focusing solely on its core CLI 'ask' command for AI-powered local code search. The project involves refactoring the codebase, updating the build system and documentation, and aims to reduce the codebase size by approximately 60%.