WHAT: Fix critical CLI crash with content.filter() error and implement OpenAI Responses API integration with comprehensive testing
WHY: CLI was crashing with 'TypeError: undefined is not an object (evaluating "content.filter")' when using OpenAI models, preventing users from making API calls. Additionally needed proper Responses API support with reasoning tokens.
HOW:
• Fix content extraction from OpenAI response structure in legacy path
• Add JSON/Zod schema detection in responsesAPI adapter
• Create comprehensive test suite for both integration and production scenarios
• Document the new adapter architecture and usage
CRITICAL FIXES:
• claude.ts: Extract content from response.choices[0].message.content instead of undefined response.content
• responsesAPI.ts: Detect if schema is already JSON (has 'type' property) vs Zod schema before conversion
FILES:
• src/services/claude.ts - Critical bug fix for OpenAI response content extraction
• src/services/adapters/responsesAPI.ts - Robust schema detection for tool parameters
• src/test/integration-cli-flow.test.ts - Integration tests for full flow
• src/test/chat-completions-e2e.test.ts - End-to-end Chat Completions compatibility tests
• src/test/production-api-tests.test.ts - Production API tests with environment configuration
• docs/develop/modules/openai-adapters.md - New adapter system documentation
• docs/develop/README.md - Updated development documentation
- Add WebSearchTool with DuckDuckGo integration for web search
- Provides titles, snippets, and links for current information
- Add URLFetcherTool for AI-powered web content analysis
- Fetches and converts HTML content to markdown
- Processes content using AI with user-provided prompts
- Includes 15-minute caching for efficiency
- Uses queryQuick for fast content analysis
- Register both tools in the tools registry
- Update documentation to reflect new web capabilities
- Add advanced fuzzy matching with 7+ strategies (exact, prefix, substring, acronym, initials, fuzzy, Levenshtein)
- Create comprehensive database of 500+ common Unix commands for smart autocompletion
- Implement intelligent Tab completion with @ prefix injection for agents and files
- Add sophisticated input pattern recognition for commands like "dao", "gp5", "py3"
- Enhance mention system with TaskProgressMessage component for better user feedback
- Update documentation with comprehensive intelligent completion guide
- Clean up 21 temporary markdown files to maintain repository cleanliness
- Improve project structure and configuration documentation
- Optimize completion system performance with advanced caching and scoring
- Update project branding from claude-cli to Kode
- Reorganize documentation with new development guides
- Add CONTRIBUTING.md and Chinese README
- Remove worktree_merge command and relocate system-design.md
- Update dependencies and package configuration
- Improve custom commands service with better error handling
- Clean up storage utilities and debug logging
