Changelog

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All notable changes to this project will be documented in this file.

The format is based on Keep a Changelog, and this project adheres to Semantic Versioning.

0.11.0

Changed

mix ragex.chat — agent-based RAG via Ragex MCP tools

User queries are now answered exclusively by the agent executor (ReAct loop) instead of the previous two-path approach (pipeline first, agent fallback). The AI actively calls Ragex MCP query tools (hybrid_search, semantic_search, read_file, query_graph, find_callers, etc.) to retrieve relevant code context before composing its answer. This means the AI drives the retrieval rather than having pre-fetched context injected on its behalf.

Behavioural changes:

  • The --strategy option is accepted for compatibility but no longer has any effect; all queries go through the agent ReAct loop.
  • Blocking Core.chat/3 is always used (not streaming) to ensure tool-call responses are captured correctly on providers that mix content and tool_call deltas (e.g. DeepSeek R1).
  • The conversation system prompt no longer caps tool calls at 2-3 per turn; the AI may call as many tools as needed for a thorough answer.
  • The old render_stream / Pipeline.stream_query path has been removed.

mix ragex.audit — AI report enriched with RAG evidence retrieval

The AI assistant generating the audit report can now call read-only Ragex MCP query tools to retrieve concrete code-level evidence for its findings (e.g. quote an actual function body, confirm a circular dependency path, or check coupling metrics) rather than being limited to the pre-computed statistics alone.

The tool set passed to the executor is restricted to ToolSchema.rag_tool_names/0 (10 read-only tools: read_file, semantic_search, hybrid_search, query_graph, list_nodes, find_callers, find_paths, find_circular_dependencies, coupling_report, graph_stats). Heavy re-analysis tools are excluded so the pipeline is not re-triggered.

Added

  • ToolSchema.rag_tool_names/0 — returns the list of 10 read-only RAG query tool names.
  • ToolSchema.rag_query_tools/1 — returns those tools formatted for a given AI provider (:openai, :anthropic, :deepseek_r1, :ollama).

Planned

  • Additional language support (Go, Rust, Java)
  • Cross-language refactoring via Metastatic
  • Production optimizations
  • Enhanced semantic analysis for advanced refactoring operations

0.2.0 - 2026-01-27

Added

  • Comprehensive library packaging for Hex publication
  • ExDoc documentation generation with logo and assets
  • Module grouping and documentation extras
  • Quality aliases for CI/CD integration
  • Dialyzer configuration with ignore patterns

Changed

  • Updated project structure to library format
  • Enhanced mix.exs with package metadata
  • Improved dependency management
  • Updated Metastatic dependency to ~> 0.5

0.1.0 - 2026-01-24

Added

Core Features

  • MCP Server Protocol: JSON-RPC 2.0 over stdio and socket
  • Multi-language code analysis (Elixir, Erlang, Python, JavaScript/TypeScript)
  • Knowledge graph with ETS-based storage
  • Local ML embeddings via Bumblebee (sentence-transformers/all-MiniLM-L6-v2)
  • Semantic search and hybrid retrieval (RRF)
  • Advanced graph algorithms (PageRank, centrality, community detection)

Code Editing Capabilities

  • Safe file editing with atomic operations and backups
  • Multi-language syntax validation
  • Multi-file atomic transactions
  • Semantic refactoring (rename function/module)
  • Advanced refactoring operations (8 types: extract_function, inline_function, etc.)
  • Format integration (mix, rebar3, black, prettier)

Analysis & Quality

  • Code duplication detection (AST-based Type I-IV clones)
  • Dead code detection (interprocedural + intraprocedural)
  • Dependency analysis and coupling metrics
  • Impact analysis with risk scoring
  • Automated refactoring suggestions with RAG-powered advice

AI Features

  • AI-enhanced validation error explanations
  • Refactoring preview with risk assessment
  • Dead code false positive reduction
  • Semantic Type IV clone detection
  • Architectural insights for coupling/dependencies
  • Feature flags with graceful degradation
  • Automatic caching (3-7 day TTLs)

Production Features

  • Custom embedding models (4 pre-configured)
  • Embedding persistence and caching
  • Incremental updates with file tracking
  • Path finding limits for dense graphs
  • MCP streaming notifications
  • Graph visualization (Graphviz DOT, D3.js JSON)

MCP Tools (15 total)

  • Code analysis: analyze_file, analyze_directory, query_graph, list_nodes
  • Semantic search: semantic_search, hybrid_search, get_embeddings_stats
  • Graph algorithms: find_paths, graph_stats, betweenness_centrality, closeness_centrality, detect_communities, export_graph
  • Code editing: edit_file, validate_edit, rollback_edit, edit_history, edit_files, refactor_code, advanced_refactor
  • Analysis: find_duplicates, find_similar_code, find_dead_code, analyze_dead_code_patterns
  • Quality: analyze_dependencies, find_circular_dependencies, coupling_report, analyze_quality, quality_report, find_complex_code
  • Impact: analyze_impact, estimate_refactoring_effort, risk_assessment
  • Suggestions: suggest_refactorings, explain_suggestion
  • AI features: validate_with_ai, preview_refactor (AI-enhanced)

MCP Resources

  • Graph statistics, cache status, model configuration
  • Project index, algorithm catalog, analysis summary

MCP Prompts

  • Analyze Architecture (shallow/deep)
  • Find Impact, Explain Code Flow

Documentation

  • Comprehensive README with features overview
  • ALGORITHMS.md: Graph algorithm reference
  • ANALYSIS.md: Code analysis guide
  • SUGGESTIONS.md: Refactoring suggestions guide
  • CONFIGURATION.md: Configuration reference
  • PERSISTENCE.md: Caching and persistence
  • PROMPTS.md: MCP prompts guide
  • RESOURCES.md: MCP resources reference
  • STREAMING.md: Streaming notifications guide
  • USAGE.md: Usage examples