docs(conductor): Synchronize docs for track 'RAG Support'

2026-05-04 22:51:39 -04:00
parent 7bed4a8f97
commit af6be10d47
2 changed files with 9 additions and 1 deletions
@@ -52,6 +52,12 @@ For deep implementation details when planning or implementing tracks, consult `d
  - **Auto-Start & Discovery:** Automatically initializes configured servers on project load and dynamically aggregates their tools into the agent's capability declarations.
  - **Dedicated Operations UI:** Features a new **External Tools** section within the Operations Hub for monitoring server status (idle, starting, running, error) and browsing discovered tool schemas. Supports **Pop-Out Panel functionality**, allowing the External Tools interface to be detached into a standalone window for optimized multi-monitor workflows.
  - **Strict HITL Safety:** All external tool calls are intercepted and require explicit human-in-the-loop approval via the standard confirmation dialog before execution.
 - **Retrieval-Augmented Generation (RAG) Support:** Introduces advanced retrieval capabilities to overcome context window limitations and reduce hallucination.
  - **Multi-Source Retrieval:** Supports local vector stores (ChromaDB) and an **External RAG Bridge** via the Model Context Protocol (MCP) for connecting to third-party retrieval services.
  - **High-Performance Indexing:** Employs a parallelized indexing pipeline using `ThreadPoolExecutor` and incremental updates based on file `mtime` to handle large codebases efficiently.
  - **Deep Discussion Integration:** Retrieved context fragments are automatically prepended to agent prompts and captured in the discussion history, featuring a dedicated visualization mode with source buttons for instant file navigation.
  - **Configurable Strategy:** Users can toggle RAG globally and fine-tune retrieval parameters (source, embedding provider, chunk size/overlap) directly within the AI Settings.
  - **Automated Synchronization:** Features background re-indexing of the project workspace, ensuring the vector store remains consistent with the current project state.
 - **High-Fidelity Selectable UI:** Most read-only labels and logs across the interface (including discussion history, comms payloads, tool outputs, and telemetry metrics) are now implemented as selectable text fields. This enables standard OS-level text selection and copying (Ctrl+C) while maintaining a high-density, non-editable aesthetic.
 - **High-Fidelity UI Rendering:** Employs advanced 3x font oversampling and sub-pixel positioning to ensure crisp, high-clarity text rendering across all resolutions, enhancing readability for dense logs and complex code fragments.
 - **Enhanced MMA Observability:** Worker streams and ticket previews now support direct text selection, allowing for easy extraction of specific logs or reasoning fragments during parallel execution.
@@ -40,12 +40,14 @@
 - **src/tool_bias.py:** Implements the `ToolBiasEngine` for semantic tool description nudging and dynamic tooling strategy generation.
 - **src/tool_presets.py:** Extends `ToolPresetManager` to handle nested `Tool` models, weights, and global `BiasProfile` persistence within `tool_presets.toml`.
 - **src/mcp_client.py:** Implements the native tool registry and the `ExternalMCPManager` for orchestrating third-party Model Context Protocol servers. Provides dynamic tool discovery and validation.
  - **StdioMCPServer:** Manages local MCP servers via asynchronous subprocess pipes (stdin/stdout/stderr).
  - **RemoteMCPServer (SSE):** Provides a foundation for remote MCP integration via Server-Sent Events.
  - **JSON-RPC 2.0 Engine:** Handles asynchronous message routing, request/response matching, and error handling for all external MCP communication.
 - **src/rag_engine.py:** Core RAG implementation managing the vector store lifecycle, chunking strategies (character-based and AST-aware), and multi-provider search. Integrates with **ChromaDB** for local persistence and provides a bridge for external MCP retrieval tools.
 - **src/paths.py:** Centralized module for path resolution.
 - **tree-sitter / AST Parsing:** For deterministic AST parsing and automated generation of curated "Skeleton Views" and "Targeted Views" (extracting specific functions and their dependencies). Features an integrated AST cache with mtime-based invalidation to minimize re-parsing overhead. Supplemented by `SummaryCache` which provides persistent, hash-based (SHA256) caching with LRU eviction for AI-generated file summaries.
 - **pydantic / dataclasses:** For defining strict state schemas (Tracks, Tickets) used in linear orchestration.
 - **tomli-w:** For writing TOML configuration files.