charles
15dfbfb467
- Add LLM_BACKEND to environment configuration - Implement detailed debug logging for LLM request/response cycles - Add missing llama-index dependencies for embeddings and chroma - Update prompt constraints to prevent lore redundancy - Enable CUDA for transcription and set logging to DEBUG level - Add entry point for running the orchestrator directly - Cleanup unused comment in TUI context updates
D&D Helpers
D&D Helpers is designed to solve the "missing notes" problem. It focuses on the automatic extraction of game-relevant data from live conversation, turning spoken dialogue into structured records.
Core Objective: Automated Data Capture
The primary goal is to listen to game sessions and automatically identify and record critical information into structured files, while ignoring the "noise" of out-of-character (OOC) conversation.
The Pipeline
- Listen: Capture audio and convert it to text via Speech-to-Text (STT).
- Filter: An LLM analyzes the transcript to strip away OOC nonsense and non-game-relevant chatter.
- Extract: The system identifies key events and routes them to the appropriate destination:
- Lore: Narrative details, NPC introductions, and world-building are appended to Markdown files.
- Character State & Inventory: Changes to health, status effects, and loot are updated in JSON files.
- Confirm: A human-in-the-loop system suggests these updates via a CLI tool, allowing the user to confirm, edit, or reject the change before it is committed.
Features
Data Trackers
- Lore Tracker: A personal wiki for your campaign's lore, NPCs, and locations. Stored in Markdown for rich text and easy version control.
- Character & Inventory Tracker: A centralized record of character identity, stats, effects, and gear. Stored in JSON for portability and VTT compatibility.
Summarizer
Distill long sessions into concise highlights. Use LLMs to summarize recorded transcripts into a brief "The Story So Far" document.
Interface & Usage
- CLI: The primary interface for confirming automated updates and querying current game state.
- Text Editors: Since data is stored in Markdown and JSON, you can use any editor (VS Code, Vim, Obsidian) to manually refine your campaign data.
Technical Stack
- Language: Python 3.10+
- Data Persistence: Local JSON and Markdown files.
- AI Backend: vLLM / OpenAI API compatible endpoints (via
openaiPython library). - STT Engine: OpenAI Whisper (local) for high-accuracy transcription.
- Audio Capture (Linux):
sounddeviceorPyAudiofor microphone and system audio capture.ffmpegfor audio stream processing and format conversion.
- Interface:
TextualorRichfor a modern, intuitive Terminal User Interface (TUI).ClickorTyperfor command-line argument parsing.