105 lines
3.5 KiB
Markdown
105 lines
3.5 KiB
Markdown
# 🐉 Dungeon Masters Vault: Local RAG Assistant
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An advanced Retrieval-Augmented Generation (RAG) system designed for Dungeon Masters. This tool ingests markdown-based campaign notes, enriches them with AI-generated metadata, and provides an interactive terminal interface to query your world’s lore using **DSPy** and **Local LLMs**.
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## ⚔️ Key Features
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* **Parallel Enrichment:** Utilizes a configurable multithreading to process multiple document chunks simultaneously across local LLM slots for high-speed ingestion.
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* **Deep Context Retrieval:** Unlike standard RAG, this system retrieves relevant chunks and then "peeks" at the full source file to provide the LLM with broader narrative context.
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* **Local-First:** Designed to run entirely on your hardware using **LM Studio**, keeping your campaign secrets private.
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---
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## 🏗️ Architecture
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1. **Ingestion:** Scans `DATA_DIR` for `.md` files.
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2. **Chunking:** Splits documents into 800-character segments with overlap.
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3. **Enrichment:** A DSPy `IngestionAgent` analyzes each chunk to extract:
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* **Synopsis:** A one-sentence summary.
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* **Tags:** Plot points, item names, or themes.
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* **Entities:** Specific NPCs, Locations, or Factions.
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4. **Vector Store:** Chunks and metadata are embedded using `text-embedding-qwen3` and stored in a local **Turso** database.
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5. **Interactive RAG:** A terminal loop that uses **ReAct (Reasoning and Acting)** to answer queries based on retrieved context.
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---
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## 🛠️ Setup
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### Prerequisites
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* **UV [Link to install here](https://docs.astral.sh/uv/)**
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* **LM Studio:** Running a local server at `localhost:1234` (or your specific IP).
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* **Models:** * Inference & Embedding: Configurable for your preference. grab your model in LMStudio and update the conifg
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### Installation
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```bash
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uv sync
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```
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---
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## 🚀 Usage
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### 1. Ingest & Enrich
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Run the ingestion script to process your markdown files and build the vector database.
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```bash
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uv run src/ingest.py
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```
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### 2. Query the LLM
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Launch the interactive session to ask questions about your campaign.
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```bash
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uv run src/retrieve.py
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```
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**Example Query:**
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> `📝 Query: Why did the party get free bread at the Golden Grain Inn?`
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> `📜 AI RESPONSE: Based on the session notes from 'Session_12.md', the party received free bread because the Rogue successfully intimidated the baker's assistant, and the Cleric later performed a minor miracle (Thaumaturgy) that impressed the owner.`
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---
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## 📂 File Structure
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```
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.
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├── config.yaml # Configuration for the app
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├── load_ingestion_llms.sh # script to load multiple LLMs (Run before ingest)
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├── README.md
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├── ROADMAP.md
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├── src
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│ ├── config_loader.py # Loads the config yaml file
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│ ├── embedding.py # Class to talk to LMStudio Embedding Model Server
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│ ├── experts
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│ │ ├── ingestion_agent.py # Agent Class for ingestion enrichment
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│ │ └── retrieval_agent.py # Agent Class for retrieval, with tools and database calls
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│ ├── ingest.py # Ingestion script to load your DnD Campaign Notes
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│ └── retrieve.py # main Q&A for your notes
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├── data # GitIgnored Folder for Notes Database
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│ ├── dmv.db
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│ ├── dmv.db-wal
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│ ├── dmv.log
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│ └── time_file.txt
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├── pyproject.toml
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├── LICENSE
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└── uv.lock
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```
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---
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## ⚙️ Configuration
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In `config.yaml`, you can adjust multiple things:
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* Enrichment / embedding & Retrieval Mdels
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* DnD Notes Location (data_dir)
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* System Prompts for Ingestion & Retrieval Agents
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---
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