Heimgeist

Heimgeist is a local desktop chat client for Ollama. It combines a Tauri + React renderer with a FastAPI backend, stores chat history in SQLite, supports optional SearXNG-backed web search, and can enrich prompts with context from local library indexes.

Features

Local desktop chat UI with Tauri
Ollama-backed chat with streaming and non-streaming replies
Persistent chat sessions and automatic title generation
Edit-and-regenerate flow for earlier user messages
Optional web search enrichment with source chips
Local library management for RAG-style prompt enrichment
Theme selection and UI scale controls

Local Libraries

The DBs tab is no longer a placeholder. You can:

create and rename libraries
register files
let Heimgeist rebuild retrieval automatically when files change
open or remove registered files from the UI

When files are added or removed, Heimgeist automatically rebuilds the local RAG pipeline for that database: corpus, enrichment, embeddings, and indexes. In the chat composer, you can select which database the current chat should use. For each chat turn, Heimgeist queries the selected database, turns the top results into a local context block, appends that block to the user prompt, and sends the enriched prompt to Ollama.

Local Data

Heimgeist stores chat history and local library indexes on the local machine. During development, the backend keeps using backend/app.db and backend/libraries so existing local data remains available.

Packaged Tauri builds should launch the backend with app-managed data paths so chats and local libraries live under the operating system's normal application data location, such as Application Support on macOS, LocalAppData on Windows, or the XDG data directory on Linux. These paths are managed by the app and are not exposed as normal user settings.

Stack

Frontend: Tauri, React, Vite
Backend: FastAPI, SQLAlchemy, SQLite
Search enrichment: SearXNG + page fetching/reranking
Local RAG pipeline: corpus build, enrichment, embedding, and retrieval helpers under backend/rag/

Development

Requirements:

Node.js 18+
Python 3.13
Ollama running locally
Optional: SearXNG on http://127.0.0.1:8888

Quick start:

./run.sh

This creates or refreshes backend/.venv, installs Python dependencies, installs npm dependencies, and starts the dev stack.

On Linux x86_64, run.sh now selects a PyTorch flavor before installing openai-whisper:

Steam Deck / SteamOS and other non-NVIDIA Linux hosts default to CPU-only PyTorch, which avoids downloading NVIDIA CUDA runtime wheels that Whisper does not need there.
NVIDIA Linux hosts keep the default PyTorch install path.
Override with HEIMGEIST_TORCH_FLAVOR=default, HEIMGEIST_TORCH_FLAVOR=cpu, or HEIMGEIST_TORCH_FLAVOR=rocm6.4.
Use HEIMGEIST_TORCH_INDEX_URL=... if you need a custom PyTorch wheel index.

Manual startup:

python3.13 -m venv backend/.venv
backend/.venv/bin/python -m pip install --upgrade pip
# Steam Deck / SteamOS / CPU-only Linux:
# backend/.venv/bin/python -m pip install --index-url https://download.pytorch.org/whl/cpu torch
backend/.venv/bin/python -m pip install -r backend/requirements.txt
npm install
npm run dev

File Tree

.
├── backend/
│   ├── main.py
│   ├── local_rag.py
│   ├── rag/
│   ├── websearch.py
│   ├── ollama_client.py
│   ├── models.py
│   ├── database.py
│   ├── paths.py
│   ├── schemas.py
│   └── requirements.txt
├── src-tauri/
│   ├── src/main.rs
│   ├── tauri.conf.json
│   └── capabilities/
├── src/
│   ├── App.jsx
│   ├── LibraryManager.jsx
│   ├── GeneralSettings.jsx
│   ├── InterfaceSettings.jsx
│   ├── WebsearchSettings.jsx
│   ├── markdown.js
│   ├── colorSchemes.js
│   └── styles.css
├── package.json
├── run.sh
└── vite.config.js

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