LocalChat

A fully offline chat interface for your local Ollama models. No cloud. No telemetry. Runs a lightweight Python backend with optional RAG support.

Features

• Real-time streaming responses from any Ollama model
• Sidebar with grouped chat history (Today / Yesterday / Last 7 days / Older)
• Rename and delete chats
• Switch models mid-chat via a dropdown in the header
• Markdown rendering with syntax-highlighted code blocks
• Copy button on code blocks and messages
• Dark / light theme toggle
• Chat history persisted in localStorage (survives refreshes)
• Clear chat without losing the session
• RAG (Retrieval-Augmented Generation) support via ChromaDB
• Python FastAPI backend proxies all Ollama requests (avoids CORS issues)

Prerequisites

1. Ollama must be installed and running.

   • Install: https://ollama.com or curl -fsSL https://ollama.com/install.sh | sh

   • Start: ollama serve (or it may already be running as a systemd service)

   • Pull at least one model: ollama pull llama3.2

2. Node.js 18+ and npm (for building the frontend).

3. Python 3.10+ and pip (for the backend).

Setup

# Clone or copy the project
git clone https://github.com/macbuildssys/ollama-orig.git

cd ollama-orig

# Install frontend dependencies (one-time)
npm install

# Create and activate a Python virtual environment (one-time)
python3 -m venv venv

source venv/bin/activate   # fish shell: source venv/bin/activate.fish

# Install backend dependencies (one-time)
pip install -r requirements.txt

# Build the frontend
npm run build

Run

source venv/bin/activate   # fish shell: source venv/bin/activate.fish

python3 run.py

Open http://localhost:8765 in your browser.

The backend proxies all Ollama requests, so you do not need to configure CORS settings in Ollama.

Accessing from Another Machine or VM

By default, LocalChat binds to 127.0.0.1:8765 and is only reachable from the same machine.

To allow access from another device on your network (e.g. a VM host or a second machine), start with:

OLLAMA_HOST=0.0.0.0 python3 run.py

Alternatively, edit the script run.py and change the uvicorn host from 0.0.0.0 to `127.0.0.1 (this is the current default). Then open the machine's local network IP in your browser:

http://192.168.x.x:8765

Note: crypto.randomUUID() requires a secure context in modern browsers. When accessing over plain HTTP from a non-localhost address, the app patches this automatically. If you see UUID-related errors, rebuild after pulling the latest changes.

If the host Ollama is on a different machine than where LocalChat is running, set the OLLAMA_HOST environment variable before starting:

OLLAMA_HOST=http://192.168.xxx.xxx:11434 python3 run.py

Make sure Ollama on the remote machine is also bound to 0.0.0.0:

# On the machine running Ollama, edit its systemd service:

sudo systemctl edit ollama

# Add (Add the service and environment as shown below):

# [Service]
Environment="OLLAMA_HOST=0.0.0.0:11434"

# Restart ollama:

sudo systemctl restart ollama

Current Models (example: ollama list)

qwen3:4b                   2.5 GB
phi4-mini:latest           2.5 GB
llama3.2:3b                2.0 GB
ministral-3:3b             3.0 GB
deepseek-r1:1.5b           1.1 GB
gemma4:e4b                 9.6 GB
nomic-embed-text:latest    274 MB

All of these appear automatically in the model dropdown once Ollama is running.

Adding New Models

ollama pull mistral

ollama pull codellama

ollama pull deepseek-coder-v2

Refresh the browser tab after pulling. The new model appears in the dropdown immediately.

Build for Production

npm run build

python3 run.py

The backend serves the built frontend directly. There is no separate static file server needed.

Data Storage

Chat sessions are stored in your browser's localStorage under the key localchat-v1. No chat data is written to disk by the app itself.

RAG document embeddings are stored in a local ChromaDB database at ./chroma_db/ inside the project directory. This persists across restarts.

To export or back up chats, open DevTools (F12 or Ctrl + Shift + I) and navigate to Application > Local Storage (Chrome) or Storage > Local Storage (Firefox), then copy the JSON value under the localchat-v1 key.

Troubleshooting

"Could not connect to Ollama"

• Run ollama serve in a terminal.

• Check ss -tlnp | grep 11434 to confirm Ollama is listening.

• If Ollama is on a different machine, set OLLAMA_HOST as described above and ensure port 11434 is not blocked by a firewall.

Backend fails to start with ModuleNotFoundError

• Make sure the virtual environment is activated: source venv/bin/activate.fish

• Run pip install -r requirements.txt inside the venv.

Model not appearing in the dropdown

• Run ollama list to verify it is downloaded.

• Refresh the browser tab.

Slow responses

• Normal for large models (gemma4, phi4, etc.) on CPU.

• Use qwen3:4b or llama3.2:3b for faster responses on lighter hardware.

Port 8765 not reachable from another machine

• Check the firewall on the machine running LocalChat: sudo ufw allow 8765

• Confirm the backend is bound to 0.0.0.0 and not 127.0.0.1.

Tech Stack

Layer	Technology
UI framework	React 18 + TypeScript + Vite
Styling	Tailwind CSS
State / store	Zustand (persisted to localStorage)
Markdown	react-markdown + remark-gfm
Highlighting	rehype-highlight + highlight.js
Icons	lucide-react
Fonts	DM Sans + JetBrains Mono (Google Fonts)
Backend	Python + FastAPI + uvicorn
RAG / embeddings	ChromaDB
HTTP client	httpx
LLM backend	Ollama (local)

License

Distributed under the MIT License. See LICENSE.