Simple Chat¶
A lightweight conversational AI with no tools and no agent overhead. This is the simplest possible OpenJarvis setup: just Ollama and a local model. Ideal for general-purpose chat, Q&A, brainstorming, and getting started quickly.
Quickstart (3 minutes)¶
1. Install Ollama and pull a model¶
2. Install and initialize OpenJarvis¶
git clone https://github.com/open-jarvis/OpenJarvis.git
cd OpenJarvis
uv sync
jarvis init --preset chat-simple
3. Ask a question¶
That's it. No API keys, no tools, no cloud -- just a local model answering your questions.
CLI Commands¶
# Single question
jarvis ask "Explain the difference between TCP and UDP"
# Interactive chat session (multi-turn conversation)
jarvis chat
# Start the API server for the browser or desktop app
jarvis serve
# Override the model for a single query
jarvis ask -m qwen3.5:9b "Explain general relativity"
# Adjust temperature (0.0 = deterministic, 1.0 = creative)
jarvis ask -t 0.2 "List the planets in our solar system"
# Output raw JSON
jarvis ask --json "What is 2+2?"
Configuration Reference¶
The preset writes this to ~/.openjarvis/config.toml:
[engine]
default = "ollama"
[intelligence]
default_model = "qwen3.5:4b" # Fast and lightweight
# default_model = "qwen3.5:9b" # Better quality
# default_model = "llama3.1:8b" # Alternative model
[agent]
default_agent = "simple" # Single-turn, no tools
[server]
host = "0.0.0.0"
port = 8000
Model options¶
| Model | Parameters | Speed | Quality | Best for |
|---|---|---|---|---|
qwen3.5:4b |
4B | Fast | Good | Quick answers, lightweight hardware |
qwen3.5:9b |
9B | Balanced | Better | General-purpose chat, explanations |
qwen3.5:35b |
35B | Slower | Best | Complex reasoning, detailed analysis |
llama3.1:8b |
8B | Balanced | Good | Alternative if you prefer Meta models |
To switch models, either edit ~/.openjarvis/config.toml or override per-query:
To pull a new model:
Using the Browser App¶
Start the backend server and the React frontend with one command:
This opens http://localhost:5173 in your browser with a full chat interface, streaming responses, and an energy monitoring dashboard.
To run just the API server (for use with the desktop app or external clients):
The server is OpenAI-compatible, so any client that works with the OpenAI API can point to http://localhost:8000/v1.
Using the Desktop App¶
- Start the backend:
jarvis serve(or./scripts/quickstart.sh) - Download and open the desktop app from the releases page
- The app connects to
http://localhost:8000automatically
Switching Models¶
You can change the default model at any time:
Edit the config:
# Open the config file
${EDITOR:-nano} ~/.openjarvis/config.toml
# Change default_model to your preferred model
Pull and switch in one step:
Use an environment variable:
Troubleshooting¶
"No running engine found" -- Make sure Ollama is running. Start it with ollama serve or open the Ollama desktop app.
"Model not found" -- Pull the model first with ollama pull <model-name>. List available models with ollama list.
Slow responses -- Use a smaller model (qwen3.5:4b). Check available memory; models need RAM roughly equal to their parameter count in GB (e.g., 9B model needs ~9 GB).
Want to add tools later? -- Switch to the Code Assistant or Deep Research config. Simple chat is intentionally minimal.
Browser app not loading -- Make sure both the backend (jarvis serve) and frontend are running. The ./scripts/quickstart.sh script starts both automatically.