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Jon Saad-FalconandClaude Opus 4.6
638d8780a0
Four new docs matching the morning-digest.md pattern: - deep-research.md — multi-hop research with document indexing - code-assistant.md — orchestrator with code execution + file I/O - scheduled-monitor.md — persistent operative on cron schedule - chat-simple.md — lightweight chat, simplest setup Updated quickstart with tabs for all agent types and expanded starter configs table from 3 to 7 presets. Updated MkDocs nav and index page to link all 5 user guides. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
155 lines
4.2 KiB
Markdown
155 lines
4.2 KiB
Markdown
# Simple Chat
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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.
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## Quickstart (3 minutes)
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### 1. Install Ollama and pull a model
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```bash
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# Install Ollama: https://ollama.com
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ollama pull qwen3.5:4b
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```
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### 2. Install and initialize OpenJarvis
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```bash
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git clone https://github.com/open-jarvis/OpenJarvis.git
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cd OpenJarvis
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uv sync
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jarvis init --preset chat-simple
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```
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### 3. Ask a question
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```bash
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jarvis ask "What is quantum computing?"
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```
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That's it. No API keys, no tools, no cloud -- just a local model answering your questions.
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## CLI Commands
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```bash
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# Single question
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jarvis ask "Explain the difference between TCP and UDP"
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# Interactive chat session (multi-turn conversation)
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jarvis chat
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# Start the API server for the browser or desktop app
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jarvis serve
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# Override the model for a single query
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jarvis ask -m qwen3.5:9b "Explain general relativity"
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# Adjust temperature (0.0 = deterministic, 1.0 = creative)
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jarvis ask -t 0.2 "List the planets in our solar system"
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# Output raw JSON
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jarvis ask --json "What is 2+2?"
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```
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## Configuration Reference
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The preset writes this to `~/.openjarvis/config.toml`:
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```toml
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[engine]
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default = "ollama"
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[intelligence]
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default_model = "qwen3.5:4b" # Fast and lightweight
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# default_model = "qwen3.5:9b" # Better quality
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# default_model = "llama3.1:8b" # Alternative model
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[agent]
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default_agent = "simple" # Single-turn, no tools
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[server]
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host = "0.0.0.0"
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port = 8000
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```
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### Model options
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| Model | Parameters | Speed | Quality | Best for |
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|-------|-----------|-------|---------|----------|
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| `qwen3.5:4b` | 4B | Fast | Good | Quick answers, lightweight hardware |
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| `qwen3.5:9b` | 9B | Balanced | Better | General-purpose chat, explanations |
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| `qwen3.5:35b` | 35B | Slower | Best | Complex reasoning, detailed analysis |
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| `llama3.1:8b` | 8B | Balanced | Good | Alternative if you prefer Meta models |
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To switch models, either edit `~/.openjarvis/config.toml` or override per-query:
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```bash
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jarvis ask -m qwen3.5:35b "Write a detailed comparison of REST and GraphQL"
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```
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To pull a new model:
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```bash
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ollama pull qwen3.5:35b
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```
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## Using the Browser App
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Start the backend server and the React frontend with one command:
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```bash
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./scripts/quickstart.sh
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```
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This opens [http://localhost:5173](http://localhost:5173) in your browser with a full chat interface, streaming responses, and an energy monitoring dashboard.
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To run just the API server (for use with the desktop app or external clients):
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```bash
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jarvis serve
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```
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The server is OpenAI-compatible, so any client that works with the OpenAI API can point to `http://localhost:8000/v1`.
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## Using the Desktop App
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1. Start the backend: `jarvis serve` (or `./scripts/quickstart.sh`)
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2. Download and open the desktop app from the [releases page](https://github.com/open-jarvis/OpenJarvis/releases)
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3. The app connects to `http://localhost:8000` automatically
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## Switching Models
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You can change the default model at any time:
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**Edit the config:**
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```bash
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# Open the config file
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${EDITOR:-nano} ~/.openjarvis/config.toml
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# Change default_model to your preferred model
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```
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**Pull and switch in one step:**
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```bash
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ollama pull deepseek-r1:14b
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jarvis ask -m deepseek-r1:14b "Hello"
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```
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**Use an environment variable:**
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```bash
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OPENJARVIS_MODEL=qwen3.5:9b jarvis ask "Hello"
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```
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## Troubleshooting
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**"No running engine found"** -- Make sure Ollama is running. Start it with `ollama serve` or open the Ollama desktop app.
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**"Model not found"** -- Pull the model first with `ollama pull <model-name>`. List available models with `ollama list`.
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**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).
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**Want to add tools later?** -- Switch to the [Code Assistant](code-assistant.md) or [Deep Research](deep-research.md) config. Simple chat is intentionally minimal.
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**Browser app not loading** -- Make sure both the backend (`jarvis serve`) and frontend are running. The `./scripts/quickstart.sh` script starts both automatically.
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