Techalicious Academy / 2026-02-24-openclaw-ollama

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USING OPENCLAW

Good news: you do not need WhatsApp, Telegram, or any messaging platform to use OpenClaw. The built-in interfaces work great and don't require any external services.

The Web Dashboard

The fastest way to start chatting:

openclaw dashboard

This opens your browser to http://127.0.0.1:18789/ with an authenticated URL (the gateway token is embedded). You get a full chat interface where you can type messages, see responses, and monitor tool calls in real time.

This is the best option for demos. Visual, easy to understand, works in any browser. No setup beyond what we've already done.

The Terminal UI

If you prefer staying in the terminal:

openclaw tui

This gives you an interactive chat right in your terminal. It supports slash commands:

/status       Check connection to Ollama
/model        Switch models (e.g., /model ollama/qwen2.5-coder:14b)
/new          Start a new conversation session
/history      View past sessions

Prefix commands with ! to run shell commands directly:

!git status
!ls -la

The TUI is lightweight and keeps everything in one window. Nice for working alongside other terminal tools.

One-Shot CLI

For scripting or quick questions:

openclaw agent --message "List the files in my home directory"

This sends a single message, gets a response, and exits. Useful for automation or when you just want a quick answer without entering an interactive session.

Add --thinking high for more detailed reasoning:

openclaw agent --message "Explain this error: <paste error here>" --thinking high

What You Can Do With It

Once you're in a conversation (via Dashboard, TUI, or CLI), the agent can do things on your behalf. This is where tool calling comes in. The model doesn't just generate text. It can invoke tools to interact with your system.

Try these, escalating in complexity:

Basic response test:
"What day is it today?"
This confirms the model responds at all. If you get nothing, check
the troubleshooting section.

Tool-calling test:
"List the files in my current directory"
The agent should invoke a shell command and return real results from
your filesystem. If it describes what it WOULD do instead of actually
doing it, tool calling isn't working. Check that your model supports
tool calling (qwen2.5-coder:14b does) and that the "api" field in
your config is set correctly.

Multi-step test:
"Create a file called test.txt with 'Hello from OpenClaw' inside it,
then read it back to me"
This tests file I/O tools and multi-step reasoning. The agent should
create the file, then read it, then report the contents.

Code generation test:
"Write a Python script that downloads a web page and counts the
word frequencies, then save it as wordcount.py"
This tests the agent's ability to write code and save files.

Optional: Connecting Telegram

If you want a more impressive demo, Telegram is the simplest messaging platform to set up. It uses long-polling, which means no public URL, no webhooks, no port forwarding. Everything works behind your NAT.

  1. Open Telegram. Message @BotFather. Send /newbot.
  2. Follow the prompts to name your bot. Copy the bot token.
  3. During openclaw onboard (or manually in the config), select Telegram and enter the token.
  4. Message your new bot on Telegram. You'll receive a pairing code.
  5. Approve: openclaw pairing approve telegram <CODE>

Now you can chat with your local AI through Telegram on your phone. The messages go through Telegram's servers (encrypted) but the AI processing happens entirely on your Mac.

Important caveat: all messaging platforms (Telegram, WhatsApp, Discord, Signal) require their respective cloud servers for message transport. For a truly air-gapped setup with zero cloud contact, use the Web Dashboard or TUI only.

Session Management

OpenClaw maintains conversation sessions. Each session has its own context and history. Sessions are stored locally at:

~/.openclaw/agents/<agentId>/sessions/

If Ollama crashes mid-conversation (it happens), don't panic. The session state is preserved independently. Restart Ollama, send another message, and OpenClaw reconnects automatically. You might need to re-warm the model:

ollama run qwen2.5-coder:14b "ping" --verbose

The conversation continues where it left off.

Checking The Logs

If something seems off, watch the logs in real time:

openclaw logs --follow

In another terminal, send a message through the Dashboard or TUI. Watch the log output for errors, warnings, or references to cloud providers (which would indicate the local-only configuration isn't working).

Log files are stored at:

/tmp/openclaw/openclaw-YYYY-MM-DD.log

They're in JSON lines format (one JSON object per line). For verbose debugging:

OPENCLAW_LOG_LEVEL=debug openclaw gateway run --verbose

This produces a LOT of output. Useful for diagnosing stubborn issues, overwhelming for everyday use.