5.1 KiB
summary, read_when
| summary | read_when | ||
|---|---|---|---|
| Run Clawdbot with Ollama (local LLM runtime) |
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Ollama
Ollama is a local LLM runtime that makes it easy to run open-source models on your machine. Clawdbot integrates with Ollama's OpenAI-compatible API and can auto-discover tool-capable models when you opt in with OLLAMA_API_KEY (or an auth profile) and do not define an explicit models.providers.ollama entry.
Quick start
-
Install Ollama: https://ollama.ai
-
Pull a model:
ollama pull llama3.3
# or
ollama pull qwen2.5-coder:32b
# or
ollama pull deepseek-r1:32b
- Enable Ollama for Clawdbot (any value works; Ollama doesn't require a real key):
# Set environment variable
export OLLAMA_API_KEY="ollama-local"
# Or configure in your config file
clawdbot config set models.providers.ollama.apiKey "ollama-local"
- Use Ollama models:
{
agents: {
defaults: {
model: { primary: "ollama/llama3.3" }
}
}
}
Model discovery (implicit provider)
When you set OLLAMA_API_KEY (or an auth profile) and do not define models.providers.ollama, Clawdbot discovers models from the local Ollama instance at http://127.0.0.1:11434:
- Queries
/api/tagsand/api/show - Keeps only models that report
toolscapability - Marks
reasoningwhen the model reportsthinking - Reads
contextWindowfrommodel_info["<arch>.context_length"]when available - Sets
maxTokensto 10× the context window - Sets all costs to
0
This avoids manual model entries while keeping the catalog aligned with Ollama's capabilities.
To see what models are available:
ollama list
clawdbot models list
To add a new model, simply pull it with Ollama:
ollama pull mistral
The new model will be automatically discovered and available to use.
If you set models.providers.ollama explicitly, auto-discovery is skipped and you must define models manually (see below).
Configuration
Basic setup (implicit discovery)
The simplest way to enable Ollama is via environment variable:
export OLLAMA_API_KEY="ollama-local"
Explicit setup (manual models)
Use explicit config when:
- Ollama runs on another host/port.
- You want to force specific context windows or model lists.
- You want to include models that do not report tool support.
{
models: {
providers: {
ollama: {
// Use a host that includes /v1 for OpenAI-compatible APIs
baseUrl: "http://ollama-host:11434/v1",
apiKey: "ollama-local",
api: "openai-completions",
models: [
{
id: "llama3.3",
name: "Llama 3.3",
reasoning: false,
input: ["text"],
cost: { input: 0, output: 0, cacheRead: 0, cacheWrite: 0 },
contextWindow: 8192,
maxTokens: 8192 * 10
}
]
}
}
}
}
If OLLAMA_API_KEY is set, you can omit apiKey in the provider entry and Clawdbot will fill it for availability checks.
Custom base URL (explicit config)
If Ollama is running on a different host or port (explicit config disables auto-discovery, so define models manually):
{
models: {
providers: {
ollama: {
apiKey: "ollama-local",
baseUrl: "http://ollama-host:11434/v1"
}
}
}
}
Model selection
Once configured, all your Ollama models are available:
{
agents: {
defaults: {
model: {
primary: "ollama/llama3.3",
fallback: ["ollama/qwen2.5-coder:32b"]
}
}
}
}
Advanced
Reasoning models
Clawdbot marks models as reasoning-capable when Ollama reports thinking in /api/show:
ollama pull deepseek-r1:32b
Model Costs
Ollama is free and runs locally, so all model costs are set to $0.
Context windows
For auto-discovered models, Clawdbot uses the context window reported by Ollama when available, otherwise it defaults to 8192. You can override contextWindow and maxTokens in explicit provider config.
Troubleshooting
Ollama not detected
Make sure Ollama is running and that you set OLLAMA_API_KEY (or an auth profile), and that you did not define an explicit models.providers.ollama entry:
ollama serve
And that the API is accessible:
curl http://localhost:11434/api/tags
No models available
Clawdbot only auto-discovers models that report tool support. If your model isn't listed, either:
- Pull a tool-capable model, or
- Define the model explicitly in
models.providers.ollama.
To add models:
ollama list # See what's installed
ollama pull llama3.3 # Pull a model
Connection refused
Check that Ollama is running on the correct port:
# Check if Ollama is running
ps aux | grep ollama
# Or restart Ollama
ollama serve
See Also
- Model Providers - Overview of all providers
- Model Selection - How to choose models
- Configuration - Full config reference