---
name: ollama-local-dfe40773fe3e
description: Manage and use local Ollama models. Use for model management (list/pull/remove), chat/completions, embeddings, and tool-use with local LLMs. Covers OpenClaw sub-agent integration and model selection guidance.
---

# Ollama Local

Work with local Ollama models for inference, embeddings, and tool use.

## Configuration

Set your Ollama host (defaults to `http://localhost:11434`):

```bash
export OLLAMA_HOST="http://localhost:11434"
# Or for remote server:
export OLLAMA_HOST="http://192.168.1.100:11434"
```

## Quick Reference

```bash
# List models
python3 scripts/ollama.py list

# Pull a model
python3 scripts/ollama.py pull llama3.1:8b

# Remove a model
python3 scripts/ollama.py rm modelname

# Show model details
python3 scripts/ollama.py show qwen3:4b

# Chat with a model
python3 scripts/ollama.py chat qwen3:4b "What is the capital of France?"

# Chat with system prompt
python3 scripts/ollama.py chat llama3.1:8b "Review this code" -s "You are a code reviewer"

# Generate completion (non-chat)
python3 scripts/ollama.py generate qwen3:4b "Once upon a time"

# Get embeddings
python3 scripts/ollama.py embed bge-m3 "Text to embed"
```

## Model Selection

See [references/models.md](references/models.md) for full model list and selection guide.

**Quick picks:**
- Fast answers: `qwen3:4b`
- Coding: `qwen2.5-coder:7b`
- General: `llama3.1:8b`
- Reasoning: `deepseek-r1:8b`

## Tool Use

Some local models support function calling. Use `ollama_tools.py`:

```bash
# Single request with tools
python3 scripts/ollama_tools.py single qwen2.5-coder:7b "What's the weather in Amsterdam?"

# Full tool loop (model calls tools, gets results, responds)
python3 scripts/ollama_tools.py loop qwen3:4b "Search for Python tutorials and summarize"

# Show available example tools
python3 scripts/ollama_tools.py tools
```

**Tool-capable models:** qwen2.5-coder, qwen3, llama3.1, mistral

## OpenClaw Sub-Agents

Spawn local model sub-agents with `sessions_spawn`:

```python
# Example: spawn a coding agent
sessions_spawn(
    task="Review this Python code for bugs",
    model="ollama/qwen2.5-coder:7b",
    label="code-review"
)
```

Model path format: `ollama/<model-name>`

### Parallel Agents (Think Tank Pattern)

Spawn multiple local agents for collaborative tasks:

```python
agents = [
    {"label": "architect", "model": "ollama/gemma3:12b", "task": "Design the system architecture"},
    {"label": "coder", "model": "ollama/qwen2.5-coder:7b", "task": "Implement the core logic"},
    {"label": "reviewer", "model": "ollama/llama3.1:8b", "task": "Review for bugs and improvements"},
]

for a in agents:
    sessions_spawn(task=a["task"], model=a["model"], label=a["label"])
```

## Direct API

For custom integrations, use the Ollama API directly:

```bash
# Chat
curl $OLLAMA_HOST/api/chat -d '{
  "model": "qwen3:4b",
  "messages": [{"role": "user", "content": "Hello"}],
  "stream": false
}'

# Generate
curl $OLLAMA_HOST/api/generate -d '{
  "model": "qwen3:4b",
  "prompt": "Why is the sky blue?",
  "stream": false
}'

# List models
curl $OLLAMA_HOST/api/tags

# Pull model
curl $OLLAMA_HOST/api/pull -d '{"name": "phi3:mini"}'
```

## Troubleshooting

**Connection refused?**
- Check Ollama is running: `ollama serve`
- Verify OLLAMA_HOST is correct
- For remote servers, ensure firewall allows port 11434

**Model not loading?**
- Check VRAM: larger models may need CPU offload
- Try a smaller model first

**Slow responses?**
- Model may be running on CPU
- Use smaller quantization (e.g., `:7b` instead of `:30b`)

**OpenClaw sub-agent falls back to default model?**
- Ensure `ollama:default` auth profile exists in OpenClaw config
- Check model path format: `ollama/modelname:tag`


---
Source attribution: modbender
Original project: https://github.com/modbender/skill-library-mcp/blob/d9c8fe903b5b4e82237dbe8d0df8567783022e18/data/ollama-local/SKILL.md
License: MIT
License information: https://opensource.org/license/mit
Original upstream instructions; downloaded from Mega AI Hub.

## Upstream license notice

MIT License

Copyright (c) 2025 skill-library-mcp contributors

Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.



# Mega AI Hub resource metadata

Creator / publisher: modbender
Original project: https://github.com/modbender/skill-library-mcp/blob/d9c8fe903b5b4e82237dbe8d0df8567783022e18/data/ollama-local/SKILL.md
Attribution basis: Source repository record

Fields of work: Development & Engineering
Roles: Backend Developer, Data Engineer, ML / AI Engineer
Specialties: API, Backend
Tools: OpenAI API, Ollama
Country applicability: Country not specified
Classification basis: Source catalog labels
Instruction SHA-256: b29cd141addbcfe8400567118729f414bb67f0d0026240e0dc944aa3d5d75a43