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AutoGPT/docs/platform/ollama.md
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> [!NOTE]
> Migrates documentation to GitBook and removes the old MkDocs setup.
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## Summary by CodeRabbit

* **Documentation**
* Updated contribution guide for new documentation platform and workflow
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---------

Co-authored-by: Claude Opus 4.5 <noreply@anthropic.com>
2026-01-09 19:22:05 +00:00

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Markdown

# Running Ollama with AutoGPT
> **Important**: Ollama integration is only available when self-hosting the AutoGPT platform. It cannot be used with the cloud-hosted version.
Follow these steps to set up and run Ollama with the AutoGPT platform.
## Prerequisites
1. Make sure you have gone through and completed the [AutoGPT Setup](/platform/getting-started) steps, if not please do so before continuing with this guide.
2. Before starting, ensure you have [Ollama installed](https://ollama.com/download) on your machine.
## Setup Steps
### 1. Launch Ollama
To properly set up Ollama for network access, choose one of these methods:
**Method A: Using Ollama Desktop App (Recommended)**
1. Open the Ollama desktop application
2. Go to **Settings** and toggle **"Expose Ollama to the network"**
![Expose Ollama to Network](../imgs/ollama/Ollama-Expose-Network.png)
3. Click on the model name field in the "New Chat" window
4. Search for "llama3.2" (or your preferred model)
![Select llama3.2 model](../imgs/ollama/Ollama-Select-llama3.2.png)
5. Click on it to start the download and load the model to be used
??? note "Method B: Using Docker (Alternative)"
If you prefer to run Ollama via Docker instead of the desktop app, you can use the official [Ollama Docker image](https://hub.docker.com/r/ollama/ollama):
1. **Start Ollama container** (choose based on your hardware):
**CPU only:**
```bash
docker run -d -v ollama:/root/.ollama -p 11434:11434 --name ollama ollama/ollama
```
**With NVIDIA GPU** (requires [NVIDIA Container Toolkit](https://docs.nvidia.com/datacenter/cloud-native/container-toolkit/latest/install-guide.html)):
```bash
docker run -d --gpus=all -v ollama:/root/.ollama -p 11434:11434 --name ollama ollama/ollama
```
**With AMD GPU:**
```bash
docker run -d --device /dev/kfd --device /dev/dri -v ollama:/root/.ollama -p 11434:11434 --name ollama ollama/ollama:rocm
```
**Download your desired model:**
```bash
docker exec -it ollama ollama run llama3.2
```
!!! note
The Docker method automatically exposes Ollama on `0.0.0.0:11434`, making it accessible to AutoGPT. More models can be found on the [Ollama library](https://ollama.com/library).
??? warning "Method C: Using Ollama Via Command Line (Legacy)"
For users still using the traditional CLI approach or older Ollama installations:
1. **Set the host environment variable:**
**Windows (Command Prompt):**
```cmd
set OLLAMA_HOST=0.0.0.0:11434
```
**Linux/macOS (Terminal):**
```bash
export OLLAMA_HOST=0.0.0.0:11434
```
2. **Start the Ollama server:**
```bash
ollama serve
```
3. **Open a new terminal/command window** and download your desired model:
```bash
ollama pull llama3.2
```
!!! note
This will download the [llama3.2](https://ollama.com/library/llama3.2) model. Keep the terminal with `ollama serve` running in the background throughout your session.
### 2. Start the AutoGPT Platform
Navigate to the autogpt_platform directory and start all services:
```bash
cd autogpt_platform
docker compose up -d --build
```
This command starts both the backend and frontend services. Once running, visit [http://localhost:3000](http://localhost:3000) to access the platform. After registering/logging in, navigate to the build page at [http://localhost:3000/build](http://localhost:3000/build).
### 3. Using Ollama with AutoGPT
Now that both Ollama and the AutoGPT platform are running, we can use Ollama with AutoGPT:
1. Add an AI Text Generator block to your workspace (it can work with any AI LLM block but for this example will be using the AI Text Generator block):
![Add AI Text Generator Block](../imgs/ollama/Select-AI-block.png)
2. **Configure the API Key field**: Enter any value (e.g., "dummy" or "not-needed") since Ollama doesn't require authentication.
3. In the "LLM Model" dropdown, select "llama3.2" (This is the model we downloaded earlier)
![Select Ollama Model](../imgs/ollama/Ollama-Select-Llama32.png)
> **Compatible Models**: The following Ollama models are available in AutoGPT by default:
> - `llama3.2` (Recommended for most use cases)
> - `llama3`
> - `llama3.1:405b`
> - `dolphin-mistral:latest`
>
> **Note**: To use other models, follow the "Add Custom Models" step above.
4. **Set your local IP address** in the "Ollama Host" field:
**To find your local IP address:**
**Windows (Command Prompt):**
```cmd
ipconfig
```
**Linux/macOS (Terminal):**
```bash
ip addr show
```
or
```bash
ifconfig
```
Look for your IPv4 address (e.g., `192.168.0.39`), then enter it with port `11434` in the "Ollama Host" field:
```
192.168.0.39:11434
```
![Ollama Remote Host](../imgs/ollama/Ollama-Remote-Host.png)
> **Important**: Since AutoGPT runs in Docker containers, you must use your host machine's IP address instead of `localhost` or `127.0.0.1`. Docker containers cannot reach `localhost` on the host machine.
5. Add prompts to your AI block, save the graph, and run it:
![Add Prompt](../imgs/ollama/Ollama-Add-Prompts.png)
That's it! You've successfully setup the AutoGPT platform and made a LLM call to Ollama.
![Ollama Output](../imgs/ollama/Ollama-Output.png)
### Using Ollama on a Remote Server with AutoGPT
For running Ollama on a remote server, simply make sure the Ollama server is running and is accessible from other devices on your network/remotely through the port 11434.
**To find your local IP address of the system running Ollama:**
**Windows (Command Prompt):**
```cmd
ipconfig
```
**Linux/macOS (Terminal):**
```bash
ip addr show
```
or
```bash
ifconfig
```
Look for your IPv4 address (e.g., `192.168.0.39`).
Then you can use the same steps above but you need to add the Ollama server's IP address to the "Ollama Host" field in the block settings like so:
```
192.168.0.39:11434
```
![Ollama Remote Host](../imgs/ollama/Ollama-Remote-Host.png)
## Add Custom Models (Advanced)
If you want to use models other than the default ones, you'll need to add them to the model list. Follow these steps:
1. **Add the model to the LlmModel enum** in `autogpt_platform/backend/backend/blocks/llm.py`:
Find the Ollama models section (around line 119) and add your model like the other Ollama models:
```python
# Ollama models
OLLAMA_LLAMA3_3 = "llama3.3"
OLLAMA_LLAMA3_2 = "llama3.2"
OLLAMA_YOUR_MODEL = "The-model-name-from-ollama" # Add your model here
```
2. **Add model metadata** in the same file:
Find the `MODEL_METADATA` dictionary (around line 181) and add your model with its metadata:
```python
# In MODEL_METADATA dictionary, add:
LlmModel.OLLAMA_YOUR_MODEL: ModelMetadata("ollama", 8192, None),
```
Where:
- `"ollama"` = provider name
- `8192` = max context window (adjust based on your model)
- `None` = max output tokens (None means no specific limit)
3. **Add model cost configuration** in `autogpt_platform/backend/backend/data/block_cost_config.py`:
Find the `MODEL_COST` dictionary (around line 54) and add your model:
```python
# In MODEL_COST dictionary, add:
LlmModel.OLLAMA_YOUR_MODEL: 1,
```
> **Note**: Setting cost to `1` is fine for local usage as cost tracking is disabled for self-hosted instances.
4. **Rebuild the backend**:
```bash
docker compose up -d --build
```
5. **Pull the model in Ollama**:
```bash
ollama pull your-model-name
```
## Troubleshooting
If you encounter any issues, verify that:
- Ollama is properly installed and running with `ollama serve`
- Docker is running before starting the platform
- If running Ollama outside Docker, ensure it's set to `0.0.0.0:11434` for network access
### Common Issues
#### Connection Refused / Cannot Connect to Ollama
- **Most common cause**: Using `localhost` or `127.0.0.1` in the Ollama Host field
- **Solution**: Use your host machine's IP address (e.g., `192.168.0.39:11434`)
- **Why**: AutoGPT runs in Docker containers and cannot reach `localhost` on the host
- **Find your IP**: Use `ipconfig` (Windows) or `ifconfig` (Linux/macOS)
- **Test Ollama is running**: `curl http://localhost:11434/api/tags` should work from your host machine
#### Model Not Found
- Pull the model manually:
```bash
ollama pull llama3.2
```
- If using a custom model, ensure it's added to the model list in `backend/server/model.py`
#### Docker Issues
- Ensure Docker daemon is running:
```bash
docker ps
```
- Try rebuilding:
```bash
docker compose up -d --build
```
#### API Key Errors
- Remember that Ollama doesn't require authentication - any value works for the API key field
#### Model Selection Issues
- Look for models with "ollama" in their description in the dropdown
- Only the models listed in the "Compatible Models" section are guaranteed to work