mirror of
https://github.com/Significant-Gravitas/AutoGPT.git
synced 2026-01-30 17:38:17 -05:00
<!-- Clearly explain the need for these changes: -->
gitbook branch has changes that need synced to dev
### Changes 🏗️
Pull changes from gitbook into dev
<!-- Concisely describe all of the changes made in this pull request:
-->
<!-- CURSOR_SUMMARY -->
---
> [!NOTE]
> Migrates documentation to GitBook and removes the old MkDocs setup.
>
> - Removes MkDocs configuration and infra: `docs/mkdocs.yml`,
`docs/netlify.toml`, `docs/overrides/main.html`,
`docs/requirements.txt`, and JS assets (`_javascript/mathjax.js`,
`_javascript/tablesort.js`)
> - Updates `docs/content/contribute/index.md` to describe GitBook
workflow (gitbook branch, editing, previews, and `SUMMARY.md`)
> - Adds GitBook navigation file `docs/platform/SUMMARY.md` and a new
platform overview page `docs/platform/what-is-autogpt-platform.md`
>
> <sup>Written by [Cursor
Bugbot](https://cursor.com/dashboard?tab=bugbot) for commit
e7e118b5a8. This will update automatically
on new commits. Configure
[here](https://cursor.com/dashboard?tab=bugbot).</sup>
<!-- /CURSOR_SUMMARY -->
<!-- This is an auto-generated comment: release notes by coderabbit.ai
-->
## Summary by CodeRabbit
* **Documentation**
* Updated contribution guide for new documentation platform and workflow
* Added new platform overview and navigation documentation
* **Chores**
* Removed MkDocs configuration and related dependencies
* Removed deprecated JavaScript integrations and deployment overrides
<sub>✏️ Tip: You can customize this high-level summary in your review
settings.</sub>
<!-- end of auto-generated comment: release notes by coderabbit.ai -->
---------
Co-authored-by: Claude Opus 4.5 <noreply@anthropic.com>
267 lines
8.9 KiB
Markdown
267 lines
8.9 KiB
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"**
|
|

|
|
3. Click on the model name field in the "New Chat" window
|
|
4. Search for "llama3.2" (or your preferred model)
|
|

|
|
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):
|
|

|
|
|
|
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)
|
|

|
|
|
|
> **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
|
|
```
|
|
|
|

|
|
|
|
> **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:
|
|

|
|
|
|
That's it! You've successfully setup the AutoGPT platform and made a LLM call to Ollama.
|
|

|
|
|
|
### 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
|
|
```
|
|
|
|

|
|
|
|
## 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
|