Also check our sibling project, [OllamaHub](https://ollamahub.com/), where you can discover, download, and explore customized Modelfiles for Ollama! 🦙🔍
- ⚙️ **Many Models Conversations**: Effortlessly engage with various models simultaneously, harnessing their unique strengths for optimal responses. Enhance your experience by leveraging a diverse set of models in parallel.
- 🗣️ **Voice Input Support**: Engage with your model through voice interactions; enjoy the convenience of talking to your model directly. Additionally, explore the option for sending voice input automatically after 3 seconds of silence for a streamlined experience.
- ⚙️ **Fine-Tuned Control with Advanced Parameters**: Gain a deeper level of control by adjusting parameters such as temperature and defining your system prompts to tailor the conversation to your specific preferences and needs.
- 🔐 **Auth Header Support**: Effortlessly enhance security by adding Authorization headers to Ollama requests directly from the web UI settings, ensuring access to secured Ollama servers.
- 🔗 **External Ollama Server Connection**: Seamlessly link to an external Ollama server hosted on a different address by configuring the environment variable during the Docker build phase. Additionally, you can also set the external server connection URL from the web UI post-build.
- 🔒 **Backend Reverse Proxy Support**: Strengthen security by enabling direct communication between Ollama Web UI backend and Ollama, eliminating the need to expose Ollama over LAN.
Don't forget to explore our sibling project, [OllamaHub](https://ollamahub.com/), where you can discover, download, and explore customized Modelfiles. OllamaHub offers a wide range of exciting possibilities for enhancing your chat interactions with Ollama! 🚀
This command will install both Ollama and Ollama Web UI on your system. Ensure to modify the `compose.yaml` file for GPU support and Exposing Ollama API outside the container stack if needed.
Make sure you have the latest version of Ollama installed before proceeding with the installation. You can find the latest version of Ollama at [https://ollama.ai/](https://ollama.ai/).
After installing Ollama, verify that Ollama is running by accessing the following link in your web browser: [http://127.0.0.1:11434/](http://127.0.0.1:11434/). Note that the port number may differ based on your system configuration.
While we strongly recommend using our convenient Docker container installation for optimal support, we understand that some situations may require a non-Docker setup, especially for development purposes. Please note that non-Docker installations are not officially supported, and you might need to troubleshoot on your own.
### Project Components
The Ollama Web UI consists of two primary components: the frontend and the backend (which serves as a reverse proxy, handling static frontend files, and additional features). Both need to be running concurrently for the development environment using `npm run dev`. Alternatively, you can set the `PUBLIC_API_BASE_URL` during the build process to have the frontend connect directly to your Ollama instance or build the frontend as static files and serve them with the backend.
If you wish to run the backend for deployment, ensure that the frontend is built so that the backend can serve the frontend files along with the API route.
#### Setup Instructions
1.**Install Python Requirements:**
```sh
cd ./backend
pip install -r requirements.txt
```
2.**Run Python Backend:**
- Dev Mode with Hot Reloading:
```sh
sh dev.sh
```
- Deployment:
```sh
sh start.sh
```
Now, you should have the Ollama Web UI up and running at [http://localhost:8080/](http://localhost:8080/). Feel free to explore the features and functionalities of Ollama! If you encounter any issues, please refer to the instructions above or reach out to the community for assistance.
See [TROUBLESHOOTING.md](/TROUBLESHOOTING.md) for information on how to troubleshoot and/or join our [Ollama Web UI Discord community](https://discord.gg/5rJgQTnV4s).
- 🗃️ **Modelfile Builder**: Easily create Ollama modelfiles via the web UI. Create and add your own character to Ollama by customizing system prompts, conversation starters, and more.
- 🔄 **Multi-Modal Support**: Seamlessly engage with models that support multimodal interactions, including images (e.g., LLava).
- 📚 **RAG Integration**: Experience first-class retrieval augmented generation support, enabling chat with your documents.
- 🔐 **Access Control**: Securely manage requests to Ollama by utilizing the backend as a reverse proxy gateway, ensuring only authenticated users can send specific requests.
- 🧪 **Research-Centric Features**: Empower researchers in the fields of LLM and HCI with a comprehensive web UI for conducting user studies. Stay tuned for ongoing feature enhancements (e.g., surveys, analytics, and participant tracking) to facilitate their research.
- 📈 **User Study Tools**: Providing specialized tools, like heat maps and behavior tracking modules, to empower researchers in capturing and analyzing user behavior patterns with precision and accuracy.
