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doc: better comments for tldr
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README.md
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README.md
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@ -35,7 +35,7 @@ Also check our sibling project, [OllamaHub](https://ollamahub.com/), where you c
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- 🤖 **Multiple Model Support**: Seamlessly switch between different chat models for diverse interactions.
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- 🗃️ **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.
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- 🧩 **Modelfile Builder**: Easily create Ollama modelfiles via the web UI. Create and add characters/agents, customize chat elements, and import modelfiles effortlessly through [OllamaHub](https://ollamahub.com/) integration.
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- ⚙️ **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.
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@ -121,7 +121,7 @@ docker run -d -p 3000:8080 -e OLLAMA_API_BASE_URL=https://example.com/api --name
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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.
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### TL;DR
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### TL;DR 🚀
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Run the following commands to install:
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@ -129,16 +129,19 @@ Run the following commands to install:
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git clone https://github.com/ollama-webui/ollama-webui.git
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cd ollama-webui/
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# Building Frontend
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# Copying required .env file
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cp -RPp example.env .env
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# Building Frontend
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npm i
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npm run build
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# Serve Frontend with the Backend
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# Serving Frontend with the Backend
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cd ./backend
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pip install -r requirements.txt
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sh start.sh
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```
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You should have the Ollama Web UI up and running at http://localhost:8080/. Enjoy! 😄
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### Project Components
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@ -231,7 +234,6 @@ See [TROUBLESHOOTING.md](/TROUBLESHOOTING.md) for information on how to troubles
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Here are some exciting tasks on our roadmap:
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- 🔄 **Multi-Modal Support**: Seamlessly engage with models that support multimodal interactions, including images (e.g., LLava).
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- 📚 **RAG Integration**: Experience first-class retrieval augmented generation support, enabling chat with your documents.
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- 🔐 **Access Control**: Securely manage requests to Ollama by utilizing the backend as a reverse proxy gateway, ensuring only authenticated users can send specific requests.
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