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It provides flexibility to interact with LLMs either locally (on-prem) using technologies like **vLLM** or **Ollama** or through remote **OpenAI-compatible endpoints**.\n\nWith LlamaChat, users can easily chat with powerful LLMs both in private environments (for enhanced privacy and control) and using cloud-based APIs for scalability.\n\n## Features\n\n- **Unified Chat**: Interact with LLMs hosted on-premises or remotely using **llama-stack**\n- **User-Friendly Interface**: Simple web interface to initiate and maintain conversations with LLMs.\n- **API Key Support**: Securely manage and switch between different API keys (for remote services).\n- **Multiple Models**: Support for multiple LLM models such as GPT-based models, Ollama models, and others.\n- **RAG Support**: Chat with your documents, using a vector database as embeddings backend\n- **Safety Shields**: Add safety guardrails to user prompts\n- **Agents Support**: Use tools to enhance the LLM capabilities\n\n## Screenshot\n\n![LlamaChat Screenshot](assets/screenshot.png)\n\n## Installation\n\n### Prerequisites\n\n- Python 3.12+\n- Streamlit\n- An Ollama/vLLM instance or a public OpenAI-Compatible API endpoint.\n- Llama-Stack instance running on-prem or in the cloud.\n\n## Issues\n\nOn MacOS 26, there could be problems during importing `torchcodec` into the application due to missing DYLD_LIBRARY_PATH settings.\nProject needs `ffmpeg@7`, so a workaround could be:\n\n```\n$ brew install ffmpeg@7\n$ DYLD_LIBRARY_PATH=\"/opt/homebrew/opt/ffmpeg@7/lib:$DYLD_LIBRARY_PATH\" uv run streamlit run main.py\n```\n```\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmcaimi%2Fllamachat","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fmcaimi%2Fllamachat","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmcaimi%2Fllamachat/lists"}