LocalGPT: Secure, Local Conversations with Your Documents
What is the project about?
LocalGPT is an open-source project that enables users to interact with their documents locally, ensuring privacy and security. It allows users to "chat" with their documents using a language model, all without data leaving the user's computer.
What problem does it solve?
It addresses the privacy concerns associated with sending sensitive document data to third-party services for processing. By running everything locally, it guarantees that no data is exposed externally.
What are the features of the project?
- Utmost Privacy: Data stays on the user's computer.
- Versatile Model Support: Supports various open-source models (HF, GPTQ, GGML, GGUF).
- Diverse Embeddings: Offers a choice of open-source embeddings.
- LLM Reuse: Avoids repeated downloads of the language model.
- Chat History: Remembers previous conversations within a session.
- API: Provides an API for building Retrieval-Augmented Generation (RAG) applications.
- Graphical Interface: Includes two GUIs for user interaction.
- Platform Support: Runs on various platforms (CUDA, CPU, HPU, MPS).
What are the technologies used in the project?
- LangChain
- HuggingFace LLMs
- InstructorEmbeddings
- LLAMACPP
- ChromaDB
- Streamlit
What are the benefits of the project?
- Data Security: Complete control over sensitive data.
- Privacy: No data leaves the user's environment.
- Flexibility: Supports multiple models and embeddings.
- Offline Capability: Works without an internet connection after initial setup.
- Cost-Effective: Reduces reliance on paid cloud services.
What are the use cases of the project?
- Analyzing confidential documents without risking exposure.
- Building local, privacy-focused question-answering systems.
- Developing RAG applications with complete data control.
- Researching and experimenting with LLMs in a secure environment.
- Interacting with personal documents in a conversational manner.
