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Kotaemon
Overview :
Kotaemon is an open-source tool based on the Retrieval-Augmented Generation (RAG) model designed to interact with user documents through a chat interface. It supports various language model API providers and local language models, offering a clean and customizable user interface suitable for end users conducting document Q&A and developers building their own RAG Q&A workflows.
Target Users :
The target audience includes end users who wish to conduct Q&A on their documents, as well as developers looking to build their own RAG Q&A workflows. This tool is ideal for users who need to interact with documents, retrieve information, or create customized question-answering systems.
Use Cases
Users can use kotaemon to query data within documents and retrieve accurate answers.
Developers can leverage kotaemon to build a custom Q&A system specifically for document analysis in particular fields.
Teams can deploy kotaemon to support collaborative work, jointly managing and retrieving document information.
Features
Supports multi-user login and organization of files in private/public collections.
Compatible with local language models and popular API providers (e.g., OpenAI, Azure, Ollama, Groq).
Provides a hybrid RAG workflow combining full-text and vector retrievers with re-ranking to ensure optimal retrieval quality.
Supports multimodal Q&A, including querying documents containing charts, and allows for multimodal document parsing.
Offers detailed citations to ensure the accuracy of LLM answers, with direct viewing of highlighted citations in the built-in PDF viewer.
Supports complex reasoning techniques, employing question decomposition to answer intricate or multi-hop questions.
Provides a configurable settings interface where users can adjust most critical aspects of the retrieval and generation processes from within the UI.
Built on Gradio for extensibility, allowing users to customize or add any UI elements.
How to Use
1. Clone the kotaemon GitHub repository to your local environment.
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2. Install the required Python packages and dependencies.
3. Configure the environment variables as needed, including API keys and endpoints.
4. Start the web server and access the UI through a browser.
5. Log in to the system using default or custom user accounts.
6. Upload or organize documents and begin interacting with them through the chat interface.
7. Adjust settings as necessary, such as retrieval and generation configurations.
8. Leverage kotaemon's multimodal and complex reasoning capabilities for in-depth analysis and content retrieval.
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