#html #data_pipelines #deep_learning #document_ai #document_image_analysis #document_image_processing #document_parser #document_parsing #docx #donut #information_retrieval #langchain #machine_learning #ml #natural_language_processing #nlp #ocr #pdf #pdf_to_json #pdf_to_text #preprocessing
https://github.com/Unstructured-IO/unstructured
https://github.com/Unstructured-IO/unstructured
GitHub
GitHub - Unstructured-IO/unstructured: Convert documents to structured data effortlessly. Unstructured is open-source ETL solution…
Convert documents to structured data effortlessly. Unstructured is open-source ETL solution for transforming complex documents into clean, structured formats for language models. Visit our website...
#python #agent #agents #ai_search #chatbot #chatgpt #data_pipelines #deep_learning #document_parser #document_understanding #genai #graph #graphrag #llm #nlp #pdf_to_text #preprocessing #rag #retrieval_augmented_generation #table_structure_recognition #text2sql
RAGFlow is an open-source tool that helps businesses answer questions accurately using large language models and deep document understanding. It extracts information from various complex data formats, such as Word documents, Excel files, and web pages, and provides grounded citations to support its answers. You can try a demo online or set it up on your own server using Docker. The setup is relatively straightforward, requiring a few steps like cloning the repository, building the Docker image, and configuring the system settings. RAGFlow offers key features like template-based chunking, reduced hallucinations, and compatibility with multiple data sources, making it a powerful tool for truthful question-answering capabilities. This benefits users by providing reliable and explainable answers, streamlining their workflow, and supporting integration with their business systems.
https://github.com/infiniflow/ragflow
RAGFlow is an open-source tool that helps businesses answer questions accurately using large language models and deep document understanding. It extracts information from various complex data formats, such as Word documents, Excel files, and web pages, and provides grounded citations to support its answers. You can try a demo online or set it up on your own server using Docker. The setup is relatively straightforward, requiring a few steps like cloning the repository, building the Docker image, and configuring the system settings. RAGFlow offers key features like template-based chunking, reduced hallucinations, and compatibility with multiple data sources, making it a powerful tool for truthful question-answering capabilities. This benefits users by providing reliable and explainable answers, streamlining their workflow, and supporting integration with their business systems.
https://github.com/infiniflow/ragflow
GitHub
GitHub - infiniflow/ragflow: RAGFlow is a leading open-source Retrieval-Augmented Generation (RAG) engine that fuses cutting-edge…
RAGFlow is a leading open-source Retrieval-Augmented Generation (RAG) engine that fuses cutting-edge RAG with Agent capabilities to create a superior context layer for LLMs - infiniflow/ragflow