#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

#typescript #chatbot #cot #graphrag #knowledge_graph #mysql #rag #serverless #vector_database

TiDB.AI is a free and open-source tool that helps you find information easily. It uses a Knowledge Graph built on top of TiDB Vector, LlamaIndex, and DSPy. You can use it to search for information in a conversational way, similar to talking to a person. It also allows you to edit the knowledge graph to make sure the information is accurate. You can even add a search widget to your website with just a few lines of code. This makes it easier for users to get quick answers to their questions, improving their overall experience.

https://github.com/pingcap/autoflow

#python #gpt #gpt_4 #gpt4 #graphrag #llm #llms #rag

GraphRAG is a tool that helps extract useful, structured data from unstructured text using large language models (LLMs). It creates a data pipeline to make sense of your private data. To get started, you can use the Solution Accelerator package, which provides a simple way to use GraphRAG with Azure resources. The benefit to you is that GraphRAG can enhance your LLM's ability to understand and reason about your data, making it easier to extract valuable information from texts. However, be aware that using GraphRAG can be costly, so it's important to read the documentation carefully and start with small tests.

https://github.com/microsoft/graphrag

#python #genai #gpt #gpt_4 #graphrag #knowledge_graph #large_language_models #llm #rag #retrieval_augmented_generation

LightRAG is a system that helps computers understand and answer questions better by using a special way of organizing information called a "graph." This graph shows how different pieces of information are connected, making it easier for the system to find related answers. It works fast and can handle complex questions by combining two types of searches: one that looks at specific details and another that looks at broader topics. This makes it very useful for answering questions that need both specific and general information. Users benefit from getting accurate and relevant answers quickly, which is helpful in many applications like customer service and document retrieval.

https://github.com/HKUDS/LightRAG

#python #ai #ai_agents #ai_memory #cognitive_architecture #cognitive_memory #contributions_welcome #good_first_issue #good_first_pr #graph_database #graph_rag #graphrag #help_wanted #knowledge #knowledge_graph #neo4j #open_source #openai #rag #vector_database

Cognee is an open-source AI memory engine that helps improve how AI systems understand and process data. It mimics human cognitive processes, creating "memories" from various data types like text and images. This enhances the accuracy of large language models (LLMs) and allows them to recall past interactions and documents. Cognee is scalable, cost-effective, and integrates easily with existing systems, making it a valuable tool for developers seeking to boost AI performance without relying on expensive APIs.

https://github.com/topoteretes/cognee