Showing 5 open source projects for "can="

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    Open Semantic Search

    Open Semantic Search

    Open source semantic search and text analytics for large document sets

    ...It provides an integrated search server combined with a document processing pipeline that supports crawling, text extraction, and automated analysis of content from many different sources. Open Semantic Search includes an ETL framework that can ingest documents, process them through analysis steps, and enrich the data with extracted information such as named entities and metadata. It also supports optical character recognition to extract text from images and scanned documents, including images embedded inside PDF files. It integrates text mining and analytics capabilities that allow users to examine relationships, topics, and structured data within document collections.
    Downloads: 6 This Week
    Last Update:
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  • 2
    PandaWiki

    PandaWiki

    AI-powered open source platform for building intelligent wiki bases

    ...It combines traditional wiki functionality with modern AI capabilities, allowing teams and individuals to create and manage product documentation, technical manuals, FAQs, and blog-style knowledge resources. PandaWiki provides tools for managing knowledge bases through an administrative interface while also generating public-facing wiki sites where users can browse and interact with content. AI capabilities are integrated to assist with content creation, intelligent question answering, and semantic search, helping users find information more efficiently within stored documentation. PandaWiki also supports importing knowledge from different external sources such as web pages, RSS feeds, sitemaps, and offline files to quickly populate documentation collections.
    Downloads: 4 This Week
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  • 3
    RAG from Scratch

    RAG from Scratch

    Demystify RAG by building it from scratch

    ...The project walks through key concepts such as generating embeddings, building vector databases, retrieving relevant documents, and integrating the retrieved context into language model prompts. Each example is written with detailed explanations so that developers can understand the internal mechanics of semantic search and context-aware language generation. The repository emphasizes learning through direct implementation, allowing users to see how each component of the RAG architecture functions independently.
    Downloads: 2 This Week
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  • 4
    Node.js Client For NLP Cloud

    Node.js Client For NLP Cloud

    NLP Cloud serves high performance pre-trained or custom models

    ...NLP Cloud serves high-performance pre-trained or custom models for NER, sentiment analysis, classification, summarization, dialogue summarization, paraphrasing, intent classification, product description and ad generation, chatbot, grammar and spelling correction, keywords and keyphrases extraction, text generation, image generation, blog post generation, text generation, question answering, automatic speech recognition, machine translation, language detection, semantic search, semantic similarity, tokenization, POS tagging, embeddings, and dependency parsing. It is ready for production, and served through a REST API. You can either use the NLP Cloud pre-trained models, fine-tune your own models, or deploy your own models.
    Downloads: 1 This Week
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  • 5
    S3B - Social Semantic Search and Browsing - is a middleware that delivers a set of search and browsing components that can be used in J2EE web applications to deliver user-oriented features based on semantic descriptions and social networking
    Downloads: 0 This Week
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