296 skills found · Page 10 of 10
ravipgm / RFC6330An Implementation of the FEC code as specified in IETF - RFC 6330. This implementation is simple and works fine for small values of K. It can be improved for larger K values later. The implemented encoder and decoder is tested with the test vectors specified in the section 6.3 in the document provided in the link http://www.3gpp.org/ftp/tsg_sa/WG4_CODEC/TSGS4_69/Docs/s4-120717.zip .
zuldeveloper2023 / PreVectorChunksA Python module that allows to convert a document into chunks to be inserted into pinecone vector database
hackalog / Vectorizers PlaygroundUsing the TIMC Document Vectorizers library
AzureCosmosDB / Document Vector PipelinePipeline for ingesting documents (like pdfs and docx) into a searchable Azure Cosmos DB container for vector and hybrid searching.
Kiode / AutoStegaFontAutoStegaFont: Synthesizing Vector Fonts for Hiding Information in Documents
Bgzh / Dv Cosine RevisitedCode for the article "The Document Vectors Using Cosine Similarity Revisited"
Azure-Samples / App Service Rag Openai AI Search NodejsAn Express.js app demonstrating Retrieval Augmented Generation (RAG) with App Service, Azure OpenAI, and AI Search. Chat with your documents using hybrid search (vector + keyword + semantic ranking).
0x01369 / RoundcubeRoundcube Document Leak Attack Vector
OliverKahn21 / Fact Extraction And VerificationText Statistics, Vector Space Document retrieval, Probabilistic Document Retrieval, Sentence Relevance,Truthfulness of Claims on Fact Extraction and Verification (FEVER) dataset#Data Mining#Fact Checking#Information Retrieval
chris-belcher / Timelocked Addresses Fidelity Bond Bip TestvectorsGenerates test vectors for the fidelity bonds BIP document
pashpashpash / Python Rag ScaffoldA comprehensive RAG FastAPI service that handles document uploads and retrievals, built with Python. Uses PyMuPDF for document processing, turbopuffer for vector storage, OpenAI for models, and cohere for reranking.
doganarif / Pdf Gpt Vectordb QaBuild your own ChatGPT for PDFs: A secure, production-ready Q&A system using OpenAI GPT, Vector Search, and Python. Chat with your documents using AI.
mrankitvish / Rag ChatbotA FastAPI application that uses Retrieval-Augmented Generation (RAG) with a large language model (LLM) to create an interactive chatbot. This chatbot leverages PostgreSQL vector store for efficient document retrieval and supports text and CSV data sources for initialization.
sammiazaki / Persian Semantic SearchUsing the similarity of the input query with the document, the most relevant embedding vectors for the document (or sentence) are returned.
mark-watson / Docs QaChat interface to document repository for my book "Loving Common Lisp" implementing a local vector database
sunnybedi990 / RAG With LLM"A Retrieval-Augmented Generation (RAG) system for document query and summarization using vector-based search and language models.
axiom-of-choice / LLM ChatbotBuild a Chatbot in Streamlit to perform Generative QA with indexed documents in a Vector DB as knowledge base
MishraShardendu22 / Rag BaitRAG (Retrieval-Augmented Generation) pipeline in Python using ChromaDB for vector storage, with chunking strategies and semantic document retrieval.
Sam-Si / Vector Space Model Aka TF IDFVector space model or term vector model is an algebraic model for representing text documents (and any objects, in general) as vectors of identifiers, such as, for example, index terms. It is used in information filtering, information retrieval, indexing and relevancy rankings.
jaskier07 / DocumentComparatorCompares PDF documents and visualizes similarity using graph. Documents are represented as TF-IDF vector and their similarity is based on cosinus similarity. Visualization is done using Python's library Dash.
