Text Summarization App built using Langchain and Streamlit

Summarize/analyze large amounts of text using local LLM models, langchain, ollama, and flask. No data leaves your computer.

Python studies and Pracitce using LLMs, Langchain, Text Summarization, FastAPI and more.

I made ChatPDF using Langchain which leverages the power of LLMs like LLama, ChatGPT,OpenAssistant and allows the user to upload documents and use them as the knowledge base. Therefore, allowing the user to make any queries about the document which can be a daunting task sometimes. eg summarizing text, explaining certain parts of the document

OCR Process: Extracting text from PDF with TesseractTable Recognition: Detecting tables with YOLOv8 and saving in CSV format NLP Analysis: Summarizing text and sentiment analysis with BERT Smart Search: Finding answers to questions in the document with LangChain Output Management: Saving text and table outputs to the outputs folder

LangChain Text Summarization and Image Generation

GPT-Book Reader is a powerful app that enables reading, summarizing, and translating long texts using the cutting-edge GPT technology. It leverages the vectorstore approach provided in LangChain Index to deliver an enhanced user experience and improve support for Chinese content.

summarize long text using langchain + gcp

A tool that converts long audio files into a thorough, summarized report. Leverages OpenAI and its API (ChatGPT backend), Langchain for text processing, and Pinecone for vector database facilitation.

A Neovim plugin that leverages Large Language Models (LLMs) via LangChain to check grammar and typos, rewrite text, and summarize content in your buffers.

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An LLM-based chatbot trained on philosophical texts built using OpenAI GPT models, Langchain Tokenizers, HuggingFace transformers, and Meta BART summarization model wrapped in a NextJS web app hosted completely on AWS

RAGent Chatbot is a smart AI assistant that combines Retrieval-Augmented Generation (RAG) with a tool-using LLM agent. It can answer user queries using uploaded documents, perform web searches, summarize text, solve math expressions, check weather, and more — all powered by LangChain, Qdrant, and Gemini.

Generative-AI-with-Langchain-and-Huggingface explores cutting-edge generative AI concepts. Topics include LangChain basics, ChromaDB, conversational memory, vector databases, document Q&A with RAG, text summarization (refine chains, YT/video summarization), building LLMs, search engines, and advanced tools/agents.

extracts text from pdfs and powerpoint documents and summarizes it into key points and bullet lists, uses LangChain and Google's Gemini.

Multimodal RAG: Chat with Any PDF (Text + Tables + Images) – A LangChain-powered pipeline that parses PDF files, summarizes content using Groq and OpenAI, and enables intelligent question answering across text, tables, and embedded images.

A telegram speech to text transcriber and summarizer using langchain and openai

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text summarization, document summarization and document question answering application built using Django and GPT-3

Creating a customer care application involving a L1-query resolver automation chatbot/voicebot involving use of GenAI, Langchain v3.0, LLM API (Azure OpenAI), Sentiment Analysis , Text/Speech Conversion, Summarized Memory Prompts, Database and Logging, Threading and Interactive Frontend (HTML/CSS/JS) etc.

Generative AI models for text generation, summarization, and Q&A using LLMs via LangChain, Hugging Face,Gemini and open-source APIs.

In this Project We perform NLP tasks like QA Pair Generation, Question Answering, Text Summarization and Data Extraction from webpages using Large Language Models (Like Gemini ) and Langchain

Developed a PDF-based chatbot using Streamlit to extract, summarize, and interact with document content, integrating Google Gemini AI for contextual Q&A. Utilized PyMuPDF for text extraction and LangChain for summarization, optimizing document processing efficiency.

A web application that enables users to upload documents and utilize AI techniques like semantic search and text summarization for efficient analysis. Built with Python, FastAPI, Svelte, PostgreSQL, and LangChain.

This project demonstrates a modular AI service offering text summarization, question answering, and learning path generation APIs. It uses Google's Gemini LLM through LangChain and incorporates a simulated blockchain for response integrity verification.

A FastAPI + LangChain PDF app: upload PDFs, extract text, summarize, and chat with your documents. Frontend in HTML/JS + Tailwind, backend with MongoDB, Chroma vector DB, and AI LLMs (Ollama/OpenAI).

This repository covers core LangChain concepts including models, prompts, structured outputs, output parsers, chains, runnables, document loaders, text splitters, vector stores, retrievers, tools, tool calling, and a YouTube video summarizer, focused on building practical GenAI and RAG workflows.

QueryPage is an AI-powered tool that summarizes and answers questions from webpages, PDFs, and text documents. Just upload a file or share a link, and instantly get concise insights and accurate answers using advanced language models built with LangChain.

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