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

RAG‑PDF‑Analyzer is a Streamlit chatbot that lets users upload PDFs and query them with natural language. It uses PyPDF2 for text extraction, HuggingFace embeddings with FAISS for semantic search, and Mistral LLM via LangGraph to deliver context‑aware answers from documents.

Most advanced and in depth prompt analyzer, refiner and generator, built and trained on a collection frontier LLM system prompts, including Antrophic(Claude code 2.1), Cursor IDE, Perplexity, Google Gemini(AI studio). It utilizes a RAG pipeline with a vecotr database containing a collection of 40000 tested prompts, for image, text and image gen

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A simple LLM text analyzer that takes unstructured text and outputs it in a structured form

Financial PDF Analyzer processes financial PDF reports by extracting and structuring unstructured text and tables. It uses LangChain and RAG with LLMs to generate summary reports and answer user questions accurately.

Government RFP analyzer for extracting compliance requirements and mapping to controls. This module provides an async, multi‑stage analyzer that can: - Extract requirements from RFP text via pattern matching and LLM assistance - Identify referenced frameworks (FedRAMP, FISMA, NIST SP 800‑53/171, CMMC, etc.) - Map requirements to concrete security

An AI-powered Resume Analyzer and Ranker built with FastAPI and NLP. This micro-SaaS tool extracts text from uploaded resumes (PDFs), analyzes technical skills, and generates a Match Score against job descriptions using LLM-based evaluation.

FastAPI-based PDF Analyzer processes medical claim documents by extracting text from each page, classifying document types, and pulling key fields for identity, discharge summary, and itemized bills. It combines PyPDF2 parsing, rule-driven segregation, and LangGraph-managed LLM agents to produce one structured JSON output for claim workflows.

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A Chrome extension that analyzes the text selected on the website with a custom prompt. Your own API keys are required.

A Google Colab notebook to analyze word count, sentence count, and average sentence length of text files using spaCy

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A system for analyzing text documents using the LLM OpenAI API. It can generate a short summary of the document, also build the table of contents of the document and select theses or quotes.

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LLM-based Text Quality and Toxicity Analyzer

A TEXT sentiment analyzer and summarizer using Huggingface llm's

Full-stack resume analyzer that extracts text from PDF resumes and generates structured summaries using OpenRouter LLMs.

AI-powered document analyzer that extracts text, metadata, and summaries from PDFs using FastAPI and OpenRouter LLMs.

AI-powered Resume Analyzer that extracts text from PDFs, identifies skills, detects gaps, and provides actionable suggestions using LLMs.

AI-powered Legal Document Analyzer that extracts text from PDFs and generates summaries, clauses, and risks using Groq LLM. Built with MERN stack.

Text Analyzer is a Full stack project (React + Flask + Gemini API Key) in which user will insert raw text and output will generate with the help of LLM and NLTK.

AI-powered legal document analyzer using NLP and LLMs to extract, summarize, and analyze contracts and legal texts with entity recognition and risk assessment.

Smart Resume Analyzer that extracts resume text, generates embeddings using Hugging Face Inference API, and provides ATS-style insights through an LLM-powered analysis API.

The Plate Calorie Analyzer notebook transforms a user-uploaded plate photograph into a concise nutritional report using a hybrid image-to-text and LLM pipeline.

LLM-powered text analyzer built with FastAPI and SQLite. Extracts summaries, topics, sentiment, and keywords from unstructured text with optional OpenAI API integration. Includes a web UI, search endpoint, tests, and Docker support.

LLM Text Analyzer API A modular Node.js/TypeScript API that uses state-of-the-art Large Language Models (LLMs) to analyze text documents. This API delivers content summarization, topic categorization, keyword extraction, and sentiment analysis—all available via a straightforward REST interface.

The LitLoom analyzer is an LLM-augmented pipeline for extracting, filtering, and analyzing or synthesizing structured data from unstructured text. Originally developed under the RePower-CEST project.