Projects with this topic
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StoryMirror CLI is a CPU-first command-line application that transforms unstructured stories into meaningful insights through local AI processing. It provides story analysis, multilingual text-to-speech (TTS), runtime performance metrics, and customizable terminal themes, all while running on a local FastAPI backend.
Designed for offline and resource-efficient environments, StoryMirror performs inference on the CPU without requiring a dedicated GPU, making it suitable for developers, students, and writers who need an accessible AI-powered storytelling tool.
Key Features📖 Analyze stories from text or files🎙️ Generate multilingual text-to-speech narration🎨 Customize the CLI with multiple themes📊 Monitor CPU usage, memory, and inference performance⚡ Run entirely on a local FastAPI backend💻 CPU-first design with no GPU dependency🌐 Supports offline or local deployment🚀 Simple command-line interface for quick workflowsUpdated -
EcoSort AI is an offline-first, CPU-powered web application that transforms unstructured garbage images into structured waste intelligence. Using local AI inference, it identifies waste categories, generates structured JSON reports, and stores results in SQLite for analysis and retrieval. The system works without an internet connection, making it suitable for smart cities, municipalities, campuses, and remote environment
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This project is an offline-first, CPU-only AI app that converts unstructured inputs like documents or images into clean structured data locally on the user’s device. It uses local OCR, small on-device models, and SQLite storage to extract key details, validate them, and help users quickly turn messy files into usable records without needing the internet.
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SmartSave is an AI-powered multilingual expense tracker that helps students build better financial habits through analytics, gamification, and local AI assistance.
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FarmDirect - Broker-free farmer marketplace built with Streamlit and Python
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SafeRoute AI is a machine-learning-powered road safety platform that predicts accident blackspots, analyzes route risk, and recommends safer travel routes using FastAPI, Next.js, SQLite, and XGBoost.
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Smart Food Finder is a preference-based restaurant recommendation platform that helps users discover nearby dining options using their location, budget, cuisine preferences, and dining style.
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live link : https://study-sprint-ai.vercel.app/
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PulseLink is a blood donor matching platform that connects patients with nearby compatible donors during emergencies. Built using React, FastAPI, and MySQL.
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LearnLite is an AI-powered multilingual learning assistant that simplifies complex topics using Gemini and Ollama, supporting English, Hindi, and Telugu with both cloud and local AI options.
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DeepFake Shield is an AI-powered platform designed to detect and analyze manipulated digital media, including images, videos, and audio. The system uses machine learning and forensic analysis techniques to identify deepfakes, synthetic content, and media tampering. It provides users with trust scores, authenticity reports, real-time alerts, and both online and offline analysis capabilities, helping individuals, organizations, and law enforcement combat misinformation and digital fraud.
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TravelSathi is an AI-powered travel planning assistant developed for the Swecha Hackathon. It combines Retrieval-Augmented Generation (RAG), offline local language models (via Ollama), and multilingual support to generate personalized itineraries, budget estimations, local phrases, and destination recommendations.
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Streamlit assistant for classifying Hyderabad civic issues, routing complaints, and drafting formal civic complaint letters.
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Utsav Kathalu is a web application built with Streamlit for collecting and organizing festival stories in multiple Indian languages. Users can submit stories as text, attach images for each section, and view the content as an interactive virtual book. The platform aims to preserve and present cultural narratives in a structured and user-friendly format.
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AI Chat Assistant is a conversational platform built using Streamlit, designed to integrate multiple Large Language Models (LLMs) such as Ollama (local hosting), OpenAI, and Google Gemini. The system provides a flexible interface for seamless interaction across different models while supporting customization through fine-tuned domain-specific datasets. Its architecture emphasizes scalability, multilingual support (including Indic languages), and accessibility, making it suitable for both personal productivity and enterprise use.
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This project is a real-time voice translator web application built with Streamlit. It captures live speech input via microphone, recognizes the spoken text using speech recognition, translates it to a selected target language via machine translation, and plays back the translated audio using text-to-speech synthesis. The app supports multiple languages, provides start/stop controls for continuous conversation flows, displays original and translated text, allows editing of transcriptions, and enables exporting of recordings and analysis. It aims to facilitate accessible, multilingual communication and contribute to language corpora for research purposes.
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A creative Telugu dream journaling web app that allows users to write, rewrite, tag, and share dreams in poetic or story formats.
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AI/ML-based tool that predicts the likelihood of diabetes using medical parameters such as glucose, BMI, age, and blood pressure.
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The Image Captioning project is an AI-based system that automatically generates textual descriptions for images. It combines computer vision and natural language processing (NLP) techniques to understand the content of an image and produce a human-readable caption.
The system uses deep learning models, typically a Convolutional Neural Network (CNN) for extracting image features and a Recurrent Neural Network (RNN) or Transformer-based model for generating sentences. This enables applications such as assisting visually impaired users, enhancing image search engines, and automating social media content tagging.
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A family recipe sharing app built with Python for managing and sharing recipes across family members.
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