streamlit

⭐ College.ai is an advanced AI-powered platform that provide a set of tools for students, job seekers, and professionals.

Streamlit + Langchain + LlamaCPP + Mistral + Rag

AI-powered semantic search engine for emojis in 50+ languages, developed in Python

AI assistant built with Streamlit, NVIDIA NIM (LLaMa 3.3:70B) / Ollama, and Model Control Protocol (MCP).

An AI-powered interactive web application built with Streamlit that predicts whether a candidate will get placed in a job (or admitted) based on academic performance and other features.

A basic application using langchain, streamlit, and large language models to build a system for Retrieval-Augmented Generation (RAG) based on documents, also includes how to use Groq and deploy your own applications.

An AI-powered chatbot that leverages RAG (Retrieval-Augmented Generation) to answer your questions based on the content of uploaded PDFs

Ask question over your Notion Database! A naive Retrieval-Augmented Generation (RAG) pipeline backed by Langchain and Streamlit

Analyse environmental, social, and governance policies for potential gaps using AI - powered by LLMs, RAG techniques, and a regulatory knowledge base using OpenAI API, LangChain, Pinecone and Streamlit.

Practical step-by-step LangChain guides

A Streamlit app for generating high-quality Q&A training datasets from text and PDFs, leveraging Gemini, Claude, and OpenAI for LLM fine-tuning.

Ask question to your Airtable base in natural language

Text Summarization App built using Langchain and Streamlit

An interactive AI chatbot for querying and discussing the contents of PDF documents using Streamlit and OpenAI/other AI language models.

Turn any website into clean, LLM-ready data. Open-source web crawler with stealth mode, distributed crawling, real-time WebSocket progress & Markdown output. Power your AI apps with GcrawlAI.

AI-powered fashion recommendation system leveraging LLMs, embeddings, and retrieval techniques to deliver personalized shopping experiences.

Your intelligent ally for effortless information retrieval and seamless browsing across documents and the web.

Multimodal Chatbot with Amazon Bedrock Knowledge Bases Integration

Deploy PhoBERT for Abstractive Text Summarization as REST API using StreamLit, Transformers by Hugging Face and PyTorch

Chat with Phi 3.5/3 Vision LLMs. Phi-3.5-vision is a lightweight, state-of-the-art open multimodal model built upon datasets which include - synthetic data and filtered publicly available websites - with a focus on very high-quality, reasoning dense data both on text and vision.