Charm AI's repositories
keras-rag-chatbot
A project written in the Rust language with the goal of offline load of small LLM Model, specifically RAG (Retrieval Augmented Generation) on mobile devices.
rust-webrtc
A simple WebRTC streaming server. It streams video and audio from a file to a browser client.
ai-meeting-raspberrypi-tkinter
AI meeting summary project for raspberry pi
analyze-eth-ui
This project analyzes WOLF and BRETT tokens, focusing on the behavior of their top holders. Key aspects include holder overlap, investment behavior, token swapping, transaction frequency, purchase sources, portfolio diversity, wallet activity, historical performance, wallet creation dates, and token flow patterns. The frontend is built with React.
bug-tracker
Bug Tracking App - Real time communication using HTMX
fastapi_docker_ci_cd_template
Python Fastapi template using CI/CD & Docker & Docker-Compose & Github Action & Makefile
finra_api
This script pulls short interest data from the FINRA API and generates an Excel table with specific filters and columns as specified.
grab-manufacturing-data
Scrapping api to grab manufacturing data using Python
img2txt-fine-tuning-api
This project showcases a comprehensive solution for converting images to text using OCR (Optical Character Recognition) and fine-tuning the extracted content. Leveraging powerful tools like AWS, Docker, OpenAI, and CI/CD pipelines, this system ensures high accuracy and efficiency.
Kanban-Board
Mini Kanban board using React, Python, DynamoDB, GraphQL
rust-ai-embedding
OpenAI Embeddings & Completion & Rust
rust-amazon-topsellers
This program will scrape the title, link, rating, and number of comments from the Amazon bestsellers page and save extracted data to a bestsellers.csv file.
SDXL-Generative-AI
SDXL t2i i2i - base & refiner & scheduler & docker & cicd & github action & makefile & runpod
text-to-video
A cutting-edge project leveraging DALL-E 3 and gpt-4o for AI-driven video generation, with FFmpeg for multimedia manipulation.
ramped-api
ramped api
rust-chat-app
The essence of the work is that the client sends a message to the backend and these messages are shared with other connected clients via websockets.