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20 documents available
**Project Start Date:** [To be filled]
- [x] AdSense integration across 26+ blog pages and listing page
The Knowledge Graph Discovery System aims to automatically extract structured knowledge from the Verizon website and build a comprehensive knowledge graph. The system follows ethical web scraping practices while efficiently creating a valuable knowledge resource that represents entities, relationships, and attributes found in the website content.
| **Document Version** | 1.0 |
| Metadata | Details |
This document outlines all remaining tasks to complete the Flex.IA platform from backend to frontend to deployment. The platform is currently functional but needs production-ready enhancements.
Open-source AI-powered task automation platform inspired by Anthropic's Claude Cowork feature.
Description: Implementation plan and priority improvements
- [x] Read the `README.md` to understand what the project is.
- [x] **Persistence Layer**
This document explains **exactly how** the analytics system was implemented so you can replicate it in any project.
Here we provide implementation details about the three environments (`primal`, `dual`, `config`) and reward functions.
This project is a **simple e-commerce landing page generator** for individual product sales. Sellers can create multiple **standalone product pages**, each with a "Buy Now" button leading to a universal order form. Products are not listed together in a catalog—they each live on their own unique link, allowing sellers to advertise and sell them individually.
This file tracks the documentation improvement plan for Django Cast. The goal is to address major documentation gaps identified through analysis of the codebase vs existing docs.
> **目标**: 将 Koatty 框架迁移到 Monorepo 架构，并配置自动同步
This implementation plan provides a hackathon-realistic MVP roadmap for the CCAI system. The plan focuses on core functionality: domain registry verification, embedding-based impersonation detection, authenticity score computation, explainable flag generation, translation with integrity validation, and API endpoints. The implementation uses Python with AWS serverless architecture (Lambda, DynamoDB, S3, API Gateway, Bedrock, Comprehend).
*Goal: Implement embedded feedback loop to automatically fine-tune retrieval parameters based on user ratings.* ✅ **FULLY IMPLEMENTED**
I have created the following plan after thorough exploration and analysis of the codebase. Follow the below plan verbatim. Trust the files and references. Do not re-verify what's written in the plan. Explore only when absolutely necessary. First implement all the proposed file changes and then I'll review all the changes together at the end.
Large language models (LLMs) such as Llama2 have been shown effective for question-answering ([Touvron et al., 2023](https://arxiv.org/abs/2307.09288)), however, they are often limited by their knowledge in certain domains. A common technique here is to augment LLM's knowledge with documents that are relevant to the question. In this assignment, you will *develop a retrieval augmented generation system (RAG)* ([Lewis et al., 2021](https://arxiv.org/abs/2005.11401)) that's capable of answering qu
A Python-based analog clock application that combines real-time clock display with AI-generated backgrounds using local Stable Diffusion via Diffusers, enhanced with ControlNet and GPT-2 prompt generation. Supports both NVIDIA (CUDA) and Apple Silicon (MPS) hardware acceleration.
