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| Publish by | Sania Debda |
| Project Name | Word per minute typing test web app |
| Upload Date | November 1, 2024 |
| Platform | Python |
| Programming Language | htm css bootstrap python |
| Database | any database |
| Front end | html css bootstrap |
| Back end | according to code |
| Project Type | web Application |
| View | 1858 |
a web app having leaderboard user statistics typing in english hindi marathi random paragraphs for typing practice
user login user can randomly select paragraph user have statistics acc to performance user should have a separate leaderboard
Computer/Laptop RAM: 4 GB or higher Processor: Intel Core i3 Operating System: Windows 11 RAM: 4 GB or higher
Jupyter Notebook Python 3.8 or higher Python Libraries
Query any SQLite database using plain English with no SQL knowledge required. The agent automatically discovers the schema, translates plain English questions into SQL queries, executes them and returns human readable answers. Includes auto repair for broken queries. Features include automatic schema discovery, natural language to SQL conversion ... [ Download Source Code ]
A document summarization pipeline capable of handling texts of any length using map-reduce strategy. Long documents are split into chunks, each chunk is summarized independently then all summaries are combined into a final output. Works on books, reports and transcripts. Features include three summary modes Brief, Detailed and Bullet Points, map ... [ Download Source Code ]
An autonomous AI agent that searches the live web in real time to answer any question. Uses the ReAct framework where the agent thinks about what to search, performs the search, observes the results and repeats until confident answer is found. Features include live web search via Tavily API, multi-step ReAct reasoning loop, transparent step by s ... [ Download Source Code ]
Upload any PDF and ask natural language questions about it using Retrieval-Augmented Generation. The program splits the PDF into chunks, embeds them into a FAISS vector store, and retrieves the most relevant sections to answer each question accurately. Key features include PDF ingestion and smart chunking, semantic search via FAISS vector store, ... [ Download Source Code ]
A conversational chatbot built with LangChain and GPT-4o that remembers the full session history. Users type any question and receive intelligent context-aware replies. The bot uses ConversationBufferMemory to retain all previous messages. Features include persistent conversation memory, GPT-4o integration, custom system prompt, clean CLI interf ... [ Download Source Code ]
