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| Publish by | M Logesh |
| Project Name | Construction worker plans |
| Upload Date | April 16, 2024 |
| Platform | Python |
| Programming Language | Any language |
| Database | Sql |
| Front end | |
| Back end | |
| Project Type | web Application |
| View | 1354 |
A project that shows the information about the working process of labours Our project motive is awareness customer
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 ]
