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3-Transform

Web2 -> Web3 in one click

3-Transform

Created At

ETHIndia 2023

Winner of

Filecoin & IPFS - Unique Projects in Filecoin Ecosystem (up to 15 teams)

Prize Pool

Scroll - Deploy on Scroll

Prize Pool

Okto - Integrate Okto SDK as your Wallet

ETHGlobal - 🏆 ETHIndia 2023 Finalist

Project Description

1) Educational Tool for Web3 Beginners

The transition tool serves as an invaluable educational resource for individuals venturing into the realm of web3 technologies. Learning by Doing: Users can input the URL of their existing web2 site, gaining hands-on experience in understanding how web3 integrations can enhance their digital presence. Guided Integration: Step-by-step suggestions empower users to seamlessly incorporate smart contracts into their web applications. Instant Deployment: The one-click deploy feature allows beginners to witness the real-world implementation of smart contracts.

2) Empowering Enterprise Users to Embrace Web3

For enterprise users, the tool becomes a strategic asset, simplifying the adoption of web3 technologies mandated by leadership. Efficiency in Decision-Making: Executives and project managers can quickly assess the potential impact of web3 integration on their existing web infrastructure, facilitating informed decision-making. Rapid Deployment for Business Agility: The one-click deploy feature ensures swift execution of web3 integrations, allowing enterprises to adapt to market demands and stay ahead of the competition. Cost-Effective Solutions: By automating the generation of smart contracts and integration processes, the tool helps companies for rapid prototyping.

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How it's Made

  1. Understanding how to provide users a environment by running a hardhat project. We solved this by creating a runtime in the backend and then running users code through the hardhat environment.
  2. The very high time cost of installing a new environment. Solved this using shell scripts by reusing the same environment but with file modifications.
  3. Providing relevant examples to the LLM for fine tuning. It might seem siple at first but it actually took a lot of time to make sure it provided accurate results.
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