Kamara – Survto AI
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Kamara
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Coding in VScode (2)

Kamara

Generated optimized code for devs.

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Starting price from $10

Tool Information

Kamara is an AI-powered coding tool that helps developers to write and edit their code more efficiently. It is a VS Code extension that can be installed and accessed within the IDE. The tool leverages GPT-4 technology and allows users to describe what they want to accomplish by just providing the instructions, which Kamara then translates into code snippets. Kamara has been tested with multiple languages, but it works best with TypeScript, and it can split long files into shorter ones for better results. Furthermore, Kamara uses a credit-based pricing system, where developers pay for how much code is read and written by Kamara. The pricing is $10 for every 200k credits and users can choose the amount they want to pay. Overall, Kamara seeks to help developers save time by automating some parts of the coding process. The tool was developed by Gonza Nardini and Diego Vazquez, and the team is actively working on improving Kamara. Developers can provide feedback by filling out a form or joining the Kamara Discord server. In conclusion, Kamara is a valuable tool that can help developers streamline their coding process and increase their productivity.

F.A.Q (20)

Kamara is an AI-powered coding tool designed to optimize the coding process for developers. It's a VS Code extension that translates the user's instructions into code snippets. It utilizes GPT-4 technology and works well with multiple languages, but best with TypeScript. Kamara can also split longer files into shorter ones for improved output. The tool has a credit-based pricing system and it was developed by Gonza Nardini and Diego Vazquez.

Kamara works by translating the developer's instructions into code. It leverages GPT-4 technology to interpret the user's commands and then creates code snippets based on that. Kamara is applied within the user's VS Code IDE which means that the developer can type instructions directly into the integrated tool and Kamara will generate the code.

Kamara works best with TypeScript. However, it has been tested and functions successfully with many other programming languages.

Kamara employs a credit-based pricing system. With this system, developers pay for the amount of code that is read and written by Kamara. The pricing is $10 for every 200,000 credits. Users have the flexibility to choose how much they wish to pay.

To install Kamara on your VS Code, you simply have to go to the VS Code marketplace and download the Kamara extension. Once installed, it is accessible directly from your VS Code environment.

Kamara was developed by Software Engineers Gonza Nardini and Diego Vazquez.

Feedback about Kamara can be given by filling out a form on their website, or by joining the Kamara Discord server where users can interact with the development team and other users.

Kamara is optimized for short files. If there's a long file, Kamara has the capability to split it up into several smaller ones for better results.

Kamara, using advanced GPT-4 technology, interprets the user's instructions and translates them into appropriate code snippets. The generated code rests on the user's instructions and Kamara's understanding of the coding language being used.

After installing Kamara, log into your account using either GitHub or Google on the Kamara view on VS Code. Create a .kamara.json file in your project root and begin dictating what Kamara should build for you.

Credits for Kamara can be purchased directly from their website. It operates a flexible payment structure where $10 provides users with 200,000 credits.

Kamara prompt tips include using the tool with TypeScript where it works best, employing the tool with shorter files for optimum results, and using Kamara when having a concrete idea of how to implement a certain piece of code.

GPT-4 technology in Kamara plays a crucial role in translating the user's instructions into code. This sophisticated AI technology aids Kamara in its comprehension of the developer's commands and the creation of corresponding code snippets.

The credit-based system in Kamara is a pricing model where users pay for the volume of code read and written by Kamara. Each time Kamara generates or reads code, it utilizes a certain number of credits. The cost is $10 for every 200,000 credits.

To log into Kamara, go to the Kamara view on your VS Code, press the login button, and sign in using either your GitHub or Google account.

Yes, Kamara can split long files into several smaller ones. This improves the efficacy of code generation, especially if the original file is quite extensive.

Kamara can technically be used with most programming languages. However, it has been extensively tested and functions best with TypeScript.

Saying that Kamara works best with TypeScript means it is more proficient at interpreting instructions and generating code in this particular language. Essentially, the quality and efficiency of Kamara's output are enhanced when used with TypeScript.

Yes, Kamara works best when you already have an implementation idea. The precision of instructions directly affects Kamara's output, hence, clarity about the desired output or function will result in more accurate code generation.

Yes, you can join a community of Kamara users. They have a Discord server where current and potential users can interact, share experiences, give feedback, and receive updates regarding the tool.

Pros and Cons

Pros

  • VS Code extension
  • Works best with TypeScript
  • Splits long files
  • Credit-based pricing system
  • Actively improved
  • Feedback through form/Discord
  • Productivity enhancer
  • Translates instructions to code
  • Tested with multiple languages
  • Works better with short files
  • Encourages specific problem description
  • Helps build complex projects
  • Login with GitHub/Google
  • Installable from VS Marketplace

Cons

  • Works best with TypeScript only
  • Splits long files only
  • Not free
  • credit-based pricing
  • Requires .kamara.json file setup
  • Limited capabilities with other languages
  • Reliant on user specificity
  • Best results require pre-existing knowledge
  • Disjointed file management

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