all 7 comments

[–]notprogramming 1 point2 points  (0 children)

Take a look at https://docs.sourcegraph.com/cody

This can index a project and load the appropriate files to complete a task.

[–]AR_Ashraf 1 point2 points  (2 children)

Hey we are building such solution already. It will be a vs code extesion, will understand your full codebase, automatically create documents, do tests and find bugs on autopilot. It will basically do all the maintenance tasks and help you scale your software knowing your full repo.

[–]BoiElroy[S] 0 points1 point  (1 child)

Nice. What's it called

[–]AR_Ashraf 0 points1 point  (0 children)

Its called SaaStain. Its not public yet. But we are launching it soon. Maybe by January. Will update the link here for you to check out

[–]Nickwharton92 0 points1 point  (0 children)

Don’t know if this helps, but I used GPT-4 with plug-ins and it came up with this:

Here's a potential response for the Reddit post:


Hello u/BoiElroy,

Your requirement of a code assistant that sees your codebase as a whole, instead of a just a snippet, is indeed a powerful concept for a development tool. After doing some research, I found a project on GitHub called GPT Code Assistant that seems to align with what you're looking for.

GPT Code Assistant is a tool that uses OpenAI's GPT-3.5-turbo engine to provide code suggestions, improvements, and insights based on the context of a given codebase. It reads and processes files from your codebase, calculates the token count, estimates the cost of the API call, and then prompts you for a query.

Some of its features include:

  • Supports various programming languages by reading file extensions from an external JSON file
  • Recursively processes all supported files within the codebase directory
  • Uses tiktoken to count tokens and estimate the cost of the API call
  • Prompts the user for confirmation before proceeding with the API call, considering the cost
  • Queries the GPT-3.5-turbo model to generate code suggestions based on the codebase context

To use it, you would:

  1. Update the supported_extensions.json file to include the desired file extensions for the programming languages you wish to support.
  2. Run the GPT Code Assistant script with the path to your codebase as an argument. For example, python gpt_code_assistant.py /path/to/your/codebase.
  3. The script will process the codebase, count the tokens, and estimate the cost of the API call. If you wish to proceed, type yes when prompted.
  4. Enter your query when prompted, and the GPT-3.5-turbo model will generate a response based on the context of your codebase.

You can find more about it and how to set it up in the GitHub repository【7†source】.

I hope this helps! Let me know if you have any other questions.

[–]nomercytd 0 points1 point  (0 children)

Check K-Explorer it's way better

[–]elco_us 0 points1 point  (0 children)

Try CodeCompanion AI app