How to Upload Your Typescript file to OpenAI Assistant and Talk to it!
Using an OpenAI assistant as a partner in the development process is like enhancing the quality of every line of code written!
In this video you will learn how to...
Upload Your Code: You learn how to automate the process of uploading your TypeScript files to OpenAI. This is a crucial step where your local development environment communicates with OpenAI's cloud-based AI models.
Function Call: The tutorial delves into how to use OpenAI's API to make function calls. This isn't about simple text queries; it's about asking the AI to perform specific tasks, like analyzing code, identifying patterns, or suggesting improvements.
Receive AI Insights: After the AI processes your uploaded file, it generates feedback based on your code. This could range from syntax errors and code optimization suggestions to more sophisticated advice like architectural improvements or best practice recommendations.
Practical Application: The real gem here is seeing how these insights can be directly applied to your work. It's not just about getting feedback; it's about understanding how to use that feedback to make tangible improvements to your code.
Workflow Integration: The tutorial likely offers insights into integrating this process into your regular development workflow. This means you won't be manually uploading files every time but instead, setting up a system where your code is automatically analyzed as part of your development cycle.
Here's your video guide:
00:00 - Intro & Issue Recap
Old video referencing upload issues with OpenAI
Debugging past issues
Introducing AI "Jarvis" for coding assistance
00:54 - AI Assistant & File Handling
TypeScript file and AI assistant interaction
Challenges with file uploads
01:37 - Demonstrating the Solution
Running npm start to demonstrate the fix
Explanation of the code process with GitHub integration
Troubleshooting file stream not closing
Deleting unnecessary indexes after processing
03:23 - Automating Bug Report Handling
Explaining the process for automated bug handling
The assistant's role in identifying issues
Creating functions for the assistant to use
Embedding the GitHub token for repository access
07:26 - Testing the Improved Functionality
Testing updates and reviewing the execution process
Adjustments to function calls and error handling
09:30 - Reviewing the Assistant's Responses
Analysis of the assistant's responses to function calls
Refining instructions for better clarity
11:41 - Success & Next Steps
Celebrating the successful file upload and AI integration
Planning future improvements for developer interaction
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