OpenAI Go Assistant is a Go project that allows you to interact with the OpenAI API to automate various code generation and optimization operations. Designed for developers, this wizard makes creating Go code easy by offering advanced features, such as generating code from natural instructions, optimizing existing code, fixing errors, and adding unit tests.
- Features
- Requirements
- Installation
- Usage
- Disclaimer
- Best Practices
- Known Limitations
- Compatibility
- OpenAI usage cost
- Tips to optimize OpenAI API usage costs
- Resources
- Contribution
- License
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Code generation: Create Go code from simple natural language instructions by leveraging the power of the OpenAI API. The wizard generates initial code for functions, structures, algorithms, and more.
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Error Correction: Analyze code to automatically detect and correct syntax, logic, or optimization errors, making the debugging process faster and more efficient.
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Code Optimization: Rewrite and optimize existing code to improve performance, reduce complexity, or adhere to Go programming best practices.
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Unit test generation: Generate Go unit tests associated with code to ensure feature coverage and automatically validate expected behavior.
Install goimport tools to repair missing imports
go install golang.org/x/tools/cmd/goimports@latestInstall staticCheck to detect unused functions in generated code.
go install honnef.co/go/tools/cmd/staticcheck@latestStart by cloning this repository and navigating to the project folder:
git clone https://github.com/ariden83/openai-go-assistant.git
cd openai-go-assistantAdd your OpenAI API keys and configure settings in an .goia file located in the project root or in your home directory.:
language: "fr"
openai_model: "gpt-4-turbo"
openai_api_key: "your-api-key"
openai_url: "https://api.openai.com/v1/chat/completions"
openai_temperature: 0.6
openai_max_tokens: 256
max_attempts: 3Goimports: Automatically repairs missing imports in code.
go install golang.org/x/tools/cmd/goimports@latestStaticcheck: Detects unused functions and other problems in the code.
go install honnef.co/go/tools/cmd/staticcheck@latestYou have two options to run the project: install the utility or launch the project directly from the command line.
Build and install the binary using the following command:
make installOnce installed, you will be able to run the wizard via specific commands to take advantage of its different features.
If you prefer to run the project without installing the utility, simply run:
go run ./...Usage: goia [flags] [path ...]
-d display diffs instead of rewriting files
-l list files whose formatting differs from goimport's
-local string
put imports beginning with this string after 3rd-party package
-prefix value
relative local prefix to from a new import group (can be given several times)
-w write result to (source) file instead of stdout
Example :
goia -l -w ./test/.Use of OpenAI Go Assistant is at your own risk..
- I cannot be held responsible for any errors generated by the utility, whether errors in the code created, incorrect modifications made to your existing code, or possible loss of data.
- It is strongly recommended to always verify generated or modified code before using it in a production environment.
- Also remember to save your code before using this tool to avoid any loss.
Thank you for your understanding, and enjoy exploring the tool ! 🚀
Here are the best practices to follow for optimal use of OpenAI Go Assistant :
- Limit the size of submitted files.
- Structure natural instructions for better results.
- Use test or development files rather than production files.
- Back up files before submitting them to the tool.
- Check the modifications made by the tool before validating them.
- Use clean, well-formatted code files for best results.
- Avoid submitting code files containing syntactic or logical errors.
- Use clear and precise natural instructions to obtain optimal results.
- Always check the generated code before using it!
Here are the known limitations of OpenAI Go Assistant:
- Natural instructions must be clear and precise to achieve optimal results.
- Large code files may result in longer processing times.
- Complex code files may generate inaccurate results.
- Code files containing syntactic or logical errors may not be processed correctly.
- The tool may not be able to correct all types of errors or optimize all types of code.
- The tool may not generate unit tests for all types of code or functions.
- The tool may not be able to optimize all types of code or functions.
- The tool may not be able to generate code for all types of natural instructions.
- The tool may not be able to detect all types of errors in code files.
- The tool may not be able to optimize all types of code files.
- The tool may not be able to generate unit tests for all types of code files.
- The tool may not be able to analyze all types of code files.
- The tool may not be able to generate code for all types of code files.
OpenAI Go Assistant is compatible with the following operating systems: -Linux
You can then track API usage costs in real time on the OpenAI platform OpenAI usage cost.
Using the OpenAI API may incur varying costs depending on settings and frequency of calls. Here are some tips for optimizing your spending:
- temperature: A lower value (like 0.2) produces more deterministic responses, while a higher value (like 0.8) favors creative responses. For technical or specific tasks, choose a low value to reduce unnecessary iterations.
- max_tokens: This parameter limits the number of tokens generated per response. Set a value appropriate to your needs to avoid excessively long responses (for example, between 100 and 300 for simple Go functions).
Example of optimized configuration:
openai_temperature: 0.3
openai_max_tokens: 150
- Before calling the API, perform local tests on your files or instructions.
- Use tools like staticcheck or goimports to fix simple errors without relying on the API.
- Consolidate your requirements into a single API call when possible, instead of making multiple small calls.
- Visit the OpenAI usage cost page regularly to monitor your spending and adjust your settings accordingly.
- Set up alerts or notifications to receive updates on your consumption and avoid exceeding your budget.
- Analyze your usage patterns to identify areas where you can optimize your spending.
- Use the OpenAI playground to test models and refine your queries before making API calls.
- Monitor the performance of your queries and adjust your settings to improve response times and reduce costs.
- Review the results of your queries to identify areas where you can optimize your code or instructions.
- Use the OpenAI API documentation to learn about available models and parameters and make informed decisions about your queries.
- Share best practices with your team to ensure that everyone is using the API efficiently and cost-effectively.
- Consider using the OpenAI API for specific tasks that require advanced natural language processing capabilities, rather than general-purpose tasks that can be handled by other tools.
- Use the OpenAI API for tasks that require real-time responses or interactive conversations, rather than batch processing or offline analysis.
- Optimize your queries to reduce the number of tokens generated per response and avoid unnecessary iterations.
- Use the OpenAI API for tasks that require advanced natural language processing capabilities, such as generating code from natural language instructions, rather than simple text generation tasks.
- Monitor your usage and adjust your settings to optimize your spending and avoid exceeding your budget.
- Provide clear and concise instructions to get accurate answers on the first call. For example, instead of saying "Fix this Go file", specify "Fix syntax errors in this function and optimize imports".
By following these best practices, you will be able to maximize the effectiveness of OpenAI Go Assistant while controlling your costs. 🚀
Contributions are welcome! If you want to improve OpenAI Go Assistant, feel free to open an issue or submit a pull request.
Here are some ideas for possible improvements for the project:
- Support for other languages or OpenAI models.
- Integration with IDEs (like VSCode).
- Added a more interactive command line user interface.
- Added new features for code generation.
- Improved error detection and correction.
- Added new features for code optimization.
- Improved unit test generation.
- Added new features for code analysis.
- Improved documentation and examples.
- Bug fixes and performance improvements.
This project is licensed under the MIT license. You are free to use, modify and distribute it under the terms of the license.