emu
1.0.0
Menghasilkan kode untuk deskripsi program yang diminta oleh pengguna menggunakan Azure OpenAi API GPT-3.5-Turbo.
Perubahan/penambahan kode ditambahkan berdasarkan per waspadai per-menu-api.
Jika program melempar saat dijalankan, kesalahan log dikirim ke model GPT, kode atau teks-davinci untuk debug.
Repo file structure:
.
├── config_dir #file configuration
├── config.json #project files, paths, token limits metadata
├── config.py #set by user API, model, temperature for each request
├── credentials #credentials folder for OpenAI API
│ └── self_config.py #Azure OpenAI API credentials & model names metadata
#Move sample_self_config.py to self_config.py and fill data
├── emu_cli.py #run this module to run the program
├── feature_common.py #common methods for feature requests to API
├── feature_manager.py #manager for each feature requested by user in the menu
├── ft_operations #non-API requests directory
│ ├── op_loadcode.py #loads code from local file to apply code change requests to it
│ ├── op_run_program.py #run the code
├── ft_requests #feature text requests directory
│ ├── feature_request_argparse.py #standard add argparse request
│ ├── feature_request_custom_req.py #user enters custom system and request prompt
│ ├── feature_request_debuglogs.py #send logs from running the program to API to debug error found in logs
│ ├── feature_request_docstrings.py #add docstrings
│ ├── feature_request_excpt_and_log.py #add exception handling and logs to the code
│ ├── feature_request_rawcode.py #generate initial code from a program description
├── log_list_handler.py
├── project #project output directory
│ ├── module.log
│ ├── module.py #code requested stored here and versioned
├── prompt_txt #prompt specs directory for each request
│ ├── clean_json_rq.py
│ ├── custom_req.py
│ ├── debug_rq.py
│ ├── docstrings_rq.py
│ ├── error_hndl_logging_rq.py
│ ├── input_and_argparse_rq.py
│ ├── raw_code_rq.py
├── README.md
├── requirements.txt
├── sample_self_config.py
├── tools #file and request management utilities directory
│ ├── file_management.py
│ └── request_utils.py
├── user_interaction.py #user interaction class
Python V3.10+ Paket yang Diperlukan Python yang Diperlukan: Lihat Persyaratan.tx Tambahkan Paket ini ke Sys.Path Anda
Perubahan Path Diperlukan: Ubah Jalur ke Lingkungan Python Anda di config.json: misalnya "python_env_path": "/home/sergio/anaconda3/bin/python" untuk jalur apa pun yang ditetapkan untuk "python"
Otentikasi: Buat Direktori "Kredo" di akar proyek ini dan simpan di dalamnya sample_self_config.py. Ubah nama file PY ini menjadi self_config.py dan masukkan titik akhir, model/nama penempatan dan kunci Anda. Proyek diuji dengan Azure Openai API. API OpenAI yang belum teruji.
Mengkonfigurasi Model OpenAI dan Suhu Per Permintaan:
Eksekusi program ini: di baris perintah ./emu_cli.py menampilkan menu:
1. Generate Raw Code
Request model for code according to a description you provide.
2. Load Raw Code Script From File
3. Add Argparse
4. Exception Handling and Logging
5. User Custom Request
Requirement: code to be already loaded. Expected JSON response as specified in custom_req.py json_required_format variable.
6. Run Program And Request Repair of Debug Logs
Run the program and upon errors send the log error captured for the model to amend the code accordingly.
7. Add Docstrings To Program Code.
8. Set Menu Sequence
9. Run All
10. Exit
Choose your request:
Toggle Untuk menampilkan prompt untuk setiap permintaan: di config_dir/config.py sakelar bool show_request
Jika Anda menemukan ini membantu, Anda dapat membelikan saya kopi :)
