| Name | g4f-xn JSON |
| Version |
0.0.6
JSON |
| download |
| home_page | None |
| Summary | library for easy access to GPT models based on g4f |
| upload_time | 2024-05-17 10:08:22 |
| maintainer | None |
| docs_url | None |
| author | Xandr0v |
| requires_python | None |
| license | None |
| keywords |
python
g4f
gpt
|
| VCS |
|
| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
| Travis-CI |
No Travis.
|
| coveralls test coverage |
No coveralls.
|
### g4f_xn
---
#### A library that allows you to use different GPT models!
Also has some other stuff like:
- reading and writing to files
- sound playback(i mean why not)
- other functions for convenience
The project is not ready for public use, but more for a fun and convinient (in my opinion) use of gpt models
#### code example:
```python
import g4f_xn as xn
# specify model
xn.settings('gpt-3.5-turbo')
prompt = '''
type numbers from 1 to 10
'''
result = xn.gpt(prompt)
print(result)
```
---
also you can provide an array to xn.gpt that will represent history of previous prompts and answers. It will use it as context and append prompt with response.
#### advanced example:
```python
import g4f_xn as xn
# specify model and provider
xn.settings('gpt-4', 'Bing')
p1 = '''
type numbers from 1 to 10
'''
p2 = '''
multiply each number by 2
'''
chat = []
r1 = xn.gpt(p1, chat)
r2 = xn.gpt(p2, chat)
print(r1) # 1, 2, 3, ...
print(r2) # 2, 4, 6, ...
```
---
#### gpt -> chat gpt
You can also save chat variable to txt file using xn.write, xn.read <br>
it will be basically chatgpt now
#### example with local chat history:
```python
import g4f_xn as xn
xn.settings('gpt-3.5-turbo')
history = xn.read(r'path/to/file.txt')
chat = [history]
prompt = '''
type numbers from 1 to 10
'''
result = xn.gpt(prompt, chat)
print(result)
xn.write(''.join(chat), r'path/to/file.txt')
```
---
It is highly recommended to use .ipynb files with this library as it is really flexible for that task
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"description": "### g4f_xn\r\n\r\n---\r\n#### A library that allows you to use different GPT models!\r\n\r\nAlso has some other stuff like:\r\n- reading and writing to files\r\n- sound playback(i mean why not)\r\n- other functions for convenience\r\n\r\nThe project is not ready for public use, but more for a fun and convinient (in my opinion) use of gpt models \r\n\r\n#### code example:\r\n\r\n```python\r\nimport g4f_xn as xn\r\n\r\n# specify model\r\nxn.settings('gpt-3.5-turbo')\r\n\r\nprompt = '''\r\ntype numbers from 1 to 10\r\n'''\r\n\r\nresult = xn.gpt(prompt)\r\nprint(result)\r\n```\r\n\r\n---\r\nalso you can provide an array to xn.gpt that will represent history of previous prompts and answers. It will use it as context and append prompt with response.\r\n\r\n\r\n#### advanced example:\r\n\r\n```python\r\nimport g4f_xn as xn\r\n\r\n# specify model and provider\r\nxn.settings('gpt-4', 'Bing')\r\n\r\np1 = '''\r\ntype numbers from 1 to 10\r\n'''\r\np2 = '''\r\nmultiply each number by 2\r\n'''\r\n\r\nchat = []\r\n\r\nr1 = xn.gpt(p1, chat)\r\nr2 = xn.gpt(p2, chat)\r\nprint(r1) # 1, 2, 3, ...\r\nprint(r2) # 2, 4, 6, ...\r\n```\r\n---\r\n\r\n#### gpt -> chat gpt\r\nYou can also save chat variable to txt file using xn.write, xn.read <br>\r\nit will be basically chatgpt now\r\n\r\n#### example with local chat history:\r\n\r\n```python\r\nimport g4f_xn as xn\r\n\r\nxn.settings('gpt-3.5-turbo')\r\n\r\nhistory = xn.read(r'path/to/file.txt')\r\nchat = [history]\r\nprompt = '''\r\ntype numbers from 1 to 10\r\n'''\r\n\r\nresult = xn.gpt(prompt, chat)\r\nprint(result)\r\n\r\nxn.write(''.join(chat), r'path/to/file.txt')\r\n```\r\n---\r\nIt is highly recommended to use .ipynb files with this library as it is really flexible for that task\r\n\r\n\r\n",
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