返回提交历史
Modified
README.md
+42
-1
Added
t3nsor/__init__.py
+118
-0
XFEstudio/gpt4free
t3nsor api gpt-3.5
81e03302
代码差异
2 个文件
+160
-1
@@ -1 +1,42 @@
1
soon.
1
working on it...
2
3
`t3nsor` (use like openai pypi package)
4
5
Import t3nsor:
6
7
```python
8
import t3nsor
9
10
# t3nsor.Completion.create
11
# t3nsor.StreamCompletion.create
12
```
13
14
Example Chatbot
15
```python
16
messages = []
17
18
while True:
19
user = input('you: ')
20
21
t3nsor_cmpl = t3nsor.Completion.create(
22
prompt = user,
23
messages = messages
24
)
25
26
print('gpt:', t3nsor_cmpl.completion.choices[0].text)
27
28
messages.extend([
29
{'role': 'user', 'content': user },
30
{'role': 'assistant', 'content': t3nsor_cmpl.completion.choices[0].text}
31
])
32
```
33
34
Streaming Response:
35
36
```python
37
for response in t3nsor.StreamCompletion.create(
38
prompt = 'write python code to reverse a string',
39
messages = []):
40
41
print(response.completion.choices[0].text)
42
```
@@ -0,0 +1,118 @@
1
from requests import post
2
from time import time
3
4
class T3nsorResponse:
5
6
class Completion:
7
8
class Choices:
9
def __init__(self, choice: dict) -> None:
10
self.text = choice['text']
11
self.content = self.text.encode()
12
self.index = choice['index']
13
self.logprobs = choice['logprobs']
14
self.finish_reason = choice['finish_reason']
15
16
def __repr__(self) -> str:
17
return f'''<__main__.APIResponse.Completion.Choices(\n text = {self.text.encode()},\n index = {self.index},\n logprobs = {self.logprobs},\n finish_reason = {self.finish_reason})object at 0x1337>'''
18
19
def __init__(self, choices: dict) -> None:
20
self.choices = [self.Choices(choice) for choice in choices]
21
22
class Usage:
23
def __init__(self, usage_dict: dict) -> None:
24
self.prompt_tokens = usage_dict['prompt_tokens']
25
self.completion_tokens = usage_dict['completion_tokens']
26
self.total_tokens = usage_dict['total_tokens']
27
28
def __repr__(self):
29
return f'''<__main__.APIResponse.Usage(\n prompt_tokens = {self.prompt_tokens},\n completion_tokens = {self.completion_tokens},\n total_tokens = {self.total_tokens})object at 0x1337>'''
30
31
def __init__(self, response_dict: dict) -> None:
32
33
self.response_dict = response_dict
34
self.id = response_dict['id']
35
self.object = response_dict['object']
36
self.created = response_dict['created']
37
self.model = response_dict['model']
38
self.completion = self.Completion(response_dict['choices'])
39
self.usage = self.Usage(response_dict['usage'])
40
41
def json(self) -> dict:
42
return self.response_dict
43
44
class Completion:
45
model = {
46
'model': {
47
'id' : 'gpt-3.5-turbo',
48
'name' : 'Default (GPT-3.5)'
49
}
50
}
51
52
def create(
53
prompt: str = 'hello world',
54
messages: list = []) -> T3nsorResponse:
55
56
response = post('https://www.t3nsor.tech/api/chat', json = Completion.model | {
57
'messages' : messages,
58
'key' : '',
59
'prompt' : prompt
60
})
61
62
return T3nsorResponse({
63
'id' : f'cmpl-1337-{int(time())}',
64
'object' : 'text_completion',
65
'created': int(time()),
66
'model' : Completion.model,
67
'choices': [{
68
'text' : response.text,
69
'index' : 0,
70
'logprobs' : None,
71
'finish_reason' : 'stop'
72
}],
73
'usage': {
74
'prompt_chars' : len(prompt),
75
'completion_chars' : len(response.text),
76
'total_chars' : len(prompt) + len(response.text)
77
}
78
})
79
80
class StreamCompletion:
81
model = {
82
'model': {
83
'id' : 'gpt-3.5-turbo',
84
'name' : 'Default (GPT-3.5)'
85
}
86
}
87
88
def create(
89
prompt: str = 'hello world',
90
messages: list = []) -> T3nsorResponse:
91
92
response = post('https://www.t3nsor.tech/api/chat', stream = True, json = Completion.model | {
93
'messages' : messages,
94
'key' : '',
95
'prompt' : prompt
96
})
97
98
for resp in response.iter_lines():
99
if resp:
100
yield T3nsorResponse({
101
'id' : f'cmpl-1337-{int(time())}',
102
'object' : 'text_completion',
103
'created': int(time()),
104
'model' : Completion.model,
105
106
'choices': [{
107
'text' : resp.decode(),
108
'index' : 0,
109
'logprobs' : None,
110
'finish_reason' : 'stop'
111
}],
112
113
'usage': {
114
'prompt_chars' : len(prompt),
115
'completion_chars' : len(resp.decode()),
116
'total_chars' : len(prompt) + len(resp.decode())
117
}
118
})