1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
|
import ast
import logging
import time
import json
import random
import string
import uvicorn
import nest_asyncio
from fastapi import FastAPI, Response, Request
from fastapi.responses import StreamingResponse
from typing import List, Union, Any, Dict, AnyStr
#from ._tokenizer import tokenize
import g4f
from .. import debug
debug.logging = True
class Api:
def __init__(self, engine: g4f, debug: bool = True, sentry: bool = False,
list_ignored_providers: List[str] = None) -> None:
self.engine = engine
self.debug = debug
self.sentry = sentry
self.list_ignored_providers = list_ignored_providers
self.app = FastAPI()
nest_asyncio.apply()
JSONObject = Dict[AnyStr, Any]
JSONArray = List[Any]
JSONStructure = Union[JSONArray, JSONObject]
@self.app.get("/")
async def read_root():
return Response(content=json.dumps({"info": "g4f API"}, indent=4), media_type="application/json")
@self.app.get("/v1")
async def read_root_v1():
return Response(content=json.dumps({"info": "Go to /v1/chat/completions or /v1/models."}, indent=4), media_type="application/json")
@self.app.get("/v1/models")
async def models():
model_list = []
for model in g4f.Model.__all__():
model_info = (g4f.ModelUtils.convert[model])
model_list.append({
'id': model,
'object': 'model',
'created': 0,
'owned_by': model_info.base_provider}
)
return Response(content=json.dumps({
'object': 'list',
'data': model_list}, indent=4), media_type="application/json")
@self.app.get("/v1/models/{model_name}")
async def model_info(model_name: str):
try:
model_info = (g4f.ModelUtils.convert[model_name])
return Response(content=json.dumps({
'id': model_name,
'object': 'model',
'created': 0,
'owned_by': model_info.base_provider
}, indent=4), media_type="application/json")
except:
return Response(content=json.dumps({"error": "The model does not exist."}, indent=4), media_type="application/json")
@self.app.post("/v1/chat/completions")
async def chat_completions(request: Request, item: JSONStructure = None):
item_data = {
'model': 'gpt-3.5-turbo',
'stream': False,
}
# item contains byte keys, and dict.get suppresses error
item_data.update({
key.decode('utf-8') if isinstance(key, bytes) else key: str(value)
for key, value in (item or {}).items()
})
# messages is str, need dict
if isinstance(item_data.get('messages'), str):
item_data['messages'] = ast.literal_eval(item_data.get('messages'))
model = item_data.get('model')
stream = True if item_data.get("stream") == "True" else False
messages = item_data.get('messages')
provider = item_data.get('provider', '').replace('g4f.Provider.', '')
provider = provider if provider and provider != "Auto" else None
temperature = item_data.get('temperature')
try:
response = g4f.ChatCompletion.create(
model=model,
stream=stream,
messages=messages,
temperature = temperature,
provider = provider,
ignored=self.list_ignored_providers
)
except Exception as e:
logging.exception(e)
content = json.dumps({
"error": {"message": f"An error occurred while generating the response:\n{e}"},
"model": model,
"provider": g4f.get_last_provider(True)
})
return Response(content=content, status_code=500, media_type="application/json")
completion_id = ''.join(random.choices(string.ascii_letters + string.digits, k=28))
completion_timestamp = int(time.time())
if not stream:
#prompt_tokens, _ = tokenize(''.join([message['content'] for message in messages]))
#completion_tokens, _ = tokenize(response)
json_data = {
'id': f'chatcmpl-{completion_id}',
'object': 'chat.completion',
'created': completion_timestamp,
'model': model,
'provider': g4f.get_last_provider(True),
'choices': [
{
'index': 0,
'message': {
'role': 'assistant',
'content': response,
},
'finish_reason': 'stop',
}
],
'usage': {
'prompt_tokens': 0, #prompt_tokens,
'completion_tokens': 0, #completion_tokens,
'total_tokens': 0, #prompt_tokens + completion_tokens,
},
}
return Response(content=json.dumps(json_data, indent=4), media_type="application/json")
def streaming():
try:
for chunk in response:
completion_data = {
'id': f'chatcmpl-{completion_id}',
'object': 'chat.completion.chunk',
'created': completion_timestamp,
'model': model,
'provider': g4f.get_last_provider(True),
'choices': [
{
'index': 0,
'delta': {
'role': 'assistant',
'content': chunk,
},
'finish_reason': None,
}
],
}
yield f'data: {json.dumps(completion_data)}\n\n'
time.sleep(0.03)
end_completion_data = {
'id': f'chatcmpl-{completion_id}',
'object': 'chat.completion.chunk',
'created': completion_timestamp,
'model': model,
'provider': g4f.get_last_provider(True),
'choices': [
{
'index': 0,
'delta': {},
'finish_reason': 'stop',
}
],
}
yield f'data: {json.dumps(end_completion_data)}\n\n'
except GeneratorExit:
pass
except Exception as e:
logging.exception(e)
content = json.dumps({
"error": {"message": f"An error occurred while generating the response:\n{e}"},
"model": model,
"provider": g4f.get_last_provider(True),
})
yield f'data: {content}'
return StreamingResponse(streaming(), media_type="text/event-stream")
@self.app.post("/v1/completions")
async def completions():
return Response(content=json.dumps({'info': 'Not working yet.'}, indent=4), media_type="application/json")
def run(self, ip):
split_ip = ip.split(":")
uvicorn.run(app=self.app, host=split_ip[0], port=int(split_ip[1]), use_colors=False)
|
