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
|
import os
from gpt4all import GPT4All
from .models import models
class LocalProvider:
@staticmethod
def create_completion(model, messages, stream, **kwargs):
if model not in models:
raise ValueError(f"Model '{model}' not found / not yet implemented")
model = models[model]
model_dir = os.path.join(os.path.dirname(os.path.abspath(__file__)), '../models/')
full_model_path = os.path.join(model_dir, model['path'])
if not os.path.isfile(full_model_path):
print(f"Model file '{full_model_path}' not found.")
download = input(f'Do you want to download {model["path"]} ? [y/n]')
if download in ['y', 'Y']:
GPT4All.download_model(model['path'], model_dir)
else:
raise ValueError(f"Model '{model['path']}' not found.")
model = GPT4All(model_name=model['path'],
n_threads=8,
verbose=False,
allow_download=False,
model_path=model_dir)
system_template = next((message['content'] for message in messages if message['role'] == 'system'),
'A chat between a curious user and an artificial intelligence assistant.')
prompt_template = 'USER: {0}\nASSISTANT: '
conversation = '\n'.join(f"{msg['role'].upper()}: {msg['content']}" for msg in messages) + "\nASSISTANT: "
with model.chat_session(system_template, prompt_template):
if stream:
for token in model.generate(conversation, streaming=True):
yield token
else:
yield model.generate(conversation)
|
