File size: 3,687 Bytes
badcf3c
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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
from openai import OpenAI
import os
import pandas as pd
import google.generativeai as genai
import requests

# 输入模型系列和内容
def zero_shot(model_series, model_name, content):
    # 读取txt文件
    df = pd.read_csv('./LLM_APIs.txt')
    # 由于列名包含制表符,需要先分割列名
    df = pd.DataFrame([x.split('\t') for x in df.values.flatten()], columns=['name','series','API'])
    # 获取对应的API密钥
    api_key = df[df['name'] == model_series]['API'].values[0]
    
    # 根据不同模型系列调用不同API
    if model_series == 'gpt':
        client = OpenAI(
            api_key=api_key,
            base_url="https://api.bianxie.ai/v1"
        )
        # print("##1")
        completion = client.chat.completions.create(
            model = model_name,
            messages=[
                {
                    "role": "user",
                    "content": content
                }
            ]
        )
        # print("##2")
        return completion.choices[0].message
        
    elif model_series == 'llama':
        client = OpenAI(
            api_key=api_key,
            base_url="https://api.bianxie.ai/v1"
        )
        completion = client.chat.completions.create(
            model=model_name,
            messages=[
                {
                    "role": "user",
                    "content": content
                }
            ]
        )
        return completion.choices[0].message
        
    elif model_series == 'deepSeek':

        client = OpenAI(api_key=api_key,
                         base_url="https://api.studio.nebius.ai/v1")

        response = client.chat.completions.create(
            model=model_name,
            messages=[
                {"role": "user", "content": content},
            ],
            stream=False
        )
        # client = OpenAI(api_key=api_key,
        #                  base_url="https://api.deepseek.com")

        # response = client.chat.completions.create(
        #     model=model_name,
        #     messages=[
        #         {"role": "user", "content": content},
        #     ],
        #     stream=False
        # )

        return response.choices[0].message

        
    elif model_series == 'gemini':
        # genai.configure(api_key=api_key)
        # model = genai.GenerativeModel(model_name)
        # response = model.generate_content(content)
        # print(response.text)
        # return response.text
        api_key = api_key
        url = 'https://api.bianxie.ai/v1/chat/completions'
        headers = {
            'Content-Type': 'application/json',
            'Authorization': f'Bearer {api_key}'
        }
        data = {
            'model': model_name,
            'messages': [{'role': 'user', 'content': content}],
        }
        response = requests.post(url, headers=headers, json=data)
        content = response.json()['choices'][0]['message']
        return content
        
    elif model_series == 'claude':
        api_key = api_key
        url = 'https://api.bianxie.ai/v1/chat/completions'

        headers = {
            'Content-Type': 'application/json',
            'Authorization': f'Bearer {api_key}'
        }

        data = {
            'model': model_name,
            'messages': [{'role': 'user', 'content': content}],
        }

        response = requests.post(url, headers=headers, json=data)
        print(response.json())
        content = response.json()['choices'][0]['message']
        return content
    
    else:
        return "不支持的模型系列"