summaryrefslogtreecommitdiffstats
path: root/g4f/gui/server/api.py
blob: 966319e42120820eaffc0de6d4809df05d0af11a (plain) (blame)
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
import logging
import json
from typing import Iterator

try:
    import webview
except ImportError:
    ...

from g4f import version, models
from g4f import get_last_provider, ChatCompletion
from g4f.errors import VersionNotFoundError
from g4f.Provider import ProviderType, __providers__, __map__
from g4f.providers.base_provider import ProviderModelMixin
from g4f.Provider.bing.create_images import patch_provider
from g4f.Provider.Bing import Conversation

conversations: dict[str, Conversation] = {}

class Api():

    def get_models(self) -> list[str]:
        """
        Return a list of all models.

        Fetches and returns a list of all available models in the system.

        Returns:
            List[str]: A list of model names.
        """
        return models._all_models

    def get_provider_models(self, provider: str) -> list[dict]:
        if provider in __map__:
            provider: ProviderType = __map__[provider]
            if issubclass(provider, ProviderModelMixin):
                return [{"model": model, "default": model == provider.default_model} for model in provider.get_models()]
            elif provider.supports_gpt_35_turbo or provider.supports_gpt_4:
                return [
                    *([{"model": "gpt-4", "default": not provider.supports_gpt_4}] if provider.supports_gpt_4 else []),
                    *([{"model": "gpt-3.5-turbo", "default": not provider.supports_gpt_4}] if provider.supports_gpt_35_turbo else [])
                ]
            else:
                return [];

    def get_providers(self) -> list[str]:
        """
        Return a list of all working providers.
        """
        return [provider.__name__ for provider in __providers__ if provider.working]

    def get_version(self):
        """
        Returns the current and latest version of the application.

        Returns:
            dict: A dictionary containing the current and latest version.
        """
        try:
            current_version = version.utils.current_version
        except VersionNotFoundError:
            current_version = None
        return {
            "version": current_version,
            "latest_version": version.utils.latest_version,
        }

    def generate_title(self):
        """
        Generates and returns a title based on the request data.

        Returns:
            dict: A dictionary with the generated title.
        """
        return {'title': ''}

    def get_conversation(self, options: dict, **kwargs) -> Iterator:
        window = webview.active_window()
        for message in self._create_response_stream(
            self._prepare_conversation_kwargs(options, kwargs),
            options.get("conversation_id")
        ):
            window.evaluate_js(f"this.add_message_chunk({json.dumps(message)})")

    def _prepare_conversation_kwargs(self, json_data: dict, kwargs: dict):
        """
        Prepares arguments for chat completion based on the request data.

        Reads the request and prepares the necessary arguments for handling 
        a chat completion request.

        Returns:
            dict: Arguments prepared for chat completion.
        """ 
        provider = json_data.get('provider', None)
        if "image" in kwargs and provider is None:
            provider = "Bing"
        if provider == 'OpenaiChat':
            kwargs['auto_continue'] = True

        messages = json_data['messages']
        if json_data.get('web_search'):
            if provider == "Bing":
                kwargs['web_search'] = True
            else:
                from .internet import get_search_message
                messages[-1]["content"] = get_search_message(messages[-1]["content"])

        conversation_id = json_data.get("conversation_id")
        if conversation_id and conversation_id in conversations:
            kwargs["conversation"] = conversations[conversation_id]

        model = json_data.get('model')
        model = model if model else models.default
        patch = patch_provider if json_data.get('patch_provider') else None

        return {
            "model": model,
            "provider": provider,
            "messages": messages,
            "stream": True,
            "ignore_stream": True,
            "patch_provider": patch,
            "return_conversation": True,
            **kwargs
        }

    def _create_response_stream(self, kwargs, conversation_id: str) -> Iterator:
        """
        Creates and returns a streaming response for the conversation.

        Args:
            kwargs (dict): Arguments for creating the chat completion.

        Yields:
            str: JSON formatted response chunks for the stream.

        Raises:
            Exception: If an error occurs during the streaming process.
        """
        try:
            first = True
            for chunk in ChatCompletion.create(**kwargs):
                if first:
                    first = False
                    yield self._format_json("provider", get_last_provider(True))
                if isinstance(chunk, Conversation):
                    conversations[conversation_id] = chunk
                    yield self._format_json("conversation", conversation_id)
                elif isinstance(chunk, Exception):
                    logging.exception(chunk)
                    yield self._format_json("message", get_error_message(chunk))
                else:
                    yield self._format_json("content", chunk)
        except Exception as e:
            logging.exception(e)
            yield self._format_json('error', get_error_message(e))

    def _format_json(self, response_type: str, content):
        """
        Formats and returns a JSON response.

        Args:
            response_type (str): The type of the response.
            content: The content to be included in the response.

        Returns:
            str: A JSON formatted string.
        """
        return {
            'type': response_type,
            response_type: content
        }
    
def get_error_message(exception: Exception) -> str:
    """
    Generates a formatted error message from an exception.

    Args:
        exception (Exception): The exception to format.

    Returns:
        str: A formatted error message string.
    """
    return f"{get_last_provider().__name__}: {type(exception).__name__}: {exception}"