gpt4free/g4f/gui/server/api.py

from __future__ import annotations

import logging
import json
import os.path
from typing import Iterator
from uuid import uuid4
from functools import partial

try:
    import webview
    import platformdirs
    from plyer import camera
    from plyer import filechooser
    app_storage_path = platformdirs.user_pictures_dir
    user_select_image = partial(
        filechooser.open_file,
        path=platformdirs.user_pictures_dir(),
        filters=[["Image", "*.jpg", "*.jpeg", "*.png", "*.webp", "*.svg"]],
    )
    has_plyer = True
except ImportError:
    has_plyer = False
try:
    from android.runnable import run_on_ui_thread
    import android.permissions
    from android.permissions import Permission
    from android.permissions import _RequestPermissionsManager
    _RequestPermissionsManager.register_callback()
    from .android_gallery import user_select_image
    has_android = True
except ImportError:
    run_on_ui_thread = lambda a : a
    has_android = False

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.providers.conversation import BaseConversation

conversations: dict[str, BaseConversation] = {}

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.windows[0]
        if hasattr(self, "image") and self.image is not None:
            kwargs["image"] = open(self.image, "rb")
        for message in self._create_response_stream(
            self._prepare_conversation_kwargs(options, kwargs),
            options.get("conversation_id")
        ):
            if not window.evaluate_js(f"if (!this.abort) this.add_message_chunk({json.dumps(message)}); !this.abort && !this.error;"):
                break
        self.image = None
        self.set_selected(None)

    @run_on_ui_thread
    def choose_file(self):
        self.request_permissions()
        filechooser.open_file(
            path=platformdirs.user_pictures_dir(),
            on_selection=print
        )

    @run_on_ui_thread
    def choose_image(self):
        self.request_permissions()
        user_select_image(
            on_selection=self.on_image_selection
        )

    @run_on_ui_thread
    def take_picture(self):
        self.request_permissions()
        filename = os.path.join(app_storage_path(), f"chat-{uuid4()}.png")
        camera.take_picture(filename=filename, on_complete=self.on_camera)

    def on_image_selection(self, filename):
        filename = filename[0] if isinstance(filename, list) else filename
        if filename is not None and os.path.exists(filename):
            self.image = filename
        else:
            self.image = None
        self.set_selected(None if self.image is None else "image")

    def on_camera(self, filename):
        if filename is not None and os.path.exists(filename):
            self.image = filename
        else:
            self.image = None
        self.set_selected(None if self.image is None else "camera")

    def set_selected(self, input_id: str = None):
        window = webview.windows[0]
        if window is not None:
            window.evaluate_js(
                f"document.querySelector(`.image-label.selected`)?.classList.remove(`selected`);"
            )
            if input_id is not None and input_id in ("image", "camera"):
                window.evaluate_js(
                    f'document.querySelector(`label[for="{input_id}"]`)?.classList.add(`selected`);'
                )

    def request_permissions(self):
        if has_android:
            android.permissions.request_permissions([
                Permission.CAMERA,
                Permission.READ_EXTERNAL_STORAGE,
                Permission.WRITE_EXTERNAL_STORAGE
            ])

    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, BaseConversation):
                    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", str(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}"