Add Cerebras and HuggingFace2 provider, Fix RubiksAI provider

Add support for image generation in Copilot provider

g4f/Provider/Blackbox.py

@@ -28,6 +28,9 @@ class Blackbox(AsyncGeneratorProvider, ProviderModelMixin):
     image_models = [default_image_model, 'repomap']
     text_models = [default_model, 'gpt-4o', 'gemini-pro', 'claude-sonnet-3.5', 'blackboxai-pro']
     vision_models = [default_model, 'gpt-4o', 'gemini-pro', 'blackboxai-pro']
+    model_aliases = {
+        "claude-3.5-sonnet": "claude-sonnet-3.5",
+    }
     agentMode = {
         default_image_model: {'mode': True, 'id': "ImageGenerationLV45LJp", 'name': "Image Generation"},
     }
@@ -198,6 +201,7 @@ class Blackbox(AsyncGeneratorProvider, ProviderModelMixin):
         async with ClientSession(headers=headers) as session:
             async with session.post(cls.api_endpoint, json=data, proxy=proxy) as response:
                 response.raise_for_status()
+                is_first = False
                 async for chunk in response.content.iter_any():
                     text_chunk = chunk.decode(errors="ignore")
                     if model in cls.image_models:
@@ -217,5 +221,9 @@ class Blackbox(AsyncGeneratorProvider, ProviderModelMixin):
                         for i, result in enumerate(search_results, 1):
                             formatted_response += f"\n{i}. {result['title']}: {result['link']}"
                         yield formatted_response
-                    else:
+                    elif text_chunk:
-                        yield text_chunk.strip()
+                        if is_first:
+                            is_first = False
+                            yield text_chunk.lstrip()
+                        else:
+                            yield text_chunk

g4f/Provider/Copilot.py

@@ -21,8 +21,9 @@ from .helper import format_prompt
 from ..typing import CreateResult, Messages, ImageType
 from ..errors import MissingRequirementsError
 from ..requests.raise_for_status import raise_for_status
+from ..providers.helper import format_cookies
 from ..requests import get_nodriver
-from ..image import to_bytes, is_accepted_format
+from ..image import ImageResponse, to_bytes, is_accepted_format
 from .. import debug
 
 class Conversation(BaseConversation):
@@ -70,18 +71,21 @@ class Copilot(AbstractProvider):
                 access_token, cookies = asyncio.run(cls.get_access_token_and_cookies(proxy))
             else:
                 access_token = conversation.access_token
-            websocket_url = f"{websocket_url}&acessToken={quote(access_token)}"
+            debug.log(f"Copilot: Access token: {access_token[:7]}...{access_token[-5:]}")
-            headers = {"Authorization": f"Bearer {access_token}"}
+            debug.log(f"Copilot: Cookies: {';'.join([*cookies])}")
+            websocket_url = f"{websocket_url}&accessToken={quote(access_token)}"
+            headers = {"authorization": f"Bearer {access_token}", "cookie": format_cookies(cookies)}
     
         with Session(
             timeout=timeout,
             proxy=proxy,
             impersonate="chrome",
             headers=headers,
-            cookies=cookies
+            cookies=cookies,
         ) as session:
-            response = session.get(f"{cls.url}/")
+            response = session.get("https://copilot.microsoft.com/c/api/user")
             raise_for_status(response)
+            debug.log(f"Copilot: User: {response.json().get('firstName', 'null')}")
             if conversation is None:
                 response = session.post(cls.conversation_url)
                 raise_for_status(response)
@@ -119,6 +123,7 @@ class Copilot(AbstractProvider):
 
             is_started = False
             msg = None
+            image_prompt: str = None
             while True:
                 try:
                     msg = wss.recv()[0]
@@ -128,7 +133,11 @@ class Copilot(AbstractProvider):
                 if msg.get("event") == "appendText":
                     is_started = True
                     yield msg.get("text")
-                elif msg.get("event") in ["done", "partCompleted"]:
+                elif msg.get("event") == "generatingImage":
+                    image_prompt = msg.get("prompt")
+                elif msg.get("event") == "imageGenerated":
+                    yield ImageResponse(msg.get("url"), image_prompt, {"preview": msg.get("thumbnailUrl")})
+                elif msg.get("event") == "done":
                     break
             if not is_started:
                 raise RuntimeError(f"Last message: {msg}")
@@ -152,7 +161,7 @@ class Copilot(AbstractProvider):
                 })()
             """)
             if access_token is None:
-                asyncio.sleep(1)
+                await asyncio.sleep(1)
         cookies = {}
         for c in await page.send(nodriver.cdp.network.get_cookies([cls.url])):
             cookies[c.name] = c.value

g4f/Provider/RubiksAI.py

@@ -1,7 +1,6 @@
+
 from __future__ import annotations
 
-import asyncio
-import aiohttp
 import random
 import string
 import json
@@ -11,34 +10,24 @@ from aiohttp import ClientSession
 
 from ..typing import AsyncResult, Messages
 from .base_provider import AsyncGeneratorProvider, ProviderModelMixin
-from .helper import format_prompt
+from ..requests.raise_for_status import raise_for_status
-
 
 class RubiksAI(AsyncGeneratorProvider, ProviderModelMixin):
     label = "Rubiks AI"
     url = "https://rubiks.ai"
-    api_endpoint = "https://rubiks.ai/search/api.php"
+    api_endpoint = "https://rubiks.ai/search/api/"
     working = True
     supports_stream = True
     supports_system_message = True
     supports_message_history = True
 
-    default_model = 'llama-3.1-70b-versatile'
+    default_model = 'gpt-4o-mini'
-    models = [default_model, 'gpt-4o-mini']
+    models = [default_model, 'gpt-4o', 'o1-mini', 'claude-3.5-sonnet', 'grok-beta', 'gemini-1.5-pro', 'nova-pro']
 
     model_aliases = {
         "llama-3.1-70b": "llama-3.1-70b-versatile",
     }
 
-    @classmethod
-    def get_model(cls, model: str) -> str:
-        if model in cls.models:
-            return model
-        elif model in cls.model_aliases:
-            return cls.model_aliases[model]
-        else:
-            return cls.default_model
-
     @staticmethod
     def generate_mid() -> str:
         """
@@ -70,7 +59,8 @@ class RubiksAI(AsyncGeneratorProvider, ProviderModelMixin):
         model: str,
         messages: Messages,
         proxy: str = None,
-        websearch: bool = False,
+        web_search: bool = False,
+        temperature: float = 0.6,
         **kwargs
     ) -> AsyncResult:
         """
@@ -80,20 +70,18 @@ class RubiksAI(AsyncGeneratorProvider, ProviderModelMixin):
         - model (str): The model to use in the request.
         - messages (Messages): The messages to send as a prompt.
         - proxy (str, optional): Proxy URL, if needed.
-        - websearch (bool, optional): Indicates whether to include search sources in the response. Defaults to False.
+        - web_search (bool, optional): Indicates whether to include search sources in the response. Defaults to False.
         """
         model = cls.get_model(model)
-        prompt = format_prompt(messages)
-        q_value = prompt
         mid_value = cls.generate_mid()
-        referer = cls.create_referer(q=q_value, mid=mid_value, model=model)
+        referer = cls.create_referer(q=messages[-1]["content"], mid=mid_value, model=model)
 
-        url = cls.api_endpoint
+        data = {
-        params = {
+            "messages": messages,
-            'q': q_value,
+            "model": model,
-            'model': model,
+            "search": web_search,
-            'id': '',
+            "stream": True,
-            'mid': mid_value
+            "temperature": temperature
         }
 
         headers = {
@@ -111,52 +99,34 @@ class RubiksAI(AsyncGeneratorProvider, ProviderModelMixin):
             'sec-ch-ua-mobile': '?0',
             'sec-ch-ua-platform': '"Linux"'
         }
+        async with ClientSession() as session:
+            async with session.post(cls.api_endpoint, headers=headers, json=data, proxy=proxy) as response:
+                await raise_for_status(response)
 
-        try:
+                sources = []
-            timeout = aiohttp.ClientTimeout(total=None)
+                async for line in response.content:
-            async with ClientSession(timeout=timeout) as session:
+                    decoded_line = line.decode('utf-8').strip()
-                async with session.get(url, headers=headers, params=params, proxy=proxy) as response:
+                    if not decoded_line.startswith('data: '):
-                    if response.status != 200:
+                        continue
-                        yield f"Request ended with status code {response.status}"
+                    data = decoded_line[6:]
-                        return
+                    if data in ('[DONE]', '{"done": ""}'):
+                        break
+                    try:
+                        json_data = json.loads(data)
+                    except json.JSONDecodeError:
+                        continue
 
-                    assistant_text = ''
+                    if 'url' in json_data and 'title' in json_data:
-                    sources = []
+                        if web_search:
+                            sources.append({'title': json_data['title'], 'url': json_data['url']})
 
-                    async for line in response.content:
+                    elif 'choices' in json_data:
-                        decoded_line = line.decode('utf-8').strip()
+                        for choice in json_data['choices']:
-                        if not decoded_line.startswith('data: '):
+                            delta = choice.get('delta', {})
-                            continue
+                            content = delta.get('content', '')
-                        data = decoded_line[6:]
+                            if content:
-                        if data in ('[DONE]', '{"done": ""}'):
+                                yield content
-                            break
-                        try:
-                            json_data = json.loads(data)
-                        except json.JSONDecodeError:
-                            continue
 
-                        if 'url' in json_data and 'title' in json_data:
+                if web_search and sources:
-                            if websearch:
+                    sources_text = '\n'.join([f"{i+1}. [{s['title']}]: {s['url']}" for i, s in enumerate(sources)])
-                                sources.append({'title': json_data['title'], 'url': json_data['url']})
+                    yield f"\n\n**Source:**\n{sources_text}"
-
-                        elif 'choices' in json_data:
-                            for choice in json_data['choices']:
-                                delta = choice.get('delta', {})
-                                content = delta.get('content', '')
-                                role = delta.get('role', '')
-                                if role == 'assistant':
-                                    continue
-                                assistant_text += content
-
-                    if websearch and sources:
-                        sources_text = '\n'.join([f"{i+1}. [{s['title']}]: {s['url']}" for i, s in enumerate(sources)])
-                        assistant_text += f"\n\n**Source:**\n{sources_text}"
-
-                    yield assistant_text
-
-        except asyncio.CancelledError:
-            yield "The request was cancelled."
-        except aiohttp.ClientError as e:
-            yield f"An error occurred during the request: {e}"
-        except Exception as e:
-            yield f"An unexpected error occurred: {e}"

g4f/Provider/needs_auth/Cerebras.py

@@ -0,0 +1,65 @@
+from __future__ import annotations
+
+import requests
+from aiohttp import ClientSession
+
+from .OpenaiAPI import OpenaiAPI
+from ...typing import AsyncResult, Messages, Cookies
+from ...requests.raise_for_status import raise_for_status
+from ...cookies import get_cookies
+
+class Cerebras(OpenaiAPI):
+    label = "Cerebras Inference"
+    url = "https://inference.cerebras.ai/"
+    working = True
+    default_model = "llama3.1-70b"
+    fallback_models = [
+        "llama3.1-70b",
+        "llama3.1-8b",
+    ]
+    model_aliases = {"llama-3.1-70b": "llama3.1-70b", "llama-3.1-8b": "llama3.1-8b"}
+
+    @classmethod
+    def get_models(cls, api_key: str = None):
+        if not cls.models:
+            try:
+                headers = {}
+                if api_key:
+                    headers["authorization"] = f"Bearer ${api_key}"
+                response = requests.get(f"https://api.cerebras.ai/v1/models", headers=headers)
+                raise_for_status(response)
+                data = response.json()
+                cls.models = [model.get("model") for model in data.get("models")]
+            except Exception:
+                cls.models = cls.fallback_models
+        return cls.models
+
+    @classmethod
+    async def create_async_generator(
+        cls,
+        model: str,
+        messages: Messages,
+        api_base: str = "https://api.cerebras.ai/v1",
+        api_key: str = None,
+        cookies: Cookies = None,
+        **kwargs
+    ) -> AsyncResult:
+        if api_key is None and cookies is None:
+            cookies = get_cookies(".cerebras.ai")
+        async with ClientSession(cookies=cookies) as session:
+            async with session.get("https://inference.cerebras.ai/api/auth/session") as response:
+                raise_for_status(response)
+                data = await response.json()
+                if data:
+                    api_key = data.get("user", {}).get("demoApiKey")
+        async for chunk in super().create_async_generator(
+            model, messages,
+            api_base=api_base,
+            impersonate="chrome",
+            api_key=api_key,
+            headers={
+                "User-Agent": "ex/JS 1.5.0",
+            },
+            **kwargs
+        ):
+            yield chunk

g4f/Provider/needs_auth/CopilotAccount.py

@@ -1,9 +1,12 @@
 from __future__ import annotations
 
+from ..base_provider import ProviderModelMixin
 from ..Copilot import Copilot
 
-class CopilotAccount(Copilot):
+class CopilotAccount(Copilot, ProviderModelMixin):
     needs_auth = True
     parent = "Copilot"
     default_model = "Copilot"
-    default_vision_model = default_model
+    default_vision_model = default_model
+    models = [default_model]
+    image_models = models

g4f/Provider/needs_auth/HuggingFace2.py

@@ -0,0 +1,28 @@
+from __future__ import annotations
+
+from .OpenaiAPI import OpenaiAPI
+from ..HuggingChat import HuggingChat
+from ...typing import AsyncResult, Messages
+
+class HuggingFace2(OpenaiAPI):
+    label = "HuggingFace (Inference API)"
+    url = "https://huggingface.co"
+    working = True
+    default_model = "meta-llama/Llama-3.2-11B-Vision-Instruct"
+    default_vision_model = default_model
+    models = [
+        *HuggingChat.models
+    ]
+
+    @classmethod
+    def create_async_generator(
+        cls,
+        model: str,
+        messages: Messages,
+        api_base: str = "https://api-inference.huggingface.co/v1",
+        max_tokens: int = 500,
+        **kwargs
+    ) -> AsyncResult:
+        return super().create_async_generator(
+            model, messages, api_base=api_base, max_tokens=max_tokens, **kwargs
+        )

g4f/Provider/needs_auth/OpenaiAPI.py

@@ -34,6 +34,7 @@ class OpenaiAPI(AsyncGeneratorProvider, ProviderModelMixin):
         stop: Union[str, list[str]] = None,
         stream: bool = False,
         headers: dict = None,
+        impersonate: str = None,
         extra_data: dict = {},
         **kwargs
     ) -> AsyncResult:
@@ -55,7 +56,8 @@ class OpenaiAPI(AsyncGeneratorProvider, ProviderModelMixin):
         async with StreamSession(
             proxies={"all": proxy},
             headers=cls.get_headers(stream, api_key, headers),
-            timeout=timeout
+            timeout=timeout,
+            impersonate=impersonate,
         ) as session:
             data = filter_none(
                 messages=messages,

g4f/Provider/needs_auth/__init__.py

@@ -1,6 +1,7 @@
 from .gigachat         import *
 
 from .BingCreateImages import BingCreateImages
+from .Cerebras         import Cerebras
 from .CopilotAccount   import CopilotAccount
 from .DeepInfra        import DeepInfra
 from .DeepInfraImage   import DeepInfraImage
@@ -8,6 +9,7 @@ from .Gemini           import Gemini
 from .GeminiPro        import GeminiPro
 from .Groq             import Groq
 from .HuggingFace      import HuggingFace
+from .HuggingFace2     import HuggingFace2
 from .MetaAI           import MetaAI
 from .MetaAIAccount    import MetaAIAccount
 from .OpenaiAPI        import OpenaiAPI

g4f/gui/client/index.html

@@ -128,6 +128,10 @@
                 <label for="BingCreateImages-api_key" class="label" title="">Microsoft Designer in Bing:</label>
                 <textarea id="BingCreateImages-api_key" name="BingCreateImages[api_key]" placeholder="&quot;_U&quot; cookie"></textarea>
             </div>
+            <div class="field box">
+                <label for="Cerebras-api_key" class="label" title="">Cerebras Inference:</label>
+                <textarea id="Cerebras-api_key" name="Cerebras[api_key]" placeholder="api_key"></textarea>
+            </div>
             <div class="field box">
                 <label for="DeepInfra-api_key" class="label" title="">DeepInfra:</label>
                 <textarea id="DeepInfra-api_key" name="DeepInfra[api_key]" class="DeepInfraImage-api_key" placeholder="api_key"></textarea>
@@ -142,7 +146,7 @@
             </div>
             <div class="field box">
                 <label for="HuggingFace-api_key" class="label" title="">HuggingFace:</label>
-                <textarea id="HuggingFace-api_key" name="HuggingFace[api_key]" placeholder="api_key"></textarea>
+                <textarea id="HuggingFace-api_key" name="HuggingFace[api_key]" class="HuggingFace2-api_key" placeholder="api_key"></textarea>
             </div>
             <div class="field box">
                 <label for="Openai-api_key" class="label" title="">OpenAI API:</label>
@@ -192,7 +196,7 @@
                 <div class="stop_generating stop_generating-hidden">
                     <button id="cancelButton">
                         <span>Stop Generating</span>
-                        <i class="fa-regular fa-stop"></i>
+                        <i class="fa-solid fa-stop"></i>
                     </button>
                 </div>
                 <div class="regenerate">

g4f/gui/client/static/css/style.css

@@ -512,9 +512,7 @@ body {
 
 @media only screen and (min-width: 40em) {
     .stop_generating {
-        left: 50%;
+        right: 4px;
-        transform: translateX(-50%);
-        right: auto;
     }
     .toolbar .regenerate span {
         display: block;

g4f/gui/client/static/js/chat.v1.js

@@ -215,7 +215,6 @@ const register_message_buttons = async () => {
                 const message_el = el.parentElement.parentElement.parentElement;
                 el.classList.add("clicked");
                 setTimeout(() => el.classList.remove("clicked"), 1000);
-                await hide_message(window.conversation_id, message_el.dataset.index);
                 await ask_gpt(message_el.dataset.index, get_message_id());
             })
         }
@@ -317,6 +316,7 @@ async function remove_cancel_button() {
 
 regenerate.addEventListener("click", async () => {
     regenerate.classList.add("regenerate-hidden");
+    setTimeout(()=>regenerate.classList.remove("regenerate-hidden"), 3000);
     stop_generating.classList.remove("stop_generating-hidden");
     await hide_message(window.conversation_id);
     await ask_gpt(-1, get_message_id());
@@ -383,12 +383,12 @@ const prepare_messages = (messages, message_index = -1) => {
     return new_messages;
 }
 
-async function add_message_chunk(message, message_index) {
+async function add_message_chunk(message, message_id) {
-    content_map = content_storage[message_index];
+    content_map = content_storage[message_id];
     if (message.type == "conversation") {
         console.info("Conversation used:", message.conversation)
     } else if (message.type == "provider") {
-        provider_storage[message_index] = message.provider;
+        provider_storage[message_id] = message.provider;
         content_map.content.querySelector('.provider').innerHTML = `
             <a href="${message.provider.url}" target="_blank">
                 ${message.provider.label ? message.provider.label : message.provider.name}
@@ -398,7 +398,7 @@ async function add_message_chunk(message, message_index) {
     } else if (message.type == "message") {
         console.error(message.message)
     } else if (message.type == "error") {
-        error_storage[message_index] = message.error
+        error_storage[message_id] = message.error
         console.error(message.error);
         content_map.inner.innerHTML += `<p><strong>An error occured:</strong> ${message.error}</p>`;
         let p = document.createElement("p");
@@ -407,8 +407,8 @@ async function add_message_chunk(message, message_index) {
     } else if (message.type == "preview") {
         content_map.inner.innerHTML = markdown_render(message.preview);
     } else if (message.type == "content") {
-        message_storage[message_index] += message.content;
+        message_storage[message_id] += message.content;
-        html = markdown_render(message_storage[message_index]);
+        html = markdown_render(message_storage[message_id]);
         let lastElement, lastIndex = null;
         for (element of ['</p>', '</code></pre>', '</p>\n</li>\n</ol>', '</li>\n</ol>', '</li>\n</ul>']) {
             const index = html.lastIndexOf(element)
@@ -421,7 +421,7 @@ async function add_message_chunk(message, message_index) {
             html = html.substring(0, lastIndex) + '<span class="cursor"></span>' + lastElement;
         }
         content_map.inner.innerHTML = html;
-        content_map.count.innerText = count_words_and_tokens(message_storage[message_index], provider_storage[message_index]?.model);
+        content_map.count.innerText = count_words_and_tokens(message_storage[message_id], provider_storage[message_id]?.model);
         highlight(content_map.inner);
     } else if (message.type == "log") {
         let p = document.createElement("p");
@@ -453,7 +453,7 @@ const ask_gpt = async (message_index = -1, message_id) => {
     let total_messages = messages.length;
     messages = prepare_messages(messages, message_index);
     message_index = total_messages
-    message_storage[message_index] = "";
+    message_storage[message_id] = "";
     stop_generating.classList.remove(".stop_generating-hidden");
 
     message_box.scrollTop = message_box.scrollHeight;
@@ -477,10 +477,10 @@ const ask_gpt = async (message_index = -1, message_id) => {
         </div>
     `;
 
-    controller_storage[message_index] = new AbortController();
+    controller_storage[message_id] = new AbortController();
 
     let content_el = document.getElementById(`gpt_${message_id}`)
-    let content_map = content_storage[message_index] = {
+    let content_map = content_storage[message_id] = {
         content: content_el,
         inner: content_el.querySelector('.content_inner'),
         count: content_el.querySelector('.count'),
@@ -492,12 +492,7 @@ const ask_gpt = async (message_index = -1, message_id) => {
         const file = input && input.files.length > 0 ? input.files[0] : null;
         const provider = providerSelect.options[providerSelect.selectedIndex].value;
         const auto_continue = document.getElementById("auto_continue")?.checked;
-        let api_key = null;
+        let api_key = get_api_key_by_provider(provider);
-        if (provider) {
-            api_key = document.getElementById(`${provider}-api_key`)?.value || null;
-            if (api_key == null)
-                api_key = document.querySelector(`.${provider}-api_key`)?.value || null;
-        }
         await api("conversation", {
             id: message_id,
             conversation_id: window.conversation_id,
@@ -506,10 +501,10 @@ const ask_gpt = async (message_index = -1, message_id) => {
             provider: provider,
             messages: messages,
             auto_continue: auto_continue,
-            api_key: api_key
+            api_key: api_key,
-        }, file, message_index);
+        }, file, message_id);
-        if (!error_storage[message_index]) {
+        if (!error_storage[message_id]) {
-            html = markdown_render(message_storage[message_index]);
+            html = markdown_render(message_storage[message_id]);
             content_map.inner.innerHTML = html;
             highlight(content_map.inner);
 
@@ -520,14 +515,14 @@ const ask_gpt = async (message_index = -1, message_id) => {
     } catch (e) {
         console.error(e);
         if (e.name != "AbortError") {
-            error_storage[message_index] = true;
+            error_storage[message_id] = true;
             content_map.inner.innerHTML += `<p><strong>An error occured:</strong> ${e}</p>`;
         }
     }
-    delete controller_storage[message_index];
+    delete controller_storage[message_id];
-    if (!error_storage[message_index] && message_storage[message_index]) {
+    if (!error_storage[message_id] && message_storage[message_id]) {
-        const message_provider = message_index in provider_storage ? provider_storage[message_index] : null;
+        const message_provider = message_id in provider_storage ? provider_storage[message_id] : null;
-        await add_message(window.conversation_id, "assistant", message_storage[message_index], message_provider);
+        await add_message(window.conversation_id, "assistant", message_storage[message_id], message_provider);
         await safe_load_conversation(window.conversation_id);
     } else {
         let cursorDiv = message_box.querySelector(".cursor");
@@ -1156,7 +1151,7 @@ async function on_api() {
             evt.preventDefault();
             console.log("pressed enter");
             prompt_lock = true;
-            setTimeout(()=>prompt_lock=false, 3);
+            setTimeout(()=>prompt_lock=false, 3000);
             await handle_ask();
         } else {
             messageInput.style.removeProperty("height");
@@ -1167,7 +1162,7 @@ async function on_api() {
         console.log("clicked send");
         if (prompt_lock) return;
         prompt_lock = true;
-        setTimeout(()=>prompt_lock=false, 3);
+        setTimeout(()=>prompt_lock=false, 3000);
         await handle_ask();
     });
     messageInput.focus();
@@ -1189,8 +1184,8 @@ async function on_api() {
         providerSelect.appendChild(option);
     })
 
-    await load_provider_models(appStorage.getItem("provider"));
     await load_settings_storage()
+    await load_provider_models(appStorage.getItem("provider"));
 
     const hide_systemPrompt = document.getElementById("hide-systemPrompt")
     const slide_systemPrompt_icon = document.querySelector(".slide-systemPrompt i");
@@ -1316,7 +1311,7 @@ function get_selected_model() {
     }
 }
 
-async function api(ressource, args=null, file=null, message_index=null) {
+async function api(ressource, args=null, file=null, message_id=null) {
     if (window?.pywebview) {
         if (args !== null) {
             if (ressource == "models") {
@@ -1326,15 +1321,19 @@ async function api(ressource, args=null, file=null, message_index=null) {
         }
         return pywebview.api[`get_${ressource}`]();
     }
+    let api_key;
     if (ressource == "models" && args) {
+        api_key = get_api_key_by_provider(args);
         ressource = `${ressource}/${args}`;
     }
     const url = `/backend-api/v2/${ressource}`;
+    const headers = {};
+    if (api_key) {
+        headers.authorization = `Bearer ${api_key}`;
+    }
     if (ressource == "conversation") {
         let body = JSON.stringify(args);
-        const headers = {
+        headers.accept = 'text/event-stream';
-            accept: 'text/event-stream'
-        }
         if (file !== null) {
             const formData = new FormData();
             formData.append('file', file);
@@ -1345,17 +1344,17 @@ async function api(ressource, args=null, file=null, message_index=null) {
         }
         response = await fetch(url, {
             method: 'POST',
-            signal: controller_storage[message_index].signal,
+            signal: controller_storage[message_id].signal,
             headers: headers,
-            body: body
+            body: body,
         });
-        return read_response(response, message_index);
+        return read_response(response, message_id);
     }
-    response = await fetch(url);
+    response = await fetch(url, {headers: headers});
     return await response.json();
 }
 
-async function read_response(response, message_index) {
+async function read_response(response, message_id) {
     const reader = response.body.pipeThrough(new TextDecoderStream()).getReader();
     let buffer = ""
     while (true) {
@@ -1368,7 +1367,7 @@ async function read_response(response, message_index) {
                 continue;
             }
             try {
-                add_message_chunk(JSON.parse(buffer + line), message_index);
+                add_message_chunk(JSON.parse(buffer + line), message_id);
                 buffer = "";
             } catch {
                 buffer += line
@@ -1377,6 +1376,16 @@ async function read_response(response, message_index) {
     }
 }
 
+function get_api_key_by_provider(provider) {
+    let api_key = null;
+    if (provider) {
+        api_key = document.getElementById(`${provider}-api_key`)?.value || null;
+        if (api_key == null)
+            api_key = document.querySelector(`.${provider}-api_key`)?.value || null;
+    }
+    return api_key;
+}
+
 async function load_provider_models(providerIndex=null) {
     if (!providerIndex) {
         providerIndex = providerSelect.selectedIndex;

g4f/gui/server/api.py

@@ -38,10 +38,11 @@ class Api:
         return models._all_models
 
     @staticmethod
-    def get_provider_models(provider: str) -> list[dict]:
+    def get_provider_models(provider: str, api_key: str = None) -> list[dict]:
         if provider in __map__:
             provider: ProviderType = __map__[provider]
             if issubclass(provider, ProviderModelMixin):
+                models = provider.get_models() if api_key is None else provider.get_models(api_key=api_key)
                 return [
                     {
                         "model": model,
@@ -49,7 +50,7 @@ class Api:
                         "vision": getattr(provider, "default_vision_model", None) == model or model in getattr(provider, "vision_models", []),
                         "image": model in getattr(provider, "image_models", []),
                     }
-                    for model in provider.get_models()
+                    for model in models
                 ]
         return []
 

g4f/gui/server/backend.py

@@ -94,7 +94,8 @@ class Backend_Api(Api):
         )
 
     def get_provider_models(self, provider: str):
-        models = super().get_provider_models(provider)
+        api_key = None if request.authorization is None else request.authorization.token
+        models = super().get_provider_models(provider, api_key)
         if models is None:
             return 404, "Provider not found"
         return models

g4f/requests/raise_for_status.py

@@ -11,7 +11,9 @@ class CloudflareError(ResponseStatusError):
     ...
 
 def is_cloudflare(text: str) -> bool:
-    if "<title>Attention Required! | Cloudflare</title>" in text or 'id="cf-cloudflare-status"' in text:
+    if "Generated by cloudfront" in text:
+        return True
+    elif "<title>Attention Required! | Cloudflare</title>" in text or 'id="cf-cloudflare-status"' in text:
         return True
     return '<div id="cf-please-wait">' in text or "<title>Just a moment...</title>" in text