Merge pull request #2490 from hlohaus/ccccc

Fix docker build and fix api_base issue in OpenaiAPI providers

.github/workflows/publish-workflow.yaml

@@ -57,19 +57,19 @@ jobs:
           username: ${{ github.repository_owner }}
           password: ${{ secrets.GHCR_PAT }}
 
-      - name: Build and push armv7 image
+      # - name: Build and push armv7 image
-        uses: docker/build-push-action@v5
+      #   uses: docker/build-push-action@v5
-        with:
+      #   with:
-            context: .
+      #       context: .
-            file: docker/Dockerfile-armv7
+      #       file: docker/Dockerfile-armv7
-            platforms: linux/arm/v7
+      #       platforms: linux/arm/v7
-            push: true
+      #       push: true
-            tags: |
+      #       tags: |
-              hlohaus789/g4f:latest-armv7
+      #         hlohaus789/g4f:latest-armv7
-              hlohaus789/g4f:${{ github.ref_name }}-armv7
+      #         hlohaus789/g4f:${{ github.ref_name }}-armv7
-            labels: ${{ steps.metadata.outputs.labels }}
+      #       labels: ${{ steps.metadata.outputs.labels }}
-            build-args: |
+      #       build-args: |
-              G4F_VERSION=${{ github.ref_name }}
+      #         G4F_VERSION=${{ github.ref_name }}
 
       - name: Build and push small images
         uses: docker/build-push-action@v5

etc/tool/copilot.py

@@ -18,7 +18,7 @@ g4f.debug.version_check = False
 GITHUB_TOKEN = os.getenv('GITHUB_TOKEN')
 GITHUB_REPOSITORY = os.getenv('GITHUB_REPOSITORY')
 G4F_PROVIDER = os.getenv('G4F_PROVIDER')
-G4F_MODEL = os.getenv('G4F_MODEL') or g4f.models.default
+G4F_MODEL = os.getenv('G4F_MODEL') or g4f.models.gpt_4
 
 def get_pr_details(github: Github) -> PullRequest:
     """

g4f/Provider/Airforce.py

@@ -158,7 +158,7 @@ class Airforce(AsyncGeneratorProvider, ProviderModelMixin):
             "User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64; rv:133.0) Gecko/20100101 Firefox/133.0",
             "Accept": "image/avif,image/webp,image/png,image/svg+xml,image/*;q=0.8,*/*;q=0.5",
             "Accept-Language": "en-US,en;q=0.5",
-            "Accept-Encoding": "gzip, deflate, br, zstd",
+            "Accept-Encoding": "gzip, deflate, br",
             "Content-Type": "application/json",
             "Authorization": f"Bearer {api_key}",
         }
@@ -192,7 +192,7 @@ class Airforce(AsyncGeneratorProvider, ProviderModelMixin):
             "User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64; rv:133.0) Gecko/20100101 Firefox/133.0",
             "Accept": "application/json, text/event-stream",
             "Accept-Language": "en-US,en;q=0.5",
-            "Accept-Encoding": "gzip, deflate, br, zstd",
+            "Accept-Encoding": "gzip, deflate, br",
             "Content-Type": "application/json",
             "Authorization": f"Bearer {api_key}",
         }

g4f/Provider/Cloudflare.py

@@ -79,9 +79,9 @@ class Cloudflare(AsyncGeneratorProvider, ProviderModelMixin):
                 cls._args["cookies"] = merge_cookies(cls._args["cookies"] , response)
                 try:
                     await raise_for_status(response)
-                except ResponseStatusError as e:
+                except ResponseStatusError:
                     cls._args = None
-                    raise e
+                    raise
                 async for line in response.iter_lines():
                     if line.startswith(b'data: '):
                         if line == b'data: [DONE]':

g4f/Provider/DeepInfraChat.py

@@ -7,6 +7,7 @@ class DeepInfraChat(OpenaiAPI):
     label = "DeepInfra Chat"
     url = "https://deepinfra.com/chat"
     working = True
+    api_base = "https://api.deepinfra.com/v1/openai"
 
     default_model = 'meta-llama/Meta-Llama-3.1-70B-Instruct-Turbo'
     models = [
@@ -34,7 +35,6 @@ class DeepInfraChat(OpenaiAPI):
         model: str,
         messages: Messages,
         proxy: str = None,
-        api_base: str = "https://api.deepinfra.com/v1/openai",
         **kwargs
     ) -> AsyncResult:
         headers = {
@@ -46,4 +46,4 @@ class DeepInfraChat(OpenaiAPI):
             'X-Deepinfra-Source': 'web-page',
             'accept': 'text/event-stream',
         }
-        return super().create_async_generator(model, messages, proxy, api_base=api_base, headers=headers, **kwargs)
+        return super().create_async_generator(model, messages, proxy, headers=headers, **kwargs)

g4f/Provider/PollinationsAI.py

@@ -15,16 +15,14 @@ from .helper import format_prompt
 class PollinationsAI(OpenaiAPI):
     label = "Pollinations AI"
     url = "https://pollinations.ai"
-    
     working = True
     needs_auth = False
     supports_stream = True
-    
+    api_base = "https://text.pollinations.ai/openai"
+
     default_model = "openai"
-    
     additional_models_image = ["midjourney", "dall-e-3"]
     additional_models_text = ["sur", "sur-mistral", "claude"]
-    
     model_aliases = {
         "gpt-4o": "openai",
         "mistral-nemo": "mistral",
@@ -66,7 +64,6 @@ class PollinationsAI(OpenaiAPI):
         model: str,
         messages: Messages,
         prompt: str = None,
-        api_base: str = "https://text.pollinations.ai/openai",
         api_key: str = None,
         proxy: str = None,
         seed: str = None,
@@ -76,25 +73,28 @@ class PollinationsAI(OpenaiAPI):
     ) -> AsyncResult:
         model = cls.get_model(model)
         if model in cls.image_models:
-            async for response in cls._generate_image(model, messages, prompt, seed, width, height):
+            async for response in cls._generate_image(model, messages, prompt, proxy, seed, width, height):
                 yield response
         elif model in cls.models:
-            async for response in cls._generate_text(model, messages, api_base, api_key, proxy, **kwargs):
+            async for response in cls._generate_text(model, messages, api_key, proxy, **kwargs):
                 yield response
         else:
             raise ValueError(f"Unknown model: {model}")
 
     @classmethod
-    async def _generate_image(cls, model: str, messages: Messages, prompt: str = None, seed: str = None, width: int = 1024, height: int = 1024):
+    async def _generate_image(cls, model: str, messages: Messages, prompt: str = None, proxy: str = None, seed: str = None, width: int = 1024, height: int = 1024):
         if prompt is None:
             prompt = messages[-1]["content"]
         if seed is None:
             seed = random.randint(0, 100000)
         image = f"https://image.pollinations.ai/prompt/{quote(prompt)}?width={width}&height={height}&seed={int(seed)}&nofeed=true&nologo=true&model={quote(model)}"
+        async with ClientSession(connector=get_connector(proxy=proxy), headers=cls.headers) as session:
+            async with session.get(image) as response:
+                await raise_for_status(response)
         yield ImageResponse(image, prompt)
 
     @classmethod
-    async def _generate_text(cls, model: str, messages: Messages, api_base: str, api_key: str = None, proxy: str = None, **kwargs):
+    async def _generate_text(cls, model: str, messages: Messages, api_key: str = None, proxy: str = None, **kwargs):
         if api_key is None:
             async with ClientSession(connector=get_connector(proxy=proxy), headers=cls.headers) as session:
                 prompt = format_prompt(messages)
@@ -104,6 +104,6 @@ class PollinationsAI(OpenaiAPI):
                         yield line.decode(errors="ignore")
         else:
             async for chunk in super().create_async_generator(
-                model, messages, api_base=api_base, proxy=proxy, **kwargs
+                model, messages, proxy=proxy, **kwargs
             ):
-                yield chunk
+                yield chunk

g4f/Provider/local/Ollama.py

@@ -31,10 +31,10 @@ class Ollama(OpenaiAPI):
         api_base: str = None,
         **kwargs
     ) -> AsyncResult:
-        if not api_base:
+        if api_base is None:
             host = os.getenv("OLLAMA_HOST", "localhost")
             port = os.getenv("OLLAMA_PORT", "11434")
             api_base: str = f"http://{host}:{port}/v1"
         return super().create_async_generator(
             model, messages, api_base=api_base, **kwargs
-        )
+        )

g4f/Provider/needs_auth/Cerebras.py

@@ -25,7 +25,6 @@ class Cerebras(OpenaiAPI):
         cls,
         model: str,
         messages: Messages,
-        api_base: str = api_base,
         api_key: str = None,
         cookies: Cookies = None,
         **kwargs
@@ -41,7 +40,6 @@ class Cerebras(OpenaiAPI):
                         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={

g4f/Provider/needs_auth/CopilotAccount.py

@@ -1,9 +1,8 @@
 from __future__ import annotations
 
-from ..base_provider import ProviderModelMixin
 from ..Copilot import Copilot
 
-class CopilotAccount(Copilot, ProviderModelMixin):
+class CopilotAccount(Copilot):
     needs_auth = True
     parent = "Copilot"
     default_model = "Copilot"

g4f/Provider/needs_auth/DeepInfra.py

@@ -8,6 +8,7 @@ class DeepInfra(OpenaiAPI):
     label = "DeepInfra"
     url = "https://deepinfra.com"
     working = True
+    api_base = "https://api.deepinfra.com/v1/openai",
     needs_auth = True
     supports_stream = True
     supports_message_history = True
@@ -27,7 +28,6 @@ class DeepInfra(OpenaiAPI):
         model: str,
         messages: Messages,
         stream: bool,
-        api_base: str = "https://api.deepinfra.com/v1/openai",
         temperature: float = 0.7,
         max_tokens: int = 1028,
         **kwargs
@@ -50,7 +50,6 @@ class DeepInfra(OpenaiAPI):
         return super().create_async_generator(
             model, messages,
             stream=stream,
-            api_base=api_base,
             temperature=temperature,
             max_tokens=max_tokens,
             headers=headers,

g4f/Provider/needs_auth/Groq.py

@@ -1,7 +1,6 @@
 from __future__ import annotations
 
 from .OpenaiAPI import OpenaiAPI
-from ...typing import AsyncResult, Messages
 
 class Groq(OpenaiAPI):
     label = "Groq"
@@ -29,16 +28,4 @@ class Groq(OpenaiAPI):
         "whisper-large-v3",
         "whisper-large-v3-turbo",
     ]
-    model_aliases = {"mixtral-8x7b": "mixtral-8x7b-32768", "llama2-70b": "llama2-70b-4096"}
+    model_aliases = {"mixtral-8x7b": "mixtral-8x7b-32768", "llama2-70b": "llama2-70b-4096"}
-
-    @classmethod
-    def create_async_generator(
-        cls,
-        model: str,
-        messages: Messages,
-        api_base: str = api_base,
-        **kwargs
-    ) -> AsyncResult:
-        return super().create_async_generator(
-            model, messages, api_base=api_base, **kwargs
-        )

g4f/Provider/needs_auth/HuggingFaceAPI.py

@@ -2,7 +2,6 @@ from __future__ import annotations
 
 from .OpenaiAPI import OpenaiAPI
 from .HuggingChat import HuggingChat
-from ...typing import AsyncResult, Messages
 
 class HuggingFaceAPI(OpenaiAPI):
     label = "HuggingFace (Inference API)"
@@ -13,17 +12,4 @@ class HuggingFaceAPI(OpenaiAPI):
     default_vision_model = default_model
     models = [
         *HuggingChat.models
-    ]
+    ]
-
-    @classmethod
-    def create_async_generator(
-        cls,
-        model: str,
-        messages: Messages,
-        api_base: str = api_base,
-        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

@@ -23,10 +23,12 @@ class OpenaiAPI(AsyncGeneratorProvider, ProviderModelMixin):
     fallback_models = []
 
     @classmethod
-    def get_models(cls, api_key: str = None, api_base: str = api_base) -> list[str]:
+    def get_models(cls, api_key: str = None, api_base: str = None) -> list[str]:
         if not cls.models:
             try:
                 headers = {}
+                if api_base is None:
+                    api_base = cls.api_base
                 if api_key is not None:
                     headers["authorization"] = f"Bearer {api_key}"
                 response = requests.get(f"{api_base}/models", headers=headers)
@@ -48,7 +50,7 @@ class OpenaiAPI(AsyncGeneratorProvider, ProviderModelMixin):
         timeout: int = 120,
         images: ImagesType = None,
         api_key: str = None,
-        api_base: str = api_base,
+        api_base: str = None,
         temperature: float = None,
         max_tokens: int = None,
         top_p: float = None,
@@ -61,6 +63,8 @@ class OpenaiAPI(AsyncGeneratorProvider, ProviderModelMixin):
     ) -> AsyncResult:
         if cls.needs_auth and api_key is None:
             raise MissingAuthError('Add a "api_key"')
+        if api_base is None:
+            api_base = cls.api_base
         if images is not None:
             if not model and hasattr(cls, "default_vision_model"):
                 model = cls.default_vision_model
@@ -134,8 +138,10 @@ class OpenaiAPI(AsyncGeneratorProvider, ProviderModelMixin):
         elif "error" in data:
             if "code" in data["error"]:
                 raise ResponseError(f'Error {data["error"]["code"]}: {data["error"]["message"]}')
-            else:
+            elif "message" in data["error"]:
                 raise ResponseError(data["error"]["message"])
+            else:
+                raise ResponseError(data["error"])
 
     @classmethod
     def get_headers(cls, stream: bool, api_key: str = None, headers: dict = None) -> dict:

g4f/Provider/needs_auth/OpenaiChat.py

@@ -438,7 +438,7 @@ class OpenaiChat(AsyncGeneratorProvider, ProviderModelMixin):
                     async for line in response.iter_lines():
                         async for chunk in cls.iter_messages_line(session, line, conversation):
                             yield chunk
-                if not history_disabled and RequestConfig.access_token is not None:
+                if not history_disabled and cls._api_key is not None:
                     yield SynthesizeData(cls.__name__, {
                         "conversation_id": conversation.conversation_id,
                         "message_id": conversation.message_id,

g4f/Provider/needs_auth/PerplexityApi.py

@@ -1,12 +1,12 @@
 from __future__ import annotations
 
 from .OpenaiAPI import OpenaiAPI
-from ...typing import AsyncResult, Messages
 
 class PerplexityApi(OpenaiAPI):
     label = "Perplexity API"
     url = "https://www.perplexity.ai"
     working = True
+    api_base = "https://api.perplexity.ai"
     default_model = "llama-3-sonar-large-32k-online"
     models = [
         "llama-3-sonar-small-32k-chat",
@@ -15,16 +15,4 @@ class PerplexityApi(OpenaiAPI):
         "llama-3-sonar-large-32k-online",
         "llama-3-8b-instruct",
         "llama-3-70b-instruct",
-    ]
+    ]
-
-    @classmethod
-    def create_async_generator(
-        cls,
-        model: str,
-        messages: Messages,
-        api_base: str = "https://api.perplexity.ai",
-        **kwargs
-    ) -> AsyncResult:
-        return super().create_async_generator(
-            model, messages, api_base=api_base, **kwargs
-        )

g4f/Provider/needs_auth/ThebApi.py

@@ -31,6 +31,7 @@ class ThebApi(OpenaiAPI):
     label = "TheB.AI API"
     url = "https://theb.ai"
     working = True
+    api_base = "https://api.theb.ai/v1"
     needs_auth = True
     default_model = "gpt-3.5-turbo"
     models = list(models)
@@ -40,7 +41,6 @@ class ThebApi(OpenaiAPI):
         cls,
         model: str,
         messages: Messages,
-        api_base: str = "https://api.theb.ai/v1",
         temperature: float = 1,
         top_p: float = 1,
         **kwargs
@@ -58,4 +58,4 @@ class ThebApi(OpenaiAPI):
                 "top_p": top_p,
             }
         }
-        return super().create_async_generator(model, messages, api_base=api_base, extra_data=data, **kwargs)
+        return super().create_async_generator(model, messages, extra_data=data, **kwargs)

g4f/Provider/needs_auth/xAI.py

@@ -1,22 +1,9 @@
 from __future__ import annotations
 
 from .OpenaiAPI import OpenaiAPI
-from ...typing import AsyncResult, Messages
 
 class xAI(OpenaiAPI):
     label = "xAI"
     url = "https://console.x.ai"
     api_base = "https://api.x.ai/v1"
-    working = True
+    working = True
-
-    @classmethod
-    def create_async_generator(
-        cls,
-        model: str,
-        messages: Messages,
-        api_base: str = api_base,
-        **kwargs
-    ) -> AsyncResult:
-        return super().create_async_generator(
-            model, messages, api_base=api_base, **kwargs
-        )

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

@@ -93,8 +93,9 @@ body {
     height: 100vh;
 }
 
-a:-webkit-any-link {
+body:not(.white) a:link,
-    color: var(--accent);
+body:not(.white) a:visited{
+    color: var(--colour-3);
 }
 
 .row {
@@ -380,7 +381,6 @@ body.white .gradient{
 .message .content_inner a:visited{
     font-size: 15px;
     line-height: 1.3;
-    color: var(--colour-3);
 }
 .message .content_inner pre{
     white-space: pre-wrap;

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

@@ -513,21 +513,7 @@ async function add_message_chunk(message, message_id) {
         content_map.inner.innerHTML = markdown_render(message.preview);
     } else if (message.type == "content") {
         message_storage[message_id] += message.content;
-        html = markdown_render(message_storage[message_id]);
+        update_message(content_map, 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)
-            if (index - element.length > lastIndex) {
-                lastElement = element;
-                lastIndex = index;
-            }
-        }
-        if (lastIndex) {
-            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_id], provider_storage[message_id]?.model);
-        highlight(content_map.inner);
         content_map.inner.style.height = "";
     } else if (message.type == "log") {
         let p = document.createElement("p");
@@ -536,16 +522,6 @@ async function add_message_chunk(message, message_id) {
     } else if (message.type == "synthesize") {
         synthesize_storage[message_id] = message.synthesize;
     }
-    let scroll_down = ()=>{
-        if (message_box.scrollTop >= message_box.scrollHeight - message_box.clientHeight - 100) {
-            window.scrollTo(0, 0);
-            message_box.scrollTo({ top: message_box.scrollHeight, behavior: "auto" });
-        }
-    }
-    if (!content_map.container.classList.contains("regenerate")) {
-        scroll_down();
-        setTimeout(scroll_down, 200);
-    }
 }
 
 const ask_gpt = async (message_id, message_index = -1, regenerate = false, provider = null, model = null) => {
@@ -1233,6 +1209,36 @@ function count_words_and_tokens(text, model) {
     return `(${count_words(text)} words, ${count_chars(text)} chars, ${count_tokens(model, text)} tokens)`;
 }
 
+function update_message(content_map, message_id) {
+    content_map.inner.dataset.timeout = setTimeout(() => {
+        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)
+            if (index - element.length > lastIndex) {
+                lastElement = element;
+                lastIndex = index;
+            }
+        }
+        if (lastIndex) {
+            html = html.substring(0, lastIndex) + '<span class="cursor"></span>' + lastElement;
+        }
+        if (error_storage[message_id]) {
+            content_map.inner.innerHTML += markdown_render(`**An error occured:** ${error_storage[message_id]}`);
+        }
+        content_map.inner.innerHTML = html;
+        content_map.count.innerText = count_words_and_tokens(message_storage[message_id], provider_storage[message_id]?.model);
+        highlight(content_map.inner);
+        if (!content_map.container.classList.contains("regenerate")) {
+            if (message_box.scrollTop >= message_box.scrollHeight - message_box.clientHeight - 200) {
+                window.scrollTo(0, 0);
+                message_box.scrollTo({ top: message_box.scrollHeight, behavior: "auto" });
+            }
+        }
+        if (content_map.inner.dataset.timeout) clearTimeout(content_map.inner.dataset.timeout);
+    }, 100);
+};
+
 let countFocus = messageInput;
 let timeoutId;
 const count_input = async () => {

g4f/models.py

@@ -24,7 +24,6 @@ from .Provider import (
     HuggingFace,
     Liaobots,
     Airforce,
-    Mhystical,
     MetaAI,
     MicrosoftDesigner,
     OpenaiChat,
@@ -68,7 +67,6 @@ default = Model(
     best_provider = IterListProvider([
         DDG,
         Pizzagpt,
-        ReplicateHome,
         Blackbox2,
         Blackbox,
         Copilot,
@@ -78,7 +76,7 @@ default = Model(
         Cloudflare,
         PollinationsAI,
         ChatGptEs,
-        ChatGpt,
+        OpenaiChat,
     ])
 )
 

g4f/requests/__init__.py

@@ -151,14 +151,14 @@ async def get_args_from_nodriver(
     else:
         await browser.cookies.set_all(get_cookie_params_from_dict(cookies, url=url, domain=domain))
     page = await browser.get(url)
-    for c in await browser.cookies.get_all():
+    for c in await page.send(nodriver.cdp.network.get_cookies([url])):
-        if c.domain.endswith(domain):
+        cookies[c.name] = c.value
-            cookies[c.name] = c.value
     user_agent = await page.evaluate("window.navigator.userAgent")
     await page.wait_for("body:not(.no-js)", timeout=timeout)
     await page.close()
     browser.stop()
     return {
+        "impersonate": "chrome",
         "cookies": cookies,
         "headers": {
             **DEFAULT_HEADERS,