Add files via upload

Author: VadimBoev

g4f/Provider/needs_auth/Bard.py

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+from __future__ import annotations
+
+import time
+import os
+from selenium.webdriver.common.by import By
+from selenium.webdriver.support.ui import WebDriverWait
+from selenium.webdriver.support import expected_conditions as EC
+from selenium.webdriver.common.keys import Keys
+
+from ...typing import CreateResult, Messages
+from ..base_provider import BaseProvider
+from ..helper import format_prompt
+from ...webdriver import WebDriver, WebDriverSession
+
+class Bard(BaseProvider):
+    url = "https://bard.google.com"
+    working = True
+    needs_auth = True
+
+    @classmethod
+    def create_completion(
+        cls,
+        model: str,
+        messages: Messages,
+        stream: bool,
+        proxy: str = None,
+        webdriver: WebDriver = None,
+        user_data_dir: str = None,
+        headless: bool = True,
+        **kwargs
+    ) -> CreateResult:
+        prompt = format_prompt(messages)
+        session = WebDriverSession(webdriver, user_data_dir, headless, proxy=proxy)
+        with session as driver:
+            try:
+                driver.get(f"{cls.url}/chat")
+                wait = WebDriverWait(driver, 10 if headless else 240)
+                wait.until(EC.visibility_of_element_located((By.CSS_SELECTOR, "div.ql-editor.textarea")))
+            except:
+                # Reopen browser for login
+                if not webdriver:
+                    driver = session.reopen()
+                    driver.get(f"{cls.url}/chat")
+                    login_url = os.environ.get("G4F_LOGIN_URL")
+                    if login_url:
+                        yield f"Please login: [Google Bard]({login_url})\n\n"
+                    wait = WebDriverWait(driver, 240)
+                    wait.until(EC.visibility_of_element_located((By.CSS_SELECTOR, "div.ql-editor.textarea")))
+                else:
+                    raise RuntimeError("Prompt textarea not found. You may not be logged in.")
+
+            # Add hook in XMLHttpRequest
+            script = """
+const _http_request_open = XMLHttpRequest.prototype.open;
+window._message = "";
+XMLHttpRequest.prototype.open = function(method, url) {
+    if (url.includes("/assistant.lamda.BardFrontendService/StreamGenerate")) {
+        this.addEventListener("load", (event) => {
+            window._message = JSON.parse(JSON.parse(this.responseText.split("\\n")[3])[0][2])[4][0][1][0];
+        });
+    }
+    return _http_request_open.call(this, method, url);
+}
+"""
+            driver.execute_script(script)
+
+            # Submit prompt
+            driver.find_element(By.CSS_SELECTOR, "div.ql-editor.textarea").send_keys(prompt)
+            driver.find_element(By.CSS_SELECTOR, "div.ql-editor.textarea").send_keys(Keys.ENTER)
+
+            # Yield response
+            while True:
+                chunk = driver.execute_script("return window._message;")
+                if chunk:
+                    yield chunk
+                    return
+                else:
+                    time.sleep(0.1)

g4f/Provider/needs_auth/HuggingChat.py

@@ -0,0 +1,60 @@
+from __future__ import annotations
+
+import json, uuid
+
+from aiohttp import ClientSession
+
+from ...typing import AsyncResult, Messages
+from ..base_provider import AsyncGeneratorProvider
+from ..helper import format_prompt, get_cookies
+
+
+class HuggingChat(AsyncGeneratorProvider):
+    url = "https://huggingface.co/chat"
+    working = True
+    model = "meta-llama/Llama-2-70b-chat-hf"
+
+    @classmethod
+    async def create_async_generator(
+        cls,
+        model: str,
+        messages: Messages,
+        stream: bool = True,
+        proxy: str = None,
+        web_search: bool = False,
+        cookies: dict = None,
+        **kwargs
+    ) -> AsyncResult:
+        model = model if model else cls.model
+        if not cookies:
+            cookies = get_cookies(".huggingface.co")
+
+        headers = {
+            'User-Agent': 'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/111.0.0.0 Safari/537.36',
+        }
+        async with ClientSession(
+            cookies=cookies,
+            headers=headers
+        ) as session:
+            async with session.post(f"{cls.url}/conversation", json={"model": model}, proxy=proxy) as response:
+                conversation_id = (await response.json())["conversationId"]
+
+            send = {
+                "id": str(uuid.uuid4()),
+                "inputs": format_prompt(messages),
+                "is_retry": False,
+                "response_id": str(uuid.uuid4()),
+                "web_search": web_search
+            }
+            async with session.post(f"{cls.url}/conversation/{conversation_id}", json=send, proxy=proxy) as response:
+                async for line in response.content:
+                    line = json.loads(line[:-1])
+                    if "type" not in line:
+                        raise RuntimeError(f"Response: {line}")
+                    elif line["type"] == "stream":
+                        yield line["token"]
+                    elif line["type"] == "finalAnswer":
+                        break
+                
+            async with session.delete(f"{cls.url}/conversation/{conversation_id}", proxy=proxy) as response:
+                response.raise_for_status()

g4f/Provider/needs_auth/OpenAssistant.py

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+from __future__ import annotations
+
+import json
+
+from aiohttp import ClientSession
+
+from ...typing import AsyncResult, Messages
+from ..base_provider import AsyncGeneratorProvider
+from ..helper import format_prompt, get_cookies
+
+
+class OpenAssistant(AsyncGeneratorProvider):
+    url = "https://open-assistant.io/chat"
+    needs_auth = True
+    working = False
+    model = "OA_SFT_Llama_30B_6"
+
+    @classmethod
+    async def create_async_generator(
+        cls,
+        model: str,
+        messages: Messages,
+        proxy: str = None,
+        cookies: dict = None,
+        **kwargs
+    ) -> AsyncResult:
+        if not cookies:
+            cookies = get_cookies("open-assistant.io")
+
+        headers = {
+            'User-Agent': 'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/111.0.0.0 Safari/537.36',
+        }
+        async with ClientSession(
+            cookies=cookies,
+            headers=headers
+        ) as session:
+            async with session.post("https://open-assistant.io/api/chat", proxy=proxy) as response:
+                chat_id = (await response.json())["id"]
+
+            data = {
+                "chat_id": chat_id,
+                "content": f"<s>[INST]\n{format_prompt(messages)}\n[/INST]",
+                "parent_id": None
+            }
+            async with session.post("https://open-assistant.io/api/chat/prompter_message", proxy=proxy, json=data) as response:
+                parent_id = (await response.json())["id"]
+
+            data = {
+                "chat_id": chat_id,
+                "parent_id": parent_id,
+                "model_config_name": model if model else cls.model,
+                "sampling_parameters":{
+                    "top_k": 50,
+                    "top_p": None,
+                    "typical_p": None,
+                    "temperature": 0.35,
+                    "repetition_penalty": 1.1111111111111112,
+                    "max_new_tokens": 1024,
+                    **kwargs
+                },
+                "plugins":[]
+            }
+            async with session.post("https://open-assistant.io/api/chat/assistant_message", proxy=proxy, json=data) as response:
+                data = await response.json()
+                if "id" in  data:
+                    message_id = data["id"]
+                elif "message" in data:
+                    raise RuntimeError(data["message"])
+                else:
+                    response.raise_for_status()
+            
+            params = {
+                'chat_id': chat_id,
+                'message_id': message_id,
+            }
+            async with session.post("https://open-assistant.io/api/chat/events", proxy=proxy, params=params) as response:
+                start = "data: "
+                async for line in response.content:
+                    line = line.decode("utf-8")
+                    if line and line.startswith(start):
+                        line = json.loads(line[len(start):])
+                        if line["event_type"] == "token":
+                            yield line["text"]
+
+            params = {
+                'chat_id': chat_id,
+            }
+            async with session.delete("https://open-assistant.io/api/chat", proxy=proxy, params=params) as response:
+                response.raise_for_status()