Merge pull request #1264 from hlohaus/any

Improve providers

g4f/Provider/AItianhuSpace.py

@@ -11,6 +11,7 @@ from .. import debug
 class AItianhuSpace(BaseProvider):
     url = "https://chat3.aiyunos.top/"
     working = True
+    supports_stream = True
     supports_gpt_35_turbo = True
     _domains = ["aitianhu.com", "aitianhu1.top"]
 

g4f/Provider/PerplexityAi.py

@@ -22,24 +22,24 @@ class PerplexityAi(BaseProvider):
         timeout: int = 120,
         browser: WebDriver = None,
         copilot: bool = False,
-        headless: bool = True,
         **kwargs
     ) -> CreateResult:
-        driver = browser if browser else get_browser("", headless, proxy)
+        driver = browser if browser else get_browser("", False, proxy)
 
         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
 
         prompt = format_prompt(messages)
 
         driver.get(f"{cls.url}/")
         wait = WebDriverWait(driver, timeout)
 
-        # Page loaded?
+        # Is page loaded?
         wait.until(EC.visibility_of_element_located((By.CSS_SELECTOR, "textarea[placeholder='Ask anything...']")))
 
-        # Add WebSocket hook
+        # Register WebSocket hook
         script = """
 window._message = window._last_message = "";
 window._message_finished = false;
@@ -57,8 +57,9 @@ WebSocket.prototype.send = function(...args) {
                         content = JSON.parse(content);
                     }
                     window._message = content["answer"];
-                    window._message_finished = data[0] == "query_answered";
-                    window._web_results = content["web_results"];
+                    if (!window._message_finished) {
+                        window._message_finished = data[0] == "query_answered";
+                    }
                 }
             }
         });
@@ -70,20 +71,19 @@ WebSocket.prototype.send = function(...args) {
 
         if copilot:
             try:
-               # Check account
+               # Check for account
                 driver.find_element(By.CSS_SELECTOR, "img[alt='User avatar']")
                # Enable copilot
                 driver.find_element(By.CSS_SELECTOR, "button[data-testid='copilot-toggle']").click()
             except:
-                raise RuntimeError("For copilot you needs a account")
+                raise RuntimeError("You need a account for copilot")
 
-        # Enter question
+        # Submit prompt
         driver.find_element(By.CSS_SELECTOR, "textarea[placeholder='Ask anything...']").send_keys(prompt)
-        # Submit question
-        driver.find_element(By.CSS_SELECTOR, "button.bg-super svg[data-icon='arrow-right']").click()
+        driver.find_element(By.CSS_SELECTOR, "textarea[placeholder='Ask anything...']").send_keys(Keys.ENTER)
 
         try:
-            # Yield response
+            # Stream response
             script = """
 if(window._message && window._message != window._last_message) {
     try {

g4f/Provider/needs_auth/Bard.py

@@ -32,7 +32,7 @@ class Bard(BaseProvider):
 
         try:
             driver.get(f"{cls.url}/chat")
-            wait = WebDriverWait(driver, 10)
+            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
@@ -61,14 +61,13 @@ XMLHttpRequest.prototype.open = function(method, url) {
 """
             driver.execute_script(script)
 
-            # Input and submit prompt
+            # Submit prompt
             driver.find_element(By.CSS_SELECTOR, "div.ql-editor.ql-blank.textarea").send_keys(prompt)
             driver.find_element(By.CSS_SELECTOR, "button.send-button").click()
 
             # Yield response
-            script = "return window._message;"
             while True:
-                chunk = driver.execute_script(script)
+                chunk = driver.execute_script("return window._message;")
                 if chunk:
                     yield chunk
                     return

g4f/Provider/needs_auth/Theb.py

@@ -1,101 +1,158 @@
 from __future__ import annotations
 
-import json
-import random
-import requests
+import time
 
-from ...typing import Any, CreateResult, Messages
+from ...typing import CreateResult, Messages
 from ..base_provider import BaseProvider
-from ..helper import format_prompt
+from ..helper import WebDriver, format_prompt, get_browser
 
+models = {
+    "theb-ai": "TheB.AI",
+    "theb-ai-free": "TheB.AI Free",
+    "gpt-3.5-turbo": "GPT-3.5 Turbo (New)",
+    "gpt-3.5-turbo-16k": "GPT-3.5-16K",
+    "gpt-4-turbo": "GPT-4 Turbo",
+    "gpt-4": "GPT-4",
+    "gpt-4-32k": "GPT-4 32K",
+    "claude-2": "Claude 2",
+    "claude-instant-1": "Claude Instant 1.2",
+    "palm-2": "PaLM 2",
+    "palm-2-32k": "PaLM 2 32K",
+    "palm-2-codey": "Codey",
+    "palm-2-codey-32k": "Codey 32K",
+    "vicuna-13b-v1.5": "Vicuna v1.5 13B",
+    "llama-2-7b-chat": "Llama 2 7B",
+    "llama-2-13b-chat": "Llama 2 13B",
+    "llama-2-70b-chat": "Llama 2 70B",
+    "code-llama-7b": "Code Llama 7B",
+    "code-llama-13b": "Code Llama 13B",
+    "code-llama-34b": "Code Llama 34B",
+    "qwen-7b-chat": "Qwen 7B"
+}
 
 class Theb(BaseProvider):
-    url                     = "https://theb.ai"
-    working                 = True
-    supports_stream         = True
-    supports_gpt_35_turbo   = True
-    needs_auth              = True
+    url = "https://beta.theb.ai"
+    working = True
+    supports_gpt_35_turbo = True
+    supports_gpt_4 = True
+    supports_stream = True
 
-    @staticmethod
+    @classmethod
     def create_completion(
+        cls,
         model: str,
         messages: Messages,
         stream: bool,
         proxy: str = None,
+        browser: WebDriver = None,
+        headless: bool = True,
         **kwargs
     ) -> CreateResult:
-        auth = kwargs.get("auth", {
-            "bearer_token":"free",
-            "org_id":"theb",
-        })
+        if model in models:
+            model = models[model]
+        prompt = format_prompt(messages)
+        driver = browser if browser else get_browser(None, headless, proxy)
 
-        bearer_token = auth["bearer_token"]
-        org_id       = auth["org_id"]
+        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
 
-        headers = {
-            'authority': 'beta.theb.ai',
-            'accept': 'text/event-stream',
-            'accept-language': 'id-ID,id;q=0.9,en-US;q=0.8,en;q=0.7',
-            'authorization': f'Bearer {bearer_token}',
-            'content-type': 'application/json',
-            'origin': 'https://beta.theb.ai',
-            'referer': 'https://beta.theb.ai/home',
-            'sec-ch-ua': '"Chromium";v="116", "Not)A;Brand";v="24", "Google Chrome";v="116"',
-            'sec-ch-ua-mobile': '?0',
-            'sec-ch-ua-platform': '"Windows"',
-            'sec-fetch-dest': 'empty',
-            'sec-fetch-mode': 'cors',
-            'sec-fetch-site': 'same-origin',
-            'user-agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/116.0.0.0 Safari/537.36',
-            'x-ai-model': 'ee8d4f29cb7047f78cbe84313ed6ace8',
+        
+        try:
+            driver.get(f"{cls.url}/home")
+            wait = WebDriverWait(driver, 10 if headless else 240)
+            wait.until(EC.visibility_of_element_located((By.TAG_NAME, "body")))
+            time.sleep(0.1)
+            try:
+                driver.find_element(By.CSS_SELECTOR, ".driver-overlay").click()
+                driver.find_element(By.CSS_SELECTOR, ".driver-overlay").click()
+            except:
+                pass
+            if model:
+                # Load model panel
+                wait.until(EC.visibility_of_element_located((By.CSS_SELECTOR, "#SelectModel svg")))
+                time.sleep(0.1)
+                driver.find_element(By.CSS_SELECTOR, "#SelectModel svg").click()
+                try:
+                    driver.find_element(By.CSS_SELECTOR, ".driver-overlay").click()
+                    driver.find_element(By.CSS_SELECTOR, ".driver-overlay").click()
+                except:
+                    pass
+                # Select model
+                selector = f"div.flex-col div.items-center span[title='{model}']"
+                wait.until(EC.visibility_of_element_located((By.CSS_SELECTOR, selector)))
+                span = driver.find_element(By.CSS_SELECTOR, selector)
+                container = span.find_element(By.XPATH, "//div/../..")
+                button = container.find_element(By.CSS_SELECTOR, "button.btn-blue.btn-small.border")
+                button.click()
+
+            # Register fetch hook
+            script = """
+window._fetch = window.fetch;
+window.fetch = (url, options) => {
+    // Call parent fetch method
+    const result = window._fetch(url, options);
+    if (!url.startsWith("/api/conversation")) {
+        return result;
+    }
+    // Load response reader
+    result.then((response) => {
+        if (!response.body.locked) {
+            window._reader = response.body.getReader();
         }
+    });
+    // Return dummy response
+    return new Promise((resolve, reject) => {
+        resolve(new Response(new ReadableStream()))
+    });
+}
+window._last_message = "";
+"""
+            driver.execute_script(script)
 
-        req_rand = random.randint(100000000, 9999999999)
+            # Submit prompt
+            wait.until(EC.visibility_of_element_located((By.ID, "textareaAutosize")))
+            driver.find_element(By.ID, "textareaAutosize").send_keys(prompt)
+            driver.find_element(By.ID, "textareaAutosize").send_keys(Keys.ENTER)
 
-        json_data: dict[str, Any] = {
-            "text"      : format_prompt(messages),
-            "category"  : "04f58f64a4aa4191a957b47290fee864",
-            "model"     : "ee8d4f29cb7047f78cbe84313ed6ace8",
-            "model_params": {
-                "system_prompt"     : "You are ChatGPT, a large language model trained by OpenAI, based on the GPT-3.5 architecture.\nKnowledge cutoff: 2021-09\nCurrent date: {{YYYY-MM-DD}}",
-                "temperature"       : kwargs.get("temperature", 1),
-                "top_p"             : kwargs.get("top_p", 1),
-                "frequency_penalty" : kwargs.get("frequency_penalty", 0),
-                "presence_penalty"  : kwargs.get("presence_penalty", 0),
-                "long_term_memory"  : "auto"
-            }
+            # Read response with reader
+            script = """
+if(window._reader) {
+    chunk = await window._reader.read();
+    if (chunk['done']) {
+        return null;
+    }
+    text = (new TextDecoder()).decode(chunk['value']);
+    message = '';
+    text.split('\\r\\n').forEach((line, index) => {
+        if (line.startsWith('data: ')) {
+            try {
+                line = JSON.parse(line.substring('data: '.length));
+                message = line["args"]["content"];
+            } catch(e) { }
         }
-
-        response = requests.post(
-            f"https://beta.theb.ai/api/conversation?org_id={org_id}&req_rand={req_rand}",
-            headers=headers,
-            json=json_data,
-            stream=True,
-            proxies={"https": proxy}
-        )
-
-        response.raise_for_status()
-        content = ""
-        next_content = ""
-        for chunk in response.iter_lines():
-            if b"content" in chunk:
-                next_content = content
-                data = json.loads(chunk.decode().split("data: ")[1])
-                content = data["content"]
-                yield content.replace(next_content, "")
-
-    @classmethod
-    @property
-    def params(cls):
-        params = [
-            ("model", "str"),
-            ("messages", "list[dict[str, str]]"),
-            ("auth", "list[dict[str, str]]"),
-            ("stream", "bool"),
-            ("temperature", "float"),
-            ("presence_penalty", "int"),
-            ("frequency_penalty", "int"),
-            ("top_p", "int")
-        ]
-        param = ", ".join([": ".join(p) for p in params])
-        return f"g4f.provider.{cls.__name__} supports: ({param})"
+    });
+    if (message) {
+        try {
+            return message.substring(window._last_message.length);
+        } finally {
+            window._last_message = message;
+        }
+    }
+}
+return '';
+"""
+            while True:
+                chunk = driver.execute_script(script)
+                if chunk:
+                    yield chunk
+                elif chunk != "":
+                    break
+                else:
+                    time.sleep(0.1)
+        finally:
+            if not browser:
+                driver.close()
+                time.sleep(0.1)
+                driver.quit()

g4f/Provider/needs_auth/ThebApi.py

@@ -0,0 +1,77 @@
+from __future__ import annotations
+
+import requests
+
+from ...typing import Any, CreateResult, Messages
+from ..base_provider import BaseProvider
+
+models = {
+    "theb-ai": "TheB.AI",
+    "gpt-3.5-turbo": "GPT-3.5",
+    "gpt-3.5-turbo-16k": "GPT-3.5-16K",
+    "gpt-4-turbo": "GPT-4 Turbo",
+    "gpt-4": "GPT-4",
+    "gpt-4-32k": "GPT-4 32K",
+    "claude-2": "Claude 2",
+    "claude-1": "Claude",
+    "claude-1-100k": "Claude 100K",
+    "claude-instant-1": "Claude Instant",
+    "claude-instant-1-100k": "Claude Instant 100K",
+    "palm-2": "PaLM 2",
+    "palm-2-codey": "Codey",
+    "vicuna-13b-v1.5": "Vicuna v1.5 13B",
+    "llama-2-7b-chat": "Llama 2 7B",
+    "llama-2-13b-chat": "Llama 2 13B",
+    "llama-2-70b-chat": "Llama 2 70B",
+    "code-llama-7b": "Code Llama 7B",
+    "code-llama-13b": "Code Llama 13B",
+    "code-llama-34b": "Code Llama 34B",
+    "qwen-7b-chat": "Qwen 7B"
+}
+
+class ThebApi(BaseProvider):
+    url = "https://theb.ai"
+    working = True
+    needs_auth = True
+
+    @staticmethod
+    def create_completion(
+        model: str,
+        messages: Messages,
+        stream: bool,
+        auth: str,
+        proxy: str = None,
+        **kwargs
+    ) -> CreateResult:
+        if model and model not in models:
+            raise ValueError(f"Model are not supported: {model}")
+        headers = {
+            'accept': 'application/json',
+            'authorization': f'Bearer {auth}',
+            'content-type': 'application/json',
+        }
+        # response = requests.get("https://api.baizhi.ai/v1/models", headers=headers).json()["data"]
+        # models = dict([(m["id"], m["name"]) for m in response])
+        # print(json.dumps(models, indent=4))
+        data: dict[str, Any] = {
+            "model": model if model else "gpt-3.5-turbo",
+            "messages": messages,
+            "stream": False,
+            "model_params": {
+                "system_prompt": kwargs.get("system_message", "You are ChatGPT, a large language model trained by OpenAI, based on the GPT-3.5 architecture."),
+                "temperature": 1,
+                "top_p": 1,
+                **kwargs
+            }
+        }
+        response = requests.post(
+            "https://api.theb.ai/v1/chat/completions",
+            headers=headers,
+            json=data,
+            proxies={"https": proxy}
+        )
+        try:
+            response.raise_for_status()
+            yield response.json()["choices"][0]["message"]["content"]
+        except:
+            raise RuntimeError(f"Response: {next(response.iter_lines()).decode()}")

g4f/Provider/needs_auth/__init__.py

@@ -1,6 +1,7 @@
 from .Bard          import Bard
 from .Raycast       import Raycast
 from .Theb          import Theb
+from .ThebApi       import ThebApi
 from .HuggingChat   import HuggingChat
 from .OpenaiChat    import OpenaiChat
 from .OpenAssistant import OpenAssistant