Merge pull request #1565 from hlohaus/gemini

Fix OpenaiChat provider, Fix issue with curl_cffi

README.md

@@ -358,6 +358,21 @@ response = g4f.ChatCompletion.create(
 
 # Displaying the response
 print(response)
+
+from g4f.image import ImageResponse
+
+# Get image links from response
+for chunk in g4f.ChatCompletion.create(
+    model=g4f.models.default, # Using the default model
+    provider=g4f.Provider.OpenaiChat, # Specifying the provider as OpenaiChat
+    messages=[{"role": "user", "content": "Create images with dogs"}],
+    access_token="...", # Need a access token from a plus user
+    stream=True,
+    ignore_stream=True
+):
+    if isinstance(chunk, ImageResponse):
+        print(chunk.images) # Print generated image links
+        print(chunk.alt) # Print used prompt for image generation
 ```
 
 ##### Using Browser

g4f/Provider/Phind.py

@@ -1,5 +1,6 @@
 from __future__ import annotations
 
+from urllib import parse
 from datetime import datetime
 
 from ..typing import AsyncResult, Messages
@@ -55,9 +56,9 @@ class Phind(AsyncGeneratorProvider):
                     "customLinks": []
                 },
                 "context": "\n".join([message["content"] for message in messages if message["role"] == "system"]),
-                "rewrittenQuestion": prompt,
-                "challenge": 0.21132115912208504
             }
+            data["challenge"] = generate_challenge(data)
+            
             async with session.post(f"https://https.api.phind.com/infer/", headers=headers, json=data) as response:
                 new_line = False
                 async for line in response.iter_lines():
@@ -65,6 +66,8 @@ class Phind(AsyncGeneratorProvider):
                         chunk = line[6:]
                         if chunk.startswith(b'<PHIND_DONE/>'):
                             break
+                        if chunk.startswith(b'<PHIND_BACKEND_ERROR>'):
+                            raise RuntimeError(f"Response: {chunk}")
                         if chunk.startswith(b'<PHIND_WEBRESULTS>') or chunk.startswith(b'<PHIND_FOLLOWUP>'):
                             pass
                         elif chunk.startswith(b"<PHIND_METADATA>") or chunk.startswith(b"<PHIND_INDICATOR>"):
@@ -78,3 +81,46 @@ class Phind(AsyncGeneratorProvider):
                             new_line = False
                         else:
                             new_line = True
+
+def deterministic_stringify(obj):
+    def handle_value(value):
+        if isinstance(value, (dict, list)):
+            if isinstance(value, list):
+                return '[' + ','.join(sorted(map(handle_value, value))) + ']'
+            else:  # It's a dict
+                return '{' + deterministic_stringify(value) + '}'
+        elif isinstance(value, bool):
+            return 'true' if value else 'false'
+        elif isinstance(value, (int, float)):
+            return format(value, '.8f').rstrip('0').rstrip('.')
+        elif isinstance(value, str):
+            return f'"{value}"'
+        else:
+            return 'null'
+
+    items = sorted(obj.items(), key=lambda x: x[0])
+    return ','.join([f'{k}:{handle_value(v)}' for k, v in items if handle_value(v) is not None])
+
+def simple_hash(s):
+    d = 0
+    for char in s:
+        if len(char) > 1 or ord(char) >= 256:
+            continue
+        d = ((d << 5) - d + ord(char[0])) & 0xFFFFFFFF
+        if d > 0x7FFFFFFF: # 2147483647
+            d -= 0x100000000 # Subtract 2**32
+    return d
+
+def generate_challenge(obj):
+    deterministic_str = deterministic_stringify(obj)
+    encoded_str = parse.quote(deterministic_str, safe='')
+
+    c = simple_hash(encoded_str)
+    a = (9301 * c + 49297)
+    b = 233280
+
+    # If negativ, we need a special logic
+    if a < 0:
+        return ((a%b)-b)/b
+    else:
+        return a%b/b

g4f/Provider/needs_auth/OpenaiChat.py

@@ -342,26 +342,30 @@ class OpenaiChat(AsyncGeneratorProvider, ProviderModelMixin):
                 raise MissingAuthError(f'Missing "access_token"')
             cls._cookies = cookies
 
-        headers = {"Authorization": f"Bearer {access_token}"}
+        auth_headers = {"Authorization": f"Bearer {access_token}"}
         async with StreamSession(
             proxies={"https": proxy},
             impersonate="chrome110",
             timeout=timeout,
-            cookies=dict([(name, value) for name, value in cookies.items() if name == "_puid"])
+            headers={"Cookie": "; ".join(f"{k}={v}" for k, v in cookies.items())}
         ) as session:
             try:
                 image_response = None
                 if image:
-                    image_response = await cls.upload_image(session, headers, image, kwargs.get("image_name"))
+                    image_response = await cls.upload_image(session, auth_headers, image, kwargs.get("image_name"))
             except Exception as e:
                 yield e
             end_turn = EndTurn()
-            model = cls.get_model(model or await cls.get_default_model(session, headers))
+            model = cls.get_model(model or await cls.get_default_model(session, auth_headers))
             model = "text-davinci-002-render-sha" if model == "gpt-3.5-turbo" else model
             while not end_turn.is_end:
+                arkose_token = await cls.get_arkose_token(session)
                 data = {
                     "action": action,
-                    "arkose_token": await cls.get_arkose_token(session),
+                    "arkose_token": arkose_token,
+                    "conversation_mode": {"kind": "primary_assistant"},
+                    "force_paragen": False,
+                    "force_rate_limit": False,
                     "conversation_id": conversation_id,
                     "parent_message_id": parent_id,
                     "model": model,
@@ -373,7 +377,11 @@ class OpenaiChat(AsyncGeneratorProvider, ProviderModelMixin):
                 async with session.post(
                     f"{cls.url}/backend-api/conversation",
                     json=data,
-                    headers={"Accept": "text/event-stream", **headers}
+                    headers={
+                        "Accept": "text/event-stream",
+                        "OpenAI-Sentinel-Arkose-Token": arkose_token,
+                        **auth_headers
+                    }
                 ) as response:
                     if not response.ok:
                         raise RuntimeError(f"Response {response.status_code}: {await response.text()}")
@@ -439,7 +447,8 @@ class OpenaiChat(AsyncGeneratorProvider, ProviderModelMixin):
         Returns:
             tuple[str, dict]: A tuple containing the access token and cookies.
         """
-        with get_browser(proxy=proxy) as driver:
+        driver = get_browser(proxy=proxy)
+        try:
             driver.get(f"{cls.url}/")
             WebDriverWait(driver, timeout).until(EC.presence_of_element_located((By.ID, "prompt-textarea")))
             access_token = driver.execute_script(
@@ -451,6 +460,8 @@ class OpenaiChat(AsyncGeneratorProvider, ProviderModelMixin):
                 "return accessToken;"
             )
             return access_token, get_driver_cookies(driver)
+        finally:
+            driver.close() 
 
     @classmethod
     async def get_arkose_token(cls, session: StreamSession) -> str:

g4f/models.py

@@ -89,7 +89,7 @@ gpt_4 = Model(
     name          = 'gpt-4',
     base_provider = 'openai',
     best_provider = RetryProvider([
-        Bing, Phind, Liaobots, 
+        Bing, Liaobots, 
     ])
 )
 

setup.py

@@ -15,7 +15,7 @@ INSTALL_REQUIRE = [
 
 EXTRA_REQUIRE = {
     'all': [
-        "curl_cffi>=0.5.10",
+        "curl_cffi>=0.6.0b9",
         "certifi",
         "async-property",          # openai
         "py-arkose-generator",     # openai