mirror of
https://github.com/xtekky/gpt4free.git
synced 2024-11-26 21:21:21 +03:00
Add async support for H2o
Add format_prompt helper Fix create_completion in AsyncGeneratorProvider Move get_cookies from constructor to function Add ow HuggingChat implement Remove need auth form Liabots Add staic cache for access_token in OpenaiChat Add OpenAssistant provider Support stream and async in You Support async and add userId in Yqcloud Add log_time module
This commit is contained in:
Heiner Lohaus
parent
efd75a11b8
commit
7294abc890
@ -1,12 +1,9 @@
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import json
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import random
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import re
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from aiohttp import ClientSession
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import asyncio
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from ..typing import Any, CreateResult
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from .base_provider import AsyncProvider, get_cookies
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from .base_provider import AsyncProvider, get_cookies, format_prompt
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class Bard(AsyncProvider):
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url = "https://bard.google.com"
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@ -19,15 +16,14 @@ class Bard(AsyncProvider):
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model: str,
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messages: list[dict[str, str]],
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proxy: str = None,
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cookies: dict = get_cookies(".google.com"), **kwargs: Any,) -> str:
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formatted = "\n".join(
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["%s: %s" % (message["role"], message["content"]) for message in messages]
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)
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prompt = f"{formatted}\nAssistant:"
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cookies: dict = None,
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**kwargs
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) -> str:
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prompt = format_prompt(messages)
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if proxy and "://" not in proxy:
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proxy = f"http://{proxy}"
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if not cookies:
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cookies = get_cookies(".google.com")
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headers = {
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'authority': 'bard.google.com',
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@ -44,10 +40,11 @@ class Bard(AsyncProvider):
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) as session:
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async with session.get(cls.url, proxy=proxy) as response:
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text = await response.text()
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match = re.search(r'SNlM0e\":\"(.*?)\"', text)
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if match:
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snlm0e = match.group(1)
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if not match:
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raise RuntimeError("No snlm0e value.")
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snlm0e = match.group(1)
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params = {
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'bl': 'boq_assistant-bard-web-server_20230326.21_p0',
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@ -15,8 +15,11 @@ class Bing(AsyncGeneratorProvider):
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def create_async_generator(
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model: str,
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messages: list[dict[str, str]],
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cookies: dict = get_cookies(".bing.com"), **kwargs) -> AsyncGenerator:
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cookies: dict = None,
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**kwargs
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) -> AsyncGenerator:
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if not cookies:
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cookies = get_cookies(".bing.com")
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if len(messages) < 2:
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prompt = messages[0]["content"]
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context = None
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@ -273,15 +276,4 @@ async def stream_generate(
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final = True
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break
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finally:
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await delete_conversation(session, conversation)
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def run(generator: AsyncGenerator[Union[Any, str], Any]):
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loop = asyncio.get_event_loop()
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gen = generator.__aiter__()
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while True:
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try:
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yield loop.run_until_complete(gen.__anext__())
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except StopAsyncIteration:
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break
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await delete_conversation(session, conversation)
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@ -1,78 +1,85 @@
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import json, uuid, requests
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import json
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import uuid
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from aiohttp import ClientSession
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from ..typing import Any, CreateResult
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from .base_provider import BaseProvider
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from ..typing import AsyncGenerator
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from .base_provider import AsyncGeneratorProvider, format_prompt
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class H2o(BaseProvider):
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url = "https://gpt-gm.h2o.ai"
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working = True
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class H2o(AsyncGeneratorProvider):
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url = "https://gpt-gm.h2o.ai"
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working = True
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supports_stream = True
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model = "h2oai/h2ogpt-gm-oasst1-en-2048-falcon-40b-v1"
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@staticmethod
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def create_completion(
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@classmethod
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async def create_async_generator(
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cls,
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model: str,
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messages: list[dict[str, str]],
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stream: bool, **kwargs: Any) -> CreateResult:
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conversation = ""
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for message in messages:
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conversation += "%s: %s\n" % (message["role"], message["content"])
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conversation += "assistant: "
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session = requests.Session()
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headers = {"Referer": "https://gpt-gm.h2o.ai/r/jGfKSwU"}
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data = {
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"ethicsModalAccepted" : "true",
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"shareConversationsWithModelAuthors": "true",
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"ethicsModalAcceptedAt" : "",
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"activeModel" : model,
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"searchEnabled" : "true",
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}
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session.post("https://gpt-gm.h2o.ai/settings",
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headers=headers, data=data)
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proxy: str = None,
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**kwargs
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) -> AsyncGenerator:
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model = model if model else cls.model
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headers = {"Referer": "https://gpt-gm.h2o.ai/"}
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data = {"model": model}
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response = session.post("https://gpt-gm.h2o.ai/conversation",
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headers=headers, json=data).json()
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if "conversationId" not in response:
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return
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async with ClientSession(
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headers=headers
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) as session:
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data = {
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"ethicsModalAccepted": "true",
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"shareConversationsWithModelAuthors": "true",
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"ethicsModalAcceptedAt": "",
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"activeModel": model,
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"searchEnabled": "true",
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}
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async with session.post(
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"https://gpt-gm.h2o.ai/settings",
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proxy=proxy,
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data=data
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) as response:
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response.raise_for_status()
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data = {
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"inputs": conversation,
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"parameters": {
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"temperature" : kwargs.get("temperature", 0.4),
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"truncate" : kwargs.get("truncate", 2048),
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"max_new_tokens" : kwargs.get("max_new_tokens", 1024),
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"do_sample" : kwargs.get("do_sample", True),
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"repetition_penalty": kwargs.get("repetition_penalty", 1.2),
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"return_full_text" : kwargs.get("return_full_text", False),
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},
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"stream" : True,
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"options": {
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"id" : kwargs.get("id", str(uuid.uuid4())),
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"response_id" : kwargs.get("response_id", str(uuid.uuid4())),
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"is_retry" : False,
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"use_cache" : False,
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"web_search_id": "",
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},
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}
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async with session.post(
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"https://gpt-gm.h2o.ai/conversation",
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proxy=proxy,
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json={"model": model},
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) as response:
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response.raise_for_status()
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conversationId = (await response.json())["conversationId"]
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response = session.post(f"https://gpt-gm.h2o.ai/conversation/{response['conversationId']}",
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headers=headers, json=data)
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response.raise_for_status()
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response.encoding = "utf-8"
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generated_text = response.text.replace("\n", "").split("data:")
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generated_text = json.loads(generated_text[-1])
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yield generated_text["generated_text"]
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data = {
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"inputs": format_prompt(messages),
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"parameters": {
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"temperature": 0.4,
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"truncate": 2048,
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"max_new_tokens": 1024,
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"do_sample": True,
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"repetition_penalty": 1.2,
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"return_full_text": False,
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**kwargs
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},
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"stream": True,
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"options": {
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"id": str(uuid.uuid4()),
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"response_id": str(uuid.uuid4()),
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"is_retry": False,
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"use_cache": False,
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"web_search_id": "",
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},
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}
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async with session.post(
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f"https://gpt-gm.h2o.ai/conversation/{conversationId}",
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proxy=proxy,
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json=data
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) as response:
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start = "data:"
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async for line in response.content:
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line = line.decode("utf-8")
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if line and line.startswith(start):
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line = json.loads(line[len(start):-1])
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if not line["token"]["special"]:
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yield line["token"]["text"]
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@classmethod
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@property
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@ -1,65 +0,0 @@
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has_module = False
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try:
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from hugchat.hugchat import ChatBot
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except ImportError:
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has_module = False
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from .base_provider import BaseProvider, get_cookies
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from g4f.typing import CreateResult
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class Hugchat(BaseProvider):
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url = "https://huggingface.co/chat/"
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needs_auth = True
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working = has_module
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llms = ['OpenAssistant/oasst-sft-6-llama-30b-xor', 'meta-llama/Llama-2-70b-chat-hf']
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@classmethod
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def create_completion(
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cls,
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model: str,
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messages: list[dict[str, str]],
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stream: bool = False,
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proxy: str = None,
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cookies: str = get_cookies(".huggingface.co"), **kwargs) -> CreateResult:
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bot = ChatBot(
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cookies=cookies)
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if proxy and "://" not in proxy:
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proxy = f"http://{proxy}"
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bot.session.proxies = {"http": proxy, "https": proxy}
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if model:
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try:
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if not isinstance(model, int):
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model = cls.llms.index(model)
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bot.switch_llm(model)
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except:
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raise RuntimeError(f"Model are not supported: {model}")
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if len(messages) > 1:
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formatted = "\n".join(
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["%s: %s" % (message["role"], message["content"]) for message in messages]
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)
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prompt = f"{formatted}\nAssistant:"
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else:
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prompt = messages.pop()["content"]
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try:
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yield bot.chat(prompt, **kwargs)
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finally:
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bot.delete_conversation(bot.current_conversation)
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bot.current_conversation = ""
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pass
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@classmethod
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@property
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def params(cls):
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params = [
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("model", "str"),
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("messages", "list[dict[str, str]]"),
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("stream", "bool"),
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("proxy", "str"),
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]
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param = ", ".join([": ".join(p) for p in params])
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return f"g4f.provider.{cls.__name__} supports: ({param})"
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107
g4f/Provider/HuggingChat.py
Normal file
107
g4f/Provider/HuggingChat.py
Normal file
@ -0,0 +1,107 @@
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import json
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from aiohttp import ClientSession
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from ..typing import AsyncGenerator
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from .base_provider import AsyncGeneratorProvider, get_cookies, format_prompt
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class HuggingChat(AsyncGeneratorProvider):
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url = "https://huggingface.co/chat/"
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needs_auth = True
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working = True
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model = "OpenAssistant/oasst-sft-6-llama-30b-xor"
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@classmethod
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async def create_async_generator(
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cls,
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model: str,
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messages: list[dict[str, str]],
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stream: bool = True,
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proxy: str = None,
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cookies: dict = None,
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**kwargs
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) -> AsyncGenerator:
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if not cookies:
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cookies = get_cookies(".huggingface.co")
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model = model if model else cls.model
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if proxy and "://" not in proxy:
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proxy = f"http://{proxy}"
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headers = {
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'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',
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}
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async with ClientSession(
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cookies=cookies,
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headers=headers
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) as session:
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async with session.post("https://huggingface.co/chat/conversation", proxy=proxy, json={"model": model}) as response:
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conversation_id = (await response.json())["conversationId"]
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send = {
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"inputs": format_prompt(messages),
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"parameters": {
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"temperature": 0.2,
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"truncate": 1000,
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"max_new_tokens": 1024,
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"stop": ["</s>"],
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"top_p": 0.95,
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"repetition_penalty": 1.2,
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"top_k": 50,
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"return_full_text": False,
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**kwargs
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},
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"stream": stream,
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"options": {
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"id": "9e9b8bc4-6604-40c6-994e-8eb78fa32e37",
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"response_id": "04ce2602-3bea-45e8-8efc-cef00680376a",
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"is_retry": False,
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"use_cache": False,
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"web_search_id": ""
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}
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}
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start = "data:"
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first = True
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async with session.post(f"https://huggingface.co/chat/conversation/{conversation_id}", proxy=proxy, json=send) as response:
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async for line in response.content:
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line = line.decode("utf-8")
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if not line:
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continue
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if not stream:
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try:
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data = json.loads(line)
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except json.decoder.JSONDecodeError:
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raise RuntimeError(f"No json: {line}")
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if "error" in data:
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raise RuntimeError(data["error"])
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elif isinstance(data, list):
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yield data[0]["generated_text"]
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else:
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raise RuntimeError(f"Response: {line}")
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elif line.startswith(start):
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line = json.loads(line[len(start):-1])
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if not line:
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continue
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if "token" not in line:
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raise RuntimeError(f"Response: {line}")
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if not line["token"]["special"]:
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if first:
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yield line["token"]["text"].lstrip()
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first = False
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else:
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yield line["token"]["text"]
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async with session.delete(f"https://huggingface.co/chat/conversation/{conversation_id}", proxy=proxy) as response:
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response.raise_for_status()
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@classmethod
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@property
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def params(cls):
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params = [
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("model", "str"),
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("messages", "list[dict[str, str]]"),
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("stream", "bool"),
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("proxy", "str"),
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]
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param = ", ".join([": ".join(p) for p in params])
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return f"g4f.provider.{cls.__name__} supports: ({param})"
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@ -1,59 +1,77 @@
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import uuid, requests
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import uuid
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import json
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from aiohttp import ClientSession
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from ..typing import Any, CreateResult
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from .base_provider import BaseProvider
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from ..typing import AsyncGenerator
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from .base_provider import AsyncGeneratorProvider
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models = {
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"gpt-4": {
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"id": "gpt-4",
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"name": "GPT-4",
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"maxLength": 24000,
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"tokenLimit": 8000,
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},
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"gpt-3.5-turbo": {
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"id": "gpt-3.5-turbo",
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"name": "GPT-3.5",
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"maxLength": 12000,
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"tokenLimit": 4000,
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},
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"gpt-3.5-turbo-16k": {
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"id": "gpt-3.5-turbo-16k",
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"name": "GPT-3.5-16k",
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"maxLength": 48000,
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"tokenLimit": 16000,
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},
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}
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class Liaobots(BaseProvider):
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url: str = "https://liaobots.com"
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supports_stream = True
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needs_auth = True
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supports_gpt_35_turbo = True
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supports_gpt_4 = True
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class Liaobots(AsyncGeneratorProvider):
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url = "https://liaobots.com"
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supports_stream = True
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supports_gpt_35_turbo = True
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supports_gpt_4 = True
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_auth_code = None
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@staticmethod
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def create_completion(
|
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@classmethod
|
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async def create_async_generator(
|
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cls,
|
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model: str,
|
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messages: list[dict[str, str]],
|
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stream: bool, **kwargs: Any) -> CreateResult:
|
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|
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auth: str = None,
|
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proxy: str = None,
|
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**kwargs
|
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) -> AsyncGenerator:
|
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if proxy and "://" not in proxy:
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proxy = f"http://{proxy}"
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headers = {
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"authority" : "liaobots.com",
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"content-type" : "application/json",
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"origin" : "https://liaobots.com",
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"referer" : "https://liaobots.com/",
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"user-agent" : "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/112.0.0.0 Safari/537.36",
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"x-auth-code" : str(kwargs.get("auth")),
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}
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models = {
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"gpt-4": {
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"id": "gpt-4",
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"name": "GPT-4",
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"maxLength": 24000,
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"tokenLimit": 8000,
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},
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"gpt-3.5-turbo": {
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"id": "gpt-3.5-turbo",
|
||||
"name": "GPT-3.5",
|
||||
"maxLength": 12000,
|
||||
"tokenLimit": 4000,
|
||||
},
|
||||
}
|
||||
json_data = {
|
||||
"conversationId": str(uuid.uuid4()),
|
||||
"model" : models[model],
|
||||
"messages" : messages,
|
||||
"key" : "",
|
||||
"prompt" : "You are ChatGPT, a large language model trained by OpenAI. Follow the user's instructions carefully. Respond using markdown.",
|
||||
"authority": "liaobots.com",
|
||||
"content-type": "application/json",
|
||||
"origin": "https://liaobots.com",
|
||||
"referer": "https://liaobots.com/",
|
||||
"user-agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/112.0.0.0 Safari/537.36",
|
||||
}
|
||||
async with ClientSession(
|
||||
headers=headers
|
||||
) as session:
|
||||
model = model if model in models else "gpt-3.5-turbo"
|
||||
auth_code = auth if isinstance(auth, str) else cls._auth_code
|
||||
if not auth_code:
|
||||
async with session.post("https://liaobots.com/api/user", proxy=proxy, json={"authcode": ""}) as response:
|
||||
response.raise_for_status()
|
||||
auth_code = cls._auth_code = json.loads((await response.text()))["authCode"]
|
||||
data = {
|
||||
"conversationId": str(uuid.uuid4()),
|
||||
"model": models[model],
|
||||
"messages": messages,
|
||||
"key": "",
|
||||
"prompt": "You are ChatGPT, a large language model trained by OpenAI. Follow the user's instructions carefully.",
|
||||
}
|
||||
async with session.post("https://liaobots.com/api/chat", proxy=proxy, json=data, headers={"x-auth-code": auth_code}) as response:
|
||||
response.raise_for_status()
|
||||
async for line in response.content:
|
||||
yield line.decode("utf-8")
|
||||
|
||||
response = requests.post("https://liaobots.com/api/chat",
|
||||
headers=headers, json=json_data, stream=True)
|
||||
|
||||
response.raise_for_status()
|
||||
for token in response.iter_content(chunk_size=2046):
|
||||
yield token.decode("utf-8")
|
||||
|
||||
@classmethod
|
||||
@property
|
||||
@ -62,6 +80,7 @@ class Liaobots(BaseProvider):
|
||||
("model", "str"),
|
||||
("messages", "list[dict[str, str]]"),
|
||||
("stream", "bool"),
|
||||
("proxy", "str"),
|
||||
("auth", "str"),
|
||||
]
|
||||
param = ", ".join([": ".join(p) for p in params])
|
||||
|
||||
98
g4f/Provider/OpenAssistant.py
Normal file
98
g4f/Provider/OpenAssistant.py
Normal file
@ -0,0 +1,98 @@
|
||||
import json
|
||||
from aiohttp import ClientSession
|
||||
|
||||
from ..typing import Any, AsyncGenerator
|
||||
from .base_provider import AsyncGeneratorProvider, get_cookies, format_prompt
|
||||
|
||||
class OpenAssistant(AsyncGeneratorProvider):
|
||||
url = "https://open-assistant.io/chat"
|
||||
needs_auth = True
|
||||
working = True
|
||||
model = "OA_SFT_Llama_30B_6"
|
||||
|
||||
@classmethod
|
||||
async def create_async_generator(
|
||||
cls,
|
||||
model: str,
|
||||
messages: list[dict[str, str]],
|
||||
proxy: str = None,
|
||||
cookies: dict = None,
|
||||
**kwargs: Any
|
||||
) -> AsyncGenerator:
|
||||
if proxy and "://" not in proxy:
|
||||
proxy = f"http://{proxy}"
|
||||
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()
|
||||
|
||||
@classmethod
|
||||
@property
|
||||
def params(cls):
|
||||
params = [
|
||||
("model", "str"),
|
||||
("messages", "list[dict[str, str]]"),
|
||||
("stream", "bool"),
|
||||
("proxy", "str"),
|
||||
]
|
||||
param = ", ".join([": ".join(p) for p in params])
|
||||
return f"g4f.provider.{cls.__name__} supports: ({param})"
|
||||
@ -4,8 +4,11 @@ try:
|
||||
except ImportError:
|
||||
has_module = False
|
||||
|
||||
from .base_provider import AsyncGeneratorProvider, get_cookies
|
||||
from ..typing import AsyncGenerator
|
||||
from .base_provider import AsyncGeneratorProvider, get_cookies, format_prompt
|
||||
from ..typing import AsyncGenerator
|
||||
from httpx import AsyncClient
|
||||
import json
|
||||
|
||||
|
||||
class OpenaiChat(AsyncGeneratorProvider):
|
||||
url = "https://chat.openai.com"
|
||||
@ -14,6 +17,7 @@ class OpenaiChat(AsyncGeneratorProvider):
|
||||
supports_gpt_35_turbo = True
|
||||
supports_gpt_4 = True
|
||||
supports_stream = True
|
||||
_access_token = None
|
||||
|
||||
@classmethod
|
||||
async def create_async_generator(
|
||||
@ -21,9 +25,9 @@ class OpenaiChat(AsyncGeneratorProvider):
|
||||
model: str,
|
||||
messages: list[dict[str, str]],
|
||||
proxy: str = None,
|
||||
access_token: str = None,
|
||||
access_token: str = _access_token,
|
||||
cookies: dict = None,
|
||||
**kwargs
|
||||
**kwargs: dict
|
||||
) -> AsyncGenerator:
|
||||
|
||||
config = {"access_token": access_token, "model": model}
|
||||
@ -37,21 +41,12 @@ class OpenaiChat(AsyncGeneratorProvider):
|
||||
)
|
||||
|
||||
if not access_token:
|
||||
cookies = cookies if cookies else get_cookies("chat.openai.com")
|
||||
response = await bot.session.get("https://chat.openai.com/api/auth/session", cookies=cookies)
|
||||
access_token = response.json()["accessToken"]
|
||||
bot.set_access_token(access_token)
|
||||
|
||||
if len(messages) > 1:
|
||||
formatted = "\n".join(
|
||||
["%s: %s" % ((message["role"]).capitalize(), message["content"]) for message in messages]
|
||||
)
|
||||
prompt = f"{formatted}\nAssistant:"
|
||||
else:
|
||||
prompt = messages.pop()["content"]
|
||||
cookies = cookies if cookies else get_cookies("chat.openai.com")
|
||||
cls._access_token = await get_access_token(bot.session, cookies)
|
||||
bot.set_access_token(cls._access_token)
|
||||
|
||||
returned = None
|
||||
async for message in bot.ask(prompt):
|
||||
async for message in bot.ask(format_prompt(messages)):
|
||||
message = message["message"]
|
||||
if returned:
|
||||
if message.startswith(returned):
|
||||
@ -61,6 +56,9 @@ class OpenaiChat(AsyncGeneratorProvider):
|
||||
else:
|
||||
yield message
|
||||
returned = message
|
||||
|
||||
await bot.delete_conversation(bot.conversation_id)
|
||||
|
||||
|
||||
@classmethod
|
||||
@property
|
||||
@ -73,3 +71,12 @@ class OpenaiChat(AsyncGeneratorProvider):
|
||||
]
|
||||
param = ", ".join([": ".join(p) for p in params])
|
||||
return f"g4f.provider.{cls.__name__} supports: ({param})"
|
||||
|
||||
|
||||
async def get_access_token(session: AsyncClient, cookies: dict):
|
||||
response = await session.get("https://chat.openai.com/api/auth/session", cookies=cookies)
|
||||
response.raise_for_status()
|
||||
try:
|
||||
return response.json()["accessToken"]
|
||||
except json.decoder.JSONDecodeError:
|
||||
raise RuntimeError(f"Response: {response.text}")
|
||||
@ -1,55 +1,37 @@
|
||||
import urllib.parse, json
|
||||
from aiohttp import ClientSession
|
||||
import json
|
||||
|
||||
from curl_cffi import requests
|
||||
from ..typing import Any, CreateResult
|
||||
from .base_provider import BaseProvider
|
||||
from ..typing import AsyncGenerator
|
||||
from .base_provider import AsyncGeneratorProvider, format_prompt, get_cookies
|
||||
|
||||
|
||||
class You(BaseProvider):
|
||||
url = "https://you.com"
|
||||
working = True
|
||||
class You(AsyncGeneratorProvider):
|
||||
url = "https://you.com"
|
||||
working = True
|
||||
supports_gpt_35_turbo = True
|
||||
supports_stream = True
|
||||
|
||||
@staticmethod
|
||||
def create_completion(
|
||||
async def create_async_generator(
|
||||
model: str,
|
||||
messages: list[dict[str, str]],
|
||||
stream: bool, **kwargs: Any) -> CreateResult:
|
||||
|
||||
url_param = _create_url_param(messages, kwargs.get("history", []))
|
||||
headers = _create_header()
|
||||
|
||||
response = requests.get(f"https://you.com/api/streamingSearch?{url_param}",
|
||||
headers=headers, impersonate="chrome107")
|
||||
|
||||
response.raise_for_status()
|
||||
|
||||
start = 'data: {"youChatToken": '
|
||||
for line in response.content.splitlines():
|
||||
line = line.decode('utf-8')
|
||||
if line.startswith(start):
|
||||
yield json.loads(line[len(start): -1])
|
||||
|
||||
def _create_url_param(messages: list[dict[str, str]], history: list[dict[str, str]]):
|
||||
prompt = ""
|
||||
for message in messages:
|
||||
prompt += "%s: %s\n" % (message["role"], message["content"])
|
||||
prompt += "assistant:"
|
||||
chat = _convert_chat(history)
|
||||
param = {"q": prompt, "domain": "youchat", "chat": chat}
|
||||
return urllib.parse.urlencode(param)
|
||||
|
||||
|
||||
def _convert_chat(messages: list[dict[str, str]]):
|
||||
message_iter = iter(messages)
|
||||
return [
|
||||
{"question": user["content"], "answer": assistant["content"]}
|
||||
for user, assistant in zip(message_iter, message_iter)
|
||||
]
|
||||
|
||||
|
||||
def _create_header():
|
||||
return {
|
||||
"accept": "text/event-stream",
|
||||
"referer": "https://you.com/search?fromSearchBar=true&tbm=youchat",
|
||||
}
|
||||
cookies: dict = None,
|
||||
**kwargs,
|
||||
) -> AsyncGenerator:
|
||||
if not cookies:
|
||||
cookies = get_cookies("you.com")
|
||||
headers = {
|
||||
"Accept": "text/event-stream",
|
||||
"Referer": "https://you.com/search?fromSearchBar=true&tbm=youchat",
|
||||
"User-Agent": "Mozilla/5.0 (X11; Ubuntu; Linux x86_64; rv:109.0) Gecko/20100101 Firefox/116.0"
|
||||
}
|
||||
async with ClientSession(headers=headers, cookies=cookies) as session:
|
||||
async with session.get(
|
||||
"https://you.com/api/streamingSearch",
|
||||
params={"q": format_prompt(messages), "domain": "youchat", "chat": ""},
|
||||
) as response:
|
||||
start = 'data: {"youChatToken": '
|
||||
async for line in response.content:
|
||||
line = line.decode('utf-8')
|
||||
if line.startswith(start):
|
||||
yield json.loads(line[len(start): -2])
|
||||
@ -1,29 +1,27 @@
|
||||
import requests
|
||||
from aiohttp import ClientSession
|
||||
|
||||
from ..typing import Any, CreateResult
|
||||
from .base_provider import BaseProvider
|
||||
from .base_provider import AsyncProvider, format_prompt
|
||||
|
||||
|
||||
class Yqcloud(BaseProvider):
|
||||
url = "https://chat9.yqcloud.top/"
|
||||
working = True
|
||||
supports_gpt_35_turbo = True
|
||||
class Yqcloud(AsyncProvider):
|
||||
url = "https://chat9.yqcloud.top/"
|
||||
working = True
|
||||
supports_gpt_35_turbo = True
|
||||
|
||||
@staticmethod
|
||||
def create_completion(
|
||||
async def create_async(
|
||||
model: str,
|
||||
messages: list[dict[str, str]],
|
||||
stream: bool, **kwargs: Any) -> CreateResult:
|
||||
|
||||
headers = _create_header()
|
||||
payload = _create_payload(messages)
|
||||
|
||||
response = requests.post("https://api.aichatos.cloud/api/generateStream",
|
||||
headers=headers, json=payload)
|
||||
|
||||
response.raise_for_status()
|
||||
response.encoding = 'utf-8'
|
||||
yield response.text
|
||||
proxy: str = None,
|
||||
**kwargs,
|
||||
) -> str:
|
||||
async with ClientSession(
|
||||
headers=_create_header()
|
||||
) as session:
|
||||
payload = _create_payload(messages)
|
||||
async with session.post("https://api.aichatos.cloud/api/generateStream", proxy=proxy, json=payload) as response:
|
||||
response.raise_for_status()
|
||||
return await response.text()
|
||||
|
||||
|
||||
def _create_header():
|
||||
@ -35,15 +33,11 @@ def _create_header():
|
||||
|
||||
|
||||
def _create_payload(messages: list[dict[str, str]]):
|
||||
prompt = ""
|
||||
for message in messages:
|
||||
prompt += "%s: %s\n" % (message["role"], message["content"])
|
||||
prompt += "assistant:"
|
||||
|
||||
return {
|
||||
"prompt" : prompt,
|
||||
"network" : True,
|
||||
"system" : "",
|
||||
"prompt": format_prompt(messages),
|
||||
"network": True,
|
||||
"system": "",
|
||||
"withoutContext": False,
|
||||
"stream" : False,
|
||||
}
|
||||
"stream": False,
|
||||
"userId": "#/chat/1693025544336"
|
||||
}
|
||||
|
||||
@ -13,11 +13,12 @@ from .EasyChat import EasyChat
|
||||
from .Forefront import Forefront
|
||||
from .GetGpt import GetGpt
|
||||
from .H2o import H2o
|
||||
from .Hugchat import Hugchat
|
||||
from .HuggingChat import HuggingChat
|
||||
from .Liaobots import Liaobots
|
||||
from .Lockchat import Lockchat
|
||||
from .Opchatgpts import Opchatgpts
|
||||
from .OpenaiChat import OpenaiChat
|
||||
from .OpenAssistant import OpenAssistant
|
||||
from .Raycast import Raycast
|
||||
from .Theb import Theb
|
||||
from .Vercel import Vercel
|
||||
@ -48,12 +49,13 @@ __all__ = [
|
||||
'Forefront',
|
||||
'GetGpt',
|
||||
'H2o',
|
||||
'Hugchat',
|
||||
'HuggingChat',
|
||||
'Liaobots',
|
||||
'Lockchat',
|
||||
'Opchatgpts',
|
||||
'Raycast',
|
||||
'OpenaiChat',
|
||||
'OpenAssistant',
|
||||
'Theb',
|
||||
'Vercel',
|
||||
'Wewordle',
|
||||
|
||||
@ -4,8 +4,7 @@ from ..typing import Any, CreateResult, AsyncGenerator, Union
|
||||
|
||||
import browser_cookie3
|
||||
import asyncio
|
||||
from time import time
|
||||
import math
|
||||
|
||||
|
||||
class BaseProvider(ABC):
|
||||
url: str
|
||||
@ -48,6 +47,17 @@ def get_cookies(cookie_domain: str) -> dict:
|
||||
return _cookies[cookie_domain]
|
||||
|
||||
|
||||
def format_prompt(messages: list[dict[str, str]], add_special_tokens=False):
|
||||
if add_special_tokens or len(messages) > 1:
|
||||
formatted = "\n".join(
|
||||
["%s: %s" % ((message["role"]).capitalize(), message["content"]) for message in messages]
|
||||
)
|
||||
return f"{formatted}\nAssistant:"
|
||||
else:
|
||||
return messages.pop()["content"]
|
||||
|
||||
|
||||
|
||||
class AsyncProvider(BaseProvider):
|
||||
@classmethod
|
||||
def create_completion(
|
||||
@ -72,20 +82,19 @@ class AsyncGeneratorProvider(AsyncProvider):
|
||||
cls,
|
||||
model: str,
|
||||
messages: list[dict[str, str]],
|
||||
stream: bool = True, **kwargs: Any) -> CreateResult:
|
||||
|
||||
if stream:
|
||||
yield from run_generator(cls.create_async_generator(model, messages, **kwargs))
|
||||
else:
|
||||
yield from AsyncProvider.create_completion(cls=cls, model=model, messages=messages, **kwargs)
|
||||
stream: bool = True,
|
||||
**kwargs
|
||||
) -> CreateResult:
|
||||
yield from run_generator(cls.create_async_generator(model, messages, stream=stream, **kwargs))
|
||||
|
||||
@classmethod
|
||||
async def create_async(
|
||||
cls,
|
||||
model: str,
|
||||
messages: list[dict[str, str]], **kwargs: Any) -> str:
|
||||
|
||||
chunks = [chunk async for chunk in cls.create_async_generator(model, messages, **kwargs)]
|
||||
messages: list[dict[str, str]],
|
||||
**kwargs
|
||||
) -> str:
|
||||
chunks = [chunk async for chunk in cls.create_async_generator(model, messages, stream=False, **kwargs)]
|
||||
if chunks:
|
||||
return "".join(chunks)
|
||||
|
||||
@ -93,8 +102,9 @@ class AsyncGeneratorProvider(AsyncProvider):
|
||||
@abstractmethod
|
||||
def create_async_generator(
|
||||
model: str,
|
||||
messages: list[dict[str, str]]) -> AsyncGenerator:
|
||||
|
||||
messages: list[dict[str, str]],
|
||||
**kwargs
|
||||
) -> AsyncGenerator:
|
||||
raise NotImplementedError()
|
||||
|
||||
|
||||
|
||||
@ -7,6 +7,13 @@ class Model:
|
||||
base_provider: str
|
||||
best_provider: type[BaseProvider]
|
||||
|
||||
# Config for HuggingChat, OpenAssistant
|
||||
# Works for Liaobots, H2o, OpenaiChat, Yqcloud, You
|
||||
default = Model(
|
||||
name="",
|
||||
base_provider="huggingface",
|
||||
best_provider=H2o,
|
||||
)
|
||||
|
||||
# GPT-3.5 / GPT-4
|
||||
gpt_35_turbo = Model(
|
||||
|
||||
25
testing/log_time.py
Normal file
25
testing/log_time.py
Normal file
@ -0,0 +1,25 @@
|
||||
from time import time
|
||||
|
||||
|
||||
async def log_time_async(method: callable, **kwargs):
|
||||
start = time()
|
||||
result = await method(**kwargs)
|
||||
secs = f"{round(time() - start, 2)} secs"
|
||||
if result:
|
||||
return " ".join([result, secs])
|
||||
return secs
|
||||
|
||||
|
||||
def log_time_yield(method: callable, **kwargs):
|
||||
start = time()
|
||||
result = yield from method(**kwargs)
|
||||
yield f" {round(time() - start, 2)} secs"
|
||||
|
||||
|
||||
def log_time(method: callable, **kwargs):
|
||||
start = time()
|
||||
result = method(**kwargs)
|
||||
secs = f"{round(time() - start, 2)} secs"
|
||||
if result:
|
||||
return " ".join([result, secs])
|
||||
return secs
|
||||
@ -1,83 +1,25 @@
|
||||
import sys
|
||||
from pathlib import Path
|
||||
import asyncio
|
||||
from time import time
|
||||
|
||||
sys.path.append(str(Path(__file__).parent.parent))
|
||||
|
||||
import g4f
|
||||
from testing.log_time import log_time, log_time_async, log_time_yield
|
||||
|
||||
providers = [g4f.Provider.OpenaiChat, g4f.Provider.Bard, g4f.Provider.Bing]
|
||||
|
||||
# Async support
|
||||
async def log_time_async(method: callable, **kwargs):
|
||||
start = time()
|
||||
result = await method(**kwargs)
|
||||
secs = f"{round(time() - start, 2)} secs"
|
||||
if result:
|
||||
return " ".join([result, secs])
|
||||
return secs
|
||||
_providers = [
|
||||
g4f.Provider.H2o,
|
||||
g4f.Provider.You,
|
||||
g4f.Provider.HuggingChat,
|
||||
g4f.Provider.OpenAssistant,
|
||||
g4f.Provider.Bing,
|
||||
g4f.Provider.Bard
|
||||
]
|
||||
|
||||
def log_time_yield(method: callable, **kwargs):
|
||||
start = time()
|
||||
result = yield from method(**kwargs)
|
||||
yield f" {round(time() - start, 2)} secs"
|
||||
_instruct = "Hello, tell about you in one sentence."
|
||||
|
||||
def log_time(method: callable, **kwargs):
|
||||
start = time()
|
||||
result = method(**kwargs)
|
||||
secs = f"{round(time() - start, 2)} secs"
|
||||
if result:
|
||||
return " ".join([result, secs])
|
||||
return secs
|
||||
|
||||
async def run_async():
|
||||
responses = []
|
||||
for provider in providers:
|
||||
responses.append(log_time_async(
|
||||
provider.create_async,
|
||||
model=None,
|
||||
messages=[{"role": "user", "content": "Hello"}],
|
||||
log_time=True
|
||||
))
|
||||
responses = await asyncio.gather(*responses)
|
||||
for idx, provider in enumerate(providers):
|
||||
print(f"{provider.__name__}:", responses[idx])
|
||||
print("Async Total:", asyncio.run(log_time_async(run_async)))
|
||||
|
||||
# Streaming support:
|
||||
def run_stream():
|
||||
for provider in providers:
|
||||
print(f"{provider.__name__}: ", end="")
|
||||
for response in log_time_yield(
|
||||
provider.create_completion,
|
||||
model=None,
|
||||
messages=[{"role": "user", "content": "Hello"}],
|
||||
):
|
||||
print(response, end="")
|
||||
print()
|
||||
print("Stream Total:", log_time(run_stream))
|
||||
|
||||
# No streaming support:
|
||||
def create_completion():
|
||||
for provider in providers:
|
||||
print(f"{provider.__name__}:", end=" ")
|
||||
for response in log_time_yield(
|
||||
g4f.Provider.Bard.create_completion,
|
||||
model=None,
|
||||
messages=[{"role": "user", "content": "Hello"}],
|
||||
):
|
||||
print(response, end="")
|
||||
print()
|
||||
print("No Stream Total:", log_time(create_completion))
|
||||
|
||||
for response in g4f.Provider.Hugchat.create_completion(
|
||||
model=None,
|
||||
messages=[{"role": "user", "content": "Hello, tell about you."}],
|
||||
):
|
||||
print("Hugchat:", response)
|
||||
|
||||
"""
|
||||
_example = """
|
||||
OpenaiChat: Hello! How can I assist you today? 2.0 secs
|
||||
Bard: Hello! How can I help you today? 3.44 secs
|
||||
Bing: Hello, this is Bing. How can I help? 😊 4.14 secs
|
||||
@ -92,4 +34,63 @@ OpenaiChat: Hello! How can I help you today? 3.28 secs
|
||||
Bard: Hello there! How can I help you today? 3.58 secs
|
||||
Bing: Hello! How can I help you today? 3.28 secs
|
||||
No Stream Total: 10.14 secs
|
||||
"""
|
||||
"""
|
||||
|
||||
print("Yqcloud:", end="")
|
||||
for response in log_time_yield(
|
||||
g4f.ChatCompletion.create,
|
||||
model=g4f.models.gpt_35_turbo,
|
||||
messages=[{"role": "user", "content": _instruct}],
|
||||
provider=g4f.Provider.Yqcloud,
|
||||
#cookies=g4f.get_cookies(".huggingface.co"),
|
||||
stream=True,
|
||||
auth=True
|
||||
):
|
||||
print(response, end="")
|
||||
print()
|
||||
print()
|
||||
|
||||
|
||||
async def run_async():
|
||||
responses = [
|
||||
log_time_async(
|
||||
provider.create_async,
|
||||
model=None,
|
||||
messages=[{"role": "user", "content": _instruct}],
|
||||
)
|
||||
for provider in _providers
|
||||
]
|
||||
responses = await asyncio.gather(*responses)
|
||||
for idx, provider in enumerate(_providers):
|
||||
print(f"{provider.__name__}:", responses[idx])
|
||||
print("Async Total:", asyncio.run(log_time_async(run_async)))
|
||||
print()
|
||||
|
||||
|
||||
def run_stream():
|
||||
for provider in _providers:
|
||||
print(f"{provider.__name__}: ", end="")
|
||||
for response in log_time_yield(
|
||||
provider.create_completion,
|
||||
model=None,
|
||||
messages=[{"role": "user", "content": _instruct}],
|
||||
):
|
||||
print(response, end="")
|
||||
print()
|
||||
print("Stream Total:", log_time(run_stream))
|
||||
print()
|
||||
|
||||
|
||||
def create_no_stream():
|
||||
for provider in _providers:
|
||||
print(f"{provider.__name__}:", end=" ")
|
||||
for response in log_time_yield(
|
||||
provider.create_completion,
|
||||
model=None,
|
||||
messages=[{"role": "user", "content": _instruct}],
|
||||
stream=False
|
||||
):
|
||||
print(response, end="")
|
||||
print()
|
||||
print("No Stream Total:", log_time(create_no_stream))
|
||||
print()
|
||||
Loading…
Reference in New Issue
Block a user