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102 lines
3.3 KiB
Python
102 lines
3.3 KiB
Python
from __future__ import annotations
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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 AsyncGenerator
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from .base_provider import AsyncGeneratorProvider, format_prompt
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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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model = "h2oai/h2ogpt-gm-oasst1-en-2048-falcon-40b-v1"
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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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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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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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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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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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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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("temperature", "float"),
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("truncate", "int"),
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("max_new_tokens", "int"),
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("do_sample", "bool"),
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("repetition_penalty", "float"),
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("return_full_text", "bool"),
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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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