gpt4free/g4f/Provider/H2o.py

100 lines
3.3 KiB
Python
Raw Normal View History

import json
import uuid
from aiohttp import ClientSession
2023-07-28 13:07:17 +03:00
from ..typing import AsyncGenerator
from .base_provider import AsyncGeneratorProvider, format_prompt
2023-07-28 13:07:17 +03:00
class H2o(AsyncGeneratorProvider):
url = "https://gpt-gm.h2o.ai"
working = True
2023-07-28 13:07:17 +03:00
supports_stream = True
2023-08-27 18:37:44 +03:00
model = "h2oai/h2ogpt-gm-oasst1-en-2048-falcon-40b-v1"
2023-07-28 13:07:17 +03:00
@classmethod
async def create_async_generator(
cls,
2023-07-28 13:07:17 +03:00
model: str,
messages: list[dict[str, str]],
proxy: str = None,
**kwargs
) -> AsyncGenerator:
model = model if model else cls.model
2023-07-28 13:07:17 +03:00
headers = {"Referer": "https://gpt-gm.h2o.ai/"}
async with ClientSession(
headers=headers
) as session:
data = {
"ethicsModalAccepted": "true",
"shareConversationsWithModelAuthors": "true",
"ethicsModalAcceptedAt": "",
"activeModel": model,
"searchEnabled": "true",
}
async with session.post(
"https://gpt-gm.h2o.ai/settings",
proxy=proxy,
data=data
) as response:
response.raise_for_status()
2023-07-28 13:07:17 +03:00
async with session.post(
"https://gpt-gm.h2o.ai/conversation",
proxy=proxy,
json={"model": model},
) as response:
response.raise_for_status()
conversationId = (await response.json())["conversationId"]
2023-07-28 13:07:17 +03:00
data = {
"inputs": format_prompt(messages),
"parameters": {
"temperature": 0.4,
"truncate": 2048,
"max_new_tokens": 1024,
"do_sample": True,
"repetition_penalty": 1.2,
"return_full_text": False,
**kwargs
},
"stream": True,
"options": {
"id": str(uuid.uuid4()),
"response_id": str(uuid.uuid4()),
"is_retry": False,
"use_cache": False,
"web_search_id": "",
},
}
async with session.post(
f"https://gpt-gm.h2o.ai/conversation/{conversationId}",
proxy=proxy,
json=data
) 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):-1])
if not line["token"]["special"]:
yield line["token"]["text"]
2023-07-28 13:07:17 +03:00
@classmethod
@property
def params(cls):
params = [
("model", "str"),
("messages", "list[dict[str, str]]"),
("stream", "bool"),
("temperature", "float"),
("truncate", "int"),
("max_new_tokens", "int"),
("do_sample", "bool"),
("repetition_penalty", "float"),
("return_full_text", "bool"),
]
param = ", ".join([": ".join(p) for p in params])
return f"g4f.provider.{cls.__name__} supports: ({param})"