File size: 3,221 Bytes
1905805 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 | from openai import AsyncOpenAI
from .base import T2TOperation
from utils.prompter.message import ChatMessage
from utils.prompter import Prompter
class OpenAIT2T(T2TOperation):
def __init__(self):
super().__init__("openai")
self.client = None
self.base_url = "https://api.openai.com/v1/"
self.model = "gpt-4o"
self.temperature = 1
self.top_p = 0.9
self.presence_penalty = 0
self.frequency_penalty = 0
async def start(self):
await super().start()
self.client = AsyncOpenAI(base_url=self.base_url)
async def close(self):
await super().close()
await self.client.close()
self.client = None
async def configure(self, config_d):
'''Configure and validate operation-specific configuration'''
if "base_url" in config_d: self.base_url = str(config_d['base_url'])
if "model" in config_d: self.model = str(config_d['model'])
if "temperature" in config_d: self.temperature = float(config_d['temperature'])
if "top_p" in config_d: self.top_p = float(config_d['top_p'])
if "presence_penalty" in config_d: self.presence_penalty = float(config_d['presence_penalty'])
if "frequency_penalty" in config_d: self.frequency_penalty = float(config_d['frequency_penalty'])
assert self.base_url is not None and len(self.base_url) > 0
assert self.model is not None and len(self.model) > 0
assert self.temperature >= 0 and self.temperature <= 2
assert self.top_p >= 0 and self.top_p <= 1
assert self.presence_penalty >= 0 and self.presence_penalty <= 1
assert self.frequency_penalty >= 0 and self.frequency_penalty <= 1
async def get_configuration(self):
'''Returns values of configurable fields'''
return {
"base_url": self.base_url,
"model": self.model,
"temperature": self.temperature,
"top_p": self.top_p,
"presence_penalty": self.presence_penalty,
"frequency_penalty": self.frequency_penalty,
}
async def _generate(self, instruction_prompt: str = None, messages: list = None, **kwargs):
history = [{ "role": "system", "content": instruction_prompt }]
for msg in messages:
next_hist = None
if isinstance(msg, ChatMessage) and msg.user == Prompter().character_name:
next_hist = { "role": "assistant", "content": msg.message }
else:
next_hist = { "role": "user", "content": msg.to_line() }
history.append(next_hist)
stream = await self.client.chat.completions.create(
messages=history,
model=self.model,
stream=True,
temperature=self.temperature,
top_p=self.top_p,
presence_penalty=self.presence_penalty,
frequency_penalty=self.frequency_penalty
)
full_response = ""
async for chunk in stream:
content_chunk = chunk.choices[0].delta.content or ""
full_response += content_chunk
yield {"content": content_chunk}
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