LwbXc
code and datasets
b754bbe
from langchain.schema.runnable import RunnablePassthrough
from langchain.prompts import ChatPromptTemplate
from langchain.chat_models import ChatOpenAI
from langchain_core.output_parsers import StrOutputParser
class gpt4o(object):
def __init__(self, api_key, max_new_tokens=5):
OpenAIChatModel = ChatOpenAI(
temperature=0,
max_tokens=max_new_tokens,
openai_api_key=api_key,
model_name="gpt-4o-2024-05-13"
)
self._init_chain(OpenAIChatModel)
def _init_chain(self, chat_model):
common_prompt = ChatPromptTemplate.from_messages(
[
(
"system",
"You are a helpful text completion assistant. Please continue writing the text entered by the human."
),
("human", "{question}"),
]
)
self.common_chain = (
{"question": RunnablePassthrough()}
| common_prompt
| chat_model
| StrOutputParser()
)
def generate(self, code: str, max_new_tokens: int):
if max_new_tokens is not None and max_new_tokens!=self.max_new_tokens:
OpenAIChatModel = ChatOpenAI(
temperature=0,
max_tokens=max_new_tokens,
openai_api_key=self.api_key,
model_name="gpt-4o-2024-05-13"
)
self.max_new_tokens = max_new_tokens
self._init_chain(OpenAIChatModel)
return self.common_chain.invoke(code)
if __name__=='__main__':
model = gpt4o()
print(model.generate("Yesterday was Thursday, today is Friday, so tomorrow is ", 10))
print(model.generate("Yesterday was 2022-01-01, today is 2022-01-02, so tomorrow is ", 10))