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from langchain.llms import BaseLLM | |
from langchain import LLMChain, PromptTemplate | |
class TaskPrioritizationChain(LLMChain): | |
"""Chain to prioritize tasks.""" | |
def from_llm(cls, llm: BaseLLM, verbose: bool = True) -> LLMChain: | |
"""Get the response parser.""" | |
task_prioritization_template = ( | |
"You are an task prioritization AI tasked with cleaning the formatting of and reprioritizing" | |
" the following tasks: {task_names}." | |
" Consider the ultimate objective of your team: {objective}." | |
" Do not remove any tasks. Return the result as a numbered list, like:" | |
" #. First task" | |
" #. Second task" | |
" Start the task list with number {next_task_id}." | |
) | |
prompt = PromptTemplate( | |
template=task_prioritization_template, | |
input_variables=["task_names", "next_task_id", "objective"], | |
) | |
return cls(prompt=prompt, llm=llm, verbose=verbose) |