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from langchain import LLMChain
from typing import OrderedDict
from langchain.prompts import PromptTemplate
from omegaconf import OmegaConf
import datetime
SELECTION_TEMPLATE = """
{concept}
Model name and description:
{option_list}
Warning: {warning}
The avilable Options:
{choices}
Answer:
"""
def selection_chain(llm, class_concept, prompt, options):
chain = None
memory = None
if llm:
print("class_concept", class_concept)
if class_concept is None:
class_concept = 'AI assistant'
prompt_template = prompt + SELECTION_TEMPLATE
template = PromptTemplate(
input_variables=["concept", "option_list", "warning", "choices"],
template=prompt_template,
)
chain = LLMChain(
llm=llm, prompt=template, verbose=True)
print(options)
option_list = [
f"{chr(ord('A') + i)}. {conf['desc']}" for i, conf in enumerate(options.values())
]
option_list = '\n'.join(option_list)
selected_model = None
warning_str = 'Choose from the available Options.'
choices = ' '.join(chr(ord('A') + i) for i in range(len(options)))
choice = chain.run({'concept': class_concept, 'option_list':option_list, 'warning': warning_str, 'choices': choices})
print(f"LLM Responds (First character was used as the choice):{choice}", )
choice = choice[0]
selected_model = list(options.keys())[ord(choice) - ord('A')]
print("Selected model name: ", selected_model)
return selected_model
def model_selection_chain(llm, class_concept=None, conf_file='resources/models_personality.yaml'):
chain = None
memory = None
if llm:
print("class_concept", class_concept)
if class_concept is None:
class_concept = 'AI assistant'
selection_config = OmegaConf.load(conf_file)
selected_model = selection_chain(llm, class_concept, selection_config['prompt'], selection_config['models'])
model_conf = selection_config['models'][selected_model]
return model_conf, selected_model