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import logging
from models.custom_parsers import CustomStringOutputParser
from langchain.chains import ConversationChain
from langchain_openai import ChatOpenAI
from langchain.prompts import PromptTemplate
from models.business_logic_utils.input_processing import initialize_conversation
OPENAI_TEMPLATE = """{template}
{{history}}
helper: {{input}}
texter:"""
def get_template_role_models(issue: str, language: str, texter_name: str = "") -> str:
model_input = {
"issue": issue,
"language": language,
"texter_name": texter_name,
"messages": [],
}
# Initialize the conversation (adds the system message)
model_input = initialize_conversation(model_input, "")
return model_input["messages"][0]["content"]
def get_role_chain(template, memory, temperature=0.8):
template = OPENAI_TEMPLATE.format(template=template)
PROMPT = PromptTemplate(
input_variables=['history', 'input'],
template=template
)
llm = ChatOpenAI(
model="gpt-4o",
temperature=temperature,
max_tokens=256,
)
llm_chain = ConversationChain(
llm=llm,
prompt=PROMPT,
memory=memory,
output_parser=CustomStringOutputParser(),
verbose=True,
)
logging.debug(f"loaded GPT4o model")
return llm_chain, "helper:" |