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from langchain_core.output_parsers import StrOutputParser
from langchain_core.runnables import RunnablePassthrough
from langchain_core.prompts import ChatPromptTemplate
from utils.initMethods import readYaml, getConfig
from utils.exceptions import CustomException
from langchain_cerebras import ChatCerebras
from utils.logger import logger
import os
config = getConfig(os.path.join(os.getcwd(), "config.ini"))
prompts = readYaml(os.path.join(os.getcwd(), "prompts.yaml"))
class ReasoningAgent:
def __init__(self) -> None:
try:
logger.info("INITIALIZING REASONING AGENT")
promptTemplate = ChatPromptTemplate.from_template(prompts.get("reasoningTemplate"))
llm = ChatCerebras(
model = config.get("REASONINGAGENT", "modelName"),
temperature = config.getfloat("REASONINGAGENT", "temperature")
)
chain = {"query": RunnablePassthrough()} | promptTemplate | llm | StrOutputParser()
self.chain = chain
except Exception as e:
exception = CustomException(e)
logger.error(exception)
raise exception
def query(self, query) -> str:
try:
output = self.chain.invoke(query)
return output
except Exception as e:
exception = CustomException(e)
logger.error(exception)
raise exception |