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# Text generation
from src.logger.logger import logging
from src.exception.exception import customexception
import sys
from langchain_huggingface import HuggingFaceEndpoint
# Text generation model
# repo_id="Laim/Llama-3.1-MedPalm2-imitate-8B-Instruct"
# repo_id="Joycean0301/Llama-3.2-3B-Instruct-Medical-Conversational"
# repo_id = "TheBloke/medalpaca-13B-GGML"
repo_id="mistralai/Mistral-7B-Instruct-v0.3"
class DocChatProcessor:
def __init__(self, hf_token):
self.llm = HuggingFaceEndpoint(
repo_id=repo_id,
max_new_tokens=512,
top_k=10,
top_p=0.95,
typical_p=0.95,
temperature=0.01,
repetition_penalty=1.03,
streaming=False,
huggingfacehub_api_token= hf_token,
stop_sequences=['?', '</s>', '.\n\n']
)
logging.info("LLM model for medical text generation created.")
def generate_response(self, input_text):
try:
logging.info("Text response generated.")
return self.llm.invoke(input_text)
except Exception as e:
raise customexception(e,sys) |