services/llm.py

from langchain_ollama import OllamaLLM
from langchain_huggingface import HuggingFaceEmbeddings
import streamlit as st


@st.cache_resource
def initialize_llm(model_name, temperature, top_p, max_tokens):
    # Configure the LLM with additional parameters
    llm = OllamaLLM(
        model=model_name,
        base_url="https://deepak7376-ollama-server.hf.space",
        temperature=temperature,   # Controls randomness (0 = deterministic, 1 = max randomness)
        max_tokens=max_tokens,   # Limit the number of tokens in the output
        top_p=top_p          # Nucleus sampling for controlling diversity
    )
    return llm

@st.cache_resource
def initialize_embeddings():
    embeddings = HuggingFaceEmbeddings(model_name="all-MiniLM-L6-v2")
    return embeddings