import logging
import multiprocessing

from langchain_community.chat_models import ChatLlamaCpp
from langchain_community.embeddings import HuggingFaceEmbeddings

DEFAULT_MODEL_PATH = "/home/sortedcord/.cache/huggingface/hub/models--ggml-org--gemma-4-E4B-it-GGUF/snapshots/6b352c53e1d2e4bb974d9f8cafcf85887c224219/gemma-4-e4b-it-Q4_K_M.gguf"

logger = logging.getLogger(__name__)

embeddings = HuggingFaceEmbeddings(model_name="all-MiniLM-L6-v2")

llm = ChatLlamaCpp(
    temperature=0.2,
    model_path=DEFAULT_MODEL_PATH,
    n_ctx=4096,
    n_gpu_layers=11,
    max_tokens=512,
    n_threads=multiprocessing.cpu_count() - 1,
    repeat_penalty=1.5,
    verbose=False,
)


def _format_prompt(messages):
    formatted = []
    for message in messages:
        formatted.append(f"{message.__class__.__name__}:\n{message.content}")
    return "\n\n".join(formatted)


def _normalize_llm_output(text: str) -> str:
    return text.replace("\r", "").replace("\n", "").strip()