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from langchain_community.chat_models import ChatOpenAI
from langchain.llms import CTransformers
from langchain.llms.huggingface_pipeline import HuggingFacePipeline
from transformers import AutoTokenizer, TextStreamer
from langchain.llms import LlamaCpp
import torch
import transformers
import os
from langchain.callbacks.manager import CallbackManager
from langchain.callbacks.streaming_stdout import StreamingStdOutCallbackHandler
class ChatModelLoader:
def __init__(self, config):
self.config = config
self.huggingface_token = os.getenv("HUGGINGFACEHUB_API_TOKEN")
def load_chat_model(self):
if self.config["llm_params"]["llm_loader"] == "openai":
llm = ChatOpenAI(
model_name=self.config["llm_params"]["openai_params"]["model"]
)
elif self.config["llm_params"]["llm_loader"] == "local_llm":
n_batch = 512 # Should be between 1 and n_ctx, consider the amount of VRAM in your GPU.
model_path = self.config["llm_params"]["local_llm_params"]["model"]
llm = LlamaCpp(
model_path=model_path,
n_batch=n_batch,
n_ctx=2048,
f16_kv=True,
verbose=True,
n_threads=2,
temperature=self.config["llm_params"]["local_llm_params"][
"temperature"
],
)
else:
raise ValueError("Invalid LLM Loader")
return llm
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