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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 | |