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from langchain.llms import LlamaCpp | |
from langchain.chains import ConversationalRetrievalChain | |
from huggingface_hub import hf_hub_download | |
import psutil | |
import os | |
def get_chain(vectorstore): | |
if not os.path.exists("ggml-vic7b-q5_1.bin"): | |
hf_hub_download(repo_id="eachadea/ggml-vicuna-7b-1.1", filename="ggml-vic7b-q5_1.bin", local_dir=".") | |
llm = LlamaCpp(model_path="ggml-vic7b-q5_1.bin", n_ctx=2048, n_threads=psutil.cpu_count(logical=False)) | |
qa_chain = ConversationalRetrievalChain.from_llm( | |
llm, | |
vectorstore.as_retriever(), | |
# condense_question_prompt=CONDENSE_QUESTION_PROMPT, | |
) | |
return qa_chain |