paperchat / qa.py
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"""Ask a question to the notion database."""
import faiss
from langchain import OpenAI
from langchain.chains import VectorDBQAWithSourcesChain
import pickle
import argparse
parser = argparse.ArgumentParser(description='Ask a question about the paper')
parser.add_argument('question', type=str, help='The question to ask about the paper')
args = parser.parse_args()
# Load the LangChain.
index = faiss.read_index("docs.index")
with open("faiss_store.pkl", "rb") as f:
store = pickle.load(f)
store.index = index
chain = VectorDBQAWithSourcesChain.from_llm(llm=OpenAI(temperature=0), vectorstore=store)
result = chain({"question": args.question})
print(f"Answer: {result['answer']}")
sources = result["sources"].split(", ")
sources = [s.title() for s in sources]
import code
code.interact(local=locals())