privateGPT/ingest.py

22 lines
806 B
Python

from langchain.document_loaders import TextLoader
from langchain.text_splitter import CharacterTextSplitter
from langchain.vectorstores import Chroma
from langchain.embeddings import LlamaCppEmbeddings
from sys import argv
def main():
# Load document and split in chunks
loader = TextLoader(argv[1], encoding="utf8")
documents = loader.load()
text_splitter = CharacterTextSplitter(chunk_size=500, chunk_overlap=50)
texts = text_splitter.split_documents(documents)
# Create embeddings
llama = LlamaCppEmbeddings(model_path="./models/ggml-model-q4_0.bin")
# Create and store locally vectorstore
persist_directory = 'db'
db = Chroma.from_documents(texts, llama, persist_directory=persist_directory)
db.persist()
db = None
if __name__ == "__main__":
main()