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Merge branch 'main' into main

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alxspiker 2023-05-11 14:34:13 -06:00 committed by GitHub
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4 changed files with 20 additions and 6 deletions
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11
constants.py Normal file
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@ -0,0 +1,11 @@
from chromadb.config import Settings
# Define the folder for storing database
PERSIST_DIRECTORY = 'db'
# Define the Chroma settings
CHROMA_SETTINGS = Settings(
chroma_db_impl='duckdb+parquet',
persist_directory=PERSIST_DIRECTORY,
anonymized_telemetry=False
)

4
ingest.py
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@ -3,6 +3,8 @@ from langchain.document_loaders import TextLoader, PDFMinerLoader, CSVLoader
from langchain.text_splitter import RecursiveCharacterTextSplitter
from langchain.vectorstores import Chroma
from langchain.embeddings import LlamaCppEmbeddings
from constants import PERSIST_DIRECTORY
from constants import CHROMA_SETTINGS
def main():
llama_embeddings_model = os.environ.get('LLAMA_EMBEDDINGS_MODEL')
@ -23,7 +25,7 @@ def main():
# Create embeddings
llama = LlamaCppEmbeddings(model_path=llama_embeddings_model, n_ctx=model_n_ctx)
# Create and store locally vectorstore
db = Chroma.from_documents(texts, llama, persist_directory=persist_directory)
db = Chroma.from_documents(texts, llama, persist_directory=PERSIST_DIRECTORY, client_settings=CHROMA_SETTINGS)
db.persist()
db = None

7
privateGPT.py
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@ -12,10 +12,11 @@ model_type = os.environ.get('MODEL_TYPE')
model_path = os.environ.get('MODEL_PATH')
model_n_ctx = os.environ.get('MODEL_N_CTX')
def main():
# Load stored vectorstore
from constants import CHROMA_SETTINGS
def main():
llama = LlamaCppEmbeddings(model_path=llama_embeddings_model, n_ctx=model_n_ctx)
db = Chroma(persist_directory=persist_directory, embedding_function=llama)
db = Chroma(persist_directory=persist_directory, embedding_function=llama, client_settings=CHROMA_SETTINGS)
retriever = db.as_retriever()
# Prepare the LLM
callbacks = [StreamingStdOutCallbackHandler()]

4
requirements.txt
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@ -1,5 +1,5 @@
langchain==0.0.162
langchain==0.0.166
pygpt4all==1.1.0
chromadb==0.3.22
llama-cpp-python==0.1.47
llama-cpp-python==0.1.48
urllib3==1.26.6