bi@bi:~/ai/quiz-maker-be$ python3 main.py
Traceback (most recent call last):
File "/home/bi/ai/quiz-maker-be/main.py", line 5, in <module>
from llama_index import SimpleDirectoryReader
File "/home/bi/.local/lib/python3.10/site-packages/llama_index/__init__.py", line 12, in <module>
from llama_index.data_structs.struct_type import IndexStructType
File "/home/bi/.local/lib/python3.10/site-packages/llama_index/data_structs/__init__.py", line 3, in <module>
from llama_index.data_structs.data_structs import (
File "/home/bi/.local/lib/python3.10/site-packages/llama_index/data_structs/data_structs.py", line 14, in <module>
from llama_index.schema import BaseNode, TextNode
File "/home/bi/.local/lib/python3.10/site-packages/llama_index/schema.py", line 9, in <module>
from llama_index.bridge.langchain import Document as LCDocument
File "/home/bi/.local/lib/python3.10/site-packages/llama_index/bridge/langchain.py", line 21, in <module>
from langchain.embeddings import HuggingFaceEmbeddings, HuggingFaceBgeEmbeddings
ImportError: cannot import name 'HuggingFaceBgeEmbeddings' from 'langchain.embeddings' (/home/bi/.local/lib/python3.10/site-packages/langchain/embeddings/__init__.py)import os
import sys
sys.path.append(os.path.join(os.getcwd(), '..'))
from llama_index import SimpleDirectoryReader
# Make our printing look nice
from llama_index.schema import MetadataMode
def load_docs(filepath):
loader = SimpleDirectoryReader(
input_dir=filepath,
recursive=True
)
return loader.load_data()
# load our documents from each folder.
# we keep them seperate for now, in order to create separate indexes later
# load the recent provincial offences act
recent_act = load_docs("docs/recent_act")
# load the old provincial offences act
old_act = load_docs("docs/old_act")
from llama_index import ServiceContext, set_global_service_context
from llama_index.llms import OpenAI
# create a global service context
service_context = ServiceContext.from_defaults(llm=OpenAI(model="gpt-4", temperature=0))
set_global_service_context(service_context)
from llama_index import VectorStoreIndex, StorageContext, load_index_from_storage
# create a vector store index for each folder
# try and load the index if already made
try:
recent_act_index = load_index_from_storage(StorageContext.from_defaults(persist_dir="./recent_act_index"))
#old_act_index = load_index_from_storage(StorageContext.from_defaults(persist_dir="old_act_index/"))
except:
recent_act_index = VectorStoreIndex.from_documents(old_act)
recent_act_index.storage_context.persist(persist_dir="./recent_act_index")