Unable to load a saved Chroma Database

Short Course Q&A LangChain: Chat with Your Data
8

Sorry for the late response on this. You have forgot to mention vectordb.persist() at step 3.

Below is the complete code for your reference:

#%% Step 1: Load PDF
from langchain.document_loaders import PyPDFLoader
from langchain.text_splitter import RecursiveCharacterTextSplitter

loader = PyPDFLoader("docs/cs229_lectures/MachineLearning-Lecture01.pdf")
pages = loader.load()
all_page_text=[p.page_content for p in pages]
joined_page_text=" ".join(all_page_text)

# Step 2: Split
text_splitter = RecursiveCharacterTextSplitter(chunk_size = 1500,chunk_overlap = 150)
splits = text_splitter.split_text(joined_page_text)

# %% Step 3: Embed and vectorize and store
from langchain.embeddings.openai import OpenAIEmbeddings
from langchain.vectorstores import Chroma

persist_directory = 'basic_langchain/chroma_storage'
embedding = OpenAIEmbeddings()

vectordb = Chroma.from_texts(
    texts=splits,
    embedding=embedding,
    persist_directory=persist_directory
)

vectordb.persist()

vectordb_loaded = Chroma(
    persist_directory=persist_directory,
    embedding_function=embedding
)
print(vectordb_loaded._collection.count())

I have tested above code and it is working fine. Also I have checked output folder basic_langchain/chroma_storage, required parquet files are present after persisting.

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