langchain-python-rag-privategpt "Cannot submit more than 5,461 embeddings at once"

[dcasota]

What is the issue?

In langchain-python-rag-privategpt, there is a bug 'Cannot submit more than x embeddings at once' which already has been mentioned in various different constellations, lately see #2572.

Now with Ollama version 0.1.38 the chromadb version already has been updated to 0.47, but the max_batch_size calculation still seems to produce issues, see actual issue case chroma-core/chroma#2181.

Meanwhile, is there a workaround for Ollama?

(.venv) dcaso [ ~/ollama/examples/langchain-python-rag-privategpt ]$ python ./ingest.py
Creating new vectorstore
Loading documents from source_documents
Loading new documents: 100%|████████████████| 1355/1355 [00:15<00:00, 88.77it/s]
Loaded 80043 new documents from source_documents
Split into 478012 chunks of text (max. 500 tokens each)
Creating embeddings. May take some minutes...
Traceback (most recent call last):
  File "/home/dcaso/ollama/examples/langchain-python-rag-privategpt/./ingest.py", line 161, in <module>
    main()
  File "/home/dcaso/ollama/examples/langchain-python-rag-privategpt/./ingest.py", line 153, in main
    db = Chroma.from_documents(texts, embeddings, persist_directory=persist_directory)
         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/dcaso/ollama/examples/langchain-python-rag-privategpt/.venv/lib/python3.11/site-packages/langchain/vectorstores/chroma.py", line 612, in from_documents
    return cls.from_texts(
           ^^^^^^^^^^^^^^^
  File "/home/dcaso/ollama/examples/langchain-python-rag-privategpt/.venv/lib/python3.11/site-packages/langchain/vectorstores/chroma.py", line 576, in from_texts
    chroma_collection.add_texts(texts=texts, metadatas=metadatas, ids=ids)
  File "/home/dcaso/ollama/examples/langchain-python-rag-privategpt/.venv/lib/python3.11/site-packages/langchain/vectorstores/chroma.py", line 222, in add_texts
    raise e
  File "/home/dcaso/ollama/examples/langchain-python-rag-privategpt/.venv/lib/python3.11/site-packages/langchain/vectorstores/chroma.py", line 208, in add_texts
    self._collection.upsert(
  File "/home/dcaso/ollama/examples/langchain-python-rag-privategpt/.venv/lib/python3.11/site-packages/chromadb/api/models/Collection.py", line 298, in upsert
    self._client._upsert(
  File "/home/dcaso/ollama/examples/langchain-python-rag-privategpt/.venv/lib/python3.11/site-packages/chromadb/api/segment.py", line 290, in _upsert
    self._producer.submit_embeddings(coll["topic"], records_to_submit)
  File "/home/dcaso/ollama/examples/langchain-python-rag-privategpt/.venv/lib/python3.11/site-packages/chromadb/db/mixins/embeddings_queue.py", line 127, in submit_embeddings
    raise ValueError(
ValueError:
                Cannot submit more than 5,461 embeddings at once.
                Please submit your embeddings in batches of size
                5,461 or less.

(.venv) dcaso [ ~/ollama/examples/langchain-python-rag-privategpt ]$

OS

WSL2

GPU

Nvidia

CPU

Intel

Ollama version

0.1.38

Research findings

In ingest.py, in def maint(), I've modified the else condition as following but it didn't help (same issue).

[dcasota]

It may be yet another subcomponent issue. With v0.1.38, langchain version is 0.0.274.

pip3 list | grep langchain
langchain                0.0.274

Not use of e.g. langchain_community.

As workaround, I've updated all components. This is not recommended because usually it creates more side effects and it's more difficult to reproduce issues.

pip --disable-pip-version-check list --outdated --format=json | python -c "import json, sys; print('\n'.join([x['name'] for x in json.load(sys.stdin)]))" | sudo xargs -n1 pip install -U

Afterwards, the following langchain packages are installed:

pip3 list |grep langchain
langchain                0.1.20
langchain-community      0.0.38
langchain-core           0.1.52
langchain-text-splitters 0.0.2

python ingest.py and python privateGPT.py run successfully, but the output contains warnings with various deprecated langchain components. From the findings so far, a curated requirements.txt list would be helpful.

python ingest.py always starts with Creating new vectorstore. It does not preserve already loaded documents. Why?

[dcasota]

Same issue with v0.1.39. Luckily the workaround works, with Nvidia drivers 552 (see #4563).

edited June 5th: Same with v0.1.41.
edited June 19th: Same with 0.1.44. Add pip install chromadb==0.5.0