ChromaDB Support for Python SDK #110
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Just wanted to let you know that I've been busy lately with my day job and probably won't be able to get to this for at least a week. |
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Sounds good, and thank you for letting me know @ristomcgehee! |
ristomcgehee
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Okay, I finally found some time to review this PR. Here are my thoughts!
python-sdk/README.md
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| ### Detect prompt injection on user input | ||
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| For vector database, Rebuff supports Pinecone (default) and Chroma. To use Chroma, install Rebuff with extras: `pip install rebuff[chromadb]` |
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| For vector database, Rebuff supports Pinecone (default) and Chroma. To use Chroma, install Rebuff with extras: `pip install rebuff[chromadb]` | |
| For vector database, Rebuff supports Pinecone (default) and Chroma. |
That same information is repeated a few lines later, so I don't think we need it here.
| input: str, similarity_threshold: float, vector_store: Pinecone | ||
| input: str, | ||
| similarity_threshold: float, | ||
| vector_store: Union[Pinecone, Optional[Chroma]], |
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| vector_store: Union[Pinecone, Optional[Chroma]], | |
| vector_store: VectorStore, |
And then you'd need to import VectorStore from langchain at the top of the file.
| try: | ||
| import chromadb | ||
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| chromadb_installed = True | ||
| except ImportError: | ||
| print( | ||
| "To use Chromadb, please install rebuff with rebuff extras. 'pip install \"rebuff[chromadb]\"'" | ||
| ) | ||
| chromadb_installed = False |
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I'd like to suggest a different approach for handling the fact that chromadb might not be installed. If I understand the code correctly, even if a user is using Pinecone, they'll always see the warning "To use Chromadb, please install...". Also, it's a bit unusual conditionally defining classes and methods.
I would move ChromaCosineSimilarity to a different file but keep init_chroma in this file. At the beginning of init_chroma, you import chromadb and ChromaCosineSimilarity within a try-except. If the import fails, then you display "To use Chromadb, please install...". Then you'd no longer need the chromadb_installed variable.
python-sdk/rebuff/sdk.py
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| ) | ||
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| elif self.vector_db.name == "CHROMA": | ||
| from rebuff.detect_pi_vectorbase import init_chroma |
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If you take my suggestion for refactoring detect_pi_vectorbase.py, you'll be able to move this import to the top of the file.
python-sdk/rebuff/sdk.py
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| if check_vector: | ||
| self.initialize_pinecone() | ||
| self.initialize_vector_store() |
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| self.initialize_vector_store() | |
| if self.vector_store is None: | |
| self.initialize_vector_store() |
| def rebuff(request) -> RebuffSdk: | ||
| rb = RebuffSdk( | ||
| get_environment_variable("OPENAI_API_KEY"), | ||
| request.param, | ||
| get_environment_variable("PINECONE_API_KEY"), | ||
| get_environment_variable("PINECONE_INDEX_NAME"), | ||
| ) |
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For most test methods, it doesn't do any good testing on both pinecone and chroma; only test_detect_injection_vectorbase needs to test with both. You could do this in the fixture:
| def rebuff(request) -> RebuffSdk: | |
| rb = RebuffSdk( | |
| get_environment_variable("OPENAI_API_KEY"), | |
| request.param, | |
| get_environment_variable("PINECONE_API_KEY"), | |
| get_environment_variable("PINECONE_INDEX_NAME"), | |
| ) | |
| def rebuff(request) -> RebuffSdk: | |
| vector_db = request.param if hasattr(request, "param") else VectorDB.PINECONE | |
| rb = RebuffSdk( | |
| get_environment_variable("OPENAI_API_KEY"), | |
| vector_db, | |
| get_environment_variable("PINECONE_API_KEY"), | |
| get_environment_variable("PINECONE_INDEX_NAME"), | |
| ) |
Which would allow you to delete:
@pytest.mark.parametrize(
"rebuff",
[VectorDB.PINECONE, VectorDB.CHROMA],
ids=["pinecone", "chroma"],
indirect=True,
)from most of the methods.
python-sdk/tests/test_sdk.py
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| ) | ||
| def test_detect_injection_vectorbase( | ||
| rebuff: RebuffSdk, | ||
| add_documents_to_chroma, |
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This parameter isn't getting used in this method, it probably shouldn't be a parameter. What I would probably do is add add_documents_to_chroma to the end of the rebuff function fixture.
| ) | ||
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| chroma_collection = ChromaCosineSimilarity( | ||
| client=chromadb.Client(), |
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When chromadb.Client() is invoked, is that creating an in-memory database that only persists as long as the process does? If that's the case, it wouldn't really work for a production use case. I think what we'd want to do is use chromadb.HttpClient to connect to a remote server. If we go that route, it looks like we might be able to use chromadb-client instead which is a more lightweight version of chromadb (https://docs.trychroma.com/usage-guide?lang=py#using-the-python-http-only-client).
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Thank you for the suggestion! I have updated the code to use chromadb.HttpClient. I will check if we can also update the dependency to chromadb-client
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I have updated the dependency to chromadb-client.
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Thank you @ristomcgehee for the review, and suggestions! I have tried to incorporate most of them. Also using |
python-sdk/tests/test_sdk.py
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| get_environment_variable("PINECONE_API_KEY"), | ||
| get_environment_variable("PINECONE_INDEX_NAME"), | ||
| ) | ||
| if hasattr(request, "param") and request.param == VectorDB.CHROMA: |
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| if hasattr(request, "param") and request.param == VectorDB.CHROMA: | |
| if vector_db == VectorDB.CHROMA: |
python-sdk/rebuff/sdk.py
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| if self.vector_db.name == "PINECONE": | ||
| self.pinecone_apikey = pinecone_apikey | ||
| self.pinecone_index = pinecone_index | ||
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| elif self.vector_db.name == "CHROMA": |
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| if self.vector_db.name == "PINECONE": | |
| self.pinecone_apikey = pinecone_apikey | |
| self.pinecone_index = pinecone_index | |
| elif self.vector_db.name == "CHROMA": | |
| if self.vector_db == VectorDB.PINECONE: | |
| self.pinecone_apikey = pinecone_apikey | |
| self.pinecone_index = pinecone_index | |
| elif self.vector_db == VectorDB.CHROMA: |
Similar recommendation for within initialize_vector_store().
python-sdk/rebuff/sdk.py
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| if check_vector: | ||
| self.initialize_pinecone() | ||
| if self.initialize_vector_store() is None: |
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| if self.initialize_vector_store() is None: | |
| if self.vector_store is None: |
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Thank you @ristomcgehee, I have now added Docker files for Chroma server. Though not sure why the JS and Python tests (integration tests) are failing. They are detecting prompt injection when there is none |
ristomcgehee
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ristomcgehee
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Though not sure why the JS and Python tests (integration tests) are failing. They are detecting prompt injection when there is none
I believe this occurs sometimes because LLMs are non-deterministic. Sometimes, you'll give a benign input and it will give a score of 0.6 or 0.8. A couple ways we could address that:
- Set the temperature to 0 when calling OpenAI
- Retry the tests multiple times when they fail
For now, you could also just re-run the tests and they'll likely pass.
| print("Possible injection detected. Take corrective action.") | ||
| ``` | ||
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| #### Chroma vector database |
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For a quickstart page, the simpler you can make it the better. I'd recommend taking out the pinecone section and just show how to use the SDK with Chroma DB (since it requires less setup than Pinecone).
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| application: | ||
| env_file: | ||
| - .env |
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It would be good to mention that an .env file is necessary in documentation, as well as describe what is necessary to be included. Something that projects often do is have an example.env file in the repo that people can copy and fill in with their values.
Thank you for the suggestions. I have tried rerunning the tests multiple times, and have also set temperature to 0 when calling OpenAI, thought don't think it is helping much. Python SDK tests are also failing because of connection error with chroma server when they do pass locally. I will continue to debug this, but if you have any suggestion please do share. |
| if vector_db == VectorDB.CHROMA: | ||
| rb = RebuffSdk(get_environment_variable("OPENAI_API_KEY"), vector_db) |
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Aren't these two lines unnecessary since we already initialized rb on line 10?
| documents = dataset["train"]["text"][:200] | ||
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| metadatas = [{"source": "Rebuff"}] * len(documents) | ||
| documents_ids = [str(uuid.uuid1()) for i in range(1, len(documents) + 1)] |
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minor simplification:
| documents_ids = [str(uuid.uuid1()) for i in range(1, len(documents) + 1)] | |
| documents_ids = [str(uuid.uuid1()) for _ in range(len(documents))] |
| chroma_collections = [ | ||
| collection for collection in chroma_client.list_collections() | ||
| ] | ||
| if chroma_collections: | ||
| chroma_collections_names = [ | ||
| collection.name for collection in chroma_collections | ||
| ] | ||
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| if rebuff_collection_name in chroma_collections_names: | ||
| document_collection = chroma_client.get_collection( | ||
| name=rebuff_collection_name, | ||
| embedding_function=openai_embedding_function, | ||
| ) | ||
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| else: | ||
| document_collection = chroma_client.create_collection( | ||
| name=rebuff_collection_name, | ||
| metadata={"hnsw:space": "cosine"}, | ||
| embedding_function=openai_embedding_function, | ||
| ) | ||
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| document_collection.add( | ||
| documents=documents, metadatas=metadatas, ids=documents_ids | ||
| ) | ||
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| else: | ||
| document_collection = chroma_client.create_collection( | ||
| name=rebuff_collection_name, | ||
| metadata={"hnsw:space": "cosine"}, | ||
| embedding_function=openai_embedding_function, | ||
| ) | ||
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| document_collection.add( | ||
| documents=documents, metadatas=metadatas, ids=documents_ids | ||
| ) |
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There's a function get_or_create_collection, so you can simplify all this to:
| chroma_collections = [ | |
| collection for collection in chroma_client.list_collections() | |
| ] | |
| if chroma_collections: | |
| chroma_collections_names = [ | |
| collection.name for collection in chroma_collections | |
| ] | |
| if rebuff_collection_name in chroma_collections_names: | |
| document_collection = chroma_client.get_collection( | |
| name=rebuff_collection_name, | |
| embedding_function=openai_embedding_function, | |
| ) | |
| else: | |
| document_collection = chroma_client.create_collection( | |
| name=rebuff_collection_name, | |
| metadata={"hnsw:space": "cosine"}, | |
| embedding_function=openai_embedding_function, | |
| ) | |
| document_collection.add( | |
| documents=documents, metadatas=metadatas, ids=documents_ids | |
| ) | |
| else: | |
| document_collection = chroma_client.create_collection( | |
| name=rebuff_collection_name, | |
| metadata={"hnsw:space": "cosine"}, | |
| embedding_function=openai_embedding_function, | |
| ) | |
| document_collection.add( | |
| documents=documents, metadatas=metadatas, ids=documents_ids | |
| ) | |
| document_collection = chroma_client.get_or_create_collection( | |
| name=rebuff_collection_name, | |
| metadata={"hnsw:space": "cosine"}, | |
| embedding_function=openai_embedding_function, | |
| ) | |
| document_collection.add( | |
| documents=documents, metadatas=metadatas, ids=documents_ids | |
| ) |
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| # Wait for the documents to be added to the collection | ||
| count = 0 | ||
| while document_collection.count() == 0 and count < 5: |
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Why do we need to wait here? Does document_collection.add() return before the documents get fully committed to the data store? If so, that would be a useful thing to mention in a comment.
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Can you give this file a name that matches its purpose better, e.g. "add_chroma_docs.py"?
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| collection_status = False | ||
| count = 0 | ||
| while not collection_status and count <= 5: |
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Why is this while loop necessary? Does creating the collection or add the documents often fail?
| ) | ||
| collection_status = True | ||
| except Exception as e: | ||
| pass |
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If chroma_client.get_or_create_collection or document_collection.add is consistently failing, it would make debugging harder since we're not showing any error messages. Maybe you could print e along with an error description outside of the while loop if collection_status == False.
2 participants
This PR adds Chroma DB support for Python SDK.