Changing the distance function for an existing Chromadb collection

[MinhPham123456789]

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Description

Hi everyone, I am new to Chromadb. I saw in the documentation how to change the distance function when creating a new collection, but it does not mention about changing distance function for an existing collection. Does anyone know the proper way to do it?
My intention is load a persisting db then change the distance function and save the new distance function and the db to the same directory.
In addition, I am using the langchain-chromadb library not the original chromadb library

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[dosubot[bot]]

Hey there, @MinhPham123456789! I'm here to help you with your Chromadb question. Let's figure this out together.

To change the distance function for an existing collection in Chromadb, load a persistent database, and save the new distance function and the database to the same directory, you can follow these steps:

1. Load the existing collection.
2. Change the distance function.
3. Save the updated collection back to the same directory.

Here is a code snippet that demonstrates how to achieve this:

import chromadb
import chromadb.config

# Load the existing collection
persist_directory = "path/to/your/persist_directory"
client_settings = chromadb.config.Settings(is_persistent=True, persist_directory=persist_directory)
client = chromadb.Client(client_settings)
collection_name = "your_collection_name"
collection = client.get_collection(name=collection_name)

# Change the distance function
new_distance_function = "cosine"  # or "l2" or "ip"
collection_metadata = collection.metadata
collection_metadata["hnsw:space"] = new_distance_function

# Save the updated collection
client.delete_collection(collection_name)
client.create_collection(name=collection_name, metadata=collection_metadata)

This code will load the existing collection, change its distance function, and save the updated collection back to the same directory. Note that since Chroma 0.4.x, the manual persistence method is no longer supported as documents are automatically persisted ^[1][2].

To continue talking to Dosu, mention @dosu.

[MinhPham123456789]

I am using the langchain chromadb, can you show me how to do that with the langchian-chromadb library? @dosu

[dosubot[bot]]

To change the distance function for an existing collection using the LangChain-Chromadb library, load a persistent database, and save the updated database with the new distance function in the same directory, you can follow these steps:

1. Load the existing collection.
2. Update the collection's metadata to change the distance function.
3. Save the updated collection.

Here is a code example to achieve this:

import chromadb
from langchain_community.vectorstores.chroma import Chroma

# Load the existing collection
persist_directory = "path/to/persist_directory"
collection_name = "existing_collection_name"
client_settings = chromadb.config.Settings(is_persistent=True, persist_directory=persist_directory)
chroma_client = chromadb.Client(client_settings)

# Initialize the Chroma vector store
vectorstore = Chroma(
    collection_name=collection_name,
    persist_directory=persist_directory,
    client=chroma_client
)

# Update the collection's metadata to change the distance function
new_distance_function = "cosine"  # or "l2" or "ip"
vectorstore._collection.metadata["hnsw:space"] = new_distance_function

# Save the updated collection
# Note: Since Chroma 0.4.x, manual persistence is no longer needed as it is automatic.

This code will load the existing collection, update the distance function in the collection's metadata, and save the updated collection in the same directory. Note that from Chroma 0.4.x onwards, manual persistence is no longer required as the data is automatically persisted ^[1][2].

To continue talking to Dosu, mention @dosu.

[MinhPham123456789]

The provided solution does not work @dosu

[dosubot[bot]]

To change the distance function for an existing collection using the LangChain-Chromadb library, you need to use the DistanceStrategy enum provided in the utils.py file. Here is an example of how you can set the distance function:

from langchain_community.vectorstores.utils import DistanceStrategy
from langchain_chroma.vectorstores import Chroma

# Load the existing collection
persist_directory = "path/to/persist_directory"
collection_name = "existing_collection_name"
client_settings = chromadb.config.Settings(is_persistent=True, persist_directory=persist_directory)
chroma_client = chromadb.Client(client_settings)

# Initialize the Chroma vector store
vectorstore = Chroma(
    collection_name=collection_name,
    persist_directory=persist_directory,
    client=chroma_client
)

# Update the collection's metadata to change the distance function
vectorstore._collection.metadata["hnsw:space"] = "cosine"  # or "l2" or "ip"

# Save the updated collection
# Note: Since Chroma 0.4.x, manual persistence is no longer needed as it is automatic.

This code will load the existing collection, update the distance function in the collection's metadata, and save the updated collection in the same directory. Make sure to replace "cosine" with the desired distance function, such as "l2" for Euclidean distance or "ip" for inner product ^[1][2].

To continue talking to Dosu, mention @dosu.

[pragone]

Careful, with the code generated above by the bot.... as it will not copy the documents in the collection.

This function clones an existing collection allowing you to change the metadata in the copy

def clone_collection(client,
                    source_collection_name: str,
                    new_collection_name: str,
                    metadata_overrides: Optional[Dict[str, Any]] = None,
                    batch_size: int = 100) -> chromadb.Collection:
    """
    Clone an existing collection into a new collection.
    
    Args:
        client: ChromaDB client instance
        source_collection_name: Name of the source collection to clone
        new_collection_name: Name for the new collection
        metadata_overrides: Optional dictionary of metadata to override in the new collection
        batch_size: Number of items to add in each batch
    
    Returns:
        chromadb.Collection: The newly created collection
    
    Raises:
        ValueError: If source collection doesn't exist
    """
    # Get source collection
    try:
        source_collection = client.get_collection(source_collection_name)
    except Exception as e:
        raise ValueError(f"Source collection '{source_collection_name}' not found: {str(e)}")
    
    # Merge original metadata with overrides
    original_metadata = source_collection.metadata or {}
    final_metadata = {
        **original_metadata,
        **(metadata_overrides or {}),
        "cloned_from": source_collection_name,
        "cloned_at": datetime.now().isoformat()
    }
    
    # Create new collection
    new_collection = client.create_collection(
        name=new_collection_name,
        metadata=final_metadata
    )
    
    # Get all items from source collection
    results = source_collection.get(
        include=['embeddings', 'documents', 'metadatas']
    )
    
    total_items = len(results["ids"])
    if total_items == 0:
        print(f"Source collection '{source_collection_name}' is empty")
        return new_collection
    
    # Add items in batches
    for i in range(0, total_items, batch_size):
        batch_end = min(i + batch_size, total_items)
        
        # Extract batch data
        batch_ids = results["ids"][i:batch_end]
        batch_embeddings = results["embeddings"][i:batch_end]
        batch_documents = results["documents"][i:batch_end]
        batch_metadatas = results["metadatas"][i:batch_end]
        
        # Add batch to new collection
        new_collection.add(
            ids=batch_ids,
            embeddings=batch_embeddings,
            documents=batch_documents,
            metadatas=batch_metadatas
        )
        
        print(f"Cloned {batch_end}/{total_items} items")
    
    print(f"Collection successfully cloned from '{source_collection_name}' to '{new_collection_name}'")
    return new_collection

[Yuanyuan-Shen]

Please refer to Chroma System Constraints. The last item on the list of constraints: The distance function cannot be changed after collection creation.

The workaround I use is to create a new collection with the distance function I need, and insert the same data. Then delete the previous collection.