04. ChromaDB Collections

Chapter 4 of 18 · 20 min

KEY INSIGHT

A collection is a container for related documentsâ€”think of it as a table in SQL, but for vectors. Collections hold documents, their embeddings, and metadata. Each collection has a name and a specific embedding function. All documents in a collection use the same embedding model. ```python import chromadb from chromadb.config import Settings client = chromadb.PersistentClient(path="./chroma_db") # Create a collection collection = client.create_collection( name="articles", metadata={"description": "Technical articles about programming"} ) print(f"Collection ID: {collection.id}") print(f"Collection name: {collection.name}") ``` If a collection with that name already exists, `create_collection` raises an error. Use `get_or_create_collection` instead: ```python # Safe: gets existing or creates new collection = client.get_or_create_collection( name="articles", metadata={"description": "Technical articles about programming"} ) ``` Listing and inspecting collections: ```python # List all collections all_collections = client.list_collections() for col in all_collections: print(f"Name: {col.name}, ID: {col.id}, Count: {col.count()}") ``` Output: ``` Name: articles, ID: 1a2b3c4d..., Count: 0 Name: support_tickets, ID: 5e6f7g8h..., Count: 1523 ``` Deleting a collection is permanent and immediate: ```python client.delete_collection(name="articles") ```

Local verification checkpoint

Run the smallest example from this chapter in a local workspace and record the package version, runtime, data path, and observed output. If the result depends on model size, vector count, CPU/GPU backend, or available memory, note that constraint beside the exercise so the lesson remains reproducible.

Local verification checkpoint

EXERCISE

Create three collections with different names. List them, verify they exist, then delete two of them. Confirm only one remains.