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Database / ChromaDB Interview Questions

What is ChromaDB's default embedding function and how does it work?

When you create a collection without specifying an embedding function, ChromaDB uses the SentenceTransformerEmbeddingFunction backed by the all-MiniLM-L6-v2 model from the sentence-transformers library. This model is downloaded automatically on first use and cached locally.

import chromadb
from chromadb.utils import embedding_functions

# Default — uses all-MiniLM-L6-v2 automatically
client = chromadb.Client()
collection_default = client.create_collection("default_embeddings")

# Equivalent explicit usage
ef = embedding_functions.SentenceTransformerEmbeddingFunction(
    model_name="all-MiniLM-L6-v2",  # 384-dim, fast, good English quality
)

# Using a different Sentence Transformer model
ef_large = embedding_functions.SentenceTransformerEmbeddingFunction(
    model_name="all-mpnet-base-v2",  # 768-dim, higher quality, slower
)

collection_large = client.create_collection(
    name="large_model",
    embedding_function=ef_large,
    metadata={"hnsw:space": "cosine"},
)

# You can call embedding functions directly to inspect output
embed = embedding_functions.SentenceTransformerEmbeddingFunction()
vectors = embed(["Hello world", "ChromaDB is great"])
print(len(vectors))      # 2 — one vector per input
print(len(vectors[0]))   # 384 — dimensions

Default model properties
PropertyValue
Model nameall-MiniLM-L6-v2
Output dimensions384
Download size~80 MB (cached after first use)
Library requiredsentence-transformers
Runs onCPU (default) or GPU
StrengthFast, good English semantic similarity
LimitationWeaker on non-English, domain-specific text
What model does ChromaDB use as its default embedding function?
What happens the first time you create a ChromaDB collection with the default embedding function?

More Related questions...

What is ChromaDB and what problem does it solve? What are embeddings and why are they central to how ChromaDB works? What distance metrics does ChromaDB support and how do you choose between them? What is a ChromaDB collection and how do you create, list, get, and delete collections? How do you add documents to a ChromaDB collection? How do you query a ChromaDB collection for similar documents? How do you retrieve, update, and delete specific documents in ChromaDB? How do you filter query results using metadata in ChromaDB? What is the difference between ChromaDB's in-memory and persistent storage modes? What is ChromaDB's default embedding function and how does it work? How do you use the OpenAI embedding function with ChromaDB? How do you use HuggingFace models as embedding functions in ChromaDB? How do you create a custom embedding function for ChromaDB? How does ChromaDB's PersistentClient store data on disk, and what are its limitations? What is the HNSW index in ChromaDB and what parameters can you tune? How do you efficiently add large numbers of documents to ChromaDB using batching? What is the where_document filter in ChromaDB and how does it differ from where? How do you control what data ChromaDB returns in query and get results using include? How do you design metadata schemas for effective filtering in ChromaDB? How do you inspect a ChromaDB collection's contents and configuration? How do you build a basic RAG (Retrieval-Augmented Generation) pipeline with ChromaDB? What are effective document chunking strategies when indexing documents into ChromaDB for RAG? How do you use ChromaDB as a vector store with LangChain? How do you implement multi-tenancy or data isolation in ChromaDB? What is embedding consistency and why is it critical in ChromaDB applications? How do you run ChromaDB as a standalone HTTP server and connect to it from multiple clients? When should you use upsert() instead of add() in ChromaDB, and what are common patterns? What are best practices for structuring ChromaDB collection metadata for production use? How does ChromaDB compare to FAISS, and when should you choose one over the other? What are common ChromaDB errors and how do you handle them in production code? How do you back up and restore a ChromaDB persistent database? How do you ensure the correct embedding function is used when reopening a persistent ChromaDB collection? How do you interpret ChromaDB query distances and convert them into meaningful relevance scores? What are ChromaDB's practical size limits and performance characteristics at scale? How do you use ChromaDB to detect and remove near-duplicate or semantically similar documents? How do you reset or clear a ChromaDB collection without deleting and recreating it? What configuration settings does ChromaDB support and how do you disable telemetry? What is a production readiness checklist for a ChromaDB-based application?
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