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Database / ChromaDB Interview Questions

How do you add documents to a ChromaDB collection?

The collection.add() method inserts items into a collection. Each item requires a unique id. You can provide raw documents (strings) and let ChromaDB embed them, or supply pre-computed embeddings directly. Optional metadatas store filterable key-value pairs alongside each document.

import chromadb

client = chromadb.Client()
collection = client.create_collection("articles")

# Basic add — ChromaDB embeds documents automatically
collection.add(
    documents=[
        "ChromaDB is an open-source vector database.",
        "Retrieval-augmented generation improves LLM accuracy.",
        "Python is a popular language for data science.",
    ],
    ids=["art-001", "art-002", "art-003"],
)

# Add with metadata — enables filtered queries later
collection.add(
    documents=[
        "FastAPI is a modern Python web framework.",
        "React is a JavaScript library for building UIs.",
    ],
    metadatas=[
        {"source": "docs", "category": "backend",  "year": 2024},
        {"source": "docs", "category": "frontend", "year": 2024},
    ],
    ids=["art-004", "art-005"],
)

# Add pre-computed embeddings (skip ChromaDB's embedding step)
import numpy as np
collection_custom = client.create_collection(
    "custom_embeddings",
    metadata={"hnsw:space": "cosine"},
)
collection_custom.add(
    embeddings=[
        [0.1, 0.5, -0.3, 0.8],  # must match embedding_function dimension
        [0.4, 0.2,  0.9, -0.1],
    ],
    documents=["Doc A", "Doc B"],  # stored as-is for retrieval
    ids=["e-1", "e-2"],
)

ID rules: IDs must be strings, must be unique within the collection, and must not be empty. Adding a duplicate ID raises a chromadb.errors.IDAlreadyExistsError.

What happens if you call collection.add() with an ID that already exists in the collection?
When would you pass embeddings= instead of documents= to collection.add()?

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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