Auto-instrument every ChromaDB collection operation, query, add, update, get, with zero code changes. Chroma spans integrate as child spans inside LangChain traces for complete RAG observability.
Free tier · No credit card · 2-minute setup
Every collection.query() call is traced with the query text, n_results, where filters, and end-to-end latency including embedding generation time.
Chroma spans automatically appear as children inside LangChain traces, full end-to-end RAG pipeline visibility without extra code.
Document addition, update, and deletion operations are traced with record counts and timing, monitor ingestion performance alongside query performance.
import fluiq
fluiq.instrument(api_key="fl_...") # patches ChromaDB automatically
import chromadb
client = chromadb.PersistentClient(path="./chroma_db")
collection = client.get_or_create_collection("my-docs")
# Add is traced with record count:
collection.add(
documents=["LLM observability is critical for production AI"],
ids=["doc1"],
metadatas=[{"source": "guide"}],
)
# Query is traced with latency and result count:
results = collection.query(
query_texts=["What is LLM monitoring?"],
n_results=5,
)Every call to these methods is automatically traced, no decorators, no wrappers, no manual spans.
Collection.query()Collection.add()Collection.update()Collection.upsert()Collection.get()Collection.delete()Collection.count()Client.create_collection()Free tier. No credit card. Full traces, security scanning, and evals on your first Chroma call.
50,000 free traces / month · 1,000 evals / month · 14-day retention