SDK reference

Fluiq Python SDK

Two lines of Python instrument any AI agent or LLM pipeline. Auto-traced integrations for OpenAI, Anthropic, Gemini, LangChain, and MCP, plus a @trace decorator for everything else. Server-side security scanning, Redis caching, and LLM-as-judge evaluations are one method call each — all on Fluiq infrastructure, nothing to deploy.

Quickstart

Install the package, grab an API key, and call instrument() once at startup. Every supported LLM call from that point is traced automatically.

Install

Python

pip install fluiq

Get an API key

Create a free account and copy your key from the dashboard. Sign up →

Instrument once at startup

Python

import fluiq

fluiq.instrument(api_key="fl_...") # or set FLUIQ_API_KEY to environment

# Every OpenAI / Anthropic / Gemini / LangChain / MCP
# call from this point on is traced automatically.
# Optionally add paid features:
fluiq.optimize()   # Redis caching — Team+
fluiq.secure()     # Security scanning — Growth+

Next steps

Open the dashboard

Watch traces stream in, inspect costs by node, and review quality scores.

Go to dashboard

Add the eval gate

Gate every PR on hallucination, faithfulness, and relevancy thresholds.

See eval gate setup

Enable optimization

One method call activates Redis caching driven by your trace history.

Upgrade to Team

Manage prompts

Discover, edit, evaluate, and promote prompt templates to dev, staging, and production.

Open Prompts