agenticlens 0.1.0

Profile, analyze, and optimize token consumption in LLM-powered applications and agentic workflows.

AgenticLens

An open-source profiler for AI agents that analyzes token usage, cost, latency, and optimization opportunities across LLM workflows.

Status: early scaffold. Core data models, provider abstraction, and the explicit profile()/step() instrumentation API are in place. The recommendation engine's heuristic rules are not yet implemented — see AgenticLens_Spec.md.

Install (development)

uv sync --extra dev

Usage

from agenticlens import profile, step

with profile("Customer Support"):
    with step("Planner", type="planner") as s:
        response = planner_llm.invoke(prompt)
        s.record(response)

Development

uv run pytest          # tests
uv run ruff check .    # lint
uv run ruff format .   # format
uv run mypy            # type check

See AgenticLens_Spec.md for the full project specification and ROADMAP.md for what's planned beyond the MVP.