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Data Analyst & AI Developer turning messy problems into clean solutions. From data pipelines to deployed LLM apps — I build things that actually ship.
pytest plugin for behavioral testing of LLM applications
Stop using LLMs to judge LLMs. llm-behave brings semantic assertions, tone detection, and drift detection to your CI pipeline — all with an offline 80MB model. No API costs. No circular dependencies.
response.mentions("refund") understands meaning, not just strings
response.tone("professional") without an LLM judge
# Install the library
$ pip install llm-behave[semantic]
# Write semantic tests, not string matchers
def test_support_response(llm):
response = llm.ask(
"How do I get a refund?"
)
# Understands meaning, not just words
assert response.mentions("refund policy")
assert response.tone("professional")
assert response.intent("helpful")
# Detect drift across model updates
def test_no_regression(drift):
drift.assert_consistent(baseline="v1.json")
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I'm a Data Analyst and AI Developer based in India. My work sits at the intersection of data engineering and applied AI — I build tools that go from prototype to production, not just notebooks that sit on GitHub.
I started in financial analytics and moved into AI-powered solutions. Today I maintain llm-behave (an open source testing library for LLM apps), run 3 production applications with real users, and help businesses automate their data workflows.
Actively looking for full-time roles in data analytics and AI. Also open to freelance projects and interesting collaborations — data analysis, AI solutions, process automation.