framework · open source
AI Evaluation & Red Teaming with Python
AI Evaluation & Red Teaming built on Python, chosen where it genuinely fits, and swapped where it does not.
- Category
- framework
- Vendor
- Open source
- Alternatives we also use
- 6
Why Python for this
Prompt injection is not theoretical once your system reads untrusted content, email, web pages, uploaded documents are all attack surface.
Python is strongest at the entire ML ecosystem lives here. For ai evaluation & red teaming that matters because the failure modes of this kind of system tend to cluster exactly there.
The honest trade-off: for high-concurrency web services, TypeScript or Go usually serve better. We say that up front because a stack chosen for fashion rather than fit becomes someone's migration project two years later. We start from the constraint, not the capability, what the system must never do, who signs off, and what happens when it is wrong.
You own the code, the models where they are open-weight, and the documentation to run it without us.
The honest assessment
- What it is
- The default language for data, machine learning and model work.
- Strongest at
- the entire ML ecosystem lives here
- Trade-off
- for high-concurrency web services, TypeScript or Go usually serve better
- Category
- framework
We are not a reseller for Python and hold no commission on this choice. Where a different option fits your workload better, the recommendation will say so. That is the entire value of asking us.
What is included
- Evaluation set built from your real domain
- Adversarial prompts including injection and jailbreak attempts
- Hallucination rate measured, not estimated
- Bias testing where the use case warrants it
- Regression suite wired into your CI
- Findings report with severity and remediation
Questions
What is prompt injection?
An attack where instructions hidden in content the model reads, an email, a web page, an uploaded file, override your intended behaviour. It matters the moment your system processes anything a user or third party supplies.
How do you measure hallucination?
Against a labelled question set from your domain with verified answers, reported as a rate rather than an impression.
Do we need this if we use a major provider?
Yes. Provider safety training covers general misuse; it knows nothing about your specific tools, data and permissions, which is where the real risk sits.
Alternatives for ai evaluation & red teaming
Same capability, different stack. Each page states its own trade-off.
Building with Python?
Bring us the workload and we will tell you whether this is the right stack for it.
Or email bd@dtrasglobal.com · call +91 74118 77878