vikrantvikaasa27/jev-gaurdrails
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CommunityJev Integrations & Adapters
Jev Guardrails — vikrantvikaasa27
Drop-in guardrails for any AI app, powered by Jev: it asks narrow yes/no questions about text, such as whether something is a prompt injection, gets a probability, and lets the app allow, review or block in milliseconds, with adapters for Gemini, Anthropic, OpenAI and FastAPI.
- Stars
- 0
- Language
- Python
- Reading time
- 2 min
- Published by
- Community
- Author
- vikrantvikaasa27
- Last verified
- Oct 2026
This is one of several Jev listings for the same project. The canonical entry is Jev Guardrails — deepansh-saxena.
- Languages
- Python
- Capabilities
- Open sourceRequires API key
Highlights
- Jev answers narrow yes/no questions about text, like whether something is a prompt injection, returning a probability instead of a generated judgment.
- Provider adapters guard_gemini, guard_anthropic and guard_openai raise GuardrailBlocked with a label and score, for example prompt_injection (0.99).
- A @protect() decorator wraps any prompt-to-reply function, and a FastAPI middleware answers 400 when a request is blocked.
- Install with pip install -e plus an extra such as [gemini], [anthropic] or [openai], or no extra for the core; keys are TYPESAFE_API_KEY or JEV_API_KEY in .env.
Quickstart
python
from jev_guardrails import protect
@protect()
def ask(prompt: str) -> str:
return my_llm(prompt)Watch out
README reviewed 2026-10-17; the digest ends mid-import in the FastAPI middleware example, so its full setup is not visible. No benchmarks, latency measurements or pricing appear in the captured text; the repo name jev-gaurdrails carries a typo, has 0 stars and lists no license.
Questions about this entry
Short answers drawn from the linked project or page.
A Python package of drop-in guardrails for any AI app, powered by Jev: it answers narrow yes/no questions about text with a probability so the app can allow, review or block.
It answers questions like whether the text is a prompt injection with a probability, with no LLM prompting or output parsing; the README's blocked example shows prompt_injection at 0.99.
Gemini through guard_gemini, Anthropic through guard_anthropic, and OpenAI through guard_openai, all under jev_guardrails.adapters; everything else on the client works as before.
Yes: decorate any prompt-to-reply function with @protect(), and blocked input raises GuardrailBlocked so you can catch it and inspect the reason.
Yes, a middleware checks the request and answers 400 if it is blocked; the captured excerpt cuts off mid-import, so the complete setup code is not visible in the digest.
Run pip install -e with one extra such as gemini, anthropic or openai, or no extra for the core; then put TYPESAFE_API_KEY or JEV_API_KEY in your .env file.
No evidence of that: it links to docs.typesafe.ai and is powered by Jev, but it is a personal repository under vikrantvikaasa27 with 0 stars, no license listed, and a README that the digest captures only in part.
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