repoGitHubTrust 82 · PrimaryPublished 1mo agoLive · 1mo ago
promptfoo/promptfoo-action
The GitHub Action for Promptfoo. Test your prompts, agents, and RAGs. AI Red teaming, pentesting, and vulnerability scanning for LLMs. Compare performance of GPT, Claude, Gemini, Llama, and more. Simple declarative configs with command line and CI/CD integration.
Lineage graph
Paper → model → repo connections mined from source citations (Tier-1 exact match).
Why these links exist
Every edge carries a method, confidence, and the source snippet that justified it — so bad links are debuggable.
- PossiblePossibly related (embedding) · 66%PromptLab →
- PossiblePossibly related (embedding) · 56%A system-level approach to prompt injection: separating instruction and data channels in LLM agents [P] →
- PossiblePossibly related (embedding) · 49%Test solution uses agentic AI to turn natural language prompts into customized instruments - Military Embedded Systems →
- PossiblePossibly related (embedding) · 48%Show HN: Bash4LLM+ – A lightweight, dependency-free Bash wrapper for LLM APIs →
- PossiblePossibly related (embedding) · 48%Defending against Prompt Injection with Structured Queries (StruQ) and Preference Optimization (SecAlign) →
Related to
Covers
newsA system-level approach to prompt injection: separating instruction and data channels in LLM agents [P]newsTest solution uses agentic AI to turn natural language prompts into customized instruments - Military Embedded SystemsnewsShow HN: Bash4LLM+ – A lightweight, dependency-free Bash wrapper for LLM APIsnewsDefending against Prompt Injection with Structured Queries (StruQ) and Preference Optimization (SecAlign)
Related across the graph
newsDefending against Prompt Injection with Structured Queries (StruQ) and Preference Optimization (SecAlign)toolPromptLabnewsShow HN: Bash4LLM+ – A lightweight, dependency-free Bash wrapper for LLM APIsnewsTest solution uses agentic AI to turn natural language prompts into customized instruments - Military Embedded SystemsnewsA system-level approach to prompt injection: separating instruction and data channels in LLM agents [P]