{"id":19308835,"url":"https://github.com/balavenkatesh3322/guardrails-demo","last_synced_at":"2025-10-31T08:36:04.248Z","repository":{"id":218323043,"uuid":"745459202","full_name":"balavenkatesh3322/guardrails-demo","owner":"balavenkatesh3322","description":"LLM Security Project with Llama Guard","archived":false,"fork":false,"pushed_at":"2024-02-18T07:30:46.000Z","size":57,"stargazers_count":10,"open_issues_count":0,"forks_count":0,"subscribers_count":2,"default_branch":"master","last_synced_at":"2025-06-27T02:42:12.028Z","etag":null,"topics":["aisecurity","attack-defense","generative-ai","llama-2","llama-guard","llm","llm-security","llmops","prompt-injection-tool","security"],"latest_commit_sha":null,"homepage":"","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/balavenkatesh3322.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2024-01-19T11:32:57.000Z","updated_at":"2025-02-14T16:40:19.000Z","dependencies_parsed_at":"2024-02-01T09:28:41.797Z","dependency_job_id":"6c9d0926-d1ae-4d56-b7b8-66b9de02eab9","html_url":"https://github.com/balavenkatesh3322/guardrails-demo","commit_stats":null,"previous_names":["balavenkatesh3322/guardrails-demo"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/balavenkatesh3322/guardrails-demo","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/balavenkatesh3322%2Fguardrails-demo","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/balavenkatesh3322%2Fguardrails-demo/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/balavenkatesh3322%2Fguardrails-demo/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/balavenkatesh3322%2Fguardrails-demo/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/balavenkatesh3322","download_url":"https://codeload.github.com/balavenkatesh3322/guardrails-demo/tar.gz/refs/heads/master","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/balavenkatesh3322%2Fguardrails-demo/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":272466814,"owners_count":24939465,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","status":"online","status_checked_at":"2025-08-28T02:00:10.768Z","response_time":74,"last_error":null,"robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":true,"can_crawl_api":true,"host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["aisecurity","attack-defense","generative-ai","llama-2","llama-guard","llm","llm-security","llmops","prompt-injection-tool","security"],"created_at":"2024-11-10T00:16:38.232Z","updated_at":"2025-10-31T08:36:04.146Z","avatar_url":"https://github.com/balavenkatesh3322.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# LLM Security Project with Llama Guard\n\nThis repository provides a quick and easy way to run the Llama Guard application on your local machine and explore LLM security.\n\n## What is Llama Guard?\n\nLlama Guard is a defensive framework designed to detect and mitigate potential security risks associated with Large Language Models (LLMs). It helps developers and researchers build safer and more reliable LLM applications.\n\n\n## What's included?\n\nNemo Guardrail Implementation: The llama-guard folder contains a NeMo Guardrail implementation, offering flexibility and customization for your specific needs.\nStreamlit Applications: Two Streamlit applications are provided for convenient testing:\nllama-guard-only.py: Test input prompts and responses directly with Llama Guard.\nllama_2_with_llama-guard.py: Run Llama Guard with the pre-trained Llama 2 13b model for real-world testing.\n\n## How to run the application:\n\n- Clone this repository\n- Install dependencies: pip install -r requirements.txt\n- Run the desired application:\n  1. Test Llama Guard: streamlit run llama-guard-only.py\n  2. Test with Llama 2 13b: streamlit run llama_2_with_llama-guard.py\n\n\n## Learn More:\n\nBlog post: Deepen your understanding of Llama Guard and LLM security with this informative blog post: https://balavenkatesh.medium.com/securing-tomorrows-ai-world-today-llama-guard-defensive-strategies-for-llm-application-c29a87ba607f\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fbalavenkatesh3322%2Fguardrails-demo","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fbalavenkatesh3322%2Fguardrails-demo","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fbalavenkatesh3322%2Fguardrails-demo/lists"}