{"id":26758252,"url":"https://github.com/ksm26/automated-testing-for-llmops","last_synced_at":"2025-03-28T16:19:01.637Z","repository":{"id":222303180,"uuid":"756860994","full_name":"ksm26/Automated-Testing-for-LLMOps","owner":"ksm26","description":"Create a continuous integration (CI) workflow for testing LLMs applications in an effective way.","archived":false,"fork":false,"pushed_at":"2024-02-14T10:31:53.000Z","size":1208,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2024-02-14T14:58:50.571Z","etag":null,"topics":["automated-testing","circleci","continuous-integration","continuous-integration-workflow","data-evaluation","large-language-models","llmops","llms","model-based-evaluations","role-based-evaluations","software-testing"],"latest_commit_sha":null,"homepage":"https://www.deeplearning.ai/short-courses/automated-testing-llmops/","language":"Jupyter Notebook","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/ksm26.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}},"created_at":"2024-02-13T13:03:28.000Z","updated_at":"2024-02-14T10:30:16.000Z","dependencies_parsed_at":"2024-02-13T15:08:51.607Z","dependency_job_id":null,"html_url":"https://github.com/ksm26/Automated-Testing-for-LLMOps","commit_stats":null,"previous_names":["ksm26/automated-testing-for-llmops"],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ksm26%2FAutomated-Testing-for-LLMOps","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ksm26%2FAutomated-Testing-for-LLMOps/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ksm26%2FAutomated-Testing-for-LLMOps/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ksm26%2FAutomated-Testing-for-LLMOps/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/ksm26","download_url":"https://codeload.github.com/ksm26/Automated-Testing-for-LLMOps/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":246059328,"owners_count":20717085,"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","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":["automated-testing","circleci","continuous-integration","continuous-integration-workflow","data-evaluation","large-language-models","llmops","llms","model-based-evaluations","role-based-evaluations","software-testing"],"created_at":"2025-03-28T16:19:01.039Z","updated_at":"2025-03-28T16:19:01.626Z","avatar_url":"https://github.com/ksm26.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# 🚀 [Automated Testing for LLMOps](https://www.deeplearning.ai/short-courses/automated-testing-llmops/)\n\u003cp align=\"center\"\u003e\n\u003cimg src=\"images/circleci.jpg\" height=\"100\"\u003e \n\u003c/p\u003e\n\n💻 Welcome to the \"Automated Testing for LLMOps\" course! Instructed by Rob Zuber, CTO at CircleCI, this course will teach you how to create a continuous integration (CI) workflow for evaluating your Large Language Model (LLM) applications at every change, enabling faster, safer, and more efficient application development.\n\n**Course Website**: 📚[deeplearning.ai](https://www.deeplearning.ai/short-courses/automated-testing-llmops/)\n\n## Course Summary\nIn this course, you will learn the importance of systematic testing in LLM application development and how to implement a continuous integration workflow to catch issues early. Here's what you can expect to learn and experience:\n\n1. 📋 **Robust LLM Evaluations**: Write robust evaluations covering common problems like hallucinations, data drift, and harmful or offensive output.\n\u003cp align=\"center\"\u003e\n\u003cimg src=\"images/2_3.png\" height=\"400\"\u003e \n\u003c/p\u003e\n\n2. ⚙️ **Continuous Integration Workflow**: Build a CI workflow to automatically evaluate every change to your LLM application.\n\u003cp align=\"center\"\u003e\n\u003cimg src=\"images/3_3.png\" height=\"200\"\u003e \n\u003c/p\u003e\n\n3. 🔄 **Orchestrating CI Workflow**: Orchestrate your CI workflow to run specific evaluations at different stages of development.\n\u003cp align=\"center\"\u003e\n\u003cimg src=\"images/3_1.png\" height=\"400\"\u003e \n\u003c/p\u003e\n\n## Key Points\n- 🧪 Learn how LLM-based testing differs from traditional software testing and implement rules-based testing to assess your LLM application.\n- 📝 Build model-graded evaluations to test your LLM application using an evaluation LLM.\n- 🔄 Automate your evaluations (rules-based and model-graded) using continuous integration tools from CircleCI.\n\n## About the Instructor\n🌟 **Rob Zuber** is the CTO at CircleCI, bringing extensive expertise in software development and continuous integration to guide you through automating testing for LLMOps.\n\n🔗 To enroll in the course or for further information, visit [deeplearning.ai](https://www.deeplearning.ai/short-courses/).\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fksm26%2Fautomated-testing-for-llmops","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fksm26%2Fautomated-testing-for-llmops","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fksm26%2Fautomated-testing-for-llmops/lists"}