{"data":{"slug":"relari-ai-continuous-eval","name":"continuous-eval","tagline":"Data-Driven Evaluation for LLM-Powered Applications","github_url":"https://github.com/relari-ai/continuous-eval","owner":"relari-ai","repo":"continuous-eval","owner_avatar_url":"https://avatars.githubusercontent.com/u/135984758?v=4","primary_language":"Python","stars":515,"forks":38,"topics":["evaluation-framework","evaluation-metrics","information-retrieval","llm-evaluation","llmops","rag","retrieval-augmented-generation"],"archived":false,"github_pushed_at":"2026-08-10T22:12:03+00:00","maintenance_label":"Active","stars_delta_30d":-1,"url":"https://www.graphcanon.com/tools/relari-ai-continuous-eval","markdown_url":"https://www.graphcanon.com/tools/relari-ai-continuous-eval.md","api_url":"https://www.graphcanon.com/api/graphcanon/tools/relari-ai-continuous-eval","graph_url":"https://www.graphcanon.com/api/graphcanon/graph?tool=relari-ai-continuous-eval","description":"Data-Driven Evaluation for LLM-Powered Applications","homepage_url":"https://continuous-eval.docs.relari.ai/","license":"Apache-2.0","open_issues":14,"watchers":5,"ai_summary":"A Python-based framework for evaluating large language models with features like evaluation metrics and information retrieval.","readme_excerpt":"## Getting Started\n\nThis code is provided as a PyPi package. To install it, run the following command:\n\n```bash\npython3 -m pip install continuous-eval\n```\n\nif you want to install from source:\n\n```bash\ngit clone https://github.com/relari-ai/continuous-eval.git && cd continuous-eval\npoetry install --all-extras\n```\n\nTo run LLM-based metrics, the code requires at least one of the LLM API keys in `.env`. Take a look at the example env file `.env.example`.\n\n---\n\n## License\n\nThis project is licensed under the Apache 2.0 - see the [LICENSE](LICENSE) file for details.","github_created_at":"2023-12-08T21:30:39+00:00","created_at":"2026-07-07T17:43:30.040863+00:00","updated_at":"2026-08-21T06:01:41.708433+00:00","categories":[{"slug":"data-retrieval","name":"Data & Retrieval","url":"https://www.graphcanon.com/categories/data-retrieval","markdown_url":"https://www.graphcanon.com/categories/data-retrieval.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/data-retrieval"},{"slug":"evaluation-observability","name":"Evaluation & Observability","url":"https://www.graphcanon.com/categories/evaluation-observability","markdown_url":"https://www.graphcanon.com/categories/evaluation-observability.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/evaluation-observability"}],"tags":[{"slug":"evaluation-framework","name":"evaluation-framework"},{"slug":"evaluation-metrics","name":"evaluation-metrics"},{"slug":"information-retrieval","name":"information-retrieval"},{"slug":"llm-evaluation","name":"llm-evaluation"},{"slug":"llmops","name":"llmops"},{"slug":"rag","name":"rag"},{"slug":"retrieval-augmented-generation","name":"retrieval-augmented-generation"}],"trust":{"provenance":{"is_fork":false,"github_id":729307404,"owner_type":"Organization","methodology":"github_public_v1","parent_repo":null,"near_duplicate_slugs":[]},"computed_at":"2026-08-21T06:01:40.612Z","maintenance":{"label":"Active","score":82,"methodology":"github_public_v1","releases_90d":0,"days_since_push":10,"last_release_at":"2025-01-10T19:54:47Z","stars_delta_30d":-1,"open_issues_delta_30d":2},"security_summary":{"status":"no_lockfile","scanner":null,"low_count":0,"high_count":0,"last_scan_at":"2026-07-11T11:23:48.629Z","medium_count":0,"scan_profile":"none","critical_count":0}},"capability_facts":{"scan":{"source":"repo_scan","observed_at":"2026-08-21T06:01:41.255Z"},"languages":{"value":["python"],"source":"github.language+pyproject.toml","observed_at":"2026-08-21T06:01:41.255Z"},"license_spdx":{"value":"Apache-2.0","source":"github.license","observed_at":"2026-08-21T06:01:41.255Z"}},"decision_facts":{"hosting":null,"pricing":{"model":"freemium","summary":"The framework itself is open source and free to use, but enhanced or enterprise features may require additional cost."},"requirements":{"min_ram_gb":4,"requires_docker":false},"constraints":{"min_ram_gb":4,"pricing_model":"freemium","requires_docker":false},"when_to_use":["When developing LLM-powered applications where a continuous evaluation of model performance over time is required.","For projects needing integration of real-time data-driven insights to improve the reliability and effectiveness of language models."],"when_not_to_use":["If your project strictly focuses on small scale or simple applications that do not require robust evaluation metrics or information retrieval features.","When working in environments where Python is not preferred, as continuous-eval is specifically built for Python applications."],"source":"enrich:decision_facts","observed_at":"2026-07-14T21:28:28.586Z"},"constraint_facets":{"min_ram_gb":4,"pricing_model":"freemium","requires_docker":false},"decision_summary":[{"label":"Pricing","value":"freemium - The framework itself is open source and free to use, but enhanced or enterprise features may require additional cost."},{"label":"Requirements","value":"Min 4 GB RAM"},{"label":"Adopt for","value":"Continuous-eval is a Python framework for evaluating large language models, with emphasis on evaluation metrics and information retrieval."},{"label":"License detail","value":"Continuous-eval is available under the Apache-2.0 license, allowing free use with attribution and no warranty provided by the authors."}]}}