{"data":{"slug":"lazyagi-lazyllm","name":"LazyLLM","tagline":"Easiest and laziest way for building multi-agent LLMs applications.","github_url":"https://github.com/LazyAGI/LazyLLM","owner":"LazyAGI","repo":"LazyLLM","owner_avatar_url":"https://avatars.githubusercontent.com/u/171651681?v=4","primary_language":"Python","stars":3866,"forks":404,"topics":["agents","ai-agent","data","deep-learning","documentation-tool","finetuning","framework","knowlege-graph","langchain","lazyllm","llamaindex","llm","llms","rag"],"archived":false,"github_pushed_at":"2026-08-07T03:03:46+00:00","maintenance_label":"Very active","url":"https://www.graphcanon.com/tools/lazyagi-lazyllm","markdown_url":"https://www.graphcanon.com/tools/lazyagi-lazyllm.md","api_url":"https://www.graphcanon.com/api/graphcanon/tools/lazyagi-lazyllm","graph_url":"https://www.graphcanon.com/api/graphcanon/graph?tool=lazyagi-lazyllm","description":"Easiest and laziest way for  building multi-agent LLMs applications.","homepage_url":"https://docs.lazyllm.ai/","license":"Apache-2.0","open_issues":41,"watchers":149,"ai_summary":"LazyLLM is a framework aimed at simplifying the process of creating multi-agent LLM applications, focusing on ease of use through streamlined installation processes.","readme_excerpt":"### pip installation (recommended)\n\nTo install only lazyllm and necessary dependencies, you can use:\n```bash\npip3 install lazyllm\n```\n\nTo install lazyllm and all dependencies, you can use:\n```bash\npip3 install lazyllm\nlazyllm install full\n```\n\n---\n\n### Installation from source\n\n```bash\ngit clone git@github.com:LazyAGI/LazyLLM.git\ncd LazyLLM\npip install -r requirements.txt\n```\n\n---\n\n### Installation on Windows or macOS\n\nFor installation on Windows or macOS, please refer to our [tutorial](https://docs.lazyllm.ai/zh-cn/stable/Home/environment)","github_created_at":"2024-06-04T05:01:45+00:00","created_at":"2026-07-11T10:41:30.423056+00:00","updated_at":"2026-08-08T00:00:43.245624+00:00","categories":[{"slug":"ai-agents","name":"AI Agents","url":"https://www.graphcanon.com/categories/ai-agents","markdown_url":"https://www.graphcanon.com/categories/ai-agents.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/ai-agents"},{"slug":"model-training","name":"Model Training","url":"https://www.graphcanon.com/categories/model-training","markdown_url":"https://www.graphcanon.com/categories/model-training.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/model-training"}],"tags":[{"slug":"agents","name":"agents"},{"slug":"ai-agent","name":"ai-agent"},{"slug":"deep-learning","name":"deep-learning"},{"slug":"framework","name":"framework"},{"slug":"llm","name":"llm"},{"slug":"multi-agent","name":"multi-agent"}],"trust":{"provenance":{"is_fork":false,"github_id":810121174,"owner_type":"Organization","methodology":"github_public_v1","parent_repo":null,"near_duplicate_slugs":[]},"computed_at":"2026-08-08T00:00:42.360Z","maintenance":{"label":"Very active","score":96,"methodology":"github_public_v1","releases_90d":9,"days_since_push":0,"last_release_at":"2026-08-02T15:29:23Z"},"security_summary":{"status":"findings","scanner":"osv@v1","low_count":31,"high_count":0,"last_scan_at":"2026-07-11T10:41:32.027Z","medium_count":0,"scan_profile":"deps","critical_count":0}},"capability_facts":{"scan":{"source":"repo_scan","observed_at":"2026-08-08T00:00:42.896Z"},"has_cli":{"value":true,"source":"pyproject.toml:[project.scripts]","observed_at":"2026-08-08T00:00:42.896Z"},"languages":{"value":["python"],"source":"github.language+pyproject.toml","observed_at":"2026-08-08T00:00:42.896Z"},"license_spdx":{"value":"Apache-2.0","source":"github.license","observed_at":"2026-08-08T00:00:42.896Z"}},"decision_facts":{"hosting":null,"pricing":{"model":"freemium","summary":"LazyLLM is open-source under the Apache-2.0 license, making it free to use for both personal and commercial projects."},"requirements":{"notes":["Installation can be done via pip or from source. No Docker required, but a Python environment is necessary."],"min_ram_gb":8,"requires_docker":false},"constraints":{"min_ram_gb":8,"pricing_model":"freemium","requires_docker":false},"when_to_use":["- When you need a highly user-friendly framework specifically designed for building multi-agent LLM applications, emphasizing simplicity and streamlined installation.","- If your project requires leveraging deep learning techniques with minimal setup hassles, as LazyLLM aims to provide an ease-of-use experience that competitors might not match."],"when_not_to_use":["- Avoid if you require extensive customization options or a more complex framework; LazyLLM's focus on being the 'laziest' way may mean it lacks advanced or specialized features found in other tools.","- If you are working with non-Python environments, as LazyLLM is specifically language-oriented towards Python. Users needing cross-language support might not find LazyLLM suitable."],"source":"enrich:decision_facts","observed_at":"2026-07-12T10:15:59.527Z"},"constraint_facets":{"min_ram_gb":8,"pricing_model":"freemium","requires_docker":false},"decision_summary":[{"label":"Pricing","value":"freemium - LazyLLM is open-source under the Apache-2.0 license, making it free to use for both personal and commercial projects."},{"label":"Requirements","value":"Min 8 GB RAM; Installation can be done via pip or from source. No Docker required, but a Python environment is necessary."},{"label":"Adopt for","value":"Critical facts for LazyLLM"}]}}