[{"data":1,"prerenderedAt":134},["ShallowReactive",2],{"ki-evidenznetz-dossier-package-pypi-langchain-community-ee8a8d54":3},{"edges":4,"entity":35,"fingerprint":56,"generatedAt":57,"neighbors":58,"schemaVersion":133},[5,17,23,29],{"evidence":6,"evidenceClass":11,"from":12,"id":13,"observedAt":14,"relation":15,"to":16},{"dataset":7,"field":8,"sourceId":9,"url":10},"german-public-sector-ai-dependency-atlas","repository_commit_manifest_package_identity","opencode:8742@cd6b854b1b400d7e45796aaa22bded8183642916:pypi:langchain-community","https:\u002F\u002Fgitlab.opencode.de\u002Fdatenlabor-bmz\u002Fai-websearch-benchmark\u002F-\u002Fcommit\u002Fcd6b854b1b400d7e45796aaa22bded8183642916","exact","opencode:8742","edge:018c3aa2af5ed765ae980534","2026-07-21T08:58:16.708Z","declares_dependency","package:pypi:langchain-community",{"evidence":18,"evidenceClass":11,"from":21,"id":22,"observedAt":14,"relation":15,"to":16},{"dataset":7,"field":8,"sourceId":19,"url":20},"opencode:7202@a41841d96e875b74c63cac3dc40a91247a959be4:pypi:langchain-community","https:\u002F\u002Fgitlab.opencode.de\u002Flandeshauptstadt-muenchen\u002Fmucgpt\u002F-\u002Fcommit\u002Fa41841d96e875b74c63cac3dc40a91247a959be4","opencode:7202","edge:241d268ffdf8dda92487c73e",{"evidence":24,"evidenceClass":11,"from":27,"id":28,"observedAt":14,"relation":15,"to":16},{"dataset":7,"field":8,"sourceId":25,"url":26},"opencode:4166@8c26aa4fed1fcb1be4ecfbbf745144dbf812e4be:pypi:langchain-community","https:\u002F\u002Fgitlab.opencode.de\u002Fiorb\u002Fai-legal-graph\u002F-\u002Fcommit\u002F8c26aa4fed1fcb1be4ecfbbf745144dbf812e4be","opencode:4166","edge:59da170e269c7bb811991ea9",{"evidence":30,"evidenceClass":11,"from":33,"id":34,"observedAt":14,"relation":15,"to":16},{"dataset":7,"field":8,"sourceId":31,"url":32},"opencode:4609@fddd886ab2fd3824e269d40cefde90cbed709201:pypi:langchain-community","https:\u002F\u002Fgitlab.opencode.de\u002Fbbsr_ida_public\u002Fllm_workshop\u002F-\u002Fcommit\u002Ffddd886ab2fd3824e269d40cefde90cbed709201","opencode:4609","edge:7ab96b652066cbf38845a233",{"attributes":36,"edgeCount":37,"id":16,"indexable":44,"label":45,"links":46,"slug":51,"sourceRefs":52,"type":55},{"advisoryCount":37,"category":38,"ecosystem":39,"identity":40,"licenseExpressions":41,"occurrenceCount":37,"provider":43,"repositoryCount":37},4,"orchestration","pypi","pypi:langchain-community",[42],"MIT",null,true,"LangChain Community",[47],{"kind":48,"label":49,"url":50},"local_dossier","KI-Abhängigkeitsatlas","\u002Ftools\u002Fki-abhaengigkeitsatlas\u002Fpaket\u002Flangchain-community-b296254c\u002F","package-pypi-langchain-community-ee8a8d54",[53],{"dataset":7,"field":54,"sourceId":40},"package_ecosystem_identity","package","sha256:745e8e363e5fdfc3f14183e2879442ce71a77c4479b0014d27959f92d68262ed","2026-07-21T08:59:15.288Z",[59,84,101,117],{"attributes":60,"description":65,"edgeCount":61,"id":12,"indexable":44,"label":64,"links":66,"slug":77,"sourceRefs":78,"type":83},{"aiPackageCount":61,"commitSha":62,"lastActivityAt":63,"pathWithNamespace":64,"treeComplete":44},9,"cd6b854b1b400d7e45796aaa22bded8183642916","2026-05-07T14:25:51.430Z","datenlabor-bmz\u002Fai-websearch-benchmark","Small vibecoded benchmark meant as a smoke test for search API results.",[67,71,74],{"kind":68,"label":69,"url":70},"official_source","openCode","https:\u002F\u002Fgitlab.opencode.de\u002Fdatenlabor-bmz\u002Fai-websearch-benchmark",{"kind":72,"label":73,"url":10},"snapshot","Commit",{"kind":48,"label":75,"url":76},"KI-Code-Radar","\u002Ftools\u002Fki-code-radar\u002Frepository\u002Fopencode-8742\u002F","repository-opencode-8742-ca1c9770",[79],{"dataset":80,"field":81,"fingerprint":82,"sourceId":12,"url":10},"german-public-sector-ai-code-radar","opencode_project_id_and_commit","git:cd6b854b1b400d7e45796aaa22bded8183642916","repository",{"attributes":85,"description":90,"edgeCount":86,"id":21,"indexable":44,"label":89,"links":91,"slug":97,"sourceRefs":98,"type":83},{"aiPackageCount":86,"commitSha":87,"lastActivityAt":88,"pathWithNamespace":89,"treeComplete":44},10,"a41841d96e875b74c63cac3dc40a91247a959be4","2026-07-20T21:53:50.345Z","landeshauptstadt-muenchen\u002Fmucgpt","MUCGPT ist ein KI-Werkzeug zur Arbeit mit großen Sprachmodellen und bietet u.a. personalisierbare Assistenten und Tools an.\r\nDies ist ein Readonly-Mirror, die Entwicklung findet auf GitHub statt: https:\u002F\u002Fgithub.com\u002Fit-at-m\u002Fmucgpt",[92,94,95],{"kind":68,"label":69,"url":93},"https:\u002F\u002Fgitlab.opencode.de\u002Flandeshauptstadt-muenchen\u002Fmucgpt",{"kind":72,"label":73,"url":20},{"kind":48,"label":75,"url":96},"\u002Ftools\u002Fki-code-radar\u002Frepository\u002Fopencode-7202\u002F","repository-opencode-7202-be810caa",[99],{"dataset":80,"field":81,"fingerprint":100,"sourceId":21,"url":20},"git:a41841d96e875b74c63cac3dc40a91247a959be4",{"attributes":102,"edgeCount":103,"id":27,"indexable":44,"label":106,"links":107,"slug":113,"sourceRefs":114,"type":83},{"aiPackageCount":103,"commitSha":104,"lastActivityAt":105,"pathWithNamespace":106,"treeComplete":44},8,"8c26aa4fed1fcb1be4ecfbbf745144dbf812e4be","2025-04-10T15:29:54.353Z","iorb\u002Fai-legal-graph",[108,110,111],{"kind":68,"label":69,"url":109},"https:\u002F\u002Fgitlab.opencode.de\u002Fiorb\u002Fai-legal-graph",{"kind":72,"label":73,"url":26},{"kind":48,"label":75,"url":112},"\u002Ftools\u002Fki-code-radar\u002Frepository\u002Fopencode-4166\u002F","repository-opencode-4166-0f67d70f",[115],{"dataset":80,"field":81,"fingerprint":116,"sourceId":27,"url":26},"git:8c26aa4fed1fcb1be4ecfbbf745144dbf812e4be",{"attributes":118,"description":122,"edgeCount":103,"id":33,"indexable":44,"label":121,"links":123,"slug":129,"sourceRefs":130,"type":83},{"aiPackageCount":103,"commitSha":119,"lastActivityAt":120,"pathWithNamespace":121,"treeComplete":44},"fddd886ab2fd3824e269d40cefde90cbed709201","2025-05-02T11:59:04.875Z","bbsr_ida_public\u002Fllm_workshop","This repository accompanies a three-day hands-on workshop on Large Language Models (LLMs), Prompt Engineering, and Retrieval-Augmented Generation (RAG). The workshop is designed to equip participants with practical skills and foundational knowledge to understand, deploy, and evaluate LLM-based applications across a wide range of fields.\r\nThe program combines a lecture series covering theoretical foundations with a programming workshop in Jupyter Notebooks. Participants explore core technologies such as OpenAI APIs, LangChain, vector databases, document parsing, and AI toolchains—supported by real-world examples and scientific documents.\r\nThe workshop is suitable for professionals, researchers, and students who seek a structured and practice-oriented introduction to state-of-the-art AI workflows based on LLMs.",[124,126,127],{"kind":68,"label":69,"url":125},"https:\u002F\u002Fgitlab.opencode.de\u002Fbbsr_ida_public\u002Fllm_workshop",{"kind":72,"label":73,"url":32},{"kind":48,"label":75,"url":128},"\u002Ftools\u002Fki-code-radar\u002Frepository\u002Fopencode-4609\u002F","repository-opencode-4609-5f31378f",[131],{"dataset":80,"field":81,"fingerprint":132,"sourceId":33,"url":32},"git:fddd886ab2fd3824e269d40cefde90cbed709201","ki-evidenznetz.entity.v1",1784624715786]