{"adoption": {"forks": 3076, "observed_at": "2026-08-28T04:11:32.248337+00:00", "stars": 21995}, "canonical_url": "https://ross.abutalabs.com/products/generative_agents", "card": {"archived": false, "artifact_type": "application", "description": "Generative Agents: Interactive Simulacra of Human Behavior", "domain": ["artificial-intelligence", "large-language-models", "simulation"], "enriched": true, "function": ["agent-framework", "llm-inference", "simulation", "game-engine"], "health_score": 20, "homepage": null, "language": null, "license": "Apache-2.0", "license_family": "permissive", "maturity": "maintenance", "member_repos": ["joonspk-research/generative_agents"], "name": "joonspk-research/generative_agents", "platform": ["python", "cross-platform"], "pushed_at": "2024-08-05T21:38:56+00:00", "repo": "joonspk-research/generative_agents", "stars": 21995, "tags": ["generative-agents", "llm-agents", "social-simulation", "smallville", "research-paper", "believable-agents", "ai-agents", "research", "web-server"], "topics": [], "urls": [], "use_cases": ["simulate believable human-like agents in a virtual town", "reproduce the generative agents research paper experiments", "build LLM-powered agent simulations with memory and planning", "run the Smallville demo animation of agent behavior", "study social simulation with large language models", "prototype agent architectures like memory streams and reflection"], "what_it_is": "The official code release for the Stanford 'Generative Agents' research paper, implementing computational agents powered by LLMs that simulate believable human behavior in a Smallville game environment. It consists of a Django-based environment server and an agent simulation backend that requires an OpenAI API key.", "when_to_avoid": ["you need a production-ready or actively maintained agent framework", "you want to avoid OpenAI API costs or vendor lock-in", "you need a lightweight library rather than a full two-server simulation setup"], "when_to_choose": ["you want to replicate or extend the canonical generative agents research", "you need a reference implementation of LLM agents with memory, planning, and reflection", "you are doing academic work on believable agent simulation"]}, "data_as_of": "2026-08-30T08:39:29.467469+00:00", "members": [{"path": "/products/generative_agents", "repo": "joonspk-research/generative_agents", "role": "main", "score": 28}], "provenance": {"archived": {"kind": "observed", "observed_at": "2026-08-28T04:11:32.248337+00:00", "source": "github"}, "artifact_type": {"confidence": null, "enriched_at": "2026-08-29T16:57:44.710995+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "cdc667ab230734facc8d4f6f793da137978066a985c520fc949e0eb4919d81b4", "fetched_at": "2026-08-28T04:11:32.248337+00:00", "kind": "readme", "missing": false, "url": "https://github.com/joonspk-research/generative_agents"}], "taxonomy_version": 1}, "description": {"kind": "observed", "observed_at": "2026-08-28T04:11:32.248337+00:00", "source": "github"}, "domain": {"confidence": null, "enriched_at": "2026-08-29T16:57:44.710995+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "cdc667ab230734facc8d4f6f793da137978066a985c520fc949e0eb4919d81b4", "fetched_at": "2026-08-28T04:11:32.248337+00:00", "kind": "readme", "missing": false, "url": "https://github.com/joonspk-research/generative_agents"}], "taxonomy_version": 1}, "enriched": {"inputs": [], "kind": "computed", "method": "enrichment_status"}, "function": {"confidence": null, "enriched_at": "2026-08-29T16:57:44.710995+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "cdc667ab230734facc8d4f6f793da137978066a985c520fc949e0eb4919d81b4", "fetched_at": "2026-08-28T04:11:32.248337+00:00", "kind": "readme", "missing": false, "url": "https://github.com/joonspk-research/generative_agents"}], "taxonomy_version": 1}, "health_score": {"inputs": ["days_since_push", "days_since_release", "archived"], "kind": "computed", "method": "health_v1"}, "homepage": {"kind": "observed", "observed_at": "2026-08-28T04:11:32.248337+00:00", "source": "github"}, "language": {"kind": "observed", "observed_at": "2026-08-28T04:11:32.248337+00:00", "source": "github"}, "license": {"kind": "observed", "observed_at": "2026-08-28T04:11:32.248337+00:00", "source": "github"}, "license_family": {"inputs": ["license"], "kind": "computed", "method": "license_family"}, "maturity": {"confidence": null, "enriched_at": "2026-08-29T16:57:44.710995+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "cdc667ab230734facc8d4f6f793da137978066a985c520fc949e0eb4919d81b4", "fetched_at": "2026-08-28T04:11:32.248337+00:00", "kind": "readme", "missing": false, "url": "https://github.com/joonspk-research/generative_agents"}], "taxonomy_version": 1}, "member_repos": {"kind": "observed", "observed_at": "2026-08-28T04:11:32.248337+00:00", "source": "github"}, "name": {"kind": "observed", "observed_at": "2026-08-28T04:11:32.248337+00:00", "source": "github"}, "platform": {"confidence": null, "enriched_at": "2026-08-29T16:57:44.710995+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "cdc667ab230734facc8d4f6f793da137978066a985c520fc949e0eb4919d81b4", "fetched_at": "2026-08-28T04:11:32.248337+00:00", "kind": "readme", "missing": false, "url": "https://github.com/joonspk-research/generative_agents"}], "taxonomy_version": 1}, "pushed_at": {"kind": "observed", "observed_at": "2026-08-28T04:11:32.248337+00:00", "source": "github"}, "repo": {"kind": "observed", "observed_at": "2026-08-28T04:11:32.248337+00:00", "source": "github"}, "stars": {"kind": "observed", "observed_at": "2026-08-28T04:11:32.248337+00:00", "source": "github"}, "tags": {"confidence": null, "enriched_at": "2026-08-29T16:57:44.710995+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "cdc667ab230734facc8d4f6f793da137978066a985c520fc949e0eb4919d81b4", "fetched_at": "2026-08-28T04:11:32.248337+00:00", "kind": "readme", "missing": false, "url": "https://github.com/joonspk-research/generative_agents"}], "taxonomy_version": 1}, "topics": {"kind": "observed", "observed_at": "2026-08-28T04:11:32.248337+00:00", "source": "github"}, "urls": {"kind": "observed", "observed_at": "2026-08-28T04:11:32.248337+00:00", "source": "github"}, "use_cases": {"confidence": null, "enriched_at": "2026-08-29T16:57:44.710995+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "cdc667ab230734facc8d4f6f793da137978066a985c520fc949e0eb4919d81b4", "fetched_at": "2026-08-28T04:11:32.248337+00:00", "kind": "readme", "missing": false, "url": "https://github.com/joonspk-research/generative_agents"}], "taxonomy_version": 1}, "what_it_is": {"confidence": null, "enriched_at": "2026-08-29T16:57:44.710995+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "cdc667ab230734facc8d4f6f793da137978066a985c520fc949e0eb4919d81b4", "fetched_at": "2026-08-28T04:11:32.248337+00:00", "kind": "readme", "missing": false, "url": "https://github.com/joonspk-research/generative_agents"}], "taxonomy_version": 1}, "when_to_avoid": {"confidence": null, "enriched_at": "2026-08-29T16:57:44.710995+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "cdc667ab230734facc8d4f6f793da137978066a985c520fc949e0eb4919d81b4", "fetched_at": "2026-08-28T04:11:32.248337+00:00", "kind": "readme", "missing": false, "url": "https://github.com/joonspk-research/generative_agents"}], "taxonomy_version": 1}, "when_to_choose": {"confidence": null, "enriched_at": "2026-08-29T16:57:44.710995+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "cdc667ab230734facc8d4f6f793da137978066a985c520fc949e0eb4919d81b4", "fetched_at": "2026-08-28T04:11:32.248337+00:00", "kind": "readme", "missing": false, "url": "https://github.com/joonspk-research/generative_agents"}], "taxonomy_version": 1}}, "score": {"components": {"activity": 0, "longevity": 81, "rhythm": 35}, "computed_at": "2026-09-03T02:20:16.233290+00:00", "flags": ["no_releases"], "formula": "round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)", "inputs": {"age_days": 1137, "days_push": 758, "days_rel": null, "gap_med": null, "n_releases_24m": 0}, "score": 28, "version": 2}, "staleness": {"enrichment_outdated": false, "low_confidence": false, "scrape_days": 9, "stale_scrape": false}}