{"adoption": {"forks": 99, "observed_at": "2026-08-28T04:03:47.502537+00:00", "stars": 1153}, "canonical_url": "https://ross.abutalabs.com/products/ml-clara", "card": {"archived": false, "artifact_type": "library", "description": null, "domain": ["large-language-models", "machine-learning"], "enriched": true, "function": ["rag", "llm-inference", "machine-learning", "search-engine"], "health_score": 55, "homepage": null, "language": "Python", "license": "NOASSERTION", "license_family": "other", "maturity": "active", "member_repos": ["apple/ml-clara"], "name": "apple/ml-clara", "platform": ["python"], "pushed_at": "2025-12-19T17:17:56+00:00", "repo": "apple/ml-clara", "stars": 1153, "tags": ["document-compression", "latent-reasoning", "huggingface", "research-model", "apple", "retrieval-augmented-generation", "natural-language-processing", "gpu", "linux", "macos"], "topics": [], "urls": [], "use_cases": ["build a RAG system with compressed document representations", "reduce long-context costs in retrieval-augmented generation", "fine-tune a model that jointly optimizes retrieval and generation", "compress knowledge documents into latent embeddings for LLMs", "evaluate state-of-the-art RAG compression approaches", "run an end-to-end RAG model without a separate retriever"], "what_it_is": "CLaRa is Apple's open-source end-to-end Retrieval-Augmented Generation model that compresses documents into continuous latent representations (32x-64x compression) unifying retrieval and generation in a single optimized model. The repository provides training code, evaluation data, and 7B model checkpoints (Base, Instruct, E2E) on Hugging Face.", "when_to_avoid": ["you need a production-ready plug-and-play RAG framework with broad ecosystem support", "you require permissive licensing (Apple license, NOASSERTION)", "you need small models or CPU-only inference", "you want a mature tool with long-term community support"], "when_to_choose": ["you want cutting-edge research RAG with document compression", "long context lengths are a bottleneck in your RAG pipeline", "you want to reproduce or build on the CLaRa paper", "you need jointly trained retrieval and generation instead of separate components"]}, "data_as_of": "2026-08-30T08:39:29.467469+00:00", "members": [{"path": "/products/ml-clara", "repo": "apple/ml-clara", "role": "main", "score": 43}], "provenance": {"archived": {"kind": "observed", "observed_at": "2026-08-28T04:03:47.502537+00:00", "source": "github"}, "artifact_type": {"confidence": null, "enriched_at": "2026-08-30T06:33:27.096118+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "687ea99e854fe85d3e4a6cee8435c9e60ae8e9418c3a1a3e4130d900f03b6d16", "fetched_at": "2026-08-28T04:03:47.502537+00:00", "kind": "readme", "missing": false, "url": "https://github.com/apple/ml-clara"}], "taxonomy_version": 1}, "description": {"kind": "observed", "observed_at": "2026-08-28T04:03:47.502537+00:00", "source": "github"}, "domain": {"confidence": null, "enriched_at": "2026-08-30T06:33:27.096118+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "687ea99e854fe85d3e4a6cee8435c9e60ae8e9418c3a1a3e4130d900f03b6d16", "fetched_at": "2026-08-28T04:03:47.502537+00:00", "kind": "readme", "missing": false, "url": "https://github.com/apple/ml-clara"}], "taxonomy_version": 1}, "enriched": {"inputs": [], "kind": "computed", "method": "enrichment_status"}, "function": {"confidence": null, "enriched_at": "2026-08-30T06:33:27.096118+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "687ea99e854fe85d3e4a6cee8435c9e60ae8e9418c3a1a3e4130d900f03b6d16", "fetched_at": "2026-08-28T04:03:47.502537+00:00", "kind": "readme", "missing": false, "url": "https://github.com/apple/ml-clara"}], "taxonomy_version": 1}, "health_score": {"inputs": ["days_since_push", "days_since_release", "archived"], "kind": "computed", "method": "health_v1"}, "homepage": {"kind": "observed", "observed_at": "2026-08-28T04:03:47.502537+00:00", "source": "github"}, "language": {"kind": "observed", "observed_at": "2026-08-28T04:03:47.502537+00:00", "source": "github"}, "license": {"kind": "observed", "observed_at": "2026-08-28T04:03:47.502537+00:00", "source": "github"}, "license_family": {"inputs": ["license"], "kind": "computed", "method": "license_family"}, "maturity": {"confidence": null, "enriched_at": "2026-08-30T06:33:27.096118+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "687ea99e854fe85d3e4a6cee8435c9e60ae8e9418c3a1a3e4130d900f03b6d16", "fetched_at": "2026-08-28T04:03:47.502537+00:00", "kind": "readme", "missing": false, "url": "https://github.com/apple/ml-clara"}], "taxonomy_version": 1}, "member_repos": {"kind": "observed", "observed_at": "2026-08-28T04:03:47.502537+00:00", "source": "github"}, "name": {"kind": "observed", "observed_at": "2026-08-28T04:03:47.502537+00:00", "source": "github"}, "platform": {"confidence": null, "enriched_at": "2026-08-30T06:33:27.096118+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "687ea99e854fe85d3e4a6cee8435c9e60ae8e9418c3a1a3e4130d900f03b6d16", "fetched_at": "2026-08-28T04:03:47.502537+00:00", "kind": "readme", "missing": false, "url": "https://github.com/apple/ml-clara"}], "taxonomy_version": 1}, "pushed_at": {"kind": "observed", "observed_at": "2026-08-28T04:03:47.502537+00:00", "source": "github"}, "repo": {"kind": "observed", "observed_at": "2026-08-28T04:03:47.502537+00:00", "source": "github"}, "stars": {"kind": "observed", "observed_at": "2026-08-28T04:03:47.502537+00:00", "source": "github"}, "tags": {"confidence": null, "enriched_at": "2026-08-30T06:33:27.096118+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "687ea99e854fe85d3e4a6cee8435c9e60ae8e9418c3a1a3e4130d900f03b6d16", "fetched_at": "2026-08-28T04:03:47.502537+00:00", "kind": "readme", "missing": false, "url": "https://github.com/apple/ml-clara"}], "taxonomy_version": 1}, "topics": {"kind": "observed", "observed_at": "2026-08-28T04:03:47.502537+00:00", "source": "github"}, "urls": {"kind": "observed", "observed_at": "2026-08-28T04:03:47.502537+00:00", "source": "github"}, "use_cases": {"confidence": null, "enriched_at": "2026-08-30T06:33:27.096118+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "687ea99e854fe85d3e4a6cee8435c9e60ae8e9418c3a1a3e4130d900f03b6d16", "fetched_at": "2026-08-28T04:03:47.502537+00:00", "kind": "readme", "missing": false, "url": "https://github.com/apple/ml-clara"}], "taxonomy_version": 1}, "what_it_is": {"confidence": null, "enriched_at": "2026-08-30T06:33:27.096118+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "687ea99e854fe85d3e4a6cee8435c9e60ae8e9418c3a1a3e4130d900f03b6d16", "fetched_at": "2026-08-28T04:03:47.502537+00:00", "kind": "readme", "missing": false, "url": "https://github.com/apple/ml-clara"}], "taxonomy_version": 1}, "when_to_avoid": {"confidence": null, "enriched_at": "2026-08-30T06:33:27.096118+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "687ea99e854fe85d3e4a6cee8435c9e60ae8e9418c3a1a3e4130d900f03b6d16", "fetched_at": "2026-08-28T04:03:47.502537+00:00", "kind": "readme", "missing": false, "url": "https://github.com/apple/ml-clara"}], "taxonomy_version": 1}, "when_to_choose": {"confidence": null, "enriched_at": "2026-08-30T06:33:27.096118+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "687ea99e854fe85d3e4a6cee8435c9e60ae8e9418c3a1a3e4130d900f03b6d16", "fetched_at": "2026-08-28T04:03:47.502537+00:00", "kind": "readme", "missing": false, "url": "https://github.com/apple/ml-clara"}], "taxonomy_version": 1}}, "score": {"components": {"activity": 58, "longevity": 21, "rhythm": 35}, "computed_at": "2026-09-03T02:20:16.233290+00:00", "flags": ["no_releases", "no_license"], "formula": "round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)", "inputs": {"age_days": 294, "days_push": 257, "days_rel": null, "gap_med": null, "n_releases_24m": 0}, "score": 43, "version": 2}, "staleness": {"enrichment_outdated": false, "low_confidence": false, "scrape_days": 9, "stale_scrape": false}}