V0.2 distribution and summarizer - #86
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e2hln merged 2 commits intoJul 20, 2026
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Add two format-agnostic, repo-level distribution attributes extracted from
the HuggingFace file listing:
* model_file_size — total bytes of all weight files
* runtime_requirement — "python" (safetensors/PyTorch/etc. loadable from a
Python ML stack) or "llm-stack" (GGUF/GGML-only,
needs llama.cpp/Ollama)
- model_file_extractors.py: new extract_distribution_metadata() runs for every
repo regardless of weight format
- extractor.py: wire into EnhancedExtractor (REPOSITORY_FILES / HIGH confidence)
- service.py: emit as CycloneDX properties under the custom
owasp:aibom:distribution namespace (kept out of the official genai:aibom
namespace, which forbids unofficial names)
- field_registry.json: register both as supplementary-tier fields
- result.html: render a friendly "Deployment & Hardware" section
…backend - Switch summarization model from google/flan-t5-small to facebook/bart-large-cnn - Fix prompt-leak bug: BART is a summarization model, not instruction-following. Feed it document text only (never an instruction prompt), which it would otherwise echo into the output and hallucinate generic summaries. Add _strip_prompt_leak() as defense-in-depth - Add optional instruction-tuned backend via Ollama (AIBOM_SUMMARIZER_BACKEND=ollama), falling back to BART on any failure - Guard against BART hallucination on short inputs (<280 chars): return the clean extract instead of abstracting - Penalize quant-repackaging marketing text; strip markdown emphasis/headings; add no_repeat_ngram_size to stop repetition loops
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