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Merge branch 'wip/oie-pipeline-eval-harness' into exp/dual-index-and-name-packer
Sync with PR #1088 upstream. Prefer dual-index librarian defaults on conflicts; take 1088-only harness/full-pipeline/NIST/harvester additions.
2 parents 0276336 + 394c10f commit ece1531

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‎.env.example‎

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@@ -52,14 +52,25 @@ GOOGLE_CLIENT_SECRET=your-client-secret
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GOOGLE_SECRET_JSON=path/to/secret.json
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LOGIN_ALLOWED_DOMAINS=example.com
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# GCP
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# GCP / Gemini (optional — any LiteLLM provider works for Module B)
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GCP_NATIVE=false
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GEMINI_API_KEY=your-gemini-api-key
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VERTEX_CHAT_MODEL=gemini-2.5-flash
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VERTEX_EMBED_CONTENT_MODEL=gemini-embedding-001
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# Noise / Relevance Filter (Module B)
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# Other chat providers (LiteLLM). Set the key that matches CRE_NOISE_FILTER_LLM_MODEL.
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# OPENAI_API_KEY=sk-...
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# ANTHROPIC_API_KEY=sk-ant-...
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# GROQ_API_KEY=gsk_...
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# MISTRAL_API_KEY=...
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# OPENROUTER_API_KEY=...
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# Noise / Relevance Filter (Module B) — LiteLLM model id (provider/model)
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# Examples: gemini/gemini-2.5-flash-lite | openai/gpt-4o-mini |
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# anthropic/claude-haiku-4-5 | groq/llama-3.3-70b-versatile
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# Any chat model LiteLLM supports; mid-size models usually work best
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# (cheap + reliable for this classify gate — avoid tiny completion stubs).
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CRE_NOISE_FILTER_LLM_MODEL=gemini/gemini-2.5-flash-lite
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CRE_NOISE_FILTER_BATCH_SIZE=10

‎.gitignore‎

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@@ -79,6 +79,8 @@ standards_cache.sqlite
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!docs/gsoc_2026_module_b/module_c_contract.md
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!docs/gsoc_2026_module_b/module_b_runbook.md
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!docs/gsoc_2026_module_b/final_metrics.md
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!docs/oie/*.md
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!scripts/oie_owasp_eval/experiments/*.md
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### Dev DBDumps
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*.sql

‎application/cmd/cre_main.py‎

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@@ -911,6 +911,25 @@ def run(args: argparse.Namespace) -> None: # pragma: no cover
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sys.exit(1)
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return
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if str(getattr(args, "ingest_github", "") or "").strip():
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import sys
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from application import sqla
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from application.utils.harvester.github_url_ingest import ingest_github_url
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db_connect(args.cache_file)
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counts = ingest_github_url(
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str(args.ingest_github).strip(),
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session=sqla.session,
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cache_file=args.cache_file,
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branch_override=(getattr(args, "ingest_branch", "") or "").strip() or None,
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keep_all=bool(getattr(args, "ingest_keep_all", False)),
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model_override=(getattr(args, "ingest_model", "") or "").strip() or None,
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)
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if counts.errors or (counts.knowledge + counts.uncertain) == 0:
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sys.exit(1)
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return
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if getattr(args, "run_noise_filter", False):
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import sys
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