{
  "name": "MODA Duo",
  "artifact_type": "retrieval_system",
  "description": "Two open constituents, one answer per query. Each query is routed to whichever constituent suits its shape: short catalogue titles to MODA Pro Lite+, longer descriptions to MODA. One text forward and one nearest-neighbour query per search.",
  "additional_learned_parameters": 0,
  "constituents": {
    "moda": {
      "base_model": "Marqo/marqo-fashionSigLIP",
      "parameters": 203155970,
      "embedding_dimension": 768,
      "gallery": {
        "views": {
          "official": 1.0,
          "pad_white": 0.25,
          "center_crop": 0.25
        },
        "normalize": true
      },
      "query": {
        "prompts": {
          "raw": 1.0,
          "product": 0.25
        },
        "normalize": true
      },
      "prompt_templates": {
        "raw": "{query}",
        "product": "a fashion product photo of {query}"
      }
    },
    "moda_pro_lite_plus": {
      "base_model": "HopitAI/moda-pro-lite",
      "parameters": 213159938,
      "embedding_dimension": 768,
      "gallery": {
        "views": {
          "official": 1.0,
          "pad": 0.25,
          "foreground_pad": 0.25
        },
        "normalize": true
      },
      "query": {
        "prompts": {
          "raw": 1.0,
          "photo": 0.25
        },
        "normalize": true
      },
      "prompt_templates": {
        "raw": "{query}",
        "photo": "a photo of {query}"
      }
    }
  },
  "router": {
    "kind": "query_word_count",
    "rule": "words(query) <= threshold -> moda_pro_lite_plus, else moda",
    "threshold": 36,
    "pluggable": true,
    "note": "The router is a callable; any policy mapping a query to a constituent name may replace it."
  },
  "serving": {
    "stored_vectors_per_item": 2,
    "indexes": 2,
    "text_forwards_per_query": 2,
    "encoders_run_per_query": 1,
    "ann_queries_per_search": 1,
    "rerank": false
  },
  "selection": {
    "criterion": "maximin regret against the per-regime oracle (better of the two constituents), tie-break mean regret",
    "target_benchmarks_accessed_during_selection": false,
    "frozen_before_target_evaluation": true,
    "receipt": "results/multiview_recipe_rebuild/SELECTION_duo.json",
    "threshold_selected_on": "development data only (OpenVTON validation 4,989 + GLAMI 2,000 x 3 query views)"
  },
  "evaluation": {
    "protocol": "full corpus, all ground-truth queries, MAP@10, pytrec_eval map_cut.10, paired bootstrap 10000 @ 20260728",
    "receipt": "results/duo_target_eval.json"
  }
}