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Semantic Search

Search a menu by intent, not keywords. The model handles typos, abstract queries, and cross-lingual terms across 100+ languages.

4648 msAPI
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3 resultscurated example
4648 msAPI

read as something spicy

What just happened
Pad Thai ranks first despite having no keyword overlap. The model understands that Pad Thai is spicy by concept, not by string match.
  1. Pad Thaicosine 0.878
    relevance
    0.996
  2. Spicy Tom Yum Soupcosine 0.480
    relevance
    0.928
  3. Spicy Beef Tacoscosine 0.683
    relevance
    0.890

The bar is the reranker relevance score. The faint tick behind it is the raw cosine similarity.

Use this in your app

Pre-filled with your query and corpus. Drop in a key and run it.

curl -X POST https://dish-embed.latimal.com/search \
  -H "X-API-Key: $LATIMAL_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
  "query": "something spicy",
  "corpus": [
    "Margherita Pizza",
    "Spicy Beef Tacos",
    "Tonkotsu Ramen",
    "Pad Thai",
    "Falafel Plate",
    "Steamed Vegetable Dumplings",
    "Pho Bo",
    "餃子",
    "Cheeseburger",
    "Gelato",
    "دجاج شاورما",
    "비빔밥",
    "Green Papaya Salad",
    "Spicy Tom Yum Soup",
    "Iced Matcha Latte",
    "Fresh Lemonade",
    "Tiramisu",
    "Chicken Katsu Curry",
    "Grilled Salmon Bowl",
    "Butter Chicken"
  ],
  "top_k": 8
}'

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