Input path: /home/debian/html/nutritwin/output_llm/6744609e548d2/input.json Output path: /home/debian/html/nutritwin/output_llm/6744609e548d2/output.json Input text: DB path: __deriveddata__/DerivedObjects/Data/KcalMeDB_fr.sl3 Picto path: __deriveddata__/DerivedObjects/Data/PictoMatcherNetNG_fr.json Sport grounding path: __deriveddata__/DerivedObjects/Data/DerivedSportMET.json ================================================================================================================================== Prompt from user: ================================================================================================================================== ########################################### # For image extraction, GPT4 is used # ########################################### ==================================== Prompt ============================================= In the image, identify all the foods and the beverages. For each of them, identify the "name", the "type", the "quantity", if it exists, the "brand" and the "cooking" mode. "Portions", like "tranche", are quantities. Ignore what it is not connected to nutrition, beverage or food. When the "brand" is not specified and the product is very well-known (like "Coca-Cola"), provide the brand name in "brand", otherwise set "brand" to "". Identify what "type" of food. Identify the "company" to which the "brand" belongs. Estimate the "weight" in grams or centiliters for each result. Identify the time is the current time, map it on the closest case: "petit-déjeuner", "déjeuner", "grignotage" or "dîner". When the "name" has synonyms, use the most common name, example: "yaourt" is more common than "yogourt". Format the result for each ingredient of food & beverage in french in JSON in an array of tuples {"name":, "quantity":, "weight":, "cooking":, "brand":, "company":, "type":, "time":, "event": "declaration"}. ========================================================================================= Image recognition.... ------------------------------ LLM Raw response ----------------------------- Based on the image provided, we have two different types of foods: 1. Slices of smoked salmon 2. Cooked potatoes Here is the requested information formatted in JSON: ```json [ { "name": "saumon fumé", "quantity": "tranches", "weight": "50", "cooking": "fumé", "brand": "", "company": "", "type": "fruit de mer", "time": "dîner", "event": "declaration" }, { "name": "pomme de terre", "quantity": "unités", "weight": "200", "cooking": "cuite", "brand": "", "company": "", "type": "légume", "time": "dîner", "event": "declaration" } ] ``` Please note: - The weights are estimated based on the common serving sizes. - Brand and company information are left blank as there is no identifiable branding present in the image. - The type of meal (time) classified as "dîner" is based on the typical foods shown, which are often eaten during evening meals; however, this may vary depending on personal eating habits and cultural contexts. - The term "event" is set to "declaration" as per instruction, assuming it is related to the act of providing ----------------------------------------------------------------------------- ----------------- Make it compliant ------------------ Based on the image provided, we have two different types of foods: 1. Slices of smoked salmon 2. Cooked potatoes Here is the requested information formatted in JSON: ```json [ { "name": "saumon fumé", "quantity": "tranches", "weight": "50", "cooking": "fumé", "brand": "", "company": "", "type": "fruit de mer", "time": "dîner", "event": "declaration" }, { "name": "pomme de terre", "quantity": "unités", "weight": "200", "cooking": "cuite", "brand": "", "company": "", "type": "légume", "time": "dîner", "event": "declaration" } ] ``` Please note: - The weights are estimated based on the common serving sizes. - Brand and company information are left blank as there is no identifiable branding present in the image. - The type of meal (time) classified as "dîner" is based on the typical foods shown, which are often eaten during evening meals; however, this may vary depending on personal eating habits and cultural contexts. - The term "event" is set to "declaration" as per instruction, assuming it is related to the act of providing ------------------------------------------------------ ------------------------ After simplification ------------------------ [ { "name": "saumon fumé", "quantity": "tranches", "weight": "50", "cooking": "fumé", "brand": "", "company": "", "type": "fruit de mer", "time": "dîner", "event": "declaration" }, { "name": "pomme de terre", "quantity": "unités", "weight": "200", "cooking": "cuite", "brand": "", "company": "", "type": "légume", "time": "dîner", "event": "declaration" }] ---------------------------------------------------------------------- --------------------------------- LLM result ----------------------------------- {'response': [{'name': 'saumon fumé', 'quantity': 'tranches', 'weight': '50', 'cooking': 'fumé', 'brand': '', 'company': '', 'type': 'fruit de mer', 'time': 'dîner', 'event': 'declaration'}, {'name': 'pomme de terre', 'quantity': 'unités', 'weight': '200', 'cooking': 'cuite', 'brand': '', 'company': '', 'type': 'légume', 'time': 'dîner', 'event': 'declaration'}], 'cost': 0.0} -------------------------------------------------------------------------------- ----------- result to be analyzed ----------- {'name': 'saumon fumé', 'quantity': 'tranches', 'weight': '50', 'cooking': 'fumé', 'brand': '', 'company': '', 'type': 'fruit de mer', 'time': 'dîner', 'event': 'declaration'} First try: SELECT V_Name,V_Comment,V_NormName,V_NormComment,V_PackType,V_GTIN,V_GTINRef,V_ID,V_GlobalCount,V_NormTrademark,V_Trademark,V_NormAggr FROM KCALME_TABLE WHERE V_NormName LIKE '% saumon fume %' AND (V_NormTrademark = '' OR V_NormTrademark IS NULL) ------------- Found solution (max 20) -------------- Saumon Fumé - saumon fume - - - 11676 - - - CIQ#d8453997de6adf67fd709f2e16e4a09f Röstis au Saumon Fumé - rosti saumon fume - - - 12 - - - KCA#14382263fff55c2e867e77149a5dc44e Salade de Saumon Fumé et Sauce au Tamarin - salade de saumon fume sauce tamarin - - - 220 - - - KCA#c5784931561a3c9bf01b76742038638a Bruschette au Saumon Fumé - bruschette saumon fume - au Fromage frais et à la roquette - - 29 - - - KCA#f4639ed3001f45c9e7e0569913f5f131 Mille-feuille Saumon Fumé - mille feuille saumon fume - Fromage frais - - 12 - - - KCA#872e1faa5af3b5a1af0abf16cc535dd5 ---------------------------------------------------- ----------- result to be analyzed ----------- {'name': 'pomme de terre', 'quantity': 'unités', 'weight': '200', 'cooking': 'cuite', 'brand': '', 'company': '', 'type': 'légume', 'time': 'dîner', 'event': 'declaration'} First try: SELECT V_Name,V_Comment,V_NormName,V_NormComment,V_PackType,V_GTIN,V_GTINRef,V_ID,V_GlobalCount,V_NormTrademark,V_Trademark,V_NormAggr FROM KCALME_TABLE WHERE V_NormName LIKE '% pomme de terre %' AND (V_NormTrademark = '' OR V_NormTrademark IS NULL) ------------- Found solution (max 20) -------------- Pomme de Terre - pomme de terre - égouttée - - 26541 - - - CIQ#bbc0fd1495ed69b7aadd91d1d9b9ae69 Pomme de Terre - pomme de terre - aliment moyen - - 0 - - - CIQ#15f690b8140afc79288abfb96a139095 Pomme de Terre - pomme de terre - sans peau, crue - - 0 - - - CIQ#9d1dc4d850cf0a126428e8235097b299 Pomme de Terre - pomme de terre - rôtie/cuite au four - - 0 - - - CIQ#73642ae51d1ceb413f96f404c2e8fcc5 Pomme de Terre - pomme de terre - purée, aliment moyen - - 0 - - - CIQ#20c56d85dc4d344fdfb3594d5e93f5ff Pomme de Terre - pomme de terre - bouillie/cuite à l'eau - - 0 - - - CIQ#6997e933cb8bbe4ad6fb62b2f04c05c2 Pomme de Terre - pomme de terre - sans peau, rôtie/cuite au four - - 0 - - - CIQ#7c973fe7644a5cc7a5e1ac7f7690f91c Pomme de Terre - pomme de terre - purée, avec lait et beurre, non salée - - 54 - - - CIQ#f6d85f887fb7a88d451e7d1390b123ee Pomme de Terre - pomme de terre - flocons déshydratés, au lait ou à la crème - - 0 - - - CIQ#1450a8209d87032018367a76931b19ad Pomme de Terre - pomme de terre - purée à base de flocons, reconstituée avec lait entier, matière grasse - - 0 - - - CIQ#e310092ee2308f72f5d4eb70daa82fbc Pomme de Terre - pomme de terre - purée à base de flocons, reconstituée avec lait demi-écrémé et eau, non salée - - 0 - - - CIQ#3b12d13dfd318911c754bcb37b7b05ab Pomme de Terre Anna - pomme de terre anna - - - 43 - - - KCA#96fe2fadd9f331eb4549227f2e4a6267 Pomme de Terre Chips - pomme de terre chip - - - 42 - - - KCA#1deb7b7eab80f8586099ee58a6db9ea2 Pomme de Terre Purée - pomme de terre puree - - - 40 - - - KCA#0d4cd5387a20885448dbbf1f634017b3 Pomme de Terre Byron - pomme de terre byron - - - 4 - - - KCA#244d59f3080438c8160682d32b6ff789 Pomme de Terre Rôties - pomme de terre rotie - - - 1077 - - - KCA#797b578eb598e7082faea0ae30d34021 Pomme de Terre Frites - pomme de terre frite - - - 178 - - - KCA#d9391c743d3aee9e28d0940b17624718 Pomme de Terre Vapeur - pomme de terre vapeur - sous vide - - 0 - - - CIQ#d52218f9e63c6cb0bf8151b244a71afd Pomme de Terre Poêlée - pomme de terre poelee - avec matière grasse - - 0 - - - CIQ#b717c125ad32aa35b8cd673ba48f8c60 Pomme de Terre Sautées - pomme de terre sautee - - - 5854 - - - KCA#7e685fe608808c6ddb2b7b1edab93c82 ---------------------------------------------------- ERROR: Wrong quantity: '' ERROR: no solution for picto in the first solution ERROR: Wrong quantity: '' ERROR: no solution for picto in the first solution ERROR: Wrong quantity: '' ERROR: no solution for picto in the first solution ERROR: Wrong quantity: '' ERROR: no solution for picto in the first solution ERROR: Wrong quantity: '' ERROR: no solution for picto in the first solution ERROR: Wrong quantity: '' ERROR: no solution for picto in the first solution ERROR: Wrong quantity: '' ERROR: no solution for picto in the first solution ERROR: Wrong quantity: '' ERROR: no solution for picto in the first solution ERROR: Wrong quantity: '' ERROR: no solution for picto in the first solution ERROR: Wrong quantity: '' ERROR: no solution for picto in the first solution ERROR: Wrong quantity: '' ERROR: no solution for picto in the first solution --------------------------------- final result ----------------------------------- {'prompt': '', 'intents': ['Identify food in an image'], 'model': 'gpt-4o-2024-05-13', 'solutions': {'nutrition': [{'name': 'Saumon Fumé', 'normName': ' saumon fume ', 'comment': '', 'normComment': '', 'rank': 11676, 'id': 'CIQ#d8453997de6adf67fd709f2e16e4a09f', 'quantity': 'tranches', 'quantityLem': 'tranche', 'pack': ['TR7.w35'], 'type': 'fruit de mer', 'gtin': '', 'gtinRef': '', 'brand': '', 'time': 'dîner', 'event': 'declaration', 'serving': 'TR7-50', 'posiNormName': 0}, {'name': 'Pomme de Terre', 'normName': ' pomme de terre ', 'comment': 'égouttée', 'normComment': ' egouttee ', 'rank': 26541, 'id': 'CIQ#bbc0fd1495ed69b7aadd91d1d9b9ae69', 'quantity': 'unités', 'quantityLem': '', 'pack': ['PDT.w120'], 'type': 'légume', 'gtin': '', 'gtinRef': '', 'brand': '', 'time': 'dîner', 'event': 'declaration', 'serving': '', 'posiNormName': 0}], 'activity': [], 'response': {}}, 'cputime': 7.21484637260437} ---------------------------------------------------------------------------------- LLM CPU Time: 7.21484637260437