Input path: /home/debian/html/nutritwin/output_llm/68b548116b7fe/input.json Output path: /home/debian/html/nutritwin/output_llm/68b548116b7fe/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: ================================================================================================================================== Image to be analyzed: /home/debian/html/nutritwin/output_llm/68b548116b7fe/capture.jpg ############################################################################################## # For image extraction, pixtral-large-2411 is used # ############################################################################################## ==================================== Prompt ============================================= In the image, identify all the foods and beverages, convert them into an array of JSON with consumed foods. Ignore what it is not connected to nutrition, beverage or food. When a food or a beverage has several instances unify them on a single food or beverage and add the quantities of each. The attribute name must remain in English but the result, so the attribute value, must be in french, and only in french. Provide a solution without explanation. Use only the food & beverage ontology described in this Turtle/RDF model: """ @prefix food: . @prefix rdfs: . @prefix xsd: . @prefix owl: . @prefix prov: . food: a owl:Ontology ; rdfs:comment "Definition of the food archetype"@en . food:name a owl:DatatypeProperty; rdfs:label "name"@en; rdfs:comment """Food or beverage identifier, the name should not contain information related to quantity or container (like glass...). Ignore food or beverage when it is not consumed in the past, now or in the future. The cooking mode is not in the name. The name is only in french."""@en; rdfs:range xsd:string. food:quantity a owl:DatatypeProperty ; rdfs:label "quantity"@en; rdfs:comment "The quantity of food or drink that is or was consumed. Quantity is only in french. Here are examples: 'un quignon', 'un cornet', 'un verre', 'une tranche', 'une boule', 'un', 'deux', 'trois',... Keep the same language."@en; rdfs:range xsd:string. food:cookingMethod a owl:DatatypeProperty ; rdfs:label "cooking method"@en; rdfs:comment "The cooking method of food. The cooking method is in french."@en; rdfs:range xsd:string. food:type a owl:DatatypeProperty ; rdfs:label "type of food"@en; rdfs:comment "Identify the type of food."@en; rdfs:range xsd:string. food:food a food:type ; rdfs:label "food" . food:beverage a food:type ; rdfs:label "beverage" . food:timeOfTheDay a owl:DatatypeProperty ; rdfs:label "time of the day"@en; rdfs:comment "Time of the day when food or drink was consumed."@en; rdfs:range xsd:string. food:breakfast a food:timeOfTheDay ; rdfs:label "breakfast" . food:lunch a food:timeOfTheDay ; rdfs:label "lunch" . food:snacking a food:timeOfTheDay ; rdfs:label "snacking" . food:dinner a food:timeOfTheDay ; rdfs:label "dinner" . food:brand a owl:DatatypeProperty ; rdfs:label "Brand"@en; rdfs:comment """Food or beverage brand. The restaurants are not brand. When the name is very known (ex: Activia, Coca) and the brand is not mentioned, guess the brand."""@en; rdfs:range xsd:string. food:company a owl:DatatypeProperty ; rdfs:label "Company"@en; rdfs:comment "Product company."@en; rdfs:range xsd:string. food:enumEvent a rdfs:Class . food:event a owl:DatatypeProperty ; rdfs:label "event"@en; rdfs:comment "Event of eating or drinking. Each must have an event"@en; rdfs:range food:enumEvent. food:intent a food:enumEvent ; rdfs:label "intent" . rdfs:comment "When the event should happen"@en. food:declaration a food:enumEvent ; rdfs:label "declaration" . rdfs:comment "When the event has already occured"@en. food:unknownEvent a food:enumEvent ; rdfs:label "unknown" ; rdfs:comment "When the event is unknown in the day"@en. food:event a owl:DatatypeProperty ; rdfs:label "event"@en; rdfs:comment "Event of eating or drinking. Each must have an event"@en; rdfs:range food:enumEvent. food:intent a food:enumEvent ; rdfs:label "intent" . rdfs:comment "When the event should happen"@en. food:declaration a food:enumEvent ; rdfs:label "declaration" . rdfs:comment "When the event has already occured"@en. food:unknownEvent a food:enumEvent ; rdfs:label "unknown" ; rdfs:comment "When the event is unknown in the day"@en. """ Here is an example of result: [ { "name": "blanquette de veau", "quantity": "un plat", "cookingMethod": "mijot\u00e9", "timeOfTheDay": "lunch", "company": "Leclerc", "type": "food", "event": "declaration" }, { "name": "eau", "brand": "Evian", "company": "Danone", "timeOfTheDay": "breakfast", "quantity": "un verre", "type": "beverage", "event": "intent" } ] ========================================================================================= ------------------------------ LLM Raw response ----------------------------- [ { "name": "guacamole", "quantity": "20 grammes", "type": "food", "event": "unknownEvent", "brand": "Old El Paso" }, { "name": "tomate", "quantity": "plusieurs morceaux", "type": "food", "event": "unknownEvent" } ] ----------------------------------------------------------------------------- ----------------- Make it compliant ------------------ [ { "name": "guacamole", "quantity": "20 grammes", "type": "food", "event": "unknownEvent", "brand": "Old El Paso" }, { "name": "tomate", "quantity": "plusieurs morceaux", "type": "food", "event": "unknownEvent" } ] ------------------------------------------------------ ------------------------ After simplification ------------------------ [ { "name": "guacamole", "quantity": "20 grammes", "type": "food", "event": "unknownEvent", "brand": "Old El Paso" }, { "name": "tomate", "quantity": "plusieurs morceaux", "type": "food", "event": "unknownEvent" } ] ---------------------------------------------------------------------- --------------------------------- LLM result ----------------------------------- {'response': [{'name': 'guacamole', 'quantity': '20 grammes', 'type': 'food', 'event': 'unknownEvent', 'brand': 'Old El Paso'}, {'name': 'tomate', 'quantity': 'plusieurs morceaux', 'type': 'food', 'event': 'unknownEvent'}], 'cost': 0.0} -------------------------------------------------------------------------------- ----------- result to be analyzed ----------- {'name': 'guacamole', 'quantity': '20 grammes', 'type': 'food', 'event': 'unknownEvent', 'brand': 'Old El Paso'} 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 '% guacamole %' AND V_NormTrademark LIKE '%old el paso%' --> CPU time in DB: 0.1177 seconds Word: Guacamole - dist: 0.39724159240722656 - row: 3772 Word: Sauce Guacamole - dist: 0.4951190948486328 - row: 31473 Word: Guacamole à la Mexicaine - dist: 0.5030080080032349 - row: 46593 Word: Guacamole BIO - dist: 0.510260820388794 - row: 41608 Word: Salsa Guacamole - dist: 0.5159580111503601 - row: 8484 Found embedding word: Guacamole Second try (embedded): 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_Name = 'Guacamole' ------------- Found solution (max 20) -------------- Guacamole - guacamole - - General Mills - 0 - 0046000815213 - 0046000815213 - OFF#7f36a7e26990c9e3579b42ed2f150b56 Guacamole - guacamole - - Metro Chef - 0 - 13504656 - 13504656 - OFF#33365e1f78d79ddc4a427e56f995fc28 Guacamole - guacamole - - Lidl - 0 - 20929404 - 20929404 - OFF#fae7f31d55e73a554a033f5e3ac0747a Guacamole - guacamole - - Labeyrie - 0 - 3033610090410 - 3033610090410 - OFF#98227a82d330723a4f793e21dcd973bc Guacamole - guacamole - - Les Mousquetaires - 0 - 3250391821754 - 3250391821754 - OFF#131b3d3866aa49436b1b895639696c4c Guacamole - guacamole - - U - 0 - 3256220252294 - 3256220252294 - OFF#aab13593c9b820ee38411a32a9edc9f8 Guacamole - guacamole - - Cora - 0 - 3257982267502 - 3257982267502 - OFF#67296543e1560ce6c7149ab8bcbcecec Guacamole - guacamole - - Franprix - 0 - 3263858771318 - 3263858771318 - OFF#a48e76be97571cdcaf80072d4e6b0c80 Guacamole - guacamole - - Leader Price - 0 - 3263858772414 - 3263858772414 - OFF#d401097a047da0986f24e9920b565133 Guacamole - guacamole - - Picard - 0 - 3270160407972 - 3270160407972 - OFF#e720a6eab7e58dfe895b7b4fd4df9311 Guacamole - guacamole - - Agrial - 0 - 3280220109142 - 3280220109142 - OFF#cc096b0eeb82fd49dd91e0a907af08aa Guacamole - guacamole - - Monoprix - 0 - 3350030167509 - 3350030167509 - OFF#4af5cf46f469fa64179104b88ed3e869 Guacamole - guacamole - - Auchan - 0 - 3596710401031 - 3596710401031 - OFF#15614f1853a2cf4dbebdbf92e4fe9dfb Guacamole - guacamole - - Carrefour - 0 - 5400101047761 - 5400101047761 - OFF#6028e704289fc364fc1d94468ad8a1a6 Guacamole - guacamole - - Delhaize - 0 - 5400112734469 - 5400112734469 - OFF#9c3fb639e30b54dd6cb693daee145761 Guacamole - guacamole - - General Mills - 0 - 85282896 - 0046000815213 - OFF#13c0b23ca6dc5c5e834669b366edbb69 Guacamole - guacamole - - General Mills - 0 - 8410076423009 - 0046000815213 - OFF#079ea571813088716fe598c3b1fefab3 Guacamole - guacamole - - General Mills - 0 - 8410076421555 - 0046000815213 - OFF#4fb9ac0d6f92687c028d15d302c0b3ea Guacamole - guacamole - - General Mills - 0 - 8410076420794 - 0046000815213 - OFF#43adc9ae9c71d2132eb1c95f5709b54e Guacamole - guacamole - - General Mills - 0 - 8410076421456 - 0046000815213 - OFF#e8eac43c2f75ba8f0b81f07762d7beff ---------------------------------------------------- ERROR: no solution for picto in the first solution ERROR: no solution for picto in the first solution ERROR: no solution for picto in the first solution ERROR: no solution for picto in the first solution ERROR: no solution for picto in the first solution ERROR: no solution for picto in the first solution ERROR: no solution for picto in the first solution ERROR: no solution for picto in the first solution ERROR: no solution for picto in the first solution ERROR: no solution for picto in the first solution ERROR: no solution for picto in the first solution ERROR: no solution for picto in the first solution ERROR: no solution for picto in the first solution ERROR: no solution for picto in the first solution ERROR: no solution for picto in the first solution ERROR: no solution for picto in the first solution ERROR: no solution for picto in the first solution ERROR: no solution for picto in the first solution ERROR: no solution for picto in the first solution ERROR: no solution for picto in the first solution ERROR: no solution for picto in the first solution ERROR: no solution for picto in the first solution ERROR: no solution for picto in the first solution ERROR: no solution for picto in the first solution ERROR: no solution for picto in the first solution ERROR: no solution for picto in the first solution ERROR: no solution for picto in the first solution ERROR: no solution for picto in the first solution ERROR: no solution for picto in the first solution ERROR: no solution for picto in the first solution ----------- result to be analyzed ----------- {'name': 'tomate', 'quantity': 'plusieurs morceaux', 'type': 'food', 'event': 'unknownEvent'} 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 '% tomate %' AND (V_NormTrademark = '' OR V_NormTrademark IS NULL) ------------- Found solution (max 20) -------------- Tomate - tomate - crue - - 50564 - - - CIQ#9019c33adc1aff1aeff07888f760e3dc Tomate - tomate - purée - - 0 - - - CIQ#98e08e3b00fecca745d7da29e1015a95 Tomate - tomate - pulpe - - 0 - - - CIQ#fd785fdebdb36567c615d2cf46456ffd Tomate - tomate - concentré - - 0 - - - CIQ#7020e6d5e5bd9e09aaa1661220ba09b7 Tomate - tomate - pelée, égouttée - - 0 - - - CIQ#e42ed02a1db9c324a72333e04d401dc1 Tomate - tomate - double concentré - - 0 - - - CIQ#316f9d6fdf5ec84b18998fae96416e09 Tomate - tomate - séchée, à l'huile - - 0 - - - CIQ#b7e1592c157fef2c1429cdc04e65f429 Tomate - tomate - rôtie/cuite au four - - 0 - - - CIQ#abc1ee10e1ef1b8d9ea01e5cf5081ac9 Tomate - tomate - pulpe et peau, rôtie/cuite au four - - 0 - - - CIQ#a670b9fa38af8c6557b321a08d7ab367 Tomate Ronde - tomate ronde - crue - - 0 - - - CIQ#684dc9134dc864e3c83f5330fa9965d4 Tomate Farcie - tomate farcie - - - 1889 - - - CIQ#6662d127dcc7f87a176e7cda4540b6d5 Tomate Cerise - tomate cerise - crue - - 0 - - - CIQ#9f76e2172737f480f1c9b66f3627bfb0 Tomate Grappe - tomate grappe - crue - - 0 - - - CIQ#2bdccc054e39de9382dcb2ff97b1204d Tomate Cerise - tomate cerise - tomate cerise - - 0 - - - KCA#fc7d1647e177b261c9a22262037f6216 Tomate Séchée - tomate sechee - tomate séchée - - 0 - - - KCA#1dfa8e1ad113a5175e6a3ba4bee46416 Tomates au Four - tomate four - au four - - 0 - - - KCA#7bd06a9534bdcb97e7af0143ac0124d5 Tomates Farcies - tomate farcie - tomates farcies - - 0 - - - KCA#6e01a7596f6a74b9bca3e51ca2721e81 Tomates Tartares - tomate tartare - tomates tartares - - 0 - - - KCA#e15190c59aa8508125d81de65be88670 Tomate Concentrée - tomate concentree - tomate concentrée - - 0 - - - KCA#22854ad0ad81beeccc0841c1f0c5d66c Tomates Provençales - tomate provencale - tomates provençales - - 0 - - - KCA#799358a4b450be03bfd4014d3908c6dc ---------------------------------------------------- ERROR: no solution for picto in the first solution ERROR: no solution for picto in the first solution ERROR: no solution for picto in the first solution ERROR: no solution for picto in the first solution ERROR: no solution for picto in the first solution ERROR: no solution for picto in the first solution ERROR: no solution for picto in the first solution ERROR: no solution for picto in the first solution ERROR: no solution for picto in the first solution --------------------------------- final result ----------------------------------- {'prompt': '', 'model': 'mistral-large-2411', 'imagePath': '/home/debian/html/nutritwin/output_llm/68b548116b7fe/capture.jpg', 'intents': ['Identify foods and beverages in an image'], 'solutions': {'nutrition': [{'name': 'Guacamole', 'normName': ' guacamole ', 'comment': '', 'normComment': '', 'rank': 0, 'id': 'OFF#7f36a7e26990c9e3579b42ed2f150b56', 'quantity': '20 grammes', 'quantityLem': '20 gramme', 'pack': ['CSL.w18', 'CCL.w5'], 'type': 'food', 'gtin': '0046000815213', 'gtinRef': '0046000815213', 'brand': 'General Mills', 'time': '', 'event': 'unknownEvent', 'serving': '', 'posiNormName': 0}, {'name': 'Tomate', 'normName': ' tomate ', 'comment': 'crue', 'normComment': ' crue ', 'rank': 50564, 'id': 'CIQ#9019c33adc1aff1aeff07888f760e3dc', 'quantity': 'plusieurs morceaux', 'quantityLem': 'plusieur morceau', 'pack': ['TOM.w150'], 'type': 'food', 'gtin': '', 'gtinRef': '', 'brand': '', 'time': '', 'event': 'unknownEvent', 'serving': '', 'posiNormName': 0}], 'activity': [], 'response': {}}, 'cputime': 3.378357172012329} ---------------------------------------------------------------------------------- LLM CPU Time: 3.378357172012329