Input path: /home/debian/html/nutritwin/output_llm/684814882769b/input.json Output path: /home/debian/html/nutritwin/output_llm/684814882769b/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/684814882769b/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": "yaourt", "quantity": "un", "brand": "Light & Free", "type": "food", "event": "declaration" } ] ----------------------------------------------------------------------------- ----------------- Make it compliant ------------------ [ { "name": "yaourt", "quantity": "un", "brand": "Light & Free", "type": "food", "event": "declaration" } ] ------------------------------------------------------ ------------------------ After simplification ------------------------ [ { "name": "yaourt", "quantity": "un", "brand": "Light & Free", "type": "food", "event": "declaration" } ] ---------------------------------------------------------------------- --------------------------------- LLM result ----------------------------------- {'response': [{'name': 'yaourt', 'quantity': 'un', 'brand': 'Light & Free', 'type': 'food', 'event': 'declaration'}], 'cost': 0.0} -------------------------------------------------------------------------------- ----------- result to be analyzed ----------- {'name': 'yaourt', 'quantity': 'un', 'brand': 'Light & Free', 'type': 'food', '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 '% yaourt %' AND V_NormTrademark LIKE '%light free%' --> CPU time in DB: 0.1383 seconds Word: Yaourt - dist: 0.294572114944458 - row: 4140 Word: Yaourt Flux - dist: 0.5238911509513855 - row: 35526 Word: Yaourt Grec - dist: 0.5391507148742676 - row: 7845 Word: Yaourt Liquide - dist: 0.5401002168655396 - row: 57393 Word: Yaourt Nature - dist: 0.5403639078140259 - row: 4248 Found embedding word: Yaourt 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 = 'Yaourt' ------------- Found solution (max 20) -------------- Yaourt - yaourt - - Danone - 8 - 13561390 - 13561390 - OFF#d05c7bad1833108d7aac87bb2be2ae6f Yaourt - yaourt - - Nestlé - 0 - 3023290063040 - 3023290063040 - OFF#5e7380a0e90e3d49231e306e9e54b5c2 Yaourt - yaourt - - group Bel - 0 - 3033491924132 - 3033491924132 - OFF#fa39f36ab6d0b5e31c62bfd54e04a6e2 Yaourt - yaourt - - Malo - 0 - 3278692420049 - 3278692420049 - OFF#91ec304e45d6d6a94154c0adab746a6e Yaourt - yaourt - - Yoplait - 0 - 3291330010570 - 3291330010570 - OFF#9365be1a724e4bd47814d9f95e3402d5 Yaourt - yaourt - - Auchan - 0 - 3596710392025 - 3596710392025 - OFF#596d35ba9b2af36262672c15fba8f859 Yaourt - yaourt - - Naturalia - 0 - 3700036907546 - 3700036907546 - OFF#2afed200486a9668882c881f9818a075 Yaourt - yaourt - - Carrefour - 0 - 5400101008366 - 5400101008366 - OFF#275a5c49e6acac1cc12872b97655e370 Yaourt - yaourt - - Delhaize - 0 - 5400601351290 - 5400601351290 - OFF#ae4df6872bc6509c1c3a7df1695f5e56 Yaourt - yaourt - - Coop - 0 - 7613379614186 - 7613379614186 - OFF#88252fa9fab9cfcee73597f15ba0f6f1 Yaourt - yaourt - - Danone - 0 - 3033491215353 - 13561390 - OFF#a44bf4719bfc97599207df830244621c Yaourt - yaourt - - Danone - 0 - 5410146417061 - 13561390 - OFF#5022f1e2b789f0f6aa44416baa0d7560 Yaourt - yaourt - - Danone - 0 - 5410146420597 - 13561390 - OFF#d7b8d211568f869d3261da4d29401ab5 Yaourt - yaourt - - Danone - 0 - 3330261041205 - 13561390 - OFF#b6e99f227eff5773c1c5fdbe53fef3b5 Yaourt - yaourt - - Danone - 0 - 3330261030506 - 13561390 - OFF#3eeb8a1eb3478b34843adaadf4d4ce85 Yaourt - yaourt - - Danone - 0 - 3330261030100 - 13561390 - OFF#5acbbfe23f23953da5c23e9d829e30f0 Yaourt - yaourt - - Danone - 0 - 5601050034950 - 13561390 - OFF#a3db60fd82209c7039e34013035e385c Yaourt - yaourt - - Danone - 0 - 5410146418273 - 13561390 - OFF#0b585358bc172d2e308131ce70de0c80 Yaourt - yaourt - - Danone - 0 - 3330261020705 - 13561390 - OFF#a99b39ad9eae80cbe801b143f7ed6ed7 Yaourt - yaourt - - Danone - 0 - 3033491235740 - 13561390 - OFF#9ffb5713e93620a28232bb9bd618ede4 ---------------------------------------------------- --------------------------------- final result ----------------------------------- {'prompt': '', 'model': 'mistral-large-2411', 'imagePath': '/home/debian/html/nutritwin/output_llm/684814882769b/capture.jpg', 'intents': ['Identify foods and beverages in an image'], 'solutions': {'nutrition': [{'name': 'Yaourt', 'normName': ' yaourt ', 'comment': '', 'normComment': '', 'rank': 8, 'id': 'OFF#d05c7bad1833108d7aac87bb2be2ae6f', 'quantity': 'un', 'quantityLem': '1', 'pack': ['YA2.w125', 'YA9.w125'], 'type': 'food', 'gtin': '13561390', 'gtinRef': '13561390', 'brand': 'Danone', 'time': '', 'event': 'declaration', 'serving': 'YA2-100', 'posiNormName': 0}], 'activity': [], 'response': {}}, 'cputime': 2.0543973445892334} ---------------------------------------------------------------------------------- LLM CPU Time: 2.0543973445892334