Input path: /home/debian/html/nutritwin/output_llm/6818c16c7453e/input.json Output path: /home/debian/html/nutritwin/output_llm/6818c16c7453e/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/6818c16c7453e/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": "chocolat au lait", "quantity": "une tablette", "type": "food", "brand": "Milka", "event": "unknownEvent" } ] ----------------------------------------------------------------------------- ----------------- Make it compliant ------------------ [ { "name": "chocolat au lait", "quantity": "une tablette", "type": "food", "brand": "Milka", "event": "unknownEvent" } ] ------------------------------------------------------ ------------------------ After simplification ------------------------ [ { "name": "chocolat au lait", "quantity": "une tablette", "type": "food", "brand": "Milka", "event": "unknownEvent" } ] ---------------------------------------------------------------------- --------------------------------- LLM result ----------------------------------- {'response': [{'name': 'chocolat au lait', 'quantity': 'une tablette', 'type': 'food', 'brand': 'Milka', 'event': 'unknownEvent'}], 'cost': 0.0} -------------------------------------------------------------------------------- ----------- result to be analyzed ----------- {'name': 'chocolat au lait', 'quantity': 'une tablette', 'type': 'food', 'brand': 'Milka', '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 '% chocolat lait %' AND V_NormTrademark LIKE '%milka%' --> CPU time in DB: 0.1206 seconds Word: Chocolat au Lait - dist: 0.35397329926490784 - row: 3620 Word: Chocolat au Lait BIO - dist: 0.4626695513725281 - row: 47179 Word: Chocolat au Lait 40% de Cacao - dist: 0.47008830308914185 - row: 33537 Word: Chocolat au Lait Suisse - dist: 0.470720499753952 - row: 9533 Word: Crème Chocolat au Lait - dist: 0.4746347963809967 - row: 43639 Found embedding word: Chocolat au Lait 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 = 'Chocolat au Lait' ------------- Found solution (max 20) -------------- Chocolat au Lait - chocolat lait - - - 17100 - - - KCA#7a8849f6f600e38254b01cd2dcb2e2eb Chocolat au Lait - chocolat lait - - U - 0 - 0954867222672 - 0954867222672 - OFF#dd03c9137a5c45d14d443663fccdcbd9 Chocolat au Lait - chocolat lait - - Jeff de Bruges - 0 - 2000000049516 - 2000000049516 - OFF#bed5799a7ffae1a97933e0fe8dd83e63 Chocolat au Lait - chocolat lait - - Lidl - 0 - 20080198 - 20080198 - OFF#89f108181bad3319ddffcc715085140f Chocolat au Lait - chocolat lait - - Nestlé - 0 - 3033710001286 - 3033710001286 - OFF#0dd85427e34ac25462ff4f6bec1c45bd Chocolat au Lait - chocolat lait - - Mondelez International - 0 - 3045140105762 - 3045140105762 - OFF#289c071f5dd1e15111e28bcf0d1376d8 Chocolat au Lait - chocolat lait - - Lindt - 0 - 3046920080088 - 3046920080088 - OFF#5a5c5b1047d9db4374694a46abb89729 Chocolat au Lait - chocolat lait - - Carrefour - 0 - 3245412417924 - 3245412417924 - OFF#c35b15e4e0dca42175c788091513f813 Chocolat au Lait - chocolat lait - - Cora - 0 - 3257980095442 - 3257980095442 - OFF#448e6eeecb5f0190d035936bd744a28b Chocolat au Lait - chocolat lait - - Belle France - 0 - 3258561060088 - 3258561060088 - OFF#0b75d879a124d6d2a584b4e6fba12875 Chocolat au Lait - chocolat lait - - Leader Price - 0 - 3263852201514 - 3263852201514 - OFF#4884152ded8a7bc0a07f08435923980f Chocolat au Lait - chocolat lait - - La Vie Claire - 0 - 3266191104058 - 3266191104058 - OFF#e1820d6fd9f717354239eea1f1aa9db8 Chocolat au Lait - chocolat lait - - Bio Village - 0 - 3564707177962 - 3564707177962 - OFF#972297e7c68b8c35a2b08cc77a4c388a Chocolat au Lait - chocolat lait - - Auchan - 0 - 3596710349388 - 3596710349388 - OFF#f939b6d632a8cb55d43b0a0f92f44f75 Chocolat au Lait - chocolat lait - - Poulain - 0 - 3664346300148 - 3664346300148 - OFF#e8b11710f7231a0c3ba294699309fcf3 Chocolat au Lait - chocolat lait - - Suchard - 0 - 3664346309134 - 3664346309134 - OFF#d282ec99cf67b62154568a98471d2077 Chocolat au Lait - chocolat lait - - Delhaize - 0 - 5400111062228 - 5400111062228 - OFF#a5444518bb92c5c38d42742e80f435f2 Chocolat au Lait - chocolat lait - - Leonidas - 0 - 5420006320608 - 5420006320608 - OFF#ded4821ec62fc5ffdc0a850d2d057085 Chocolat au Lait - chocolat lait - - Coop - 0 - 7613356228009 - 7613356228009 - OFF#2308ee4a3e7262b0cd570ffcd87ac1d2 Chocolat au Lait - chocolat lait - - Dia - 0 - 8480017129963 - 8480017129963 - OFF#5922bf915283f7415d49ec3afd5dffd5 ---------------------------------------------------- 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 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 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/6818c16c7453e/capture.jpg', 'intents': ['Identify foods and beverages in an image'], 'solutions': {'nutrition': [{'name': 'Chocolat au Lait', 'normName': ' chocolat lait ', 'comment': '', 'normComment': '', 'rank': 17100, 'id': 'KCA#7a8849f6f600e38254b01cd2dcb2e2eb', 'quantity': 'une tablette', 'quantityLem': '1 tablette', 'pack': ['CHO.w7'], 'type': 'food', 'gtin': '', 'gtinRef': '', 'brand': '', 'time': '', 'event': 'unknownEvent', 'serving': '', 'posiNormName': 0}], 'activity': [], 'response': {}}, 'cputime': 4.054014682769775} ---------------------------------------------------------------------------------- LLM CPU Time: 4.054014682769775