Input path: /home/debian/html/nutritwin/output_llm/6853e7a47cff5/input.json Output path: /home/debian/html/nutritwin/output_llm/6853e7a47cff5/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/6853e7a47cff5/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": "saucisson", "quantity": "un", "type": "food", "event": "unknownEvent" } ] ----------------------------------------------------------------------------- ----------------- Make it compliant ------------------ [ { "name": "saucisson", "quantity": "un", "type": "food", "event": "unknownEvent" } ] ------------------------------------------------------ ------------------------ After simplification ------------------------ [ { "name": "saucisson", "quantity": "un", "type": "food", "event": "unknownEvent" } ] ---------------------------------------------------------------------- --------------------------------- LLM result ----------------------------------- {'response': [{'name': 'saucisson', 'quantity': 'un', 'type': 'food', 'event': 'unknownEvent'}], 'cost': 0.0} -------------------------------------------------------------------------------- ----------- result to be analyzed ----------- {'name': 'saucisson', 'quantity': 'un', '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 '% saucisson %' AND (V_NormTrademark = '' OR V_NormTrademark IS NULL) ------------- Found solution (max 20) -------------- Saucisson Sec - saucisson sec - - - 12884 - - - CIQ#c5e0d6e793c69889cc8d0eae20701a53 Saucisson à l'Ail - saucisson ail - - - 988 - - - CIQ#a8c22f43e47e1d57de86c649c45531b7 Saucisson Brioché - saucisson brioche - - - 6 - - - CIQ#2aacf1669bcaf8c7e2a9c6945ebc97e6 Saucisson de Paris - saucisson de pari - - - 0 - - - CIQ#c00091f7ec85a77e42b56c951e697f9a Saucisson de Paris - saucisson de pari - fumé - - 0 - - - CIQ#1d1247904ade35b777510560d63159e9 Saucisson Sec Pur Porc - saucisson sec pur porc - - - 219 - - - CIQ#eb15e1db55ad4a347f9ba03a2e83b840 Saucisson Sec Pur Porc - saucisson sec pur porc - qualité supérieure - - 0 - - - CIQ#62213e836d08b892e7eb1b2550ecb54e Saucisson Cuit Pur Porc - saucisson cuit pur porc - - - 0 - - - CIQ#070df1dbb406a501caea7b0aa6a3210f Saucisson Sec aux Noix Et/ou Noisettes - saucisson sec au noix et/ou noisette - - - 0 - - - CIQ#7ca1c35bcbabd2cf0891661c40e8f457 Mini Saucissons Secs - mini saucisson sec - - - 460 - - - KCA#e1d4505826c877f5b2812000118baa33 Mini Saucissons Secs aux Noix - mini saucisson sec au noix - - - 60 - - - KCA#d4e235908d2ff232a5bf08080c5b6d76 Salade de Céleri au Saucisson - salade de celeri saucisson - - - 32 - - - KCA#4d0f28df020683ad006ad953752ad35c ---------------------------------------------------- ERROR: no solution for picto in the first solution --------------------------------- final result ----------------------------------- {'prompt': '', 'model': 'mistral-large-2411', 'imagePath': '/home/debian/html/nutritwin/output_llm/6853e7a47cff5/capture.jpg', 'intents': ['Identify foods and beverages in an image'], 'solutions': {'nutrition': [{'name': 'Saucisson Sec', 'normName': ' saucisson sec ', 'comment': '', 'normComment': '', 'rank': 12884, 'id': 'CIQ#c5e0d6e793c69889cc8d0eae20701a53', 'quantity': 'un', 'quantityLem': '1', 'pack': ['TR2.w10'], 'type': 'food', 'gtin': '', 'gtinRef': '', 'brand': '', 'time': '', 'event': 'unknownEvent', 'serving': '', 'posiNormName': 0}], 'activity': [], 'response': {}}, 'cputime': 1.2638788223266602} ---------------------------------------------------------------------------------- LLM CPU Time: 1.2638788223266602