Input path: /home/debian/html/nutritwin/output_llm/6799f41c96797/input.json Output path: /home/debian/html/nutritwin/output_llm/6799f41c96797/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/6799f41c96797/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": "vin", "quantity": "un verre", "type": "beverage", "event": "declaration" } ] ----------------------------------------------------------------------------- ----------------- Make it compliant ------------------ [ { "name": "vin", "quantity": "un verre", "type": "beverage", "event": "declaration" } ] ------------------------------------------------------ ------------------------ After simplification ------------------------ [ { "name": "vin", "quantity": "un verre", "type": "beverage", "event": "declaration" } ] ---------------------------------------------------------------------- --------------------------------- LLM result ----------------------------------- {'response': [{'name': 'vin', 'quantity': 'un verre', 'type': 'beverage', 'event': 'declaration'}], 'cost': 0.0} -------------------------------------------------------------------------------- ----------- result to be analyzed ----------- {'name': 'vin', 'quantity': 'un verre', 'type': 'beverage', '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 '% vin %' AND (V_NormTrademark = '' OR V_NormTrademark IS NULL) ------------- Found solution (max 20) -------------- Vin Cuit - vin cuit - - - 476 - - - KCA#413dce4eebdf3fdf2076ef50ae74590b Vin Blanc - vin blanc - - - 22924 - - - KCA#0a40d7fc7234085d12af2089c75f862b Vin Rouge - vin rouge - - - 0 - - - CIQ#0247898eabeefe3884ee430550359cfb Vin Rouge 9° - vin rouge 9° - - - 235 - - - KCA#9db74ea9610e574a4b5fd169739808d7 Vin Rouge 13° - vin rouge 13° - - - 27665 - - - KCA#f965995ec93171a22515f7141f3fcaec Vin Rouge 12° - vin rouge 12° - - - 13758 - - - KCA#6576b07568c57c226d3a8a15baa81be6 Vin Rouge 10° - vin rouge 10° - - - 1065 - - - KCA#8c95a77df14a31cf02c05e7b2258cdf9 Vin Rouge 11° - vin rouge 11° - - - 996 - - - KCA#4defe56e99d409c448e479743de50aad Vin Rouge 14° - vin rouge 14° - - - 891 - - - KCA#7b7cb654b939b936970e863f0cf9a707 Vin Rouge 15° - vin rouge 15° - - - 285 - - - KCA#522430b440ab36f2b30e37915271d575 Coq au Vin - coq vin - - - 97 - - - CIQ#588d397f09445cf782a6fd7abf34dd22 Bar au Vin Blanc - bar vin blanc - - - 30 - - - KCA#1ad8f1259ed6c3bf39ce51b22b7f6ec5 Pêches au Vin - peche vin - - - 39 - - - KCA#a59eaab7bfcb9b09ada234a6e2c1a7d3 Poule au Vin Rouge - poule vin rouge - - - 0 - - - KCA#16152425348f25d2abe48e2d55c22eca Dorade au Vin Blanc - dorade vin blanc - - - 140 - - - KCA#31a50d86b8de5651b38155aedb86fc12 Pruneaux au Vin - pruneau vin - - - 48 - - - KCA#0d4b4d95ca0c7588288992b65d0c876a Chipolatas au Vin Blanc - chipolata vin blanc - - - 8 - - - KCA#5fba9f7a50300f3dec74a85c0b8a3ab7 Steaks Sautés au Vin - steak saute vin - au vin - - 0 - - - KCA#3830e269f3a7cb20f83532fcaf5e9610 Vinaigre de Vin Rouge - vinaigre de vin rouge - - - 0 - - - CIQ#0e65f9a58f80513c4123cfe859bb81f5 Eau de Vie de Vin - eau de vie de vin - type armagnac, cognac - - 0 - - - CIQ#c0440021ea15aa2abf11853bbd2191a4 ---------------------------------------------------- --------------------------------- final result ----------------------------------- {'prompt': '', 'model': 'mistral-large-2411', 'imagePath': '/home/debian/html/nutritwin/output_llm/6799f41c96797/capture.jpg', 'intents': ['Identify foods and beverages in an image'], 'solutions': {'nutrition': [{'name': 'Vin Cuit', 'normName': ' vin cuit ', 'comment': '', 'normComment': '', 'rank': 476, 'id': 'KCA#413dce4eebdf3fdf2076ef50ae74590b', 'quantity': 'un verre', 'quantityLem': '1 verre', 'pack': ['VAA'], 'type': 'beverage', 'gtin': '', 'gtinRef': '', 'brand': '', 'time': '', 'event': 'declaration', 'serving': 'VAA-100', 'posiNormName': 0}], 'activity': [], 'response': {}}, 'cputime': 2.1971559524536133} ---------------------------------------------------------------------------------- LLM CPU Time: 2.1971559524536133