Input path: /home/debian/html/nutritwin/output_llm/68d7bf865db84/input.json Output path: /home/debian/html/nutritwin/output_llm/68d7bf865db84/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/68d7bf865db84/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": "jambon", "quantity": "deux tranches", "type": "food", "event": "declaration" } ] ----------------------------------------------------------------------------- ----------------- Make it compliant ------------------ [ { "name": "jambon", "quantity": "deux tranches", "type": "food", "event": "declaration" } ] ------------------------------------------------------ ------------------------ After simplification ------------------------ [ { "name": "jambon", "quantity": "deux tranches", "type": "food", "event": "declaration" } ] ---------------------------------------------------------------------- --------------------------------- LLM result ----------------------------------- {'response': [{'name': 'jambon', 'quantity': 'deux tranches', 'type': 'food', 'event': 'declaration'}], 'cost': 0.0} -------------------------------------------------------------------------------- ----------- result to be analyzed ----------- {'name': 'jambon', 'quantity': 'deux tranches', '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 '% jambon %' AND (V_NormTrademark = '' OR V_NormTrademark IS NULL) ------------- Found solution (max 20) -------------- Jambon Cru - jambon cru - - - 9885 - - - CIQ#64b8482a5f9494f91650a6dfbb0cd41e Jambon Sec - jambon sec - - - 0 - - - CIQ#96c8fe38103fc721a15cfe55d6e25c6f Jambon Cru - jambon cru - fumé - - 268 - - - CIQ#5f3f73264b7c8e8500821bffaac09aee Jambon Sec - jambon sec - découenné, dégraissé - - 293 - - - CIQ#25959c69f01c1f2120ccc677017fa727 Jambon Cru - jambon cru - fumé, allégé en matière grasse - - 0 - - - CIQ#f647a53f900ffb0f8b6bcc1b9daac3fd Jambon Fumé - jambon fume - - - 1235 - - - KCA#b89a3b14af6277985c3d77e8a43fd3a7 Jambon Cuit - jambon cuit - fumé - - 130 - - - CIQ#17ca7e15b0319f1e287cbd0bcf02e149 Jambon Cuit - jambon cuit - choix - - 0 - - - CIQ#31a3ba17bd765304c35083900245a906 Jambon Cuit - jambon cuit - supérieur - - 879 - - - CIQ#62b09fb38df99e94d05d097272b0f943 Jambon Cuit - jambon cuit - choix, avec couenne - - 0 - - - CIQ#c197beb44fda0f03581cdd01ee751078 Jambon Cuit - jambon cuit - supérieur, découenné - - 0 - - - CIQ#a4feb0298e2ed9bf7086021f843d5542 Jambon Cuit - jambon cuit - supérieur, avec couenne - - 0 - - - CIQ#44f954aa2607fc98de99e42c7a2f34f0 Jambon Cuit - jambon cuit - choix, découenné dégraissé - - 0 - - - CIQ#1bdbfa77737e32f3afd8b85235c13da8 Jambon Cuit - jambon cuit - de Paris, découenné dégraissé - - 0 - - - CIQ#2204461860d60e77475581012d525590 Jambon Cuit - jambon cuit - supérieur, découenné dégraissé - - 0 - - - CIQ#7fe80de772280767444b552c0124ab0f Jambon Cuit - jambon cuit - supérieur, à teneur réduite en sel - - 0 - - - CIQ#f6e3b7457066170ebc96fe96171fba23 Jambon Blanc - jambon blanc - - - 41088 - - - KCA#a2c3580fad4917288fe40406fb88cadb Jambon Bayonne - jambon bayonne - - - 2108 - - - KCA#a7501ed926d61fc6282a9dc417593554 Jambon Persillé - jambon persille - - - 315 - - - KCA#a68e12a46f2795c6c267b411dd8111f4 Jambon de Poulet - jambon de poulet - - - 5421 - - - KCA#8a8c7fe60575ff37bd0a2f58c58a75a0 ---------------------------------------------------- --------------------------------- final result ----------------------------------- {'prompt': '', 'model': 'mistral-large-2411', 'imagePath': '/home/debian/html/nutritwin/output_llm/68d7bf865db84/capture.jpg', 'intents': ['Identify foods and beverages in an image'], 'solutions': {'nutrition': [{'name': 'Jambon Cru', 'normName': ' jambon cru ', 'comment': '', 'normComment': '', 'rank': 9885, 'id': 'CIQ#64b8482a5f9494f91650a6dfbb0cd41e', 'quantity': 'deux tranches', 'quantityLem': '2 tranche', 'pack': ['TR3.w25'], 'type': 'food', 'gtin': '', 'gtinRef': '', 'brand': '', 'time': '', 'event': 'declaration', 'serving': 'TR3-200', 'posiNormName': 0}], 'activity': [], 'response': {}}, 'cputime': 1.4867498874664307} ---------------------------------------------------------------------------------- LLM CPU Time: 1.4867498874664307