Input path: /home/debian/html/nutritwin/output_llm/68247a2a3673a/input.json Output path: /home/debian/html/nutritwin/output_llm/68247a2a3673a/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/68247a2a3673a/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": "lentilles", "quantity": "un bol", "cookingMethod": "cuites", "type": "food", "event": "declaration" } ] ----------------------------------------------------------------------------- ----------------- Make it compliant ------------------ [ { "name": "lentilles", "quantity": "un bol", "cookingMethod": "cuites", "type": "food", "event": "declaration" } ] ------------------------------------------------------ ------------------------ After simplification ------------------------ [ { "name": "lentilles", "quantity": "un bol", "cookingMethod": "cuites", "type": "food", "event": "declaration" } ] ---------------------------------------------------------------------- --------------------------------- LLM result ----------------------------------- {'response': [{'name': 'lentilles', 'quantity': 'un bol', 'cookingMethod': 'cuites', 'type': 'food', 'event': 'declaration'}], 'cost': 0.0} -------------------------------------------------------------------------------- ----------- result to be analyzed ----------- {'name': 'lentilles', 'quantity': 'un bol', 'cookingMethod': 'cuites', '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 '% lentille %' AND (V_NormTrademark = '' OR V_NormTrademark IS NULL) ------------- Found solution (max 20) -------------- Lentille Verte - lentille verte - bouillie/cuite à l'eau - - 0 - - - CIQ#2c651245fd51430a08f5f743a38e625d Lentilles au Chou - lentille chou - - - 80 - - - KCA#489e1f0cd1ca649bf933982eeea09c76 Lentilles au Chorizo - lentille chorizo - - - 37 - - - KCA#861eb5d32ed6b0481dec0520a24603f9 Lentilles au Tapioca - lentille tapioca - - - 14 - - - KCA#ae447a6202b0cfdacefc0178b618fa9f Lentilles à la Tomate - lentille tomate - - - 90 - - - KCA#390cc8fc9ac0347cc368d9edb55c75ba Lentilles à l'Indienne - lentille indienne - - - 131 - - - KCA#aafe9bf5fa367006ca8495636212dd2c Lentilles aux Epinards - lentille au epinard - - - 22 - - - KCA#27e5618f833b2a5e6ef3f51546ae28c8 Lentilles au Petit Salé - lentille petit sale - - - 111 - - - KCA#d5a13af958f13e7553290f9759daf561 Lentilles à l'Alsacienne - lentille alsacienne - - - 11 - - - KCA#139499582757ddc0bc0c3343a90c1e3e Lentilles à la Mexicaine - lentille mexicaine - - - 6 - - - KCA#ac43d43bdd48b5149d3e11ecdc00e940 Lentilles à la Dijonnaise - lentille dijonnaise - - - 17 - - - KCA#44c977cc329aca863f2d3bade08576ca Lentilles au Fromage Blanc - lentille fromage blanc - - - 15 - - - KCA#9dc98801283c17ef5c78fb1b99fbbde7 Lentilles Cuisinées Conserve - lentille cuisinee conserve - - - 92 - - - KCA#eb0782e831ea8edc9e8d7b277f60258e Lentilles en Salade à l'Anchois - lentille en salade anchoi - - - 149 - - - KCA#e6f38f200d1a50536880339bae2385a6 Lentilles Brunes à la Courgette et au Chorizo - lentille brune courgette chorizo - - - 6 - - - KCA#488b3d0b5e6b068cb458940010656fd5 Salade Lentilles Tofu - salade lentille tofu - - - 274 - - - KCA#30c6087242cdba6fd93fe05b010645b7 Porc aux Lentilles - porc au lentille - - - 15 - - - KCA#936ca9b6d1276ef782aa1eee7aa55433 Soupe de Lentilles - soupe de lentille - de lentilles - - 0 - - - KCA#9087063b7a7bfcac582648b7dae34ee5 Soupe aux Lentilles - soupe au lentille - - - 0 - - - CIQ#5c3dd6ee1e4355ffb521410c8cfdaf7f Potage aux Lentilles - potage au lentille - - - 28 - - - KCA#c2f96b29ac915e6438bbe8d85a78e370 ---------------------------------------------------- --------------------------------- final result ----------------------------------- {'prompt': '', 'model': 'mistral-large-2411', 'imagePath': '/home/debian/html/nutritwin/output_llm/68247a2a3673a/capture.jpg', 'intents': ['Identify foods and beverages in an image'], 'solutions': {'nutrition': [{'name': 'Lentille Verte', 'normName': ' lentille verte ', 'comment': "bouillie/cuite à l'eau", 'normComment': ' bouillie/cuite eau ', 'rank': 0, 'id': 'CIQ#2c651245fd51430a08f5f743a38e625d', 'quantity': 'un bol', 'quantityLem': '1 bol', 'pack': ['LEG.w150'], 'type': 'food', 'gtin': '', 'gtinRef': '', 'brand': '', 'time': '', 'event': 'declaration', 'serving': 'LEG.w150-1bol', 'posiNormName': 0}], 'activity': [], 'response': {}}, 'cputime': 49.47966432571411} ---------------------------------------------------------------------------------- LLM CPU Time: 49.47966432571411