Input path: /home/debian/html/nutritwin/output_llm/675ddd442e9fd/input.json Output path: /home/debian/html/nutritwin/output_llm/675ddd442e9fd/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/675ddd442e9fd/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": "Cordon Bleu", "quantity": "deux", "cookingMethod": "préparé au four", "type": "food", "brand": "Père Dodu", "company": "Père Dodu", "event": "intent" } ] ----------------------------------------------------------------------------- ----------------- Make it compliant ------------------ [ { "name": "Cordon Bleu", "quantity": "deux", "cookingMethod": "préparé au four", "type": "food", "brand": "Père Dodu", "company": "Père Dodu", "event": "intent" } ] ------------------------------------------------------ ------------------------ After simplification ------------------------ [ { "name": "Cordon Bleu", "quantity": "deux", "cookingMethod": "pr\u00e9par\u00e9 au four", "type": "food", "brand": "P\u00e8re Dodu", "company": "P\u00e8re Dodu", "event": "intent" } ] ---------------------------------------------------------------------- --------------------------------- LLM result ----------------------------------- {'response': [{'name': 'Cordon Bleu', 'quantity': 'deux', 'cookingMethod': 'préparé au four', 'type': 'food', 'brand': 'Père Dodu', 'company': 'Père Dodu', 'event': 'intent'}], 'cost': 0.0} -------------------------------------------------------------------------------- ----------- result to be analyzed ----------- {'name': 'Cordon Bleu', 'quantity': 'deux', 'cookingMethod': 'préparé au four', 'type': 'food', 'brand': 'Père Dodu', 'company': 'Père Dodu', 'event': 'intent'} 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 '% cordon bleu %' AND V_NormTrademark LIKE '%pere dodu%' --> CPU time in DB: 0.2382 seconds Word: Cordon Bleu - dist: 0.001028344500809908 - row: 3463 Word: Cordon Bleu au Poulet - dist: 0.40373727679252625 - row: 11430 Word: Cordon Bleu de Volaille - dist: 0.40699076652526855 - row: 4428 Word: Cordon Bleu de Dinde - dist: 0.4387933611869812 - row: 28101 Word: Cordon Bleu et Purée de Pommes de Terre - dist: 0.4794013500213623 - row: 34404 Found embedding word: Cordon Bleu 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 = 'Cordon Bleu' ------------- Found solution (max 20) -------------- Cordon Bleu - cordon bleu - - - 2924 - - - KCA#d2ef4552de84609df5be701b1044b770 Cordon Bleu - cordon bleu - - Maitre Coq - 0 - 3230890040986 - 3230890040986 - OFF#91878875caa107efbc9f3eb1fe8d3373 Cordon Bleu - cordon bleu - - Le Gaulois - 0 - 85668584 - 85668584 - OFF#d86623f13ad23b333bfd0720b65738d3 ---------------------------------------------------- --------------------------------- final result ----------------------------------- {'prompt': '', 'model': 'mistral-large-2411', 'imagePath': '/home/debian/html/nutritwin/output_llm/675ddd442e9fd/capture.jpg', 'intents': ['Identify foods and beverages in an image'], 'solutions': {'nutrition': [{'name': 'Cordon Bleu', 'normName': ' cordon bleu ', 'comment': '', 'normComment': '', 'rank': 2924, 'id': 'KCA#d2ef4552de84609df5be701b1044b770', 'quantity': 'deux', 'quantityLem': '2', 'pack': ['GA1.w100'], 'type': 'food', 'gtin': '', 'gtinRef': '', 'brand': '', 'time': '', 'event': 'intent', 'serving': 'GA1-200', 'posiNormName': 0}], 'activity': [], 'response': {}}, 'cputime': 4.00044584274292} ---------------------------------------------------------------------------------- LLM CPU Time: 4.00044584274292