Input path: /home/debian/html/nutritwin/output_llm/67572a7ec61eb/input.json Output path: /home/debian/html/nutritwin/output_llm/67572a7ec61eb/output.json Input text: Ensuite j'ai bu une canette de Fanta. 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: Ensuite j'ai bu une canette de Fanta. ================================================================================================================================== ==================================== Prompt ============================================= Identify in this list of intents: ["Identify food and beverage consumption or declaration", "Identify the user physical activity", "Answer a nutrition question", "Other intent"], the intents of the prompt: ###Ensuite j'ai bu une canette de Fanta.###. Format the result in JSON format: {"intents": []}. ========================================================================================= ------------------------------ LLM Raw response ----------------------------- {"intents": ["Identify food and beverage consumption or declaration"]} ----------------------------------------------------------------------------- ----------------- Make it compliant ------------------ {"intents": ["Identify food and beverage consumption or declaration"]} ------------------------------------------------------ ERROR: wrong object representation: {'intents': ['Identify food and beverage consumption or declaration']} ------------------------ After simplification ------------------------ { "intents": [ "Identify food and beverage consumption or declaration" ] } ---------------------------------------------------------------------- ==================================== Prompt ============================================= Convert this natural language query : """Ensuite j'ai bu une canette de Fanta.""" into an array of JSON. Ignore what it is not connected to nutrition, beverage or food. Provide a solution without explanation. Use the following ontology and only this 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...)."@en; rdfs:comment "Ignore food or beverage when it is not consumed in the past, now or in the future."@en; rdfs:comment "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."@en; rdfs:comment "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": "Fanta", "quantity": "une canette", "timeOfTheDay": "unknown", "brand": "Fanta", "type": "beverage", "event": "declaration" } ] ----------------------------------------------------------------------------- ----------------- Make it compliant ------------------ [ { "name": "Fanta", "quantity": "une canette", "timeOfTheDay": "unknown", "brand": "Fanta", "type": "beverage", "event": "declaration" } ] ------------------------------------------------------ ------------------------ After simplification ------------------------ [ { "name": "Fanta", "quantity": "une canette", "timeOfTheDay": "unknown", "brand": "Fanta", "type": "beverage", "event": "declaration" } ] ---------------------------------------------------------------------- --------------------------------- LLM result ----------------------------------- {'response': [{'name': 'Fanta', 'quantity': 'une canette', 'timeOfTheDay': 'unknown', 'brand': 'Fanta', 'type': 'beverage', 'event': 'declaration'}], 'cost': 0.10091999999999998} -------------------------------------------------------------------------------- ----------- result to be analyzed ----------- {'name': 'Fanta', 'quantity': 'une canette', 'timeOfTheDay': 'unknown', 'brand': 'Fanta', '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 '% fanta %' AND V_NormTrademark LIKE '%fanta%' Second 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 '% fanta %' AND V_NormAggr LIKE '% fanta %' ------------- Found solution (max 20) -------------- Fanta - fanta - - The Coca-Cola Company - 0 - 5000112659610 - 5000112659610 - OFF#2cd1c5dbccdccbd27f3c2968316989e8 Fanta - fanta - - The Coca-Cola Company - 0 - 5449000188526 - 5000112659610 - OFF#0fd97675ce300bfe48474ff5edcf7968 Fanta - fanta - - The Coca-Cola Company - 0 - 5449000000088 - 5000112659610 - OFF#e5a76692fd965e23be7ab28249ac41c3 Fanta - fanta - - The Coca-Cola Company - 0 - 90495090 - 5000112659610 - OFF#9a30c250f1976a057baa7a14c0304c3f Fanta Grape - fanta grape - - The Coca-Cola Company - 0 - 4902102038720 - 4902102038720 - OFF#2f4f5f22c41c4138d3a1fd74458da5c9 Fanta Mango - fanta mango - - The Coca-Cola Company - 0 - 90494055 - 90494055 - OFF#b8239cc11f4237762d538f0bf70d3dcd Fanta Orange - fanta orange - - The Coca-Cola Company - 0 - 2000000003786 - 2000000003786 - OFF#7ddea249c993fe80ec9ba14232c2fd35 Fanta Fraise - fanta fraise - - PepsiCo - 0 - 5449000065247 - 5449000065247 - OFF#c4692eb24b23290b2f87a43b92076501 Fanta Orange - fanta orange - - The Coca-Cola Company - 0 - 5000112548082 - 2000000003786 - OFF#2dd0d44102d85fb31ee7edd296904eb8 Fanta Orange - fanta orange - - The Coca-Cola Company - 0 - 5000112547849 - 2000000003786 - OFF#10a08787485f183bfb66ffae15c58e79 Fanta Orange - fanta orange - - The Coca-Cola Company - 0 - 5449000287038 - 2000000003786 - OFF#2b5a39ca98c59b05d89896bd41183f77 Fanta Exotique - fanta exotique - - The Coca-Cola Company - 0 - 3292090141320 - 3292090141320 - OFF#9216b13105fa23bc3f88b7e01ddc613e Fanta Strawberry Kiwi - fanta strawberry kiwi - - PepsiCo - 0 - 4260231223258 - 4260231223258 - OFF#7f367b7e1a0ff82c7c610841ae7f5153 Fanta Lemon Ohne Zuker - fanta lemon ohne zuker - - The Coca-Cola Company - 0 - 5449000665928 - 5449000665928 - OFF#0e3d3175cdad9ce2691bd3bc0d1ceebb Fanta Orange Zero Sugar - fanta orange zero sugar - - The Coca-Cola Company - 0 - 5449000664761 - 5449000664761 - OFF#fd0db9b2a55f45cde3c6c8b7dc7fba36 Fanta Saveur Pomme Cerise - fanta saveur pomme cerise - - The Coca-Cola Company - 0 - 5449000091178 - - OFF#c26a42592639dcc0977cca531669ec77 ---------------------------------------------------- --------------------------------- final result ----------------------------------- {'prompt': "Ensuite j'ai bu une canette de Fanta.", 'model': 'mistral-large-2411', 'imagePath': '', 'intents': ['Identify food and beverage consumption or declaration'], 'solutions': {'nutrition': [{'name': 'Fanta', 'normName': ' fanta ', 'comment': '', 'normComment': '', 'rank': 0, 'id': 'OFF#2cd1c5dbccdccbd27f3c2968316989e8', 'quantity': 'une canette', 'quantityLem': '1 canette', 'pack': ['VX1', 'BI4', 'VA2', 'VA3', 'GOB', 'C3B', 'C33', 'C15', 'SOD', 'VA4', 'VFF'], 'type': 'beverage', 'gtin': '5000112659610', 'gtinRef': '5000112659610', 'brand': 'The Coca-Cola Company', 'time': 'unknown', 'event': 'declaration', 'serving': 'C33-100', 'posiNormName': 0}], 'activity': [], 'response': {}}, 'cputime': 3.664919376373291} ---------------------------------------------------------------------------------- LLM CPU Time: 3.664919376373291