Input path: /home/debian/html/nutritwin/output_llm/681500525573a/input.json Output path: /home/debian/html/nutritwin/output_llm/681500525573a/output.json Input text: J'ai pris une banane que j'ai mixé avec 200 ml de lait. 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: J'ai pris une banane que j'ai mixé avec 200 ml de lait. ================================================================================================================================== ==================================== 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: ###J'ai pris une banane que j'ai mixé avec 200 ml de lait.###. 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 : """J'ai pris une banane que j'ai mixé avec 200 ml de lait.""" 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...). 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": "banane", "quantity": "une", "cookingMethod": "mixé", "type": "food", "event": "declaration" }, { "name": "lait", "quantity": "200 ml", "type": "beverage", "event": "declaration" } ] ----------------------------------------------------------------------------- ----------------- Make it compliant ------------------ [ { "name": "banane", "quantity": "une", "cookingMethod": "mixé", "type": "food", "event": "declaration" }, { "name": "lait", "quantity": "200 ml", "type": "beverage", "event": "declaration" } ] ------------------------------------------------------ ------------------------ After simplification ------------------------ [ { "name": "banane", "quantity": "une", "cookingMethod": "mix\u00e9", "type": "food", "event": "declaration" }, { "name": "lait", "quantity": "200 ml", "type": "beverage", "event": "declaration" } ] ---------------------------------------------------------------------- --------------------------------- LLM result ----------------------------------- {'response': [{'name': 'banane', 'quantity': 'une', 'cookingMethod': 'mixé', 'type': 'food', 'event': 'declaration'}, {'name': 'lait', 'quantity': '200 ml', 'type': 'beverage', 'event': 'declaration'}], 'cost': 0.1038} -------------------------------------------------------------------------------- ----------- result to be analyzed ----------- {'name': 'banane', 'quantity': 'une', 'cookingMethod': 'mixé', '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 '% banane %' AND (V_NormTrademark = '' OR V_NormTrademark IS NULL) ------------- Found solution (max 20) -------------- Banane - banane - pulpe, crue - - 57967 - - - CIQ#6066b5bb884711efc0e44c9446b96aa3 Banane Sèche - banane seche - - - 346 - - - KCA#2e3e40d3b1ae9f793251e9948142d784 Bananes en Robe - banane en robe - - - 14 - - - KCA#b274666ef64f762c58695191d4286b85 Banane Plantain - banane plantain - - - 2 - - - CIQ#1055a76a23712202f3c842fba09fa691 Bananes Barbecue - banane barbecue - - - 33 - - - KCA#1d31fb8efe54f0bc7765a60cc9f8c324 Bananes au Jambon - banane jambon - - - 4 - - - KCA#e21d980b838ba89f4e9ba1d85f593c95 Smoothie Banane et Lait de Soja - smoothie banane lait de soja - de soja - - 0 - - - KCA#dc0b16a02e5290892f9adee7419ec0e7 Crème Glacée Banane, Pomme et Noix de Macadamia - creme glacee banane pomme noix de macadamia - - - 34 - - - KCA#3233d39965b7baa31d10a301ac541ffa Bruschette à la Fraise, à la Banane et à la Ricotta - bruschette fraise banane ricotta - - - 2 - - - KCA#fd9db147f698ab1c84b0905704258a5f ---------------------------------------------------- ----------- result to be analyzed ----------- {'name': 'lait', 'quantity': '200 ml', '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 '% lait %' AND (V_NormTrademark = '' OR V_NormTrademark IS NULL) ------------- Found solution (max 20) -------------- Lait - lait - teneur en matière grasse inconnue, UHT, aliment moyen - - 0 - - - CIQ#ebdfafe0fce6b513193ae9c0855b4094 Lait à 1 - lait - 2% de matière grasse, UHT, enrichi en plusieurs vitamines - - 0 - - - CIQ#825f8bcb068ecde315938147ed819623 Lait Entier - lait entier - - - 1435 - - - KCA#c131edf4d3c1e17da0b0a54b5ed8bbb6 Lait Écrémé - lait ecreme - UHT - - 9353 - - - CIQ#27de8d007093ae392f4b782851e7fd9c Lait Entier - lait entier - UHT - - 0 - - - CIQ#5118aac9b89cceae9a62423175de70eb Lait Écrémé - lait ecreme - pasteurisé - - 0 - - - CIQ#1622e54576ffea9bca81697cacb48d94 Lait Entier - lait entier - pasteurisé - - 0 - - - CIQ#d5881852b522b09ee02aa0fe46885b00 Lait de Soja - lait de soja - - - 3001 - - - KCA#7484ab8a01f886bca7607cf06a579a2c Lait d'Avoine - lait avoine - - - 837 - - - KCA#54605e0becbb04ace3db6bf78748c15f Lait de Poule - lait de poule - sans alcool - - 0 - - - CIQ#f6756ecdc46ec65e5972c6aaf481f4a2 Lait en Poudre - lait en poudre - écrémé - - 117 - - - CIQ#1d9ba583216533c41321ffd9ea51b327 Lait en Poudre - lait en poudre - entier - - 25 - - - CIQ#be7d16f0a05422e5eb1d5ff077dee20c Lait de Brebis - lait de brebi - entier - - 0 - - - CIQ#b54f3b8a48f8d3e0ba7a0228c8adca4f Lait de Jument - lait de jument - entier - - 0 - - - CIQ#05ea74b811b1a15ad91876c22391f13a Lait en Poudre - lait en poudre - demi-écrémé - - 0 - - - CIQ#ee03115de1c18f635dbb62d80d6f9715 Lait de Chèvre - lait de chevre - entier, cru - - 0 - - - CIQ#8fb6afe4302a0073de91d274e3722c3e Lait de Chèvre - lait de chevre - entier, UHT - - 0 - - - CIQ#9d462cfc80afac9cf259f0f2f305db74 Lait de Chèvre - lait de chevre - demi-écrémé, UHT - - 0 - - - CIQ#a497c21ecfbd7c2930cb99326897a779 Lait 1/2 Écrémé - lait 1/2 ecreme - - - 23220 - - - KCA#d5b12fbedab6d0f0a741feeaa8e92b35 Lait Entier UHT - lait entier uht - - - 25 - - - KCA#aeb66cc691b5e08f15b01dc094a51d18 ---------------------------------------------------- --------------------------------- final result ----------------------------------- {'prompt': "J'ai pris une banane que j'ai mixé avec 200 ml de lait.", 'model': 'mistral-large-2411', 'imagePath': '', 'intents': ['Identify food and beverage consumption or declaration'], 'solutions': {'nutrition': [{'name': 'Banane', 'normName': ' banane ', 'comment': 'pulpe, crue', 'normComment': ' pulpe crue ', 'rank': 57967, 'id': 'CIQ#6066b5bb884711efc0e44c9446b96aa3', 'quantity': 'une', 'quantityLem': '1', 'pack': ['BAN.w100'], 'type': 'food', 'gtin': '', 'gtinRef': '', 'brand': '', 'time': '', 'event': 'declaration', 'serving': 'BAN-100', 'posiNormName': 0}, {'name': 'Lait', 'normName': ' lait ', 'comment': 'teneur en matière grasse inconnue, UHT, aliment moyen', 'normComment': ' teneur en matiere grasse inconnue uht aliment moyen ', 'rank': 0, 'id': 'CIQ#ebdfafe0fce6b513193ae9c0855b4094', 'quantity': '200 ml', 'quantityLem': '200 ml', 'pack': ['VX1', 'VA2', 'VA3', 'BI4', 'VA4'], 'type': 'beverage', 'gtin': '', 'gtinRef': '', 'brand': '', 'time': '', 'event': 'declaration', 'serving': 'VX1-2ml', 'posiNormName': 0}], 'activity': [], 'response': {}}, 'cputime': 2.2007594108581543} ---------------------------------------------------------------------------------- LLM CPU Time: 2.2007594108581543