Input path: /home/debian/html/nutritwin/output_llm/67f388f3cc7c0/input.json Output path: /home/debian/html/nutritwin/output_llm/67f388f3cc7c0/output.json Input text: 30 g de lait entier. 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: 30 g de lait entier. ================================================================================================================================== ==================================== 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: ###30 g de lait entier.###. 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 : """30 g de lait entier.""" 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": "lait entier", "quantity": "30 g", "type": "beverage", "event": "unknown" } ] ----------------------------------------------------------------------------- ----------------- Make it compliant ------------------ [ { "name": "lait entier", "quantity": "30 g", "type": "beverage", "event": "unknown" } ] ------------------------------------------------------ ------------------------ After simplification ------------------------ [ { "name": "lait entier", "quantity": "30 g", "type": "beverage", "event": "unknown" } ] ---------------------------------------------------------------------- --------------------------------- LLM result ----------------------------------- {'response': [{'name': 'lait entier', 'quantity': '30 g', 'type': 'beverage', 'event': 'unknown'}], 'cost': 0.09665999999999998} -------------------------------------------------------------------------------- ----------- result to be analyzed ----------- {'name': 'lait entier', 'quantity': '30 g', 'type': 'beverage', 'event': 'unknown'} 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 entier %' AND (V_NormTrademark = '' OR V_NormTrademark IS NULL) ------------- Found solution (max 20) -------------- Lait Entier - lait entier - - - 1435 - - - KCA#c131edf4d3c1e17da0b0a54b5ed8bbb6 Lait Entier - lait entier - UHT - - 0 - - - CIQ#5118aac9b89cceae9a62423175de70eb Lait Entier - lait entier - pasteurisé - - 0 - - - CIQ#d5881852b522b09ee02aa0fe46885b00 Lait Entier UHT - lait entier uht - - - 25 - - - KCA#aeb66cc691b5e08f15b01dc094a51d18 Lait Entier Pasteurisé - lait entier pasteurise - - - 9 - - - KCA#3ae08328cd2d5f27e8f652737e424a19 Cacao au Lait Entier - cacao lait entier - - - 167 - - - KCA#f59c7a79772ae1a87bb8fd647a75aee5 Yaourt au Lait Entier - yaourt lait entier - Nature - - 272 - - - KCA#7e651ad1833df2fb24556f1fb98021da Yaourt au Lait Entier - yaourt lait entier - aux Fruits - - 389 - - - KCA#dea4ac08b7324d4bd6ec9b355441b7a4 Yaourt au Lait Entier - yaourt lait entier - Nature sucré - - 79 - - - KCA#e2ff32d81ac0932c4a4d3935b64956f4 Yaourt au Lait Entier - yaourt lait entier - Nature brassé - - 330 - - - KCA#46396d736399830a05696fa462680363 Yaourt au Lait Entier - yaourt lait entier - aromatisé sucré - - 216 - - - KCA#eacacf24ac5b19ee8206fdbf4249e0a4 Yaourt au Lait Entier - yaourt lait entier - au Bifidus, nature - - 267 - - - KCA#0e99d85351419e8f2bb476020feeb725 Yaourt au Lait Entier - yaourt lait entier - aux Céréales ou Muesli - - 95 - - - KCA#e8c294ab7c316b480ff4491e6e27f608 Yaourt au Lait Entier - yaourt lait entier - au Bifidus, aromatisé, sucré - - 18 - - - KCA#1125f7a327e4abe66380b34041ee81c7 Yaourt au Lait Entier - yaourt lait entier - au Bifidus et aux Fruits, sucré - - 7 - - - KCA#807afcb638dc1322d1abe2d2f7594d0e Yaourt au Lait Entier - yaourt lait entier - enrichi en Crème, aromatisée, sucré - - 30 - - - KCA#c03d06f57b69627ee0102312e827bedc Yaourt au Lait Entier - yaourt lait entier - enrichi en Crème, aux pépites de Chocolat - - 23 - - - KCA#5fcbbb12e138000fb2b2cae2c272ad75 ---------------------------------------------------- ERROR: no solution for picto in the first solution ERROR: no solution for picto in the first solution ERROR: no solution for picto in the first solution --------------------------------- final result ----------------------------------- {'prompt': '30 g de lait entier.', 'model': 'mistral-large-2411', 'imagePath': '', 'intents': ['Identify food and beverage consumption or declaration'], 'solutions': {'nutrition': [{'name': 'Lait Entier', 'normName': ' lait entier ', 'comment': '', 'normComment': '', 'rank': 1435, 'id': 'KCA#c131edf4d3c1e17da0b0a54b5ed8bbb6', 'quantity': '30 g', 'quantityLem': '30 g', 'pack': ['VA4', 'VA3', 'VA2', 'VX1', 'GOB', 'BOL', 'BOB', 'MUG'], 'type': 'beverage', 'gtin': '', 'gtinRef': '', 'brand': '', 'time': '', 'event': 'unknown', 'serving': '', 'posiNormName': 0}], 'activity': [], 'response': {}}, 'cputime': 2.0131986141204834} ---------------------------------------------------------------------------------- LLM CPU Time: 2.0131986141204834