Input path: /home/debian/html/nutritwin/output_llm/66e570bd99bcb/input.json Output path: /home/debian/html/nutritwin/output_llm/66e570bd99bcb/output.json Input text: Ce matin j'ai bu une bière 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: Ce matin j'ai bu une bière ================================================================================================================================== ==================================== Prompt ============================================= Identify in this list of intents: ["Identify food consumption or declaration", "Identify the user physical activity", "Answer a nutrition question", "Other intent"], the intents of the prompt: ###Ce matin j'ai bu une bière###. Format the result in JSON format: {intents: []}. ========================================================================================= ------------------------------ LLM Raw response ----------------------------- ```json { "intents": ["Identify food consumption or declaration"] } ``` ----------------------------------------------------------------------------- ----------------- Make it compliant ------------------ ```json { "intents": ["Identify food consumption or declaration"] } ``` ------------------------------------------------------ ------------------------ After simplification ------------------------ { "intents": ["Identify food consumption or declaration"]} ---------------------------------------------------------------------- ==================================== Prompt ============================================= Convert this natural language query : """Ce matin j'ai bu une bière""" into an array in JSON of consumed foods and beverages. Provide a solution without explanation. Use only the 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 drink identifier, the name should not contain information related to quantity or container (like glass...). The cooking mode is not in the name. When the brand is very well-known (ex: Activia, Coca-Cola), the name is equal to the brand. Keep the same language"@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 examples in french: '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. Keep the same language"@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 'brand' is not specified and, the food or beverage is very well-known (like 'Coca-Cola'), provide the brand name in 'brand', otherwise set 'brand' to ''."@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. """ ========================================================================================= ------------------------------ LLM Raw response ----------------------------- ```json [ { "name": "bière", "quantity": "une", "type of food": "beverage", "time of the day": "breakfast", "event": "declaration", "brand": "", "company": "" } ] ``` ----------------------------------------------------------------------------- ----------------- Make it compliant ------------------ ```json [ { "name": "bière", "quantity": "une", "type of food": "beverage", "time of the day": "breakfast", "event": "declaration", "brand": "", "company": "" } ] ``` ------------------------------------------------------ ------------------------ After simplification ------------------------ [ { "name": "bière", "quantity": "une", "type of food": "beverage", "time of the day": "breakfast", "event": "declaration", "brand": "", "company": "" }] ---------------------------------------------------------------------- --------------------------------- LLM result ----------------------------------- {'response': [{'name': 'bière', 'quantity': 'une', 'type of food': 'beverage', 'time of the day': 'breakfast', 'event': 'declaration', 'brand': '', 'company': ''}], 'cost': 0.0} -------------------------------------------------------------------------------- ----------- result to be analyzed ----------- {'name': 'bière', 'quantity': 'une', 'type of food': 'beverage', 'time of the day': 'breakfast', 'event': 'declaration', 'brand': '', 'company': ''} 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 '% biere %' AND (V_NormTrademark = '' OR V_NormTrademark IS NULL) ------------- Found solution (max 20) -------------- Bière - biere - - - 18991 - - - KCA#1d11a6915401dd88b3b740d39895862f Bière Allégée - biere allegee - - - 84 - - - KCA#84ee3801c88bbf7fe2a329f87a93cdcb Bière Blanche - biere blanche - - - 0 - - - CIQ#475caf56ce3ea751a299f73d5a818568 Bière d'Abbaye - biere abbaye - - - 2685 - - - KCA#9f3d1b16ed38f0776c6e2cb9ef7670d3 Bière sans Alcool - biere san alcool - - - 655 - - - KCA#f2b5c22bd8388d037dd6b6f5ae405f98 Bière sans Alcool - biere san alcool - <1,2° alcool - - 0 - - - CIQ#6ee02940a6e8d8882ca6f1a6a35c7c83 Bière Demi Brasserie - biere demi brasserie - - - 353 - - - KCA#b8d7d5e4cc1dcaa8ed2669a4ed59a3ee Bière 'Spéciale' 5-6° - biere speciale 6° - - - 1945 - - - KCA#0a60e3e86f21ca783cf5636a326ebc2e Bière de Spécialité ou Régionale - biere de specialite ou regionale - - - 190 - - - KCA#11b841bfd82a052d34e6c643f8bec396 Coq à la Bière - coq biere - - - 7 - - - KCA#ac6d432d8f6440ff37168d57a364091f Soupe à la Bière - soupe biere - la bière - - 0 - - - KCA#5d823e0c912390b7753ac7c6af959cf0 Levure de Bière - levure de biere - - - 533 - - - KCA#4913b875dd74e41a0a8a074476b69811 ---------------------------------------------------- --------------------------------- final result ----------------------------------- {'prompt': "Ce matin j'ai bu une bière", 'intents': ['Identify food consumption or declaration'], 'model': 'gpt-4o-2024-05-13', 'solutions': {'nutrition': [{'name': 'Bière', 'normName': ' biere ', 'comment': '', 'normComment': '', 'rank': 18991, 'id': 'KCA#1d11a6915401dd88b3b740d39895862f', 'quantity': 'une', 'quantityLem': '1', 'pack': ['BIE', 'C3B', 'C33', 'C50', 'BI4'], 'type': '', 'gtin': '', 'gtinRef': '', 'brand': '', 'time': '', 'event': 'declaration', 'serving': 'BIE-100', 'posiNormName': 0}], 'activity': [], 'response': {}}, 'cputime': 2.0462889671325684} ---------------------------------------------------------------------------------- LLM CPU Time: 2.0462889671325684