Input path: /home/debian/html/nutritwin/output_llm/66dee005407e5/input.json Output path: /home/debian/html/nutritwin/output_llm/66dee005407e5/output.json Input text: À midi j'ai mangé quatre cuillères d'huile d'olive 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: À midi j'ai mangé quatre cuillères d'huile d'olive ================================================================================================================================== ==================================== 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: ###À midi j'ai mangé quatre cuillères d'huile d'olive###. 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 : """À midi j'ai mangé quatre cuillères d'huile d'olive""" 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": "huile d'olive", "quantity": "quatre cuillères", "time of the day": "lunch", "event": "declaration" } ] ``` ----------------------------------------------------------------------------- ----------------- Make it compliant ------------------ ```json [ { "name": "huile d'olive", "quantity": "quatre cuillères", "time of the day": "lunch", "event": "declaration" } ] ``` ------------------------------------------------------ ------------------------ After simplification ------------------------ [ { "name": "huile d'olive", "quantity": "quatre cuillères", "time of the day": "lunch", "event": "declaration" }] ---------------------------------------------------------------------- --------------------------------- LLM result ----------------------------------- {'response': [{'name': "huile d'olive", 'quantity': 'quatre cuillères', 'time of the day': 'lunch', 'event': 'declaration'}], 'cost': 0.0} -------------------------------------------------------------------------------- ----------- result to be analyzed ----------- {'name': "huile d'olive", 'quantity': 'quatre cuillères', 'time of the day': 'lunch', '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 '% huile olive %' AND (V_NormTrademark = '' OR V_NormTrademark IS NULL) ------------- Found solution (max 20) -------------- Huile d'Olive - huile olive - - - 31593 - - - KCA#e3401b8ad72802d4269691213bebe06d Huile d'Olive Vierge Extra - huile olive vierge extra - - - 0 - - - CIQ#0dd5134f977ccd585a472259c8513ae6 Thon à l'Huile d'Olive - thon huile olive - l'huile d'olive - - 0 - - - KCA#d33c1882fa02cd9006589b140511fb8b ---------------------------------------------------- --------------------------------- final result ----------------------------------- {'prompt': "À midi j'ai mangé quatre cuillères d'huile d'olive", 'intents': ['Identify food consumption or declaration'], 'model': 'gpt-4o-2024-05-13', 'solutions': {'nutrition': [{'name': "Huile d'Olive", 'normName': ' huile olive ', 'comment': '', 'normComment': '', 'rank': 31593, 'id': 'KCA#e3401b8ad72802d4269691213bebe06d', 'quantity': 'quatre cuillères', 'quantityLem': '4 cuillere', 'pack': ['CSL', 'CCL'], 'type': '', 'gtin': '', 'gtinRef': '', 'brand': '', 'time': '', 'event': 'declaration', 'serving': 'CCL-400', 'posiNormName': 0}], 'activity': [], 'response': {}}, 'cputime': 1.7272911071777344} ---------------------------------------------------------------------------------- LLM CPU Time: 1.7272911071777344