Input path: /home/debian/html/nutritwin/output_llm/6711497bb5c3f/input.json Output path: /home/debian/html/nutritwin/output_llm/6711497bb5c3f/output.json Input text: Omelette. 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: Omelette. ================================================================================================================================== ==================================== 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: ###Omelette.###. 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 : """Omelette.""" 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 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. 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."@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. """ ========================================================================================= ------------------------------ LLM Raw response ----------------------------- ```json [ { "name": "Omelette", "type": "food", "event": "unknown" } ] ``` ----------------------------------------------------------------------------- ----------------- Make it compliant ------------------ ```json [ { "name": "Omelette", "type": "food", "event": "unknown" } ] ``` ------------------------------------------------------ ------------------------ After simplification ------------------------ [ { "name": "Omelette", "type": "food", "event": "unknown" }] ---------------------------------------------------------------------- --------------------------------- LLM result ----------------------------------- {'response': [{'name': 'Omelette', 'type': 'food', 'event': 'unknown'}], 'cost': 0.0} -------------------------------------------------------------------------------- ----------- result to be analyzed ----------- {'name': 'Omelette', 'type': 'food', '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 '% omelette %' AND (V_NormTrademark = '' OR V_NormTrademark IS NULL) ------------- Found solution (max 20) -------------- Omelette - omelette - garnitures diverses : légumes, fromages, viandes..., aliment moyen - - 0 - - - CIQ#f3bd368d94304e5151916a143f87c6c4 Omelette Nature - omelette nature - - - 4230 - - - KCA#caac3b8e77b9ec6239db2083c58c2077 Omelette au Thon - omelette thon - - - 52 - - - KCA#5f614bbae59b451ec691804fbd8c3b1d Omelette de Noël - omelette de noel - - - 28 - - - KCA#be4736d0e3ee43da3c659fd7769f3937 Omelette Espagnole - omelette espagnole - - - 611 - - - KCA#a967378e35edbd8d9a305ed995aa8105 Omelette Provençale - omelette provencale - - - 202 - - - KCA#a53a460a1303ada5f7245061d09547ec Omelette aux Moules - omelette au moule - - - 43 - - - KCA#61a7e944219e17a767e04f150f45251c Omelette à la Crème - omelette creme - - - 24 - - - KCA#92fa16c69f2bed36707181cb4c6da5fe Omelette au Fromage - omelette fromage - - - 0 - - - CIQ#32e747be3e0d2f2e8e88993ebc228dcd Omelette au Fromage - omelette fromage - - - 0 - - - KCA#32e747be3e0d2f2e8e88993ebc228dcd Omelettes au Fromage - omelette fromage - - - 1282 - - - KCA#32e747be3e0d2f2e8e88993ebc228dcd Omelette aux Lardons - omelette au lardon - - - 607 - - - CIQ#91e89f2662faf022d17d0a50fd266c22 Omelette Norvégienne - omelette norvegienne - - - 79 - - - KCA#5176fcbde2e1320b6e7bc64033053d4b Omelette aux Poivrons - omelette au poivron - - - 235 - - - KCA#4cb2797259acdf22918e496fa31d18e5 Omelette aux Abricots - omelette au abricot - - - 3 - - - KCA#4db67e4e3160314b2d73d4e66510cff1 Omelette Saint-pierre - omelette saint pierre - - - 2 - - - KCA#54bc3809ce3573f3759129975c5bdfd2 Omelette aux Courgettes - omelette au courgette - - - 125 - - - KCA#4b746e9c0feef9bca3c7252301d6c95d Omelette Sucrée Flambée - omelette sucree flambee - - - 4 - - - KCA#de9e04425035a8bdc1dc170c38ada3d6 Omelette aux Champignons - omelette au champignon - - - 763 - - - KCA#c39e92cc07d98c316d4b95491b7a8a31 Omelette à la Choucroute - omelette choucroute - - - 1 - - - KCA#7cab890452cffe55546fa515aa73d6f1 ---------------------------------------------------- ERROR: Wrong quantity: '' ERROR: no solution for picto in the first solution --------------------------------- final result ----------------------------------- {'prompt': 'Omelette.', 'intents': ['Identify food consumption or declaration'], 'model': 'gpt-4o-2024-05-13', 'solutions': {'nutrition': [{'name': 'Omelette', 'normName': ' omelette ', 'comment': 'garnitures diverses : légumes, fromages, viandes..., aliment moyen', 'normComment': ' garniture diverse legume fromage viandes... aliment moyen ', 'rank': 0, 'id': 'CIQ#f3bd368d94304e5151916a143f87c6c4', 'quantity': '', 'quantityLem': '', 'pack': ['OE2.w60'], 'type': 'food', 'gtin': '', 'gtinRef': '', 'brand': '', 'time': '', 'event': 'unknown', 'serving': '', 'posiNormName': 0}], 'activity': [], 'response': {}}, 'cputime': 1.7859454154968262} ---------------------------------------------------------------------------------- LLM CPU Time: 1.7859454154968262