Input path: /home/debian/html/nutritwin/output_llm/6712b1deacae8/input.json Output path: /home/debian/html/nutritwin/output_llm/6712b1deacae8/output.json Input text: Soupe. 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: Soupe. ================================================================================================================================== ==================================== 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: ###Soupe.###. 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 : """Soupe.""" 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": "Soupe", "type": "food", "event": "declaration" } ] ``` ----------------------------------------------------------------------------- ----------------- Make it compliant ------------------ ```json [ { "name": "Soupe", "type": "food", "event": "declaration" } ] ``` ------------------------------------------------------ ------------------------ After simplification ------------------------ [ { "name": "Soupe", "type": "food", "event": "declaration" }] ---------------------------------------------------------------------- --------------------------------- LLM result ----------------------------------- {'response': [{'name': 'Soupe', 'type': 'food', 'event': 'declaration'}], 'cost': 0.0} -------------------------------------------------------------------------------- ----------- result to be analyzed ----------- {'name': 'Soupe', '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 '% soupe %' AND (V_NormTrademark = '' OR V_NormTrademark IS NULL) ------------- Found solution (max 20) -------------- Soupe - soupe - - - 13 - - - CIQ#d38558470062ac5e3bcfe5f6ae1b1877 Soupe Miso - soupe miso - déshydratée reconstituée - - 0 - - - CIQ#2864246d65444d2b8a7a213e08a1941f Soupe au Pain - soupe pain - au pain - - 0 - - - KCA#198b9e8411c619859bf84e5b437f1332 Soupe à l'Ail - soupe ail - à l'ail - - 0 - - - KCA#c2752c55ad4098d77298722e98556eee Soupe au Choux - soupe chou - au choux - - 0 - - - KCA#ee07fe588be75e8402283dda604ca5b9 Soupe au Pistou - soupe pistou - - - 164 - - - CIQ#3b039f5168b1e012dc7014d41b27e748 Soupe au Cantal - soupe cantal - au cantal - - 0 - - - KCA#97c80ba38a0d393aa16941feefc06699 Soupe Asiatique - soupe asiatique - avec pâtes - - 0 - - - CIQ#3806f198e18b33f8b28e7f20df30cac8 Soupe Pékinoise - soupe pekinoise - soupe pékinoise - - 0 - - - KCA#c098a7deb4c974077b34ed3bfaf9b1a1 Soupe au Pistou - soupe pistou - déshydratée reconstituée - - 0 - - - CIQ#50825ca4c4736b6d52c653d53f4d157a Soupe Marocaine - soupe marocaine - déshydratée reconstituée - - 0 - - - CIQ#c1031e4175e40d52afa20c8d2577b1ef Soupe Asiatique - soupe asiatique - avec pâtes, déshydratée reconstituée - - 0 - - - CIQ#a40183d749005d95ac204f5d631d2529 Soupe à l'Oignon - soupe oignon - - - 403 - - - CIQ#b1ff7640f95dd2cde33e15b9cda8687a Soupe au Cresson - soupe cresson - - - 354 - - - CIQ#5622adddc0a602676f23aa772b5f9138 Soupe Minestrone - soupe minestrone - - - 353 - - - CIQ#d6a95d8bda925efc36695e9b831c08b2 Soupe au Potiron - soupe potiron - - - 145 - - - CIQ#6f75550105dd45c4009ada47f18dd0cd Soupe à la Bière - soupe biere - la bière - - 0 - - - KCA#5d823e0c912390b7753ac7c6af959cf0 Soupe de Légumes - soupe de legume - de légumes - - 0 - - - KCA#ffb1f50ec43d9ad3f79c5e0b99990d09 Soupe aux Moules - soupe au moule - aux moules - - 0 - - - KCA#3fe2a6465efacd53cf3f591a07aa0b3f Soupe à l'Oignon - soupe oignon - déshydratée reconstituée - - 0 - - - CIQ#8185849a63717db6199dc328db03c3ea ---------------------------------------------------- ERROR: Wrong quantity: '' ERROR: no solution for picto in the first solution --------------------------------- final result ----------------------------------- {'prompt': 'Soupe.', 'intents': ['Identify food consumption or declaration'], 'model': 'gpt-4o-2024-05-13', 'solutions': {'nutrition': [{'name': 'Soupe', 'normName': ' soupe ', 'comment': '', 'normComment': '', 'rank': 13, 'id': 'CIQ#d38558470062ac5e3bcfe5f6ae1b1877', 'quantity': '', 'quantityLem': '', 'pack': ['ACR', 'BOL'], 'type': 'food', 'gtin': '', 'gtinRef': '', 'brand': '', 'time': '', 'event': 'declaration', 'serving': '', 'posiNormName': 0}], 'activity': [], 'response': {}}, 'cputime': 1.5137286186218262} ---------------------------------------------------------------------------------- LLM CPU Time: 1.5137286186218262