Input path: /home/debian/html/nutritwin/output_llm/672f641e9343c/input.json Output path: /home/debian/html/nutritwin/output_llm/672f641e9343c/output.json Input text: J'ai bu un verre d'eau. 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: J'ai bu un verre d'eau. ================================================================================================================================== ==================================== 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: ###J'ai bu un verre d'eau.###. 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 : """J'ai bu un verre d'eau.""" 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": "eau", "quantity": "un verre", "type of food": "beverage", "event": "declaration" } ] ``` ----------------------------------------------------------------------------- ----------------- Make it compliant ------------------ ```json [ { "name": "eau", "quantity": "un verre", "type of food": "beverage", "event": "declaration" } ] ``` ------------------------------------------------------ ------------------------ After simplification ------------------------ [ { "name": "eau", "quantity": "un verre", "type of food": "beverage", "event": "declaration" }] ---------------------------------------------------------------------- --------------------------------- LLM result ----------------------------------- {'response': [{'name': 'eau', 'quantity': 'un verre', 'type of food': 'beverage', 'event': 'declaration'}], 'cost': 0.0} -------------------------------------------------------------------------------- ----------- result to be analyzed ----------- {'name': 'eau', 'quantity': 'un verre', 'type of food': 'beverage', '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 '% eau %' AND (V_NormTrademark = '' OR V_NormTrademark IS NULL) ------------- Found solution (max 20) -------------- Eau - eau - - - 10064 - - - KCA#08cfe774cbf7476b1e582734c7082ecd Eau de Vie - eau de vie - - - 210 - - - CIQ#2397ddba68eefec7e38e3a061b6060e3 Eau de Coco - eau de coco - - - 574 - - - CIQ#4f6cfd4687e4da85c9063e194dd3113b Eau Minérale - eau minerale - - - 0 - - - CIQ#682a311be3fc15a20a88c168408e5304 Eau Minérale - eau minerale - aliment moyen - - 160 - - - KCA#69addfd353e07f633ee05c6be8ac5d4d Eau Minérale - eau minerale - plate, aliment moyen - - 18 - - - CIQ#9f35a4198a700eac62fe4d1dc426f1a4 Eau Minérale - eau minerale - gazeuse, aliment moyen - - 28 - - - CIQ#38da155cfd970d21ba9f4b87294b96df Eau Minérale - eau minerale - ou de source aromatisée agrumes - - 33 - - - KCA#47ee70f086c3080428426febc2426e8c Eau Minérale - eau minerale - ou de source aromatisée, arôme autre qu'agrumes - - 36 - - - KCA#0daeef02b69e5526427bc855f1ec3111 Eau Minérale - eau minerale - embouteillée, faiblement minéralisée, aliment moyen - - 0 - - - CIQ#a8b887f21f002cd8ddbda99766ee5ec4 Eau de Source - eau de source - embouteillée, aliment moyen - - 0 - - - CIQ#b6c1ba3e6cb4c788d63711a9b869730b Eau du Robinet - eau robinet - - - 273 - - - CIQ#4c4a29ce4ec63b6cfc6bc3914ccf7056 Eau Minérale Dax - eau minerale da - embouteillée, non gazeuse, moyennement minéralisée, Dax, 40 - - 0 - - - CIQ#a07a880ef627fa44150fe5583484549d Eau de Vie de Vin - eau de vie de vin - type armagnac, cognac - - 0 - - - CIQ#c0440021ea15aa2abf11853bbd2191a4 Eau Minérale Néro - eau minerale nero - embouteillée, non gazeuse, faiblement minéralisée, Grèce - - 0 - - - CIQ#8ab34da104cb5b744e0ad6eaece161a6 Eau Minérale Avra - eau minerale avra - embouteillée, non gazeuse, faiblement minéralisée, Grèce - - 0 - - - CIQ#b0465b7ee2f045df840aac281b388253 Eau Minérale Luso - eau minerale luso - embouteillée, non gazeuse, très faiblement minéralisée, Portugal - - 0 - - - CIQ#45d467ce96aa14e71c62e6ca943f5621 Eau Minérale Eden - eau minerale eden - La Goa, embouteillée, non gazeuse, faiblement minéralisée, Suisse - - 0 - - - CIQ#341195c07e8f951269157ecad800778a Eau Minérale Ogeu - eau minerale ogeu - embouteillée, gazeuse, faiblement minéralisée, Ogeu-les-Bains, 64 - - 0 - - - CIQ#14fc742b6db6af7dce1a08288d62ddf6 Eau Minérale Vals - eau minerale val - embouteillée, gazeuse, moyennement minéralisée, Vals-les-Bains, 07 - - 0 - - - CIQ#11be70594fa1e46c35dca065d17b5ca6 ---------------------------------------------------- --------------------------------- final result ----------------------------------- {'prompt': "J'ai bu un verre d'eau.", 'intents': ['Identify food consumption or declaration'], 'model': 'gpt-4o-2024-05-13', 'solutions': {'nutrition': [{'name': 'Eau', 'normName': ' eau ', 'comment': '', 'normComment': '', 'rank': 10064, 'id': 'KCA#08cfe774cbf7476b1e582734c7082ecd', 'quantity': 'un verre', 'quantityLem': '1 verre', 'pack': ['VAE', 'VX1', 'VA2', 'GOB', 'VA4', 'VA4', 'VA3'], 'type': '', 'gtin': '', 'gtinRef': '', 'brand': '', 'time': '', 'event': 'declaration', 'serving': 'VA2-100', 'posiNormName': 0}], 'activity': [], 'response': {}}, 'cputime': 1.1770546436309814} ---------------------------------------------------------------------------------- LLM CPU Time: 1.1770546436309814