Input path: /home/debian/html/nutritwin/output_llm/67b466a306442/input.json Output path: /home/debian/html/nutritwin/output_llm/67b466a306442/output.json Input text: J'ai bu la moitié d'un grand verre de lait demi écrémé. 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 la moitié d'un grand verre de lait demi écrémé. ================================================================================================================================== ==================================== Prompt ============================================= Identify in this list of intents: ["Identify food and beverage consumption or declaration", "Identify the user physical activity", "Answer a nutrition question", "Other intent"], the intents of the prompt: ###J'ai bu la moitié d'un grand verre de lait demi écrémé.###. Format the result in JSON format: {"intents": []}. ========================================================================================= ------------------------------ LLM Raw response ----------------------------- {"intents": ["Identify food and beverage consumption or declaration"]} ----------------------------------------------------------------------------- ----------------- Make it compliant ------------------ {"intents": ["Identify food and beverage consumption or declaration"]} ------------------------------------------------------ ERROR: wrong object representation: {'intents': ['Identify food and beverage consumption or declaration']} ------------------------ After simplification ------------------------ { "intents": [ "Identify food and beverage consumption or declaration" ] } ---------------------------------------------------------------------- ==================================== Prompt ============================================= Convert this natural language query : """J'ai bu la moitié d'un grand verre de lait demi écrémé.""" into an array of JSON. Ignore what it is not connected to nutrition, beverage or food. Provide a solution without explanation. Use the following ontology and only this 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...). Ignore food or beverage when it is not consumed in the past, now or in the future. The cooking mode is not in the name. The name is only in french."""@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 is only in french. Here are examples: '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. The cooking method is in french."@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 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. 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. """ Here is an example of result: [ { "name": "blanquette de veau", "quantity": "un plat", "cookingMethod": "mijot\u00e9", "timeOfTheDay": "lunch", "company": "Leclerc", "type": "food", "event": "declaration" }, { "name": "eau", "brand": "Evian", "company": "Danone", "timeOfTheDay": "breakfast", "quantity": "un verre", "type": "beverage", "event": "intent" } ] ========================================================================================= ------------------------------ LLM Raw response ----------------------------- [ { "name": "lait demi écrémé", "quantity": "la moitié d'un grand verre", "timeOfTheDay": "unknown", "type": "beverage", "event": "declaration" } ] ----------------------------------------------------------------------------- ----------------- Make it compliant ------------------ [ { "name": "lait demi écrémé", "quantity": "la moitié d'un grand verre", "timeOfTheDay": "unknown", "type": "beverage", "event": "declaration" } ] ------------------------------------------------------ ------------------------ After simplification ------------------------ [ { "name": "lait demi \u00e9cr\u00e9m\u00e9", "quantity": "la moiti\u00e9 d'un grand verre", "timeOfTheDay": "unknown", "type": "beverage", "event": "declaration" } ] ---------------------------------------------------------------------- --------------------------------- LLM result ----------------------------------- {'response': [{'name': 'lait demi écrémé', 'quantity': "la moitié d'un grand verre", 'timeOfTheDay': 'unknown', 'type': 'beverage', 'event': 'declaration'}], 'cost': 0.1002} -------------------------------------------------------------------------------- ----------- result to be analyzed ----------- {'name': 'lait demi écrémé', 'quantity': "la moitié d'un grand verre", 'timeOfTheDay': 'unknown', 'type': '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 '% lait demi ecreme %' AND (V_NormTrademark = '' OR V_NormTrademark IS NULL) ------------- Found solution (max 20) -------------- Lait Demi-écrémé - lait demi ecreme - UHT - - 1882 - - - CIQ#a52f3d296711c40b0cf1a9e387dd93c3 Lait Demi-écrémé - lait demi ecreme - pasteurisé - - 0 - - - CIQ#ba021562100b158345cde3da8ea5941f Lait Demi-écrémé - lait demi ecreme - UHT, enrichi en vitamine D seulement - - 0 - - - CIQ#386868d6d030c7295418701a8d2582af Lait Demi-écrémé - lait demi ecreme - ou à teneur en matière grasse légèrement inférieure, à teneur réduite en lactose - - 0 - - - CIQ#bcb97383db7bbbc0b61664db635f7d92 Lait Demi-écrémé UHT - lait demi ecreme uht - - - 0 - - - KCA#a4ffea6cb369217cc82c2068b37730db Lait Demi-écrémé Aromatisé - lait demi ecreme aromatise - - - 38 - - - KCA#5f315c448ad7d9f47c565c26bc467d76 Lait Demi-écrémé en Poudre - lait demi ecreme en poudre - - - 13 - - - KCA#142dc57784314bb5d9232ef1c9c8c155 Lait Demi-écrémé Pasteurisé - lait demi ecreme pasteurise - - - 62 - - - KCA#3b75e189515de06da4c3d229418838e1 ---------------------------------------------------- --------------------------------- final result ----------------------------------- {'prompt': "J'ai bu la moitié d'un grand verre de lait demi écrémé.", 'model': 'mistral-large-2411', 'imagePath': '', 'intents': ['Identify food and beverage consumption or declaration'], 'solutions': {'nutrition': [{'name': 'Lait Demi-écrémé', 'normName': ' lait demi ecreme ', 'comment': 'UHT', 'normComment': ' uht ', 'rank': 1882, 'id': 'CIQ#a52f3d296711c40b0cf1a9e387dd93c3', 'quantity': "la moitié d'un grand verre", 'quantityLem': '1/2 grand verre', 'pack': ['VX1', 'VA2', 'VA3', 'BI4', 'VA4'], 'type': 'beverage', 'gtin': '', 'gtinRef': '', 'brand': '', 'time': 'unknown', 'event': 'declaration', 'serving': 'VX1-50', 'posiNormName': 0}], 'activity': [], 'response': {}}, 'cputime': 2.527322769165039} ---------------------------------------------------------------------------------- LLM CPU Time: 2.527322769165039