Input path: /home/debian/html/nutritwin/output_llm/67a9931795cd3/input.json Output path: /home/debian/html/nutritwin/output_llm/67a9931795cd3/output.json Input text: Ce matin j'ai mangé une choucroute chez Picard. 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: Ce matin j'ai mangé une choucroute chez Picard. ================================================================================================================================== ==================================== 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: ###Ce matin j'ai mangé une choucroute chez Picard.###. 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 : """Ce matin j'ai mangé une choucroute chez Picard.""" 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": "choucroute", "quantity": "une", "timeOfTheDay": "breakfast", "company": "Picard", "type": "food", "event": "declaration" } ] ----------------------------------------------------------------------------- ----------------- Make it compliant ------------------ [ { "name": "choucroute", "quantity": "une", "timeOfTheDay": "breakfast", "company": "Picard", "type": "food", "event": "declaration" } ] ------------------------------------------------------ ------------------------ After simplification ------------------------ [ { "name": "choucroute", "quantity": "une", "timeOfTheDay": "breakfast", "company": "Picard", "type": "food", "event": "declaration" } ] ---------------------------------------------------------------------- --------------------------------- LLM result ----------------------------------- {'response': [{'name': 'choucroute', 'quantity': 'une', 'timeOfTheDay': 'breakfast', 'company': 'Picard', 'type': 'food', 'event': 'declaration'}], 'cost': 0.09953999999999999} -------------------------------------------------------------------------------- ----------- result to be analyzed ----------- {'name': 'choucroute', 'quantity': 'une', 'timeOfTheDay': 'breakfast', 'company': 'Picard', '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 '% choucroute %' AND (V_NormTrademark = '' OR V_NormTrademark IS NULL) ------------- Found solution (max 20) -------------- Choucroute - choucroute - sans garniture, égouttée - - 0 - - - CIQ#6acdabefbb9a93df9a37b53a0e5a1528 Choucroute Garnie - choucroute garnie - - - 43 - - - CIQ#e868879c2133106dca8a3dd8cc9388b3 Choucroute Braisée - choucroute braisee - - - 16 - - - KCA#c1ad4c1f305ca2fcebf2c8d9da910678 Choucroute Cru en Salade - choucroute cru en salade - - - 25 - - - KCA#f22402ddcd21104911fa050cbb22613c Choucroute Garnie en Conserve - choucroute garnie en conserve - - - 48 - - - KCA#87921f579a68ecb84684a2ace8e40cce Faisan à la Choucroute - faisan choucroute - - - 8 - - - KCA#55c69c206d72d01c8434dc0d0b23e5b6 Soupe de Choucroute - soupe de choucroute - de choucroute - - 0 - - - KCA#062987b01dfffdbb9d2b35b2032c689f Omelette à la Choucroute - omelette choucroute - - - 1 - - - KCA#7cab890452cffe55546fa515aa73d6f1 Sanglier à la Choucroute - sanglier choucroute - la choucroute - - 0 - - - KCA#77f4d2e039288458f6aa93a41b78e12d ---------------------------------------------------- --------------------------------- final result ----------------------------------- {'prompt': "Ce matin j'ai mangé une choucroute chez Picard.", 'model': 'mistral-large-2411', 'imagePath': '', 'intents': ['Identify food and beverage consumption or declaration'], 'solutions': {'nutrition': [{'name': 'Choucroute', 'normName': ' choucroute ', 'comment': 'sans garniture, égouttée', 'normComment': ' san garniture egouttee ', 'rank': 0, 'id': 'CIQ#6acdabefbb9a93df9a37b53a0e5a1528', 'quantity': 'une', 'quantityLem': '1', 'pack': ['LEG.w250'], 'type': 'food', 'gtin': '', 'gtinRef': '', 'brand': '', 'time': 'breakfast', 'event': 'declaration', 'serving': 'LEG-100', 'posiNormName': 0}], 'activity': [], 'response': {}}, 'cputime': 2.135042905807495} ---------------------------------------------------------------------------------- LLM CPU Time: 2.135042905807495