Input path: /home/debian/html/nutritwin/output_llm/68ce48310ca7b/input.json Output path: /home/debian/html/nutritwin/output_llm/68ce48310ca7b/output.json Input text: Ce matin j'ai mangé un couscous de 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 un couscous de 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 un couscous de 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 un couscous de 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": "couscous", "quantity": "un", "timeOfTheDay": "breakfast", "brand": "Picard", "company": "Picard", "type": "food", "event": "declaration" } ] ----------------------------------------------------------------------------- ----------------- Make it compliant ------------------ [ { "name": "couscous", "quantity": "un", "timeOfTheDay": "breakfast", "brand": "Picard", "company": "Picard", "type": "food", "event": "declaration" } ] ------------------------------------------------------ ------------------------ After simplification ------------------------ [ { "name": "couscous", "quantity": "un", "timeOfTheDay": "breakfast", "brand": "Picard", "company": "Picard", "type": "food", "event": "declaration" } ] ---------------------------------------------------------------------- --------------------------------- LLM result ----------------------------------- {'response': [{'name': 'couscous', 'quantity': 'un', 'timeOfTheDay': 'breakfast', 'brand': 'Picard', 'company': 'Picard', 'type': 'food', 'event': 'declaration'}], 'cost': 0.10085999999999999} -------------------------------------------------------------------------------- ----------- result to be analyzed ----------- {'name': 'couscous', 'quantity': 'un', 'timeOfTheDay': 'breakfast', 'brand': 'Picard', '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 '% couscou %' AND V_NormTrademark LIKE '%picard%' ------------- Found solution (max 20) -------------- Couscous - couscou - - Picard - 0 - 3270160860753 - 3270160860753 - OFF#8b7e171b8124e7f860189f765a6b4ea2 Couscous Royal - couscou royal - - Picard - 0 - 3270160864393 - 3270160864393 - OFF#27c2e7fb882dff234b3b95a4df5e4636 Couscous Royal - couscou royal - - Picard - 0 - 3270160864591 - 3270160864393 - OFF#eb37f0ae8370565f701088c26a87cfe0 Couscous Royal - couscou royal - - Picard - 0 - 3270160864409 - 3270160864393 - OFF#47310ccedfd03dd45940970f64377555 Couscous Surgelé - couscou surgele - - Picard - 0 - 3270160381630 - 3270160381630 - OFF#bb4cdf161b37537f4370e1d8b798e05c Couscous Tout Bon Tout Veggie - couscou tout bon tout veggie - - Picard - 0 - 3270160861842 - 3270160861842 - OFF#e3316e7124e19b00de23a55912bd6af8 Couscous Royal au Poulet Merguez et Agneau - couscou royal poulet merguez agneau - - Picard - 0 - 3270160290239 - 3270160290239 - OFF#db76e32a04cc89f481754119e22ad67f Couscous Royal au Poulet Agneau et Merguez - couscou royal poulet agneau merguez - - Picard - 0 - 3270160399802 - 3270160399802 - OFF#30d4db3972a6cf4aaa2e732453d5a098 Graine de Couscous Cuisinée - graine de couscou cuisinee - - Picard - 0 - 3270160751921 - 3270160751921 - OFF#fa5a9984365b1589ac7bac1fdd3c02d2 Légumes pour Couscous - legume pour couscou - - Picard - 0 - 3270160116355 - 3270160116355 - OFF#bffa8f91b6286fd3010ae4793e051cc1 ---------------------------------------------------- --------------------------------- final result ----------------------------------- {'prompt': "Ce matin j'ai mangé un couscous de chez Picard.", 'model': 'mistral-large-2411', 'imagePath': '', 'intents': ['Identify food and beverage consumption or declaration'], 'solutions': {'nutrition': [{'name': 'Couscous', 'normName': ' couscou ', 'comment': '', 'normComment': '', 'rank': 0, 'id': 'OFF#8b7e171b8124e7f860189f765a6b4ea2', 'quantity': 'un', 'quantityLem': '1', 'pack': ['BA1.w400'], 'type': 'food', 'gtin': '3270160860753', 'gtinRef': '3270160860753', 'brand': 'Picard', 'time': 'breakfast', 'event': 'declaration', 'serving': 'BA1-100', 'posiNormName': 0}], 'activity': [], 'response': {}}, 'cputime': 2.21916127204895} ---------------------------------------------------------------------------------- LLM CPU Time: 2.21916127204895