Input path: /home/debian/html/nutritwin/output_llm/67560bb59c69b/input.json Output path: /home/debian/html/nutritwin/output_llm/67560bb59c69b/output.json Input text: Ce matin j'ai mangé deux bananes et bu une tasse de thé. 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 deux bananes et bu une tasse de thé. ================================================================================================================================== ==================================== 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 deux bananes et bu une tasse de thé.###. 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 deux bananes et bu une tasse de thé.""" 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...)."@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. 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."@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. 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": "banane", "quantity": "deux", "timeOfTheDay": "breakfast", "type": "food", "event": "declaration" }, { "name": "thé", "quantity": "une tasse", "timeOfTheDay": "breakfast", "type": "beverage", "event": "declaration" } ] ----------------------------------------------------------------------------- ----------------- Make it compliant ------------------ [ { "name": "banane", "quantity": "deux", "timeOfTheDay": "breakfast", "type": "food", "event": "declaration" }, { "name": "thé", "quantity": "une tasse", "timeOfTheDay": "breakfast", "type": "beverage", "event": "declaration" } ] ------------------------------------------------------ ------------------------ After simplification ------------------------ [ { "name": "banane", "quantity": "deux", "timeOfTheDay": "breakfast", "type": "food", "event": "declaration" }, { "name": "th\u00e9", "quantity": "une tasse", "timeOfTheDay": "breakfast", "type": "beverage", "event": "declaration" } ] ---------------------------------------------------------------------- --------------------------------- LLM result ----------------------------------- {'response': [{'name': 'banane', 'quantity': 'deux', 'timeOfTheDay': 'breakfast', 'type': 'food', 'event': 'declaration'}, {'name': 'thé', 'quantity': 'une tasse', 'timeOfTheDay': 'breakfast', 'type': 'beverage', 'event': 'declaration'}], 'cost': 0.10692} -------------------------------------------------------------------------------- ----------- result to be analyzed ----------- {'name': 'banane', 'quantity': 'deux', 'timeOfTheDay': 'breakfast', '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 '% banane %' AND (V_NormTrademark = '' OR V_NormTrademark IS NULL) ------------- Found solution (max 20) -------------- Banane - banane - pulpe, crue - - 57967 - - - CIQ#6066b5bb884711efc0e44c9446b96aa3 Banane Sèche - banane seche - - - 346 - - - KCA#2e3e40d3b1ae9f793251e9948142d784 Bananes en Robe - banane en robe - - - 14 - - - KCA#b274666ef64f762c58695191d4286b85 Banane Plantain - banane plantain - - - 2 - - - CIQ#1055a76a23712202f3c842fba09fa691 Bananes Barbecue - banane barbecue - - - 33 - - - KCA#1d31fb8efe54f0bc7765a60cc9f8c324 Bananes au Jambon - banane jambon - - - 4 - - - KCA#e21d980b838ba89f4e9ba1d85f593c95 Smoothie Banane et Lait de Soja - smoothie banane lait de soja - de soja - - 0 - - - KCA#dc0b16a02e5290892f9adee7419ec0e7 Crème Glacée Banane, Pomme et Noix de Macadamia - creme glacee banane pomme noix de macadamia - - - 34 - - - KCA#3233d39965b7baa31d10a301ac541ffa Bruschette à la Fraise, à la Banane et à la Ricotta - bruschette fraise banane ricotta - - - 2 - - - KCA#fd9db147f698ab1c84b0905704258a5f ---------------------------------------------------- ----------- result to be analyzed ----------- {'name': 'thé', 'quantity': 'une tasse', 'timeOfTheDay': 'breakfast', '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 '% the %' AND (V_NormTrademark = '' OR V_NormTrademark IS NULL) ------------- Found solution (max 20) -------------- Thé Vert - the vert - infusé, non sucré - - 0 - - - CIQ#eac5c73b642ef9eb1db2cafc9d1843ba Thé Noir - the noir - infusé, non sucré - - 0 - - - CIQ#bf75fb01672a7afe76ba5a88645e87ca Thé Infusé - the infuse - non sucré - - 0 - - - CIQ#09bb3cfe071d2337b58db8e32379af6d Thé Oolong - the oolong - infusé, non sucré - - 0 - - - CIQ#dcf2a40c30e0bd1cf9736831ce2f1a07 Thé sans Sucre - the san sucre - sans sucre - - 0 - - - KCA#9de5d7e3a39cb14df7a2014ed9319364 Thé au Lait Sucré - the lait sucre - 1 sucre - - 2799 - - - KCA#f79219b7fdb1e0186da32547f7467cc3 Thé Sucré (1 Sucre) - the sucre - sucré (1 sucre) - - 0 - - - KCA#ce556337e0d9788306e32b24fe0fe081 Thé au Lait sans Sucre - the lait san sucre - sans sucre - - 0 - - - KCA#978c8f4bf945ce13218480e6d937996a Thé à la Menthe sans Sucre - the menthe san sucre - sans sucre - - 0 - - - KCA#d6b018fd859ac0e6ee70bca51b09db90 Sex On The Beach - se on the beach - the beach - - 0 - - - KCA#f07d74af373a5290a216c60de530b430 Boisson au Thé - boisson the - aromatisée, sucrée - - 94 - - - KCA#b6e1f48e249eca1255475b06f7bf38aa Boisson au Thé - boisson the - aromatisée, sucrée - - 0 - - - CIQ#b6e1f48e249eca1255475b06f7bf38aa Boisson au Thé - boisson the - aromatisée, 'light' - - 6 - - - KCA#c1894f128b1446d7f36c0d2f350d199c Boisson au Thé - boisson the - aromatisée, teneur en sucre et édulcorant inconnue, aliment moyen - - 0 - - - CIQ#7deb532133632b6172af215d3ff1ff5b Pruneaux au Thé - pruneau the - - - 6 - - - KCA#8cb9a957c6950b74118bd4b2efeeb2b9 ---------------------------------------------------- --------------------------------- final result ----------------------------------- {'prompt': "Ce matin j'ai mangé deux bananes et bu une tasse de thé.", 'model': 'mistral-large-2411', 'imagePath': '', 'intents': ['Identify food and beverage consumption or declaration'], 'solutions': {'nutrition': [{'name': 'Banane', 'normName': ' banane ', 'comment': 'pulpe, crue', 'normComment': ' pulpe crue ', 'rank': 57967, 'id': 'CIQ#6066b5bb884711efc0e44c9446b96aa3', 'quantity': 'deux', 'quantityLem': '2', 'pack': ['BAN.w100'], 'type': 'food', 'gtin': '', 'gtinRef': '', 'brand': '', 'time': 'breakfast', 'event': 'declaration', 'serving': 'BAN-200', 'posiNormName': 0}, {'name': 'Thé Vert', 'normName': ' the vert ', 'comment': 'infusé, non sucré', 'normComment': ' infuse non sucre ', 'rank': 0, 'id': 'CIQ#eac5c73b642ef9eb1db2cafc9d1843ba', 'quantity': 'une tasse', 'quantityLem': '1 tasse', 'pack': ['TAC'], 'type': 'beverage', 'gtin': '', 'gtinRef': '', 'brand': '', 'time': 'breakfast', 'event': 'declaration', 'serving': 'TAC-100', 'posiNormName': 0}], 'activity': [], 'response': {}}, 'cputime': 3.1829874515533447} ---------------------------------------------------------------------------------- LLM CPU Time: 3.1829874515533447