Input path: /home/debian/html/nutritwin/output_llm/6755f9f7040b2/input.json Output path: /home/debian/html/nutritwin/output_llm/6755f9f7040b2/output.json Input text: Noisettes. 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: Noisettes. ================================================================================================================================== ==================================== 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: ###Noisettes.###. 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 : """Noisettes.""" 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": "noisettes", "type": "food" } ] ----------------------------------------------------------------------------- ----------------- Make it compliant ------------------ [ { "name": "noisettes", "type": "food" } ] ------------------------------------------------------ ------------------------ After simplification ------------------------ [ { "name": "noisettes", "type": "food" } ] ---------------------------------------------------------------------- --------------------------------- LLM result ----------------------------------- {'response': [{'name': 'noisettes', 'type': 'food'}], 'cost': 0.09558} -------------------------------------------------------------------------------- ----------- result to be analyzed ----------- {'name': 'noisettes', 'type': 'food'} 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 '% noisette %' AND (V_NormTrademark = '' OR V_NormTrademark IS NULL) ------------- Found solution (max 20) -------------- Café Noisette - cafe noisette - - - 971 - - - KCA#0fc9cdc7bb8a494e3e53719b2bee98c8 Huile de Noisette - huile de noisette - - - 0 - - - CIQ#24bed2b2c48a227f44a6872ed2618569 Boisson au Soja Noisette - boisson soja noisette - - - 20 - - - KCA#87e793ca44d2d523db4b70ace49d3e51 Chocolat Noir Noisettes - chocolat noir noisette - - - 1875 - - - KCA#49fc5b19d990e357f20d1160e7d62f54 Pomme de Terre Noisette - pomme de terre noisette - surgelée - - 157 - - - CIQ#bce127ab00d79ace0ff66e3709eafd22 Pomme de Terre Noisette - pomme de terre noisette - surgelée, crue - - 0 - - - CIQ#391f5b673a701be591447c173adaf18f Pomme de Terre Noisettes Surgelées - pomme de terre noisette surgelee - - - 0 - - - KCA#d43857a6fbd01bb1731fde84cf29cfa5 Cervelles au Beurre Noisette - cervelle beurre noisette - - - 4 - - - KCA#1bac1429347e303fdba3fd4cb394a2fb Bouchées Chocolat-noisettes - bouchee chocolat noisette - - - 50 - - - KCA#bf1495123a9a4c627909d042f0dc26ce Parfaits Chocolat Noir Noisettes - parfait chocolat noir noisette - - - 18 - - - KCA#205552965fb668730b8519c91500d669 Pétales de Blé Avec Noix, Noisettes ou Amandes - petale de ble avec noix noisette ou amande - - - 7 - - - KCA#3a4b816b40d2ca2fcf1525d8761ea6cf Saucisson Sec aux Noix Et/ou Noisettes - saucisson sec au noix et/ou noisette - - - 0 - - - CIQ#7ca1c35bcbabd2cf0891661c40e8f457 Barre Céréalière aux Amandes ou Noisettes - barre cerealiere au amande ou noisette - - - 0 - - - CIQ#5f4a2840e6a66958acf93b120dc45c13 Gaufrette Fourrée, Chocolat, Vanille ou Noisette - gaufrette fourree chocolat vanille ou noisette - - - 159 - - - KCA#75baba95a2a821d1233cfdd709037734 Céréales pour Petit Déjeuner Fourrées au Chocolat ou Chocolat-noisettes - cereale pour petit dejeuner fourree chocolat ou chocolat noisette - - - 3 - - - CIQ#b2f581ebe4c1d7c626f9b82500c40f2d Céréales pour Petit Déjeuner Fourrées au Chocolat ou Chocolat-noisettes - cereale pour petit dejeuner fourree chocolat ou chocolat noisette - enrichies en vitamines et minéraux - - 0 - - - CIQ#deb33f8fd6e7d92ffd7460e84d331dc8 ---------------------------------------------------- ERROR: Wrong quantity: '' ERROR: no solution for picto in the first solution --------------------------------- final result ----------------------------------- {'prompt': 'Noisettes.', 'model': 'mistral-large-2411', 'imagePath': '', 'intents': ['Identify food and beverage consumption or declaration'], 'solutions': {'nutrition': [{'name': 'Café Noisette', 'normName': ' cafe noisette ', 'comment': '', 'normComment': '', 'rank': 971, 'id': 'KCA#0fc9cdc7bb8a494e3e53719b2bee98c8', 'quantity': '', 'quantityLem': '', 'pack': ['TA2', 'TAS', 'TAC', 'TA3', 'MUG', 'BOL'], 'type': 'food', 'gtin': '', 'gtinRef': '', 'brand': '', 'time': '', 'event': 'unknown', 'serving': '', 'posiNormName': 5}], 'activity': [], 'response': {}}, 'cputime': 1.758216381072998} ---------------------------------------------------------------------------------- LLM CPU Time: 1.758216381072998