Input path: /home/debian/html/nutritwin/output_llm/67076789b750b/input.json Output path: /home/debian/html/nutritwin/output_llm/67076789b750b/output.json Input text: Miel. 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: Miel. ================================================================================================================================== ==================================== Prompt ============================================= Identify in this list of intents: ["Identify food consumption or declaration", "Identify the user physical activity", "Answer a nutrition question", "Other intent"], the intents of the prompt: ###Miel.###. Format the result in JSON format: {intents: []}. ========================================================================================= ------------------------------ LLM Raw response ----------------------------- ```json { "intents": ["Identify food consumption or declaration"] } ``` ----------------------------------------------------------------------------- ----------------- Make it compliant ------------------ ```json { "intents": ["Identify food consumption or declaration"] } ``` ------------------------------------------------------ ------------------------ After simplification ------------------------ { "intents": ["Identify food consumption or declaration"]} ---------------------------------------------------------------------- ==================================== Prompt ============================================= Convert this natural language query : """Miel.""" into an array in JSON of consumed foods and beverages. Provide a solution without explanation. Use only the 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. Keep the same language"@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 examples in french: '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. Keep the same language"@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. """ ========================================================================================= ------------------------------ LLM Raw response ----------------------------- ```json [ { "name": "Miel", "type": "food", "event": "declaration" } ] ``` ----------------------------------------------------------------------------- ----------------- Make it compliant ------------------ ```json [ { "name": "Miel", "type": "food", "event": "declaration" } ] ``` ------------------------------------------------------ ------------------------ After simplification ------------------------ [ { "name": "Miel", "type": "food", "event": "declaration" }] ---------------------------------------------------------------------- --------------------------------- LLM result ----------------------------------- {'response': [{'name': 'Miel', 'type': 'food', 'event': 'declaration'}], 'cost': 0.0} -------------------------------------------------------------------------------- ----------- result to be analyzed ----------- {'name': 'Miel', '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 '% miel %' AND (V_NormTrademark = '' OR V_NormTrademark IS NULL) ------------- Found solution (max 20) -------------- Miel - miel - - - 0 - - - KCA#96ff85afb6bb999b8e49234b7c73b6bf Miel à la Crème - miel creme - - - 11 - - - KCA#a8954a11bb2f917d2296765e03573431 Yaourt au Miel - yaourt miel - au miel - - 0 - - - KCA#7bc806db91685c4866b04b5c0572e837 Poulet au Miel - poulet miel - et salade de Fenouil et Céleri à la crème - - 43 - - - KCA#10b8495a1834253e87733dc33ffcfd80 Céréales au Miel - cereale miel - - - 101 - - - KCA#b7c3cb966f2cb1fa8c64e261bae639cb Tartine de Miel - tartine de miel - de miel - - 0 - - - KCA#f1120bad0f1824670c66545c12c253b8 Smoothie Fraise, Miel et Lait de Soja - smoothie fraise miel lait de soja - de soja - - 0 - - - KCA#0df871f30036f11a511b24cd8865c9d1 Gaufre Fine Fourrée au Miel - gaufre fine fourree miel - - - 0 - - - CIQ#d7548ec38dd18f8b746f4a84d1c5a299 Grains de Blé Soufflés au Miel ou Caramel - grain de ble souffle miel ou caramel - enrichis en vitamines et minéraux - - 0 - - - CIQ#2069162d695f520f936002ca3ae5b9ba Boules de Maïs Soufflées au Miel - boule de mai soufflee miel - enrichies en vitamines et minéraux - - 0 - - - CIQ#38b642aa77c7f83166bc66cda176b3a2 Boules de Maïs Soufflées au Miel - boule de mai soufflee miel - non enrichies en vitamines et minéraux - - 0 - - - CIQ#0a24c0c921aa72366a89dba7d796aa56 Salade Betteraves et Agneau au Miel - salade betterave agneau miel - - - 24 - - - KCA#2166cb4870932bad02161df026c04633 Brochette de Fruits et Yaourt au Miel - brochette de fruit yaourt miel - - - 28 - - - KCA#11eeb2c6445f4bdf8b9cea8483524d8e Céréales pour Petit Déjeuner "équilibre" Nature ou au Miel - cereale pour petit dejeuner equilibre nature ou miel - enrichies en vitamines et minéraux - - 0 - - - CIQ#35a6751d63934e94c6ee6428fc45e658 ---------------------------------------------------- ERROR: Wrong quantity: '' ERROR: no solution for picto in the first solution --------------------------------- final result ----------------------------------- {'prompt': 'Miel.', 'intents': ['Identify food consumption or declaration'], 'model': 'gpt-4o-2024-05-13', 'solutions': {'nutrition': [{'name': 'Miel', 'normName': ' miel ', 'comment': '', 'normComment': '', 'rank': 0, 'id': 'KCA#96ff85afb6bb999b8e49234b7c73b6bf', 'quantity': '', 'quantityLem': '', 'pack': ['CCS.w10', 'MAR.w35'], 'type': 'food', 'gtin': '', 'gtinRef': '', 'brand': '', 'time': '', 'event': 'declaration', 'serving': '', 'posiNormName': 0}], 'activity': [], 'response': {}}, 'cputime': 1.384408950805664} ---------------------------------------------------------------------------------- LLM CPU Time: 1.384408950805664