Input path: /home/debian/html/nutritwin/output_llm/674ef5303676c/input.json Output path: /home/debian/html/nutritwin/output_llm/674ef5303676c/output.json Input text: Et trois courgettes. 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: Et trois courgettes. ================================================================================================================================== ==================================== 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: ###Et trois courgettes.###. 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 : """Et trois courgettes.""" 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": "courgettes", "quantity": "trois", "type": "food", "event": "declaration" } ] ``` ----------------------------------------------------------------------------- ----------------- Make it compliant ------------------ ```json [ { "name": "courgettes", "quantity": "trois", "type": "food", "event": "declaration" } ] ``` ------------------------------------------------------ ------------------------ After simplification ------------------------ [ { "name": "courgettes", "quantity": "trois", "type": "food", "event": "declaration" }] ---------------------------------------------------------------------- --------------------------------- LLM result ----------------------------------- {'response': [{'name': 'courgettes', 'quantity': 'trois', 'type': 'food', 'event': 'declaration'}], 'cost': 0.0} -------------------------------------------------------------------------------- ----------- result to be analyzed ----------- {'name': 'courgettes', 'quantity': 'trois', '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 '% courgette %' AND (V_NormTrademark = '' OR V_NormTrademark IS NULL) ------------- Found solution (max 20) -------------- Courgette - courgette - pulpe et peau - - 6197 - - - CIQ#8f15e99f917acaea5e5d4d09c1ac70fd Courgette - courgette - pulpe et peau, crue - - 10037 - - - CIQ#293f06655b9594a266b55f179a16bd56 Courgette - courgette - pulpe et peau, rôtie/cuite au four - - 0 - - - CIQ#2a09434ec4c982719db3b87fb986b92a Courgettes Frites - courgette frite - - - 207 - - - KCA#959d0fa787188921ad4497a575b243ab Courgettes Farcies - courgette farcie - - - 862 - - - KCA#77e254b2cd7edd2930ea260315eff594 Courgettes Mousseline - courgette mousseline - - - 168 - - - KCA#25d0446a01b3d8dd52d503827adba452 Courgettes à l'Orientale - courgette orientale - - - 26 - - - KCA#67d86f19e38566e0d5b257f32b627f4d Courgettes Façon Actifry - courgette facon actifry - - - 15 - - - KCA#10c8891e84e0c283919c921e9acde855 Courgettes Farcies au Maigre - courgette farcie maigre - - - 42 - - - KCA#c6d1d8514e1d9b2ea736c6751ba2e452 Flan de Courgette - flan de courgette - - - 890 - - - KCA#9809af1c34ea8cd82f667ff2d233bf58 Pâtes aux Courgettes et à la Ricotta - pate au courgette ricotta - - - 86 - - - KCA#b083d2bc60b9e47b8d1416c1969b5f6d Purée de Courgettes Pomme de Terre - puree de courgette pomme de terre - - - 96 - - - KCA#33431af664194d56f5845a8d1fa010a9 Gratin de Courgettes à la Bolognaise - gratin de courgette bolognaise - - - 99 - - - KCA#3a9a287b43639c40798a6e25743e7505 Beignets de Courgettes - beignet de courgette - - - 147 - - - KCA#d826bc4b23eebc71f3a93e4321e1632f Omelette aux Courgettes - omelette au courgette - - - 125 - - - KCA#4b746e9c0feef9bca3c7252301d6c95d Lentilles Brunes à la Courgette et au Chorizo - lentille brune courgette chorizo - - - 6 - - - KCA#488b3d0b5e6b068cb458940010656fd5 ---------------------------------------------------- --------------------------------- final result ----------------------------------- {'prompt': 'Et trois courgettes.', 'intents': ['Identify food consumption or declaration'], 'model': 'gpt-4o-2024-05-13', 'solutions': {'nutrition': [{'name': 'Courgette', 'normName': ' courgette ', 'comment': 'pulpe et peau', 'normComment': ' pulpe peau ', 'rank': 6197, 'id': 'CIQ#8f15e99f917acaea5e5d4d09c1ac70fd', 'quantity': 'trois', 'quantityLem': '3', 'pack': ['CO3.w300'], 'type': 'food', 'gtin': '', 'gtinRef': '', 'brand': '', 'time': '', 'event': 'declaration', 'serving': 'CO3-300', 'posiNormName': 0}], 'activity': [], 'response': {}}, 'cputime': 1.349029779434204} ---------------------------------------------------------------------------------- LLM CPU Time: 1.349029779434204