Input path: /home/debian/html/nutritwin/output_llm/688f0f720d3e2/input.json Output path: /home/debian/html/nutritwin/output_llm/688f0f720d3e2/output.json Input text: Pain de mie. 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: Pain de mie. ================================================================================================================================== ==================================== 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: ###Pain de mie.###. 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 : """Pain de mie.""" 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": "Pain de mie", "type": "food", "event": "unknown" } ] ----------------------------------------------------------------------------- ----------------- Make it compliant ------------------ [ { "name": "Pain de mie", "type": "food", "event": "unknown" } ] ------------------------------------------------------ ------------------------ After simplification ------------------------ [ { "name": "Pain de mie", "type": "food", "event": "unknown" } ] ---------------------------------------------------------------------- --------------------------------- LLM result ----------------------------------- {'response': [{'name': 'Pain de mie', 'type': 'food', 'event': 'unknown'}], 'cost': 0.09498} -------------------------------------------------------------------------------- ----------- result to be analyzed ----------- {'name': 'Pain de mie', 'type': 'food', 'event': 'unknown'} 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 '% pain de mie %' AND (V_NormTrademark = '' OR V_NormTrademark IS NULL) ------------- Found solution (max 20) -------------- Pain de Mie - pain de mie - au son - - 0 - - - CIQ#1f8d06921f1e892824b0f8cef870e840 Pain de Mie - pain de mie - complet - - 7211 - - - CIQ#d93405497d2314d29dbd770c5b956eeb Pain de Mie - pain de mie - courant - - 0 - - - CIQ#667832b5357e637fdb28760b7d6c2d8d Pain de Mie - pain de mie - sans croûte - - 32 - - - CIQ#be3f663945b51703d39413cadc3becab Pain de Mie - pain de mie - multicéréale - - 0 - - - CIQ#1a7f6353f1d198d63d9190f20bf65b94 Pain de Mie BIO - pain de mie bio - - - 573 - - - KCA#de7cb7a29dddd397d84bb63484176775 Pain de Mie Brioché - pain de mie brioche - - - 39 - - - CIQ#43270a90a216c85ab3a94ad1e1b540dc Pain de Mie Complet - pain de mie complet - - - 0 - - - KCA#1f762b65417f3922103fbe02a3d22d58 Pain de Mie Blanc Complet - pain de mie blanc complet - - - 185 - - - KCA#eb6f24aca02b0ede670860dc4e4684bd Sandwich Pain de Mie - sandwich pain de mie - garnitures diverses - - 0 - - - CIQ#8af1bc20920d41ac8b1895bc748ebd00 Sandwich Pain de Mie Complet - sandwich pain de mie complet - jambon, fromage - - 0 - - - CIQ#49b8cf6a14f0f9cfd1f8e4600f5de165 Sandwich Pain de Mie Complet - sandwich pain de mie complet - thon, crudités, mayonnaise - - 0 - - - CIQ#49e46e93f6417859429add73e5ccb6bd Sandwich Pain de Mie Complet - sandwich pain de mie complet - poulet, crudités, mayonnaise - - 0 - - - CIQ#f4eecdeef4880cb180975eb8b0af38bc Sandwich Pain de Mie Complet - sandwich pain de mie complet - jambon, crudités, fromage optionnel - - 0 - - - CIQ#fd8d57dae2cac42db713e068a5372f67 ---------------------------------------------------- ERROR: Wrong quantity: '' ERROR: no solution for picto in the first solution ERROR: Wrong quantity: '' ERROR: no solution for picto in the first solution ERROR: Wrong quantity: '' ERROR: no solution for picto in the first solution ERROR: Wrong quantity: '' ERROR: no solution for picto in the first solution ERROR: Wrong quantity: '' ERROR: no solution for picto in the first solution --------------------------------- final result ----------------------------------- {'prompt': 'Pain de mie.', 'model': 'mistral-large-2411', 'imagePath': '', 'intents': ['Identify food and beverage consumption or declaration'], 'solutions': {'nutrition': [{'name': 'Pain de Mie', 'normName': ' pain de mie ', 'comment': 'au son', 'normComment': ' son ', 'rank': 0, 'id': 'CIQ#1f8d06921f1e892824b0f8cef870e840', 'quantity': '', 'quantityLem': '', 'pack': ['TR1.w20'], 'type': 'food', 'gtin': '', 'gtinRef': '', 'brand': '', 'time': '', 'event': 'unknown', 'serving': '', 'posiNormName': 0}], 'activity': [], 'response': {}}, 'cputime': 1.6622755527496338} ---------------------------------------------------------------------------------- LLM CPU Time: 1.6622755527496338