Input path: /home/debian/html/nutritwin/output_llm/679b120051157/input.json Output path: /home/debian/html/nutritwin/output_llm/679b120051157/output.json Input text: 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: ================================================================================================================================== Image to be analyzed: /home/debian/html/nutritwin/output_llm/679b120051157/capture.jpg ############################################################################################## # For image extraction, pixtral-large-2411 is used # ############################################################################################## ==================================== Prompt ============================================= In the image, identify all the foods and beverages, convert them into an array of JSON with consumed foods. Ignore what it is not connected to nutrition, beverage or food. When a food or a beverage has several instances unify them on a single food or beverage and add the quantities of each. The attribute name must remain in English but the result, so the attribute value, must be in french, and only in french. Provide a solution without explanation. Use only the food & beverage 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": "Danette", "quantity": "un", "brand": "Danone", "type": "food", "event": "declaration" } ] ----------------------------------------------------------------------------- ----------------- Make it compliant ------------------ [ { "name": "Danette", "quantity": "un", "brand": "Danone", "type": "food", "event": "declaration" } ] ------------------------------------------------------ ------------------------ After simplification ------------------------ [ { "name": "Danette", "quantity": "un", "brand": "Danone", "type": "food", "event": "declaration" } ] ---------------------------------------------------------------------- --------------------------------- LLM result ----------------------------------- {'response': [{'name': 'Danette', 'quantity': 'un', 'brand': 'Danone', 'type': 'food', 'event': 'declaration'}], 'cost': 0.0} -------------------------------------------------------------------------------- ----------- result to be analyzed ----------- {'name': 'Danette', 'quantity': 'un', 'brand': 'Danone', '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 '% danette %' AND V_NormTrademark LIKE '%danone%' ------------- Found solution (max 20) -------------- Danette - danette - - Danone - 0 - 3033490198640 - 3033490198640 - OFF#f789b0076d9b058a8264aada1b55b736 Danette - danette - - Danone - 0 - 3033491420702 - 3033490198640 - OFF#b289934e1f4d0753348e3813dced3ddf Danette - danette - - Danone - 0 - 3033491312380 - 3033490198640 - OFF#eaf5713a989f641aa4972f1c8d8edbbb Danette - danette - - Danone - 0 - 3033491063961 - 3033490198640 - OFF#9a9f6df18c627d1a1f3ce6f56f6131be Danette - danette - - Danone - 0 - 3033491434136 - 3033490198640 - OFF#aae1e433b0b7f190ded530b70f9722ee Danette - danette - - Danone - 0 - 3033490913243 - 3033490198640 - OFF#6c5b0406b33986ea85a21ae1d6446266 Danette - danette - - Danone - 0 - 3033490906337 - 3033490198640 - OFF#d693bd9b76adaa57975547320fc5daf6 Danette - danette - - Danone - 0 - 3033490906290 - 3033490198640 - OFF#f5d99a5a19bfd854a66261433259cea9 Danette - danette - - Danone - 0 - 3033490913250 - 3033490198640 - OFF#55d57375842b66e1c8c90b29d2550cf1 Danette - danette - - Danone - 0 - 3033491420382 - 3033490198640 - OFF#03f9ec38345769682f6bfb9622c35ebf Danette - danette - - Danone - 0 - 3033490906276 - 3033490198640 - OFF#4ec09a818ad2f4f9cdeb855b2aaa3867 Danette - danette - - Danone - 0 - 3368850006175 - 3033490198640 - OFF#9a77e472aa23f46f81f92ff5734c1186 Danette - danette - - Danone - 0 - 3033491312397 - 3033490198640 - OFF#0b6a4691f32925c49bce7e46a6860c3b Danette Noir - danette noir - - Danone - 0 - 3033491279744 - 3033491279744 - OFF#9e551ad69ebea37dde4b2260bb54cc01 Danette Cafe - danette cafe - - Danone - 0 - 3033491420665 - 3033491420665 - OFF#a55f16a46e0726de6582ae009666bb79 Danette Choco - danette choco - - Danone - 0 - 5601050034172 - 5601050034172 - OFF#c93fd5d04bd21a89fd693cc2572965ff Danette 4 Pots - danette pot - - Danone - 0 - 3033490753337 - 3033490753337 - OFF#b393219cf2c65c0d4ed122eb2a7ec0f3 Danette Par 16 - danette par 16 - - Danone - 0 - 3033491554612 - 3033491554612 - OFF#923d20a64705986300d527d2b03f040c Danette Mousse - danette mousse - - Danone - 0 - 5410146416415 - 5410146416415 - OFF#251719064ca33c54d5ffc3995265d91c Danette 4 Pots - danette pot - - Danone - 0 - 3033490754426 - 3033490753337 - OFF#681cdee871eda0fd44e181daa3cc1324 ---------------------------------------------------- --------------------------------- final result ----------------------------------- {'prompt': '', 'model': 'mistral-large-2411', 'imagePath': '/home/debian/html/nutritwin/output_llm/679b120051157/capture.jpg', 'intents': ['Identify foods and beverages in an image'], 'solutions': {'nutrition': [{'name': 'Danette', 'normName': ' danette ', 'comment': '', 'normComment': '', 'rank': 0, 'id': 'OFF#f789b0076d9b058a8264aada1b55b736', 'quantity': 'un', 'quantityLem': '1', 'pack': ['GA5.w100'], 'type': 'food', 'gtin': '3033490198640', 'gtinRef': '3033490198640', 'brand': 'Danone', 'time': '', 'event': 'declaration', 'serving': 'GA5-100', 'posiNormName': 0}], 'activity': [], 'response': {}}, 'cputime': 2.637153387069702} ---------------------------------------------------------------------------------- LLM CPU Time: 2.637153387069702