Input path: /home/debian/html/nutritwin/output_llm/67f627e2c8dca/input.json Output path: /home/debian/html/nutritwin/output_llm/67f627e2c8dca/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/67f627e2c8dca/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": "bonbons", "quantity": "une boîte", "type": "food", "brand": "Haribo", "event": "unknownEvent" } ] ----------------------------------------------------------------------------- ----------------- Make it compliant ------------------ [ { "name": "bonbons", "quantity": "une boîte", "type": "food", "brand": "Haribo", "event": "unknownEvent" } ] ------------------------------------------------------ ------------------------ After simplification ------------------------ [ { "name": "bonbons", "quantity": "une bo\u00eete", "type": "food", "brand": "Haribo", "event": "unknownEvent" } ] ---------------------------------------------------------------------- --------------------------------- LLM result ----------------------------------- {'response': [{'name': 'bonbons', 'quantity': 'une boîte', 'type': 'food', 'brand': 'Haribo', 'event': 'unknownEvent'}], 'cost': 0.0} -------------------------------------------------------------------------------- ----------- result to be analyzed ----------- {'name': 'bonbons', 'quantity': 'une boîte', 'type': 'food', 'brand': 'Haribo', 'event': 'unknownEvent'} 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 '% bonbon %' AND V_NormTrademark LIKE '%haribo%' ------------- Found solution (max 20) -------------- Bonbon - bonbon - - Haribo - 0 - 1103734034774 - 1103734034774 - OFF#89f70f09a0d5b4d344d6321333c9b380 Bonbon - bonbon - - Haribo - 0 - 8691216092938 - 1103734034774 - OFF#74865193bb2df56a02c3d0bdc706552d Bonbon - bonbon - - Haribo - 0 - 8691216016903 - 1103734034774 - OFF#cb1b05008367e0ea423a0f337ac7d436 Bonbon - bonbon - - Haribo - 0 - 3103220039533 - 1103734034774 - OFF#b9142fc0509ca3b5ee4ce3b7538e1208 Bonbon - bonbon - - Haribo - 0 - 3103220041086 - 1103734034774 - OFF#d597e4e5e2567a8ec190caaf8cc5204d Bonbon - bonbon - - Haribo - 0 - 3103220062166 - 1103734034774 - OFF#1b2be107f829d2de7e742333f54b08ad Bonbon - bonbon - - Haribo - 0 - 46890719 - 1103734034774 - OFF#7081a40a2312ea1aacf32baafd138b18 Bonbons Maoam - bonbon maoam - - Haribo - 0 - 3103220044025 - 3103220044025 - OFF#0bbe3729e1004e0a908fc4d6ef796029 Bonbon Haribo - bonbon haribo - - Haribo - 0 - 3103220063231 - 3103220063231 - OFF#5e5a08ab0966f7389a3b9e1209cfd139 Bonbons Banan'S - bonbon banan - - Haribo - 0 - 3103220040430 - 3103220040430 - OFF#d452b96965e7e756a46db0fbd1458edf Bonbons Starmix - bonbon starmi - - Haribo - 0 - 3103220042533 - 3103220042533 - OFF#344cb4a49a79d1a718e951cd332f504a Bonbons Dragibus - bonbon dragibu - - Haribo - 0 - 3103220040799 - 3103220040799 - OFF#22bf6dd1322b705356740e58a8878266 Bonbons Dragiween - bonbon dragiween - - Haribo - 0 - 3103220036341 - 3103220036341 - OFF#81fa6a6179ce2abf34cb7647157eda1c Bonbons Happy' Mix - bonbon happy mi - - Haribo - 0 - 3103220040812 - 3103220040812 - OFF#3f0d25d7843269fc616457c4fbae5ecc Bonbon A la Menthe - bonbon menthe - - Haribo - 0 - 8426617066604 - 8426617066604 - OFF#dbadf1d0df7f58f01cf77cc35b623e63 Bonbon Haribo Croco - bonbon haribo croco - - Haribo - 0 - 3103220030462 - 3103220030462 - OFF#a113cfbc4d2773794a1e4e9f12f98c0f Bonbons Schtroumpfs - bonbon schtroumpf - - Haribo - 0 - 4001686333709 - 4001686333709 - OFF#0788da1b0e685e2753d99e0b7cb00546 Bonbons Pasta Flagga - bonbon pasta flagga - - Haribo - 0 - 4001686364406 - 4001686364406 - OFF#99568f3e18baa2518d85a94b56a88abd Bonbon Haribo Lampions - bonbon haribo lampion - - Haribo - 0 - 3103220020609 - 3103220020609 - OFF#af62ec5d6e2116c9cc3edc9725f93c87 Bonbons Chamallows 300 - bonbon chamallow 300 - - Haribo - 0 - 3103220035993 - 3103220035993 - OFF#b6cb93bb1f124782c09f077bc0da46c3 ---------------------------------------------------- ERROR: no solution for picto in the first solution ERROR: no solution for picto in the first solution ERROR: no solution for picto in the first solution ERROR: no solution for picto in the first solution ERROR: no solution for picto in the first solution ERROR: no solution for picto in the first solution ERROR: no solution for picto in the first solution --------------------------------- final result ----------------------------------- {'prompt': '', 'model': 'mistral-large-2411', 'imagePath': '/home/debian/html/nutritwin/output_llm/67f627e2c8dca/capture.jpg', 'intents': ['Identify foods and beverages in an image'], 'solutions': {'nutrition': [{'name': 'Bonbon', 'normName': ' bonbon ', 'comment': '', 'normComment': '', 'rank': 0, 'id': 'OFF#89f70f09a0d5b4d344d6321333c9b380', 'quantity': 'une boîte', 'quantityLem': '1 boite', 'pack': ['UN2.w21'], 'type': 'food', 'gtin': '1103734034774', 'gtinRef': '1103734034774', 'brand': 'Haribo', 'time': '', 'event': 'unknownEvent', 'serving': '', 'posiNormName': 0}], 'activity': [], 'response': {}}, 'cputime': 2.671499490737915} ---------------------------------------------------------------------------------- LLM CPU Time: 2.671499490737915