Input path: /home/debian/html/nutritwin/output_llm/6804cdaeb506b/input.json Output path: /home/debian/html/nutritwin/output_llm/6804cdaeb506b/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/6804cdaeb506b/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": "chocolat", "quantity": "une boule", "type": "food", "event": "declaration", "brand": "Lindt", "timeOfTheDay": "snacking" } ] ----------------------------------------------------------------------------- ----------------- Make it compliant ------------------ [ { "name": "chocolat", "quantity": "une boule", "type": "food", "event": "declaration", "brand": "Lindt", "timeOfTheDay": "snacking" } ] ------------------------------------------------------ ------------------------ After simplification ------------------------ [ { "name": "chocolat", "quantity": "une boule", "type": "food", "event": "declaration", "brand": "Lindt", "timeOfTheDay": "snacking" } ] ---------------------------------------------------------------------- --------------------------------- LLM result ----------------------------------- {'response': [{'name': 'chocolat', 'quantity': 'une boule', 'type': 'food', 'event': 'declaration', 'brand': 'Lindt', 'timeOfTheDay': 'snacking'}], 'cost': 0.0} -------------------------------------------------------------------------------- ----------- result to be analyzed ----------- {'name': 'chocolat', 'quantity': 'une boule', 'type': 'food', 'event': 'declaration', 'brand': 'Lindt', 'timeOfTheDay': 'snacking'} 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 '% chocolat %' AND V_NormTrademark LIKE '%lindt%' ------------- Found solution (max 20) -------------- Chocolat - chocolat - - Lindt - 4 - 3046920011440 - 3046920011440 - OFF#adcf6c655a866c4f398672e00c7a9a9e Chocolat - chocolat - - Lindt - 0 - 7610400087551 - 3046920011440 - OFF#231409b2a8ceffbce4b568249fd109d0 Chocolat - chocolat - - Lindt - 0 - 3770001938059 - 3046920011440 - OFF#505021980f274f1107ca29d91ddaf2d5 Chocolat - chocolat - - Lindt - 0 - 3046920126632 - 3046920011440 - OFF#93739e1dc2989da5fe2ae8c1e70009eb Chocolat - chocolat - - Lindt - 0 - 3046920071239 - 3046920011440 - OFF#1de2c46d1004d4d41158dc166bbedd5d Chocolat - chocolat - - Lindt - 0 - 3046920025003 - 3046920011440 - OFF#98eb2be017985fff59c7d49a6c8cb601 Chocolat - chocolat - - Lindt - 0 - 8712417101141 - 3046920011440 - OFF#99c2e847e2ae08082af91e1d8d0b53e3 Chocolat - chocolat - - Lindt - 0 - 3046920020992 - 3046920011440 - OFF#d6c2267ce58fcdb7482a67b2384a0c8e Chocolat - chocolat - - Lindt - 0 - 7610400010481 - 3046920011440 - OFF#e5e55851af56a2452972acf30cd8e620 Chocolat - chocolat - - Lindt - 0 - 7610400086417 - 3046920011440 - OFF#9e9b38e99f60bfabc88072342d25a05d Chocolat Noir - chocolat noir - - Lindt - 0 - 3046920013857 - 3046920013857 - OFF#049ecdd33adb74c945c1627bb5699262 Chocolat Noir - chocolat noir - - Lindt - 0 - 7610400082907 - 3046920013857 - OFF#fa9a56e095b35d01b2eeee41818b20a6 Chocolat Noir - chocolat noir - - Lindt - 0 - 8013108699795 - 3046920013857 - OFF#58b9f5a8bba71c057e08a15b541e42e2 Chocolat Lindt - chocolat lindt - - Lindt - 0 - 2000000022171 - 2000000022171 - OFF#d4b4fd9f6cfc2f915e44031bfe3d83c1 Chocolat Blanc - chocolat blanc - - Lindt - 0 - 7610400094474 - 7610400094474 - OFF#a3b5cfa6fe9f147703ab575ca0fa6233 Chocolat au Lait - chocolat lait - - Lindt - 0 - 3046920080088 - 3046920080088 - OFF#5a5c5b1047d9db4374694a46abb89729 Chocolat au Lait - chocolat lait - - Lindt - 0 - 4000539280504 - 3046920080088 - OFF#12da637a203e232d4fd553c452a1b253 Chocolat Tiramisu - chocolat tiramisu - - Lindt - 0 - 3046920040556 - 3046920040556 - OFF#3bff99e44ffa8b6174c7941d7262ca1e Chocolats Assortis - chocolat assorti - - Lindt - 0 - 3046920010344 - 3046920010344 - OFF#325ebfa03f9e1acc0ea0d2655e598d08 Chocolat 70% Cacao - chocolat 70% cacao - - Lindt - 0 - 7610400077439 - 7610400077439 - OFF#363544c1624d2c7be8f05f98c3c7737a ---------------------------------------------------- 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 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/6804cdaeb506b/capture.jpg', 'intents': ['Identify foods and beverages in an image'], 'solutions': {'nutrition': [{'name': 'Chocolat', 'normName': ' chocolat ', 'comment': '', 'normComment': '', 'rank': 4, 'id': 'OFF#adcf6c655a866c4f398672e00c7a9a9e', 'quantity': 'une boule', 'quantityLem': '1 boule', 'pack': ['CHO.w7'], 'type': 'food', 'gtin': '3046920011440', 'gtinRef': '3046920011440', 'brand': 'Lindt', 'time': 'snacking', 'event': 'declaration', 'serving': '', 'posiNormName': 0}], 'activity': [], 'response': {}}, 'cputime': 2.759002447128296} ---------------------------------------------------------------------------------- LLM CPU Time: 2.759002447128296