Input path: /home/debian/html/nutritwin/output_llm/68bde5481c91c/input.json Output path: /home/debian/html/nutritwin/output_llm/68bde5481c91c/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/68bde5481c91c/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": "un", "type": "food", "timeOfTheDay": "snacking", "brand": "Pim's", "event": "declaration" }, { "name": "orange", "quantity": "une tranche", "type": "food", "timeOfTheDay": "snacking", "event": "declaration" } ] ----------------------------------------------------------------------------- ----------------- Make it compliant ------------------ [ { "name": "chocolat", "quantity": "un", "type": "food", "timeOfTheDay": "snacking", "brand": "Pim's", "event": "declaration" }, { "name": "orange", "quantity": "une tranche", "type": "food", "timeOfTheDay": "snacking", "event": "declaration" } ] ------------------------------------------------------ ------------------------ After simplification ------------------------ [ { "name": "chocolat", "quantity": "un", "type": "food", "timeOfTheDay": "snacking", "brand": "Pim's", "event": "declaration" }, { "name": "orange", "quantity": "une tranche", "type": "food", "timeOfTheDay": "snacking", "event": "declaration" } ] ---------------------------------------------------------------------- --------------------------------- LLM result ----------------------------------- {'response': [{'name': 'chocolat', 'quantity': 'un', 'type': 'food', 'timeOfTheDay': 'snacking', 'brand': "Pim's", 'event': 'declaration'}, {'name': 'orange', 'quantity': 'une tranche', 'type': 'food', 'timeOfTheDay': 'snacking', 'event': 'declaration'}], 'cost': 0.0} -------------------------------------------------------------------------------- ----------- result to be analyzed ----------- {'name': 'chocolat', 'quantity': 'un', 'type': 'food', 'timeOfTheDay': 'snacking', 'brand': "Pim's", '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 '% chocolat %' AND V_NormTrademark LIKE '%pim s%' --> CPU time in DB: 0.1366 seconds Word: Chocolat - dist: 0.4263405203819275 - row: 3609 Word: Le Chocolat - dist: 0.4895692765712738 - row: 16413 Word: Chocolats - dist: 0.5121781229972839 - row: 51416 Word: Chocolat Dessert - dist: 0.5590576529502869 - row: 40816 Word: Chocolat Cake - dist: 0.5633316040039062 - row: 53198 Found embedding word: Chocolat Second try (embedded): 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_Name = 'Chocolat' ------------- Found solution (max 20) -------------- Chocolat - chocolat - - Lidl - 18 - 20807061 - 20807061 - OFF#44788ca73c28bc9fb1e68a9f21bf19fa Chocolat - chocolat - - Lindt - 4 - 3046920011440 - 3046920011440 - OFF#adcf6c655a866c4f398672e00c7a9a9e Chocolat - chocolat - - Mondelez International - 0 - 3045140105564 - 3045140105564 - OFF#107009c3e1aed6a7bc1b1a76685a2ad1 Chocolat - chocolat - - Casino - 0 - 3222476423931 - 3222476423931 - OFF#77f8e34e5d312fbefabf30f8527b78e7 Chocolat - chocolat - - U - 0 - 3256225738397 - 3256225738397 - OFF#88e87a75247d9b995e30139064d66ceb Chocolat - chocolat - - Cora - 0 - 3257980632005 - 3257980632005 - OFF#b683a87202e86470b337c6847d980d65 Chocolat - chocolat - - Moulin des Moines - 0 - 3347437001369 - 3347437001369 - OFF#b380ef62b824fe6f46b0b6d4de20c88e Chocolat - chocolat - - Leclerc - 0 - 3450970001274 - 3450970001274 - OFF#ceed89e021c7e186a8ca67c01f3a8b56 Chocolat - chocolat - - Auchan - 0 - 3596710347339 - 3596710347339 - OFF#3adb22e03d28bd6a36539ff6dde8ae32 Chocolat - chocolat - - Suchard - 0 - 3664346309202 - 3664346309202 - OFF#54bd603da7c4a394eac0c4b75ca1b11d Chocolat - chocolat - - Poulain - 0 - 3664346317115 - 3664346317115 - OFF#748cd12f9002f7d4846c058ff5814821 Chocolat - chocolat - - Leonidas - 0 - 5420006320325 - 5420006320325 - OFF#1977195fbf0f949a7f4eb49f1104da8c Chocolat - chocolat - - Lidl - 0 - 4056489182788 - 20807061 - OFF#92950981ae0a1b0a7de12ac1dc9c1d4e Chocolat - chocolat - - Mondelez International - 0 - 7622201766559 - 3045140105564 - OFF#23312519ffb2ca2c4ef12ae2c0172655 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 ---------------------------------------------------- ----------- result to be analyzed ----------- {'name': 'orange', 'quantity': 'une tranche', 'type': 'food', 'timeOfTheDay': 'snacking', '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 '% orange %' AND (V_NormTrademark = '' OR V_NormTrademark IS NULL) ------------- Found solution (max 20) -------------- Orange - orange - pulpe, crue - - 19789 - - - CIQ#a84ec3c1b9bc46c10b639fa15eeef5f4 Orange Givrée - orange givree - - - 31 - - - KCA#78bd77a68826904b6b891043ddcc9d5a Orange Pressée - orange pressee - - - 3137 - - - KCA#d951c9057cfe647b69b7f30181322ad1 Jus d'Orange - ju orange - - - 52983 - - - KCA#da7a1f81a8cd82dbbbbbedf56a167258 Jus d'Orange - ju orange - pur jus - - 0 - - - CIQ#a4328be11b7e0fb0c4474532724cf38f Jus d'Orange - ju orange - à base de concentré - - 0 - - - CIQ#72928c242781a6ee15266175037b3fb8 Jus d'Orange Pasteurisé - ju orange pasteurise - - - 44 - - - KCA#8dc9e7ac955777e77122f7bd97350613 Jus d'Orange et Gingembre - ju orange gingembre - - - 31 - - - KCA#ac517779183d5fdeff117cfe8eb4be98 Jus d'Orange, Mangue et Fraise - ju orange mangue fraise - - - 60 - - - KCA#12cc18043b0813e5110bb808101edc8e Jus Orange Pamplemousse Pressés - ju orange pamplemousse presse - - - 517 - - - KCA#e606e760b12355e0cc070fbf069b4261 Jus d'Orange, Carotte et Céleri - ju orange carotte celeri - - - 117 - - - KCA#ba4cb33c47a671db82eeaad9ddd5c63e Jus d'Orange, Gingembre et Ananas - ju orange gingembre anana - - - 6 - - - KCA#e2edd8bdeebd69177ece6caee7f071d8 Jus d'Orange, Carotte et Gingembre - ju orange carotte gingembre - - - 73 - - - KCA#0c209cbc5beac761ddcf7ea316e5b29e Jus d'Orange, Ananas et Glace au Melon - ju orange anana glace melon - - - 21 - - - KCA#3e4e71456576da23059304f3eba50c9c Gin Orange - gin orange - - - 11 - - - KCA#69422eafcd803a4841e22ba7a24dbeaf Vodka Orange - vodka orange - - - 303 - - - KCA#afee6734db3389d9a53ba62d8e345e8e Tarte à l'Orange - tarte orange - à l'orange - - 0 - - - KCA#8cf553da1e0c3135218833739419ea98 Salade d'Oranges - salade orange - - - 71 - - - KCA#a7fe61d6cb0d6c12eba4ca95e0f74781 Dorade à l'Orange - dorade orange - - - 76 - - - KCA#f37ceb94004879aa0221259fea9ea8bd Canard à l'Orange - canard orange - - - 33 - - - KCA#42651abfdc29355ec0cf7e410b802f1a ---------------------------------------------------- ERROR: no solution for picto in the first solution --------------------------------- final result ----------------------------------- {'prompt': '', 'model': 'mistral-large-2411', 'imagePath': '/home/debian/html/nutritwin/output_llm/68bde5481c91c/capture.jpg', 'intents': ['Identify foods and beverages in an image'], 'solutions': {'nutrition': [{'name': 'Chocolat', 'normName': ' chocolat ', 'comment': '', 'normComment': '', 'rank': 18, 'id': 'OFF#44788ca73c28bc9fb1e68a9f21bf19fa', 'quantity': 'un', 'quantityLem': '1', 'pack': ['UN2.w21'], 'type': 'food', 'gtin': '20807061', 'gtinRef': '20807061', 'brand': 'Lidl', 'time': 'snacking', 'event': 'declaration', 'serving': 'UN2-10', 'posiNormName': 0}, {'name': 'Orange', 'normName': ' orange ', 'comment': 'pulpe, crue', 'normComment': ' pulpe crue ', 'rank': 19789, 'id': 'CIQ#a84ec3c1b9bc46c10b639fa15eeef5f4', 'quantity': 'une tranche', 'quantityLem': '1 tranche', 'pack': ['ORA.w200'], 'type': 'food', 'gtin': '', 'gtinRef': '', 'brand': '', 'time': 'snacking', 'event': 'declaration', 'serving': '', 'posiNormName': 0}], 'activity': [], 'response': {}}, 'cputime': 3.4404873847961426} ---------------------------------------------------------------------------------- LLM CPU Time: 3.4404873847961426