Input path: /home/debian/html/nutritwin/output_llm/67f4fe006095f/input.json Output path: /home/debian/html/nutritwin/output_llm/67f4fe006095f/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/67f4fe006095f/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": "lentilles", "quantity": "400 grammes", "cookingMethod": "préparées", "type": "food", "event": "declaration", "brand": "Cidacos" }, { "name": "eau", "quantity": "un verre", "type": "beverage", "event": "declaration" } ] ----------------------------------------------------------------------------- ----------------- Make it compliant ------------------ [ { "name": "lentilles", "quantity": "400 grammes", "cookingMethod": "préparées", "type": "food", "event": "declaration", "brand": "Cidacos" }, { "name": "eau", "quantity": "un verre", "type": "beverage", "event": "declaration" } ] ------------------------------------------------------ ------------------------ After simplification ------------------------ [ { "name": "lentilles", "quantity": "400 grammes", "cookingMethod": "pr\u00e9par\u00e9es", "type": "food", "event": "declaration", "brand": "Cidacos" }, { "name": "eau", "quantity": "un verre", "type": "beverage", "event": "declaration" } ] ---------------------------------------------------------------------- --------------------------------- LLM result ----------------------------------- {'response': [{'name': 'lentilles', 'quantity': '400 grammes', 'cookingMethod': 'préparées', 'type': 'food', 'event': 'declaration', 'brand': 'Cidacos'}, {'name': 'eau', 'quantity': 'un verre', 'type': 'beverage', 'event': 'declaration'}], 'cost': 0.0} -------------------------------------------------------------------------------- ----------- result to be analyzed ----------- {'name': 'lentilles', 'quantity': '400 grammes', 'cookingMethod': 'préparées', 'type': 'food', 'event': 'declaration', 'brand': 'Cidacos'} 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 '% lentille %' AND V_NormTrademark LIKE '%cidacos%' --> CPU time in DB: 0.1419 seconds Word: Lentilles - dist: 0.30558013916015625 - row: 4967 Word: Lentille - dist: 0.4101356565952301 - row: 4178 Word: Les Lentilles - dist: 0.45534202456474304 - row: 14650 Word: Lentilles BIO - dist: 0.48225370049476624 - row: 44924 Word: Lentilles Vertes - dist: 0.49803265929222107 - row: 4975 Found embedding word: Lentilles 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 = 'Lentilles' ------------- Found solution (max 20) -------------- Lentilles - lentille - - Auchan - 0 - 13339346 - 13339346 - OFF#7096c95612426cddc43bad93710c0977 Lentilles - lentille - - Aldi - 0 - 26044408 - 26044408 - OFF#9f8e44b85bfc226827a34a6e6cb927fe Lentilles - lentille - - D'Aucy - 0 - 3017800010518 - 3017800010518 - OFF#70a9d43ade4e4aefe8344b9708f8860f Lentilles - lentille - - Bonduelle - 0 - 3083680995085 - 3083680995085 - OFF#3372291b99ccac7e211cf646d8d2ba3f Lentilles - lentille - - Monoprix - 0 - 3112940851899 - 3112940851899 - OFF#83c7e15ef9f607575230e2c3363d20fc Lentilles - lentille - - Casino - 0 - 3222471005293 - 3222471005293 - OFF#2e1ac54c4b0884e0ee6a672286a27c99 Lentilles - lentille - - U - 0 - 3256220280167 - 3256220280167 - OFF#d36dcc74b07a49601a0d9f97d2f7812d Lentilles - lentille - - Leader Price - 0 - 3263851355812 - 3263851355812 - OFF#9e7825149742fa4ca374d3b6175d7ff5 Lentilles - lentille - - Rochambeau - 0 - 3439495127959 - 3439495127959 - OFF#de08e686c7697590b93b797502fa1fed Lentilles - lentille - - Carrefour - 0 - 3560070329441 - 3560070329441 - OFF#376561c4313cb2b232d29fb02b0e3de0 Lentilles - lentille - - Delhaize - 0 - 5400113610922 - 5400113610922 - OFF#b68e81d0aa9379ec803d7f1d72edc8dd Lentilles - lentille - - Auchan - 0 - 79993333 - 13339346 - OFF#f946f351111356655a7bf29f4081adc0 Lentilles - lentille - - Auchan - 0 - 3596710473724 - 13339346 - OFF#dbc862a55cf8ee57ef8a3a57454b8ffd Lentilles - lentille - - Auchan - 0 - 40921525 - 13339346 - OFF#277dde51370401baf7cd97b96977a07e Lentilles - lentille - - Auchan - 0 - 3596710526000 - 13339346 - OFF#165864484956e762ff4e761374ae532c Lentilles - lentille - - Auchan - 0 - 3596710511105 - 13339346 - OFF#f9234b5b903a6447d7c5f2e102bf93be Lentilles - lentille - - Auchan - 0 - 3596710389964 - 13339346 - OFF#a4749167d72e237fa5f5b63a646ec812 Lentilles - lentille - - Auchan - 0 - 3254560034709 - 13339346 - OFF#bd9d06a9f06bc5412a0bcf12dbb44d66 Lentilles - lentille - - Auchan - 0 - 3596710491216 - 13339346 - OFF#2c86f657d06621e787832c181dfab4d0 Lentilles - lentille - - Auchan - 0 - 3596710509133 - 13339346 - OFF#d6c13f6e926d51884da54d712eb6a5ca ---------------------------------------------------- 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 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 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 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 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 ----------- result to be analyzed ----------- {'name': 'eau', 'quantity': 'un verre', 'type': 'beverage', '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 '% eau %' AND (V_NormTrademark = '' OR V_NormTrademark IS NULL) ------------- Found solution (max 20) -------------- Eau - eau - - - 10064 - - - KCA#08cfe774cbf7476b1e582734c7082ecd Eau de Vie - eau de vie - - - 210 - - - CIQ#2397ddba68eefec7e38e3a061b6060e3 Eau de Coco - eau de coco - - - 574 - - - CIQ#4f6cfd4687e4da85c9063e194dd3113b Eau Minérale - eau minerale - - - 0 - - - CIQ#682a311be3fc15a20a88c168408e5304 Eau Minérale - eau minerale - aliment moyen - - 160 - - - KCA#69addfd353e07f633ee05c6be8ac5d4d Eau Minérale - eau minerale - plate, aliment moyen - - 18 - - - CIQ#9f35a4198a700eac62fe4d1dc426f1a4 Eau Minérale - eau minerale - gazeuse, aliment moyen - - 28 - - - CIQ#38da155cfd970d21ba9f4b87294b96df Eau Minérale - eau minerale - ou de source aromatisée agrumes - - 33 - - - KCA#47ee70f086c3080428426febc2426e8c Eau Minérale - eau minerale - ou de source aromatisée, arôme autre qu'agrumes - - 36 - - - KCA#0daeef02b69e5526427bc855f1ec3111 Eau Minérale - eau minerale - embouteillée, faiblement minéralisée, aliment moyen - - 0 - - - CIQ#a8b887f21f002cd8ddbda99766ee5ec4 Eau de Source - eau de source - embouteillée, aliment moyen - - 0 - - - CIQ#b6c1ba3e6cb4c788d63711a9b869730b Eau du Robinet - eau robinet - - - 273 - - - CIQ#4c4a29ce4ec63b6cfc6bc3914ccf7056 Eau Minérale Dax - eau minerale da - embouteillée, non gazeuse, moyennement minéralisée, Dax, 40 - - 0 - - - CIQ#a07a880ef627fa44150fe5583484549d Eau de Vie de Vin - eau de vie de vin - type armagnac, cognac - - 0 - - - CIQ#c0440021ea15aa2abf11853bbd2191a4 Eau Minérale Néro - eau minerale nero - embouteillée, non gazeuse, faiblement minéralisée, Grèce - - 0 - - - CIQ#8ab34da104cb5b744e0ad6eaece161a6 Eau Minérale Avra - eau minerale avra - embouteillée, non gazeuse, faiblement minéralisée, Grèce - - 0 - - - CIQ#b0465b7ee2f045df840aac281b388253 Eau Minérale Luso - eau minerale luso - embouteillée, non gazeuse, très faiblement minéralisée, Portugal - - 0 - - - CIQ#45d467ce96aa14e71c62e6ca943f5621 Eau Minérale Eden - eau minerale eden - La Goa, embouteillée, non gazeuse, faiblement minéralisée, Suisse - - 0 - - - CIQ#341195c07e8f951269157ecad800778a Eau Minérale Ogeu - eau minerale ogeu - embouteillée, gazeuse, faiblement minéralisée, Ogeu-les-Bains, 64 - - 0 - - - CIQ#14fc742b6db6af7dce1a08288d62ddf6 Eau Minérale Vals - eau minerale val - embouteillée, gazeuse, moyennement minéralisée, Vals-les-Bains, 07 - - 0 - - - CIQ#11be70594fa1e46c35dca065d17b5ca6 ---------------------------------------------------- --------------------------------- final result ----------------------------------- {'prompt': '', 'model': 'mistral-large-2411', 'imagePath': '/home/debian/html/nutritwin/output_llm/67f4fe006095f/capture.jpg', 'intents': ['Identify foods and beverages in an image'], 'solutions': {'nutrition': [{'name': 'Lentilles', 'normName': ' lentille ', 'comment': '', 'normComment': '', 'rank': 0, 'id': 'OFF#7096c95612426cddc43bad93710c0977', 'quantity': '400 grammes', 'quantityLem': '400 gramme', 'pack': ['BOB.w30', 'BOL.w50'], 'type': 'food', 'gtin': '13339346', 'gtinRef': '13339346', 'brand': 'Auchan', 'time': '', 'event': 'declaration', 'serving': '', 'posiNormName': 0}, {'name': 'Eau', 'normName': ' eau ', 'comment': '', 'normComment': '', 'rank': 10064, 'id': 'KCA#08cfe774cbf7476b1e582734c7082ecd', 'quantity': 'un verre', 'quantityLem': '1 verre', 'pack': ['VAE', 'VX1', 'VA2', 'GOB', 'VA4', 'VA4', 'VA3'], 'type': 'beverage', 'gtin': '', 'gtinRef': '', 'brand': '', 'time': '', 'event': 'declaration', 'serving': 'VA2-100', 'posiNormName': 0}], 'activity': [], 'response': {}}, 'cputime': 5.259685039520264} ---------------------------------------------------------------------------------- LLM CPU Time: 5.259685039520264