Input path: /home/debian/html/nutritwin/output_llm/688f5bc8e4777/input.json Output path: /home/debian/html/nutritwin/output_llm/688f5bc8e4777/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/688f5bc8e4777/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": "skyr", "quantity": "un pot", "type": "food", "brand": "Délisse", "event": "unknown" } ] ----------------------------------------------------------------------------- ----------------- Make it compliant ------------------ [ { "name": "skyr", "quantity": "un pot", "type": "food", "brand": "Délisse", "event": "unknown" } ] ------------------------------------------------------ ------------------------ After simplification ------------------------ [ { "name": "skyr", "quantity": "un pot", "type": "food", "brand": "D\u00e9lisse", "event": "unknown" } ] ---------------------------------------------------------------------- --------------------------------- LLM result ----------------------------------- {'response': [{'name': 'skyr', 'quantity': 'un pot', 'type': 'food', 'brand': 'Délisse', 'event': 'unknown'}], 'cost': 0.0} -------------------------------------------------------------------------------- ----------- result to be analyzed ----------- {'name': 'skyr', 'quantity': 'un pot', 'type': 'food', 'brand': 'Délisse', 'event': 'unknown'} 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 '% skyr %' AND V_NormTrademark LIKE '%delisse%' --> CPU time in DB: 0.1166 seconds Word: Skyr - dist: 0.4138643741607666 - row: 4458 Word: Skyr To Go - dist: 0.5772335529327393 - row: 53571 Word: Skyr Nature - dist: 0.5898911952972412 - row: 5564 Word: Skyr Vanilla - dist: 0.6076709628105164 - row: 13492 Word: Skyr Light Free - dist: 0.624891459941864 - row: 5287 Found embedding word: Skyr 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 = 'Skyr' ------------- Found solution (max 20) -------------- Skyr - skyr - - Danone - 0 - 00000000000026772226 - 00000000000026772226 - OFF#cc2947e747670c68b2a88eb33ca48481 Skyr - skyr - - U - 0 - 3256229477162 - 3256229477162 - OFF#dde60edcac6d7eff5195d551bf9a8124 Skyr - skyr - - Yoplait - 0 - 3329770073265 - 3329770073265 - OFF#ea91c3646d980f860ebfb9fe3824772f Skyr - skyr - - Lidl - 0 - 4056489013921 - 4056489013921 - OFF#ed3a58ca7e4ea7b8c265f8584bdf5c0c Skyr - skyr - - Carrefour - 0 - 5400101062207 - 5400101062207 - OFF#5140a3e3c45e86177b6fff16bdb9e17c Skyr - skyr - - Delhaize - 0 - 5400119538442 - 5400119538442 - OFF#6e1896ebb62d881b087c351b7d5ed3e1 Skyr - skyr - - Danone - 0 - 44244743 - 00000000000026772226 - OFF#33bf3d0445cbab2000a2d1acf4bb80ce Skyr - skyr - - Danone - 0 - 3033490004743 - 00000000000026772226 - OFF#4e2f5df02037d4865338f6ac09db5f27 Skyr - skyr - - Danone - 0 - 3033491454080 - 00000000000026772226 - OFF#0187f86d1e42297d7b2dedbe150a10d8 Skyr - skyr - - Danone - 0 - 10330791 - 00000000000026772226 - OFF#e25a67260ef68c8bbc282734d131095f Skyr - skyr - - Danone - 0 - 03414569 - 00000000000026772226 - OFF#7233f418587784a39fc3d0d3da2f59b6 Skyr - skyr - - Danone - 0 - 2033496445756 - 00000000000026772226 - OFF#82752b0266082d9d701cadcedc5e793f Skyr - skyr - - Danone - 0 - 0034361454080 - 00000000000026772226 - OFF#2c73bfd38f6ae207fcde4bf8fa94256e Skyr - skyr - - Danone - 0 - 3033491704642 - 00000000000026772226 - OFF#92fbe50fc69ec708f06886fb08ed94ec Skyr - skyr - - Yoplait - 0 - 3329770085169 - 3329770073265 - OFF#e87e653d4d282822f9b96ded937aa7bb Skyr - skyr - - Yoplait - 0 - 3329770084490 - 3329770073265 - OFF#903352582bbc76524db307914781e11f Skyr - skyr - - Yoplait - 0 - 3329770082359 - 3329770073265 - OFF#445b851bda54f172398bd3a7751bc2b1 Skyr - skyr - - Yoplait - 0 - 3329770077003 - 3329770073265 - OFF#1275e77e3c46e9853ef4209b20cb6383 Skyr - skyr - - Carrefour - 0 - 5400101078673 - 5400101062207 - OFF#f86d7fbb98e69a65a98bb49cf194a1c5 ---------------------------------------------------- --------------------------------- final result ----------------------------------- {'prompt': '', 'model': 'mistral-large-2411', 'imagePath': '/home/debian/html/nutritwin/output_llm/688f5bc8e4777/capture.jpg', 'intents': ['Identify foods and beverages in an image'], 'solutions': {'nutrition': [{'name': 'Skyr', 'normName': ' skyr ', 'comment': '', 'normComment': '', 'rank': 0, 'id': 'OFF#cc2947e747670c68b2a88eb33ca48481', 'quantity': 'un pot', 'quantityLem': '1 pot', 'pack': ['YA5.w200', 'AAD.w200'], 'type': 'food', 'gtin': '00000000000026772226', 'gtinRef': '00000000000026772226', 'brand': 'Danone', 'time': '', 'event': 'unknown', 'serving': 'YA5-100', 'posiNormName': 0}], 'activity': [], 'response': {}}, 'cputime': 1.683966875076294} ---------------------------------------------------------------------------------- LLM CPU Time: 1.683966875076294