Input path: /home/debian/html/nutritwin/output_llm/681f3cc7ed7c7/input.json Output path: /home/debian/html/nutritwin/output_llm/681f3cc7ed7c7/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/681f3cc7ed7c7/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": "fromage frais", "quantity": "un", "type": "food", "brand": "Elle & Vire", "company": "Elle & Vire", "event": "unknownEvent" } ] ----------------------------------------------------------------------------- ----------------- Make it compliant ------------------ [ { "name": "fromage frais", "quantity": "un", "type": "food", "brand": "Elle & Vire", "company": "Elle & Vire", "event": "unknownEvent" } ] ------------------------------------------------------ ------------------------ After simplification ------------------------ [ { "name": "fromage frais", "quantity": "un", "type": "food", "brand": "Elle & Vire", "company": "Elle & Vire", "event": "unknownEvent" } ] ---------------------------------------------------------------------- --------------------------------- LLM result ----------------------------------- {'response': [{'name': 'fromage frais', 'quantity': 'un', 'type': 'food', 'brand': 'Elle & Vire', 'company': 'Elle & Vire', 'event': 'unknownEvent'}], 'cost': 0.0} -------------------------------------------------------------------------------- ----------- result to be analyzed ----------- {'name': 'fromage frais', 'quantity': 'un', 'type': 'food', 'brand': 'Elle & Vire', 'company': 'Elle & Vire', '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 '% fromage frai %' AND V_NormTrademark LIKE '%elle vire%' --> CPU time in DB: 0.1275 seconds Word: Fromage Frais - dist: 0.33853939175605774 - row: 6828 Word: Fromage Frais au Fruits - dist: 0.41957053542137146 - row: 31729 Word: Fromage Frais aux Fruits - dist: 0.41970184445381165 - row: 6867 Word: Fromage Frais à la Fraise - dist: 0.42142927646636963 - row: 54855 Word: Fromage Frais aux Fruis - dist: 0.42192643880844116 - row: 31728 Found embedding word: Fromage Frais 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 = 'Fromage Frais' ------------- Found solution (max 20) -------------- Fromage Frais - fromage frai - - group Bel - 0 - 3073781159660 - 3073781159660 - OFF#f00324b59776e865cdcf4cdaa8093da3 Fromage Frais - fromage frai - - Carrefour - 0 - 3245390020161 - 3245390020161 - OFF#01e530e112da3ec741d99cf2ecede593 Fromage Frais - fromage frai - - Les Mousquetaires - 0 - 3250392055950 - 3250392055950 - OFF#ac8aa0b7ed3bf51ce252c4db0efd9f5f Fromage Frais - fromage frai - - Cora - 0 - 3257980021229 - 3257980021229 - OFF#a397859624ac75bd45b6dc1072b37e21 Fromage Frais - fromage frai - - Malo - 0 - 3278691220015 - 3278691220015 - OFF#17c0fdef1da7ab48ad24e9bc0862783a Fromage Frais - fromage frai - - Biocoop - 0 - 3700640420004 - 3700640420004 - OFF#f500512d9f9ca17795afc9a4453af6f5 Fromage Frais - fromage frai - - Delhaize - 0 - 5400112141403 - 5400112141403 - OFF#3b705747ff7368774b267579c9a03efa Fromage Frais - fromage frai - - Lactalis - 0 - 8000430166057 - 8000430166057 - OFF#1706020b72369b76f24a0db9210b4bfd Fromage Frais - fromage frai - - Carrefour - 0 - 3560071470081 - 3245390020161 - OFF#037e1a0e51d4a922802e32381bb15bca Fromage Frais - fromage frai - - Carrefour - 0 - 3560071242107 - 3245390020161 - OFF#e29d96aed5fa910ff553e04db183a014 Fromage Frais - fromage frai - - Carrefour - 0 - 5400101076297 - 3245390020161 - OFF#eb696494b4f5a86335172d5efdafc7c5 Fromage Frais - fromage frai - - Cora - 0 - 3257980040534 - 3257980021229 - OFF#4f176c20c8f0c2607e45e60a210899c9 Fromage Frais - fromage frai - - Delhaize - 0 - 5400119547970 - 5400112141403 - OFF#367e74b57f4048b62b80079108a69c3d ---------------------------------------------------- --------------------------------- final result ----------------------------------- {'prompt': '', 'model': 'mistral-large-2411', 'imagePath': '/home/debian/html/nutritwin/output_llm/681f3cc7ed7c7/capture.jpg', 'intents': ['Identify foods and beverages in an image'], 'solutions': {'nutrition': [{'name': 'Fromage Frais', 'normName': ' fromage frai ', 'comment': '', 'normComment': '', 'rank': 0, 'id': 'OFF#f00324b59776e865cdcf4cdaa8093da3', 'quantity': 'un', 'quantityLem': '1', 'pack': ['UN2.w20'], 'type': 'food', 'gtin': '3073781159660', 'gtinRef': '3073781159660', 'brand': 'group Bel', 'time': '', 'event': 'unknownEvent', 'serving': 'UN2-10', 'posiNormName': 0}], 'activity': [], 'response': {}}, 'cputime': 2.830010414123535} ---------------------------------------------------------------------------------- LLM CPU Time: 2.830010414123535