Input path: /home/debian/html/nutritwin/output_llm/68b5efe688bd2/input.json Output path: /home/debian/html/nutritwin/output_llm/68b5efe688bd2/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/68b5efe688bd2/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": "limonade", "quantity": "une bouteille", "brand": "Lorina", "type": "beverage", "event": "unknownEvent" } ] ----------------------------------------------------------------------------- ----------------- Make it compliant ------------------ [ { "name": "limonade", "quantity": "une bouteille", "brand": "Lorina", "type": "beverage", "event": "unknownEvent" } ] ------------------------------------------------------ ------------------------ After simplification ------------------------ [ { "name": "limonade", "quantity": "une bouteille", "brand": "Lorina", "type": "beverage", "event": "unknownEvent" } ] ---------------------------------------------------------------------- --------------------------------- LLM result ----------------------------------- {'response': [{'name': 'limonade', 'quantity': 'une bouteille', 'brand': 'Lorina', 'type': 'beverage', 'event': 'unknownEvent'}], 'cost': 0.0} -------------------------------------------------------------------------------- ----------- result to be analyzed ----------- {'name': 'limonade', 'quantity': 'une bouteille', 'brand': 'Lorina', 'type': 'beverage', '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 '% limonade %' AND V_NormTrademark LIKE '%lorina%' --> CPU time in DB: 0.1214 seconds Word: Limonade - dist: 0.35007694363594055 - row: 4404 Word: Limonade Or - dist: 0.4937593638896942 - row: 52252 Word: Limonade Light - dist: 0.5078749656677246 - row: 3270 Word: Limonade Artisanale - dist: 0.517332911491394 - row: 32663 Word: Limonade au Citron - dist: 0.5188087821006775 - row: 3247 Found embedding word: Limonade 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 = 'Limonade' ------------- Found solution (max 20) -------------- Limonade - limonade - - PepsiCo - 0 - 0048500021323 - 0048500021323 - OFF#d8172cf2086d83b9e05008fb613cdd5d Limonade - limonade - - Biocoop - 0 - 14307706 - 14307706 - OFF#4ab671a228e63124903f46d8a306ecf8 Limonade - limonade - - Lidl - 0 - 20044216 - 20044216 - OFF#aa56e3bffa28426c34615005b68f275b Limonade - limonade - - Carrefour - 0 - 3245390014948 - 3245390014948 - OFF#b6cd7a4c6c8749a6d7bc5da8d61af604 Limonade - limonade - - Les Mousquetaires - 0 - 3250390759102 - 3250390759102 - OFF#68dcbbd56f53f2176b95fea8614dc071 Limonade - limonade - - U - 0 - 3256221134742 - 3256221134742 - OFF#7f5fd855b72a179f4f6e38ab3736c891 Limonade - limonade - - Cora - 0 - 3257980698223 - 3257980698223 - OFF#9a6db7bbc218ba33a501481d9b52e572 Limonade - limonade - - Belle France - 0 - 3258560300048 - 3258560300048 - OFF#5409b6ae9548cbd50bfb058e703ba9bc Limonade - limonade - - Leader Price - 0 - 3263852570016 - 3263852570016 - OFF#786e5f4df0d7164bafe98e84aae37a1c Limonade - limonade - - Monoprix - 0 - 3350031660634 - 3350031660634 - OFF#80008102a6ba2c713fefd0223446136d Limonade - limonade - - Rochambeau - 0 - 3439497014677 - 3439497014677 - OFF#d8e43e78db705c8ce63c3419637ee1c0 Limonade - limonade - - Breizh Cola - 0 - 3484705000072 - 3484705000072 - OFF#b985979e92945904e742d3e15c9cf366 Limonade - limonade - - Auchan - 0 - 3596710089987 - 3596710089987 - OFF#1cd770906468a95474729a9c99f95d15 Limonade - limonade - - group Bel - 0 - 3760023250116 - 3760023250116 - OFF#a4e1b2b263437875c71c1d46bc817302 Limonade - limonade - - Lidl - 0 - 20044916 - 20044216 - OFF#2b382c1dbbd9d169e9bbc2b7e3fd8eaf Limonade - limonade - - Carrefour - 0 - 3560070357819 - 3245390014948 - OFF#3fd3c146cecce145b3fdd49dcb66bc24 Limonade - limonade - - Carrefour - 0 - 3560070791118 - 3245390014948 - OFF#8c04bc7acfc6169113ef283c2d90a518 Limonade - limonade - - Carrefour - 0 - 3245411441982 - 3245390014948 - OFF#c846370ecd72b80558819482e42d8484 Limonade - limonade - - Carrefour - 0 - 3245411901509 - 3245390014948 - OFF#369d6bbd8dad72e32aec92c8bb26c1e8 Limonade - limonade - - U - 0 - 3256228122292 - 3256221134742 - OFF#5db07818182aac9ddfc694625812b97a ---------------------------------------------------- --------------------------------- final result ----------------------------------- {'prompt': '', 'model': 'mistral-large-2411', 'imagePath': '/home/debian/html/nutritwin/output_llm/68b5efe688bd2/capture.jpg', 'intents': ['Identify foods and beverages in an image'], 'solutions': {'nutrition': [{'name': 'Limonade', 'normName': ' limonade ', 'comment': '', 'normComment': '', 'rank': 0, 'id': 'OFF#d8172cf2086d83b9e05008fb613cdd5d', 'quantity': 'une bouteille', 'quantityLem': '1 bouteille', 'pack': ['VX1', 'BI4', 'VA2', 'VA3', 'GOB', 'C3B', 'C33', 'C15', 'SOD', 'VA4', 'VFF'], 'type': 'beverage', 'gtin': '0048500021323', 'gtinRef': '0048500021323', 'brand': 'PepsiCo', 'time': '', 'event': 'unknownEvent', 'serving': 'SOD-100', 'posiNormName': 0}], 'activity': [], 'response': {}}, 'cputime': 2.564481735229492} ---------------------------------------------------------------------------------- LLM CPU Time: 2.564481735229492