Input path: /home/debian/html/nutritwin/output_llm/68fcbc2a58134/input.json Output path: /home/debian/html/nutritwin/output_llm/68fcbc2a58134/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/68fcbc2a58134/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 de chèvre", "quantity": "160 grammes", "type": "food", "event": "declaration", "brand": "Le Sylvaner", "company": "Eugène Chèvre" } ] ----------------------------------------------------------------------------- ----------------- Make it compliant ------------------ [ { "name": "fromage de chèvre", "quantity": "160 grammes", "type": "food", "event": "declaration", "brand": "Le Sylvaner", "company": "Eugène Chèvre" } ] ------------------------------------------------------ ------------------------ After simplification ------------------------ [ { "name": "fromage de ch\u00e8vre", "quantity": "160 grammes", "type": "food", "event": "declaration", "brand": "Le Sylvaner", "company": "Eug\u00e8ne Ch\u00e8vre" } ] ---------------------------------------------------------------------- --------------------------------- LLM result ----------------------------------- {'response': [{'name': 'fromage de chèvre', 'quantity': '160 grammes', 'type': 'food', 'event': 'declaration', 'brand': 'Le Sylvaner', 'company': 'Eugène Chèvre'}], 'cost': 0.0} -------------------------------------------------------------------------------- ----------- result to be analyzed ----------- {'name': 'fromage de chèvre', 'quantity': '160 grammes', 'type': 'food', 'event': 'declaration', 'brand': 'Le Sylvaner', 'company': 'Eugène Chèvre'} 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 de chevre %' AND V_NormTrademark LIKE '%sylvaner%' --> CPU time in DB: 0.1128 seconds Word: Fromage de Chèvre - dist: 0.3409397602081299 - row: 4129 Word: Fromage de Chevre - dist: 0.3760477900505066 - row: 34550 Word: Fromage de Chévre - dist: 0.37748101353645325 - row: 56432 Word: Fromage au Chèvre - dist: 0.38337719440460205 - row: 18039 Word: Fromage Chèvre - dist: 0.3960963785648346 - row: 44112 Found embedding word: Fromage de Chèvre 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 de Chèvre' ------------- Found solution (max 20) -------------- Fromage de Chèvre - fromage de chevre - - - 4537 - - - KCA#87a40b8f006dcb11aafd4e97014ed3f4 Fromage de Chèvre - fromage de chevre - - Leclerc - 0 - 0203038029788 - 0203038029788 - OFF#055329f31f9a936fdbcd4c9f614d8925 Fromage de Chèvre - fromage de chevre - - Lidl - 0 - 20195595 - 20195595 - OFF#296fffbeb1a9e0658b4434fcfcf8d276 Fromage de Chèvre - fromage de chevre - - Soignon - 0 - 2217820878377 - 2217820878377 - OFF#957d5b7f620e2e114e962f8cb5928920 Fromage de Chèvre - fromage de chevre - - Casino - 0 - 3222471153819 - 3222471153819 - OFF#b41aa39d4aa082b11558c824e7ed5984 Fromage de Chèvre - fromage de chevre - - Carrefour - 0 - 3245390046222 - 3245390046222 - OFF#8c4825ff37c88d352b08b31029350a90 Fromage de Chèvre - fromage de chevre - - Auchan - 0 - 3254560321465 - 3254560321465 - OFF#3b2096ab52abe0426392cb44cd6681d8 Fromage de Chèvre - fromage de chevre - - Cora - 0 - 3257980060761 - 3257980060761 - OFF#93f644643c5869824be86d213649bcf1 Fromage de Chèvre - fromage de chevre - - Belle France - 0 - 3258561430713 - 3258561430713 - OFF#f6d7cfec66240713b110299562b55096 Fromage de Chèvre - fromage de chevre - - Franprix - 0 - 3263856411414 - 3263856411414 - OFF#c8c146cefecb77ddc40735531235df4b Fromage de Chèvre - fromage de chevre - - Leader Price - 0 - 3263859370411 - 3263859370411 - OFF#f72a7724a03dce117d3e6c6a49a4767c Fromage de Chèvre - fromage de chevre - - Compagnie des fromages & RichesMonts - 0 - 3272770093286 - 3272770093286 - OFF#92b60341d7c3e61cb85865020a8a48ef Fromage de Chèvre - fromage de chevre - - Monoprix - 0 - 3350030102593 - 3350030102593 - OFF#30db3b3d0d5a4807a26bcfe8373b50a6 Fromage de Chèvre - fromage de chevre - - Rochambeau - 0 - 3439495901412 - 3439495901412 - OFF#61083fe632fa1835d405ccfb1e19d350 Fromage de Chèvre - fromage de chevre - - Bio Village - 0 - 3564707140126 - 3564707140126 - OFF#69a3a69f1c66cada9f46e5d09777a11d Fromage de Chèvre - fromage de chevre - - Delhaize - 0 - 5400119535083 - 5400119535083 - OFF#eeb710242d7b59cfd6aefeac245c4f1e Fromage de Chèvre - fromage de chevre - - U - 0 - 64633558 - 64633558 - OFF#2e044d04a7d7728658032529355a4de9 Fromage de Chèvre - fromage de chevre - - Lidl - 0 - 4056489369820 - 20195595 - OFF#8d5bc40707c13eaa599d9ddb6052cdd7 Fromage de Chèvre - fromage de chevre - - Lidl - 0 - 4056489416371 - 20195595 - OFF#a0611ceddb8fccdbc71e50d77df705d2 Fromage de Chèvre - fromage de chevre - - Lidl - 0 - 52615047 - 20195595 - OFF#af3b5d75032cd09e2792f5587ef364fe ---------------------------------------------------- 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 --------------------------------- final result ----------------------------------- {'prompt': '', 'model': 'mistral-large-2411', 'imagePath': '/home/debian/html/nutritwin/output_llm/68fcbc2a58134/capture.jpg', 'intents': ['Identify foods and beverages in an image'], 'solutions': {'nutrition': [{'name': 'Fromage de Chèvre', 'normName': ' fromage de chevre ', 'comment': '', 'normComment': '', 'rank': 4537, 'id': 'KCA#87a40b8f006dcb11aafd4e97014ed3f4', 'quantity': '160 grammes', 'quantityLem': '160 gramme', 'pack': ['CH2.w20', 'CHE.w20'], 'type': 'food', 'gtin': '', 'gtinRef': '', 'brand': '', 'time': '', 'event': 'declaration', 'serving': '', 'posiNormName': 0}], 'activity': [], 'response': {}}, 'cputime': 2.4424798488616943} ---------------------------------------------------------------------------------- LLM CPU Time: 2.4424798488616943