Input path: /home/debian/html/nutritwin/output_llm/684337c057f16/input.json Output path: /home/debian/html/nutritwin/output_llm/684337c057f16/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/684337c057f16/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": "café", "quantity": "un", "type": "beverage", "event": "declaration" } ] ----------------------------------------------------------------------------- ----------------- Make it compliant ------------------ [ { "name": "café", "quantity": "un", "type": "beverage", "event": "declaration" } ] ------------------------------------------------------ ------------------------ After simplification ------------------------ [ { "name": "caf\u00e9", "quantity": "un", "type": "beverage", "event": "declaration" } ] ---------------------------------------------------------------------- --------------------------------- LLM result ----------------------------------- {'response': [{'name': 'café', 'quantity': 'un', 'type': 'beverage', 'event': 'declaration'}], 'cost': 0.0} -------------------------------------------------------------------------------- ----------- result to be analyzed ----------- {'name': 'café', 'quantity': 'un', '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 '% cafe %' AND (V_NormTrademark = '' OR V_NormTrademark IS NULL) ------------- Found solution (max 20) -------------- Café - cafe - instantané, non sucré, prêt à boire - - 0 - - - CIQ#264e95338204dca4258b74b77eb82c9d Café - cafe - non instantané, non sucré, prêt à boire - - 0 - - - CIQ#3c8ab223f148936c6d387b43adfd13fd Café Noir - cafe noir - sucré - - 41467 - - - KCA#4340bea443e4a31592a29591931d64f4 Café Noir - cafe noir - non sucré - - 48621 - - - KCA#7783b77c6af961856829a78ae941e4f5 Café Crème - cafe creme - - - 795 - - - KCA#0fb4970e6ac2d812b39e89ee8fd4d737 Café Liégois - cafe liegoi - - - 213 - - - KCA#c4757bb9d7b5ef114a1b9111b15b705d Café au Lait - cafe lait - entier sucré - - 686 - - - KCA#79a7269ac953a86d5d8964ee0f4152db Café au Lait - cafe lait - écrémé sucré - - 653 - - - KCA#cea770a189e838bbc39e36cf537abb5a Café au Lait - cafe lait - 1/2 écrémé sucré - - 15199 - - - KCA#138ec7dba7fa585306b852c3f7e0a463 Café au Lait - cafe lait - écrémé non sucré - - 6369 - - - KCA#eefa4e0f868d9c342316060e62f23159 Café au Lait - cafe lait - entier non sucré - - 1063 - - - KCA#766d75aba9738d735cfb5303e24e0712 Café au Lait - cafe lait - 1/2 écrémé non sucré - - 21616 - - - KCA#e8f1a390014f879ed671041ebfeb6366 Café Soluble - cafe soluble - reconstitué non sucré - - 90 - - - KCA#0c31272ac325fe94fd9d5005ecb8ac13 Café au Lait - cafe lait - café crème ou cappuccino, instantané ou non, non sucré, prêt à boire - - 0 - - - CIQ#61667259d09a30eac4d1919dafb0f043 Café Noisette - cafe noisette - - - 971 - - - KCA#0fc9cdc7bb8a494e3e53719b2bee98c8 Café Expresso - cafe expresso - non instantané, non sucré, prêt à boire - - 5358 - - - CIQ#71484d6749acf1476e8d6abb42471db7 Café Décaféiné - cafe decafeine - sucré - - 984 - - - KCA#8a390d02b1d614cdea70649e29d1eb33 Café Décaféiné - cafe decafeine - instantané, non sucré, prêt à boire - - 0 - - - CIQ#74256f0fb8c48036bc45f36ec358fe89 Café Décaféiné - cafe decafeine - non instantané, non sucré, prêt à boire - - 0 - - - CIQ#ee0c2c2c94c61b5486ce3cdc38d75906 Café Poudre Soluble - cafe poudre soluble - - - 735 - - - KCA#4e1ee649d6587af50fb6c6c59ba70334 ---------------------------------------------------- --------------------------------- final result ----------------------------------- {'prompt': '', 'model': 'mistral-large-2411', 'imagePath': '/home/debian/html/nutritwin/output_llm/684337c057f16/capture.jpg', 'intents': ['Identify foods and beverages in an image'], 'solutions': {'nutrition': [{'name': 'Café', 'normName': ' cafe ', 'comment': 'instantané, non sucré, prêt à boire', 'normComment': ' instantane non sucre pret boire ', 'rank': 0, 'id': 'CIQ#264e95338204dca4258b74b77eb82c9d', 'quantity': 'un', 'quantityLem': '1', 'pack': ['TA2', 'TA3'], 'type': 'beverage', 'gtin': '', 'gtinRef': '', 'brand': '', 'time': '', 'event': 'declaration', 'serving': 'TA2-100', 'posiNormName': 0}], 'activity': [], 'response': {}}, 'cputime': 1.553215503692627} ---------------------------------------------------------------------------------- LLM CPU Time: 1.553215503692627