Input path: /home/debian/html/nutritwin/output_llm/664aed5c711da/input.json Output path: /home/debian/html/nutritwin/output_llm/664aed5c711da/output.json Input text: Ce matin j'ai mangé un Danone 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: Ce matin j'ai mangé un Danone ================================================================================================================================== ==================================== Prompt ============================================= Identify in this list of intents: ["Identify food and beverage consumption or declaration", "Identify the user physical activity", "Answer a nutrition question", "Other intent"], the intents of the prompt: ###Ce matin j'ai mangé un Danone###. Format the result in JSON format: {"intents": []}. ========================================================================================= ------------------------------ LLM Raw response ----------------------------- {"intents": ["Identify food and beverage consumption or declaration"]} ----------------------------------------------------------------------------- ----------------- Make it compliant ------------------ {"intents": ["Identify food and beverage consumption or declaration"]} ------------------------------------------------------ ERROR: wrong object representation: {'intents': ['Identify food and beverage consumption or declaration']} ------------------------ After simplification ------------------------ { "intents": [ "Identify food and beverage consumption or declaration" ] } ---------------------------------------------------------------------- ==================================== Prompt ============================================= Convert this natural language query : """Ce matin j'ai mangé un Danone""" into an array of JSON. Ignore what it is not connected to nutrition, beverage or food. Provide a solution without explanation. Use the following ontology and only this 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...)."@en; rdfs:comment "Ignore food or beverage when it is not consumed in the past, now or in the future."@en; rdfs:comment "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."@en; rdfs:comment "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": "yaourt", "quantity": "un", "timeOfTheDay": "breakfast", "brand": "Danone", "type": "food", "event": "declaration" } ] ----------------------------------------------------------------------------- ----------------- Make it compliant ------------------ [ { "name": "yaourt", "quantity": "un", "timeOfTheDay": "breakfast", "brand": "Danone", "type": "food", "event": "declaration" } ] ------------------------------------------------------ ------------------------ After simplification ------------------------ [ { "name": "yaourt", "quantity": "un", "timeOfTheDay": "breakfast", "brand": "Danone", "type": "food", "event": "declaration" } ] ---------------------------------------------------------------------- --------------------------------- LLM result ----------------------------------- {'response': [{'name': 'yaourt', 'quantity': 'un', 'timeOfTheDay': 'breakfast', 'brand': 'Danone', 'type': 'food', 'event': 'declaration'}], 'cost': 0.10074} -------------------------------------------------------------------------------- ----------- result to be analyzed ----------- {'name': 'yaourt', 'quantity': 'un', 'timeOfTheDay': 'breakfast', 'brand': 'Danone', 'type': 'food', '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 '% yaourt %' AND V_NormTrademark LIKE '%danone%' ------------- Found solution (max 20) -------------- Yaourt - yaourt - - Danone - 8 - 13561390 - 13561390 - OFF#d05c7bad1833108d7aac87bb2be2ae6f Yaourt - yaourt - - Danone - 0 - 3033491215353 - 13561390 - OFF#a44bf4719bfc97599207df830244621c Yaourt - yaourt - - Danone - 0 - 5410146417061 - 13561390 - OFF#5022f1e2b789f0f6aa44416baa0d7560 Yaourt - yaourt - - Danone - 0 - 5410146420597 - 13561390 - OFF#d7b8d211568f869d3261da4d29401ab5 Yaourt - yaourt - - Danone - 0 - 3330261041205 - 13561390 - OFF#b6e99f227eff5773c1c5fdbe53fef3b5 Yaourt - yaourt - - Danone - 0 - 3330261030506 - 13561390 - OFF#3eeb8a1eb3478b34843adaadf4d4ce85 Yaourt - yaourt - - Danone - 0 - 3330261030100 - 13561390 - OFF#5acbbfe23f23953da5c23e9d829e30f0 Yaourt - yaourt - - Danone - 0 - 5601050034950 - 13561390 - OFF#a3db60fd82209c7039e34013035e385c Yaourt - yaourt - - Danone - 0 - 5410146418273 - 13561390 - OFF#0b585358bc172d2e308131ce70de0c80 Yaourt - yaourt - - Danone - 0 - 3330261020705 - 13561390 - OFF#a99b39ad9eae80cbe801b143f7ed6ed7 Yaourt - yaourt - - Danone - 0 - 3033491235740 - 13561390 - OFF#9ffb5713e93620a28232bb9bd618ede4 Yaourt - yaourt - - Danone - 0 - 5900643038277 - 13561390 - OFF#3cdb76ac70adc6ed2b917faac77b6df1 Yaourt - yaourt - - Danone - 0 - 6130646003128 - 13561390 - OFF#fa8b036dd2e4dbcef32bf006113bbb09 Yaourt - yaourt - - Danone - 0 - 3033491208386 - 13561390 - OFF#76b5f9b99f87c98bc01411a30d232cd2 Yaourt - yaourt - - Danone - 0 - 3033491920318 - 13561390 - OFF#6b57474329ecc35fe6828a24ba092e26 Yaourt - yaourt - - Danone - 0 - 5410146417177 - 13561390 - OFF#b057f3bd83ed8d2669ea7b29518413b2 Yaourt 1919 - yaourt 1919 - - Danone - 0 - 3033491274138 - 3033491274138 - OFF#fb90197ae57fba65a4b56a8383d202e1 Yaourt Mixé - yaourt mixe - - Danone - 0 - 3516465000150 - 3516465000150 - OFF#23d5e5351852b6bcb2f3a50550fd5f6a Yaourt 1919 - yaourt 1919 - - Danone - 0 - 3033491274152 - 3033491274138 - OFF#afefd2ea79d712eed1f700b4da863456 Yaourt Sucre - yaourt sucre - - Danone - 0 - 3033491208362 - 3033491208362 - OFF#6ffb8bf6afbb736de38ce4510a619ce0 ---------------------------------------------------- --------------------------------- final result ----------------------------------- {'prompt': "Ce matin j'ai mangé un Danone", 'model': 'mistral-large-2411', 'imagePath': '', 'intents': ['Identify food and beverage consumption or declaration'], 'solutions': {'nutrition': [{'name': 'Yaourt', 'normName': ' yaourt ', 'comment': '', 'normComment': '', 'rank': 8, 'id': 'OFF#d05c7bad1833108d7aac87bb2be2ae6f', 'quantity': 'un', 'quantityLem': '1', 'pack': ['YA2.w125', 'YA9.w125'], 'type': 'food', 'gtin': '13561390', 'gtinRef': '13561390', 'brand': 'Danone', 'time': 'breakfast', 'event': 'declaration', 'serving': 'YA2-100', 'posiNormName': 0}], 'activity': [], 'response': {}}, 'cputime': 2.429426431655884} ---------------------------------------------------------------------------------- LLM CPU Time: 2.429426431655884