Input path: /home/debian/html/nutritwin/output_llm/67938361ebb0f/input.json Output path: /home/debian/html/nutritwin/output_llm/67938361ebb0f/output.json Input text: J'ai bu un café et un verre d'eau du robinet. 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: J'ai bu un café et un verre d'eau du robinet. ================================================================================================================================== ==================================== 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: ###J'ai bu un café et un verre d'eau du robinet.###. 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 : """J'ai bu un café et un verre d'eau du robinet.""" 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...). 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" }, { "name": "eau", "quantity": "un verre", "type": "beverage", "event": "declaration" } ] ----------------------------------------------------------------------------- ----------------- Make it compliant ------------------ [ { "name": "café", "quantity": "un", "type": "beverage", "event": "declaration" }, { "name": "eau", "quantity": "un verre", "type": "beverage", "event": "declaration" } ] ------------------------------------------------------ ------------------------ After simplification ------------------------ [ { "name": "caf\u00e9", "quantity": "un", "type": "beverage", "event": "declaration" }, { "name": "eau", "quantity": "un verre", "type": "beverage", "event": "declaration" } ] ---------------------------------------------------------------------- --------------------------------- LLM result ----------------------------------- {'response': [{'name': 'café', 'quantity': 'un', 'type': 'beverage', 'event': 'declaration'}, {'name': 'eau', 'quantity': 'un verre', 'type': 'beverage', 'event': 'declaration'}], 'cost': 0.102} -------------------------------------------------------------------------------- ----------- 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 ---------------------------------------------------- ----------- result to be analyzed ----------- {'name': 'eau', 'quantity': 'un verre', '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 '% eau %' AND (V_NormTrademark = '' OR V_NormTrademark IS NULL) ------------- Found solution (max 20) -------------- Eau - eau - - - 10064 - - - KCA#08cfe774cbf7476b1e582734c7082ecd Eau de Vie - eau de vie - - - 210 - - - CIQ#2397ddba68eefec7e38e3a061b6060e3 Eau de Coco - eau de coco - - - 574 - - - CIQ#4f6cfd4687e4da85c9063e194dd3113b Eau Minérale - eau minerale - - - 0 - - - CIQ#682a311be3fc15a20a88c168408e5304 Eau Minérale - eau minerale - aliment moyen - - 160 - - - KCA#69addfd353e07f633ee05c6be8ac5d4d Eau Minérale - eau minerale - plate, aliment moyen - - 18 - - - CIQ#9f35a4198a700eac62fe4d1dc426f1a4 Eau Minérale - eau minerale - gazeuse, aliment moyen - - 28 - - - CIQ#38da155cfd970d21ba9f4b87294b96df Eau Minérale - eau minerale - ou de source aromatisée agrumes - - 33 - - - KCA#47ee70f086c3080428426febc2426e8c Eau Minérale - eau minerale - ou de source aromatisée, arôme autre qu'agrumes - - 36 - - - KCA#0daeef02b69e5526427bc855f1ec3111 Eau Minérale - eau minerale - embouteillée, faiblement minéralisée, aliment moyen - - 0 - - - CIQ#a8b887f21f002cd8ddbda99766ee5ec4 Eau de Source - eau de source - embouteillée, aliment moyen - - 0 - - - CIQ#b6c1ba3e6cb4c788d63711a9b869730b Eau du Robinet - eau robinet - - - 273 - - - CIQ#4c4a29ce4ec63b6cfc6bc3914ccf7056 Eau Minérale Dax - eau minerale da - embouteillée, non gazeuse, moyennement minéralisée, Dax, 40 - - 0 - - - CIQ#a07a880ef627fa44150fe5583484549d Eau de Vie de Vin - eau de vie de vin - type armagnac, cognac - - 0 - - - CIQ#c0440021ea15aa2abf11853bbd2191a4 Eau Minérale Néro - eau minerale nero - embouteillée, non gazeuse, faiblement minéralisée, Grèce - - 0 - - - CIQ#8ab34da104cb5b744e0ad6eaece161a6 Eau Minérale Avra - eau minerale avra - embouteillée, non gazeuse, faiblement minéralisée, Grèce - - 0 - - - CIQ#b0465b7ee2f045df840aac281b388253 Eau Minérale Luso - eau minerale luso - embouteillée, non gazeuse, très faiblement minéralisée, Portugal - - 0 - - - CIQ#45d467ce96aa14e71c62e6ca943f5621 Eau Minérale Eden - eau minerale eden - La Goa, embouteillée, non gazeuse, faiblement minéralisée, Suisse - - 0 - - - CIQ#341195c07e8f951269157ecad800778a Eau Minérale Ogeu - eau minerale ogeu - embouteillée, gazeuse, faiblement minéralisée, Ogeu-les-Bains, 64 - - 0 - - - CIQ#14fc742b6db6af7dce1a08288d62ddf6 Eau Minérale Vals - eau minerale val - embouteillée, gazeuse, moyennement minéralisée, Vals-les-Bains, 07 - - 0 - - - CIQ#11be70594fa1e46c35dca065d17b5ca6 ---------------------------------------------------- --------------------------------- final result ----------------------------------- {'prompt': "J'ai bu un café et un verre d'eau du robinet.", 'model': 'mistral-large-2411', 'imagePath': '', 'intents': ['Identify food and beverage consumption or declaration'], '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}, {'name': 'Eau', 'normName': ' eau ', 'comment': '', 'normComment': '', 'rank': 10064, 'id': 'KCA#08cfe774cbf7476b1e582734c7082ecd', 'quantity': 'un verre', 'quantityLem': '1 verre', 'pack': ['VAE', 'VX1', 'VA2', 'GOB', 'VA4', 'VA4', 'VA3'], 'type': 'beverage', 'gtin': '', 'gtinRef': '', 'brand': '', 'time': '', 'event': 'declaration', 'serving': 'VA2-100', 'posiNormName': 0}], 'activity': [], 'response': {}}, 'cputime': 2.5199413299560547} ---------------------------------------------------------------------------------- LLM CPU Time: 2.5199413299560547