Input path: /home/debian/html/nutritwin/output_llm/6758c89221549/input.json Output path: /home/debian/html/nutritwin/output_llm/6758c89221549/output.json Input text: Ce matin j'ai mangé un filet de saumon. 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 filet de saumon. ================================================================================================================================== ==================================== 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 filet de saumon.###. 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 filet de saumon.""" 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": "saumon", "quantity": "un filet", "timeOfTheDay": "breakfast", "type": "food", "event": "declaration" } ] ----------------------------------------------------------------------------- ----------------- Make it compliant ------------------ [ { "name": "saumon", "quantity": "un filet", "timeOfTheDay": "breakfast", "type": "food", "event": "declaration" } ] ------------------------------------------------------ ------------------------ After simplification ------------------------ [ { "name": "saumon", "quantity": "un filet", "timeOfTheDay": "breakfast", "type": "food", "event": "declaration" } ] ---------------------------------------------------------------------- --------------------------------- LLM result ----------------------------------- {'response': [{'name': 'saumon', 'quantity': 'un filet', 'timeOfTheDay': 'breakfast', 'type': 'food', 'event': 'declaration'}], 'cost': 0.0984} -------------------------------------------------------------------------------- ----------- result to be analyzed ----------- {'name': 'saumon', 'quantity': 'un filet', 'timeOfTheDay': 'breakfast', '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 '% saumon %' AND (V_NormTrademark = '' OR V_NormTrademark IS NULL) ------------- Found solution (max 20) -------------- Saumon - saumon - égoutté - - 0 - - - CIQ#ade5613634b5a98b355d2c160ba92b11 Saumon - saumon - à la vapeur - - 0 - - - CIQ#b3e9314258a5f523753d1b3e0d81792c Saumon - saumon - grillé/poêlé - - 0 - - - CIQ#1bbf5286767c3e0c44876a767787d000 Saumon - saumon - cru, sauvage - - 0 - - - CIQ#51feba31b17547b9137b71eb7226a8dd Saumon - saumon - cru, élevage - - 0 - - - CIQ#c8287362ac00c89902eae000e0e4c124 Saumon - saumon - aliment moyen - - 0 - - - CIQ#ff1666b2df4b9989f1a9c6b0a02dc93c Saumon - saumon - au micro-ondes, élevage - - 0 - - - CIQ#cc11fcd15c72c773b82b192e8887e23a Saumon - saumon - élevage, rôti/cuit au four - - 0 - - - CIQ#84a9c51768b4de88e909ecdf0067a966 Saumon - saumon - bouilli/cuit à l'eau, élevage - - 0 - - - CIQ#f55d77c458b7370f03d90ab21a698aaf Saumon Fumé - saumon fume - - - 11676 - - - CIQ#d8453997de6adf67fd709f2e16e4a09f Saumon Farci - saumon farci - - - 0 - - - CIQ#61af7b646d375a64a8af54fa22cd3709 Saumon à l'Oseille - saumon oseille - - - 7 - - - CIQ#78f9c8ecc76216402bd6d82a033010c5 Maki Saumon - maki saumon - - - 1080 - - - KCA#3ac315133b892d2a4629a1ab26c48768 Maki Saumon Avocat - maki saumon avocat - - - 861 - - - KCA#725e4073ccaee17f4a77ab78eb5b90a5 Sushi Saumon - sushi saumon - sushi saumon - - 0 - - - KCA#f366d90248edc0d02f459cc18228171a Tarte au Saumon - tarte saumon - - - 0 - - - CIQ#df3d146a0b5d8475bb92ccfb839aa962 Pizza au Saumon - pizza saumon - - - 0 - - - CIQ#531c0deee226a1ed25c6ad7e9344ecef Röstis au Saumon Fumé - rosti saumon fume - - - 12 - - - KCA#14382263fff55c2e867e77149a5dc44e Tarte Saumon et Oseille - tarte saumon oseille - et oseille - - 0 - - - KCA#4c90651bf0030bf66a4324b273991f08 Pavé de Saumon - pave de saumon - - - 9408 - - - KCA#65b031a28707cc1cba8900c617fd1e01 ---------------------------------------------------- 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': "Ce matin j'ai mangé un filet de saumon.", 'model': 'mistral-large-2411', 'imagePath': '', 'intents': ['Identify food and beverage consumption or declaration'], 'solutions': {'nutrition': [{'name': 'Saumon', 'normName': ' saumon ', 'comment': 'égoutté', 'normComment': ' egoutte ', 'rank': 0, 'id': 'CIQ#ade5613634b5a98b355d2c160ba92b11', 'quantity': 'un filet', 'quantityLem': '1 filet', 'pack': ['PAV.w200'], 'type': 'food', 'gtin': '', 'gtinRef': '', 'brand': '', 'time': 'breakfast', 'event': 'declaration', 'serving': '', 'posiNormName': 0}], 'activity': [], 'response': {}}, 'cputime': 2.6473374366760254} ---------------------------------------------------------------------------------- LLM CPU Time: 2.6473374366760254