Input path: /home/debian/html/nutritwin/output_llm/6703cc9b0f8cc/input.json Output path: /home/debian/html/nutritwin/output_llm/6703cc9b0f8cc/output.json Input text: À midi j'ai mangé des sardines à l'huile. 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: À midi j'ai mangé des sardines à l'huile. ================================================================================================================================== ==================================== Prompt ============================================= Identify in this list of intents: ["Identify food consumption or declaration", "Identify the user physical activity", "Answer a nutrition question", "Other intent"], the intents of the prompt: ###À midi j'ai mangé des sardines à l'huile.###. Format the result in JSON format: {intents: []}. ========================================================================================= ------------------------------ LLM Raw response ----------------------------- ```json { "intents": ["Identify food consumption or declaration"] } ``` ----------------------------------------------------------------------------- ----------------- Make it compliant ------------------ ```json { "intents": ["Identify food consumption or declaration"] } ``` ------------------------------------------------------ ------------------------ After simplification ------------------------ { "intents": ["Identify food consumption or declaration"]} ---------------------------------------------------------------------- ==================================== Prompt ============================================= Convert this natural language query : """À midi j'ai mangé des sardines à l'huile.""" into an array in JSON of consumed foods and beverages. Provide a solution without explanation. Use only the 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. Keep the same language"@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 examples in french: '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. Keep the same language"@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. """ ========================================================================================= ------------------------------ LLM Raw response ----------------------------- ```json [ { "name": "sardines", "cooking method": "à l'huile", "type of food": "food", "time of the day": "lunch", "event": "declaration" } ] ``` ----------------------------------------------------------------------------- ----------------- Make it compliant ------------------ ```json [ { "name": "sardines", "cooking method": "à l'huile", "type of food": "food", "time of the day": "lunch", "event": "declaration" } ] ``` ------------------------------------------------------ ------------------------ After simplification ------------------------ [ { "name": "sardines", "cooking method": "à l'huile", "type of food": "food", "time of the day": "lunch", "event": "declaration" }] ---------------------------------------------------------------------- --------------------------------- LLM result ----------------------------------- {'response': [{'name': 'sardines', 'cooking method': "à l'huile", 'type of food': 'food', 'time of the day': 'lunch', 'event': 'declaration'}], 'cost': 0.0} -------------------------------------------------------------------------------- ----------- result to be analyzed ----------- {'name': 'sardines', 'cooking method': "à l'huile", 'type of food': 'food', 'time of the day': 'lunch', '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 '% sardine %' AND (V_NormTrademark = '' OR V_NormTrademark IS NULL) ------------- Found solution (max 20) -------------- Sardine - sardine - crue - - 0 - - - CIQ#afb57ee9c908fbb7b50b8c0f837db8c1 Sardine - sardine - grillée - - 343 - - - CIQ#eff3528d633d32922074581779ea9e70 Sardine - sardine - à l'huile, égouttée - - 0 - - - CIQ#447e70ab2aeba4cb57ed526363b62fb9 Sardine - sardine - sauce tomate, égouttée - - 0 - - - CIQ#6cd74ce42bd3752b673d8b2a1a9b727b Sardine - sardine - à l'huile d'olive, égouttée - - 0 - - - CIQ#39cf1c474ade28ef7fa53a15e35314f5 Sardine - sardine - filets sans arêtes à l'huile d'olive, égouttés - - 0 - - - CIQ#eda4c495091533d4dcbcd77bc238426e Sardines Grillées - sardine grillee - sardines grillées - - 0 - - - KCA#a385f038f5c6693704c704d93fd8bd87 Sushi Sardine - sushi sardine - sushi sardine - - 0 - - - KCA#81f953af4a8945bbcb76e20742a98ddf Huile de Sardine - huile de sardine - - - 0 - - - CIQ#5cf37ad51c37813403fa5a705b2c7255 Tomates Farcies aux Sardines - tomate farcie au sardine - aux sardines - - 0 - - - KCA#4c8e0328e94cbf54c0b62befcb63b259 ---------------------------------------------------- ERROR: Wrong quantity: '' ERROR: no solution for picto in the first solution ERROR: Wrong quantity: '' ERROR: no solution for picto in the first solution ERROR: Wrong quantity: '' ERROR: no solution for picto in the first solution ERROR: Wrong quantity: '' ERROR: no solution for picto in the first solution ERROR: Wrong quantity: '' ERROR: no solution for picto in the first solution ERROR: Wrong quantity: '' ERROR: no solution for picto in the first solution --------------------------------- final result ----------------------------------- {'prompt': "À midi j'ai mangé des sardines à l'huile.", 'intents': ['Identify food consumption or declaration'], 'model': 'gpt-4o-2024-05-13', 'solutions': {'nutrition': [{'name': 'Sardine', 'normName': ' sardine ', 'comment': 'crue', 'normComment': ' crue ', 'rank': 0, 'id': 'CIQ#afb57ee9c908fbb7b50b8c0f837db8c1', 'quantity': '', 'quantityLem': '', 'pack': ['PO4.w50'], 'type': '', 'gtin': '', 'gtinRef': '', 'brand': '', 'time': '', 'event': 'declaration', 'serving': '', 'posiNormName': 0}], 'activity': [], 'response': {}}, 'cputime': 1.8636751174926758} ---------------------------------------------------------------------------------- LLM CPU Time: 1.8636751174926758