Input path: /home/debian/html/nutritwin/output_llm/67a992dae310a/input.json
Output path: /home/debian/html/nutritwin/output_llm/67a992dae310a/output.json
Input text: Ce matin j'ai mangé un pain au chocolat et bu une tasse de thé.
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 pain au chocolat et bu une tasse de thé.
==================================================================================================================================

==================================== 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 pain au chocolat et bu une tasse de thé.###. 
 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 pain au chocolat et bu une tasse de thé.""" 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: <http://www.3dminded.com/RDF/ontology/food#> .

@prefix rdfs: <http://www.w3.org/2000/01/rdf-schema#> . 
@prefix xsd: <http://www.w3.org/2001/XMLSchema#> .
@prefix owl: <http://www.w3.org/2002/07/owl#> .
@prefix prov: <http://www.w3.org/ns/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": "pain au chocolat",
        "quantity": "un",
        "timeOfTheDay": "breakfast",
        "type": "food",
        "event": "declaration"
    },
    {
        "name": "th\u00e9",
        "quantity": "une tasse",
        "timeOfTheDay": "breakfast",
        "type": "beverage",
        "event": "declaration"
    }
]
-----------------------------------------------------------------------------

----------------- Make it compliant ------------------
[
    {
        "name": "pain au chocolat",
        "quantity": "un",
        "timeOfTheDay": "breakfast",
        "type": "food",
        "event": "declaration"
    },
    {
        "name": "th\u00e9",
        "quantity": "une tasse",
        "timeOfTheDay": "breakfast",
        "type": "beverage",
        "event": "declaration"
    }
]
------------------------------------------------------

------------------------ After simplification ------------------------
[
    {
        "name": "pain au chocolat",
        "quantity": "un",
        "timeOfTheDay": "breakfast",
        "type": "food",
        "event": "declaration"
    },
    {
        "name": "th\u00e9",
        "quantity": "une tasse",
        "timeOfTheDay": "breakfast",
        "type": "beverage",
        "event": "declaration"
    }
]
----------------------------------------------------------------------

--------------------------------- LLM result -----------------------------------
{'response': [{'name': 'pain au chocolat', 'quantity': 'un', 'timeOfTheDay': 'breakfast', 'type': 'food', 'event': 'declaration'}, {'name': 'thé', 'quantity': 'une tasse', 'timeOfTheDay': 'breakfast', 'type': 'beverage', 'event': 'declaration'}], 'cost': 0.10619999999999999}
--------------------------------------------------------------------------------

----------- result to be analyzed -----------
{'name': 'pain au chocolat', 'quantity': 'un', '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 '% pain chocolat %' AND (V_NormTrademark = '' OR V_NormTrademark IS NULL)


------------- Found solution (max 20) --------------
Pain au Chocolat -  pain chocolat  -  -  - 8865 -  -  - CIQ#aa621dd97d922a7b28ca0ee09aed7449
Pain au Chocolat Feuilleté -  pain chocolat feuillete  - artisanal -  - 0 -  -  - CIQ#bd38d8f7658a11f0a504009aaaa44ead
----------------------------------------------------


----------- result to be analyzed -----------
{'name': 'thé', 'quantity': 'une tasse', 'timeOfTheDay': 'breakfast', '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 '% the %' AND (V_NormTrademark = '' OR V_NormTrademark IS NULL)


------------- Found solution (max 20) --------------
Thé Vert -  the vert  - infusé, non sucré -  - 0 -  -  - CIQ#eac5c73b642ef9eb1db2cafc9d1843ba
Thé Noir -  the noir  - infusé, non sucré -  - 0 -  -  - CIQ#bf75fb01672a7afe76ba5a88645e87ca
Thé Infusé -  the infuse  - non sucré -  - 0 -  -  - CIQ#09bb3cfe071d2337b58db8e32379af6d
Thé Oolong -  the oolong  - infusé, non sucré -  - 0 -  -  - CIQ#dcf2a40c30e0bd1cf9736831ce2f1a07
Thé sans Sucre -  the san sucre  - sans sucre -  - 0 -  -  - KCA#9de5d7e3a39cb14df7a2014ed9319364
Thé au Lait Sucré -  the lait sucre  - 1 sucre -  - 2799 -  -  - KCA#f79219b7fdb1e0186da32547f7467cc3
Thé Sucré (1 Sucre) -  the sucre  - sucré (1 sucre) -  - 0 -  -  - KCA#ce556337e0d9788306e32b24fe0fe081
Thé au Lait sans Sucre -  the lait san sucre  - sans sucre -  - 0 -  -  - KCA#978c8f4bf945ce13218480e6d937996a
Thé à la Menthe sans Sucre -  the menthe san sucre  - sans sucre -  - 0 -  -  - KCA#d6b018fd859ac0e6ee70bca51b09db90
Sex On The Beach -  se on the beach  - the beach -  - 0 -  -  - KCA#f07d74af373a5290a216c60de530b430
Boisson au Thé -  boisson the  - aromatisée, sucrée -  - 94 -  -  - KCA#b6e1f48e249eca1255475b06f7bf38aa
Boisson au Thé -  boisson the  - aromatisée, sucrée -  - 0 -  -  - CIQ#b6e1f48e249eca1255475b06f7bf38aa
Boisson au Thé -  boisson the  - aromatisée, 'light' -  - 6 -  -  - KCA#c1894f128b1446d7f36c0d2f350d199c
Boisson au Thé -  boisson the  - aromatisée, teneur en sucre et édulcorant inconnue, aliment moyen -  - 0 -  -  - CIQ#7deb532133632b6172af215d3ff1ff5b
Pruneaux au Thé -  pruneau the  -  -  - 6 -  -  - KCA#8cb9a957c6950b74118bd4b2efeeb2b9
----------------------------------------------------


--------------------------------- final result -----------------------------------
{'prompt': "Ce matin j'ai mangé un pain au chocolat et bu une tasse de thé.", 'model': 'mistral-large-2411', 'imagePath': '', 'intents': ['Identify food and beverage consumption or declaration'], 'solutions': {'nutrition': [{'name': 'Pain au Chocolat', 'normName': ' pain chocolat ', 'comment': '', 'normComment': '', 'rank': 8865, 'id': 'CIQ#aa621dd97d922a7b28ca0ee09aed7449', 'quantity': 'un', 'quantityLem': '1', 'pack': ['PAC.w80'], 'type': 'food', 'gtin': '', 'gtinRef': '', 'brand': '', 'time': 'breakfast', 'event': 'declaration', 'serving': 'PAC-100', 'posiNormName': 0}, {'name': 'Thé Vert', 'normName': ' the vert ', 'comment': 'infusé, non sucré', 'normComment': ' infuse non sucre ', 'rank': 0, 'id': 'CIQ#eac5c73b642ef9eb1db2cafc9d1843ba', 'quantity': 'une tasse', 'quantityLem': '1 tasse', 'pack': ['TAC'], 'type': 'beverage', 'gtin': '', 'gtinRef': '', 'brand': '', 'time': 'breakfast', 'event': 'declaration', 'serving': 'TAC-100', 'posiNormName': 0}], 'activity': [], 'response': {}}, 'cputime': 3.3179931640625}
----------------------------------------------------------------------------------
LLM CPU Time: 3.3179931640625