Input path: /home/debian/html/nutritwin/output_llm/6797e74f6af8c/input.json
Output path: /home/debian/html/nutritwin/output_llm/6797e74f6af8c/output.json
Input text: Avec des pépites de chocolat et elles étaient petites et j'ai mangé un croissant au jambon ce soir.
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: Avec des pépites de chocolat et elles étaient petites et j'ai mangé un croissant au jambon ce soir.
==================================================================================================================================

==================================== 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: ###Avec des pépites de chocolat et elles étaient petites et j'ai mangé un croissant au jambon ce soir.###. 
 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 : """Avec des pépites de chocolat et elles étaient petites et j'ai mangé un croissant au jambon ce soir.""" 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": "pépites de chocolat",
        "quantity": "petites",
        "type": "food",
        "event": "declaration"
    },
    {
        "name": "croissant au jambon",
        "quantity": "un",
        "timeOfTheDay": "dinner",
        "type": "food",
        "event": "declaration"
    }
]
-----------------------------------------------------------------------------

----------------- Make it compliant ------------------
[
    {
        "name": "pépites de chocolat",
        "quantity": "petites",
        "type": "food",
        "event": "declaration"
    },
    {
        "name": "croissant au jambon",
        "quantity": "un",
        "timeOfTheDay": "dinner",
        "type": "food",
        "event": "declaration"
    }
]
------------------------------------------------------

------------------------ After simplification ------------------------
[
    {
        "name": "p\u00e9pites de chocolat",
        "quantity": "petites",
        "type": "food",
        "event": "declaration"
    },
    {
        "name": "croissant au jambon",
        "quantity": "un",
        "timeOfTheDay": "dinner",
        "type": "food",
        "event": "declaration"
    }
]
----------------------------------------------------------------------

--------------------------------- LLM result -----------------------------------
{'response': [{'name': 'pépites de chocolat', 'quantity': 'petites', 'type': 'food', 'event': 'declaration'}, {'name': 'croissant au jambon', 'quantity': 'un', 'timeOfTheDay': 'dinner', 'type': 'food', 'event': 'declaration'}], 'cost': 0.10511999999999999}
--------------------------------------------------------------------------------

----------- result to be analyzed -----------
{'name': 'pépites de chocolat', 'quantity': 'petites', '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 '% pepite de chocolat %' AND (V_NormTrademark = '' OR V_NormTrademark IS NULL)


------------- Found solution (max 20) --------------
Muffin Pépites de Chocolat -  muffin pepite de chocolat  -  -  - 953 -  -  - KCA#671562cdedac9d3dc4e189a25ef9d908
Pain au Lait aux Pépites de Chocolat -  pain lait au pepite de chocolat  -  -  - 22 -  -  - CIQ#d39f699d0c70de159812b19256a70a19
----------------------------------------------------

ERROR: Wrong quantity: 'petit'
ERROR: no solution for picto in the first solution

----------- result to be analyzed -----------
{'name': 'croissant au jambon', 'quantity': 'un', 'timeOfTheDay': 'dinner', '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 '% croissant jambon %' AND (V_NormTrademark = '' OR V_NormTrademark IS NULL)


------------- Found solution (max 20) --------------
Croissant au Jambon -  croissant jambon  -  -  - 212 -  -  - CIQ#8cd4fb25e8fd9b214dc8f8ca0dfd4d1a
Croissant au Jambon Fromage -  croissant jambon fromage  -  -  - 0 -  -  - CIQ#62e60d508ab7cd11d065c260425c770b
----------------------------------------------------


--------------------------------- final result -----------------------------------
{'prompt': "Avec des pépites de chocolat et elles étaient petites et j'ai mangé un croissant au jambon ce soir.", 'model': 'mistral-large-2411', 'imagePath': '', 'intents': ['Identify food and beverage consumption or declaration'], 'solutions': {'nutrition': [{'name': 'Muffin Pépites de Chocolat', 'normName': ' muffin pepite de chocolat ', 'comment': '', 'normComment': '', 'rank': 953, 'id': 'KCA#671562cdedac9d3dc4e189a25ef9d908', 'quantity': 'petites', 'quantityLem': 'petit', 'pack': ['MUF.w80'], 'type': 'food', 'gtin': '', 'gtinRef': '', 'brand': '', 'time': '', 'event': 'declaration', 'serving': '', 'posiNormName': 7}, {'name': 'Croissant au Jambon', 'normName': ' croissant jambon ', 'comment': '', 'normComment': '', 'rank': 212, 'id': 'CIQ#8cd4fb25e8fd9b214dc8f8ca0dfd4d1a', 'quantity': 'un', 'quantityLem': '1', 'pack': ['VIE.w170'], 'type': 'food', 'gtin': '', 'gtinRef': '', 'brand': '', 'time': 'dinner', 'event': 'declaration', 'serving': 'VIE-100', 'posiNormName': 0}], 'activity': [], 'response': {}}, 'cputime': 2.9399993419647217}
----------------------------------------------------------------------------------
LLM CPU Time: 2.9399993419647217