Input path: /home/debian/html/nutritwin/output_llm/67ae3f0c97dcd/input.json
Output path: /home/debian/html/nutritwin/output_llm/67ae3f0c97dcd/output.json
Input text: 
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: 
==================================================================================================================================
Image to be analyzed: /home/debian/html/nutritwin/output_llm/67ae3f0c97dcd/capture.jpg
##############################################################################################
#   For image extraction, pixtral-large-2411 is used    #
##############################################################################################

==================================== Prompt =============================================
In the image, identify all the foods and beverages, convert them into an array of JSON with consumed foods.
Ignore what it is not connected to nutrition, beverage or food. 
When a food or a beverage has several instances unify them on a single food or beverage and add the quantities of each.
The attribute name must remain in English but the result, so the attribute value, must be in french, and only in french.

Provide a solution without explanation.

Use only the food & beverage 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": "Ferrero Rocher",
        "quantity": "un",
        "type": "food",
        "event": "declaration",
        "timeOfTheDay": "snacking",
        "brand": "Ferrero",
        "company": "Ferrero"
    }
]
-----------------------------------------------------------------------------

----------------- Make it compliant ------------------
[
    {
        "name": "Ferrero Rocher",
        "quantity": "un",
        "type": "food",
        "event": "declaration",
        "timeOfTheDay": "snacking",
        "brand": "Ferrero",
        "company": "Ferrero"
    }
]
------------------------------------------------------

------------------------ After simplification ------------------------
[
    {
        "name": "Ferrero Rocher",
        "quantity": "un",
        "type": "food",
        "event": "declaration",
        "timeOfTheDay": "snacking",
        "brand": "Ferrero",
        "company": "Ferrero"
    }
]
----------------------------------------------------------------------

--------------------------------- LLM result -----------------------------------
{'response': [{'name': 'Ferrero Rocher', 'quantity': 'un', 'type': 'food', 'event': 'declaration', 'timeOfTheDay': 'snacking', 'brand': 'Ferrero', 'company': 'Ferrero'}], 'cost': 0.0}
--------------------------------------------------------------------------------

----------- result to be analyzed -----------
{'name': 'Ferrero Rocher', 'quantity': 'un', 'type': 'food', 'event': 'declaration', 'timeOfTheDay': 'snacking', 'brand': 'Ferrero', 'company': 'Ferrero'}

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 '% rocher %' AND V_NormTrademark LIKE '%ferrero%' 


------------- Found solution (max 20) --------------
Rocher -  rocher  -  - Ferrero - 0 - 4008400163826 - 4008400163826 - OFF#f18993f6bd32b13f5de230cd459f8895
Rocher T18 Cube -  rocher t18 cube  -  - Ferrero - 0 - 8000500149812 - 8000500149812 - OFF#dd2245335080575947bde4fdfb78d7eb
Rocher Zartbitter Haselnuss -  rocher zartbitter haselnus  -  - Ferrero - 0 - 8000500359815 - 8000500359815 - OFF#7ad91cdd5aff894b868304a8d2351eec
Avello Rochers -  avello rocher  -  - Ferrero - 0 - 3588400259190 - 3588400259190 - OFF#4c2a443340e28ef53874840a906ce4c0
Ferrero Rocher -  ferrero rocher  -  - Ferrero - 0 - 8000500009673 - 8000500009673 - OFF#0d78f262ddb18b7322f1c67677a87e14
Ferrero Rocher -  ferrero rocher  -  - Ferrero - 0 - 8000500296486 - 8000500009673 - OFF#3c7f9791cc308a694bbef535efaf23bc
Ferrero Rocher -  ferrero rocher  -  - Ferrero - 0 - 8000500363539 - 8000500009673 - OFF#0743ec77dc331470dc8bc404e858fbbe
Ferrero Rocher -  ferrero rocher  -  - Ferrero - 0 - 8000500313183 - 8000500009673 - OFF#971bb6d4dde4112e7e385db99a1f80c7
Ferrero Rocher -  ferrero rocher  -  - Ferrero - 0 - 8000500297025 - 8000500009673 - OFF#518e8c509ab911c730d6f7ce10e34ad4
Ferrero Rocher -  ferrero rocher  -  - Ferrero - 0 - 8000500013465 - 8000500009673 - OFF#d8f2bcf080a3b2c9396a994f3db335e5
Ferrero Rocher -  ferrero rocher  -  - Ferrero - 0 - 8000500011461 - 8000500009673 - OFF#2f1362af4f9fc2db19e5f77b5c418972
Ferrero Rocher -  ferrero rocher  -  - Ferrero - 0 - 8000500170823 - 8000500009673 - OFF#03499db7f80e88af72397edfc785207d
Ferrero Rocher -  ferrero rocher  -  - Ferrero - 0 - 8000500273296 - 8000500009673 - OFF#3c5b71d7eba0b86625b9ba270217f888
Ferrero Rocher -  ferrero rocher  -  - Ferrero - 0 - 8000500084649 - 8000500009673 - OFF#aa8b1a7ba0ec5f9d969389ffd1cf1d06
Ferrero Rocher Novciola White -  ferrero rocher novciola white  -  - Ferrero - 0 - 8000500359884 - 8000500359884 - OFF#cbeed71ca1771cb236f1ae12f73fd516
Ferrero Rocher Heart Box 4 Pack -  ferrero rocher heart bo pack  -  - Ferrero - 0 - 8000500216712 - 8000500216712 - OFF#bb91a2fb9500e437c0ff57af7b834f30
Ferrero Rocher Fines Gaufrettes Enrobées de Chocolat -  ferrero rocher fine gaufrette enrobee de chocolat  -  - Ferrero - 0 - 8000500032237 - 8000500032237 - OFF#5c52eec23183d75c7b18d41765b7bfbb
Ferrero Rocher Gaufrettes Chocolat au Lait et Fourrées Noisettes Cloche6 -  ferrero rocher gaufrette chocolat lait fourree noisette cloche6  -  - Ferrero - 0 - 3017621815002 - 3017621815002 - OFF#bbbdb6e5339429e9f184557f78357fdc
Lapin Ferrero Rocher -  lapin ferrero rocher  -  - Ferrero - 0 - 4008400173825 - 4008400173825 - OFF#0eb8ef03633df4c26f29050fa2da6ec9
Grand Ferrero Rocher -  grand ferrero rocher  -  - Ferrero - 0 - 4008400660622 - 4008400660622 - OFF#5a22967f4991dfeddd61f697d989cf34
----------------------------------------------------


--------------------------------- final result -----------------------------------
{'prompt': '', 'model': 'mistral-large-2411', 'imagePath': '/home/debian/html/nutritwin/output_llm/67ae3f0c97dcd/capture.jpg', 'intents': ['Identify foods and beverages in an image'], 'solutions': {'nutrition': [{'name': 'Rocher', 'normName': ' rocher ', 'comment': '', 'normComment': '', 'rank': 0, 'id': 'OFF#f18993f6bd32b13f5de230cd459f8895', 'quantity': 'un', 'quantityLem': '1', 'pack': ['UN2.w21'], 'type': 'food', 'gtin': '4008400163826', 'gtinRef': '4008400163826', 'brand': 'Ferrero', 'time': 'snacking', 'event': 'declaration', 'serving': 'UN2-10', 'posiNormName': 0}], 'activity': [], 'response': {}}, 'cputime': 3.22816801071167}
----------------------------------------------------------------------------------
LLM CPU Time: 3.22816801071167