Input path: /home/debian/html/nutritwin/output_llm/690b8a46ab393/input.json
Output path: /home/debian/html/nutritwin/output_llm/690b8a46ab393/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/690b8a46ab393/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": "compote de pommes",
        "quantity": "une portion",
        "type": "food",
        "event": "declaration",
        "brand": "Charles & Alice",
        "timeOfTheDay": "snacking"
    },
    {
        "name": "compote d'ananas",
        "quantity": "une portion",
        "type": "food",
        "event": "declaration",
        "brand": "Charles & Alice",
        "timeOfTheDay": "snacking"
    }
]
-----------------------------------------------------------------------------

----------------- Make it compliant ------------------
[
    {
        "name": "compote de pommes",
        "quantity": "une portion",
        "type": "food",
        "event": "declaration",
        "brand": "Charles & Alice",
        "timeOfTheDay": "snacking"
    },
    {
        "name": "compote d'ananas",
        "quantity": "une portion",
        "type": "food",
        "event": "declaration",
        "brand": "Charles & Alice",
        "timeOfTheDay": "snacking"
    }
]
------------------------------------------------------

------------------------ After simplification ------------------------
[
    {
        "name": "compote de pommes",
        "quantity": "une portion",
        "type": "food",
        "event": "declaration",
        "brand": "Charles & Alice",
        "timeOfTheDay": "snacking"
    },
    {
        "name": "compote d'ananas",
        "quantity": "une portion",
        "type": "food",
        "event": "declaration",
        "brand": "Charles & Alice",
        "timeOfTheDay": "snacking"
    }
]
----------------------------------------------------------------------

--------------------------------- LLM result -----------------------------------
{'response': [{'name': 'compote de pommes', 'quantity': 'une portion', 'type': 'food', 'event': 'declaration', 'brand': 'Charles & Alice', 'timeOfTheDay': 'snacking'}, {'name': "compote d'ananas", 'quantity': 'une portion', 'type': 'food', 'event': 'declaration', 'brand': 'Charles & Alice', 'timeOfTheDay': 'snacking'}], 'cost': 0.0}
--------------------------------------------------------------------------------

----------- result to be analyzed -----------
{'name': 'compote de pommes', 'quantity': 'une portion', 'type': 'food', 'event': 'declaration', 'brand': 'Charles & Alice', 'timeOfTheDay': 'snacking'}

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 '% compote de pomme %' AND V_NormTrademark LIKE '%charles alice%' 


------------- Found solution (max 20) --------------
Compote de Pomme -  compote de pomme  -  - Charles & Alice - 0 - 3288310842207 - 3288310842207 - OFF#7197d9a43998f7d53f54210dcb248b33
Compote de Pommes Allégée en Sucres -  compote de pomme allegee en sucre  -  - Charles & Alice - 0 - 3288310843662 - 3288310843662 - OFF#63444a85bbd757da90a6e9a7e5b00c09
Compote de Pommes sans Sucres Ajoutés -  compote de pomme san sucre ajoute  -  - Charles & Alice - 0 - 3297760097303 - 3297760097303 - OFF#cf559c3f26c49e0aae684e88f197c30a
Compote de Pomme Fraises Allégée en Sucres -  compote de pomme fraise allegee en sucre  -  - Charles & Alice - 0 - 3288310845284 - 3288310845284 - OFF#4268655797efddf14266c7a43b893b34
Compote de Pommes et Fraises Allégée en Sucre -  compote de pomme fraise allegee en sucre  -  - Charles & Alice - 0 - 3288310849459 - 3288310845284 - OFF#005c8f8ae0ee9d3b864ecea9d35d4b09
----------------------------------------------------

ERROR: no solution for picto in the first solution

----------- result to be analyzed -----------
{'name': "compote d'ananas", 'quantity': 'une portion', 'type': 'food', 'event': 'declaration', 'brand': 'Charles & Alice', 'timeOfTheDay': 'snacking'}

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 '% compote anana %' AND V_NormTrademark LIKE '%charles alice%' 

--> CPU time in DB: 0.1633 seconds
Word: Compote Ananas  -  dist: 0.4204677939414978  -  row: 56602
Word: Compote Pomme Ananas  -  dist: 0.46703222393989563  -  row: 14888
Word: Ananas en Compote  -  dist: 0.4836498498916626  -  row: 3026
Word: Compotée Ananas au Rhum  -  dist: 0.5168452262878418  -  row: 8926
Word: Compote Pommes Ananas Avec Morceaux sans Sucres Ajoutés  -  dist: 0.5308796167373657  -  row: 39482
Found embedding word: Compote Ananas

Second try (embedded):
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_Name = 'Compote Ananas'


------------- Found solution (max 20) --------------
Compote Ananas -  compote anana  -  - group Bel - 0 - 5410046018849 - 5410046018849 - OFF#b5f73e5cec75fd41b2e45c2ac8d2401b
----------------------------------------------------

ERROR: no solution for picto in the first solution

--------------------------------- final result -----------------------------------
{'prompt': '', 'model': 'mistral-large-2411', 'imagePath': '/home/debian/html/nutritwin/output_llm/690b8a46ab393/capture.jpg', 'intents': ['Identify foods and beverages in an image'], 'solutions': {'nutrition': [{'name': 'Compote de Pomme', 'normName': ' compote de pomme ', 'comment': '', 'normComment': '', 'rank': 0, 'id': 'OFF#7197d9a43998f7d53f54210dcb248b33', 'quantity': 'une portion', 'quantityLem': '1 portion', 'pack': ['YA1.w125'], 'type': 'food', 'gtin': '3288310842207', 'gtinRef': '3288310842207', 'brand': 'Charles & Alice', 'time': 'snacking', 'event': 'declaration', 'serving': '', 'posiNormName': 0}, {'name': 'Compote Ananas', 'normName': ' compote anana ', 'comment': '', 'normComment': '', 'rank': 0, 'id': 'OFF#b5f73e5cec75fd41b2e45c2ac8d2401b', 'quantity': 'une portion', 'quantityLem': '1 portion', 'pack': ['YA1.w125'], 'type': 'food', 'gtin': '5410046018849', 'gtinRef': '5410046018849', 'brand': 'group Bel', 'time': 'snacking', 'event': 'declaration', 'serving': '', 'posiNormName': 0}], 'activity': [], 'response': {}}, 'cputime': 4.680950164794922}
----------------------------------------------------------------------------------
LLM CPU Time: 4.680950164794922