Input path: /home/debian/html/nutritwin/output_llm/684337cfaedef/input.json
Output path: /home/debian/html/nutritwin/output_llm/684337cfaedef/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/684337cfaedef/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": "jus de fruits",
        "quantity": "un verre",
        "brand": "Sojasun",
        "type": "beverage",
        "event": "declaration"
    }
]
-----------------------------------------------------------------------------

----------------- Make it compliant ------------------
[
    {
        "name": "jus de fruits",
        "quantity": "un verre",
        "brand": "Sojasun",
        "type": "beverage",
        "event": "declaration"
    }
]
------------------------------------------------------

------------------------ After simplification ------------------------
[
    {
        "name": "jus de fruits",
        "quantity": "un verre",
        "brand": "Sojasun",
        "type": "beverage",
        "event": "declaration"
    }
]
----------------------------------------------------------------------

--------------------------------- LLM result -----------------------------------
{'response': [{'name': 'jus de fruits', 'quantity': 'un verre', 'brand': 'Sojasun', 'type': 'beverage', 'event': 'declaration'}], 'cost': 0.0}
--------------------------------------------------------------------------------

----------- result to be analyzed -----------
{'name': 'jus de fruits', 'quantity': 'un verre', 'brand': 'Sojasun', '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 '% ju de fruit %' AND V_NormTrademark LIKE '%sojasun%' 

--> CPU time in DB: 0.1249 seconds
Word: Jus de Fruits  -  dist: 0.3470279276371002  -  row: 3880
Word: Jus de Fruit  -  dist: 0.35959845781326294  -  row: 12085
Word: Jus de Fruit 100%  -  dist: 0.44431614875793457  -  row: 1906
Word: Jus de Fruit(s) et de Légume(s)  -  dist: 0.45855098962783813  -  row: 183
Word: Jus de Fruit au Fruigria  -  dist: 0.4616558849811554  -  row: 50768
Found embedding word: Jus de Fruits

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 = 'Jus de Fruits'


------------- Found solution (max 20) --------------
Jus de Fruits -  ju de fruit  -  -  - 51 -  -  - CIQ#a740777e72c384dcba7dd70e15139791
Jus de Fruits -  ju de fruit  -  - The Coca-Cola Company - 0 - 0067311011675 - 0067311011675 - OFF#874f81193a2d01127013c19bdb390add
Jus de Fruits -  ju de fruit  -  - The Coca-Cola Company - 0 - 0067311031673 - 0067311011675 - OFF#efb36a1a29c2ee7bd07ab2c462cac94c
Jus de Fruits -  ju de fruit  -  - The Coca-Cola Company - 0 - 9038899137270 - 0067311011675 - OFF#e93884ce362b30703fd7ced4f6ed2330
Jus de Fruits -  ju de fruit  -  - Granini France - 0 - 57315928 - 1001003920 - OFF#ef02e5fa854e4b77039160553ed9c600
Jus de Fruits -  ju de fruit  - aliment moyen -  - 768 -  -  - KCA#fdb98f58ffd5e3edc1e3418dd7ad6c33
Jus de Fruits -  ju de fruit  - pur jus, aliment moyen -  - 0 -  -  - CIQ#b9aeecd9734482f64da07c6d2edeb5af
Jus de Fruits -  ju de fruit  - à base de concentré, aliment moyen -  - 0 -  -  - CIQ#37524b76732ea5256ecd70c99282f17d
----------------------------------------------------

ERROR: no solution for picto in the first solution

--------------------------------- final result -----------------------------------
{'prompt': '', 'model': 'mistral-large-2411', 'imagePath': '/home/debian/html/nutritwin/output_llm/684337cfaedef/capture.jpg', 'intents': ['Identify foods and beverages in an image'], 'solutions': {'nutrition': [{'name': 'Jus de Fruits', 'normName': ' ju de fruit ', 'comment': '', 'normComment': '', 'rank': 0, 'id': 'OFF#874f81193a2d01127013c19bdb390add', 'quantity': 'un verre', 'quantityLem': '1 verre', 'pack': ['VX1', 'BI4', 'VA2', 'VA3', 'GOB'], 'type': 'beverage', 'gtin': '0067311011675', 'gtinRef': '0067311011675', 'brand': 'The Coca-Cola Company', 'time': '', 'event': 'declaration', 'serving': 'BI4-100', 'posiNormName': 0}], 'activity': [], 'response': {}}, 'cputime': 5.013638019561768}
----------------------------------------------------------------------------------
LLM CPU Time: 5.013638019561768