Input path: /home/debian/html/nutritwin/output_llm/68f2283e58453/input.json
Output path: /home/debian/html/nutritwin/output_llm/68f2283e58453/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/68f2283e58453/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": "tomates cerises",
        "quantity": "plusieurs",
        "cookingMethod": "cru",
        "type": "food",
        "event": "declaration"
    },
    {
        "name": "mozzarella",
        "quantity": "plusieurs boules",
        "cookingMethod": "cru",
        "type": "food",
        "event": "declaration"
    },
    {
        "name": "basilic",
        "quantity": "quelques feuilles",
        "cookingMethod": "cru",
        "type": "food",
        "event": "declaration"
    }
]
-----------------------------------------------------------------------------

----------------- Make it compliant ------------------
[
    {
        "name": "tomates cerises",
        "quantity": "plusieurs",
        "cookingMethod": "cru",
        "type": "food",
        "event": "declaration"
    },
    {
        "name": "mozzarella",
        "quantity": "plusieurs boules",
        "cookingMethod": "cru",
        "type": "food",
        "event": "declaration"
    },
    {
        "name": "basilic",
        "quantity": "quelques feuilles",
        "cookingMethod": "cru",
        "type": "food",
        "event": "declaration"
    }
]
------------------------------------------------------

------------------------ After simplification ------------------------
[
    {
        "name": "tomates cerises",
        "quantity": "plusieurs",
        "cookingMethod": "cru",
        "type": "food",
        "event": "declaration"
    },
    {
        "name": "mozzarella",
        "quantity": "plusieurs boules",
        "cookingMethod": "cru",
        "type": "food",
        "event": "declaration"
    },
    {
        "name": "basilic",
        "quantity": "quelques feuilles",
        "cookingMethod": "cru",
        "type": "food",
        "event": "declaration"
    }
]
----------------------------------------------------------------------

--------------------------------- LLM result -----------------------------------
{'response': [{'name': 'tomates cerises', 'quantity': 'plusieurs', 'cookingMethod': 'cru', 'type': 'food', 'event': 'declaration'}, {'name': 'mozzarella', 'quantity': 'plusieurs boules', 'cookingMethod': 'cru', 'type': 'food', 'event': 'declaration'}, {'name': 'basilic', 'quantity': 'quelques feuilles', 'cookingMethod': 'cru', 'type': 'food', 'event': 'declaration'}], 'cost': 0.0}
--------------------------------------------------------------------------------

----------- result to be analyzed -----------
{'name': 'tomates cerises', 'quantity': 'plusieurs', 'cookingMethod': 'cru', '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 '% tomate cerise %' AND (V_NormTrademark = '' OR V_NormTrademark IS NULL)


------------- Found solution (max 20) --------------
Tomate Cerise -  tomate cerise  - crue -  - 0 -  -  - CIQ#9f76e2172737f480f1c9b66f3627bfb0
Tomate Cerise -  tomate cerise  - tomate cerise -  - 0 -  -  - KCA#fc7d1647e177b261c9a22262037f6216
Tomates Cerises Rôties aux Broccolinis -  tomate cerise rotie au broccolini  - et graines de citrouille -  - 7 -  -  - KCA#b4e4bc20b89f5f2678a4843a5d0f40ea
----------------------------------------------------

ERROR: no solution for picto in the first solution
ERROR: no solution for picto in the first solution

----------- result to be analyzed -----------
{'name': 'mozzarella', 'quantity': 'plusieurs boules', 'cookingMethod': 'cru', '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 '% mozzarella %' AND (V_NormTrademark = '' OR V_NormTrademark IS NULL)


------------- Found solution (max 20) --------------
Raviolis Frais Mozzarella, Aubergines, Tomates -  ravioli frai mozzarella aubergine tomate  -  -  - 106 -  -  - KCA#d4f4e3a8c39b3ea26608b7b1be1e7382
----------------------------------------------------

ERROR: no solution for picto in the first solution

----------- result to be analyzed -----------
{'name': 'basilic', 'quantity': 'quelques feuilles', 'cookingMethod': 'cru', '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 '% basilic %' AND (V_NormTrademark = '' OR V_NormTrademark IS NULL)


------------- Found solution (max 20) --------------
Basilic -  basilic  - frais -  - 213 -  -  - CIQ#c3209fdb22917e746ba7b72c2fadd92e
Basilic -  basilic  - séché -  - 0 -  -  - CIQ#32ae428ee27457039c54d8808c40bb3f
Foie de Veau au Basilic -  foie de veau basilic  -  -  - 2 -  -  - KCA#6d285bccd633e34f89ac69fe5fe86687
Mouliné Tomate / Basilic -  mouline tomate basilic  -  -  - 0 -  -  - KCA#b6513c63f84e7a5a61f9e5901f796b89
Purée de Tomate au Basilic -  puree de tomate basilic  -  -  - 29 -  -  - KCA#04648cc2d8d08621e97f44cd26f33635
Crevettes Sautées au Basilic -  crevette sautee basilic  -  -  - 286 -  -  - KCA#717c940acdb428fe12f9aabee135b0b0
----------------------------------------------------

ERROR: no solution for picto in the first solution
ERROR: no solution for picto in the first solution

--------------------------------- final result -----------------------------------
{'prompt': '', 'model': 'mistral-large-2411', 'imagePath': '/home/debian/html/nutritwin/output_llm/68f2283e58453/capture.jpg', 'intents': ['Identify foods and beverages in an image'], 'solutions': {'nutrition': [{'name': 'Tomate Cerise', 'normName': ' tomate cerise ', 'comment': 'crue', 'normComment': ' crue ', 'rank': 0, 'id': 'CIQ#9f76e2172737f480f1c9b66f3627bfb0', 'quantity': 'plusieurs', 'quantityLem': 'plusieur', 'pack': ['CER.w150'], 'type': 'food', 'gtin': '', 'gtinRef': '', 'brand': '', 'time': '', 'event': 'declaration', 'serving': '', 'posiNormName': 0}, {'name': 'Raviolis Frais Mozzarella, Aubergines, Tomates', 'normName': ' ravioli frai mozzarella aubergine tomate ', 'comment': '', 'normComment': '', 'rank': 106, 'id': 'KCA#d4f4e3a8c39b3ea26608b7b1be1e7382', 'quantity': 'plusieurs boules', 'quantityLem': 'plusieur boule', 'pack': ['RAV.w150'], 'type': 'food', 'gtin': '', 'gtinRef': '', 'brand': '', 'time': '', 'event': 'declaration', 'serving': '', 'posiNormName': 13}, {'name': 'Basilic', 'normName': ' basilic ', 'comment': 'frais', 'normComment': ' frai ', 'rank': 213, 'id': 'CIQ#c3209fdb22917e746ba7b72c2fadd92e', 'quantity': 'quelques feuilles', 'quantityLem': 'quelque feuille', 'pack': ['XXX.w20'], 'type': 'food', 'gtin': '', 'gtinRef': '', 'brand': '', 'time': '', 'event': 'declaration', 'serving': '', 'posiNormName': 0}], 'activity': [], 'response': {}}, 'cputime': 4.160852909088135}
----------------------------------------------------------------------------------
LLM CPU Time: 4.160852909088135