Input path: /home/debian/html/nutritwin/output_llm/67e91e4781f27/input.json
Output path: /home/debian/html/nutritwin/output_llm/67e91e4781f27/output.json
Input text: J'ai mangé une telle de sept aussi.
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: J'ai mangé une telle de sept aussi.
==================================================================================================================================
==================================== 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: ###J'ai mangé une telle de sept aussi.###.
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 : """J'ai mangé une telle de sept aussi.""" 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: .
@prefix rdfs: .
@prefix xsd: .
@prefix owl: .
@prefix 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": "",
"quantity": "sept",
"cookingMethod": "",
"timeOfTheDay": "",
"company": "",
"type": "",
"event": "declaration"
}
]
-----------------------------------------------------------------------------
----------------- Make it compliant ------------------
[
{
"name": "",
"quantity": "sept",
"cookingMethod": "",
"timeOfTheDay": "",
"company": "",
"type": "",
"event": "declaration"
}
]
------------------------------------------------------
------------------------ After simplification ------------------------
[
{
"name": "",
"quantity": "sept",
"cookingMethod": "",
"timeOfTheDay": "",
"company": "",
"type": "",
"event": "declaration"
}
]
----------------------------------------------------------------------
--------------------------------- LLM result -----------------------------------
{'response': [{'name': '', 'quantity': 'sept', 'cookingMethod': '', 'timeOfTheDay': '', 'company': '', 'type': '', 'event': 'declaration'}], 'cost': 0.09869999999999998}
--------------------------------------------------------------------------------
----------- result to be analyzed -----------
{'name': '', 'quantity': 'sept', 'cookingMethod': '', 'timeOfTheDay': '', 'company': '', 'type': '', '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 '%%' AND (V_NormTrademark = '' OR V_NormTrademark IS NULL)
------------- Found solution (max 20) --------------
Eau - eau - - - 10064 - - - KCA#08cfe774cbf7476b1e582734c7082ecd
Gin - gin - - - 305 - - - CIQ#94521206bf4c275eb265a86ea6036082
Ipa - ipa - - - 0 - - - KCA#ebd50d5b6b6cb2ec8bfa3e6a8bdeba4d
Ail - ail - cru - - 0 - - - CIQ#5b43141446e8d43dd8a8533ef7df0a78
Ris - ri - agneau - - 0 - - - CIQ#1c34fab892076c406949cd124c6de767
Mil - mil - non salé - - 0 - - - CIQ#423cec13a11d0bc53abfde877718ee1d
Ail - ail - rôti/cuit au four - - 0 - - - CIQ#fc72e8a70a284f71c96dc85627daf0c0
Ris - ri - veau, braisé ou sauté/poêlé - - 0 - - - CIQ#e3826facfe30a4f4b86d24f31899fe03
Oie - oie - viande, rôtie/cuite au four - - 0 - - - CIQ#6e7b58f3808a5c893520bfef929da2e5
Ail - ail - sauté/poêlé, sans matière grasse - - 0 - - - CIQ#dfc4bebee78432f8420f5de7a7e744b2
Dés - de - allumettes, râpé ou haché de jambon - - 0 - - - CIQ#02dc641768c9e88837b342007b780d77
Oie - oie - viande et peau, rôtie/cuite au four - - 0 - - - CIQ#d5e2c38b4d8c1dfeebdea850c2770bd5
Dés - de - allumettes, râpé ou haché de jambon de volaille - - 0 - - - CIQ#f292e1e4204c44fc64784fd3360ff924
Riz - riz - mélange de variétés, blanc, complet, rouge, sauvage,., cru - - 0 - - - CIQ#a07819c9749e64bb8fdf05c82933f975
Pain - pain - - - 261532 - - - CIQ#78316c0b820d8f80c640c9d0bc741c50
Noix - noix - - - 9716 - - - KCA#c906c6893ddeb4160c6962e435a64070
Feta - feta - - - 4690 - - - KCA#836376d4d946da7f776d2aecb0221de2
Chou - chou - - - 1970 - - - KCA#03da66f29a5aea409ea105a6a4386e78
Rhum - rhum - - - 1579 - - - CIQ#9888ebb293c4f80dfa7fe483c8c794ed
Bleu - bleu - - - 1163 - - - KCA#b198b5549d924f8c47b17936f7f6b0cd
----------------------------------------------------
--------------------------------- final result -----------------------------------
{'prompt': "J'ai mangé une telle de sept aussi.", 'model': 'mistral-large-2411', 'imagePath': '', 'intents': ['Identify food and beverage consumption or declaration'], 'solutions': {'nutrition': [{'name': 'Eau', 'normName': ' eau ', 'comment': '', 'normComment': '', 'rank': 10064, 'id': 'KCA#08cfe774cbf7476b1e582734c7082ecd', 'quantity': 'sept', 'quantityLem': '7', 'pack': ['VAE', 'VX1', 'VA2', 'GOB', 'VA4', 'VA4', 'VA3'], 'type': '', 'gtin': '', 'gtinRef': '', 'brand': '', 'time': '', 'event': 'declaration', 'serving': 'VAE-700', 'posiNormName': 0}], 'activity': [], 'response': {}}, 'cputime': 2.2003426551818848}
----------------------------------------------------------------------------------
LLM CPU Time: 2.2003426551818848