Input path: /home/debian/html/nutritwin/output_llm/6894cadd8503b/input.json
Output path: /home/debian/html/nutritwin/output_llm/6894cadd8503b/output.json
Input text: Frais.
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: Frais.
==================================================================================================================================
==================================== 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: ###Frais.###.
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 : """Frais.""" 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": "frais",
"type": "food",
"event": "unknown"
}
]
-----------------------------------------------------------------------------
----------------- Make it compliant ------------------
[
{
"name": "frais",
"type": "food",
"event": "unknown"
}
]
------------------------------------------------------
------------------------ After simplification ------------------------
[
{
"name": "frais",
"type": "food",
"event": "unknown"
}
]
----------------------------------------------------------------------
--------------------------------- LLM result -----------------------------------
{'response': [{'name': 'frais', 'type': 'food', 'event': 'unknown'}], 'cost': 0.09461999999999998}
--------------------------------------------------------------------------------
----------- result to be analyzed -----------
{'name': 'frais', 'type': 'food', 'event': 'unknown'}
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 '% frai %' AND (V_NormTrademark = '' OR V_NormTrademark IS NULL)
------------- Found solution (max 20) --------------
Lard Frais - lard frai - - - 81 - - - KCA#2df11b8994d12c2a8f38ae45b587008d
Thon Frais Grillé - thon frai grille - frais grillé - - 0 - - - KCA#ef5c8ee3898db16000e8fb04965a7ae3
Thon Frais à la Génoise - thon frai genoise - la génoise - - 0 - - - KCA#20f3229ef0ba1c06df6e400c3369bf71
Ananas Frais - anana frai - - - 12364 - - - KCA#acf1ae54036ef4c5465f0dda8fd7cffd
Chèvre Frais - chevre frai - - - 1780 - - - KCA#d52f23e88ffb98d7eb730bc8c40b315b
Hareng Frais - hareng frai - - - 31 - - - KCA#fea33234d7a64cd0e82ce8454ea27908
Persil Frais - persil frai - - - 0 - - - KCA#7290c8b50f37041789c140f8b2b14147
Anchois Frais - anchoi frai - - - 99 - - - KCA#534a407309dd6bd2fb3c5a78bda28309
Abricot Frais - abricot frai - - - 12951 - - - KCA#ae0959ad3e09e2f660d26aff2e8c5458
Fromage Frais 0% MG - fromage frai 0% mg - - - 519 - - - KCA#88f1992eded597fa4d19465f74683774
Fromage Frais 30% MG - fromage frai 30% mg - - - 145 - - - KCA#7925728898a08e85f13745b60bc71320
Fromage Frais 20% MG - fromage frai 20% mg - - - 81 - - - KCA#0c277d2e26315ef0b610a1ac6f0b2c8f
Raviolis Frais au Boeuf - ravioli frai boeuf - - - 136 - - - KCA#3760c4332a73affe55b5b3e5bb9a7d1a
Raviolis Frais au Jambon - ravioli frai jambon - - - 113 - - - KCA#bcef1965f56a42bc053acdd28bf2624e
Raviolis Frais aux Fromages - ravioli frai au fromage - - - 85 - - - KCA#02b9435d3965af9d128c27c7c5a0f1a8
Raviolis Frais aux Epinards - ravioli frai au epinard - - - 76 - - - KCA#0933097fa2901b5e5e0e29590a3b0b95
Raviolis Frais Ricotta-epinards - ravioli frai ricotta epinard - - - 362 - - - KCA#08bd3dee018c7d1de7780e83157db3bb
Fromage Frais Type Petit Suisse - fromage frai type petit suisse - aux fruits, 2-3% MG - - 0 - - - CIQ#73cdc0ed06d7dae14d8f4af7f1d26d08
Fromage Frais Type Petit Suisse - fromage frai type petit suisse - nature, 4% MG environ - - 0 - - - CIQ#96495c393b505ed2542b7b6e7722a0ff
Fromage Frais Type Petit Suisse - fromage frai type petit suisse - nature, 10% MG environ - - 0 - - - CIQ#09070ff74775e5fa93151b578a83b59c
----------------------------------------------------
ERROR: Wrong quantity: ''
ERROR: no solution for picto in the first solution
--------------------------------- final result -----------------------------------
{'prompt': 'Frais.', 'model': 'mistral-large-2411', 'imagePath': '', 'intents': ['Identify food and beverage consumption or declaration'], 'solutions': {'nutrition': [{'name': 'Lard Frais', 'normName': ' lard frai ', 'comment': '', 'normComment': '', 'rank': 81, 'id': 'KCA#2df11b8994d12c2a8f38ae45b587008d', 'quantity': '', 'quantityLem': '', 'pack': ['TR5.w50'], 'type': 'food', 'gtin': '', 'gtinRef': '', 'brand': '', 'time': '', 'event': 'unknown', 'serving': '', 'posiNormName': 5}], 'activity': [], 'response': {}}, 'cputime': 1.9875998497009277}
----------------------------------------------------------------------------------
LLM CPU Time: 1.9875998497009277