Input path: /home/debian/html/nutritwin/output_llm/66c4ac2cbd4dc/input.json
Output path: /home/debian/html/nutritwin/output_llm/66c4ac2cbd4dc/output.json
Input text: J'ai mangé une omelette
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 omelette
==================================================================================================================================
==================================== Prompt =============================================
Identify in this list of intents: ["Identify food consumption or declaration", "Identify the user physical activity", "Answer a nutrition question", "Other intent"], the intents of the prompt: ###J'ai mangé une omelette###.
Format the result in JSON format: {intents: []}.
=========================================================================================
------------------------------ LLM Raw response -----------------------------
```json
{
"intents": ["Identify food consumption or declaration"]
}
```
-----------------------------------------------------------------------------
----------------- Make it compliant ------------------
```json
{
"intents": ["Identify food consumption or declaration"]
}
```
------------------------------------------------------
------------------------ After simplification ------------------------
{ "intents": ["Identify food consumption or declaration"]}
----------------------------------------------------------------------
==================================== Prompt =============================================
Convert this natural language query : """J'ai mangé une omelette""" into an array in JSON of consumed foods and beverages.
Provide a solution without explanation.
Use only the 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 drink identifier, the name should not contain information related to quantity or container (like glass...). The cooking mode is not in the name. When the brand is very well-known (ex: Activia, Coca-Cola), the name is equal to the brand. Keep the same language"@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 examples in french: '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. Keep the same language"@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 'brand' is not specified and, the food or beverage is very well-known (like 'Coca-Cola'), provide the brand name in 'brand', otherwise set 'brand' to ''."@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.
"""
=========================================================================================
------------------------------ LLM Raw response -----------------------------
```json
[
{
"name": "omelette",
"quantity": "",
"cookingMethod": "",
"type": "food",
"timeOfTheDay": "",
"brand": "",
"company": "",
"event": "declaration"
}
]
```
-----------------------------------------------------------------------------
----------------- Make it compliant ------------------
```json
[
{
"name": "omelette",
"quantity": "",
"cookingMethod": "",
"type": "food",
"timeOfTheDay": "",
"brand": "",
"company": "",
"event": "declaration"
}
]
```
------------------------------------------------------
------------------------ After simplification ------------------------
[ { "name": "omelette", "quantity": "", "cookingMethod": "", "type": "food", "timeOfTheDay": "", "brand": "", "company": "", "event": "declaration" }]
----------------------------------------------------------------------
--------------------------------- LLM result -----------------------------------
{'response': [{'name': 'omelette', 'quantity': '', 'cookingMethod': '', 'type': 'food', 'timeOfTheDay': '', 'brand': '', 'company': '', 'event': 'declaration'}], 'cost': 0.0}
--------------------------------------------------------------------------------
----------- result to be analyzed -----------
{'name': 'omelette', 'quantity': '', 'cookingMethod': '', 'type': 'food', 'timeOfTheDay': '', 'brand': '', 'company': '', '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 '% omelette %' AND (V_NormTrademark = '' OR V_NormTrademark IS NULL)
------------- Found solution (max 20) --------------
Omelette - omelette - garnitures diverses : légumes, fromages, viandes..., aliment moyen - - 0 - - - CIQ#f3bd368d94304e5151916a143f87c6c4
Omelette Nature - omelette nature - - - 4230 - - - KCA#caac3b8e77b9ec6239db2083c58c2077
Omelette au Thon - omelette thon - - - 52 - - - KCA#5f614bbae59b451ec691804fbd8c3b1d
Omelette de Noël - omelette de noel - - - 28 - - - KCA#be4736d0e3ee43da3c659fd7769f3937
Omelette Espagnole - omelette espagnole - - - 611 - - - KCA#a967378e35edbd8d9a305ed995aa8105
Omelette Provençale - omelette provencale - - - 202 - - - KCA#a53a460a1303ada5f7245061d09547ec
Omelette aux Moules - omelette au moule - - - 43 - - - KCA#61a7e944219e17a767e04f150f45251c
Omelette à la Crème - omelette creme - - - 24 - - - KCA#92fa16c69f2bed36707181cb4c6da5fe
Omelette au Fromage - omelette fromage - - - 0 - - - CIQ#32e747be3e0d2f2e8e88993ebc228dcd
Omelette au Fromage - omelette fromage - - - 0 - - - KCA#32e747be3e0d2f2e8e88993ebc228dcd
Omelettes au Fromage - omelette fromage - - - 1282 - - - KCA#32e747be3e0d2f2e8e88993ebc228dcd
Omelette aux Lardons - omelette au lardon - - - 607 - - - CIQ#91e89f2662faf022d17d0a50fd266c22
Omelette Norvégienne - omelette norvegienne - - - 79 - - - KCA#5176fcbde2e1320b6e7bc64033053d4b
Omelette aux Poivrons - omelette au poivron - - - 235 - - - KCA#4cb2797259acdf22918e496fa31d18e5
Omelette aux Abricots - omelette au abricot - - - 3 - - - KCA#4db67e4e3160314b2d73d4e66510cff1
Omelette Saint-pierre - omelette saint pierre - - - 2 - - - KCA#54bc3809ce3573f3759129975c5bdfd2
Omelette aux Courgettes - omelette au courgette - - - 125 - - - KCA#4b746e9c0feef9bca3c7252301d6c95d
Omelette Sucrée Flambée - omelette sucree flambee - - - 4 - - - KCA#de9e04425035a8bdc1dc170c38ada3d6
Omelette aux Champignons - omelette au champignon - - - 763 - - - KCA#c39e92cc07d98c316d4b95491b7a8a31
Omelette à la Choucroute - omelette choucroute - - - 1 - - - KCA#7cab890452cffe55546fa515aa73d6f1
----------------------------------------------------
ERROR: Wrong quantity: ''
ERROR: no solution for picto in the first solution
--------------------------------- final result -----------------------------------
{'prompt': "J'ai mangé une omelette", 'intents': ['Identify food consumption or declaration'], 'model': 'gpt-4o-2024-05-13', 'solutions': {'nutrition': [{'name': 'Omelette', 'normName': ' omelette ', 'comment': 'garnitures diverses : légumes, fromages, viandes..., aliment moyen', 'normComment': ' garniture diverse legume fromage viandes... aliment moyen ', 'rank': 0, 'id': 'CIQ#f3bd368d94304e5151916a143f87c6c4', 'quantity': '', 'quantityLem': '', 'pack': ['OE2.w60'], 'type': 'food', 'gtin': '', 'gtinRef': '', 'brand': '', 'time': '', 'event': 'declaration', 'serving': '', 'posiNormName': 0}], 'activity': [], 'response': {}}, 'cputime': 7.829302549362183}
----------------------------------------------------------------------------------
LLM CPU Time: 7.829302549362183