Input path: /home/debian/html/nutritwin/output_llm/669fe45de2756/input.json
Output path: /home/debian/html/nutritwin/output_llm/669fe45de2756/output.json
Input text: Audine et deux oeufs durs
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: Audine et deux oeufs durs
==================================================================================================================================
==================================== 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: ###Audine et deux oeufs durs###.
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 : """Audine et deux oeufs durs""" 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": "Audine",
"quantity": "un",
"type": "beverage",
"event": "declaration"
},
{
"name": "oeuf",
"quantity": "deux",
"cookingMethod": "dur",
"type": "food",
"event": "declaration"
}
]
```
-----------------------------------------------------------------------------
----------------- Make it compliant ------------------
```json
[
{
"name": "Audine",
"quantity": "un",
"type": "beverage",
"event": "declaration"
},
{
"name": "oeuf",
"quantity": "deux",
"cookingMethod": "dur",
"type": "food",
"event": "declaration"
}
]
```
------------------------------------------------------
------------------------ After simplification ------------------------
[ { "name": "Audine", "quantity": "un", "type": "beverage", "event": "declaration" }, { "name": "oeuf", "quantity": "deux", "cookingMethod": "dur", "type": "food", "event": "declaration" }]
----------------------------------------------------------------------
--------------------------------- LLM result -----------------------------------
{'response': [{'name': 'Audine', 'quantity': 'un', 'type': 'beverage', 'event': 'declaration'}, {'name': 'oeuf', 'quantity': 'deux', 'cookingMethod': 'dur', 'type': 'food', 'event': 'declaration'}], 'cost': 0.0}
--------------------------------------------------------------------------------
----------- result to be analyzed -----------
{'name': 'Audine', 'quantity': 'un', '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 '% audine %' AND (V_NormTrademark = '' OR V_NormTrademark IS NULL)
Second 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_NormAggr LIKE '% audine %' AND V_NormTrademark LIKE '%%'
-------------------------------------------
------ERROR--------------------------------
No solution for query: 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_NormAggr LIKE '% audine %' AND V_NormTrademark LIKE '%%'
-------------------------------------------
-------------------------------------------
----------- result to be analyzed -----------
{'name': 'oeuf', 'quantity': 'deux', 'cookingMethod': 'dur', '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 '% oeuf %' AND (V_NormTrademark = '' OR V_NormTrademark IS NULL)
------------- Found solution (max 20) --------------
Oeuf - oeuf - cru - - 177 - - - CIQ#89c78a1c04879b2ae973694f50092c79
Oeuf - oeuf - dur - - 0 - - - CIQ#fda269f79263c80adf5b9b2c3c29c1d7
Oeuf - oeuf - poché - - 0 - - - CIQ#8d04a52d9c575bdba000c6f1cf343ab0
Oeuf - oeuf - en poudre - - 0 - - - CIQ#f4b4ef030ae3fcf5bbfea0a792a9ab66
Oeuf - oeuf - à la coque - - 3414 - - - CIQ#37567ba433b1d5278fcb1a7813128c96
Oeuf - oeuf - blanc, blanc d'oeuf - - 0 - - - CIQ#f8541a0a53cfc718c4be702af74b13a6
Oeuf - oeuf - jaune, jaune d'oeuf - - 0 - - - CIQ#caff0c1a1a02e4d086dd987b784e898a
Oeuf - oeuf - au plat, frit, salé - - 0 - - - CIQ#f9852838d9a21ae4940ea5102b58e8d1
Oeuf - oeuf - blanc, blanc d'oeuf, cru - - 0 - - - CIQ#91658f86dcc6220b09b2ffc7d5e4d309
Oeuf - oeuf - jaune, jaune d'oeuf, cru - - 0 - - - CIQ#cab44469339c33f14bf4c536019e8f57
Oeuf - oeuf - au plat, sans matière grasse - - 0 - - - CIQ#36e518c64c0e0c5a908f4674e1587a9c
Oeuf - oeuf - brouillé, avec matière grasse - - 0 - - - CIQ#89ffd23269a5b9a6910f6a7bb1a17945
Oeuf - oeuf - blanc, blanc d'oeuf, en poudre - - 0 - - - CIQ#6dc23efe8a247a89ac865e3539278bb1
Oeuf - oeuf - jaune, jaune d'oeuf, en poudre - - 0 - - - CIQ#20ab10b969e15e835fce7d54c1815eeb
Oeuf Dur - oeuf dur - - - 34213 - - - KCA#0c9196f2d28e211ac0aeb81d4c9361a9
Oeuf Poché - oeuf poche - - - 645 - - - KCA#1759edc574d011bf3a8af743ed941e6e
Oeuf d'Oie - oeuf oie - cru - - 0 - - - CIQ#d5a0273c1cb314a819952b4272379b24
Oeuf Miroir - oeuf miroir - - - 11945 - - - KCA#5cf9cdac852c9777e406442fcfd51315
Oeufs Panés - oeuf pane - - - 15 - - - KCA#476eea019750878ec03fbc60bcfa9020
Oeufs Frits - oeuf frit - aux Tomates Provençales - - 13 - - - KCA#1939ad70c8a272d6285ac0509778f087
----------------------------------------------------
--------------------------------- final result -----------------------------------
{'prompt': 'Audine et deux oeufs durs', 'intents': ['Identify food consumption or declaration'], 'model': 'gpt-4o-2024-05-13', 'solutions': {'nutrition': [{'name': 'Oeuf', 'normName': ' oeuf ', 'comment': 'cru', 'normComment': ' cru ', 'rank': 177, 'id': 'CIQ#89c78a1c04879b2ae973694f50092c79', 'quantity': 'deux', 'quantityLem': '2', 'pack': ['OEU.w60'], 'type': 'food', 'gtin': '', 'gtinRef': '', 'brand': '', 'time': '', 'event': 'declaration', 'serving': 'OEU-200', 'posiNormName': 0}], 'activity': [], 'response': {}}, 'cputime': 2.779911518096924}
----------------------------------------------------------------------------------
LLM CPU Time: 2.779911518096924