Input path: /home/debian/html/nutritwin/output_llm/670a838aec984/input.json
Output path: /home/debian/html/nutritwin/output_llm/670a838aec984/output.json
Input text: Quelques grains de raisin.
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: Quelques grains de raisin.
==================================================================================================================================
==================================== 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: ###Quelques grains de raisin.###.
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 : """Quelques grains de raisin.""" 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 beverage identifier, the name should not contain information related to quantity or container (like glass...)."@en;
rdfs:comment "Ignore food or beverage when it is not consumed in the past, now or in the future."@en;
rdfs:comment "The cooking mode is not in the name. 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."@en;
rdfs:comment "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.
"""
=========================================================================================
------------------------------ LLM Raw response -----------------------------
```json
[
{
"name": "raisin",
"quantity": "quelques grains",
"type": "food",
"event": "declaration"
}
]
```
-----------------------------------------------------------------------------
----------------- Make it compliant ------------------
```json
[
{
"name": "raisin",
"quantity": "quelques grains",
"type": "food",
"event": "declaration"
}
]
```
------------------------------------------------------
------------------------ After simplification ------------------------
[ { "name": "raisin", "quantity": "quelques grains", "type": "food", "event": "declaration" }]
----------------------------------------------------------------------
--------------------------------- LLM result -----------------------------------
{'response': [{'name': 'raisin', 'quantity': 'quelques grains', 'type': 'food', 'event': 'declaration'}], 'cost': 0.0}
--------------------------------------------------------------------------------
----------- result to be analyzed -----------
{'name': 'raisin', 'quantity': 'quelques grains', '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 '% raisin %' AND (V_NormTrademark = '' OR V_NormTrademark IS NULL)
------------- Found solution (max 20) --------------
Raisin - raisin - sec - - 3301 - - - CIQ#b4259d01a33e32c5013efafd8431d795
Raisins Secs - raisin sec - - - 0 - - - KCA#1629eba3d871ec3e0fd5431f9291bf6d
Raisin Blanc - raisin blanc - à gros grain, type Italia ou Dattier, cru - - 0 - - - CIQ#2fdb7b01fab3eb180fcd7f614d97e68f
Raisin Chasselas - raisin chassela - cru - - 0 - - - CIQ#540cb502316f69468904e34e0af965e3
Raisin Noir Frais - raisin noir frai - - - 768 - - - KCA#4bf363f94f08fb0f38b13e0bfb2f5857
Raisin Noir Muscat - raisin noir muscat - cru - - 0 - - - CIQ#0cec10f8c2fc25b05d0a26ab7921f852
Pain au Raisin - pain raisin - - - 1786 - - - KCA#553835be3dd8de0a372815e6d0eb7399
Jus de Raisin - ju de raisin - pur jus - - 0 - - - CIQ#17080b63b0236dd627893c70c6cfd9b6
Jus de Raisin - ju de raisin - à base de concentré - - 0 - - - CIQ#4a8a96807435d75264e1ad52cb69dcc2
Tarte au Raisin - tarte raisin - au raisin - - 0 - - - KCA#1cf2c3141d8378920fc495d980ab806e
Jus de Raisin Noir et Poire - ju de raisin noir poire - - - 1 - - - KCA#df5169d83aaa4341013aefe547c854e0
Pain aux Raisins - pain au raisin - viennoiserie - - 0 - - - CIQ#9e67ae293093774fb909e93ebebbad70
Faisan aux Raisins - faisan au raisin - - - 1 - - - KCA#bcd92953f110e16e960e1b526d85d99d
Pigeons aux Raisins - pigeon au raisin - - - 2 - - - KCA#a6791e0bdaf470d03ed6aa2a6d3e6248
Jus de Kiwi et Raisin Blanc - ju de kiwi raisin blanc - - - 83 - - - KCA#9afe1c1fee0f95f35bb04712f31fb9e8
Pain Avec des Raisins - pain avec de raisin - - - 313 - - - KCA#b3d22a15de728eb6fae5884093730c96
Huile de Pépins de Raisin - huile de pepin de raisin - - - 60 - - - CIQ#a8565e3927893c601646df098f444205
Pain de Seigle aux Raisins - pain de seigle au raisin - - - 267 - - - KCA#713622ef4e191b70a42bdf4313b99401
Foie de Canard aux Raisins - foie de canard au raisin - - - 7 - - - KCA#42f226eb97896c4adca6e90d2fc0f14d
Gâteau de Semoule aux Raisins et Caramel - gateau de semoule au raisin caramel - - - 0 - - - CIQ#7600ca98415ad5d02089e76a9cf96f32
----------------------------------------------------
ERROR: no solution for picto in the first solution
--------------------------------- final result -----------------------------------
{'prompt': 'Quelques grains de raisin.', 'intents': ['Identify food consumption or declaration'], 'model': 'gpt-4o-2024-05-13', 'solutions': {'nutrition': [{'name': 'Raisin', 'normName': ' raisin ', 'comment': 'sec', 'normComment': ' sec ', 'rank': 3301, 'id': 'CIQ#b4259d01a33e32c5013efafd8431d795', 'quantity': 'quelques grains', 'quantityLem': 'quelque grain', 'pack': ['POG.w15'], 'type': 'food', 'gtin': '', 'gtinRef': '', 'brand': '', 'time': '', 'event': 'declaration', 'serving': '', 'posiNormName': 0}], 'activity': [], 'response': {}}, 'cputime': 1.5067830085754395}
----------------------------------------------------------------------------------
LLM CPU Time: 1.5067830085754395