Input path: /home/debian/html/nutritwin/output_llm/66feb5ee46062/input.json
Output path: /home/debian/html/nutritwin/output_llm/66feb5ee46062/output.json
Input text: J'ai mangé une demie orange.
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 demie orange.
==================================================================================================================================
==================================== 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 demie orange.###.
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 demie orange.""" 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": "orange",
"quantity": "une demie",
"type": "food",
"event": "declaration"
}
]
```
-----------------------------------------------------------------------------
----------------- Make it compliant ------------------
```json
[
{
"name": "orange",
"quantity": "une demie",
"type": "food",
"event": "declaration"
}
]
```
------------------------------------------------------
------------------------ After simplification ------------------------
[ { "name": "orange", "quantity": "une demie", "type": "food", "event": "declaration" }]
----------------------------------------------------------------------
--------------------------------- LLM result -----------------------------------
{'response': [{'name': 'orange', 'quantity': 'une demie', 'type': 'food', 'event': 'declaration'}], 'cost': 0.0}
--------------------------------------------------------------------------------
----------- result to be analyzed -----------
{'name': 'orange', 'quantity': 'une demie', '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 '% orange %' AND (V_NormTrademark = '' OR V_NormTrademark IS NULL)
------------- Found solution (max 20) --------------
Orange - orange - pulpe, crue - - 19789 - - - CIQ#a84ec3c1b9bc46c10b639fa15eeef5f4
Orange Givrée - orange givree - - - 31 - - - KCA#78bd77a68826904b6b891043ddcc9d5a
Orange Pressée - orange pressee - - - 3137 - - - KCA#d951c9057cfe647b69b7f30181322ad1
Jus d'Orange - ju orange - - - 52983 - - - KCA#da7a1f81a8cd82dbbbbbedf56a167258
Jus d'Orange - ju orange - pur jus - - 0 - - - CIQ#a4328be11b7e0fb0c4474532724cf38f
Jus d'Orange - ju orange - à base de concentré - - 0 - - - CIQ#72928c242781a6ee15266175037b3fb8
Jus d'Orange Pasteurisé - ju orange pasteurise - - - 44 - - - KCA#8dc9e7ac955777e77122f7bd97350613
Jus d'Orange et Gingembre - ju orange gingembre - - - 31 - - - KCA#ac517779183d5fdeff117cfe8eb4be98
Jus d'Orange, Mangue et Fraise - ju orange mangue fraise - - - 60 - - - KCA#12cc18043b0813e5110bb808101edc8e
Jus Orange Pamplemousse Pressés - ju orange pamplemousse presse - - - 517 - - - KCA#e606e760b12355e0cc070fbf069b4261
Jus d'Orange, Carotte et Céleri - ju orange carotte celeri - - - 117 - - - KCA#ba4cb33c47a671db82eeaad9ddd5c63e
Jus d'Orange, Gingembre et Ananas - ju orange gingembre anana - - - 6 - - - KCA#e2edd8bdeebd69177ece6caee7f071d8
Jus d'Orange, Carotte et Gingembre - ju orange carotte gingembre - - - 73 - - - KCA#0c209cbc5beac761ddcf7ea316e5b29e
Jus d'Orange, Ananas et Glace au Melon - ju orange anana glace melon - - - 21 - - - KCA#3e4e71456576da23059304f3eba50c9c
Gin Orange - gin orange - - - 11 - - - KCA#69422eafcd803a4841e22ba7a24dbeaf
Vodka Orange - vodka orange - - - 303 - - - KCA#afee6734db3389d9a53ba62d8e345e8e
Tarte à l'Orange - tarte orange - à l'orange - - 0 - - - KCA#8cf553da1e0c3135218833739419ea98
Salade d'Oranges - salade orange - - - 71 - - - KCA#a7fe61d6cb0d6c12eba4ca95e0f74781
Dorade à l'Orange - dorade orange - - - 76 - - - KCA#f37ceb94004879aa0221259fea9ea8bd
Canard à l'Orange - canard orange - - - 33 - - - KCA#42651abfdc29355ec0cf7e410b802f1a
----------------------------------------------------
--------------------------------- final result -----------------------------------
{'prompt': "J'ai mangé une demie orange.", 'intents': ['Identify food consumption or declaration'], 'model': 'gpt-4o-2024-05-13', 'solutions': {'nutrition': [{'name': 'Orange', 'normName': ' orange ', 'comment': 'pulpe, crue', 'normComment': ' pulpe crue ', 'rank': 19789, 'id': 'CIQ#a84ec3c1b9bc46c10b639fa15eeef5f4', 'quantity': 'une demie', 'quantityLem': '1/2', 'pack': ['ORA.w200'], 'type': 'food', 'gtin': '', 'gtinRef': '', 'brand': '', 'time': '', 'event': 'declaration', 'serving': 'ORA-50', 'posiNormName': 0}], 'activity': [], 'response': {}}, 'cputime': 1.4782967567443848}
----------------------------------------------------------------------------------
LLM CPU Time: 1.4782967567443848