Input path: /home/debian/html/nutritwin/output_llm/66b9115262af0/input.json
Output path: /home/debian/html/nutritwin/output_llm/66b9115262af0/output.json
Input text: J'ai mangé de la compote de pommes
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 de la compote de pommes
==================================================================================================================================
==================================== 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 de la compote de pommes###.
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 de la compote de pommes""" 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": "compote de pommes",
"type": "food",
"event": "declaration"
}
]
```
-----------------------------------------------------------------------------
----------------- Make it compliant ------------------
```json
[
{
"name": "compote de pommes",
"type": "food",
"event": "declaration"
}
]
```
------------------------------------------------------
------------------------ After simplification ------------------------
[ { "name": "compote de pommes", "type": "food", "event": "declaration" }]
----------------------------------------------------------------------
--------------------------------- LLM result -----------------------------------
{'response': [{'name': 'compote de pommes', 'type': 'food', 'event': 'declaration'}], 'cost': 0.0}
--------------------------------------------------------------------------------
----------- result to be analyzed -----------
{'name': 'compote de pommes', '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 '% compote de pomme %' AND (V_NormTrademark = '' OR V_NormTrademark IS NULL)
------------- Found solution (max 20) --------------
Compote de Pomme - compote de pomme - - - 18523 - - - CIQ#b03321a86ac3c7bdbf1fdd06152fe3a4
Compote de Pomme - compote de pomme - appertisée - - 26 - - - KCA#4abbe95b97dc51099f7c74281eb56b7e
Compote de Pomme - compote de pomme - allégée en sucres - - 0 - - - CIQ#4c6f85d09f34c5881f71baaee4367d62
----------------------------------------------------
ERROR: Wrong quantity: ''
ERROR: no solution for picto in the first solution
ERROR: Wrong quantity: ''
ERROR: no solution for picto in the first solution
ERROR: Wrong quantity: ''
ERROR: no solution for picto in the first solution
--------------------------------- final result -----------------------------------
{'prompt': "J'ai mangé de la compote de pommes", 'intents': ['Identify food consumption or declaration'], 'model': 'gpt-4o-2024-05-13', 'solutions': {'nutrition': [{'name': 'Compote de Pomme', 'normName': ' compote de pomme ', 'comment': '', 'normComment': '', 'rank': 18523, 'id': 'CIQ#b03321a86ac3c7bdbf1fdd06152fe3a4', 'quantity': '', 'quantityLem': '', 'pack': ['RAM.w200', 'YA5.w120'], 'type': 'food', 'gtin': '', 'gtinRef': '', 'brand': '', 'time': '', 'event': 'declaration', 'serving': '', 'posiNormName': 0}], 'activity': [], 'response': {}}, 'cputime': 1.3860657215118408}
----------------------------------------------------------------------------------
LLM CPU Time: 1.3860657215118408