Input path: /home/debian/html/nutritwin/output_llm/660b063d70901/input.json
Output path: /home/debian/html/nutritwin/output_llm/660b063d70901/output.json
Input text: J'ai mangé deux portions de vache kiri
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 deux portions de vache kiri
==================================================================================================================================

==================================== Prompt =============================================
Identify in this list of intents: ["Capture the user food consumption", "Capture the user physical activity", "Other intent"], the intents of the prompt: ###J'ai mangé deux portions de vache kiri###. 
 Format the result in JSON format: {intents: []}.
=========================================================================================


------------------------------ LLM Raw response -----------------------------
{
"intents": ["Capture the user food consumption"]
}
-----------------------------------------------------------------------------

----------------- Make it compliant ------------------
{
"intents": ["Capture the user food consumption"]
}
------------------------------------------------------

------------------------ After simplification ------------------------
{"intents": ["Capture the user food consumption"]}
----------------------------------------------------------------------

==================================== Prompt =============================================
I need to identify food information from sentences.

Analyze the following french sentence: "J'ai mangé deux portions de vache kiri".

I want to identify for the food or beverage: the name, the type, the quantity for each ingredient and, if it exists, identify the brand, the cooking mode and the company name.
Containers, like "canette" or "verre", are quantities and not ingredients or food product.
"Portions", like "tranche", are quantities. 
"Quantity" is in french.
"Company" is the company of the brand.
"Quignon" is a quantity. 
Ignore what it is not connected to nutrition, beverage or food. 
Music and is not nutrition. 
Extract how the product is consumed. 
In the name, ignore the level of cooking mode. 
When brand is not specified and the product is very well-known (like "Coca-Cola"), provide the brand name in "brand", otherwise set "brand" to "". 
Ignore the actions. 
The restaurants are not brand. 
Identify what type of food. 
Ignore food with a negative verb, ex "Je n'ai pas pris de viande".
Do not extract ingredients for product with a brand. 
If the food or beverage consumption is in the past, the event is a "declaration", for example: "J'ai mangé du pain", the event is a declaration. 
If the food or beverage consumption will be in the future or even soon, the event is an "intent", for example: "Je vais manger du pain", the event is an intent. 
Otherwise the event is unknown. 
Map the event of eating on ["intent", "declaration", "unknown"]. 
Identify the time of day when the foods were eaten and map it on "petit-déjeuner", "déjeuner", "grignotage" or "dîner". 

Format the result in french in JSON in an array of tuples {"name":, "quantity":, "cooking":, "brand":, "company":, "type":, "time":, "event":}.


=========================================================================================


------------------------------ LLM Raw response -----------------------------
Based on your instructions, here's the analysis of the sentence "J'ai mangé deux portions de vache kiri".

The sentence indicates that the person ate two portions of Kiri cheese. Kiri is a well-known brand of processed cheese.

The time of eating is not specified in the sentence, so it cannot be determined whether it was breakfast, lunch, snack, or dinner.

The event is a "declaration" because the eating is in the past.

Here's the result in the requested JSON format:

```json
[
  {
    "name": "vache kiri",
    "quantity": "deux portions",
    "cooking": "",
    "brand": "Kiri",
    "company": "",
    "type": "fromage",
    "time": "inconnu",
    "event": "déclaration"
  }
]
```
-----------------------------------------------------------------------------

----------------- Make it compliant ------------------
Based on your instructions, here's the analysis of the sentence "J'ai mangé deux portions de vache kiri".

The sentence indicates that the person ate two portions of Kiri cheese. Kiri is a well-known brand of processed cheese.

The time of eating is not specified in the sentence, so it cannot be determined whether it was breakfast, lunch, snack, or dinner.

The event is a "declaration" because the eating is in the past.

Here's the result in the requested JSON format:

```json
[
  {
    "name": "vache kiri",
    "quantity": "deux portions",
    "cooking": "",
    "brand": "Kiri",
    "company": "",
    "type": "fromage",
    "time": "inconnu",
    "event": "déclaration"
  }
]
```
------------------------------------------------------

------------------------ After simplification ------------------------
[  {    "name": "vache kiri",    "quantity": "deux portions",    "cooking": "",    "brand": "Kiri",    "company": "",    "type": "fromage",    "time": "inconnu",    "event": "déclaration"  }]
----------------------------------------------------------------------

--------------------------------- LLM result -----------------------------------
{'response': [{'name': 'vache kiri', 'quantity': 'deux portions', 'cooking': '', 'brand': 'Kiri', 'company': '', 'type': 'fromage', 'time': 'inconnu', 'event': 'déclaration'}], 'cost': 0.0552}
--------------------------------------------------------------------------------

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 '% vache kiri %' AND V_NormTrademark LIKE '%kiri%' 


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 '% vache kiri %' AND V_NormTrademark LIKE '%kiri%' 

-------------------------------------------
------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 '% vache kiri %' AND V_NormTrademark LIKE '%kiri%' 
-------------------------------------------
-------------------------------------------

--------------------------------- final result -----------------------------------
{'prompt': "J'ai mangé deux portions de vache kiri", 'intents': ['Capture the user food consumption'], 'model': 'mistral-large-latest', 'solutions': {'nutrition': [], 'activity': []}, 'cputime': 9.361026048660278}
----------------------------------------------------------------------------------
LLM CPU Time: 9.361026048660278