Input path: /home/debian/html/nutritwin/output_llm/67236bb5c20f0/input.json
Output path: /home/debian/html/nutritwin/output_llm/67236bb5c20f0/output.json
Input text: 
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: 
==================================================================================================================================
###########################################
#   For image extraction, GPT4 is used    #
###########################################

==================================== Prompt =============================================
In the image, identify all the foods and the beverages.
For each of them, identify the "name", the "type", the "quantity", if it exists, the "brand" and the "cooking" mode. 
"Portions", like "tranche", are quantities. 
Ignore what it is not connected to nutrition, beverage or food. 
When the "brand" is not specified and the product is very well-known (like "Coca-Cola"), provide the brand name in "brand", otherwise set "brand" to "". 
Identify what "type" of food.
Identify the "company" to which the "brand" belongs.
Estimate the "weight" in grams or centiliters for each result.
Identify the time is the current time, map it on the closest case: "petit-déjeuner", "déjeuner", "grignotage" or "dîner".
When the "name" has synonyms, use the most common name, example: "yaourt" is more common than "yogourt".
Format the result for each ingredient of food & beverage in french in JSON in an array of tuples {"name":, "quantity":, "weight":, "cooking":, "brand":, "company":, "type":, "time":, "event": "declaration"}. 


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

Image recognition....

------------------------------ LLM Raw response -----------------------------
```json
[
  {
    "name": "banane",
    "quantity": "1",
    "weight": "120",
    "cooking": "raw",
    "brand": "",
    "company": "",
    "type": "fruit",
    "time": "grignotage",
    "event": "declaration"
  }
]
```
-----------------------------------------------------------------------------

----------------- Make it compliant ------------------
```json
[
  {
    "name": "banane",
    "quantity": "1",
    "weight": "120",
    "cooking": "raw",
    "brand": "",
    "company": "",
    "type": "fruit",
    "time": "grignotage",
    "event": "declaration"
  }
]
```
------------------------------------------------------

------------------------ After simplification ------------------------
[  {    "name": "banane",    "quantity": "1",    "weight": "120",    "cooking": "raw",    "brand": "",    "company": "",    "type": "fruit",    "time": "grignotage",    "event": "declaration"  }]
----------------------------------------------------------------------

--------------------------------- LLM result -----------------------------------
{'response': [{'name': 'banane', 'quantity': '1', 'weight': '120', 'cooking': 'raw', 'brand': '', 'company': '', 'type': 'fruit', 'time': 'grignotage', 'event': 'declaration'}], 'cost': 0.0}
--------------------------------------------------------------------------------

----------- result to be analyzed -----------
{'name': 'banane', 'quantity': '1', 'weight': '120', 'cooking': 'raw', 'brand': '', 'company': '', 'type': 'fruit', 'time': 'grignotage', '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 '% banane %' AND (V_NormTrademark = '' OR V_NormTrademark IS NULL)


------------- Found solution (max 20) --------------
Banane -  banane  - pulpe, crue -  - 57967 -  -  - CIQ#6066b5bb884711efc0e44c9446b96aa3
Banane Sèche -  banane seche  -  -  - 346 -  -  - KCA#2e3e40d3b1ae9f793251e9948142d784
Bananes en Robe -  banane en robe  -  -  - 14 -  -  - KCA#b274666ef64f762c58695191d4286b85
Banane Plantain -  banane plantain  -  -  - 2 -  -  - CIQ#1055a76a23712202f3c842fba09fa691
Bananes Barbecue -  banane barbecue  -  -  - 33 -  -  - KCA#1d31fb8efe54f0bc7765a60cc9f8c324
Bananes au Jambon -  banane jambon  -  -  - 4 -  -  - KCA#e21d980b838ba89f4e9ba1d85f593c95
Smoothie Banane et Lait de Soja -  smoothie banane lait de soja  - de soja -  - 0 -  -  - KCA#dc0b16a02e5290892f9adee7419ec0e7
Crème Glacée Banane, Pomme et Noix de Macadamia -  creme glacee banane pomme noix de macadamia  -  -  - 34 -  -  - KCA#3233d39965b7baa31d10a301ac541ffa
Bruschette à la Fraise, à la Banane et à la Ricotta -  bruschette fraise banane ricotta  -  -  - 2 -  -  - KCA#fd9db147f698ab1c84b0905704258a5f
----------------------------------------------------


--------------------------------- final result -----------------------------------
{'prompt': '', 'intents': ['Identify food in an image'], 'model': 'gpt-4o-2024-05-13', 'solutions': {'nutrition': [{'name': 'Banane', 'normName': ' banane ', 'comment': 'pulpe, crue', 'normComment': ' pulpe crue ', 'rank': 57967, 'id': 'CIQ#6066b5bb884711efc0e44c9446b96aa3', 'quantity': '1', 'quantityLem': '1', 'pack': ['BAN.w100'], 'type': 'fruit', 'gtin': '', 'gtinRef': '', 'brand': '', 'time': 'grignotage', 'event': 'declaration', 'serving': 'BAN-100', 'posiNormName': 0}], 'activity': [], 'response': {}}, 'cputime': 4.316586494445801}
----------------------------------------------------------------------------------
LLM CPU Time: 4.316586494445801