Input path: /home/debian/html/nutritwin/output_llm/6703b70b982d0/input.json
Output path: /home/debian/html/nutritwin/output_llm/6703b70b982d0/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": "radis",
    "quantity": "plusieurs",
    "weight": "",
    "cooking": "cru",
    "brand": "",
    "company": "",
    "type": "légume",
    "time": "grignotage",
    "event": "declaration"
  }
]
```
-----------------------------------------------------------------------------

----------------- Make it compliant ------------------
```json
[
  {
    "name": "radis",
    "quantity": "plusieurs",
    "weight": "",
    "cooking": "cru",
    "brand": "",
    "company": "",
    "type": "légume",
    "time": "grignotage",
    "event": "declaration"
  }
]
```
------------------------------------------------------

------------------------ After simplification ------------------------
[  {    "name": "radis",    "quantity": "plusieurs",    "weight": "",    "cooking": "cru",    "brand": "",    "company": "",    "type": "légume",    "time": "grignotage",    "event": "declaration"  }]
----------------------------------------------------------------------

--------------------------------- LLM result -----------------------------------
{'response': [{'name': 'radis', 'quantity': 'plusieurs', 'weight': '', 'cooking': 'cru', 'brand': '', 'company': '', 'type': 'légume', 'time': 'grignotage', 'event': 'declaration'}], 'cost': 0.0}
--------------------------------------------------------------------------------

----------- result to be analyzed -----------
{'name': 'radis', 'quantity': 'plusieurs', 'weight': '', 'cooking': 'cru', 'brand': '', 'company': '', 'type': 'légume', '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 '% radi %' AND (V_NormTrademark = '' OR V_NormTrademark IS NULL)


------------- Found solution (max 20) --------------
Radis Noir -  radi noir  -  -  - 1098 -  -  - KCA#7fdcd16a61b81b39968582bf08a16c34
Radis Noir -  radi noir  - cru -  - 0 -  -  - CIQ#7ad6cf020759131121ce8b6b8edb498b
Radis Rouge -  radi rouge  - cru -  - 0 -  -  - CIQ#b5c63acc21f689bba2e73102521e1e28
Radis au Fromage Blanc -  radi fromage blanc  -  -  - 22 -  -  - KCA#8a027b5a4126accdc5e0bdab41511892
Salade de Chou à l'Orange et aux Radis -  salade de chou orange au radi  -  -  - 24 -  -  - KCA#928c092c510bf33ddfc58150abb33cd5
----------------------------------------------------

ERROR: no solution for picto in the first solution
ERROR: no solution for picto in the first solution

--------------------------------- final result -----------------------------------
{'prompt': '', 'intents': ['Identify food in an image'], 'model': 'gpt-4o-2024-05-13', 'solutions': {'nutrition': [{'name': 'Radis Noir', 'normName': ' radi noir ', 'comment': '', 'normComment': '', 'rank': 1098, 'id': 'KCA#7fdcd16a61b81b39968582bf08a16c34', 'quantity': 'plusieurs', 'quantityLem': 'plusieur', 'pack': ['TR2.w10'], 'type': 'légume', 'gtin': '', 'gtinRef': '', 'brand': '', 'time': 'grignotage', 'event': 'declaration', 'serving': '', 'posiNormName': 0}], 'activity': [], 'response': {}}, 'cputime': 3.2600667476654053}
----------------------------------------------------------------------------------
LLM CPU Time: 3.2600667476654053