Input path: /home/debian/html/nutritwin/output_llm/6735e76895e4e/input.json
Output path: /home/debian/html/nutritwin/output_llm/6735e76895e4e/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": "Fromage à pâte molle à croûte fleurie",
    "quantity": "portion",
    "weight": "50",
    "cooking": "",
    "brand": "",
    "company": "",
    "type": "produit laitier",
    "time": "grignotage",
    "event": "declaration"
  }
]
```
-----------------------------------------------------------------------------

----------------- Make it compliant ------------------
```json
[
  {
    "name": "Fromage à pâte molle à croûte fleurie",
    "quantity": "portion",
    "weight": "50",
    "cooking": "",
    "brand": "",
    "company": "",
    "type": "produit laitier",
    "time": "grignotage",
    "event": "declaration"
  }
]
```
------------------------------------------------------

------------------------ After simplification ------------------------
[  {    "name": "Fromage à pâte molle à croûte fleurie",    "quantity": "portion",    "weight": "50",    "cooking": "",    "brand": "",    "company": "",    "type": "produit laitier",    "time": "grignotage",    "event": "declaration"  }]
----------------------------------------------------------------------

--------------------------------- LLM result -----------------------------------
{'response': [{'name': 'Fromage à pâte molle à croûte fleurie', 'quantity': 'portion', 'weight': '50', 'cooking': '', 'brand': '', 'company': '', 'type': 'produit laitier', 'time': 'grignotage', 'event': 'declaration'}], 'cost': 0.0}
--------------------------------------------------------------------------------

----------- result to be analyzed -----------
{'name': 'Fromage à pâte molle à croûte fleurie', 'quantity': 'portion', 'weight': '50', 'cooking': '', 'brand': '', 'company': '', 'type': 'produit laitier', '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 '% fromage pate molle croute fleurie %' AND (V_NormTrademark = '' OR V_NormTrademark IS NULL)


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 '% fromage pate molle croute fleurie %' AND V_NormTrademark LIKE '%%' 


------------- Found solution (max 20) --------------
Coulommiers -  coulommier  -  - Carrefour - 0 - 3560070349791 - 3245391919723 - OFF#e6cb8e4e83f49c2d4f8247205f43e328
Coulommiers -  coulommier  -  - Carrefour - 0 - 3270190021148 - 3245391919723 - OFF#d75f02660b9fc26dcc273a2d0f0cb900
Brie de Meaux -  brie de meau  -  - Carrefour - 0 - 3245390136046 - 2689131015619 - OFF#36e6ce5d2997cc130372c95409744fb3
Le Petit Camembert -  petit camembert  -  - Auchan - 0 - 3596710442386 - 3596710442386 - OFF#203934841c5b59ad6dbedffb3be8d785
Onctueux Tendre et Doux -  onctueu tendre dou  -  - Casino - 0 - 3222475416392 - 3222475416392 - OFF#278e5691b3cdf86594262a17bc87cd2d
Coulommiers de Caractère -  coulommier de caractere  -  - Carrefour - 0 - 3560070275878 - 3560070275878 - OFF#f4010d8eccfcd8d88c199b6651003a0b
Le Carré Doux et Onctueux -  carre dou onctueu  -  - Auchan - 0 - 3596710489794 - 3596710489794 - OFF#eb3ab34cf8ee7c021195c0321ac62927
Le Coulommiers 10 Portions -  coulommier 10 portion  -  - Carrefour - 0 - 3560070562251 - 3560070562251 - OFF#94dd8db420ed7c04823b6c73d89da031
Saint Félicien Moulé à la Louche -  saint felicien moule louche  -  - Carrefour - 0 - 3560070966097 - 3560070966097 - OFF#f7d0bc5f1ce2ca0c712ce6acad06fce8
Tranches Gourmandes Spécial Sandwich -  tranche gourmande special sandwich  -  - Carrefour - 0 - 3560070573202 - 3560070573202 - OFF#38a4d223039752abd687e77dab7041f3
Le Rustique à la Truffe Noire du Périgord -  rustique truffe noire perigord  -  - Compagnie des fromages & RichesMonts - 0 - 3176582008295 - 3176582008295 - OFF#76c9e900f8c679bebda2435639f67af6
----------------------------------------------------

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': 'Coulommiers', 'normName': ' coulommier ', 'comment': '', 'normComment': '', 'rank': 0, 'id': 'OFF#e6cb8e4e83f49c2d4f8247205f43e328', 'quantity': 'portion', 'quantityLem': 'portion', 'pack': ['MIM.w20', 'CAM.w30'], 'type': 'produit laitier', 'gtin': '3560070349791', 'gtinRef': '3245391919723', 'brand': 'Carrefour', 'time': 'grignotage', 'event': 'declaration', 'serving': '', 'posiNormName': -1}], 'activity': [], 'response': {}}, 'cputime': 3.3255324363708496}
----------------------------------------------------------------------------------
LLM CPU Time: 3.3255324363708496