Input path: /home/debian/html/nutritwin/output_llm/673502aa5adf6/input.json
Output path: /home/debian/html/nutritwin/output_llm/673502aa5adf6/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 -----------------------------
The image provided shows a close-up of a canned product label, making it difficult to identify the specific food item inside. Because the item in the image is not fully visible and the main label is not shown, I cannot accurately provide details such as the name, quantity, weight, cooking mode, brand, company, or type of the food item within the can. The only visible information is the manufacturer "FRINSA DEL NOROESTE, S.A.", which does not provide sufficient information to complete the requested format accurately.

If there were more context or a clearer image showing the entirety of the product, I would be able to deliver the requested information in the format specified.
-----------------------------------------------------------------------------

----------------- Make it compliant ------------------
The image provided shows a close-up of a canned product label, making it difficult to identify the specific food item inside. Because the item in the image is not fully visible and the main label is not shown, I cannot accurately provide details such as the name, quantity, weight, cooking mode, brand, company, or type of the food item within the can. The only visible information is the manufacturer "FRINSA DEL NOROESTE, S.A.", which does not provide sufficient information to complete the requested format accurately.

If there were more context or a clearer image showing the entirety of the product, I would be able to deliver the requested information in the format specified.
------------------------------------------------------

------------------------ After simplification ------------------------

----------------------------------------------------------------------

++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
ERROR: impossible to parse [II]:
The image provided shows a close-up of a canned product label, making it difficult to identify the specific food item inside. Because the item in the image is not fully visible and the main label is not shown, I cannot accurately provide details such as the name, quantity, weight, cooking mode, brand, company, or type of the food item within the can. The only visible information is the manufacturer "FRINSA DEL NOROESTE, S.A.", which does not provide sufficient information to complete the requested format accurately.

If there were more context or a clearer image showing the entirety of the product, I would be able to deliver the requested information in the format specified.

The extracted string is 
++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++

--------------------------------- LLM result -----------------------------------
{'response': {}, 'cost': 0.0}
--------------------------------------------------------------------------------

--------------------------------- final result -----------------------------------
{'prompt': '', 'intents': ['Identify food in an image'], 'model': 'gpt-4o-2024-05-13', 'solutions': {'nutrition': [], 'activity': [], 'response': {}}, 'cputime': 4.527419328689575}
----------------------------------------------------------------------------------
LLM CPU Time: 4.527419328689575