Input path: /home/debian/html/nutritwin/output_llm/674709d00b28a/input.json
Output path: /home/debian/html/nutritwin/output_llm/674709d00b28a/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": "salade verte",
"quantity": "",
"weight": "150",
"cooking": "cru",
"brand": "",
"company": "",
"type": "légume",
"time": "déjeuner",
"event": "declaration"
},
{
"name": "vinaigrette",
"quantity": "",
"weight": "30",
"cooking": "",
"brand": "",
"company": "",
"type": "assaisonnement",
"time": "déjeuner",
"event": "declaration"
}
]
```
-----------------------------------------------------------------------------
----------------- Make it compliant ------------------
```json
[
{
"name": "salade verte",
"quantity": "",
"weight": "150",
"cooking": "cru",
"brand": "",
"company": "",
"type": "légume",
"time": "déjeuner",
"event": "declaration"
},
{
"name": "vinaigrette",
"quantity": "",
"weight": "30",
"cooking": "",
"brand": "",
"company": "",
"type": "assaisonnement",
"time": "déjeuner",
"event": "declaration"
}
]
```
------------------------------------------------------
------------------------ After simplification ------------------------
[ { "name": "salade verte", "quantity": "", "weight": "150", "cooking": "cru", "brand": "", "company": "", "type": "légume", "time": "déjeuner", "event": "declaration" }, { "name": "vinaigrette", "quantity": "", "weight": "30", "cooking": "", "brand": "", "company": "", "type": "assaisonnement", "time": "déjeuner", "event": "declaration" }]
----------------------------------------------------------------------
--------------------------------- LLM result -----------------------------------
{'response': [{'name': 'salade verte', 'quantity': '', 'weight': '150', 'cooking': 'cru', 'brand': '', 'company': '', 'type': 'légume', 'time': 'déjeuner', 'event': 'declaration'}, {'name': 'vinaigrette', 'quantity': '', 'weight': '30', 'cooking': '', 'brand': '', 'company': '', 'type': 'assaisonnement', 'time': 'déjeuner', 'event': 'declaration'}], 'cost': 0.0}
--------------------------------------------------------------------------------
----------- result to be analyzed -----------
{'name': 'salade verte', 'quantity': '', 'weight': '150', 'cooking': 'cru', 'brand': '', 'company': '', 'type': 'légume', 'time': 'déjeuner', '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 '% salade verte %' AND (V_NormTrademark = '' OR V_NormTrademark IS NULL)
------------- Found solution (max 20) --------------
Salade Verte - salade verte - avec vinaigrette - - 61586 - - - KCA#4ab5b82c387924b3ce222cda9fdf1f3e
Salade Verte - salade verte - sans vinaigrette - - 15302 - - - KCA#ffaecdf2b67b1ae9d2055afa2173c027
----------------------------------------------------
ERROR: Wrong quantity: ''
ERROR: no solution for picto in the first solution
ERROR: Wrong quantity: ''
ERROR: no solution for picto in the first solution
----------- result to be analyzed -----------
{'name': 'vinaigrette', 'quantity': '', 'weight': '30', 'cooking': '', 'brand': '', 'company': '', 'type': 'assaisonnement', 'time': 'déjeuner', '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 '% vinaigrette %' AND (V_NormTrademark = '' OR V_NormTrademark IS NULL)
------------- Found solution (max 20) --------------
Vinaigrette - vinaigrette - - - 16273 - - - KCA#e4a8d271a13253a076ecb84c590edc45
Vinaigrette au Sésame - vinaigrette sesame - - - 78 - - - KCA#42042e19b8d3b31a68f6ebd0a3670cac
Raie à la Vinaigrette - raie vinaigrette - - - 16 - - - KCA#4ca1fb45b968beb65422f8e85881ac50
Crudité Vinaigrette - crudite vinaigrette - aliment moyen - - 3404 - - - KCA#70807618ddd3f6b30e585b929c5f006a
Poireaux Vinaigrette - poireau vinaigrette - - - 1011 - - - KCA#7079a39528c94a392c83315b250f3c29
Artichauts à la Vinaigrette - artichaut vinaigrette - - - 84 - - - KCA#6821b9ef7fd9c2b91e6fada84027cbb2
Champignons Vinaigrette - champignon vinaigrette - - - 24 - - - KCA#2b370fdead13ae1b072147efe2939971
Carotte Râpée à la Vinaigrette - carotte rapee vinaigrette - - - 1371 - - - KCA#550aab930f59f61f6d4b015c1f19f2a7
Museau de Porc Vinaigrette - museau de porc vinaigrette - - - 0 - - - CIQ#6d45d5637bfe086a63507f6ce6b9b653
Salade de Tomates Vinaigrette - salade de tomate vinaigrette - - - 6673 - - - KCA#554aa2ce201cd0052f644a5f6dd86568
Museau de Boeuf en Vinaigrette - museau de boeuf en vinaigrette - - - 0 - - - CIQ#8ffeecb67101e712102cde30549c10cd
----------------------------------------------------
ERROR: Wrong quantity: ''
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': 'Salade Verte', 'normName': ' salade verte ', 'comment': 'avec vinaigrette', 'normComment': ' avec vinaigrette ', 'rank': 61586, 'id': 'KCA#4ab5b82c387924b3ce222cda9fdf1f3e', 'quantity': '', 'quantityLem': '', 'pack': ['SAL.w170'], 'type': 'légume', 'gtin': '', 'gtinRef': '', 'brand': '', 'time': 'déjeuner', 'event': 'declaration', 'serving': '', 'posiNormName': 0}, {'name': 'Vinaigrette', 'normName': ' vinaigrette ', 'comment': '', 'normComment': '', 'rank': 16273, 'id': 'KCA#e4a8d271a13253a076ecb84c590edc45', 'quantity': '', 'quantityLem': '', 'pack': ['CSL', 'CCL'], 'type': 'assaisonnement', 'gtin': '', 'gtinRef': '', 'brand': '', 'time': 'déjeuner', 'event': 'declaration', 'serving': '', 'posiNormName': 0}], 'activity': [], 'response': {}}, 'cputime': 6.481865167617798}
----------------------------------------------------------------------------------
LLM CPU Time: 6.481865167617798