Input path: /home/debian/html/nutritwin/output_llm/660edcbe094b3/input.json
Output path: /home/debian/html/nutritwin/output_llm/660edcbe094b3/output.json
Input text: Compote de pommes
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: Compote de pommes
==================================================================================================================================
==================================== Prompt =============================================
Identify in this list of intents: ["Capture the user food consumption", "Capture the user physical activity", "Other intent"], the intents of the prompt: ###Compote de pommes###.
Format the result in JSON format: {intents: []}.
=========================================================================================
------------------------------ LLM Raw response -----------------------------
{
"intents": ["Capture the user food consumption"]
}
-----------------------------------------------------------------------------
----------------- Make it compliant ------------------
{
"intents": ["Capture the user food consumption"]
}
------------------------------------------------------
------------------------ After simplification ------------------------
{"intents": ["Capture the user food consumption"]}
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==================================== Prompt =============================================
I need to identify food information from sentences.
Analyze the following french sentence: "Compote de pommes".
I want to identify for the food or beverage: the name, the type, the quantity for each ingredient and, if it exists, identify the brand, the cooking mode and the company name.
Containers, like "canette" or "verre", are quantities and not ingredients or food product.
"Portions", like "tranche", are quantities.
"Quantity" is in french.
"Company" is the company of the brand.
"Quignon" is a quantity.
Ignore what it is not connected to nutrition, beverage or food.
Music and is not nutrition.
Extract how the product is consumed.
In the name, ignore the level of cooking mode.
When brand is not specified and the product is very well-known (like "Coca-Cola"), provide the brand name in "brand", otherwise set "brand" to "".
Ignore the actions.
The restaurants are not brand.
Identify what type of food.
Ignore food with a negative verb, ex "Je n'ai pas pris de viande".
Do not extract ingredients for product with a brand.
If the food or beverage consumption is in the past, the event is a "declaration", for example: "J'ai mangé du pain", the event is a declaration.
If the food or beverage consumption will be in the future or even soon, the event is an "intent", for example: "Je vais manger du pain", the event is an intent.
Otherwise the event is unknown.
Map the event of eating on ["intent", "declaration", "unknown"].
Identify the time of day when the foods were eaten and map it on "petit-déjeuner", "déjeuner", "grignotage" or "dîner".
Format the result in french in JSON in an array of tuples {"name":, "quantity":, "cooking":, "brand":, "company":, "type":, "time":, "event":}.
=========================================================================================
------------------------------ LLM Raw response -----------------------------
Based on your instructions, here's how I would analyze the sentence "Compote de pommes":
The sentence translates to "Apple sauce" in English.
1. Name: The name of the food is "Compote de pommes".
2. Type: The type of food is a "compote", which is a dessert or a side dish made of whole or pieces of fruit in sugar syrup.
3. Quantity: The quantity is not specified in the sentence.
4. Ingredient: The ingredient is "pommes" (apples), but since the food has a specific name and is not a raw ingredient, we won't list "apples" as an ingredient.
5. Brand: The brand is not specified in the sentence.
6. Cooking mode: The cooking mode is not specified in the sentence, but "compote" implies that the apples are cooked and pureed.
7. Company: The company is not specified in the sentence.
8. Event: The sentence does not specify whether the compote is being eaten, will be eaten, or was eaten, so the event is "unknown".
9. Time: The time of day is not specified in the sentence.
Here's the information formatted in JSON:
```json
[
{
"name": "Compote de pommes",
"quantity": "",
"cooking": "Cooked and pureed",
"brand": "",
"company": "",
"type": "Dessert or side dish",
"time": "",
"event": "unknown"
}
]
```
-----------------------------------------------------------------------------
----------------- Make it compliant ------------------
Based on your instructions, here's how I would analyze the sentence "Compote de pommes":
The sentence translates to "Apple sauce" in English.
1. Name: The name of the food is "Compote de pommes".
2. Type: The type of food is a "compote", which is a dessert or a side dish made of whole or pieces of fruit in sugar syrup.
3. Quantity: The quantity is not specified in the sentence.
4. Ingredient: The ingredient is "pommes" (apples), but since the food has a specific name and is not a raw ingredient, we won't list "apples" as an ingredient.
5. Brand: The brand is not specified in the sentence.
6. Cooking mode: The cooking mode is not specified in the sentence, but "compote" implies that the apples are cooked and pureed.
7. Company: The company is not specified in the sentence.
8. Event: The sentence does not specify whether the compote is being eaten, will be eaten, or was eaten, so the event is "unknown".
9. Time: The time of day is not specified in the sentence.
Here's the information formatted in JSON:
```json
[
{
"name": "Compote de pommes",
"quantity": "",
"cooking": "Cooked and pureed",
"brand": "",
"company": "",
"type": "Dessert or side dish",
"time": "",
"event": "unknown"
}
]
```
------------------------------------------------------
------------------------ After simplification ------------------------
[ { "name": "Compote de pommes", "quantity": "", "cooking": "Cooked and pureed", "brand": "", "company": "", "type": "Dessert or side dish", "time": "", "event": "unknown" }]
----------------------------------------------------------------------
--------------------------------- LLM result -----------------------------------
{'response': [{'name': 'Compote de pommes', 'quantity': '', 'cooking': 'Cooked and pureed', 'brand': '', 'company': '', 'type': 'Dessert or side dish', 'time': '', 'event': 'unknown'}], 'cost': 0.07368}
--------------------------------------------------------------------------------
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 '% compote de pomme %' AND (V_NormTrademark = '' OR V_NormTrademark IS NULL)
------------- Found solution (max 20) --------------
Compote de Pomme - compote de pomme - - - 18523 - - - CIQ#b03321a86ac3c7bdbf1fdd06152fe3a4
Compote de Pomme - compote de pomme - appertisée - - 26 - - - KCA#4abbe95b97dc51099f7c74281eb56b7e
Compote de Pomme - compote de pomme - allégée en sucres - - 0 - - - CIQ#4c6f85d09f34c5881f71baaee4367d62
----------------------------------------------------
ERROR: Wrong quantity: ''
ERROR: no solution for picto in the first solution
ERROR: Wrong quantity: ''
ERROR: no solution for picto in the first solution
ERROR: Wrong quantity: ''
ERROR: no solution for picto in the first solution
--------------------------------- final result -----------------------------------
{'prompt': 'Compote de pommes', 'intents': ['Capture the user food consumption'], 'model': 'mistral-large-latest', 'solutions': {'nutrition': [{'name': 'Compote de Pomme', 'normName': ' compote de pomme ', 'comment': '', 'normComment': '', 'rank': 18523, 'id': 'CIQ#b03321a86ac3c7bdbf1fdd06152fe3a4', 'quantity': '', 'quantityLem': '', 'pack': ['RAM.w200', 'YA5.w120'], 'type': 'Dessert or side dish', 'gtin': '', 'gtinRef': '', 'brand': '', 'time': '', 'event': 'unknown', 'serving': '', 'posiNormName': 0}], 'activity': []}, 'cputime': 10.023138523101807}
----------------------------------------------------------------------------------
LLM CPU Time: 10.023138523101807