Input path: /home/debian/html/nutritwin/output_llm/660edbe582fa9/input.json
Output path: /home/debian/html/nutritwin/output_llm/660edbe582fa9/output.json
Input text: Quatre friture chocolat
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: Quatre friture chocolat
==================================================================================================================================
==================================== Prompt =============================================
Identify in this list of intents: ["Capture the user food consumption", "Capture the user physical activity", "Other intent"], the intents of the prompt: ###Quatre friture chocolat###.
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"]}
----------------------------------------------------------------------
==================================== Prompt =============================================
I need to identify food information from sentences.
Analyze the following french sentence: "Quatre friture chocolat".
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, I've analyzed the sentence "Quatre friture chocolat". However, the sentence is not grammatically correct and seems to be missing some context. "Friture" in French usually refers to a method of cooking (frying), but it doesn't make sense in this context with "chocolat" (chocolate).
However, I'll try to extract as much information as possible based on the given sentence. Here's the result:
```json
[
{
"name": "chocolat",
"quantity": "quatre",
"cooking": "",
"brand": "",
"company": "",
"type": "dessert",
"time": "",
"event": "unknown"
}
]
```
Please note that the "cooking", "brand", "company", "time", and "event" fields are empty because the sentence does not provide enough information to fill these fields. The "type" field is assumed to be "dessert" because "chocolat" is usually considered a dessert. The "quantity" is "quatre" (four), but it's unclear what the quantity refers to because "friture" doesn't make sense in this context.
-----------------------------------------------------------------------------
----------------- Make it compliant ------------------
Based on your instructions, I've analyzed the sentence "Quatre friture chocolat". However, the sentence is not grammatically correct and seems to be missing some context. "Friture" in French usually refers to a method of cooking (frying), but it doesn't make sense in this context with "chocolat" (chocolate).
However, I'll try to extract as much information as possible based on the given sentence. Here's the result:
```json
[
{
"name": "chocolat",
"quantity": "quatre",
"cooking": "",
"brand": "",
"company": "",
"type": "dessert",
"time": "",
"event": "unknown"
}
]
```
Please note that the "cooking", "brand", "company", "time", and "event" fields are empty because the sentence does not provide enough information to fill these fields. The "type" field is assumed to be "dessert" because "chocolat" is usually considered a dessert. The "quantity" is "quatre" (four), but it's unclear what the quantity refers to because "friture" doesn't make sense in this context.
------------------------------------------------------
------------------------ After simplification ------------------------
[ { "name": "chocolat", "quantity": "quatre", "cooking": "", "brand": "", "company": "", "type": "dessert", "time": "", "event": "unknown" }]
----------------------------------------------------------------------
--------------------------------- LLM result -----------------------------------
{'response': [{'name': 'chocolat', 'quantity': 'quatre', 'cooking': '', 'brand': '', 'company': '', 'type': 'dessert', 'time': '', 'event': 'unknown'}], 'cost': 0.06425999999999998}
--------------------------------------------------------------------------------
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 '% chocolat %' AND (V_NormTrademark = '' OR V_NormTrademark IS NULL)
------------- Found solution (max 20) --------------
Chocolat - chocolat - en tablette, aliment moyen - - 0 - - - CIQ#ce78d6e2da46a5b975cfe742e849374c
Chocolat au Lait - chocolat lait - - - 17100 - - - KCA#7a8849f6f600e38254b01cd2dcb2e2eb
Chocolat à l'Eau - chocolat eau - - - 853 - - - KCA#31815811896ede162223a8bb59e9dc11
Chocolat au Lait - chocolat lait - tablette - - 0 - - - CIQ#0c766e8e90e26098e79738866cacd819
Chocolat au Lait - chocolat lait - aux Céréales croustillantes - - 2056 - - - KCA#f5d4edabe0f965da0f72bcc4c5dfb4c2
Chocolat Liégeois - chocolat liegeoi - - - 116 - - - KCA#3a4aab213a2571bd6870873db5260b98
Chocolat en Poudre - chocolat en poudre - - - 624 - - - KCA#cff72918732e66361d144848bd6d76cd
Chocolat en Poudre - chocolat en poudre - et lait demi écrémé - - 9752 - - - KCA#04fe986b8c7c6d36b63cbd16492b7712
Chocolat Noir à Croquer - chocolat noir croquer - - - 18834 - - - KCA#9b500c08695e76b67b18e2fa08773333
Chocolat Noir Noisettes - chocolat noir noisette - - - 1875 - - - KCA#49fc5b19d990e357f20d1160e7d62f54
Chocolat Noir Dégustation - chocolat noir degustation - 70% Cacao - - 7359 - - - KCA#0268c0bb7380b1456496d668269e3ff4
Chocolat Noir Dégustation - chocolat noir degustation - 70% Cacao sans sucre ajouté - - 1221 - - - KCA#34b04a8e141eece15dc24eb779ae71ef
Chocolat Noir aux Fruits Secs - chocolat noir au fruit sec - noisettes, amandes, raisins, praline, tablette - - 0 - - - CIQ#2ebd03c0dd9aab3bfb07ac8958b5239c
Chocolat Noir à 70% Cacao Minimum - chocolat noir 70% cacao minimum - extra, dégustation, tablette - - 0 - - - CIQ#fece0a5a54ed327de64a617f20b78b6c
Chocolat Noir sans Sucres Ajoutés - chocolat noir san sucre ajoute - avec édulcorants, en tablette - - 0 - - - CIQ#3cece312c84cb7ddd4bcc80edf31a153
Chocolat au Lait sans Sucres Ajoutés - chocolat lait san sucre ajoute - avec édulcorants, tablette - - 0 - - - CIQ#09bc5fef8a8b1113265bb2a0ddc95b2f
Pain au Chocolat - pain chocolat - - - 8865 - - - CIQ#aa621dd97d922a7b28ca0ee09aed7449
Pain au Chocolat Feuilleté - pain chocolat feuillete - artisanal - - 0 - - - CIQ#bd38d8f7658a11f0a504009aaaa44ead
Crème au Chocolat - creme chocolat - - - 210 - - - KCA#bcc59e88e7d8f6babecc21c8b7e622aa
Sauce au Chocolat - sauce chocolat - - - 0 - - - CIQ#499da9cecdcb14e8c3264dd25833827c
----------------------------------------------------
ERROR: no solution for picto in the first solution
--------------------------------- final result -----------------------------------
{'prompt': 'Quatre friture chocolat', 'intents': ['Capture the user food consumption'], 'model': 'mistral-large-latest', 'solutions': {'nutrition': [{'name': 'Chocolat', 'normName': ' chocolat ', 'comment': 'en tablette, aliment moyen', 'normComment': ' en tablette aliment moyen ', 'rank': 0, 'id': 'CIQ#ce78d6e2da46a5b975cfe742e849374c', 'quantity': 'quatre', 'quantityLem': '4', 'pack': ['CHO.w5'], 'type': 'dessert', 'gtin': '', 'gtinRef': '', 'brand': '', 'time': '', 'event': 'unknown', 'serving': '', 'posiNormName': 0}], 'activity': []}, 'cputime': 7.90265154838562}
----------------------------------------------------------------------------------
LLM CPU Time: 7.90265154838562