Input path: /home/debian/html/nutritwin/output_llm/66083a8da0117/input.json
Output path: /home/debian/html/nutritwin/output_llm/66083a8da0117/output.json
Input text: J'ai mangé un yaourt nature et une tranche de pain de mie
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: J'ai mangé un yaourt nature et une tranche de pain de mie
==================================================================================================================================
==================================== Prompt =============================================
Identify in this list of intents: ["Capture the user food consumption", "Capture the user physical activity", "Other intent"], the intents of the prompt: ###J'ai mangé un yaourt nature et une tranche de pain de mie###.
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"]}
----------------------------------------------------------------------
=====> KO
==================================== Prompt =============================================
I need to identify food information from sentences.
Analyze the following french sentence: "J'ai mangé un yaourt nature et une tranche de pain de mie".
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 the analysis of the sentence "J'ai mangé un yaourt nature et une tranche de pain de mie".
The sentence indicates that the person has eaten a natural yogurt and a slice of bread. The event is in the past, so it's a "declaration". The time of eating is not specified in the sentence.
Here's the formatted result in French:
```json
[
{
"name": "yaourt nature",
"quantity": "un",
"cooking": "",
"brand": "",
"company": "",
"type": "produit laitier",
"time": "inconnu",
"event": "déclaration"
},
{
"name": "tranche de pain de mie",
"quantity": "une",
"cooking": "",
"brand": "",
"company": "",
"type": "produit de boulangerie",
"time": "inconnu",
"event": "déclaration"
}
]
```
-----------------------------------------------------------------------------
----------------- Make it compliant ------------------
Based on your instructions, here's the analysis of the sentence "J'ai mangé un yaourt nature et une tranche de pain de mie".
The sentence indicates that the person has eaten a natural yogurt and a slice of bread. The event is in the past, so it's a "declaration". The time of eating is not specified in the sentence.
Here's the formatted result in French:
```json
[
{
"name": "yaourt nature",
"quantity": "un",
"cooking": "",
"brand": "",
"company": "",
"type": "produit laitier",
"time": "inconnu",
"event": "déclaration"
},
{
"name": "tranche de pain de mie",
"quantity": "une",
"cooking": "",
"brand": "",
"company": "",
"type": "produit de boulangerie",
"time": "inconnu",
"event": "déclaration"
}
]
```
------------------------------------------------------
------------------------ After simplification ------------------------
[ { "name": "yaourt nature", "quantity": "un", "cooking": "", "brand": "", "company": "", "type": "produit laitier", "time": "inconnu", "event": "déclaration" }, { "name": "tranche de pain de mie", "quantity": "une", "cooking": "", "brand": "", "company": "", "type": "produit de boulangerie", "time": "inconnu", "event": "déclaration" }]
----------------------------------------------------------------------
--------------------------------- LLM result -----------------------------------
{'response': [{'name': 'yaourt nature', 'quantity': 'un', 'cooking': '', 'brand': '', 'company': '', 'type': 'produit laitier', 'time': 'inconnu', 'event': 'déclaration'}, {'name': 'tranche de pain de mie', 'quantity': 'une', 'cooking': '', 'brand': '', 'company': '', 'type': 'produit de boulangerie', 'time': 'inconnu', 'event': 'déclaration'}], 'cost': 0.06197999999999999}
--------------------------------------------------------------------------------
First try:
SELECT V_Name,V_Comment,V_NormName,V_NormComment,V_PackType,V_GTIN,V_ID,V_GlobalCount,V_NormTrademark,V_Trademark,V_NormAggr FROM KCALME_TABLE WHERE V_NormName LIKE '% yaourt nature %' AND (V_NormTrademark = '' OR V_NormTrademark IS NULL)
------------- Found solution (max 10) --------------
Yaourt Nature - yaourt nature - - 0 - - KCA#1bb387dba0faa825bf1b41958b69f8b8
Yaourt Nature Sucré - nature sucré - - 0 - - KCA#04a07931e0bb88a2fa79ac588ff372a1
Yaourt Nature Étuvé - nature étuvé - - 0 - - KCA#fd4ce55781f889e0e76135284e824916
Yaourt Nature Sucré Canne - sucré canne - - 0 - - KCA#d4d5ace21d166e38b4293d4e7494b03b
----------------------------------------------------
First try:
SELECT V_Name,V_Comment,V_NormName,V_NormComment,V_PackType,V_GTIN,V_ID,V_GlobalCount,V_NormTrademark,V_Trademark,V_NormAggr FROM KCALME_TABLE WHERE V_NormName LIKE '% tranche de pain de mie %' AND (V_NormTrademark = '' OR V_NormTrademark IS NULL)
Second try:
SELECT V_Name,V_Comment,V_NormName,V_NormComment,V_PackType,V_GTIN,V_ID,V_GlobalCount,V_NormTrademark,V_Trademark,V_NormAggr FROM KCALME_TABLE WHERE V_NormAggr LIKE '% tranche de pain de mie %' AND V_NormTrademark LIKE '%%'
------------- Found solution (max 10) --------------
Croque Monsieur à Poêler - - Dia - 0 - 8480017178640 - OFF#fd1f69c5589316a100690c64d83aef04
----------------------------------------------------
--------------------------------- final result -----------------------------------
{'prompt': "J'ai mangé un yaourt nature et une tranche de pain de mie", 'intents': ['Capture the user food consumption'], 'model': 'mistral-large-latest', 'solutions': {'nutrition': [{'name': 'Yaourt Nature', 'normName': ' yaourt nature ', 'comment': 'yaourt nature', 'normComment': ' yaourt nature ', 'rank': 0, 'id': 'KCA#1bb387dba0faa825bf1b41958b69f8b8', 'quantity': 'un', 'quantityLem': '1', 'pack': ['YA2.w125'], 'type': 'produit laitier', 'gtin': '', 'brand': '', 'time': 'inconnu', 'event': 'déclaration', 'serving': 'YA2-100', 'posiNormName': 0}, {'name': 'Croque Monsieur à Poêler', 'normName': ' croque monsieur poeler ', 'comment': '', 'normComment': '', 'rank': 0, 'id': 'OFF#fd1f69c5589316a100690c64d83aef04', 'quantity': 'une', 'quantityLem': '1', 'pack': ['SAN.w150'], 'type': 'produit de boulangerie', 'gtin': '8480017178640', 'brand': 'Dia', 'time': 'inconnu', 'event': 'déclaration', 'serving': 'SAN-100', 'posiNormName': -1}], 'activity': []}, 'cputime': 6.757978439331055}
----------------------------------------------------------------------------------
LLM CPU Time: 6.757978439331055