Input path: /home/debian/html/nutritwin/output_llm/6613e05cb3829/input.json
Output path: /home/debian/html/nutritwin/output_llm/6613e05cb3829/output.json
Input text: Une salade de fraises avec des kiwis
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: Une salade de fraises avec des kiwis
==================================================================================================================================
==================================== Prompt =============================================
Identify in this list of intents: ["Capture the user food consumption", "Capture the user physical activity", "Other intent"], the intents of the prompt: ###Une salade de fraises avec des kiwis###.
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: "Une salade de fraises avec des kiwis".
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 "Une salade de fraises avec des kiwis".
The sentence does not provide information about the brand, the company, the cooking mode, the time of day when the food was eaten, or whether it's an intent, declaration, or unknown event.
However, we can identify the name and type of food, and the quantity for each ingredient.
Here's the result formatted in JSON:
```json
[
{
"name": "fraises",
"quantity": "une salade",
"cooking": "",
"brand": "",
"company": "",
"type": "fruit",
"time": "",
"event": "unknown"
},
{
"name": "kiwis",
"quantity": "des",
"cooking": "",
"brand": "",
"company": "",
"type": "fruit",
"time": "",
"event": "unknown"
}
]
```
-----------------------------------------------------------------------------
----------------- Make it compliant ------------------
Based on your instructions, here's the analysis of the sentence "Une salade de fraises avec des kiwis".
The sentence does not provide information about the brand, the company, the cooking mode, the time of day when the food was eaten, or whether it's an intent, declaration, or unknown event.
However, we can identify the name and type of food, and the quantity for each ingredient.
Here's the result formatted in JSON:
```json
[
{
"name": "fraises",
"quantity": "une salade",
"cooking": "",
"brand": "",
"company": "",
"type": "fruit",
"time": "",
"event": "unknown"
},
{
"name": "kiwis",
"quantity": "des",
"cooking": "",
"brand": "",
"company": "",
"type": "fruit",
"time": "",
"event": "unknown"
}
]
```
------------------------------------------------------
------------------------ After simplification ------------------------
[ { "name": "fraises", "quantity": "une salade", "cooking": "", "brand": "", "company": "", "type": "fruit", "time": "", "event": "unknown" }, { "name": "kiwis", "quantity": "des", "cooking": "", "brand": "", "company": "", "type": "fruit", "time": "", "event": "unknown" }]
----------------------------------------------------------------------
--------------------------------- LLM result -----------------------------------
{'response': [{'name': 'fraises', 'quantity': 'une salade', 'cooking': '', 'brand': '', 'company': '', 'type': 'fruit', 'time': '', 'event': 'unknown'}, {'name': 'kiwis', 'quantity': 'des', 'cooking': '', 'brand': '', 'company': '', 'type': 'fruit', 'time': '', 'event': 'unknown'}], 'cost': 0.06}
--------------------------------------------------------------------------------
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 '% fraise %' AND (V_NormTrademark = '' OR V_NormTrademark IS NULL)
------------- Found solution (max 20) --------------
Fraise - fraise - crue - - 0 - - - CIQ#a1e7daabf0eef222eb55cee2d9464244
Fraises - fraise - - - 17048 - - - KCA#985bbbfd3e0790251a131d2472a2a13a
Fraises au Citron - fraise citron - - - 776 - - - KCA#edebc181ffc1519049f190184ad0fe5b
Fraise au Bordeaux - fraise bordeau - - - 71 - - - KCA#f4486f0c128d82d8130e08a45c8139dc
Fraises à la Chantilly - fraise chantilly - - - 368 - - - KCA#c87d0d789e71fbc647a3c82f331cc574
Jus de Fraise - ju de fraise - - - 261 - - - KCA#4fdf0443bdabb9f07e0c95aee4fadd2c
Glace à la Fraise - glace fraise - - - 343 - - - KCA#9aa783cbd5442c9a3a7dbac2061e61b1
Tarte aux Fraises - tarte au fraise - aux fraises - - 0 - - - KCA#9334fede766e490d6e36f4982732d2c8
Smoothie Fraise, Miel et Lait de Soja - smoothie fraise miel lait de soja - de soja - - 0 - - - KCA#0df871f30036f11a511b24cd8865c9d1
Gaufre aux Fraises - gaufre au fraise - - - 65 - - - KCA#8de4904b4103fe53986c7f4c61264b68
Bruschette à la Fraise, à la Banane et à la Ricotta - bruschette fraise banane ricotta - - - 2 - - - KCA#fd9db147f698ab1c84b0905704258a5f
Actimel Goût Fraise - actimel gout fraise - - - 415 - - - KCA#7a40c0ab695dfb5c44d0c4e63af769a2
Confiture de Fraise - confiture de fraise - extra ou classique - - 0 - - - CIQ#41b7efec1a5bddcbc9466fbd067f31bf
Crème Glacée à la Fraise - creme glacee fraise - - - 45 - - - KCA#6fce1a9e8f62321ee65590b95d8a9dbf
Jus d'Orange, Mangue et Fraise - ju orange mangue fraise - - - 60 - - - KCA#12cc18043b0813e5110bb808101edc8e
Boisson Lactée Aromatisée à la Fraise - boisson lactee aromatisee fraise - sucrée, au lait partiellement écrémé, enrichie à la vitamine D - - 0 - - - CIQ#3b0dcd3193f9f8c572eef4e1e4988355
----------------------------------------------------
ERROR: no solution for picto in the first solution
ERROR: no solution for picto in the first solution
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 '% kiwi %' AND (V_NormTrademark = '' OR V_NormTrademark IS NULL)
------------- Found solution (max 20) --------------
Kiwi - kiwi - pulpe et graines, cru - - 26071 - - - CIQ#7e3ffca8aa492642e36c6e7ca82ba913
Jus de Kiwi et Raisin Blanc - ju de kiwi raisin blanc - - - 83 - - - KCA#9afe1c1fee0f95f35bb04712f31fb9e8
Salade de Kiwis et Litchis - salade de kiwi litchi - - - 7 - - - KCA#b966113eb8559af7b2dc1b93e6101047
----------------------------------------------------
ERROR: no solution for picto in the first solution
--------------------------------- final result -----------------------------------
{'prompt': 'Une salade de fraises avec des kiwis', 'intents': ['Capture the user food consumption'], 'model': 'mistral-large-latest', 'solutions': {'nutrition': [{'name': 'Fraise', 'normName': ' fraise ', 'comment': 'crue', 'normComment': ' crue ', 'rank': 0, 'id': 'CIQ#a1e7daabf0eef222eb55cee2d9464244', 'quantity': 'une salade', 'quantityLem': '1 salade', 'pack': ['FRA.w100'], 'type': 'fruit', 'gtin': '', 'gtinRef': '', 'brand': '', 'time': '', 'event': 'unknown', 'serving': '', 'posiNormName': 0}, {'name': 'Kiwi', 'normName': ' kiwi ', 'comment': 'pulpe et graines, cru', 'normComment': ' pulpe graine cru ', 'rank': 26071, 'id': 'CIQ#7e3ffca8aa492642e36c6e7ca82ba913', 'quantity': 'des', 'quantityLem': 'des', 'pack': ['KIW.w120'], 'type': 'fruit', 'gtin': '', 'gtinRef': '', 'brand': '', 'time': '', 'event': 'unknown', 'serving': '', 'posiNormName': 0}], 'activity': []}, 'cputime': 7.326750040054321}
----------------------------------------------------------------------------------
LLM CPU Time: 7.326750040054321