Input path: /home/debian/html/nutritwin/output_llm/662278df347c7/input.json
Output path: /home/debian/html/nutritwin/output_llm/662278df347c7/output.json
Input text: J'ai bu un grand verre de lait et j'ai mangé un sandwich au jambon
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 bu un grand verre de lait et j'ai mangé un sandwich au jambon
==================================================================================================================================
==================================== Prompt =============================================
Identify in this list of intents: ["Capture the user food consumption", "Capture the user physical activity", "Answer a nutrition question", "Other intent"], the intents of the prompt: ###J'ai bu un grand verre de lait et j'ai mangé un sandwich au jambon###.
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: "J'ai bu un grand verre de lait et j'ai mangé un sandwich au jambon".
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.
The level of cooking mode is not in the name.
There is no quantity in the name, ex: the name for "une pomme" is "pomme".
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 bu un grand verre de lait et j'ai mangé un sandwich au jambon".
The sentence describes two food items: "un grand verre de lait" and "un sandwich au jambon".
1. For "un grand verre de lait":
- Name: lait
- Quantity: un grand verre
- Cooking: None specified
- Brand: "" (as it's not specified in the sentence)
- Company: "" (as it's not specified in the sentence)
- Type: beverage
- Time: unknown (as it's not specified in the sentence)
- Event: declaration (as the consumption is in the past)
2. For "un sandwich au jambon":
- Name: sandwich au jambon
- Quantity: un
- Cooking: None specified
- Brand: "" (as it's not specified in the sentence)
- Company: "" (as it's not specified in the sentence)
- Type: food
- Time: unknown (as it's not specified in the sentence)
- Event: declaration (as the consumption is in the past)
The formatted result in JSON would look like this:
```json
[
{
"name": "lait",
"quantity": "un grand verre",
"cooking": "",
"brand": "",
"company": "",
"type": "beverage",
"time": "unknown",
"event": "declaration"
},
{
"name": "sandwich au jambon",
"quantity": "un",
"cooking": "",
"brand": "",
"company": "",
"type": "food",
"time": "unknown",
"event": "declaration"
}
]
```
-----------------------------------------------------------------------------
----------------- Make it compliant ------------------
Based on your instructions, here's the analysis of the sentence "J'ai bu un grand verre de lait et j'ai mangé un sandwich au jambon".
The sentence describes two food items: "un grand verre de lait" and "un sandwich au jambon".
1. For "un grand verre de lait":
- Name: lait
- Quantity: un grand verre
- Cooking: None specified
- Brand: "" (as it's not specified in the sentence)
- Company: "" (as it's not specified in the sentence)
- Type: beverage
- Time: unknown (as it's not specified in the sentence)
- Event: declaration (as the consumption is in the past)
2. For "un sandwich au jambon":
- Name: sandwich au jambon
- Quantity: un
- Cooking: None specified
- Brand: "" (as it's not specified in the sentence)
- Company: "" (as it's not specified in the sentence)
- Type: food
- Time: unknown (as it's not specified in the sentence)
- Event: declaration (as the consumption is in the past)
The formatted result in JSON would look like this:
```json
[
{
"name": "lait",
"quantity": "un grand verre",
"cooking": "",
"brand": "",
"company": "",
"type": "beverage",
"time": "unknown",
"event": "declaration"
},
{
"name": "sandwich au jambon",
"quantity": "un",
"cooking": "",
"brand": "",
"company": "",
"type": "food",
"time": "unknown",
"event": "declaration"
}
]
```
------------------------------------------------------
------------------------ After simplification ------------------------
[ { "name": "lait", "quantity": "un grand verre", "cooking": "", "brand": "", "company": "", "type": "beverage", "time": "unknown", "event": "declaration" }, { "name": "sandwich au jambon", "quantity": "un", "cooking": "", "brand": "", "company": "", "type": "food", "time": "unknown", "event": "declaration" }]
----------------------------------------------------------------------
--------------------------------- LLM result -----------------------------------
{'response': [{'name': 'lait', 'quantity': 'un grand verre', 'cooking': '', 'brand': '', 'company': '', 'type': 'beverage', 'time': 'unknown', 'event': 'declaration'}, {'name': 'sandwich au jambon', 'quantity': 'un', 'cooking': '', 'brand': '', 'company': '', 'type': 'food', 'time': 'unknown', 'event': 'declaration'}], 'cost': 0.08706}
--------------------------------------------------------------------------------
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 '% lait %' AND (V_NormTrademark = '' OR V_NormTrademark IS NULL)
------------- Found solution (max 20) --------------
Lait - lait - teneur en matière grasse inconnue, UHT, aliment moyen - - 0 - - - CIQ#ebdfafe0fce6b513193ae9c0855b4094
Lait à 1 - lait - 2% de matière grasse, UHT, enrichi en plusieurs vitamines - - 0 - - - CIQ#825f8bcb068ecde315938147ed819623
Lait Entier - lait entier - - - 1435 - - - KCA#c131edf4d3c1e17da0b0a54b5ed8bbb6
Lait Écrémé - lait ecreme - UHT - - 9353 - - - CIQ#27de8d007093ae392f4b782851e7fd9c
Lait Entier - lait entier - UHT - - 0 - - - CIQ#5118aac9b89cceae9a62423175de70eb
Lait Écrémé - lait ecreme - pasteurisé - - 0 - - - CIQ#1622e54576ffea9bca81697cacb48d94
Lait Entier - lait entier - pasteurisé - - 0 - - - CIQ#d5881852b522b09ee02aa0fe46885b00
Lait de Soja - lait de soja - - - 3001 - - - KCA#7484ab8a01f886bca7607cf06a579a2c
Lait d'Avoine - lait avoine - - - 837 - - - KCA#54605e0becbb04ace3db6bf78748c15f
Lait de Poule - lait de poule - sans alcool - - 0 - - - CIQ#f6756ecdc46ec65e5972c6aaf481f4a2
Lait en Poudre - lait en poudre - écrémé - - 117 - - - CIQ#1d9ba583216533c41321ffd9ea51b327
Lait en Poudre - lait en poudre - entier - - 25 - - - CIQ#be7d16f0a05422e5eb1d5ff077dee20c
Lait de Brebis - lait de brebi - entier - - 0 - - - CIQ#b54f3b8a48f8d3e0ba7a0228c8adca4f
Lait de Jument - lait de jument - entier - - 0 - - - CIQ#05ea74b811b1a15ad91876c22391f13a
Lait en Poudre - lait en poudre - demi-écrémé - - 0 - - - CIQ#ee03115de1c18f635dbb62d80d6f9715
Lait de Chèvre - lait de chevre - entier, cru - - 0 - - - CIQ#8fb6afe4302a0073de91d274e3722c3e
Lait de Chèvre - lait de chevre - entier, UHT - - 0 - - - CIQ#9d462cfc80afac9cf259f0f2f305db74
Lait de Chèvre - lait de chevre - demi-écrémé, UHT - - 0 - - - CIQ#a497c21ecfbd7c2930cb99326897a779
Lait 1/2 Écrémé - lait 1/2 ecreme - - - 23220 - - - KCA#d5b12fbedab6d0f0a741feeaa8e92b35
Lait Entier UHT - lait entier uht - - - 25 - - - KCA#aeb66cc691b5e08f15b01dc094a51d18
----------------------------------------------------
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 '% sandwich jambon %' AND (V_NormTrademark = '' OR V_NormTrademark IS NULL)
Second 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_NormAggr LIKE '% sandwich jambon %' AND V_NormTrademark LIKE '%%'
------------- Found solution (max 20) --------------
Croque Monsieur - croque monsieur - - Starbucks - 0 - 3700365092791 - 3700365092791 - OFF#f680b2833f2d16fdc8fa21bc2f5051f4
Pain Polaire Surprise - pain polaire surprise - - Carrefour - 0 - 3560071067533 - 3560071067533 - OFF#7ba281b28490d1d425d5448caff19ce7
Le Jambon Fumé Comté AOP - jambon fume comte aop - - Monoprix - 0 - 3350033274808 - 3350033274808 - OFF#576130ad3aa43ec111c1e2d5eaf88a05
Jambon Cheddar et Roquette - jambon cheddar roquette - - Monoprix - 0 - 3350033199552 - 3350033199552 - OFF#59768325df841c07684b18e39df6b5e9
Le Petit Viennois Jambon Beurre - petit viennoi jambon beurre - - Monoprix - 0 - 3350033183070 - 3350033183070 - OFF#ac467c1ee45336a8940d95d9e9a8f579
Simple et Bon Complet Jambon Beurre - simple bon complet jambon beurre - - Sodebo - 0 - 3242272861058 - 3242272861058 - OFF#1ed117a739d3bed3cbc7650c4afc49d0
Xxl 3 Jambon Emmental Salade 1 Gratuit - xxl jambon emmental salade gratuit - - Daunat - 0 - 3367651003680 - 3367651003680 - OFF#fdb69ad3194c5dc60dd8e1a3491565f4
Sandwich Maxi Simple Bon Jambon Salade Emmental - sandwich maxi simple bon jambon salade emmental - - Sodebo - 0 - 3242272907251 - 3242272907251 - OFF#4c8d2a7c166b43ad59940dd7062627bf
Le Club Jambon Emmental et Pain de Mie au Blé Malté - club jambon emmental pain de mie ble malte - - Monoprix - 0 - 3350033021150 - 3350033021150 - OFF#b66a66aded20a321501798cb9e068a75
Sandwich Jambon Cuit - sandwich jambon cuit - - Carrefour - 0 - 5400101055797 - 5400101055797 - OFF#1db1ee3db9926e1d54c860f2b05d23c9
Sandwich Jambon Chèvre - sandwich jambon chevre - - Sodebo - 0 - 16958395 - 16958395 - OFF#b0bd0a61822057a02bd645eeaa97cb2a
Sandwich Jambon Beurre - sandwich jambon beurre - - Cora - 0 - 3257981230804 - 3257981230804 - OFF#df2c3ed8f8d4bf5c06d723fc0f53163b
Sandwich Jambon Beurre - sandwich jambon beurre - - Belle France - 0 - 3258561471037 - 3258561471037 - OFF#80691b1d68ad2c2cae779666783f2d77
Sandwich Jambon Beurre - sandwich jambon beurre - - Franprix - 0 - 3263858768714 - 3263858768714 - OFF#1af700d4f0e31f205cebd97609b52591
Sandwich Jambon Beurre - sandwich jambon beurre - - Franprix - 0 - 3263858768721 - 3263858768714 - OFF#810cd55349743dcc3113c6000a8f13df
Sandwich Jambon Cheddar - sandwich jambon cheddar - - Daunat - 0 - 13676513 - 13676513 - OFF#be510678d401cfad6f31279f1b7c5866
Sandwich Jambon Fromage - sandwich jambon fromage - - Marks & Spencer - 0 - 29038305 - 29038305 - OFF#0cd8a35c87512eb3d3739295278be696
Sandwich Jambon Cheddar - sandwich jambon cheddar - - Cora - 0 - 3257985754580 - 3257985754580 - OFF#1813c52e6c3d085aa9bd7e7ffa5b0816
Sandwich Jambon Crudité - sandwich jambon crudite - - Monoprix - 0 - 3350033021167 - 3350033021167 - OFF#d7f7bc914e02a95528ca6754a713c432
Sandwich Jambon Emmental - sandwich jambon emmental - - Les Mousquetaires - 0 - 3250392384364 - 3250392384364 - OFF#afe625c2115a98e4139e3fce4cb16c49
----------------------------------------------------
--------------------------------- final result -----------------------------------
{'prompt': "J'ai bu un grand verre de lait et j'ai mangé un sandwich au jambon", 'intents': ['Capture the user food consumption'], 'model': 'mistral-large-latest', 'solutions': {'nutrition': [{'name': 'Lait', 'normName': ' lait ', 'comment': 'teneur en matière grasse inconnue, UHT, aliment moyen', 'normComment': ' teneur en matiere grasse inconnue uht aliment moyen ', 'rank': 0, 'id': 'CIQ#ebdfafe0fce6b513193ae9c0855b4094', 'quantity': 'un grand verre', 'quantityLem': '1 grand verre', 'pack': ['VX1', 'VA2', 'VA3', 'BI4', 'VA4'], 'type': 'beverage', 'gtin': '', 'gtinRef': '', 'brand': '', 'time': 'unknown', 'event': 'declaration', 'serving': 'VX1-100', 'posiNormName': 0}, {'name': 'Croque Monsieur', 'normName': ' croque monsieur ', 'comment': '', 'normComment': '', 'rank': 0, 'id': 'OFF#f680b2833f2d16fdc8fa21bc2f5051f4', 'quantity': 'un', 'quantityLem': '1', 'pack': ['SAN.w150'], 'type': 'food', 'gtin': '3700365092791', 'gtinRef': '3700365092791', 'brand': 'Starbucks', 'time': 'unknown', 'event': 'declaration', 'serving': 'SAN-100', 'posiNormName': -1}], 'activity': [], 'response': ''}, 'cputime': 16.032371759414673}
----------------------------------------------------------------------------------
LLM CPU Time: 16.032371759414673