Input path: /home/debian/html/nutritwin/output_llm/663134f6e33f1/input.json
Output path: /home/debian/html/nutritwin/output_llm/663134f6e33f1/output.json
Input text: Aujourd'hui j'ai mangé un sandwich fait maison par la boulangerie c'était au poulet il y avait de la mayonnaise dedans des tomates et de l'avocat
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: Aujourd'hui j'ai mangé un sandwich fait maison par la boulangerie c'était au poulet il y avait de la mayonnaise dedans des tomates et de l'avocat
==================================================================================================================================
==================================== 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: ###Aujourd'hui j'ai mangé un sandwich fait maison par la boulangerie c'était au poulet il y avait de la mayonnaise dedans des tomates et de l'avocat###.
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: "Aujourd'hui j'ai mangé un sandwich fait maison par la boulangerie c'était au poulet il y avait de la mayonnaise dedans des tomates et de l'avocat".
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 "Aujourd'hui j'ai mangé un sandwich fait maison par la boulangerie c'était au poulet il y avait de la mayonnaise dedans des tomates et de l'avocat".
The sentence indicates that the person ate a sandwich, which is a type of food. The sandwich was made by a bakery, but the bakery is not considered a brand or company in this context. The sandwich was filled with chicken, mayonnaise, tomatoes, and avocado.
The sentence does not provide specific quantities for the ingredients, so "quantity" will be left blank. The cooking mode is not specified, so "cooking" will also be left blank. The brand is not specified, so "brand" and "company" will be left blank.
The sentence does not indicate a specific time of day when the sandwich was eaten, so "time" will be left blank. However, the sentence does use the past tense "j'ai mangé", so the event is a "declaration".
Here's the analysis formatted in JSON:
[
{
"name": "sandwich",
"quantity": "",
"cooking": "",
"brand": "",
"company": "",
"type": "food",
"time": "",
"event": "declaration"
},
{
"name": "poulet",
"quantity": "",
"cooking": "",
"brand": "",
"company": "",
"type": "ingredient",
"time": "",
"event": "declaration"
},
{
"name": "mayonnaise",
"quantity": "",
"cooking": "",
"brand": "",
"company": "",
"type": "ingredient",
"time": "",
"event": "declaration"
},
{
"name": "tomates",
"quantity": "",
"cooking": "",
"brand": "",
"company": "",
"type": "ingredient",
"time": "",
"event": "declaration"
},
{
"name": "avocat",
"quantity": "",
"cooking": "",
"brand": "",
"company": "",
"type": "ingredient",
"time": "",
"event": "declaration"
}
]
-----------------------------------------------------------------------------
----------------- Make it compliant ------------------
Based on your instructions, here's the analysis of the sentence "Aujourd'hui j'ai mangé un sandwich fait maison par la boulangerie c'était au poulet il y avait de la mayonnaise dedans des tomates et de l'avocat".
The sentence indicates that the person ate a sandwich, which is a type of food. The sandwich was made by a bakery, but the bakery is not considered a brand or company in this context. The sandwich was filled with chicken, mayonnaise, tomatoes, and avocado.
The sentence does not provide specific quantities for the ingredients, so "quantity" will be left blank. The cooking mode is not specified, so "cooking" will also be left blank. The brand is not specified, so "brand" and "company" will be left blank.
The sentence does not indicate a specific time of day when the sandwich was eaten, so "time" will be left blank. However, the sentence does use the past tense "j'ai mangé", so the event is a "declaration".
Here's the analysis formatted in JSON:
[
{
"name": "sandwich",
"quantity": "",
"cooking": "",
"brand": "",
"company": "",
"type": "food",
"time": "",
"event": "declaration"
},
{
"name": "poulet",
"quantity": "",
"cooking": "",
"brand": "",
"company": "",
"type": "ingredient",
"time": "",
"event": "declaration"
},
{
"name": "mayonnaise",
"quantity": "",
"cooking": "",
"brand": "",
"company": "",
"type": "ingredient",
"time": "",
"event": "declaration"
},
{
"name": "tomates",
"quantity": "",
"cooking": "",
"brand": "",
"company": "",
"type": "ingredient",
"time": "",
"event": "declaration"
},
{
"name": "avocat",
"quantity": "",
"cooking": "",
"brand": "",
"company": "",
"type": "ingredient",
"time": "",
"event": "declaration"
}
]
------------------------------------------------------
------------------------ After simplification ------------------------
[ { "name": "sandwich", "quantity": "", "cooking": "", "brand": "", "company": "", "type": "food", "time": "", "event": "declaration" }, { "name": "poulet", "quantity": "", "cooking": "", "brand": "", "company": "", "type": "ingredient", "time": "", "event": "declaration" }, { "name": "mayonnaise", "quantity": "", "cooking": "", "brand": "", "company": "", "type": "ingredient", "time": "", "event": "declaration" }, { "name": "tomates", "quantity": "", "cooking": "", "brand": "", "company": "", "type": "ingredient", "time": "", "event": "declaration" }, { "name": "avocat", "quantity": "", "cooking": "", "brand": "", "company": "", "type": "ingredient", "time": "", "event": "declaration" }]
----------------------------------------------------------------------
--------------------------------- LLM result -----------------------------------
{'response': [{'name': 'sandwich', 'quantity': '', 'cooking': '', 'brand': '', 'company': '', 'type': 'food', 'time': '', 'event': 'declaration'}, {'name': 'poulet', 'quantity': '', 'cooking': '', 'brand': '', 'company': '', 'type': 'ingredient', 'time': '', 'event': 'declaration'}, {'name': 'mayonnaise', 'quantity': '', 'cooking': '', 'brand': '', 'company': '', 'type': 'ingredient', 'time': '', 'event': 'declaration'}, {'name': 'tomates', 'quantity': '', 'cooking': '', 'brand': '', 'company': '', 'type': 'ingredient', 'time': '', 'event': 'declaration'}, {'name': 'avocat', 'quantity': '', 'cooking': '', 'brand': '', 'company': '', 'type': 'ingredient', 'time': '', 'event': 'declaration'}], 'cost': 0.10439999999999999}
--------------------------------------------------------------------------------
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 %' AND (V_NormTrademark = '' OR V_NormTrademark IS NULL)
------------- Found solution (max 20) --------------
Sandwich - sandwich - - - 43 - - - CIQ#d04a289c52343e85dfc2a31bf6d60efe
Sandwich Panini - sandwich panini - jambon cru, mozzarella, tomates - - 569 - - - CIQ#5495daff17d84f87d1ab72bab35646cc
Sandwich Baguette - sandwich baguette - - - 0 - - - CIQ#ecdbce2254ce082246ccea95b54322d3
Sandwich Baguette - sandwich baguette - jambon, beurre - - 544 - - - CIQ#bd804df922badefbc8215232b9b741aa
Sandwich Baguette - sandwich baguette - salami, beurre - - 59 - - - CIQ#92b9f1c35fd21237d9716ba633faf6c3
Sandwich Baguette - sandwich baguette - jambon emmental - - 0 - - - CIQ#a3044be4730437e3137525aaa8469e38
Sandwich Baguette - sandwich baguette - pâté, cornichons - - 138 - - - CIQ#dffdf1e5117ae64f00c22627ab3670f2
Sandwich Baguette - sandwich baguette - camembert, beurre - - 23 - - - CIQ#0080a72a2d54a3ea5e04c0c631ac01fd
Sandwich Baguette - sandwich baguette - saucisson, beurre - - 0 - - - CIQ#64a51f36b8fcf7fb6aa69713d78a7477
Sandwich Baguette - sandwich baguette - saumon fumé, beurre - - 191 - - - CIQ#f319acba3059dd568c3ec0b09ffee8cd
Sandwich Baguette - sandwich baguette - thon, maïs, crudités - - 0 - - - CIQ#6bc3fa7c33408c471a521687ea57c022
Sandwich Baguette - sandwich baguette - jambon, emmental, beurre - - 5174 - - - CIQ#d4b56c51ab3ed4856726dc5540397da5
Sandwich Baguette - sandwich baguette - merguez, ketchup moutarde - - 71 - - - CIQ#5f4dda655b3b11f243dc5af84eb97c1f
Sandwich Baguette - sandwich baguette - crudités diverses, mayonnaise - - 17 - - - CIQ#80a019abb0e07979e1fadd760efb9be0
Sandwich Baguette - sandwich baguette - oeuf, crudités, tomate, salade, mayonnaise - - 0 - - - CIQ#ce1d206be86434bec3c26d455f9689e4
Sandwich Baguette - sandwich baguette - porc, crudités, tomate, salade, mayonnaise - - 0 - - - CIQ#8e8c84ec0b67513a1590bfedccec16eb
Sandwich Baguette - sandwich baguette - thon, crudités, tomate, salade, mayonnaise - - 0 - - - CIQ#2216cbeb818ce287e644567239e12d90
Sandwich Baguette - sandwich baguette - dinde, crudités, tomate, salade, mayonnaise - - 0 - - - CIQ#1c19785531992d7f6a59485b7ce19ca8
Sandwich Baguette - sandwich baguette - poulet, crudités, tomate, salade, mayonnaise - - 0 - - - CIQ#3d6b1b2e72884eb8494f20f7bb6afba0
Sandwich Baguette - sandwich baguette - jambon, oeuf dur, crudités, tomate, salade, beurre - - 0 - - - CIQ#f0412e36d0218917bace2a1194833eed
----------------------------------------------------
ERROR: Wrong quantity: ''
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 '% poulet %' AND (V_NormTrademark = '' OR V_NormTrademark IS NULL)
------------- Found solution (max 20) --------------
Poulet - poulet - - - 8795 - - - KCA#2b8a36538eae9db1a126faeda234fa36
Poulet - poulet - escalope panée - - 0 - - - CIQ#bae631670e62c77d45034eff236a1db0
Poulet - poulet - croquette panée ou nuggets - - 0 - - - CIQ#d8096293142be1614c2e2d792fb0d135
Poulet - poulet - cuisse, viande et peau, cru - - 0 - - - CIQ#7de39f1b0aefe1479f456f2eeffe360d
Poulet - poulet - filet, sans peau, sauté/poêlé - - 0 - - - CIQ#bdeff1663af053ba0ef4dfc523f03224
Poulet - poulet - cuisse, viande, rôti/cuit au four - - 0 - - - CIQ#2760b1ebd16b8f276e8dc49751990e69
Poulet - poulet - viande et peau, rôti/cuit au four - - 0 - - - CIQ#ea614234aa25e31d1b1bd4f1dbbbce1a
Poulet - poulet - filet, sans peau, sauté/poêlé, bio - - 0 - - - CIQ#8d157895c46690cf07811470dcb92052
Poulet - poulet - cuisse, viande, bouilli/cuit à l'eau - - 0 - - - CIQ#698505f6db4f71029aeeab2e3a06e19c
Poulet - poulet - manchons marinés, rôtis/cuits au four - - 0 - - - CIQ#960d39abb32cc5f3c56126dfd2e03e8f
Poulet - poulet - aile, viande et peau, rôti/cuit au four - - 0 - - - CIQ#f9c58ba832cc3603548917e8084ee304
Poulet - poulet - cuisse, viande et peau, rôtie/cuite au four - - 0 - - - CIQ#124b0a1b1080244ea5c3ca52f7866c32
Poulet - poulet - poitrine, viande et peau, rôti/cuit au four - - 0 - - - CIQ#e3de333fab10eb5afe51680b6cb1d486
Poulet - poulet - cuisse, viande et peau, bouilli/cuit à l'eau - - 0 - - - CIQ#b2d906c4947a322c9b05108f5b1a0ae3
Poulet Rôti - poulet roti - - - 10622 - - - KCA#8f4155b2705cf340fe3f2777bcfbe7ea
Poulet Frit - poulet frit - - - 2594 - - - KCA#dd0ae748ef0c8413ce4c89f25d8229d1
Poulet Marengo - poulet marengo - - - 57 - - - KCA#f706ed1fc95afe84c20df295d5844034
Poulet à l'Ail - poulet ail - - - 51 - - - KCA#ada607ff9b9084654b8663e6d96eaa93
Poulet au Miel - poulet miel - et salade de Fenouil et Céleri à la crème - - 43 - - - KCA#10b8495a1834253e87733dc33ffcfd80
Poulet au Curry - poulet curry - - - 1421 - - - KCA#89f6cd1b00b67266a7db24596103e009
----------------------------------------------------
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
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
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
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
ERROR: Wrong quantity: ''
ERROR: no solution for picto in the first solution
ERROR: Wrong quantity: ''
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 '% mayonnaise %' AND (V_NormTrademark = '' OR V_NormTrademark IS NULL)
------------- Found solution (max 20) --------------
Mayonnaise - mayonnaise - - - 10947 - - - KCA#f730f0a51c023e7391c34448b45fae40
Mayonnaise Piquante - mayonnaise piquante - - - 22 - - - KCA#112f3302bf7b965d8aa0a3d19f569e36
Mayonnaise à l'Huile de Tournesol - mayonnaise huile de tournesol - - - 181 - - - KCA#050ac243eafcff755bc4f515e10a1560
Mayonnaise Allégée en Matières Grasses - mayonnaise allegee en matiere grasse - - - 510 - - - KCA#d64a40af3fef944c351452c9849a32cf
Moules à la Mayonnaise - moule mayonnaise - - - 18 - - - KCA#d897514f209bce30c3e937c4d5b460da
Oeufs Durs Mayonnaise - oeuf dur mayonnaise - - - 663 - - - KCA#83f10a89cbed801d608ea90ed01c9822
Crevettes à la Mayonnaise - crevette mayonnaise - - - 53 - - - KCA#008a9811e12a43807907909aad094d60
Langouste Mayonnaise - langouste mayonnaise - - - 7 - - - KCA#e959d71726baa72432e3c3feba5b0975
Langues de Mouton à la Mayonnaise - langue de mouton mayonnaise - - - 1 - - - KCA#14f65e5fe485252b36546e4beef2c460
----------------------------------------------------
ERROR: Wrong quantity: ''
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 '% tomate %' AND (V_NormTrademark = '' OR V_NormTrademark IS NULL)
------------- Found solution (max 20) --------------
Tomate - tomate - crue - - 50564 - - - CIQ#9019c33adc1aff1aeff07888f760e3dc
Tomate - tomate - purée - - 0 - - - CIQ#98e08e3b00fecca745d7da29e1015a95
Tomate - tomate - pulpe - - 0 - - - CIQ#fd785fdebdb36567c615d2cf46456ffd
Tomate - tomate - concentré - - 0 - - - CIQ#7020e6d5e5bd9e09aaa1661220ba09b7
Tomate - tomate - pelée, égouttée - - 0 - - - CIQ#e42ed02a1db9c324a72333e04d401dc1
Tomate - tomate - double concentré - - 0 - - - CIQ#316f9d6fdf5ec84b18998fae96416e09
Tomate - tomate - séchée, à l'huile - - 0 - - - CIQ#b7e1592c157fef2c1429cdc04e65f429
Tomate - tomate - rôtie/cuite au four - - 0 - - - CIQ#abc1ee10e1ef1b8d9ea01e5cf5081ac9
Tomate - tomate - pulpe et peau, rôtie/cuite au four - - 0 - - - CIQ#a670b9fa38af8c6557b321a08d7ab367
Tomate Ronde - tomate ronde - crue - - 0 - - - CIQ#684dc9134dc864e3c83f5330fa9965d4
Tomate Farcie - tomate farcie - - - 1889 - - - CIQ#6662d127dcc7f87a176e7cda4540b6d5
Tomate Cerise - tomate cerise - crue - - 0 - - - CIQ#9f76e2172737f480f1c9b66f3627bfb0
Tomate Grappe - tomate grappe - crue - - 0 - - - CIQ#2bdccc054e39de9382dcb2ff97b1204d
Tomate Cerise - tomate cerise - tomate cerise - - 0 - - - KCA#fc7d1647e177b261c9a22262037f6216
Tomate Séchée - tomate sechee - tomate séchée - - 0 - - - KCA#1dfa8e1ad113a5175e6a3ba4bee46416
Tomates au Four - tomate four - au four - - 0 - - - KCA#7bd06a9534bdcb97e7af0143ac0124d5
Tomates Farcies - tomate farcie - tomates farcies - - 0 - - - KCA#6e01a7596f6a74b9bca3e51ca2721e81
Tomates Tartares - tomate tartare - tomates tartares - - 0 - - - KCA#e15190c59aa8508125d81de65be88670
Tomate Concentrée - tomate concentree - tomate concentrée - - 0 - - - KCA#22854ad0ad81beeccc0841c1f0c5d66c
Tomates Provençales - tomate provencale - tomates provençales - - 0 - - - KCA#799358a4b450be03bfd4014d3908c6dc
----------------------------------------------------
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
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
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
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 '% avocat %' AND (V_NormTrademark = '' OR V_NormTrademark IS NULL)
------------- Found solution (max 20) --------------
Avocat - avocat - pulpe, cru - - 18525 - - - CIQ#4c9a17da72301fbf9c8312ed66633aff
Avocats au Crabe - avocat crabe - - - 225 - - - KCA#4c24d976226e28c5fa9ee50881e6d3bf
Avocats en Turban - avocat en turban - - - 5 - - - KCA#d07f7eda1b5eeb0ad897f6ea371aeb54
Avocats en Cocktail - avocat en cocktail - - - 62 - - - KCA#eb6912896511d3f749c980b5d55dce23
Avocats aux Crevettes - avocat au crevette - - - 195 - - - KCA#5dcdeb94d09030bfe9f4f6ecb11c25c9
Avocats à la Macédoine - avocat macedoine - - - 38 - - - KCA#57a72ef4b64fb5a3ebc331e7d25d6074
Riz à l'Avocat et au Wasabi - riz avocat wasabi - - - 14 - - - KCA#573ba2a186eadbe23f8a9572bc99f30e
Maki Avocat - maki avocat - - - 272 - - - KCA#1e70f3c558729c7ee7ccbe10af55eac6
Huile d'Avocat - huile avocat - - - 0 - - - CIQ#36fd72607444ab90dea2188e2918dfc3
Maki Saumon Avocat - maki saumon avocat - - - 861 - - - KCA#725e4073ccaee17f4a77ab78eb5b90a5
Salade de Tomates à l'Avocat - salade de tomate avocat - et bouchées aux Lentilles rouges - - 132 - - - KCA#c7116cef4371b5b219a958c0c872dfb6
----------------------------------------------------
ERROR: Wrong quantity: ''
ERROR: no solution for picto in the first solution
--------------------------------- final result -----------------------------------
{'prompt': "Aujourd'hui j'ai mangé un sandwich fait maison par la boulangerie c'était au poulet il y avait de la mayonnaise dedans des tomates et de l'avocat", 'intents': ['Capture the user food consumption'], 'model': 'mistral-large-latest', 'solutions': {'nutrition': [{'name': 'Sandwich', 'normName': ' sandwich ', 'comment': '', 'normComment': '', 'rank': 43, 'id': 'CIQ#d04a289c52343e85dfc2a31bf6d60efe', 'quantity': '', 'quantityLem': '', 'pack': ['SAN.w250'], 'type': 'food', 'gtin': '', 'gtinRef': '', 'brand': '', 'time': '', 'event': 'declaration', 'serving': '', 'posiNormName': 0}, {'name': 'Poulet', 'normName': ' poulet ', 'comment': '', 'normComment': '', 'rank': 8795, 'id': 'KCA#2b8a36538eae9db1a126faeda234fa36', 'quantity': '', 'quantityLem': '', 'pack': ['POU.w100', 'CUI.w200'], 'type': 'ingredient', 'gtin': '', 'gtinRef': '', 'brand': '', 'time': '', 'event': 'declaration', 'serving': '', 'posiNormName': 0}, {'name': 'Mayonnaise', 'normName': ' mayonnaise ', 'comment': '', 'normComment': '', 'rank': 10947, 'id': 'KCA#f730f0a51c023e7391c34448b45fae40', 'quantity': '', 'quantityLem': '', 'pack': ['MAY.w15', 'CSS.w15'], 'type': 'ingredient', 'gtin': '', 'gtinRef': '', 'brand': '', 'time': '', 'event': 'declaration', 'serving': '', 'posiNormName': 0}, {'name': 'Tomate', 'normName': ' tomate ', 'comment': 'crue', 'normComment': ' crue ', 'rank': 50564, 'id': 'CIQ#9019c33adc1aff1aeff07888f760e3dc', 'quantity': '', 'quantityLem': '', 'pack': ['TOM.w150'], 'type': 'ingredient', 'gtin': '', 'gtinRef': '', 'brand': '', 'time': '', 'event': 'declaration', 'serving': '', 'posiNormName': 0}, {'name': 'Avocat', 'normName': ' avocat ', 'comment': 'pulpe, cru', 'normComment': ' pulpe cru ', 'rank': 18525, 'id': 'CIQ#4c9a17da72301fbf9c8312ed66633aff', 'quantity': '', 'quantityLem': '', 'pack': ['AVO.w200'], 'type': 'ingredient', 'gtin': '', 'gtinRef': '', 'brand': '', 'time': '', 'event': 'declaration', 'serving': '', 'posiNormName': 0}], 'activity': [], 'response': ''}, 'cputime': 13.447863101959229}
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LLM CPU Time: 13.447863101959229