Input path: /home/debian/html/nutritwin/output_llm/662a3aa26c31b/input.json
Output path: /home/debian/html/nutritwin/output_llm/662a3aa26c31b/output.json
Input text: J'ai mangé salade de riz petits pois tomates salade
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 salade de riz petits pois tomates salade
==================================================================================================================================
==================================== 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 mangé salade de riz petits pois tomates salade###.
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 mangé salade de riz petits pois tomates salade".
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, I have analyzed the sentence "J'ai mangé salade de riz petits pois tomates salade". However, please note that the sentence is a bit ambiguous as it mentions "salade" twice, which could either mean two different types of salads or a repetition for emphasis. I will assume the former for this analysis.
Here is the information extracted from the sentence:
```json
[
{
"name": "salade de riz",
"quantity": "",
"cooking": "",
"brand": "",
"company": "",
"type": "food",
"time": "",
"event": "declaration"
},
{
"name": "petits pois",
"quantity": "",
"cooking": "",
"brand": "",
"company": "",
"type": "food",
"time": "",
"event": "declaration"
},
{
"name": "tomates",
"quantity": "",
"cooking": "",
"brand": "",
"company": "",
"type": "food",
"time": "",
"event": "declaration"
},
{
"name": "salade",
"quantity": "",
"cooking": "",
"brand": "",
"company": "",
"type": "food",
"time": "",
"event": "declaration"
}
]
```
The sentence does not provide information about the time of day when the food was consumed, the brand, the company, the cooking method, or the quantity of the ingredients. The event is a "declaration" as the food consumption is in the past. The type of food is not specified in the sentence, so I have generally categorized all items as "food".
-----------------------------------------------------------------------------
----------------- Make it compliant ------------------
Based on your instructions, I have analyzed the sentence "J'ai mangé salade de riz petits pois tomates salade". However, please note that the sentence is a bit ambiguous as it mentions "salade" twice, which could either mean two different types of salads or a repetition for emphasis. I will assume the former for this analysis.
Here is the information extracted from the sentence:
```json
[
{
"name": "salade de riz",
"quantity": "",
"cooking": "",
"brand": "",
"company": "",
"type": "food",
"time": "",
"event": "declaration"
},
{
"name": "petits pois",
"quantity": "",
"cooking": "",
"brand": "",
"company": "",
"type": "food",
"time": "",
"event": "declaration"
},
{
"name": "tomates",
"quantity": "",
"cooking": "",
"brand": "",
"company": "",
"type": "food",
"time": "",
"event": "declaration"
},
{
"name": "salade",
"quantity": "",
"cooking": "",
"brand": "",
"company": "",
"type": "food",
"time": "",
"event": "declaration"
}
]
```
The sentence does not provide information about the time of day when the food was consumed, the brand, the company, the cooking method, or the quantity of the ingredients. The event is a "declaration" as the food consumption is in the past. The type of food is not specified in the sentence, so I have generally categorized all items as "food".
------------------------------------------------------
------------------------ After simplification ------------------------
[ { "name": "salade de riz", "quantity": "", "cooking": "", "brand": "", "company": "", "type": "food", "time": "", "event": "declaration" }, { "name": "petits pois", "quantity": "", "cooking": "", "brand": "", "company": "", "type": "food", "time": "", "event": "declaration" }, { "name": "tomates", "quantity": "", "cooking": "", "brand": "", "company": "", "type": "food", "time": "", "event": "declaration" }, { "name": "salade", "quantity": "", "cooking": "", "brand": "", "company": "", "type": "food", "time": "", "event": "declaration" }]
----------------------------------------------------------------------
--------------------------------- LLM result -----------------------------------
{'response': [{'name': 'salade de riz', 'quantity': '', 'cooking': '', 'brand': '', 'company': '', 'type': 'food', 'time': '', 'event': 'declaration'}, {'name': 'petits pois', 'quantity': '', 'cooking': '', 'brand': '', 'company': '', 'type': 'food', 'time': '', 'event': 'declaration'}, {'name': 'tomates', 'quantity': '', 'cooking': '', 'brand': '', 'company': '', 'type': 'food', 'time': '', 'event': 'declaration'}, {'name': 'salade', 'quantity': '', 'cooking': '', 'brand': '', 'company': '', 'type': 'food', 'time': '', 'event': 'declaration'}], 'cost': 0.08448}
--------------------------------------------------------------------------------
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 '% salade de riz %' AND (V_NormTrademark = '' OR V_NormTrademark IS NULL)
------------- Found solution (max 20) --------------
Salade de Riz aux Moules - salade de riz au moule - - - 44 - - - KCA#f9957cdb565d14ac3d1e293e8bac29ef
----------------------------------------------------
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 '% petit poi %' AND (V_NormTrademark = '' OR V_NormTrademark IS NULL)
------------- Found solution (max 20) --------------
Petits Pois - petit poi - égouttés - - 0 - - - CIQ#9ffb5e2c01c96af228f86965c9fb948c
Petits Pois - petit poi - bouillis/cuits à l'eau - - 0 - - - CIQ#dd2da67877ed7f0ac635c10b96769dfc
Petits Pois Cuits - petit poi cuit - - - 111 - - - KCA#c88d8094c5c197d784f8a0c702ef9543
Petits Pois Carottes - petit poi carotte - - - 2323 - - - KCA#7ed2f2b587f72e6b7df2451c218da51e
Petits Pois Surgelés - petit poi surgele - - - 68 - - - KCA#edcd10d133f428fe98f831538e4bd1a2
Petits Pois en Conserve - petit poi en conserve - - - 47 - - - KCA#3bc91a7a7d76aee0c5557fd34697de46
Petits Pois à la Menthe - petit poi menthe - - - 10 - - - KCA#d845720f926d115a4ed1800e1adb93e4
Petits Pois et Carottes - petit poi carotte - égouttés - - 0 - - - CIQ#a210ec3e8f7d4847243833333bd6b29b
Petits Pois à l'Anglaise - petit poi anglaise - - - 10 - - - KCA#3a3b4f6230f5baa603089081dc138a5a
Petits Pois à la Française - petit poi francaise - - - 38 - - - KCA#a4e4d707479fdfbd664f9605815349d4
Petits Pois à la Florentine - petit poi florentine - - - 0 - - - KCA#f7a6e9e3bbf63a662d987a1692cd6cae
Purée de Petits Pois - puree de petit poi - - - 87 - - - KCA#24e05443f69122ac730ba1308a049845
Pigeons aux Petits Pois - pigeon au petit poi - - - 9 - - - KCA#12da10fb01a5c6041026471c38ec8a86
Langouste aux Petits Pois - langouste au petit poi - - - 0 - - - KCA#43f35aa33f745bac853f7ef36f634ee8
Spaghetti aux Petits Pois - spaghetti au petit poi - petits pois - - 0 - - - KCA#a2399bcd885726804760f4e591b0f367
Roti de Cabillaud aux Petits Pois - roti de cabillaud au petit poi - - - 9 - - - KCA#e3b1e6e717d0d11b911ab8e6bb67253c
Purée de Pomme de Terre et Petits Pois - puree de pomme de terre petit poi - - - 12 - - - KCA#4808a903dcc9ab2f718e33de7ab64d00
----------------------------------------------------
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 '% 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 '% salade %' AND (V_NormTrademark = '' OR V_NormTrademark IS NULL)
------------- Found solution (max 20) --------------
Salade Verte - salade verte - avec vinaigrette - - 61586 - - - KCA#4ab5b82c387924b3ce222cda9fdf1f3e
Salade Verte - salade verte - sans vinaigrette - - 15302 - - - KCA#ffaecdf2b67b1ae9d2055afa2173c027
Salade Niçoise - salade nicoise - - - 1348 - - - KCA#efe4104c925882c65bd6f6b73fa7d83d
Salade de Thon - salade de thon - - - 497 - - - KCA#045576a4e0c108e96a1b52eeba4beadd
Salade d'Hiver - salade hiver - - - 78 - - - KCA#5a960774d04f50fe578e463e0f9e2162
Salade Annette - salade annette - - - 41 - - - KCA#79c3168ea2ae726f8a9413652e1e494d
Salade Sucrine - salade sucrine - crue - - 0 - - - CIQ#585cc2b31af0e7eb529fdf895528fe05
Salade Toscane - salade toscane - aux Haricots blancs - - 18 - - - KCA#be8ed7a89aed17fdfb40b9281b842da6
Salade au Crabe - salade crabe - - - 146 - - - KCA#49933e7bbe5c7951d1dc36a9f359bb9e
Salade aux Noix - salade au noix - - - 95 - - - KCA#ec74cd73a5ad2e8c35d392cd1be18ad1
Salade de Crabe - salade de crabe - - - 41 - - - KCA#5f326d471456f93c0648be1cdc2d972b
Salade Bretonne - salade bretonne - - - 24 - - - KCA#f0ec29196404ebd264368d7a3d6ec613
Salade d'Endives - salade endive - - - 3059 - - - KCA#22f49bd5d9db2619011406f0bcce4e4b
Salade Mexicaine - salade mexicaine - - - 71 - - - KCA#baefde744d8bd6461d54f675f6d9df8f
Salade d'Oranges - salade orange - - - 71 - - - KCA#a7fe61d6cb0d6c12eba4ca95e0f74781
Salade Parmesane - salade parmesane - - - 37 - - - KCA#00d21cf2bcf54f149c3be1e85cc57c86
Salade de Boeufs - salade de boeuf - - - 31 - - - KCA#6e7fef1920807286c41436f9dd80d7cd
Salade Savoyarde - salade savoyarde - - - 22 - - - KCA#3f0772f9b75d2e84abb90af05577fa4f
Salade Orientale - salade orientale - - - 19 - - - KCA#1357f3188295c40790017dd101179e20
Salade Antiboise - salade antiboise - - - 14 - - - KCA#31b0831c98bae8b9e92f1a2c4b233310
----------------------------------------------------
ERROR: Wrong quantity: ''
ERROR: no solution for picto in the first solution
ERROR: Wrong quantity: ''
ERROR: no solution for picto in the first solution
--------------------------------- final result -----------------------------------
{'prompt': "J'ai mangé salade de riz petits pois tomates salade", 'intents': ['Capture the user food consumption'], 'model': 'mistral-large-latest', 'solutions': {'nutrition': [{'name': 'Salade de Riz aux Moules', 'normName': ' salade de riz au moule ', 'comment': '', 'normComment': '', 'rank': 44, 'id': 'KCA#f9957cdb565d14ac3d1e293e8bac29ef', 'quantity': '', 'quantityLem': '', 'pack': ['SAL.w125'], 'type': 'food', 'gtin': '', 'gtinRef': '', 'brand': '', 'time': '', 'event': 'declaration', 'serving': '', 'posiNormName': 0}, {'name': 'Petits Pois', 'normName': ' petit poi ', 'comment': 'égouttés', 'normComment': ' egoutte ', 'rank': 0, 'id': 'CIQ#9ffb5e2c01c96af228f86965c9fb948c', 'quantity': '', 'quantityLem': '', 'pack': ['LEG.w150'], 'type': 'food', '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': 'food', 'gtin': '', 'gtinRef': '', 'brand': '', 'time': '', 'event': 'declaration', 'serving': '', 'posiNormName': 0}, {'name': 'Salade Verte', 'normName': ' salade verte ', 'comment': 'avec vinaigrette', 'normComment': ' avec vinaigrette ', 'rank': 61586, 'id': 'KCA#4ab5b82c387924b3ce222cda9fdf1f3e', 'quantity': '', 'quantityLem': '', 'pack': ['SAL.w170'], 'type': 'food', 'gtin': '', 'gtinRef': '', 'brand': '', 'time': '', 'event': 'declaration', 'serving': '', 'posiNormName': 0}], 'activity': [], 'response': ''}, 'cputime': 20.262394905090332}
----------------------------------------------------------------------------------
LLM CPU Time: 20.262394905090332