Input path: /home/debian/html/nutritwin/output_llm/660805712d93d/input.json
Output path: /home/debian/html/nutritwin/output_llm/660805712d93d/output.json
Input text: Champignons betteraves et un peu de chorizo
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: Champignons betteraves et un peu de chorizo
==================================================================================================================================
==================================== Prompt =============================================
Identify in this list of intents: ["Capture the user food consumption", "Capture the user physical activity", "Other intent"], the intents of the prompt: ###Champignons betteraves et un peu de chorizo###.
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: "Champignons betteraves et un peu de chorizo".
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, I have analyzed the sentence "Champignons betteraves et un peu de chorizo". Here is the information extracted:
```json
[
{
"name": "Champignons",
"quantity": "",
"cooking": "",
"brand": "",
"company": "",
"type": "Légume",
"time": "",
"event": "unknown"
},
{
"name": "Betteraves",
"quantity": "",
"cooking": "",
"brand": "",
"company": "",
"type": "Légume",
"time": "",
"event": "unknown"
},
{
"name": "Chorizo",
"quantity": "un peu",
"cooking": "",
"brand": "",
"company": "",
"type": "Viande",
"time": "",
"event": "unknown"
}
]
```
The sentence does not provide information about the brand, company, cooking method, time of eating, or whether it's a declaration or intent. The type of food is identified as "Légume" for mushrooms and beetroot, and "Viande" for chorizo. The quantity for chorizo is "un peu" (a little).
-----------------------------------------------------------------------------
----------------- Make it compliant ------------------
Based on your instructions, I have analyzed the sentence "Champignons betteraves et un peu de chorizo". Here is the information extracted:
```json
[
{
"name": "Champignons",
"quantity": "",
"cooking": "",
"brand": "",
"company": "",
"type": "Légume",
"time": "",
"event": "unknown"
},
{
"name": "Betteraves",
"quantity": "",
"cooking": "",
"brand": "",
"company": "",
"type": "Légume",
"time": "",
"event": "unknown"
},
{
"name": "Chorizo",
"quantity": "un peu",
"cooking": "",
"brand": "",
"company": "",
"type": "Viande",
"time": "",
"event": "unknown"
}
]
```
The sentence does not provide information about the brand, company, cooking method, time of eating, or whether it's a declaration or intent. The type of food is identified as "Légume" for mushrooms and beetroot, and "Viande" for chorizo. The quantity for chorizo is "un peu" (a little).
------------------------------------------------------
------------------------ After simplification ------------------------
[ { "name": "Champignons", "quantity": "", "cooking": "", "brand": "", "company": "", "type": "Légume", "time": "", "event": "unknown" }, { "name": "Betteraves", "quantity": "", "cooking": "", "brand": "", "company": "", "type": "Légume", "time": "", "event": "unknown" }, { "name": "Chorizo", "quantity": "un peu", "cooking": "", "brand": "", "company": "", "type": "Viande", "time": "", "event": "unknown" }]
----------------------------------------------------------------------
--------------------------------- LLM result -----------------------------------
{'response': [{'name': 'Champignons', 'quantity': '', 'cooking': '', 'brand': '', 'company': '', 'type': 'Légume', 'time': '', 'event': 'unknown'}, {'name': 'Betteraves', 'quantity': '', 'cooking': '', 'brand': '', 'company': '', 'type': 'Légume', 'time': '', 'event': 'unknown'}, {'name': 'Chorizo', 'quantity': 'un peu', 'cooking': '', 'brand': '', 'company': '', 'type': 'Viande', 'time': '', 'event': 'unknown'}], 'cost': 0.06839999999999999}
--------------------------------------------------------------------------------
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 '% champignon %' AND (V_NormTrademark = '' OR V_NormTrademark IS NULL)
------------- Found solution (max 10) --------------
Champignon - cèpe, cru - - 0 - - CIQ#507bf7eedd01023a656de6a680e5253b
Champignon - morille, crue - - 0 - - CIQ#5a42db3f720c459ca8a664618d25cb75
Champignon - tout type, cru - - 0 - - CIQ#5a45b2147e895e9c204f1ec73d856944
Champignon - pleurote, crue - - 0 - - CIQ#8a27db7118edd4e9f4660a26806fc021
Champignon - tout type, égoutté - - 0 - - CIQ#334a7f823845a3a699895c405348f517
Champignon - rosé des prés, cru - - 0 - - CIQ#f324b9c23b69a938642850ec277feabe
Champignon - oronge vraie, crue - - 0 - - CIQ#dae7b304a96a7fcf5a6a266a6d84aad8
Champignon - chanterelle ou girolle, crue - - 0 - - CIQ#92c83cfc5f670913dcac08ecee3da035
Champignon - lentin comestible ou shiitaké - - 0 - - CIQ#3c4b31a66351114e03870c4dd8b9ae1b
Champignon - lentin comestible ou shiitaké, séché - - 0 - - CIQ#fca11dc03464769331766aed3628d0ba
----------------------------------------------------
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_ID,V_GlobalCount,V_NormTrademark,V_Trademark,V_NormAggr FROM KCALME_TABLE WHERE V_NormName LIKE '% betterave %' AND (V_NormTrademark = '' OR V_NormTrademark IS NULL)
------------- Found solution (max 10) --------------
Betterave Rouge - - - 8160 - - CIQ#19e3af05ec2db8b4603c4be2bc446a39
Betterave Ménagère - - - 196 - - KCA#cf59645b55ec29f3def37e35399eb3d0
Jus de Betterave, Carotte et Epinard - - - 190 - - KCA#bc44fc6902bae2f6850e3afe6f063d2d
Salade Betteraves et Agneau au Miel - - - 24 - - KCA#2166cb4870932bad02161df026c04633
Salade Betterave, Fenouil et Saumon au Carvi - - - 31 - - KCA#7c82baca18b6e6cbeeeec05c39082e8f
Salade de Betterave, Haricots, Feta et Menthe - - - 106 - - KCA#f31a5e8ed43442368982779c1513d16f
Risotto aux Betteraves - et à la roquette - - 9 - - KCA#76a7da44ad3d01e54c8d3d7ebe35ed32
----------------------------------------------------
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_ID,V_GlobalCount,V_NormTrademark,V_Trademark,V_NormAggr FROM KCALME_TABLE WHERE V_NormName LIKE '% chorizo %' AND (V_NormTrademark = '' OR V_NormTrademark IS NULL)
------------- Found solution (max 10) --------------
Chorizo - - - 14 - - CIQ#a46af02da5ec7aa0a9fa5961dcb42209
Chorizo Sec - - - 3084 - - KCA#d4d56798a68171de83a1251ddbf828fb
Chorizo Supérieur - doux ou fort, type saucisse sèche - - 0 - - CIQ#6c2bfc7543a083f0a2c79697d7a95821
Chorizo Supérieur - doux ou fort, type charcuterie en tranches - - 0 - - CIQ#889704b5222cf94f8d8f0d2196cf793b
Pizza au Chorizo ou Salami - - - 0 - - CIQ#3ea9e0270d39c3f2672f4fb4edf0fe77
Lentilles au Chorizo - - - 37 - - KCA#861eb5d32ed6b0481dec0520a24603f9
Salade de Chorizo - aux Artichauts et aux Poivrons rouges - - 18 - - KCA#a7ca4bd710a44c707d2bfba71c92422e
Lentilles Brunes à la Courgette et au Chorizo - - - 6 - - KCA#488b3d0b5e6b068cb458940010656fd5
----------------------------------------------------
ERROR: no solution for picto in the first solution
--------------------------------- final result -----------------------------------
{'prompt': 'Champignons betteraves et un peu de chorizo', 'intents': ['Capture the user food consumption'], 'model': 'mistral-large-latest', 'solutions': {'nutrition': [{'name': 'Champignon', 'normName': ' champignon ', 'comment': 'cèpe, cru', 'normComment': ' cepe cru ', 'rank': 0, 'id': 'CIQ#507bf7eedd01023a656de6a680e5253b', 'quantity': '', 'quantityLem': '', 'pack': ['LEG.w150'], 'type': 'Légume', 'gtin': '', 'brand': '', 'time': '', 'event': 'unknown', 'serving': '', 'posiNormName': 0}, {'name': 'Betterave Rouge', 'normName': ' betterave rouge ', 'comment': '', 'normComment': '', 'rank': 8160, 'id': 'CIQ#19e3af05ec2db8b4603c4be2bc446a39', 'quantity': '', 'quantityLem': '', 'pack': ['LEG.w150'], 'type': 'Légume', 'gtin': '', 'brand': '', 'time': '', 'event': 'unknown', 'serving': '', 'posiNormName': 0}, {'name': 'Chorizo', 'normName': ' chorizo ', 'comment': '', 'normComment': '', 'rank': 14, 'id': 'CIQ#a46af02da5ec7aa0a9fa5961dcb42209', 'quantity': 'un peu', 'quantityLem': '1 peu', 'pack': ['TR2.w15'], 'type': 'Viande', 'gtin': '', 'brand': '', 'time': '', 'event': 'unknown', 'serving': '', 'posiNormName': 0}], 'activity': []}, 'cputime': 8.732860565185547}
----------------------------------------------------------------------------------
LLM CPU Time: 8.732860565185547