Input path: /home/debian/html/nutritwin/output_llm/660cea435ff49/input.json
Output path: /home/debian/html/nutritwin/output_llm/660cea435ff49/output.json
Input text: J'ai mangé deux fraises et je suis allé courir dans le parc d'à côté
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 deux fraises et je suis allé courir dans le parc d'à côté
==================================================================================================================================
==================================== Prompt =============================================
Identify in this list of intents: ["Capture the user food consumption", "Capture the user physical activity", "Other intent"], the intents of the prompt: ###J'ai mangé deux fraises et je suis allé courir dans le parc d'à côté###.
Format the result in JSON format: {intents: []}.
=========================================================================================
------------------------------ LLM Raw response -----------------------------
{
"intents": ["Capture the user food consumption", "Capture the user physical activity"]
}
-----------------------------------------------------------------------------
----------------- Make it compliant ------------------
{
"intents": ["Capture the user food consumption", "Capture the user physical activity"]
}
------------------------------------------------------
------------------------ After simplification ------------------------
{"intents": ["Capture the user food consumption", "Capture the user physical activity"]}
----------------------------------------------------------------------
==================================== Prompt =============================================
I need to identify food information from sentences.
Analyze the following french sentence: "J'ai mangé deux fraises et je suis allé courir dans le parc d'à côté".
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 "J'ai mangé deux fraises et je suis allé courir dans le parc d'à côté".
The sentence mentions the consumption of food in the past, so the event is a "declaration". However, the time of day when the food was eaten is not specified in the sentence.
The food item mentioned is "fraises" (strawberries). The quantity is "deux" (two). The type of food is "fruit". The brand, cooking mode, and company are not specified in the sentence.
Here's the information formatted in JSON:
```json
[
{
"name": "fraises",
"quantity": "deux",
"cooking": "",
"brand": "",
"company": "",
"type": "fruit",
"time": "unknown",
"event": "declaration"
}
]
```
-----------------------------------------------------------------------------
----------------- Make it compliant ------------------
Based on your instructions, here's the analysis of the sentence "J'ai mangé deux fraises et je suis allé courir dans le parc d'à côté".
The sentence mentions the consumption of food in the past, so the event is a "declaration". However, the time of day when the food was eaten is not specified in the sentence.
The food item mentioned is "fraises" (strawberries). The quantity is "deux" (two). The type of food is "fruit". The brand, cooking mode, and company are not specified in the sentence.
Here's the information formatted in JSON:
```json
[
{
"name": "fraises",
"quantity": "deux",
"cooking": "",
"brand": "",
"company": "",
"type": "fruit",
"time": "unknown",
"event": "declaration"
}
]
```
------------------------------------------------------
------------------------ After simplification ------------------------
[ { "name": "fraises", "quantity": "deux", "cooking": "", "brand": "", "company": "", "type": "fruit", "time": "unknown", "event": "declaration" }]
----------------------------------------------------------------------
--------------------------------- LLM result -----------------------------------
{'response': [{'name': 'fraises', 'quantity': 'deux', 'cooking': '', 'brand': '', 'company': '', 'type': 'fruit', 'time': 'unknown', 'event': 'declaration'}], 'cost': 0.05796}
--------------------------------------------------------------------------------
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
==================================== Prompt =============================================
I need to identify physical activities information from sentences.
Analyze the following french sentence: "J'ai mangé deux fraises et je suis allé courir dans le parc d'à côté".
Identify all sports or physical activities, its current name and its duration if it exists.
If possible, map the name on one of the following activities in french: ["Basket-ball", "Cyclisme", "Boxe", "Danse", "Zumba", "Plong\u00e9e sous-marine", "Escrime", "Football", "Jardinage", "Golf", "Gymnastique", "Judo", "Karat\u00e9", "Corde \u00e0 sauter", "Rameur d'appartement", "Course \u00e0 pied", "Faire l'amour", "Ski de descente", "Natation", "Tennis", "Tapis de course", "A\u00e9robic", "Ski de fond", "danse", "V\u00e9lo d'appartement", "Aquabiking", "V\u00e9lo elliptique", "Exercice physique", "Equitation", "sports", "Escalade", "sports", "Patins en ligne", "sports", "Tennis de table", "sports", "Marche", "Activit\u00e9s nautiques et aquatiques", "Marche avec un chien", "T\u00e2ches m\u00e9nag\u00e8res", "Marche nordique"].
Ignore what it is not mapped to sport or physical activities.
"Ménage" is similar to "Nettoyage".
Cooking or eating are not a sport or a physical activities.
Define "intensity" of the sport. Map for "intensity" on one of these values: ["unknown", "low", "moderate", "high", "intense", "very intense"].
Duration must be a number.
Duration must be in minute.
If a physical activity will occur in the future, the event is an "intent".
If a physical activity has occured in the past, the event is a "declaration".
Map this event of the physical activity on ["intent", "declaration", "unknown"].
Ignore the negative action .
If the duration is unknown, set duration to 0.
Format the result for sport in french in JSON in an array of tuples {"name":, "duration":, "intensity":, "event":}.
When there is no solution, the result is: []
=========================================================================================
------------------------------ LLM Raw response -----------------------------
Based on your instructions, I have analyzed the sentence "J'ai mangé deux fraises et je suis allé courir dans le parc d'à côté". The sentence mentions one physical activity, which is running. Here is the formatted result:
```json
[
{
"name": "Course à pied",
"duration": 0,
"intensity": "moderate",
"event": "declaration"
}
]
```
Explanation:
- The physical activity "courir" is mapped to "Course à pied" from your provided list.
- The duration is unknown, so it is set to 0.
- The intensity of running can vary, but without additional context, I've set it to "moderate".
- The event is a "declaration" because the action has occurred in the past.
-----------------------------------------------------------------------------
----------------- Make it compliant ------------------
Based on your instructions, I have analyzed the sentence "J'ai mangé deux fraises et je suis allé courir dans le parc d'à côté". The sentence mentions one physical activity, which is running. Here is the formatted result:
```json
[
{
"name": "Course à pied",
"duration": 0,
"intensity": "moderate",
"event": "declaration"
}
]
```
Explanation:
- The physical activity "courir" is mapped to "Course à pied" from your provided list.
- The duration is unknown, so it is set to 0.
- The intensity of running can vary, but without additional context, I've set it to "moderate".
- The event is a "declaration" because the action has occurred in the past.
------------------------------------------------------
------------------------ After simplification ------------------------
[ { "name": "Course à pied", "duration": 0, "intensity": "moderate", "event": "declaration" }]
----------------------------------------------------------------------
--------------------------------- LLM result -----------------------------------
{'response': [{'name': 'Course à pied', 'duration': 0, 'intensity': 'moderate', 'event': 'declaration'}], 'cost': 0.061919999999999996}
--------------------------------------------------------------------------------
--------------------------------- final result -----------------------------------
{'prompt': "J'ai mangé deux fraises et je suis allé courir dans le parc d'à côté", 'intents': ['Capture the user food consumption', 'Capture the user physical activity'], 'model': 'mistral-large-latest', 'solutions': {'nutrition': [{'name': 'Fraise', 'normName': ' fraise ', 'comment': 'crue', 'normComment': ' crue ', 'rank': 0, 'id': 'CIQ#a1e7daabf0eef222eb55cee2d9464244', 'quantity': 'deux', 'quantityLem': '2', 'pack': ['FRA.w100'], 'type': 'fruit', 'gtin': '', 'gtinRef': '', 'brand': '', 'time': 'unknown', 'event': 'declaration', 'serving': '', 'posiNormName': 0}], 'activity': [{'trigram': 'RUN', 'duration': 0, 'event': 'declaration', 'level': 'RUN06'}]}, 'cputime': 11.269320249557495}
----------------------------------------------------------------------------------
LLM CPU Time: 11.269320249557495