Input path: /home/debian/html/nutritwin/output_llm/660cede49117f/input.json Output path: /home/debian/html/nutritwin/output_llm/660cede49117f/output.json Input text: J'ai mangé un morceau de kiri ce matin 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 un morceau de kiri ce matin ================================================================================================================================== ==================================== 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 un morceau de kiri ce matin###. 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 un morceau de kiri ce matin". 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 un morceau de kiri ce matin". The food item mentioned is "Kiri", which is a well-known brand of cheese. The quantity is "un morceau" (a piece). The time of eating is "ce matin" (this morning), which corresponds to "petit-déjeuner" (breakfast). The event is a "declaration" because the consumption is in the past. The JSON format of the information is as follows: ```json [ { "name": "Kiri", "quantity": "un morceau", "cooking": "", "brand": "Kiri", "company": "Groupe Bel", "type": "fromage", "time": "petit-déjeuner", "event": "declaration" } ] ``` ----------------------------------------------------------------------------- ----------------- Make it compliant ------------------ Based on your instructions, here's the analysis of the sentence "J'ai mangé un morceau de kiri ce matin". The food item mentioned is "Kiri", which is a well-known brand of cheese. The quantity is "un morceau" (a piece). The time of eating is "ce matin" (this morning), which corresponds to "petit-déjeuner" (breakfast). The event is a "declaration" because the consumption is in the past. The JSON format of the information is as follows: ```json [ { "name": "Kiri", "quantity": "un morceau", "cooking": "", "brand": "Kiri", "company": "Groupe Bel", "type": "fromage", "time": "petit-déjeuner", "event": "declaration" } ] ``` ------------------------------------------------------ ------------------------ After simplification ------------------------ [ { "name": "Kiri", "quantity": "un morceau", "cooking": "", "brand": "Kiri", "company": "Groupe Bel", "type": "fromage", "time": "petit-déjeuner", "event": "declaration" }] ---------------------------------------------------------------------- --------------------------------- LLM result ----------------------------------- {'response': [{'name': 'Kiri', 'quantity': 'un morceau', 'cooking': '', 'brand': 'Kiri', 'company': 'Groupe Bel', 'type': 'fromage', 'time': 'petit-déjeuner', 'event': 'declaration'}], 'cost': 0.056819999999999996} -------------------------------------------------------------------------------- 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 '% kiri %' 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 '% kiri %' AND V_NormTrademark LIKE '%%' ------------- Found solution (max 20) -------------- Kiri - kiri - - group Bel - 0 - 01525130 - 01525130 - OFF#16588a8f1bf99010d85eb328be9079fc Kiri - kiri - - group Bel - 0 - 3073781119244 - 01525130 - OFF#d5bac78b3e9f069643e9e3e089be7f93 Kiri - kiri - - group Bel - 0 - 3073780984515 - 01525130 - OFF#3c360cf4020f964ab1ab0245a08d3491 Kiri - kiri - - group Bel - 0 - 3073781062762 - 01525130 - OFF#926b4b954febcbda34e78cfccc04bf38 Kiri - kiri - - group Bel - 0 - 3073781081312 - 01525130 - OFF#913b8f8b6965719626b3de5f8f0489a9 Kiri - kiri - - group Bel - 0 - 6111028001031 - 01525130 - OFF#b0baf7490d7071c101f782e53da63743 Kiri - kiri - - group Bel - 0 - 3073781181432 - 01525130 - OFF#20eaa9cfca899ad152f7d15a4a9b2bff Kiri - kiri - - group Bel - 0 - 3073781131949 - 01525130 - OFF#903e73665d2881dfcfe443d18c386066 Kiri - kiri - - group Bel - 0 - 3073781090802 - 01525130 - OFF#13724435965a1f4703e373f214e74bed Kiri - kiri - - group Bel - 0 - 3073781095135 - 01525130 - OFF#7833173cd3b1f345374a5cef9c6c3890 Kiri - kiri - - group Bel - 0 - 3073781097238 - 01525130 - OFF#d52be0208d6ca9e1af1f70e706c66a15 Kiri - kiri - - group Bel - 0 - 3073781097290 - 01525130 - OFF#ee026907412aa35a55ff9fe61319db64 Kiri - kiri - - group Bel - 0 - 3073781125283 - 01525130 - OFF#4c3d29b06026743e2d3f59e4ea441298 Kiri - kiri - - group Bel - 0 - 3073781197365 - 01525130 - OFF#f00ee45037bb681fd9ec588c63e35f99 Kiri - kiri - - group Bel - 0 - 3073781097337 - 01525130 - OFF#161b026e5c1d8b1879430274c20afb29 Kiri - kiri - - group Bel - 0 - 3073781117783 - 01525130 - OFF#62d52530673172acc1333f11587eb3fa Kiri Kse - kiri kse - - group Bel - 0 - 3073781131888 - 3073781131888 - OFF#bef8c1cc500268dae1c491b70a79f20d Kiri BIO - kiri bio - - group Bel - 0 - 3073781140927 - 3073781140927 - OFF#620a7111cf201faba266dc783c78d544 Kiri BIO - kiri bio - - group Bel - 0 - 3073781176650 - 3073781140927 - OFF#841c16555e511ec9b73950282674dab3 Kiri Dippi - kiri dippi - - group Bel - 0 - 3073781056358 - 3073781056358 - OFF#266df94a4390b9b505a83e3ad7794eb0 ---------------------------------------------------- ERROR: no solution for picto in the first solution ERROR: no solution for picto in the first solution ERROR: no solution for picto in the first solution ERROR: no solution for picto in the first solution ERROR: no solution for picto in the first solution ERROR: no solution for picto in the first solution ERROR: no solution for picto in the first solution ERROR: no solution for picto in the first solution ERROR: no solution for picto in the first solution ERROR: no solution for picto in the first solution ERROR: no solution for picto in the first solution ERROR: no solution for picto in the first solution ERROR: no solution for picto in the first solution ERROR: no solution for picto in the first solution ERROR: no solution for picto in the first solution ERROR: no solution for picto in the first solution --------------------------------- final result ----------------------------------- {'prompt': "J'ai mangé un morceau de kiri ce matin", 'intents': ['Capture the user food consumption'], 'model': 'mistral-large-latest', 'solutions': {'nutrition': [{'name': 'Kiri', 'normName': ' kiri ', 'comment': '', 'normComment': '', 'rank': 0, 'id': 'OFF#16588a8f1bf99010d85eb328be9079fc', 'quantity': 'un morceau', 'quantityLem': '1 morceau', 'pack': ['UNI.w20'], 'type': 'fromage', 'gtin': '01525130', 'gtinRef': '01525130', 'brand': 'group Bel', 'time': 'petit-déjeuner', 'event': 'declaration', 'serving': '', 'posiNormName': 0}], 'activity': []}, 'cputime': 6.299156904220581} ---------------------------------------------------------------------------------- LLM CPU Time: 6.299156904220581