Input path: /home/debian/html/nutritwin/output_llm/68b42c4edd570/input.json Output path: /home/debian/html/nutritwin/output_llm/68b42c4edd570/output.json Input text: Une orange. 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: Une orange. ================================================================================================================================== ==================================== Prompt ============================================= Identify in this list of intents: ["Identify food and beverage consumption or declaration", "Identify the user physical activity", "Answer a nutrition question", "Other intent"], the intents of the prompt: ###Une orange.###. Format the result in JSON format: {"intents": []}. ========================================================================================= ------------------------------ LLM Raw response ----------------------------- {"intents": ["Identify food and beverage consumption or declaration"]} ----------------------------------------------------------------------------- ----------------- Make it compliant ------------------ {"intents": ["Identify food and beverage consumption or declaration"]} ------------------------------------------------------ ERROR: wrong object representation: {'intents': ['Identify food and beverage consumption or declaration']} ------------------------ After simplification ------------------------ { "intents": [ "Identify food and beverage consumption or declaration" ] } ---------------------------------------------------------------------- ==================================== Prompt ============================================= Convert this natural language query : """Une orange.""" into an array of JSON. Ignore what it is not connected to nutrition, beverage or food. Provide a solution without explanation. Use the following ontology and only this ontology described in this Turtle/RDF model: """ @prefix food: . @prefix rdfs: . @prefix xsd: . @prefix owl: . @prefix prov: . food: a owl:Ontology ; rdfs:comment "Definition of the food archetype"@en . food:name a owl:DatatypeProperty; rdfs:label "name"@en; rdfs:comment """Food or beverage identifier, the name should not contain information related to quantity or container (like glass...). Ignore food or beverage when it is not consumed in the past, now or in the future. The cooking mode is not in the name. The name is only in french."""@en; rdfs:range xsd:string. food:quantity a owl:DatatypeProperty ; rdfs:label "quantity"@en; rdfs:comment "The quantity of food or drink that is or was consumed. Quantity is only in french. Here are examples: 'un quignon', 'un cornet', 'un verre', 'une tranche', 'une boule', 'un', 'deux', 'trois',... Keep the same language."@en; rdfs:range xsd:string. food:cookingMethod a owl:DatatypeProperty ; rdfs:label "cooking method"@en; rdfs:comment "The cooking method of food. The cooking method is in french."@en; rdfs:range xsd:string. food:type a owl:DatatypeProperty ; rdfs:label "type of food"@en; rdfs:comment "Identify the type of food."@en; rdfs:range xsd:string. food:food a food:type ; rdfs:label "food" . food:beverage a food:type ; rdfs:label "beverage" . food:timeOfTheDay a owl:DatatypeProperty ; rdfs:label "time of the day"@en; rdfs:comment "Time of the day when food or drink was consumed."@en; rdfs:range xsd:string. food:breakfast a food:timeOfTheDay ; rdfs:label "breakfast" . food:lunch a food:timeOfTheDay ; rdfs:label "lunch" . food:snacking a food:timeOfTheDay ; rdfs:label "snacking" . food:dinner a food:timeOfTheDay ; rdfs:label "dinner" . food:brand a owl:DatatypeProperty ; rdfs:label "Brand"@en; rdfs:comment """Food or beverage brand. The restaurants are not brand. When the name is very known (ex: Activia, Coca) and the brand is not mentioned, guess the brand."""@en; rdfs:range xsd:string. food:company a owl:DatatypeProperty ; rdfs:label "Company"@en; rdfs:comment "Product company."@en; rdfs:range xsd:string. food:enumEvent a rdfs:Class . food:event a owl:DatatypeProperty ; rdfs:label "event"@en; rdfs:comment "Event of eating or drinking. Each must have an event"@en; rdfs:range food:enumEvent. food:intent a food:enumEvent ; rdfs:label "intent" . rdfs:comment "When the event should happen"@en. food:declaration a food:enumEvent ; rdfs:label "declaration" . rdfs:comment "When the event has already occured"@en. food:unknownEvent a food:enumEvent ; rdfs:label "unknown" ; rdfs:comment "When the event is unknown in the day"@en. food:event a owl:DatatypeProperty ; rdfs:label "event"@en; rdfs:comment "Event of eating or drinking. Each must have an event"@en; rdfs:range food:enumEvent. food:intent a food:enumEvent ; rdfs:label "intent" . rdfs:comment "When the event should happen"@en. food:declaration a food:enumEvent ; rdfs:label "declaration" . rdfs:comment "When the event has already occured"@en. food:unknownEvent a food:enumEvent ; rdfs:label "unknown" ; rdfs:comment "When the event is unknown in the day"@en. """ Here is an example of result: [ { "name": "blanquette de veau", "quantity": "un plat", "cookingMethod": "mijot\u00e9", "timeOfTheDay": "lunch", "company": "Leclerc", "type": "food", "event": "declaration" }, { "name": "eau", "brand": "Evian", "company": "Danone", "timeOfTheDay": "breakfast", "quantity": "un verre", "type": "beverage", "event": "intent" } ] ========================================================================================= ------------------------------ LLM Raw response ----------------------------- [ { "name": "orange", "quantity": "une", "type": "food", "event": "unknownEvent" } ] ----------------------------------------------------------------------------- ----------------- Make it compliant ------------------ [ { "name": "orange", "quantity": "une", "type": "food", "event": "unknownEvent" } ] ------------------------------------------------------ ------------------------ After simplification ------------------------ [ { "name": "orange", "quantity": "une", "type": "food", "event": "unknownEvent" } ] ---------------------------------------------------------------------- --------------------------------- LLM result ----------------------------------- {'response': [{'name': 'orange', 'quantity': 'une', 'type': 'food', 'event': 'unknownEvent'}], 'cost': 0.09581999999999999} -------------------------------------------------------------------------------- ----------- result to be analyzed ----------- {'name': 'orange', 'quantity': 'une', 'type': 'food', 'event': 'unknownEvent'} 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 '% orange %' AND (V_NormTrademark = '' OR V_NormTrademark IS NULL) ------------- Found solution (max 20) -------------- Orange - orange - pulpe, crue - - 19789 - - - CIQ#a84ec3c1b9bc46c10b639fa15eeef5f4 Orange Givrée - orange givree - - - 31 - - - KCA#78bd77a68826904b6b891043ddcc9d5a Orange Pressée - orange pressee - - - 3137 - - - KCA#d951c9057cfe647b69b7f30181322ad1 Jus d'Orange - ju orange - - - 52983 - - - KCA#da7a1f81a8cd82dbbbbbedf56a167258 Jus d'Orange - ju orange - pur jus - - 0 - - - CIQ#a4328be11b7e0fb0c4474532724cf38f Jus d'Orange - ju orange - à base de concentré - - 0 - - - CIQ#72928c242781a6ee15266175037b3fb8 Jus d'Orange Pasteurisé - ju orange pasteurise - - - 44 - - - KCA#8dc9e7ac955777e77122f7bd97350613 Jus d'Orange et Gingembre - ju orange gingembre - - - 31 - - - KCA#ac517779183d5fdeff117cfe8eb4be98 Jus d'Orange, Mangue et Fraise - ju orange mangue fraise - - - 60 - - - KCA#12cc18043b0813e5110bb808101edc8e Jus Orange Pamplemousse Pressés - ju orange pamplemousse presse - - - 517 - - - KCA#e606e760b12355e0cc070fbf069b4261 Jus d'Orange, Carotte et Céleri - ju orange carotte celeri - - - 117 - - - KCA#ba4cb33c47a671db82eeaad9ddd5c63e Jus d'Orange, Gingembre et Ananas - ju orange gingembre anana - - - 6 - - - KCA#e2edd8bdeebd69177ece6caee7f071d8 Jus d'Orange, Carotte et Gingembre - ju orange carotte gingembre - - - 73 - - - KCA#0c209cbc5beac761ddcf7ea316e5b29e Jus d'Orange, Ananas et Glace au Melon - ju orange anana glace melon - - - 21 - - - KCA#3e4e71456576da23059304f3eba50c9c Gin Orange - gin orange - - - 11 - - - KCA#69422eafcd803a4841e22ba7a24dbeaf Vodka Orange - vodka orange - - - 303 - - - KCA#afee6734db3389d9a53ba62d8e345e8e Tarte à l'Orange - tarte orange - à l'orange - - 0 - - - KCA#8cf553da1e0c3135218833739419ea98 Salade d'Oranges - salade orange - - - 71 - - - KCA#a7fe61d6cb0d6c12eba4ca95e0f74781 Dorade à l'Orange - dorade orange - - - 76 - - - KCA#f37ceb94004879aa0221259fea9ea8bd Canard à l'Orange - canard orange - - - 33 - - - KCA#42651abfdc29355ec0cf7e410b802f1a ---------------------------------------------------- --------------------------------- final result ----------------------------------- {'prompt': 'Une orange.', 'model': 'mistral-large-2411', 'imagePath': '', 'intents': ['Identify food and beverage consumption or declaration'], 'solutions': {'nutrition': [{'name': 'Orange', 'normName': ' orange ', 'comment': 'pulpe, crue', 'normComment': ' pulpe crue ', 'rank': 19789, 'id': 'CIQ#a84ec3c1b9bc46c10b639fa15eeef5f4', 'quantity': 'une', 'quantityLem': '1', 'pack': ['ORA.w200'], 'type': 'food', 'gtin': '', 'gtinRef': '', 'brand': '', 'time': '', 'event': 'unknownEvent', 'serving': 'ORA-100', 'posiNormName': 0}], 'activity': [], 'response': {}}, 'cputime': 1.421295166015625} ---------------------------------------------------------------------------------- LLM CPU Time: 1.421295166015625 Traceback (most recent call last): File "/home/debian/html/nutritwin/resources/KCALLMMainService.py", line 71, in omess = KCALLMMain.runEvent(event) ^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/home/debian/html/nutritwin/resources/KCALLMMain.py", line 132, in runEvent resp = KCALLMMainSpeechToData.execute(speech, imagePath, image64, comment, appId, device, version, age, gender, longitude, latitude, test) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/home/debian/html/nutritwin/resources/KCALLMMainSpeechToData.py", line 111, in execute response = table.put_item( ^^^^^^^^^^^^^^^ File "/home/debian/myVirtualPythonEnvV2/lib/python3.11/site-packages/boto3/resources/factory.py", line 581, in do_action response = action(self, *args, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/home/debian/myVirtualPythonEnvV2/lib/python3.11/site-packages/boto3/resources/action.py", line 88, in __call__ response = getattr(parent.meta.client, operation_name)(*args, **params) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/home/debian/myVirtualPythonEnvV2/lib/python3.11/site-packages/botocore/client.py", line 565, in _api_call return self._make_api_call(operation_name, kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/home/debian/myVirtualPythonEnvV2/lib/python3.11/site-packages/botocore/client.py", line 1021, in _make_api_call raise error_class(parsed_response, operation_name) botocore.exceptions.ClientError: An error occurred (UnrecognizedClientException) when calling the PutItem operation: The security token included in the request is invalid.