Input path: /home/debian/html/nutritwin/output_llm/68ff53490c66b/input.json
Output path: /home/debian/html/nutritwin/output_llm/68ff53490c66b/output.json
Input text: Ajouter.
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: Ajouter.
==================================================================================================================================

==================================== 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: ###Ajouter.###. 
 Format the result in JSON format: {"intents": []}.
=========================================================================================


------------------------------ LLM Raw response -----------------------------
{"intents":["Other intent"]}
-----------------------------------------------------------------------------

----------------- Make it compliant ------------------
{"intents":["Other intent"]}
------------------------------------------------------
ERROR: wrong object representation:
{'intents': ['Other intent']}

------------------------ After simplification ------------------------
{
    "intents": [
        "Other intent"
    ]
}
----------------------------------------------------------------------

--------------------------------- final result -----------------------------------
{'prompt': 'Ajouter.', 'model': 'mistral-large-2411', 'imagePath': '', 'intents': ['Other intent'], 'solutions': {'nutrition': [], 'activity': [], 'response': {}}, 'cputime': 0.40077996253967285}
----------------------------------------------------------------------------------
LLM CPU Time: 0.40077996253967285
Traceback (most recent call last):
  File "/home/debian/html/nutritwin/resources/KCALLMMainService.py", line 71, in <module>
    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.