Input path: /home/debian/html/nutritwin/output_llm/6641224f8376b/input.json
Output path: /home/debian/html/nutritwin/output_llm/6641224f8376b/output.json
Input text: Enregistrer
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: Enregistrer
==================================================================================================================================

==================================== Prompt =============================================
Identify in this list of intents: ["Identify food consumption or declaration", "Identify the user physical activity", "Answer a nutrition question", "Other intent"], the intents of the prompt: ###Enregistrer###. 
 Format the result in JSON format: {intents: []}.
=========================================================================================


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

----------------- Make it compliant ------------------
```json
{intents: ["Other intent"]}
```
------------------------------------------------------

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

++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
ERROR: impossible to parse [II]:
```json
{intents: ["Other intent"]}
```

The extracted string is {intents: ["Other intent"]}
++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++

--------------------------------- final result -----------------------------------
{'prompt': 'Enregistrer', 'intents': [], 'model': 'gpt-4-0125-preview', 'solutions': {'nutrition': [], 'activity': [], 'response': {}}, 'cputime': 0.9723036289215088}
----------------------------------------------------------------------------------
LLM CPU Time: 0.9723036289215088