----------------------------- **While I generate an answer, here are some sources that might be helpful**: * [Function Calling]() * [Delete Assistant]() * [Vapi iOS SDK]() * [Get Assistant]() -----------------------------

### Answer The challenge you're facing with premature function triggering and hallucination is not uncommon in conversational AI, including scenarios utilizing GPT-3.5. It's important to note that while GPT-3.5 is a powerful model, it is not specifically tailored to avoid presumptions or "hallucinations" during interactions without careful tuning or additional logic layers. One way to mitigate such issues is through more granular control over the conversation flow and logic integration, which might involve customizing the prompts or adjusting the parameters sent to the model to guide its responses more effectively. Additionally, incorporating a layer of logic that evaluates the likelihood or relevance of triggering a function based on the conversation context before doing so can help. Vapi provides certain capabilities that could be leveraged to adjust the behavior of the AI in response to the user's input, such as modifying the system prompts or using intermediary custom ML models to better manage conversational dynamics [(1)]() . While the documentation provided does not directly address limitations or enhancements specific to GPT-3.5 for reducing hallucinations, Vapi's architecture allows for a high degree of customization and optimization, possibly including the integration of mechanisms to better manage premature function triggering . For applications where the latency of GPT-4 is a concern, it might be worth exploring a hybrid approach, using GPT-3.5 for parts of the conversation that require faster response times and resorting to GPT-4 or other mechanisms for parts of the conversation where accuracy and understanding context are more critical, albeit within the constraints of Vapi's platform capabilities. Lastly, experimenting with different configurations and closely monitoring the assistant's performance in various sc

enarios could provide insights into optimizing its behavior for your specific use case.

Got it. Tagging @User for additional help.

ive rigorously tested it, it isnt anywhere

will dm you!

Starting to really hate it too but 4'# delay is genuinely very unnatural for a conversation Will try fine tuning!

ie. does the previous call transcript gets into new call session?

as i stated, somehow the AI is ALWAYS hallucinating for the SAME time at the same day

and its so specific, "tomorrow at 3:00 PM"

i do think there is SOME sort of memory sharing going on because there is no reason otherwise why the hallucination would be so consistent on its value and yes the prompt has been very carefully probed to ensure there is no possible chance of any influence from within the prompt

to the point where i even removed the term "tomorrow" and all numbers, time or not, from the script

havent left any places where i could look for anything

the first few hours were spent genueinly thinking i MUST have inserted it SOMEWHERe for it to use such a consistent example

isnt the case unfortunately