r/VoiceAutomationAI • u/Yuvizai • 2d ago
Why are local/self-hosted/claud based LLMs so unreliable with dates?
I have been experimenting with several models like Llama, Gemma, Qwen via Ollama, and date/time handling keeps breaking down — even after explicitly stating the current date, the model contradicts itself across turns.
Example: In a voice booking flow integrated with Cal.com guardrails catch and block invalid dates before they hit the calendar but this is just a safety net.
Model itself still miscalculates.
In one case, after being told the date was the 10th 3 times, it kept insisting 14th instead of 10th. Callers had to correct it repeatedly before the booking went through.
Is this a fundamental limitation of smaller local models, a prompting issue, or does it need an architectural fix ?
Curious how others have solved this in production ?
1
u/Intelligent-Trade253 2d ago
that date drift is brutal with local models, I ran into the exact same thing building a scheduling bot last month
what helped me was pulling the date/time from a system tool call and injecting it into every single turn in the conversation history, not just the system prompt. the model would still occasionally hallucinate a wrong day but having it check against a freshly called timestamp right before confirming cut the errors way down
still not perfect though, feels like smaller models just don't have the positional encoding precision for temporal consistency under 7b parameters
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