I have created a WhatsApp agent that is supposed to answer questions about an event. Technically, everything works as I envisioned it, but I have a major problem. The agent is supplied with event information via a Supabase vector storage. I uploaded around 30 pages of a Word document as a knowledge base there (following the example from Nate’s RAG YouTube video). When I query the agent via WhatsApp, it is supposed to retrieve its knowledge from the vector database every time. However, it occasionally responds without searching for specific information in the database. It then simply replies that it doesn’t have the information or it makes up fictional information, even though the information is actually available in the database—it just doesn’t call the tool. When I point out that it should check its database, it does so and usually finds the information. Of course, I have noted in the system message that it should always refer to the database. But I don’t understand why it sometimes does this and sometimes doesn’t. The system message is quite long and extensive because the agent has to consider many factors to answer correctly. Could that be the reason? Or could it be due to the context window or the model I’m using? I have ChatGPT-4o Mini in use. In the screenshot, I’ve only included the agent node. Does anyone have an idea? If you need more information, just let me know. Thanks!

I'm working on an n8n workflow where I generate an MPEG audio file using ElevenLabs and need to send it as a voice message in WhatsApp via the WhatsApp Cloud API. I'm facing an issue when making the HTTP Request in n8n Should the file be in a specific format like OGG or OPUS instead of MPEG?🔹 Is there a specific API parameter to make WhatsApp recognize it as a voice message instead of an audio file?🔹 Has anyone successfully implemented this in n8n? Any insights or solutions would be greatly appreciated! 🙏🚀