I got the bug to try and develop an assistant and Google Gemini APIs are pretty cost effective. I started with an idea based on Geminis remote system calls that allow it to make a request locally to call a function or service. I started with an intent and tool calling agent. The intent agent is given a cached context of current tools and how to use them. this way as more tools and functions becom available, the model doesn't need to be retrained. each tool is a function within python. when a user asks about the weather for example, the intent agent simply calls the weather tool. I programmed it so most tools when called simply make API calls to separate agents. Having agents run separately greatly improves development and improvement on the fly. the most important and hardest part was the memory tool. I programmed a local SQL db that is searchable and editable via these tools. the AI uses memory calls to query previous history. the intent and chat agent are given a brief history in context cache for all conversations. When a user starts talking about things that seam out of context, the agents can call on all history via the memory tool. like humans needing a prompt to remember, it takes a users intent and conversation then breaks it down into keyword searches. the search results are presented to these agents to enrich the conversation. same for; news, fuel prices, recycling guide, web searching, calendar management and more. keeping everything modular and combining multiple AI models together makes for a great assistant. I'm not trying to get anywhere near chatgpt but it maintains context in a single form chat very well. the user doesn't need to reset the conversation or start again. a user can ask it to change what it remembers and delete history just with natural language. just thought I would share some experience. just needing to improve its interface. right now I'm just using sms and text chat programs to interact. I might work on a web UI or something via voice.

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A new AI assistant with Gemini

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