Master Python: Build Local AI Agent with Langchain & Olama
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Today on NeuralNine, we're embarking on a thrilling journey to construct a local AI agent in Python. This isn't your run-of-the-mill system; oh no, this AI agent is a powerhouse designed to tackle tasks autonomously, even those with multiple intricate steps. Picture this: your trusty mail assistant can do the basics, sure, like listing unread emails or summarizing one. But our AI agent? It goes above and beyond, sifting through emails, cherry-picking the ones you care about, summarizing them, and even converting it all into a neat PDF document. It's like having a personal assistant with a turbocharged brain, ready to tackle any task you throw its way.
To bring this marvel to life, we're diving deep into Python, harnessing the power of Langchain, Langraph, and Olama for our local models. But hold on, you'll need a GPU with ample VRAM to handle the heavy lifting. Think Nvidia GeForce RTX 3060Ti with 8 GB of VRAM – a beast of a card that can handle models like Quen 3 with 8 billion parameters. And speaking of excitement, the NeuralNine team is gearing up for the Nvidia GTC event in Paris, promising a showcase of machine learning wonders and GPU delights. Jensen Huang's keynote on June 11th is just the tip of the iceberg; brace yourself for a flood of insights and opportunities at this unmissable event.
Now, let me paint a vivid picture of what awaits you at the end of this exhilarating ride. Imagine having your very own AI agent, not reliant on giants like OpenAI or Google, but running solely on Olama on your hardware, with no pesky API keys in sight. This agent isn't just about making tool calls; it's about orchestrating a symphony of tools to achieve complex tasks seamlessly. Want to list all unread emails from a specific sender and get a summary? No problem. Our AI agent can handle it with finesse, showcasing its prowess in combining tools intelligently. And the best part? It's all based on a graph structure, allowing for a fluid and dynamic interaction that sets it leagues apart from your average LLM.
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