Whats up everyone? This blog is to understand what Ollama is and what functionalities it offers.
Ollama is a platform that lets you run and interact with LLMs on your local machine, providing a way to work with AI models without relying on cloud services. This is high level explanation of Ollama.
Further, I have used an interesting analogy of Ollama with Docker to explain it in more detail and give a clear idea of what services Ollama provides. Hence, as a prerequisite, to understand this paragraph, you need to have a brief understanding of Docker and the services it provides. Docker has the functionality to pull a pre-built application's image (e.g., web services, databases) from a registry, run the container on the local machine, and expose APIs to allow interaction with the services running inside the container. Similarly, Ollama is a platform with the capability to pull LLM models from a library of available models, running the LLM locally on users' machines, utilizing local hardware resources like CPU, GPU and providing API to developers to send prompts and get responses from the model. Before moving forward, just a disclaimer, this does not mean that Docker and Ollama are a similar platform; however, both platforms facilitates running complex systems locally and provide an easy way to interact with those systems through APIs. Hence, Docker is a perfect example to help explain what Ollama is and how it functions.
Utilizing Ollama can be a deal breaker for small to medium sized companies. Most of the developers uses AI these days to assist in development of applications. Nonetheless, companies might have concerns since utilizing cloud-based AI can potentially expose sensitive data and intellectual property. But, with Ollama in the picture, it literally solves this issue. Since it runs the model on local machine, companies can have their own internal AI chatbot which developers can utilize to increase their development productivity. This can help companies make sure that their codebase is intact within their own proximity.
Lastly, I believe Ollama will be a game changer in building RAG Applications. Due to Ollama, it becomes very easy for developers to interact with different LLMs and integrate the power of AI in their already existing applications. I am excited to use Ollama for my RAG projects. You can check out one of my RAG projects and how I integrated it with my other project to add AI features. Let me know in comments if you have or are planning to work on any such project. I am curious.
Thats all folks. I am very excited to see all the innovations developers will being in future with the technologies like LangChain, Ollama, Vector Databases, LLMs, GenAI etc.
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I would like to acknowledge that I took help from ChatGPT to structure my blog and simplify content.
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