{"id":73191,"date":"2025-01-09T21:00:07","date_gmt":"2025-01-09T13:00:07","guid":{"rendered":"https:\/\/www.hongkiat.com\/blog\/?p=73191"},"modified":"2025-01-02T20:58:28","modified_gmt":"2025-01-02T12:58:28","slug":"ollama-ai-setup-guide","status":"publish","type":"post","link":"https:\/\/www.hongkiat.com\/blog\/ollama-ai-setup-guide\/","title":{"rendered":"Getting Started with Ollama"},"content":{"rendered":"

AI<\/a> has revolutionized how we work, helping with everything from coding<\/a> to creative writing<\/a>. However, many of these tools rely on internet access and third-party services, raising concerns about privacy and reliability when offline.<\/p>\n

\"Ollama<\/figure>\n

That\u2019s where a local-first approach comes in, such as Ollama<\/a><\/strong>. It allows you to run AI using various LLMs directly on your computer without needing an internet connection.<\/p>\n

Whether you\u2019re a developer looking for assistance with code or someone exploring what AI can do, Ollama is a great tool to have in your toolkit. It supports a wide range of models and provides an API that you can use to interact with the models programmatically.<\/p>\n

Installation<\/h2>\n

To get started with Ollama, you\u2019ll need to install it on your computer.<\/p>\n

Head over to the Download page<\/a> and select the appropriate installer for your machine. It supports macOS, Windows, and Linux, and also comes with an official Docker image<\/a>.<\/p>\n

If you\u2019re using macOS, you could also install it with Homebrew<\/a> by running the command below:<\/p>\n

\r\nbrew install ollama\r\n<\/pre>\n
Once the installation is complete, you can verify it by running ollama --version<\/code> in your terminal to see the current version installed.<\/p>\n
\"Ollama<\/figure>\n
Running Ollama<\/h2>\n
Now that we have Ollama installed, we can start running an LLM with it. We can pick an LLM from their Models library<\/a>.<\/p>\n
In this example, we\u2019ll run the llama3.2<\/strong> model.<\/p>\n
\"Running<\/figure>\n
llama3.2<\/strong> is a model from Meta designed for tasks like content creation, summarization, and retrieval-augmented generation (RAG). It supports multiple languages, including English, Spanish, and French, and is compact, making it perfect for lightweight applications. If you need more power, you can opt for a larger model like llama3.3<\/strong> with 70 billion parameters. However, larger models require significantly more computing resources, so ensure your system can handle it before making the switch.<\/p>\n
To use llama3.2<\/strong> with Ollama, we can type:<\/p>\n
\r\nollama run llama3.2\r\n<\/pre>\n
If this is the first time you\u2019re running this model, Ollama will download the model files and cache them on your computer. This process might take a few minutes depending on your internet speed.<\/p>\n
After the download is complete, we can start interacting with it right from the terminal. It will provide you with a prompt where you can type your input, and the model will generate a response based on the input you provided.<\/p>\n
\"Ollama<\/figure>\n
To exit the interaction with the current model in the Terminal, you can type \/bye<\/code> or press Ctrl\/Cmd + D<\/code> on your keyboard.<\/p>\n
Ollama API<\/h2>\n
Ollama provides an API that allows you to interact with its models programmatically, which you can use to integrate it into your applications, websites, or other projects.<\/p>\n
By default, the API is accessible at http:\/\/127.0.0.1:11434<\/code>, and below are some of the key endpoints you can utilize for these purposes:<\/p>\n\n\n\n\n\n\n\n\n
Endpoint<\/th>\nExplanation<\/th>\n<\/tr>\n<\/thead>\n
POST \/api\/generate<\/code><\/td>\nGenerate a response for a given prompt with a provided model.<\/td>\n<\/tr>\n
POST \/api\/embed<\/code><\/td>\nGenerate an embedding for a given text with a provided model.<\/td>\n<\/tr>\n
GET \/api\/tags<\/code><\/td>\nList available models on the local machine.<\/td>\n<\/tr>\n
GET \/api\/ps<\/code><\/td>\nList models that are currently running.<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n
Ollama also provides SDKs for Python<\/a> and JavaScript<\/a> to make it easier to interact with the APIs.<\/p>\n
OpenAI Compatibility<\/h3>\n
In addition to its own API, Ollama includes a compatibility layer for OpenAI\u2019s API. This lets you reuse the code and SDKs designed for OpenAI\u2019s API with Ollama, making it easier to transition between the two.<\/p>\n
However, as of now, the compatibility layer is in beta, and some features may not work perfectly yet. For the best experience, it\u2019s recommended to use Ollama\u2019s API directly.<\/p>\n
Conclusion<\/h2>\n
Ollama is a powerful and flexible tool for running AI locally, offering privacy, reliability, and full control over the models you run.<\/p>\n
With its API and tools, Ollama opens endless possibilities for integrating AI into your projects. From generating quick responses to solving complex problems, it delivers a seamless and private experience.<\/p>\n
Stay tuned for more tutorials where we\u2019ll explore advanced features and use cases!<\/p>","protected":false},"excerpt":{"rendered":"
AI has revolutionized how we work, helping with everything from coding to creative writing. However, many of these tools rely on internet access and third-party services, raising concerns about privacy and reliability when offline. That\u2019s where a local-first approach comes in, such as Ollama. It allows you to run AI using various LLMs directly on…<\/p>\n","protected":false},"author":113,"featured_media":0,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_jetpack_memberships_contains_paid_content":false,"footnotes":""},"categories":[3398],"tags":[3545],"topic":[],"class_list":["entry-content","is-maxi"],"acf":[],"yoast_head":"\nGetting Started with Ollama - Hongkiat<\/title>\n<meta name=\"description\" content=\"AI has revolutionized how we work, helping with everything from coding to creative writing. 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