Using the Ollama API to run LLMs and generate responses locally

This page summarizes the projects mentioned and recommended in the original post on dev.to

Our great sponsors
  • WorkOS - The modern identity platform for B2B SaaS
  • InfluxDB - Power Real-Time Data Analytics at Scale
  • SaaSHub - Software Alternatives and Reviews
  • ollama-python

    Ollama Python library

  • Ollama allows us to run open-source Large language models (LLMs) locally on our system. If you don't have Ollama installed on your system and don't know how to use it, I suggest you go through my Beginner's Guide to Ollama. It will guide you through the installation and initial steps of Ollama. In this article, I am going to share how we can use the REST API that Ollama provides us to run and generate responses from LLMs. I will also show how we can use Python to programmatically generate responses from Ollama.

  • ollama

    Get up and running with Llama 3, Mistral, Gemma, and other large language models.

  • Now, as we see, the /api/generate endpoint is used to generate a response/completion for a given prompt. There are various endpoints that we can use for different purposes. You can check them out at the API Documentation of Ollama.

  • WorkOS

    The modern identity platform for B2B SaaS. The APIs are flexible and easy-to-use, supporting authentication, user identity, and complex enterprise features like SSO and SCIM provisioning.

    WorkOS logo
NOTE: The number of mentions on this list indicates mentions on common posts plus user suggested alternatives. Hence, a higher number means a more popular project.

Suggest a related project

Related posts