Introduction - Ollama Ollama’s API isn’t strictly versioned, but the API is expected to be stable and backwards compatible Deprecations are rare and will be announced in the release notes
API Reference - Ollama English Documentation You may choose to use the raw parameter if you are specifying a full templated prompt in your request to the API keep_alive: controls how long the model will stay loaded into memory following the request (default: 5m)
ollama docs api. md at main · ollama ollama · GitHub Use api blobs :digest to first push each of the files to the server before calling this API Files will remain in the cache until the Ollama server is restarted
API Reference | ollama ollama | DeepWiki This document provides a comprehensive reference for Ollama's HTTP REST API It covers all endpoints for model inference (generation, chat, embeddings), model management (pull, push, create, delete), and system information
Ollama Commands: CLI and API Reference [Cheat Sheet] Complete Ollama cheat sheet with every CLI command and REST API endpoint Tested examples for model management, generate, chat, and OpenAI-compatible endpoints
How to Use Ollama API - oneuptime. com A comprehensive guide to the Ollama API for building applications with local large language models Learn REST endpoints, streaming responses, embeddings, model management, and integration patterns
Overview - Ollama API Enable JSON mode by setting the format parameter to json This will structure the response as a valid JSON object See the JSON mode example below Important It's important to instruct the model to use JSON in the prompt Otherwise, the model may generate large amounts whitespace
Ollama REST API Tutorial: Building AI Applications with HTTP Requests Today, you can build powerful AI applications with simple HTTP requests using Ollama 's REST API No complex SDKs, no mysterious configurations—just straightforward web requests that work The Ollama REST API transforms your local AI models into accessible web services