{"categories":[{"label":"Artificial Intelligence","url":"https://skillfed.io/packages/category/scientific-engineering-artificial-intelligence"}],"enrichment":{"capability":"Provides a Python client to interact with Ollama, a local or cloud-based large language model server, enabling chat, text generation, embeddings, and model management through a simple API.","skillfed_tags":["llm-client","local-inference","async-support"],"use_cases":["Build a chatbot or conversational AI feature in a Python application by sending user messages to a local Ollama instance and streaming responses back.","Generate text embeddings for semantic search or similarity comparisons without calling an external API.","Automate model management tasks\u2014pulling, creating, copying, or deleting models\u2014as part of a larger data pipeline.","Prototype LLM-powered features locally during development before deploying to cloud models via Ollama's cloud API.","Create an async worker that processes chat or generation requests concurrently using AsyncClient.","Integrate Ollama cloud models (e.g., gpt-oss, deepseek-v3.1) into Python code by authenticating with an API key."],"what_it_does":"Ollama is the official Python client library for interacting with Ollama, a system for running large language models locally or via cloud. It wraps Ollama's REST API into a straightforward Python interface, letting you send chat messages, generate text, create embeddings, and manage models without dealing with HTTP calls directly. The library supports both synchronous and asynchronous workflows, streaming responses for real-time output, and custom client configuration via httpx.\n\nThe package is designed for developers who want to integrate local or cloud-hosted LLMs into Python applications. It handles the common patterns\u2014chat conversations, single-prompt generation, batch embeddings, and model lifecycle operations\u2014with minimal boilerplate. Dependencies are light (httpx for HTTP, pydantic for response validation), and the API closely mirrors Ollama's REST endpoints, so the learning curve is shallow if you're already familiar with the server.","worth_installing":"Yes. The package is actively maintained, has no known vulnerabilities, carries a permissive MIT license, and installs with minimal friction. It is the official client for Ollama and is well-suited for any Python project that needs to call local or cloud LLMs. Install it if you are already running Ollama or plan to; if you have no Ollama server, it is not useful on its own."},"id":"ollama","links":{"html":"https://skillfed.io/packages/ollama","md":"https://skillfed.io/packages/ollama.md","pypi":"https://pypi.org/project/ollama/"},"maintenance":{"status":"active"},"meta":{"latest_release":"2026-04-29","license_spdx":"MIT","license_treatment":"permissive","name":"ollama","python_support":"supports_current","summary":"The official Python client for Ollama."},"popularity":{"monthly_downloads":19885974,"position":1052,"tier":"top_5000"},"security":{"n_vulnerabilities":0},"version":"0.6.2"}