License and Terms of Use
Relevant source files
The following files were used as context for generating this wiki page:
The runpod-worker-ollama project is an open-source serverless runner designed to integrate the Ollama inference engine with the RunPod infrastructure. It facilitates the deployment of Large Language Models (LLMs) via Docker containers, supporting both standard Ollama interactions and OpenAI-compatible API routes.
The licensing framework defines the permissions and obligations for developers and organizations who wish to use, modify, or redistribute this worker. It specifically adopts a permissive international standard that encourages commercial utilization and adaptation while maintaining clear requirements for credit.
Sources: README.md:1-25, src/engine.py:12-16
Creative Commons Attribution 4.0 International
The project is licensed under the Creative Commons Attribution 4.0 International (CC BY 4.0) license. This legal framework permits a wide range of activities provided that the user complies with specific attribution requirements.
Permitted Actions
Under the CC BY 4.0 license, users are granted the following rights:
- Share: Copy and redistribute the material in any medium or format.
- Adapt: Remix, transform, and build upon the material for any purpose, including commercial ventures.
Mandatory Terms
To maintain compliance with the license, users must adhere to the following conditions:
- Attribution: Users must provide appropriate credit, include a link to the license, and indicate if any modifications were made to the original source code.
- Reference: Users must explicitly reference the original repository located at `https://github.com/svenbrnn/runpod-worker-ollama%60.
Sources: README.md:31-40
Implementation and Compliance Context
The license applies to the core logic of the worker, including the engine orchestration, the handler interface, and the environment configuration scripts.
Architectural Scope
The following diagram illustrates the components governed by the project's license and how they interact with the execution environment:
The diagram shows the internal scripts (handler, engine, utils, start.sh) that constitute the licensed work and their relationships with external dependencies.
Sources: src/handler.py:1-35, src/engine.py:1-20, src/start.sh:1-40
Dependency and Environment Variables
The software utilizes several third-party libraries and environment configurations to function. While the core worker is under CC BY 4.0, users must also respect the licenses of the underlying dependencies specified in the project.
| Variable/Dependency | Role | Source |
|---|---|---|
OLLAMA_MODEL_NAME | Defines the LLM to be downloaded and served. | README.md:15 |
MAX_CONCURRENCY | Controls the number of simultaneous jobs. | src/handler.py:7 |
runpod | Python SDK for serverless integration. | src/requirements.txt:1 |
openai | Client library for OpenAI-compatible routing. | src/requirements.txt:3 |
python-dotenv | Management of environment variables. | src/requirements.txt:2 |
Sources: src/requirements.txt:1-4, src/handler.py:6-8
Model Preloading and Redistribution
The project provides mechanisms for preloading models into Docker images. When users build and distribute custom images containing pre-downloaded models, the attribution terms of the project license apply to the scripts used to generate those images.
The sequence diagram demonstrates the preloading process using project-provided scripts, which remain under the project's license.
Sources: embed_model/README.md:3, embed_model/preload_model.sh:1-36
Summary of Usage Terms
The "License and Terms of Use" ensures that the runpod-worker-ollama remains an open resource while protecting the original author's right to attribution. It is designed for flexibility in both individual and enterprise environments, specifically supporting the high-concurrency demands of RunPod's serverless infrastructure.
Sources: README.md:31-42, src/handler.py:32-40