Ollama Workflows is a framework that enables users to program LLMs through workflows. Workflows are JSON files with specific syntax that allow LLMs to divide complex tasks into smaller sub-tasks and complete them using tools and program memory.
This framework was created to address the challenges faced when working with agentic frameworks and local LLMs. Some of the problems encountered include:
- The ReAct framework does not work well for local models and long-executed tasks.
- Different tasks require different types of optimizations and prompts.
- Local models with limited context length require a file system based on embeddings.
Existing agent libraries are extremely abstract, while the what we need are clear workflows and prompts. Ollama, in combination with llama.cpp, provides a great tool for running LLMs on consumer hardware. As people mostly use smaller LLMs without GPUs, task execution should be flexible and achievable in such cases.
The design of Ollama Workflows is heavily inspired by the LLM OS created by Andrej Karpathy. Ollama Workflows is designed to enable users to execute any task by providing task-specific programs, eliminating the need to use rust for programming.
Ollama Workflows does not require chat history and allows attaching specific prompts for each subtask along with I/O from memory. Learn how to design workflows
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Executor: The Executor acts as the CPU, executing the workflow with operators.
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ProgramMemory: Memory is used to pass data between steps of the workflow.
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Workflows: A Workflow is the instruction set for the program.
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OpenAI Testing: Ollama-workflows fully supports OpenAI, for faster prototyping and seamless testing for your workflows.
For detailed documentation, please refer to the documentation.
Created by @andthattoo