WayFlow is a powerful, intuitive Python library for building sophisticated AI-powered assistants. It is a reference runtime for Agent Spec, with native support for all Agent Spec Agents and Flows.
See the codeWayFlow is a powerful, intuitive Python library for building sophisticated AI-powered assistants. It includes a standard library of plan steps to streamline the creation of AI-powered assistants, supports re-usability and is ideal for rapid development.
To get started, set up your Python environment (Python 3.10 or newer required), and then install the WayFlow Core package.
python -m venv .venv
source .venv/bin/activate # On Windows: .venv\Scripts\activate
pip install wayflowcore
You can also use uv for faster install times:
pip install uv
uv pip install wayflowcore
Initialize a Large Language Model (LLM) of your choice:
| OCI Gen AI | Open AI | Ollama |
|---|---|---|
from wayflowcore.models import OCIGenAIModel | from wayflowcore.models import OpenAIModel | from wayflowcore.models import OllamaModel |
See the list of supported LLMs in the WayFlow documentation.
Then, create an agent using a WayFlow Agent:
from wayflowcore.agent import Agent
assistant = Agent(llm=llm)
conversation = assistant.start_conversation()
conversation.append_user_message("I need help regarding my sql query")
conversation.execute()
# get the assistant's response to your query
assistant_answer = conversation.get_last_message()
assistant_answer.content
# I'd be happy to help with your SQL query...
For more information on how to build flexible Agents, structured Flows and multi-agent patterns, read the WayFlow Tutorials
WayFlow is the reference runtime implementation for Open Agent Spec.
Explore practical examples for working with WayFlow.
| Name | Description |
|---|---|
| Build a Simple Conversational Assistant with Agents | A demo using dummy HR data to answer employee-related questions with an agent. |
| Build a Simple Fixed-Flow Assistant with Flows | A basic HR chatbot built as a fixed-flow assistant to answer employee questions. |
| Build a Simple Code Review Assistant | An advanced assistant using Flows to automate Python pull request reviews. |
This project welcomes contributions from the community. Before submitting a pull request, please review the contributor guide.
Please refer to the security guide for information on responsibly disclosing security vulnerabilities.
Copyright (c) 2025 Oracle and/or its affiliates.
This software is under the Apache License 2.0 (LICENSE-APACHE or http://www.apache.org/licenses/LICENSE-2.0) or Universal Permissive License (UPL) 1.0 (LICENSE-UPL or https://oss.oracle.com/licenses/upl), at your option.
Python
99.7%
WayFlow is a powerful, intuitive Python library for building sophisticated AI-powered assistants. It is a reference runtime for Agent Spec, with native support for all Agent Spec Agents and Flows.
See the codeWayFlow is a powerful, intuitive Python library for building sophisticated AI-powered assistants. It includes a standard library of plan steps to streamline the creation of AI-powered assistants, supports re-usability and is ideal for rapid development.
To get started, set up your Python environment (Python 3.10 or newer required), and then install the WayFlow Core package.
python -m venv .venv
source .venv/bin/activate # On Windows: .venv\Scripts\activate
pip install wayflowcore
You can also use uv for faster install times:
pip install uv
uv pip install wayflowcore
Initialize a Large Language Model (LLM) of your choice:
| OCI Gen AI | Open AI | Ollama |
|---|---|---|
from wayflowcore.models import OCIGenAIModel | from wayflowcore.models import OpenAIModel | from wayflowcore.models import OllamaModel |
See the list of supported LLMs in the WayFlow documentation.
Then, create an agent using a WayFlow Agent:
from wayflowcore.agent import Agent
assistant = Agent(llm=llm)
conversation = assistant.start_conversation()
conversation.append_user_message("I need help regarding my sql query")
conversation.execute()
# get the assistant's response to your query
assistant_answer = conversation.get_last_message()
assistant_answer.content
# I'd be happy to help with your SQL query...
For more information on how to build flexible Agents, structured Flows and multi-agent patterns, read the WayFlow Tutorials
WayFlow is the reference runtime implementation for Open Agent Spec.
Explore practical examples for working with WayFlow.
| Name | Description |
|---|---|
| Build a Simple Conversational Assistant with Agents | A demo using dummy HR data to answer employee-related questions with an agent. |
| Build a Simple Fixed-Flow Assistant with Flows | A basic HR chatbot built as a fixed-flow assistant to answer employee questions. |
| Build a Simple Code Review Assistant | An advanced assistant using Flows to automate Python pull request reviews. |
This project welcomes contributions from the community. Before submitting a pull request, please review the contributor guide.
Please refer to the security guide for information on responsibly disclosing security vulnerabilities.
Copyright (c) 2025 Oracle and/or its affiliates.
This software is under the Apache License 2.0 (LICENSE-APACHE or http://www.apache.org/licenses/LICENSE-2.0) or Universal Permissive License (UPL) 1.0 (LICENSE-UPL or https://oss.oracle.com/licenses/upl), at your option.
Python
99.7%