A lightweight Python framework for building modular AI pipelines with function nodes and agent nodes.
Project description
Pipeline Node Agents
A lightweight Python framework for building modular AI pipelines with function nodes and agent nodes. Designed to work well with lightweight local LLMs by giving you full control over context and task complexity at each step.
Table of Contents
Basic Usage
Requirements
- Python 3.11 - 3.13 (required)
- Ollama for local LLM support
Installation
(Optional, but recommended) create python virtual environment:
python3 -m venv .venv && source .venv/bin/activate
Install package:
pip install pipeline-node-agents
Verify Installation
from pipeline_node_agents import greet
print(greet())
Expected output:
Hello, World! Pipeline Node Agents <version> is working.
Run Pipelines
Prerequisites:
- Start Ollama in a separate terminal:
ollama serve
- Make sure the required model is installed using
ollama list
as of January 15th 2026, the default LLM is llama3.2
Option 1: With defined model and logger (recommended)
from crewai import LLM
from pipeline_node_agents import init_pipeline_logger, get_logger, TripPlannerPipeline
init_pipeline_logger(pipeline_name="trip_planner_pipeline", project_root=".")
logger = get_logger(__name__)
# Default model is llama3.2, change if needed
ollama_llm = LLM(model="ollama/llama3.2", base_url="http://localhost:11434")
pipeline = TripPlannerPipeline(ollama_llm=ollama_llm, logger=logger)
pipeline.run()
Option 2: Without logger
from pipeline_node_agents import TripPlannerPipeline
# Default model is llama3.2
pipeline = TripPlannerPipeline()
pipeline.run()
Usage as Developer
Requirements
- curl: For installing dependencies
- git: For cloning the repository
- Poetry for dependency management
- Ollama for local LLM support
Installation
In this guide, curl and git are assumed to be installed. If you do not have them, please follow the official documentation to install.
-
Install Poetry (if not already installed):
curl -sSL https://install.python-poetry.org | python3 -
-
Install Ollama (if not already installed):
curl -fsSL https://ollama.com/install.sh | sh
-
Clone the repository and install dependencies:
git clone <repository_url> cd pipeline_node_agents poetry install
-
Install LLM (default:
llama3.2:latest):ollama pull llama3.2:latest
How to Run
Prerequisites:
- Start Ollama in a separate terminal:
ollama serve- Make sure the required model is installed using
ollama list(as of January 15th 2026, it's llama3.2)
Option 1: Run an example directly
poetry run python3 examples/<example_name>.py
e.g.
poetry run python3 examples/random_mean_pipeline.py
Option 2: Using Runner Scripts
Additional requirement: All scripts in the
scripts/folder must have execution permissions.If not, run:
chmod +x scripts/*.sh
Run a Single Pipeline
./scripts/run_single_pipeline.sh <path_to_pipeline> <runs> [input_strings]
Parameters:
<path_to_pipeline>- Path to the Python pipeline file<runs>- Number of times to run the pipeline[input_strings]- Optional: newline-separated inputs for interactive prompts
Examples:
# Run a simple pipeline 3 times
./scripts/run_single_pipeline.sh src/pipeline_node_agents/examples/random_mean_pipeline.py 3
# Run with single input
./scripts/run_single_pipeline.sh src/pipeline_node_agents/examples/input_checker_pipeline.py 2 "Munich, Vienna"
# Run with multiple inputs (use $'\n' to separate)
./scripts/run_single_pipeline.sh src/pipeline_node_agents/examples/trip_planner/pipeline.py 1 $'Madrid, Dubai\n30 January 2026\n5 February 2026'
Run All Smoke Tests
./scripts/run_smoke_pipelines.sh [number_of_runs_per_pipeline]
Examples:
# Run all example pipelines once
./scripts/run_smoke_pipelines.sh
# Run all example pipelines 3 times each
./scripts/run_smoke_pipelines.sh 3
Logs are automatically saved to logs/ directory by the Python logging system.
Maintenance Guide
For detailed maintenance instructions, including how to create nodes, build pipelines, and extend the framework, please refer to the Maintenance Guide.
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