Skip to main content

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:

  1. Start Ollama in a separate terminal:
ollama serve
  1. 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.

  1. Install Poetry (if not already installed):

    curl -sSL https://install.python-poetry.org | python3 -
    
  2. Install Ollama (if not already installed):

    curl -fsSL https://ollama.com/install.sh | sh
    
  3. Clone the repository and install dependencies:

    git clone <repository_url>
    cd pipeline_node_agents
    poetry install
    
  4. Install LLM (default: llama3.2:latest):

    ollama pull llama3.2:latest
    

How to Run

Prerequisites:

  1. Start Ollama in a separate terminal: ollama serve
  2. 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.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

pipeline_node_agents-0.1.3.tar.gz (15.7 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

pipeline_node_agents-0.1.3-py3-none-any.whl (27.2 kB view details)

Uploaded Python 3

File details

Details for the file pipeline_node_agents-0.1.3.tar.gz.

File metadata

  • Download URL: pipeline_node_agents-0.1.3.tar.gz
  • Upload date:
  • Size: 15.7 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.9.6

File hashes

Hashes for pipeline_node_agents-0.1.3.tar.gz
Algorithm Hash digest
SHA256 b9bc63cffd745a5de2213dc40a78020d53a3d877dd64d2acbf33fccf82f4faef
MD5 fc71414bcb44f5fa85315def832c7fdb
BLAKE2b-256 901b380876b2a2fae49ee99b0377b401853c78ab3e6deb4ab8db0c8a45e7864e

See more details on using hashes here.

File details

Details for the file pipeline_node_agents-0.1.3-py3-none-any.whl.

File metadata

File hashes

Hashes for pipeline_node_agents-0.1.3-py3-none-any.whl
Algorithm Hash digest
SHA256 7b2a05cc14263c08ccb467b5c8b5d9332bc202cc6d0346cce95f9029a6b58efc
MD5 53d64f389e58be8258f3bb5fe5a8e47f
BLAKE2b-256 e723bced582dd2a377f66d63180f7a8c8da596f407e4c8bff3b308d6bcdc1585

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page