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  An open-source, configurable multi-step agent framework for building advanced LLM-powered assistants
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<details open="open">
<summary>Table of Contents</summary>

- [About](#about)
  - [Features](#features)
  - [Built With](#built-with)
- [Getting Started](#getting-started)
  - [Prerequisites](#prerequisites)
  - [Installation](#installation)
- [Usage](#usage)
  - [CLI: Bootstrap a New Agent](#cli-bootstrap-a-new-agent)
  - [Python API Example](#python-api-example)
  - [YAML Config Example](#yaml-config-example)
  - [Error Handling](#error-handling)
- [LLM Support](#llm-support)
  - [OpenAI](#openai)
  - [Mistral AI](#mistral-ai)
  - [Google Gemini](#google-gemini)
- [Configuration](#configuration)
- [Package Tool Integration](#package-tool-integration)
- [Examples](#examples)
  - [Barista Agent](#example-barista-agent)
  - [Financial Planning Assistant](#example-financial-planning-assistant)
- [Deployment](#deployment)
  - [Docker Base Image](#docker-base-image)
  - [Tracing and Elastic APM Integration](#tracing-and-elastic-apm-integration)
  - [Persistent Storage and Session Management](#persistent-storage-and-session-management)
  - [API Endpoints](#api-endpoints)
- [Roadmap](#roadmap)
- [Support](#support)
- [Project assistance](#project-assistance)
- [Contributing](#contributing)
- [Authors & contributors](#authors--contributors)
- [License](#license)
- [Acknowledgements](#acknowledgements)

</details>

---

## About

`NOMOS` (previously `S.O.F.I.A - Simple Orchestrated Flow Intelligence Agent`) is an open-source, configurable multi-step agent framework for building advanced LLM-powered assistants. Define your agent's persona, tools, and step-by-step flows in Python or YAML—perfect for conversational, workflow, and automation use cases.

The name `NOMOS` comes from the Greek word for "law" or "custom" - literally "the rulebook" powering every agentic step. This reflects the framework's core principle of providing structured, rule-based guidance for AI behavior.

The framework allows you to move from no-code to low-code development, making it accessible for both non-programmers and experienced developers to create sophisticated AI agents.

### Features

- **Step-based agent flows**: Define agent behavior as a sequence of steps, each with its own tools and transitions.
- **Persona-driven**: Easily set the agent's persona for consistent, branded responses.
- **Tool integration**: Register Python functions as tools for the agent to call.
- **Package-based tools**: Reference Python package functions directly using `package_name:function` syntax.
- **Auto tool documentation**: Tool descriptions and parameter documentation are automatically generated from docstrings.
- **YAML or Python config**: Configure agents via code or declarative YAML.
- **Step-level answer models**: Specify an `answer_model` for any step to receive structured (JSON/object) responses.
- **OpenAI, Mistral, and Gemini LLM support**
- **Session management**: Save and resume conversations with Redis or PostgreSQL persistent storage.
- **Advanced error handling**: Built-in error recovery mechanisms with configurable retry limits.
- **API integration**: Ready-to-use FastAPI endpoints for web and WebSocket interaction.
- **Elastic APM tracing**: Built-in support for distributed tracing and monitoring.
- **Docker deployment**: Pre-built base image for rapid deployment.
- **Extensible**: Build your own tools, steps, and integrations.
- **Interactive CLI**: Bootstrap new agents with `nomos init` (install with `[cli]` extra).

### Built With

- Python
- OpenAI, Mistral, and Gemini LLMs
- Redis/PostgreSQL (optional for storage)
- OpenTelemetry and Elastic APM (optional for tracing)
- FastAPI & Docker (optional for deployment)

## Getting Started

### Prerequisites

- Python 3.9 or higher
- Optional: Redis or PostgreSQL for session storage
- Optional: Elastic APM for tracing

### Installation

#### From PyPI

```bash
pip install nomos
```

#### With CLI support

```bash
pip install nomos[cli]
```

#### With LLM support

```bash
pip install nomos[openai]      # For OpenAI support
pip install nomos[mistralai]   # For Mistral AI support
pip install nomos[gemini]      # For Google Gemini support
```

#### With tracing support

```bash
pip install nomos[traces]
```

## Usage

NOMOS supports a spectrum of implementation approaches from no-code to low-code to full-code development.

### CLI: Bootstrap a New Agent

```bash
nomos init
```

This will interactively guide you to create a config YAML and starter Python file for your agent.

### Python API Example (Full Code)

```python
from nomos import *
from nomos.llms import OpenAIChatLLM

def get_time():
    """Get the current time.

    Returns:
        str: The current time in string format.
    """
    from datetime import datetime
    return f"Current time: {datetime.now()}"

steps = [
    Step(
        step_id="start",
        description="Greet and offer to tell the time or perform calculations.",
        available_tools=["get_time", "math:sqrt"],  # Direct reference to the sqrt function from math package
        routes=[Route(target="end", condition="User is done")],
    ),
    Step(
        step_id="end",
        description="Say goodbye.",
    ),
]

llm = OpenAIChatLLM()
agent = Nomos(
    name="clockbot",
    llm=llm,
    steps=steps,
    start_step_id="start",
    tools=[get_time, "math:sqrt"],  # Mix of custom functions and package references (Optional for package functions)
    persona="You are a friendly assistant that can tell time and perform calculations.",
    max_errors=3  # Will retry up to 3 times before failing
    max_iter=5,  # Maximum number of iterations (tool calls, step transitions, error_handling) allowed in a single interaction
)
sess = agent.create_session()
# ... interact with sess.next(user_input)
```

### YAML Config Example (Low-Code)

```yaml
name: utility-bot
persona: You are a helpful utility bot that can perform various calculations and data operations.
steps:
  - step_id: start
    description: Handle user requests for mathematical operations or data processing.
    available_tools:
      - math:sqrt
      - json:loads
      - itertools:combinations
    routes:
      - target: end
        condition: User is done with calculations
  - step_id: end
    description: Say goodbye to the user.
start_step_id: start
max_errors: 3  # Maximum consecutive errors before stopping
```

See [`examples/config.barista.yaml`](examples/config.barista.yaml) for a more full-featured example.
More examples are available in the [`examples`](examples/) directory.

## LLM Support

### Choose Your LLM (We are adding more soon!)

```python
from nomos.llms import OpenAI, Mistral, Gemini

# Choose your LLM provider
llm = OpenAI(model="gpt-4o-mini")
llm = Mistral(model="mistral-medium")
llm = Gemini(model="gemini-pro")
```

Or You can also specify LLM configuration in your YAML config:

```yaml
# ... rest of config
llm:
  provider: openai
  model: gpt-4o-mini
# ...rest of config
```

## Package Tool Integration

NOMOS allows you to reference Python package functions directly using the `package_name:function` syntax:

```python
# Reference a function from a standard library
"math:sqrt"                      # Standard library function
"json:loads"                     # Another standard library function
"itertools:combinations"         # Complex functions work too!

# Reference nested module functions
"package_name:module.submodule.function"
```

Benefits of package tool integration:

1. **No-code/low-code development**: Use existing Python functions without writing wrapper code
2. **Automatic documentation**: Function docstrings are used to generate tool descriptions and parameter documentation
3. **Simplified configuration**: Easily reference any Python function in your environment

Tool parameter descriptions in configuration files take precedence over automatically extracted docstring descriptions.

> **NOTE**: Make sure the package is installed in your environment and function returns an output that is string representable.

## Examples

### Example: Barista Agent

A full example is provided in [`examples/barista/barista.py`](examples/barista.py) and [`examples/config.barista.yaml`](examples/config.barista.yaml).

To run the Barista agent:

```bash
cd examples/barista
export OPENAI_API_KEY=your-api-key-here
python barista.py
# or
python barista_with_config.py
```

### Example: Financial Planning Assistant

A production-ready example of a Financial Planning Assistant is available in [`examples/financial-advisor/`](examples/financial-advisor/). This example demonstrates:

- Budget planning and expense tracking
- Savings goal management
- Financial health assessment
- Uses the nomos-base Docker image
- Production-ready configuration

To run the Financial Planning Assistant:

```bash
docker run -e OPENAI_API_KEY=your-api-key-here -p 8000:8000 financial-advisor
```

## Deployment

### Docker Base Image

NOMOS provides a base Docker image that you can use to quickly containerize your agents. The base image is available on Docker Hub as `chandralegend/nomos-base`.

To use the base image in your own agent:

1. Create a Dockerfile:

```dockerfile
FROM chandralegend/nomos-base:latest

# Copy your config file
COPY config.agent.yaml /app/config.agent.yaml

# Copy your tools
COPY tools.py /app/tools/
```

2. Build and run your container:

```bash
docker build -t my-nomos-agent .
docker run -e OPENAI_API_KEY=your-api-key-here -p 8000:8000 my-nomos-agent
```

The base image supports configuration via environment variables:

| Variable | Description | Required |
|----------|-------------|----------|
| `OPENAI_API_KEY` | OpenAI API key | Yes (if using OpenAI) |
| `CONFIG_URL` | URL to download agent configuration | No |
| `CONFIG_PATH` | Path to mounted configuration file | No |
| `PORT` | Server port (default: 8000) | No |
| `DATABASE_URL` | PostgreSQL connection URL | No |
| `REDIS_URL` | Redis connection URL | No |
| `ENABLE_TRACING` | Enable OpenTelemetry tracing (`true`/`false`) | No |
| `ELASTIC_APM_SERVER_URL` | Elastic APM server URL | If tracing enabled |
| `ELASTIC_APM_TOKEN` | Elastic APM Token | If tracing enabled |
| `SERVICE_NAME` | Service name for tracing | No (default: `nomos-agent`) |
| `SERVICE_VERSION` | Service version for tracing | No (default: `1.0.0`) |

### Tracing and Elastic APM Integration

NOMOS supports distributed tracing using [OpenTelemetry](https://opentelemetry.io/) and can export traces to [Elastic APM](https://www.elastic.co/apm/).

To enable tracing, set the following environment variables:

| Variable | Description | Required |
|----------|-------------|----------|
| `ENABLE_TRACING` | Enable OpenTelemetry tracing (`true`/`false`) | No (default: `false`) |
| `ELASTIC_APM_SERVER_URL` | Elastic APM server URL | If tracing enabled |
| `ELASTIC_APM_TOKEN` | Elastic APM Token | If tracing enabled |
| `SERVICE_NAME` | Service name for tracing | No (default: `nomos-agent`) |
| `SERVICE_VERSION` | Service version for tracing | No (default: `1.0.0`) |

Example:

```bash
docker run \
  -e ENABLE_TRACING=true \
  -e ELASTIC_APM_SERVER_URL=http://your-apm-server:8200 \
  -e ELASTIC_APM_TOKEN=your-apm-token \
  -e SERVICE_NAME=my-nomos-agent \
  -e SERVICE_VERSION=1.0.0 \
  -e OPENAI_API_KEY=your-openai-key \
  -p 8000:8000 my-nomos-agent
```

### Persistent Storage and Session Management

NOMOS base image supports multiple options for session storage:

#### In-Memory Storage

The default storage mechanism is in-memory, which does not persist sessions between container restarts.

#### Redis Session Storage

For caching and distributed deployments, you can use Redis as a session store:

```bash
docker run \
  -e REDIS_URL=redis://redis:6379/0 \
  -e OPENAI_API_KEY=your-openai-key \
  -p 8000:8000 my-nomos-agent
```

#### PostgreSQL Persistent Storage

For fully persistent sessions that survive container restarts:

```bash
docker run \
  -e DATABASE_URL=postgresql+asyncpg://user:pass@postgres/dbname \
  -e OPENAI_API_KEY=your-openai-key \
  -p 8000:8000 my-nomos-agent
```

### API Endpoints

NOMOS base image provides the following REST and WebSocket endpoints:

#### Server-side Session Management

- `POST /session` - Create a new session
- `POST /session/{session_id}/message` - Send a message to a session
- `WS /ws/{session_id}` - WebSocket connection for real-time interaction
- `DELETE /session/{session_id}` - End a session
- `GET /session/{session_id}/history` - Get session history

#### Client-side Session Management

- `POST /chat` - Stateless chat endpoint where the client maintains session state

For more details, see the [base image README](tools/base-image/README.md).

## Roadmap

See the [open issues](https://github.com/dowhiledev/nomos/issues) for a list of proposed features and known issues.

- [Top Feature Requests](https://github.com/dowhiledev/nomos/issues?q=label%3Aenhancement+is%3Aopen+sort%3Areactions-%2B1-desc) (Add your votes using the 👍 reaction)
- [Top Bugs](https://github.com/dowhiledev/nomos/issues?q=is%3Aissue+is%3Aopen+label%3Abug+sort%3Areactions-%2B1-desc) (Add your votes using the 👍 reaction)
- [Newest Bugs](https://github.com/dowhiledev/nomos/issues?q=is%3Aopen+is%3Aissue+label%3Abug)

## Support

If you have any questions or need help with NOMOS:

- [GitHub issues](https://github.com/dowhiledev/nomos/issues/new?assignees=&labels=question&template=04_SUPPORT_QUESTION.md&title=support%3A+)
- Join our [community discussions](https://github.com/dowhiledev/nomos/discussions)

## Project assistance

If you want to say **thank you** or/and support active development of NOMOS:

- Add a [GitHub Star](https://github.com/dowhiledev/nomos) to the project.
- Tweet about NOMOS.
- Write articles about the project on [Dev.to](https://dev.to/), [Medium](https://medium.com/) or your personal blog.

Together, we can make NOMOS **better**!

## Contributing

Contributions are welcome! Please open issues or pull requests on GitHub.

First off, thanks for taking the time to contribute! Contributions are what make the open-source community such an amazing place to learn, inspire, and create. Any contributions you make will benefit everybody else and are **greatly appreciated**.

Please read our contribution guidelines (coming soon), and thank you for being involved!

## Authors & contributors

For a full list of all authors and contributors, see [the contributors page](https://github.com/dowhiledev/nomos/contributors).

## License

This project is licensed under the **MIT license**.

See [LICENSE](LICENSE) for more information.

## Acknowledgements

- Inspired by the open-source LLM community.
- Built with ❤️
