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tags:
- ml-intern
---
# Mythos — Multi-Agent Framework
A Python framework for building dynamic, memory-aware multi-agent systems with formal orchestration.
## Core Concepts
- **Agent**: A role-based reasoning unit with memory, tools, and communication capabilities
- **Pantheon**: A collection of agents with defined relationships and workflows
- **Oracle**: The orchestration engine that routes tasks, manages state, and adapts topology
- **Memory**: MIRIX-inspired 4-component memory (Core, Episodic, Semantic, Procedural)
- **Tool**: MCP-native tool abstraction
## Quick Start
```python
from mythos import Agent, Pantheon, Oracle
researcher = Agent(name="Athena", role="Researcher", goal="Find accurate information")
writer = Agent(name="Homer", role="Writer", goal="Create compelling narratives")
pantheon = Pantheon(agents=[researcher, writer])
oracle = Oracle(pantheon=pantheon, process="sequential")
result = oracle.run("Write a story about ancient Greece")
```
<!-- ml-intern-provenance -->
## Generated by ML Intern
This model repository was generated by [ML Intern](https://github.com/huggingface/ml-intern), an agent for machine learning research and development on the Hugging Face Hub.
- Try ML Intern: https://smolagents-ml-intern.hf.space
- Source code: https://github.com/huggingface/ml-intern
## Usage
```python
from transformers import AutoModelForCausalLM, AutoTokenizer
model_id = "huronvalley21/mythos"
tokenizer = AutoTokenizer.from_pretrained(model_id)
model = AutoModelForCausalLM.from_pretrained(model_id)
```
For non-causal architectures, replace `AutoModelForCausalLM` with the appropriate `AutoModel` class.
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