Upload README.md

README.md

@@ -1,26 +1,25 @@
----
-tags:
-- ml-intern
----
+# Mythos — Multi-Agent Framework
 
-# huronvalley21/mythos
+A Python framework for building dynamic, memory-aware multi-agent systems with formal orchestration.
 
-<!-- ml-intern-provenance -->
-## Generated by ML Intern
+## Core Concepts
 
-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.
+- **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
 
-- Try ML Intern: https://smolagents-ml-intern.hf.space
-- Source code: https://github.com/huggingface/ml-intern
-
-## Usage
+## Quick Start
 
 ```python
-from transformers import AutoModelForCausalLM, AutoTokenizer
+from mythos import Agent, Pantheon, Oracle
 
-model_id = "huronvalley21/mythos"
-tokenizer = AutoTokenizer.from_pretrained(model_id)
-model = AutoModelForCausalLM.from_pretrained(model_id)
-```
+researcher = Agent(name="Athena", role="Researcher", goal="Find accurate information")
+writer = Agent(name="Homer", role="Writer", goal="Create compelling narratives")
 
-For non-causal architectures, replace `AutoModelForCausalLM` with the appropriate `AutoModel` class.
+pantheon = Pantheon(agents=[researcher, writer])
+oracle = Oracle(pantheon=pantheon, process="sequential")
+
+result = oracle.run("Write a story about ancient Greece")
+```