# Financial Digital Twin Framework
This directory contains the foundational components for the Financial Digital Twin, a next-generation intelligence platform for lending operations.
## Purpose
The goal of this framework is to provide a structured, code-based representation of the system's core components. This includes the semantic ontology, knowledge graph schemas, AI agent definitions, and supporting code.
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## Schema Strategy: A Dual Approach
This project employs a dual-schema strategy to balance rapid development with long-term strategic alignment. Two parallel schemas co-exist within this directory: a legacy/custom schema and the strategic, FIBO-aligned schema.
### 1. Strategic Schema (FIBO-Aligned)
This is the official, enterprise-grade data model for the Financial Digital Twin. It is based on the **Financial Industry Business Ontology (FIBO)** to ensure semantic interoperability and conceptual soundness. All new, core platform development should adhere to this model.
* **`ontology.md`**: The primary source of truth. This document provides a detailed overview of the FIBO-aligned ontology, the mapping of business concepts to FIBO classes, and the governance framework for extending the ontology. **All developers should start here.**
* **`schema_fibo.py`**: A Python dataclass implementation of the FIBO-aligned schema. This provides a concrete, code-based reference for data ingestion, validation, and application development.
### 2. Legacy Schema (Custom)
This schema was developed prior to the adoption of the formal FIBO standard. It remains to support existing applications and to serve as a reference or a basis for rapid prototyping of non-critical features.
* **`schema.py`**: A Python dataclass implementation of the custom schema.
* **`schema.cypher`**: A Cypher script for applying constraints for the custom schema in a Neo4j database.
* **`schema.yaml`**: A YAML representation of the custom schema.
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## Other Components
* **`nexus_agent.py`**: The core AI agent for interacting with the digital twin.
* **`influxdb_client.py`**: A client for interacting with the time-series database (InfluxDB).
* **`prompts.md`**: A library of specialized prompts for AI agents.
* **`_legacy/`**: This directory contains older, deprecated files that have been archived for historical reference.