Agent Framework

The Agent Framework represents the intelligence layer of Replicats, orchestrating complex trading strategies through a sophisticated DAG-based workflow engine.

Replicats Inteligence Framework (RIF)

DAG-Based Orchestration

  • Directed Acyclic Graph (DAG) Foundation Our Agent framework uses a DAG to coordinate tasks such as data ingestion, model inference, risk checks, and trade execution.

    • Each node in the DAG represents a specialized step (e.g., reading time series data, querying the knowledge graph, or calling a predictive model).

    • The edges define how data flows from one step to another without circular dependencies.

  • Conditional & Event-Driven Logic

    • Agents can branch into different paths based on probabilistic triggers (e.g., a predicted 80% chance of price rally) or deterministic thresholds (e.g., price surpasses $30,000).

    • This flexibility allows for complex strategies, from simple rebalancing rules to multi-step yield farming sequences.

Multi-Model Integration

  • Specialized AI Models for Triggers

  • Targeted LLM Usage

    • While specialized models handle the bulk of predictions, we still leverage LLMs (via DSPy) for natural language queries, high-level summaries, or user interactions.

    • The DAG calls the LLM steps only where human-like reasoning adds value, keeping cost and latency under control.

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