NEXOS AGENT DEVELOPMENT STUDIO

Autonomous Agent Studio

Build cyclical state graphs, configure P2P CRDT swarms, or train models directly on any GitHub/GitLab repository using DSPy MIPRO Bayesian optimization.

Architecture:
Topology:Sequential Pipeline DAG
2 nodes active (Max 2 on Free Tier)
1
researcher
Information Retrieval
Anthropic: claude-3-7-opus
↓
2
synthesizer
State Convergence
OpenAI: gpt-4o
Configure Agent: researcher
NexosStateGraph SDK
"""
Auto-generated Nexos Sequential StateGraph.
Generated with NexosStudio.
"""
from nexos.runtime import StateGraph

def step_researcher(state: dict) -> dict:
    print("[Executing researcher] Using Anthropic:claude-3-7-opus")
    state["researcher_output"] = "Verified result from Information Retrieval"
    state["history"].append("researcher")
    return state

def step_synthesizer(state: dict) -> dict:
    print("[Executing synthesizer] Using OpenAI:gpt-4o")
    state["synthesizer_output"] = "Verified result from State Convergence"
    state["history"].append("synthesizer")
    return state

def build_pipeline() -> StateGraph:
    graph = StateGraph()
    graph.add_node("researcher", step_researcher)
    graph.add_node("synthesizer", step_synthesizer)
    graph.set_entry_point("researcher")
    graph.add_edge("researcher", "synthesizer")
    graph.add_edge("synthesizer", "__END__")
    return graph

if __name__ == "__main__":
    app = build_pipeline()
    output = app.execute({"history": [], "task": "Autonomous execution"})
    print("Pipeline Output:", output)
Complete Runnable Scaffold

Exported ZIP packages contain the full runnable entry point, dependencies (`requirements.txt`), Dockerfile, `docker-compose.yml`, and environment configurations.

Bidirectional Code Sync

Every visual canvas interaction updates Python and TypeScript AST structures instantaneously with zero compilation latency.

Local & Remote Agnostic

Run the exported pipeline on local developer laptops via Ollama or deploy directly into serverless cloud fabrics.