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.