Architecting
Intelligent Systems.

import asyncio
from fastapi import FastAPI, BackgroundTasks
from zenivixon.ai import AutonomousAgent, LlamaModel

# Initialize high-performance async API
app = FastAPI(title="Zenivixon AI Core")

# Configure local agent with offline capabilities
agent = AutonomousAgent(
    model=LlamaModel.load_local("llama-3-70b"),
    memory_buffer=True,
    tools=["web_search", "document_gen"]
)

@app.post("/api/v1/execute_workflow")
async def execute_workflow(task_prompt: str, bg_tasks: BackgroundTasks):
    """
    Deploys an autonomous workflow based on client requests.
    Utilizes 100% local execution for absolute privacy.
    """
    # Step 1: Analyze context using local LLM
    context = await agent.analyze_context(task_prompt)
    
    # Step 2: Route to background processing
    bg_tasks.add_task(agent.run_autonomous_loop, context)
    
    return {
        "status": "processing",
        "agent_id": agent.id,
        "message": "AI workflow deployed to background workers."
    }