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Introduction

Orchestrate enables building and deploying multi-agent AI workflows for complex enterprise tasks. Coordinate specialized agents, manage state, and implement human-in-the-loop controls.

Create Workflow

Define multi-agent workflows

Run Workflow

Execute workflows

Get Execution

Monitor workflow progress

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Key Features

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Agent Types

AgentCapability
LLM AgentNatural language reasoning and generation
Code AgentExecute Python/JavaScript code
Search AgentWeb and document search
Tool AgentCall external APIs and tools
Human AgentHuman-in-the-loop approval/input

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Workflow Patterns

  • Sequential: Agents run in order
  • Parallel: Multiple agents run simultaneously
  • Conditional: Branch based on results
  • Loop: Iterate until condition met
  • Map-Reduce: Process items in parallel, aggregate results

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Enterprise Features

  • State persistence across executions
  • Retry and error handling
  • Audit logging
  • Cost controls and budgets
  • Human approval gates

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Quick Example

from rotavision import Rotavision

client = Rotavision()

# Create a research workflow
workflow = client.orchestrate.create_workflow(
    name="Market Research Pipeline",
    agents=[
        {
            "id": "researcher",
            "type": "llm",
            "model": "gpt-5-mini",
            "system_prompt": "You are a market research analyst..."
        },
        {
            "id": "searcher",
            "type": "search",
            "sources": ["web", "news", "academic"]
        },
        {
            "id": "writer",
            "type": "llm",
            "model": "claude-4.5-sonnet",
            "system_prompt": "You are a report writer..."
        }
    ],
    steps=[
        {"agent": "researcher", "action": "plan_research", "input": "{{topic}}"},
        {"agent": "searcher", "action": "search", "input": "{{researcher.queries}}"},
        {"agent": "writer", "action": "write_report", "input": "{{searcher.results}}"}
    ]
)

# Run the workflow
execution = client.orchestrate.run_workflow(
    workflow_id=workflow.id,
    inputs={"topic": "Electric vehicle adoption in India 2026"}
)

# Get results
result = client.orchestrate.get_execution(execution.id)
print(result.outputs["report"])

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Endpoints

MethodEndpointDescription
POST/orchestrate/workflowsCreate workflow
GET/orchestrate/workflows/{id}Get workflow
GET/orchestrate/workflowsList workflows
PATCH/orchestrate/workflows/{id}Update workflow
DELETE/orchestrate/workflows/{id}Delete workflow
POST/orchestrate/workflows/{id}/runRun workflow
GET/orchestrate/executions/{id}Get execution
GET/orchestrate/executionsList executions
POST/orchestrate/executions/{id}/cancelCancel execution
POST/orchestrate/executions/{id}/approveApprove human step