> ## Documentation Index
> Fetch the complete documentation index at: https://splinter.mintlify.site/llms.txt
> Use this file to discover all available pages before exploring further.

# Multi-Agent Pipelines

> Orchestrate multiple agents

## Basic Pipeline

```python theme={null}
from splinter import Gateway, Workflow, AgentConfig, LLMProvider, ExecutionLimits

# 1. Create gateway
gateway = Gateway(limits=ExecutionLimits(max_budget=5.0))
gateway.configure_provider("openai", api_key="sk-...")

# 2. Create workflow
workflow = Workflow(workflow_id="research-pipeline")
workflow._gateway = gateway

# 3. Add agents
workflow.add_agent(AgentConfig(
    agent_id="researcher",
    provider=LLMProvider.OPENAI,
    model="gpt-4o-mini",
    system_prompt="Research the topic.",
))

workflow.add_agent(AgentConfig(
    agent_id="writer",
    provider=LLMProvider.OPENAI,
    model="gpt-4o-mini",
    system_prompt="Write based on research.",
))

# 4. Define steps
workflow.add_step("researcher")
workflow.add_step("writer", depends_on=["researcher"])

# 5. Run
result = await workflow.run(initial_state={"topic": "AI trends"})
```

## Dependencies

### Sequential

```python theme={null}
workflow.add_step("researcher")
workflow.add_step("analyst", depends_on=["researcher"])
workflow.add_step("writer", depends_on=["analyst"])
```

```mermaid theme={null}
flowchart LR
    R[researcher] --> A[analyst] --> W[writer]
    
    style R fill:#DBEAFE,stroke:#3B82F6,stroke-width:2px,color:#000
    style A fill:#DBEAFE,stroke:#3B82F6,stroke-width:2px,color:#000
    style W fill:#DBEAFE,stroke:#3B82F6,stroke-width:2px,color:#000
```

### Parallel

```python theme={null}
workflow.add_step("researcher_a")
workflow.add_step("researcher_b")
workflow.add_step("synthesizer", depends_on=["researcher_a", "researcher_b"])
```

```mermaid theme={null}
flowchart LR
    RA[researcher_a] --> S[synthesizer]
    RB[researcher_b] --> S
    
    style RA fill:#DBEAFE,stroke:#3B82F6,stroke-width:2px,color:#000
    style RB fill:#DBEAFE,stroke:#3B82F6,stroke-width:2px,color:#000
    style S fill:#FEE2E2,stroke:#6c0404,stroke-width:2px,color:#000
```

## State Ownership

Prevent agents from overwriting each other.

```python theme={null}
workflow.add_agent(AgentConfig(
    agent_id="researcher",
    state_ownership=["research.*"],
    ...
))

workflow.add_agent(AgentConfig(
    agent_id="writer",
    state_ownership=["content.*"],
    ...
))
```

## Schema Validation

Validate handoffs between agents.

```python theme={null}
workflow.add_handoff_schema(
    source="researcher",
    target="writer",
    schema={
        "type": "object",
        "properties": {
            "findings": {"type": "array"},
        },
        "required": ["findings"],
    },
)
```

## Checkpointing

Enable resume on failure.

```python theme={null}
workflow = Workflow(
    workflow_id="my-pipeline",
    checkpoint_enabled=True,
)

# If it fails, resume:
result = await workflow.run(resume=True)
```

## Mixed Providers

Use different LLMs for different agents.

```python theme={null}
gateway.configure_provider("openai", api_key="sk-...")
gateway.configure_provider("anthropic", api_key="sk-ant-...")

workflow.add_agent(AgentConfig(
    agent_id="researcher",
    provider=LLMProvider.OPENAI,
    model="gpt-4o-mini",
))

workflow.add_agent(AgentConfig(
    agent_id="writer",
    provider=LLMProvider.ANTHROPIC,
    model="claude-3-sonnet-20240229",
))
```

## Result

```python theme={null}
result = await workflow.run(initial_state={"topic": "AI"})

print(f"Status: {result.status}")
print(f"Success: {result.success}")
print(f"Cost: ${result.metrics['total_cost']:.4f}")
print(f"Steps: {result.metrics['total_steps']}")

for agent_id, output in result.outputs.items():
    print(f"{agent_id}: {output['result']}")
```