Quick Start
How It Works
| Component | Purpose | Availability |
|---|---|---|
| Agent Node | Individual AI entity with tailored instructions | Sidebar > PraisonAI |
| Agent Team Node | Multi-agent orchestrator connecting multiple nodes | Sidebar > PraisonAI |
| CLI Command | Backend server runtime wrapper | praisonai CLI |
Agent Configuration Options
Options available on the Agent node visual component.| Option | Type | Default | Description |
|---|---|---|---|
Agent Name | str | "Agent" | Name for identification and logging. |
Previous Agent | Handle | None | Connect from previous agent to define execution order. |
Role | str | None | Role defining the agent’s expertise. |
Goal | str | None | Primary objective the agent aims to achieve. |
Instructions | str | "You are a helpful assistant." | System prompt for the agent. |
Model | str | "openai/gpt-4o-mini" | LLM model to use (provider/model format). |
Input | Handle | None | User input to process. |
Tools | Handle | None | Tools available to the agent. |
Memory | bool | False | Enable context retention. |
Guardrails | bool | False | Enable output validation guardrails. |
Knowledge Files | File | None | Files to use as knowledge sources (PDF, TXT, etc.). |
Agent Team Configuration Options
Options available on the Agent Team node visual component for multi-agent workflows.| Option | Type | Default | Description |
|---|---|---|---|
Name | str | "AgentTeam" | Name for this multi-agent team. |
Agents | Handle | [] | List of connected PraisonAI agents to orchestrate. |
Input | Handle | None | Initial input to start the multi-agent workflow. |
Process | str | "sequential" | Collaboration mode (sequential, hierarchical, workflow). |
Manager LLM | str | "openai/gpt-4o" | LLM used for auto-created managers. |
Shared Memory | bool | False | Enable shared memory across all agents. |
Planning | bool | False | Enable planning mode for task decomposition. |
Reflection | bool | False | Enable self-reflection for improved results. |
Common Patterns
Sequential Connections
Connect individualAgent nodes linearly (Agent 1 → Agent 2) by linking the Agent output handle on the first node to the Previous Agent input handle on the second node.
Multi-Agent Orchestration
Connect multipleAgent nodes directly to the Agents input handle of an Agent Team node. The team node evaluates the topology and runs the sub-agents properly.
Best Practices
Configure Knowledge Properly
Configure Knowledge Properly
When using the agent node’s knowledge capabilities, be sure to upload compatible document types (PDF, TXT, CSV) or provide valid URLs in the
Knowledge inputs.Use Sequential Handles
Use Sequential Handles
Use the
Previous Agent connection to establish hard execution boundaries. The orchestrator automatically parses node inputs backwards to map deterministic execution flow.Enable Advanced Node Features
Enable Advanced Node Features
Click the “Advanced” toggle on nodes inside Langflow to expose robust SDK parameters like custom Base URLs,
Code Execution Mode, Verbose logging, and specific Memory Providers.Related
Agent Workflow
Understand the core concepts of workflows.
Agent Teams
Learn how to build collaborative AI teams.