> ## Documentation Index > Fetch the complete documentation index at: https://docs.praison.ai/llms.txt > Use this file to discover all available pages before exploring further. # Workflow > Create and execute reusable multi-step workflows The `workflow` command manages reusable multi-step workflows stored in `.praison/workflows/`. ## Quick Start ```bash theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}} praisonai workflow list ``` List workflows example ```bash Template-Based Workflow theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}} # List available workflows praisonai workflow list # Execute a workflow praisonai workflow run "Research Blog" --tools tavily --save ``` ```bash Inline Workflow (No Template) theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}} # Quick workflow without creating a file praisonai "What is AI?" --workflow "Research,Summarize" --save # With step actions praisonai "GPT-5" --workflow "Research:Search for info,Analyze:Analyze findings,Write:Write blog" ``` ## Two Ways to Run Workflows Execute Multi-Step Workflows | Method | Command | Use Case | | ------------------ | --------------------------------------------- | ------------------------------------------------ | | **Template-based** | `praisonai workflow run "name"` | Reusable, complex workflows with per-step agents | | **Inline** | `praisonai "prompt" --workflow "step1,step2"` | Quick, ad-hoc workflows | ## Template-Based Workflows ### List Workflows ```bash theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}} praisonai workflow list ``` **Expected Output:** ``` ╭─ Available Workflows ────────────────────────────────────────────────────────╮ │ 📋 deploy - Deploy application to production │ │ 📋 Research Blog - Research and write blog posts │ ╰──────────────────────────────────────────────────────────────────────────────╯ ``` ### Execute Workflow ```bash theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}} praisonai workflow run "Research Blog" ``` ### Execute with Options ```bash theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}} # With variables praisonai workflow run deploy --workflow-var environment=staging --workflow-var branch=main # With tools and save output praisonai workflow run "Research Blog" --tools tavily --save # With planning mode (AI creates sub-steps for each workflow step) praisonai workflow run "Research Blog" --planning --verbose # With memory praisonai workflow run "Research Blog" --memory ``` ### Show Workflow Details ```bash theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}} praisonai workflow show deploy ``` ### Create Workflow Template ```bash theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}} praisonai workflow create my_workflow ``` ## Inline Workflows Run workflows directly from the command line without creating a template file: ```bash theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}} # Simple format: step names only praisonai "What is Python?" --workflow "Research,Analyze,Summarize" # Detailed format: step_name:action praisonai "AI trends" --workflow "Research:Search for AI trends,Write:Write a blog post" # With all options praisonai "GPT-5 features" --workflow "Research,Write" --tools tavily --save --verbose ``` ### Inline Workflow Format | Format | Example | Description | | -------- | --------------------------------------------- | ---------------------- | | Simple | `"Research,Summarize"` | Step name = action | | Detailed | `"Research:Search for info,Write:Write blog"` | Custom action per step | ## CLI Options Workflows use global flags (same as other commands): | Flag | Description | | -------------------------- | ------------------------------------------- | | `--workflow-var key=value` | Set workflow variable (can be repeated) | | `--llm ` | LLM model (e.g., `openai/gpt-4o-mini`) | | `--tools ` | Tools (comma-separated, e.g., `tavily`) | | `--planning` | Enable planning mode (AI creates sub-steps) | | `--memory` | Enable memory | | `--verbose` | Enable verbose output | | `--save` | Save output to file | ## Workflow File Format Workflows are stored in `.praison/workflows/` as **Markdown files** with YAML frontmatter: ```markdown theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}} --- name: Research Blog description: Research and write blog posts default_llm: gpt-4o-mini variables: topic: AI trends --- ## Step 1: Research Research the topic thoroughly. \`\`\`agent role: Researcher goal: Find comprehensive information \`\`\` \`\`\`tools tavily_search \`\`\` \`\`\`action Search for information about {{topic}} \`\`\` ## Step 2: Write Blog Write a blog post based on research. \`\`\`agent role: Writer goal: Write engaging content \`\`\` context_from: [Research] \`\`\`action Write a blog post about {{topic}} using the research data. \`\`\` ``` ## How It Works 1. **Load**: Workflow file is loaded from `.praison/workflows/` 2. **Variables**: Variables are substituted into step prompts 3. **Execution**: Each step is executed sequentially with its configured agent 4. **Context**: Results from each step are passed to the next ```mermaid theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}} flowchart TD A[Load Workflow] --> B[Substitute Variables] B --> C[Step 1: Research
Researcher Agent] C -->|context| D[Step 2: Write
Writer Agent] D --> E[Complete] ``` ## Examples ### Research Workflow ```bash theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}} # Execute with tools praisonai workflow run "Research Blog" --tools tavily --save # With planning mode (AI creates sub-steps for each step) praisonai workflow run "Research Blog" --planning --verbose ``` ### Deployment Workflow ```bash theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}} # With variables praisonai workflow run deploy --workflow-var environment=staging --workflow-var branch=main ``` ### Release Workflow ```bash theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}} praisonai workflow run release --workflow-var version=1.2.0 ``` ## Programmatic Usage ```python theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}} from praisonaiagents import AgentFlowManager manager = WorkflowManager() # Execute a workflow result = manager.execute( "deploy", executor=lambda prompt: agent.chat(prompt), variables={"environment": "production"} ) ``` ## Best Practices Use variables for environment-specific values to make workflows reusable. Workflows execute steps sequentially. Ensure each step can complete independently. | Do | Don't | | ------------------------------------ | ----------------------------- | | Use variables for environment values | Hardcode environment names | | Keep steps focused and atomic | Create monolithic steps | | Add descriptions to workflows | Skip documentation | | Test workflows in staging first | Deploy directly to production | ## Auto-Generate Workflows Generate workflow YAML files automatically from a topic description: ```bash theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}} # Basic auto-generation praisonai workflow auto "Research and write a blog post" # With specific pattern praisonai workflow auto "Analyze market trends" --pattern orchestrator-workers # With output file praisonai workflow auto "Customer support routing" --pattern routing --output support_workflow.yaml ``` ### Available Patterns | Pattern | Description | Use Case | | ---------------------- | ------------------------------------------ | --------------------------- | | `sequential` | Agents work one after another | Default, step-by-step tasks | | `parallel` | Agents work concurrently | Independent subtasks | | `routing` | Classifier routes to specialists | Different input types | | `loop` | Repeat steps until condition met | Iterative processing | | `orchestrator-workers` | Central orchestrator delegates dynamically | Complex decomposition | | `evaluator-optimizer` | Generate-evaluate loop until quality met | Content refinement | ### Pattern Examples Central orchestrator analyzes the task and delegates to specialized workers: ```bash theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}} praisonai workflow auto "Comprehensive market analysis and report" --pattern orchestrator-workers ``` Generated workflow includes: * **Orchestrator**: Analyzes task, determines required workers * **Workers**: Researcher, Analyst, Writer (run in parallel) * **Synthesizer**: Combines all worker outputs Iterative refinement with feedback loops: ```bash theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}} praisonai workflow auto "Write and polish a high-quality article" --pattern evaluator-optimizer ``` Generated workflow includes: * **Generator**: Creates initial content * **Evaluator**: Scores content (1-10), provides feedback * **Loop**: Continues until score >= 7 or max iterations Multiple agents work concurrently: ```bash theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}} praisonai workflow auto "Research from news, social media, and academic sources" --pattern parallel ``` Classifier routes to specialized agents: ```bash theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}} praisonai workflow auto "Handle technical, billing, and general customer requests" --pattern routing ``` ## Related * [Workflows Feature](/features/workflows) * [AutoAgents Feature](/features/autoagents) * [Auto Generation Mode](/nocode/auto) * [Planning CLI](/cli/planning) * [Hooks CLI](/cli/hooks)