Pipelines

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Overview

ELITEA Pipelines are powerful workflow automation tools that enable you to visually design and execute complex sequences of actions and decisions. Each pipeline is purpose-built to orchestrate multi-step processes by connecting various nodes—including LLM interactions, toolkit integrations, conditional logic, and custom code execution. Pipelines seamlessly interact with external services, toolkits, and data sources, allowing you to automate sophisticated workflows ranging from data processing and decision-making to integration with platforms like Jira, GitHub, and Salesforce. Why Use Pipelines? Unlike manual task execution or simple automation, pipelines provide a structured approach to complex workflow automation:

• Workflow Orchestration: Automate multi-step processes with conditional logic, loops, and parallel execution paths
• Visual Design: Design complex workflows using an intuitive drag-and-drop interface or advanced YAML configuration
• Service Integration: Connect multiple tools and services in a single workflow for seamless data flow
• Reusability: Create modular, reusable workflows that can be nested and combined for different use cases
• Scalability: Handle both simple linear processes and intricate multi-branch workflows with equal efficiency

How Pipelines Work Creating a pipeline involves three key aspects:

1. Node-Based Design: Build workflows by connecting nodes representing different actions—LLM calls, agent interactions, toolkit operations, code execution, routers, and decision points
2. Visual or Code Configuration: Use the Flow Designer for visual workflow creation or switch to YAML Editor for advanced programmatic configuration
3. Execution & Integration: Connect toolkits, agents, and MCPs to extend capabilities; configure model settings and conversation flows for interactive pipelines

Once configured, the pipeline executes autonomously, following the defined logic flow, making decisions based on conditions, and leveraging integrated services to complete tasks while adapting to dynamic inputs. Key Capabilities

• Visual Workflow Design: Intuitive Flow Designer with drag-and-drop nodes for easy workflow creation and management
• Conditional Logic: Implement complex decision trees using Router and Decision nodes for dynamic workflow paths
• Multi-Service Integration: Connect external toolkits, agents, MCPs, and nested pipelines within a single workflow
• Flexible Configuration: Toggle between visual Flow Designer and YAML Editor for different levels of customization
• State Management: Track and modify workflow state throughout execution using State Modifier nodes
• Version Control: Create, manage, and compare different versions of pipelines for iterative development

By leveraging ELITEA Pipelines, you can automate complex processes, reduce manual effort, and create scalable workflow solutions that adapt to your organization’s evolving needs.

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Navigating the Pipelines Menu

The Pipelines menu is accessible from the main platform navigation. Upon entering the Pipelines section, you’ll see a dashboard listing all created pipelines for your project.

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Pipelines Dashboard

The Pipelines dashboard provides multiple ways to view and manage your pipelines: View Options

• Card View - Visual cards displaying pipeline name, description, and key information. Ideal for browsing and quick identification.
• Table View - Compact table format with columns for name, description, status, and metadata. Better for managing large numbers of pipelines.

Switch between views using the view toggle button in the top-right corner of the dashboard. Search and Filter

• Search Bar - Quickly find pipelines by typing the pipeline name, description, or related keywords
• Filter by Tags - Filter pipelines by their assigned tags to find workflows in specific categories or with particular characteristics. Click tags to narrow down the list.

Pinning Pipelines Pin frequently used pipelines to keep them at the top of your list for quick access:

1. Locate the pipeline you want to pin
2. Click the pin icon (📌) on the pipeline card or in the table row
3. Pinned pipelines will appear at the top of the list, separated from unpinned ones
4. Click the pin icon again to unpin the pipeline

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Creating a Pipeline

To set up a new Pipeline:

1. Click the + Create button located in the sidebar navigation.
2. In the General section, fill out the required fields:
   • Name: Enter a unique name for your pipeline (e.g., “Test Case Generator Pipeline”)
   • Description: Provide a clear description of the pipeline’s purpose (e.g., “Automatically generates comprehensive test cases from acceptance criteria and user stories”)
3. Optionally, add and configure:
   • Tags: Add tags by typing a tag name or selecting from pre-existing tags
   • Welcome Message: Define a welcome message to guide users interacting with the pipeline. (e.g., “Welcome! I can help you generate test cases based on your acceptance criteria. Simply provide your requirements and I’ll create comprehensive test scenarios for you.”)
   • Conversation Starters: Add predefined commands or prompts to initiate interactions with the pipeline. (e.g., “Generate test cases for the login feature” or “Create test scenarios for payment processing”)
4. In the Advanced section (optional):
   • Step Limit: Set the maximum number of tool execution steps the pipeline can perform in a single turn (range: 0-999, default: 25). This parameter controls how many iterations the pipeline can execute before stopping, preventing infinite loops and managing resource usage. A higher step limit allows more complex multi-step workflows, while a lower limit ensures faster execution for simpler tasks.
5. Click Save to save your work on a Pipeline for the first time. This action creates what’s known as the “base” version of your pipeline.

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How to Select and Configure Toolkits

Toolkits are integrations with external or ELITEA’s internal services that enhance your pipeline’s capabilities by allowing it to interact with various resources and perform specific tasks. In addition to toolkits, you can also add other Agents, MCPs (Model Context Protocol servers), and Pipelines to extend your pipeline’s functionality. You can add these resources to your pipeline during the creation process or edit them later. Adding Resources to Your Pipeline:

1. In the pipeline Configuration interface, navigate to the TOOLKITS section
2. Use the dedicated add buttons to attach resources. Each button opens its own searchable dropdown:
   • +Toolkit: Browse and select from available toolkits, or click “Create new” to create a new toolkit. See Toolkits.
   • +MCP: Browse and select Model Context Protocol servers, or click “Create new” to create a new MCP. See MCPs.
   • +Agent: Browse and select agents to enable your pipeline to delegate tasks or collaborate with specialized agents. See Agents.
   • +Pipeline:Browse other pipelines to create complex multi-step workflows by chaining pipelines together
3. Each dropdown supports inline search and paginated scrolling to locate resources quickly.

Note: Your changes are saved automatically when you add or remove resources.

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Designing Your Pipeline

The center panel of the pipeline page contains the Editor. Use the Flow/YAML toggle at the top of the editor to switch between the two modes.

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State Management

The State feature in pipelines allows you to define and manage variables that persist throughout the entire pipeline execution. State variables enable data to be shared between different nodes, maintain context across workflow steps, and control the flow of information through your pipeline. What is Pipeline State? Pipeline state is a collection of key-value pairs that store data during pipeline execution. These variables can be accessed and modified by any node in your workflow, making it possible to:

• Pass data between nodes without explicit connections
• Store intermediate results for later use
• Implement conditional logic based on accumulated data
• Track workflow progress and decision outcomes

How to Define State Variables:

1. In the left panel, locate the State section
2. Click + Context to create a new state variable
3. Enter a Variable Name (use descriptive names like project_id, analysis_result, counter)
4. Set an default Value (optional) - can be text, numbers, or JSON objects
5. Click Save to apply your changes

Using State in Your Pipeline: Once defined, state variables can be accessed and modified throughout your pipeline:

• State Modifier Nodes: Use these specialized nodes to read from and write to state variables during pipeline execution
• Reference in Nodes: Access state variables in other nodes using the syntax {{state.variable_name}}
• Conditional Logic: Use state variables in Decision and Router nodes to control workflow branches
• Data Transformation: Pass state values between LLM, Code, and Toolkit nodes for complex processing

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Flow Designer:

• Use Flow mode (selected via the Flow/YAML toggle in the editor panel) to visually design your pipeline by connecting various nodes, such as LLM, Agent, Toolkit, MCP, Code, Custom, Router, Decision, State Modifier, and Printer.
• Add new nodes by clicking the + icon and selecting the desired node type from the dropdown menu.
• Use the End node to define the completion of the pipeline.
• Drag and drop connections between nodes to establish the workflow’s logic and transitions.
• Zoom in or out and adjust the view for better navigation and management of complex workflows.

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YAML Editor:

• Switch to YAML mode using the Flow/YAML toggle in the editor panel for code-based configuration.
• Define complex workflows, conditions, and logic that may not be easily achievable through the visual Flow Designer.
• Use the YAML editor to fine-tune node configurations, set advanced parameters, and integrate custom logic.
• Validate your YAML syntax to ensure the pipeline runs smoothly without errors.

• This is particularly useful for users who prefer a code-first approach, need to implement intricate logic, or want to replicate and modify existing pipelines efficiently.

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How to Execute Pipeline

To execute the pipeline and get the output:

1. Configure the Pipeline: Ensure your pipeline is properly configured with clear instructions and any necessary toolkits.
2. Navigate to Pipeline: Access the pipeline’s interface by clicking on the pipeline from your pipelines list.
3. Select the AI Model: In the interface, choose the appropriate AI model (e.g., gpt-4o, gpt-5.1, etc.) from the model selection dropdown.
4. Adjust Model Settings (Optional): Click the Model Settings icon (⚙️) next to the model selector to fine-tune the response generation. The settings vary depending on the selected model: For Reasoning Models (e.g., GPT-5.1):
   • Reasoning - Controls the depth of logical thinking and problem-solving with three levels:
     • Low: Fast, surface-level reasoning with concise answers and minimal steps
     • Medium: Balanced reasoning with clear explanations and moderate multi-step thinking (default)
     • High: Deep, thorough reasoning with detailed step-by-step analysis (may be slower)
   For Standard Models (e.g., GPT-4o):
   • Creativity - Controls response randomness and creativity. Lower values produce more focused and deterministic outputs, while higher values generate more diverse and creative responses with five levels (1-5):
     • 1: Highly focused and deterministic outputs
     • 2: Mostly focused with slight variation
     • 3: Balanced between focus and creativity (default)
     • 4: More varied and creative responses
     • 5: Maximum creativity and diversity
   Max Completion Tokens Limits the maximum length of AI responses measured in tokens (roughly 4 characters per token).(All Models):
   • Auto (default): System automatically sets the token limit to 4096 tokens
   • Custom: Manually set a specific token limit for responses
     • When Custom is selected, you can enter a specific number of maximum tokens
     • The interface shows remaining tokens available after your specified limit
     • Setting too high a value will show an error if it exceeds the model’s maximum output tokens
   
5. Start Interaction: Begin your conversation by either:
   • Clicking on a Conversation Starter (if configured) to use a predefined prompt
   • Typing your question or command directly into the chat input field
   • Using simple commands like “Go”, “Start Generating”, “Execute”, or “Run it” followed by clicking the Send button

Additional Interaction Features:

• Full Screen Mode: Increase the size of the output window for better visibility and focus. This mode can be activated to expand the output interface to the full screen.
• Continue the Dialogue: To keep the conversation going, simply type your next question or command in the chat box and click the Send icon.
• Copy the Output: Click the Copy to Clipboard icon to copy the generated text for use elsewhere.
• Regenerate Response: If the output isn’t satisfactory, click the Regenerate icon to prompt the Gen AI to produce a new response.
• Delete Output: To remove the current output from the chat, click the Delete icon.
• Purge Chat History: For a fresh start or to clear sensitive data, click the Clean icon to erase the chat history.
• Like or Dislike the Output:
  • Click the Like icon if the output meets your expectations.
  • Click the Dislike icon if the output is unsatisfactory. Upon disliking, you will have the option to leave a comment explaining why the output did not meet your expectations. This feedback helps improve the system’s performance and relevance.
  

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Managing Context Budget

When the context_manager secret is enabled at the project level, the Context Budget widget appears during pipeline execution to help you manage token usage effectively. This feature provides intelligent control over conversation token consumption through automated message pruning and summarization. What is Context Management? Context Management helps maintain conversation continuity while staying within model token limits by automatically managing message history, generating summaries of older conversations, and preserving important messages. This ensures your pipeline can handle longer conversations without hitting token limitations. Key Features:

• Real-time Token Tracking: Monitor token consumption as your pipeline processes requests
• Automatic Pruning: System removes older messages when context limit is reached
• Conversation Summarization: Generate summaries of conversation history to preserve context
• Message Preservation: Configure how many recent messages to always keep
• Flexible Strategies: Choose between different pruning strategies based on your needs

Accessing the Context Budget Widget:

1. Ensure the context_manager secret is set to true in your project settings
2. Start executing your pipeline
3. The Context Budget widget appears above the chat interface
4. Click to expand and view detailed metrics and configuration options

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Pipeline Runs

Each time you execute a pipeline, the system creates a pipeline run that captures the complete execution context, including inputs, outputs, state changes, and performance metrics. Pipeline runs provide valuable insights into how your workflows perform and help with debugging and optimization. Key Features of Pipeline Runs:

• Execution Tracking: Monitor the progress and status of each pipeline execution in real-time
• Input/Output Capture: Review the exact inputs provided and outputs generated for each run
• State Evolution: Track how state variables change throughout the execution
• Performance Metrics: Analyze execution time, token usage, and resource consumption
• Error Diagnostics: Identify where failures occur and access detailed error messages

Pipeline runs are automatically saved and can be accessed through the Run History panel (clock icon in the chat panel), where you can replay past executions, compare different runs, and analyze workflow behavior over time.

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Managing Pipeline Versions: Save, Create Versions, and Manage

To optimally manage your pipeline, understanding how to save and create versions is crucial. Follow these guidelines to efficiently save your pipeline, create versions, and manage them. How to Save a Pipeline:

• To save your work on a Pipeline for the first time, simply click the Save button. This action creates what’s known as the “base” version of your pipeline.
• You can continue to modify your pipeline and save the changes to the “base” version at any time by clicking the Save button again. If you wish to discard any changes made, you have the option to click the Discard button before saving.

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How to Create New Versions:

For instances where you need to create and manage different iterations of your Pipeline:

1. Initiate a New Version: Start by clicking the Save As Version button.
2. Name Your Version: When saving your work, provide a version name that clearly identifies the iteration or changes made.
3. Click Save to confirm your entry.

Upon creating a new version of the Pipeline, several options become available to you:

• Delete: Remove this version of the Pipeline if it’s no longer needed.
• Execute: Run this specific version of the Pipeline to see how it performs.
• Navigate Versions: Use the Version dropdown list to switch between and select different versions of the Pipeline. This allows for easy comparison and management of various iterations.

By following these steps, you can effectively manage the lifecycle and iterations of your pipelines, ensuring that each version is appropriately saved and utilized as per your requirements.

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Exporting and Importing Pipelines

ELITEA allows you to export the currently selected version of a pipeline as a file and import it into another project. Export and import are always version-specific — there is no option to export the entire pipeline with all its versions at once. Exporting a Pipeline Version:

1. Open the pipeline and select the version you want to export using the version selector.
2. Click the three-dot menu (⋮) in the toolbar.
3. Select Export. The file downloads automatically to your device.
   • If the selected version has no nested dependencies, a single .md file is downloaded.
   • If the selected version references other agents or pipelines as toolkits, the export is a .zip file containing all dependencies.

Importing a Pipeline:

1. In the Pipelines dashboard, click the Import button in the toolbar.
2. Upload the .md or .zip file previously exported from ELITEA.
3. The Import Wizard displays entity cards for the main pipeline and any nested dependencies. Review configuration before confirming.
4. Click Import to complete. The pipeline will appear in the current project.

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Forking Pipelines

Forking copies the currently selected version of a pipeline from one project to another within the same ELITEA environment — no file download required. Only one version is forked at a time; there is no option to fork the entire pipeline with all its versions. How to Fork a Pipeline Version:

1. Open the pipeline and select the version you want to fork using the version selector.
2. Click the three-dot menu (⋮) in the toolbar and select Fork.
3. In the Fork parameters wizard, choose a target project from the dropdown. No project is pre-selected; you must pick one manually.
4. Review the entity cards — the main pipeline card and any nested dependencies that will be forked automatically.
5. Click Fork. When complete, click Got it to navigate directly to the forked pipeline in the target project.

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Viewing Pipeline History

The Run History panel provides a complete audit trail of all past executions of your pipeline. How to access Run History:

1. Open any saved pipeline.
2. In the right panel (embedded chat area), click the clock icon (🕐) in the top bar. The tooltip reads “View run history”.
3. The pipeline page is replaced by the two-panel Run History display. Click the ✕ (Close) button in the top-left to return.

What Run History shows:

• Review past conversations: View complete chat histories from previous pipeline runs
• Track performance: Monitor execution duration across different versions
• Debug issues: Replay conversations to identify where problems occurred
• Compare versions: See how different pipeline versions performed with the same inputs
• Audit trail: Maintain records of all pipeline interactions for compliance purposes

Run History layout: The Run History panel uses a two-panel layout:

• Left panel — sortable list of all past runs. Click any column header to sort:

  Column	Description
  Date	Timestamp of the run in dd-MM-yyyy, hh:mm a format
  Version	Pipeline version used for the run
  Duration	Total execution time of the run

  Click a row to load the conversation replay in the right panel. Each row also has a three-dot menu (⋮) with: Share link, Delete, and Restore conversation.
• Right panel — full conversation replay of the selected run.

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INFORMATION

The Information accordion at the bottom of the left panel provides read-only metadata about the current pipeline and version.

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Best Practices

Keep It Modular

Break down complex workflows into smaller, manageable nodes for better readability and maintainability. Create reusable pipeline components.

Use Clear Node Names

Name each node descriptively to make your pipeline self-documenting. Use consistent naming conventions across your pipelines.

Test Iteratively

Test each node and connection individually before executing the entire pipeline. Use sample data to validate data flow.

Organize with Tags

Use tags to categorize pipelines by function, department, or use case. This makes pipelines easier to find and manage.

Version Your Pipelines

Create named versions for significant changes. This allows you to roll back if needed and compare different iterations.

Handle Errors Gracefully

Implement error handling and fallback mechanisms in your pipeline design. Use Decision nodes to manage error conditions.

Document Your Logic

Add descriptions to nodes and use the YAML editor comments to explain complex logic. Include conversation starters that demonstrate usage.

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Troubleshooting

Pipeline Not Executing

Check that all required toolkits are properly configured with valid credentials. Verify node connections are complete. Review the execution history for error messages.

Node Failing or Timing Out

Verify toolkit credentials and network connectivity. Check if external services are accessible. Review node configuration parameters for correctness.

Incorrect Data Flow

Review connections between nodes to ensure data is passed correctly. Test with sample data to identify where data transformation fails. Check State Modifier configurations.

Cannot Save Pipeline Changes

Verify you have edit permissions. Check for validation errors in node configurations. Try discarding changes and reapplying them incrementally.

Version Not Creating

Ensure the version name meets requirements (max 48 characters, no special characters). Check that you have permission to create versions. Try refreshing the page.

Pipeline Not Appearing in List

Clear search filters and check tag filters. Verify you’re in the correct project. Refresh the pipelines dashboard.

For further assistance, contact your platform administrator or refer to the support documentation.

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Support Contact

If you encounter issues not covered in this guide or need additional assistance with Pipeline management, please refer to Contact Support for detailed information on how to reach the ELITEA Support Team.

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