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  • Welcome to Composabl
  • Get Started
  • Reference
    • CLI Reference
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    • Glossary
    • Sample Use Cases
  • Tutorials
    • Industrial Mixer
      • Get Started
      • Deep Reinforcement Learning
      • Strategy Pattern
      • Strategy Pattern with a Perception Layer
      • Plan-Execute Pattern
  • Establish a Simulation Environment
    • Simulation Overview
    • Connect a Simulator to Composabl
    • Composabl Simulation API
  • Build Multi-Agent Systems
    • Anatomy of a Multi-Agent System
    • Create a Use Case
    • Set Goals, Constraints, and Success Criteria
    • Create Skill Agents
      • Create Skill Agents
      • Create Skill Agents with Rewards Using the SDK
      • Configure Programmed Algorithms as Skill Agents
      • Configure API Connections to Third-Party Software as Skill Agents
    • Orchestrate Skill Agents
    • Configure Scenarios
    • Add a Perception Layer
      • Create a New Perceptor
      • Configure an ML Model as a Perceptor
      • Configure an LLM Model as a Perceptor
    • Publish Skill Agent Components to the UI
  • Train Agents
    • Submit a Training Job through the UI
    • Analyze Agent System Behavior
      • View Training Session Information
      • Analyze Data in Detail with the Historian
  • Evaluate Performance
    • Set KPI and ROI
    • Analyze Data
  • Deploy Agents
    • Access a Trained Agent System
    • Deploy an Agent System in a Container
    • Deploy an Agent System as an API
    • Connect Runtime Container to Your Operation
    • Connecting to Agent System Runtime and Plotting Results of Agent System Operations
  • clusters
    • Creating a Cluster
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      • Azure
    • Connecting a Cluster
  • Troubleshooting
    • Resolving Certificate Issues for Installing the Composabl SDK on WSL
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  1. Deploy Agents

Access a Trained Agent System

PreviousAnalyze DataNextDeploy an Agent System in a Container

Last updated 1 month ago

Once you have completed training an agent and are ready to deploy it you can download it from the UI.

  1. Go to the Training tab in your project.

  2. Select the training session for the agent you want to deploy.

  3. Click on the Artifacts drop down in the upper right of the screen.

  4. Click Inference Model and you will down load a file called agent.json.