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AG2 is the community fork of AutoGen. PraisonAI supports AG2 as a dedicated framework backend with GroupChat orchestration, automatic tool registration, and native AWS Bedrock support.

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Which AG2 Option to Choose

PraisonAI has two AG2-related framework options:
OptionInstallWhen to Use
framework: ag2pip install "praisonai[ag2]"New projects, Bedrock support, latest AG2
framework: autogenpip install "praisonai[autogen]"Existing AutoGen v0.2/v0.4 projects

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Quick Start (AG2)

1

Install

pip install "praisonai[ag2]"
2

Create a YAML file

framework: ag2
topic: Research the latest developments in AI agents

roles:
  researcher:
    role: AI Research Specialist
    goal: Find and summarize recent AI agent developments
    backstory: Expert researcher with deep knowledge of AI trends.
    tasks:
      research_task:
        description: Research the latest developments in {topic}
        expected_output: Summary report with key findings
3

Run

export OPENAI_API_KEY=your-key
praisonai agents.yaml --framework ag2

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How AG2 Works

AG2 uses a GroupChat pattern: a UserProxy agent initiates the conversation, and a GroupChatManager routes messages between your defined agents. Agents collaborate until one says “TERMINATE”.

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Multi-Agent Example

framework: ag2
topic: Write a blog post about renewable energy

roles:
  researcher:
    role: Energy Research Analyst
    goal: Gather facts about renewable energy trends
    backstory: Expert in energy research and data analysis.
    tasks:
      research_task:
        description: Research current renewable energy trends for {topic}
        expected_output: Research brief with statistics and trends

  writer:
    role: Content Writer
    goal: Write engaging blog content based on research
    backstory: Skilled writer who turns technical research into readable content.
    tasks:
      writing_task:
        description: Write a blog post based on the research findings
        expected_output: Complete blog post with introduction, body, and conclusion

praisonai agents.yaml --framework ag2

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AWS Bedrock Support

AG2 natively supports AWS Bedrock models. No API key needed - uses your AWS credentials. 
framework: ag2

roles:
  cloud_architect:
    role: Cloud Solutions Architect
    goal: Design cloud architectures
    backstory: Expert in AWS cloud infrastructure.
    llm:
      model: bedrock/anthropic.claude-3-5-sonnet-20241022-v2:0
      api_type: bedrock
      aws_region: us-east-1
    tasks:
      design_task:
        description: Design a serverless architecture for a web app
        expected_output: Architecture diagram and component descriptions
Bedrock credentials come from your standard AWS setup (~/.aws/credentials, environment variables, or IAM role).

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Auto Mode

praisonai --framework ag2 --auto "Create a Movie Script About Cat in Mars"

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Legacy AutoGen (v0.2 / v0.4)

For existing projects using the older AutoGen package: 
pip install "praisonai[autogen]"

framework: autogen
topic: Create Movie Script About Cat in Mars

roles:
  researcher:
    role: Research Analyst
    goal: Gather information about Mars and cats
    backstory: Skilled in research, with a focus on gathering accurate and relevant information.
    tasks:
      research_task:
        description: Research about Mars environment and cat behavior
        expected_output: Research findings document with key facts

praisonai agents.yaml --framework autogen

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AutoGen Version Selection

# Use AutoGen v0.4 (default if available)
export AUTOGEN_VERSION=v0.4

# Use AutoGen v0.2
export AUTOGEN_VERSION=v0.2

# Auto-select (default: prefers v0.4)
export AUTOGEN_VERSION=auto

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Framework Selection Priority

  1. CLI flag (--framework ag2) takes precedence
  2. YAML file (framework: ag2) is used if no CLI flag
  3. Default: praisonai framework
The roles format YAML is required for both ag2 and autogen frameworks. The newer steps + agents workflow format only supports the praisonai framework.
Direct prompts always use the praisonai framework regardless of the --framework flag:
# This will use praisonai, NOT ag2
praisonai "What is 2+2?" --framework ag2
To use AG2, provide a YAML file with the roles format.

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Best Practices

The dedicated ag2 framework uses the latest AG2 package with LLMConfig support and native Bedrock. Use autogen only for existing codebases.
Each role should have a clear, distinct responsibility. The GroupChat manager routes messages based on role descriptions.
Set api_type: bedrock in the role’s llm config. No API keys needed when running on AWS with proper IAM roles.

CrewAI

CrewAI framework integration

Agents

PraisonAI native agents