Simple Sequential Team (YAML)

The copy-paste starting point for a multi-agent team that runs tasks in order

Two agents run in order: a researcher gathers facts, then a writer summarizes them.

Quick Start

1. Drop the YAML in place

   Save this as agents.yaml in an empty folder. Tasks run in the order they are declared — the researcher’s task first, then the writer’s.

   # yaml-language-server: $schema=https://docs.praison.ai/schemas/agents.schema.json
   # Minimal sequential team: researcher -> writer
   # Run: praisonai agents.yaml
   
   framework: "praisonai"
   topic: "renewable energy"
   
   roles:
     researcher:
       role: "Senior Researcher"
       goal: "Find accurate information about {topic}"
       backstory: "Expert at concise, factual research."
       tasks:
         research_task:
           description: "Research {topic} and list 5 key facts."
           expected_output: "A bullet list of 5 facts."
   
     writer:
       role: "Report Writer"
       goal: "Turn research into readable summaries about {topic}"
       backstory: "Clear technical writer."
       tasks:
         summary_task:
           description: "Write a 3-sentence executive summary from the research."
           expected_output: "3 sentences, plain text."
   
   # Ordering is by task declaration order above (researcher's task runs first,
   # then the writer's), which is how the roles-file loader sequences tasks.
   # The optional `dependencies:` block below documents intent; the roles-file
   # loader does not consume it, so keep tasks in the order you want them run.
   dependencies:
     - task: summary_task
       depends_on: research_task

2. Run it

   Set your API key and run the file with the praisonai CLI:

   export OPENAI_API_KEY=sk-...
   praisonai agents.yaml

   Change the subject by editing the topic: line — it is interpolated into every {topic} placeholder.

How It Works

Python equivalent

The same team using friendly top-level imports:

from praisonaiagents import Agent, Task, PraisonAIAgents

researcher = Agent(role="Senior Researcher", goal="Find accurate information")
writer = Agent(role="Report Writer", goal="Turn research into summaries")

t1 = Task(description="Research renewable energy and list 5 key facts", agent=researcher)
t2 = Task(description="Write a 3-sentence summary from the research", agent=writer, context=[t1])

PraisonAIAgents(agents=[researcher, writer], tasks=[t1, t2]).start()

When to use this vs a workflow YAML

Related