Documentation Index

Fetch the complete documentation index at: https://docs.pilottai.com/llms.txt

Use this file to discover all available pages before exploring further.

​

PilottAI Agent Examples

​

Overview

• Set up multiple specialized agents
• Create and configure tools
• Execute jobs across different agents
• Use the PilottAI Serve orchestrator

​

Installation

1. Install PilottAI:

pip install pilott

2. Set up your OpenAI API key:

export OPENAI_API_KEY="your-api-key"

​

Included Examples

​

Agents

• Customer Service Agent: Handles customer inquiries and support requests
• Document Processor: Processes and analyzes documents
• Research Analyst: Conducts research and provides insights

​

Tools

• Email Sender: Tool for sending emails to customers
• Document Processor: Tool for document analysis and processing

​

Usage

from examples.agents import main

# Run the example
import asyncio
asyncio.run(main())

​

Example Output

Job: Handle refund request
Result: Customer refund request processed successfully

Job: Analyze quarterly report
Result: Document analysis complete: 3 key insights found

Job: Research competitor pricing
Result: Market research analysis completed

​

Creating Your Own Agents

1. Configure the agent:

agent_config = AgentConfig(
    title="your_agent_title",
    goal="your_agent_goal",
    tools=["tool1", "tool2"]
)

2. Add to PilottAI:

agent = await pilott.add_agent(
    title=agent_config.title,
    goal=agent_config.goal,
    tools=agent_config.tools,
    llm_config=llm_config
)

​

Best Practices

1. Agent Design
   • Give each agent a clear, focused title
   • Provide specific goals and tools
   • Use appropriate LLM configurations
2. Tool Management
   • Create reusable tools
   • Define clear tool interfaces
   • Handle tool errors gracefully
3. Job Execution
   • Group related jobs
   • Set appropriate priorities
   • Monitor execution results

​

Configuration Options

​

LLM Configuration

llm_config = LLMConfig(
    model_name="gpt-4",  # or other models
    provider="openai",   # or other providers
    temperature=0.7     # adjust based on needs
)

​

Tool Configuration

tool = Tool(
    name="tool_name",
    description="tool_description",
    function=your_function,
    parameters={
        "param1": "type1",
        "param2": "type2"
    }
)

​

Error Handling

• Add comprehensive error handling
• Implement retries for failed jobs
• Log errors appropriately
• Handle API rate limits

​

Contributing

• Add new agent examples
• Create additional tools
• Improve documentation
• Report issues
• Submit pull requests

​

Code