import { Agent, Tool } from 'agentflare'
 
// Create a documentation search tool
const docSearchTool = new Tool({
  name: 'search-docs',
  description: 'Search product documentation',
  parameters: {
    query: { type: 'string', required: true }
  },
  execute: async ({ query }) => {
    // Search your documentation
    const results = await searchDocs(query)
    return results
  }
})
 
// Create the support agent
const supportAgent = new Agent({
  name: 'SupportAgent',
  model: 'gpt-4',
  tools: ['search-docs', 'create-ticket'],
  systemPrompt: `You are a helpful customer support agent. 
    Search documentation to answer questions. 
    If you cannot resolve the issue, create a support ticket.`,
  memory: {
    type: 'conversation',
    maxTokens: 4000
  }
})
 
supportAgent.addTool(docSearchTool)
 
// Handle customer inquiry
const response = await supportAgent.run(
  'How do I reset my password?'
)

import { Agent, Tool } from 'agentflare'
 
const pythonTool = new Tool({
  name: 'python',
  description: 'Execute Python code for data analysis',
  parameters: {
    code: { type: 'string', required: true }
  },
  execute: async ({ code }) => {
    // Execute Python code safely
    const result = await executePython(code)
    return result
  }
})
 
const dataAgent = new Agent({
  name: 'DataAnalyst',
  model: 'gpt-4',
  tools: ['python', 'visualization'],
  systemPrompt: `You are an expert data analyst. 
    Analyze datasets and provide insights.
    Create visualizations to illustrate findings.`
})
 
dataAgent.addTool(pythonTool)
 
// Analyze data
const analysis = await dataAgent.run(`
  Analyze this sales data and identify trends:
  ${salesData}
`)

import { Workflow, Agent } from 'agentflare'
 
// Create specialized agents
const researchAgent = new Agent({
  name: 'Researcher',
  model: 'gpt-4',
  tools: ['web-search', 'scraper'],
  systemPrompt: 'Research topics thoroughly and gather information.'
})
 
const writerAgent = new Agent({
  name: 'Writer',
  model: 'gpt-4',
  tools: ['grammar-check'],
  systemPrompt: 'Write clear, engaging content based on research.'
})
 
const editorAgent = new Agent({
  name: 'Editor',
  model: 'gpt-4',
  systemPrompt: 'Review and improve content for clarity and accuracy.'
})
 
// Create workflow
const contentWorkflow = new Workflow({
  name: 'ContentCreation',
  agents: [researchAgent, writerAgent, editorAgent],
  steps: [
    {
      agent: 'Researcher',
      input: 'Research AI agent frameworks'
    },
    {
      agent: 'Writer',
      input: 'Write an article based on: {{Researcher.output}}'
    },
    {
      agent: 'Editor',
      input: 'Edit and improve: {{Writer.output}}'
    }
  ]
})
 
// Execute workflow
const result = await contentWorkflow.execute()
console.log(result.output)

import { Agent } from 'agentflare'
 
const ragAgent = new Agent({
  name: 'RAGAssistant',
  model: 'gpt-4',
  tools: ['vector-search'],
  memory: {
    type: 'vector',
    vectorStore: {
      provider: 'pinecone',
      index: 'knowledge-base',
      dimension: 1536
    }
  },
  systemPrompt: `You are a knowledgeable assistant.
    Use vector search to find relevant information.
    Provide accurate answers based on the knowledge base.`
})
 
// Query with context retrieval
const answer = await ragAgent.run(
  'What are the best practices for agent design?'
)