# 1. Navigate to demo.calliope.ai
# 2. Explore the platform interface
# 3. Choose your starting component from the menu

# In your first notebook cell
from calliope import Agent, Hub

# Initialize Calliope
hub = Hub()
print(f"Connected to Calliope v{hub.version}")

# Simple AI agent - no PhD required
agent = Agent(
    name="MyFirstAgent",
    model="gpt-4",
    instructions="You are a helpful AI assistant integrated with Calliope."
)

# Test it
response = agent.chat("Hello! What can you help me with?")
print(response)

# Create specialized agents
researcher = Agent(name="Researcher", role="research")
writer = Agent(name="Writer", role="content_creation")
reviewer = Agent(name="Reviewer", role="quality_check")

# Wire them together
from calliope.autogen import Workflow

workflow = Workflow([researcher, writer, reviewer])
result = workflow.run("Write a blog post about AI trends")

import pandas as pd
from calliope.analysis import AIAnalyst

# Load data
df = pd.read_csv("your_data.csv")

# AI-powered analysis
analyst = AIAnalyst()
insights = analyst.analyze(df, 
    questions=[
        "What are the main trends?",
        "Any anomalies?",
        "What's next?"
    ]
)

from calliope.chat import ChatInterface

# Create chatbot
chatbot = ChatInterface(
    agent=agent,
    features=["rag", "memory", "tools"],
    ui_theme="modern"
)

# Deploy instantly
chatbot.deploy(subdomain="my-assistant")

from calliope.content import ContentPipeline

# Build pipeline
pipeline = ContentPipeline()
pipeline.add_stage("research", researcher)
pipeline.add_stage("writing", writer)
pipeline.add_stage("seo", seo_agent)

# Generate content
article = pipeline.generate(
    topic="Future of AI in Healthcare",
    length=1500,
    style="professional"
)