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Getting Started

First, initialize the Relevance AI client: 
from relevanceai import RelevanceAI
client = RelevanceAI()

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Working with Agents

List all available agents in your project: 
agents = client.agents.list_agents()
agents

[Agent(agent_id="xxxxxxxx", name="Sales Qualifier"), Agent(agent_id="xxxxxxxx", name="SEO Assistant")]
Retrieve a specific agent and trigger a task: 
my_agent = client.agents.retrieve_agent(agent_id="xxxxxxxx")

# Trigger a task with the agent
task = my_agent.trigger_task(message="Analyze this lead: John Smith from Acme Corp")
print(f"Task started with ID: {task.conversation_id}")

# View task progress
steps = my_agent.view_task_steps(conversation_id=task.conversation_id)

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Using Tools

List and interact with available tools: 
tools = client.tools.list_tools()
tools

[Tool(tool_id="xxxxxxxx", title="Search Website"), Tool(tool_id="xxxxxxxx", title="Extract Data")]
Trigger a tool with specific parameters: 
my_tool = client.tools.retrieve_tool(tool_id="xxxxxxxx")

# Check tool parameters schema
params_schema = my_tool.get_params_schema()

# Trigger the tool
result = my_tool.trigger(params={"search_query": "AI automation"})

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Managing Knowledge Sets

Work with knowledge sets to store and retrieve data: 
# List knowledge sets
knowledge_sets = client.knowledge.list_knowledge()

# Retrieve data from a knowledge set
data = client.knowledge.retrieve_knowledge(knowledge_set="my_dataset")

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Managing Tasks

Track and manage ongoing tasks: 
# Get task metadata
metadata = client.tasks.get_metadata(conversation_id="xxxxxxxx")

# Delete a completed task
client.tasks.delete_task(conversation_id="xxxxxxxx")

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Next Steps

Explore more detailed documentation for: