Getting Started
First, initialize the Relevance AI client:
from relevanceai import RelevanceAI
client = RelevanceAI()
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)
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"})
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")
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")
Next Steps
Explore more detailed documentation for:
