by @frankxai
Build production agentic applications on OCI using Oracle Agent Development Kit with multi-agent orchestration, function tools, and enterprise patterns
Master Oracle's Agent Development Kit (ADK) for building enterprise-grade agentic applications on OCI Generative AI Agents Service with code-first approach and advanced orchestration patterns.
Client-side library that simplifies building agentic applications on top of OCI Generative AI Agents Service.
Key Value: Code-first approach for embedding agents in applications (web apps, Slackbots, enterprise systems).
Requirements: Python 3.10 or later
Build agents that maintain context across multiple interactions.
Pattern:
from oci_adk import Agent
agent = Agent(
name="customer_support",
model="cohere.command-r-plus",
system_prompt="You are a helpful customer support agent"
)
# Multi-turn conversation
conversation = agent.create_conversation()
response1 = conversation.send("I need help with my order")
response2 = conversation.send("It's order #12345")
# Agent remembers context from previous messages
Routing Pattern:
# Route requests to specialized agents
def orchestrator(user_query):
if requires_technical_support(user_query):
return technical_agent.handle(user_query)
elif requires_billing(user_query):
return billing_agent.handle(user_query)
else:
return general_agent.handle(user_query)
Agent-as-a-Tool Pattern:
# One agent uses another agent as a tool
main_agent = Agent(
name="supervisor",
tools=[research_agent, analysis_agent, report_agent]
)
# Main agent orchestrates specialist agents
result = main_agent.execute("Research and analyze Q4 performance")
Build predictable, orchestrated workflows with explicit control flow.
from oci_adk import Workflow, Step
workflow = Workflow([
Step("validate_input", va...