digitalocean/gradient-adk-templates

digitalocean/gradient-adk-templates

Description: Contains example agents for Gradient ADK.

Language: Python

License: Apache-2.0

Stars: 8

Forks: 6

Open issues: 5

Created: 2025-10-22T19:47:46Z

Pushed: 2026-05-08T23:12:16Z

Default branch: main

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README:

Gradient ADK Templates

Production-ready templates for building and deploying AI agents on the DigitalOcean Gradient AI Platform using the Agent Development Kit (ADK).

What is Gradient ADK?

The Gradient Agent Development Kit (ADK) is DigitalOcean's framework for building, testing, and deploying AI agents. It provides:

• Simple deployment: Deploy agents with a single command using gradient agent deploy
• Framework flexibility: Build agents with LangGraph, CrewAI, or any Python framework
• Managed infrastructure: Automatic scaling, monitoring, and logging
• Integrated inference: Direct access to DigitalOcean GenAI Serverless Inference

Templates

Each template demonstrates a specific agent architecture or capability. Choose based on your use case:

| Template | Use Case | Key Concepts | Complexity | |----------|----------|--------------|------------| | [StateGraph](./StateGraph/) | Learn LangGraph basics | Conditional routing, state management | Beginner | | [WebSearch](./WebSearch/) | Simple tool-using agent | Tool binding, DuckDuckGo search | Beginner | | [FunctionCalling](./FunctionCalling/) | Invoke DO serverless functions | Dynamic tool creation, serverless integration | Beginner | | [KnowledgeBaseRAG](./KnowledgeBaseRAG/) | Query DigitalOcean Knowledge Bases | Knowledge Base integration | Beginner | | [RAG](./RAG/) | Document Q&A over PDFs | Multi-agent retrieval, query rewriting | Intermediate | | [MCP](./MCP/) | Connect to external tools | Model Context Protocol, multi-tool agents | Intermediate | | [Crew](./Crew/) | Multi-agent collaboration | CrewAI framework, sequential tasks | Intermediate | | [SocialMediaCrew](./SocialMediaCrew/) | Content creation pipeline | Multi-agent workflow, image generation | Advanced | | [DataScience](./DataScience/) | Natural language to SQL | Database queries, self-healing, visualization | Advanced | | [DeepSearch](./DeepSearch/) | Multi-step research | Human-in-the-loop, parallel execution | Advanced | | [DataEngineering](./DataEngineering/) | Snowflake + dbt pipelines | Pipeline development, data quality, dbt | Advanced | | [PromptOptimization](./PromptOptimization/) | Automated prompt tuning | DSPy MIPROv2, Gradient evaluations, version management | Advanced |

Quick Start

Prerequisites

• Python 3.10+
• DigitalOcean account with API access
• Gradient CLI installed

Installation

# Install the Gradient CLI
pip install gradient-adk

# Clone this repository
git clone https://github.com/digitalocean/gradient-adk-templates.git
cd gradient-adk-templates

Running a Template

# Navigate to a template
cd StateGraph

# Create virtual environment
python -m venv venv
source venv/bin/activate # On Windows: venv\Scripts\activate

# Install dependencies
pip install -r requirements.txt

# Configure environment
cp .env.example .env
# Edit .env with your credentials

# Run locally
export DIGITALOCEAN_API_TOKEN=your_token
gradient agent run

# Deploy to production
gradient agent deploy

Template Overview

Beginner Templates

[StateGraph](./StateGraph/) - A joke generator that demonstrates LangGraph fundamentals: state management, conditional routing, and multi-step LLM chains. Start here to understand how Gradient ADK agents work.

[WebSearch](./WebSearch/) - A minimal agent that uses DuckDuckGo for web search. Shows how to bind tools to LLMs using LangChain's create_agent helper function.

[FunctionCalling](./FunctionCalling/) - Connect an agent to any DigitalOcean Serverless Function. Features a single config file that defines your function's interface (input parameters and response schema), and the agent dynamically builds a tool the LLM can call. Includes a setup script that deploys a sample unit converter so you can try it out of the box.

[KnowledgeBaseRAG](./KnowledgeBaseRAG/) - Query your DigitalOcean-managed Knowledge Base. Demonstrates integration with DigitalOcean's Knowledge Base service for document retrieval.

Intermediate Templates

[RAG](./RAG/) - A multi-agent RAG system for document Q&A. Features query rewriting, document retrieval from local PDFs, and answer generation with citations.

[MCP](./MCP/) - Demonstrates the Model Context Protocol for connecting to external tools. Includes both cloud-hosted (Tavily search) and local (calculator) MCP servers.

[Crew](./Crew/) - A CrewAI-based agent that researches news and generates trivia facts. Shows how to deploy agents built with frameworks other than LangGraph.

Advanced Templates

[SocialMediaCrew](./SocialMediaCrew/) - A complete content creation pipeline with five specialized agents: Researcher, Copywriter, Social Media Manager, Reviewer, and Image Prompt Designer. Includes automatic revision loops and AI image generation.

[DataScience](./DataScience/) - A data science agent that converts natural language to SQL, executes queries, analyzes results, and generates visualizations. Features self-healing queries that automatically retry on failure.

[DeepSearch](./DeepSearch/) - A research agent with human-in-the-loop plan approval and parallel section research using LangGraph's Send API. Produces comprehensive reports with citations.

[DataEngineering](./DataEngineering/) - A data engineering assistant that helps build and manage Snowflake data pipelines using dbt. Can create transformation models, run data quality checks, troubleshoot pipeline failures, and explore your data warehouse. Includes a full sample e-commerce dataset with realistic data quality issues and a complete dbt project with staging, intermediate, and mart layers.

[PromptOptimization](./PromptOptimization/) - An automated prompt optimization workflow using DSPy MIPROv2 to improve a customer support agent's system prompt. Features two-tier evaluation (DSPy custom metrics + Gradient platform evaluations), prompt version tracking with rollback, and a guided CLI for the full optimize-evaluate-deploy cycle.

Common Patterns

Agent Structure

All templates follow a consistent structure:

TemplateName/
├── .gradient/
│ └── agent.yml # Deployment…