ADK Utils Go

Utilities and implementations for Google's Agent Development Kit (ADK) in Go.

This repository provides production-ready implementations for:

• LLM Clients: OpenAI and Anthropic clients compatible with ADK
• Session Management: Redis-based session persistence
• Long-term Memory: PostgreSQL + pgvector for semantic search
• Memory Tools: Toolsets for agent-controlled memory operations

Structure

├── genai/            # LLM client implementations
│   ├── openai/       # OpenAI client (works with Ollama, OpenRouter, etc.)
│   └── anthropic/    # Anthropic Claude client
├── session/          # Session service implementations
│   └── redis/        # Redis session service
├── memory/           # Memory service implementations
│   └── postgres/     # PostgreSQL + pgvector memory service
├── tools/            # Tool and toolset implementations
│   └── memory/       # Memory toolset for agents
└── examples/         # Working examples

Installation

go get github.com/achetronic/adk-utils-go

LLM Clients

OpenAI Client

Works with OpenAI API and any OpenAI-compatible API (Ollama, OpenRouter, Azure OpenAI, etc.):

import genaiopenai "github.com/achetronic/adk-utils-go/genai/openai"

// Create client
llmModel := genaiopenai.New(genaiopenai.Config{
    APIKey:    os.Getenv("OPENAI_API_KEY"),
    BaseURL:   "http://localhost:11434/v1", // For Ollama
    ModelName: "gpt-4o",                     // Or "qwen3:8b" for Ollama
})

// Use with ADK agent
agent, _ := llmagent.New(llmagent.Config{
    Name:  "assistant",
    Model: llmModel,
    // ...
})

Anthropic Client

Native Anthropic Claude support:

import genaianthropic "github.com/achetronic/adk-utils-go/genai/anthropic"

llmModel := genaianthropic.New(genaianthropic.Config{
    APIKey:    os.Getenv("ANTHROPIC_API_KEY"),
    ModelName: "claude-sonnet-4-5-20250929",
})

agent, _ := llmagent.New(llmagent.Config{
    Name:  "assistant",
    Model: llmModel,
    // ...
})

Supported Features

Both clients support:

• Streaming and non-streaming responses
• System instructions
• Tool/function calling
• Image inputs (base64)
• Temperature, TopP, MaxTokens, StopSequences
• Usage metadata

Session Service (Redis)

Persistent session storage with Redis:

import sessionredis "github.com/achetronic/adk-utils-go/session/redis"

sessionService, _ := sessionredis.NewRedisSessionService(sessionredis.RedisSessionServiceConfig{
    Addr:     "localhost:6379",
    Password: "",
    DB:       0,
    TTL:      24 * time.Hour,
})
defer sessionService.Close()

// Use with ADK runner
runner, _ := runner.New(runner.Config{
    SessionService: sessionService,
    // ...
})

Memory Service (PostgreSQL + pgvector)

Long-term memory with semantic search:

import memorypostgres "github.com/achetronic/adk-utils-go/memory/postgres"

memoryService, _ := memorypostgres.NewPostgresMemoryService(ctx, memorypostgres.PostgresMemoryServiceConfig{
    ConnString: "postgres://postgres:postgres@localhost:5432/postgres?sslmode=disable",
    EmbeddingModel: memorypostgres.NewOpenAICompatibleEmbedding(memorypostgres.OpenAICompatibleEmbeddingConfig{
        BaseURL: "http://localhost:11434/v1",
        Model:   "nomic-embed-text",
    }),
})
defer memoryService.Close()

// Use with ADK runner
runner, _ := runner.New(runner.Config{
    MemoryService: memoryService,
    // ...
})

Memory Toolset

Give agents explicit control over long-term memory:

import memorytools "github.com/achetronic/adk-utils-go/tools/memory"

memoryToolset, _ := memorytools.NewToolset(memorytools.ToolsetConfig{
    MemoryService: memoryService,
    AppName:       "my_app",
})

agent, _ := llmagent.New(llmagent.Config{
    Toolsets: []tool.Toolset{memoryToolset},
    // ...
})

The toolset provides:

• search_memory: Semantic search across stored memories
• save_to_memory: Save information for future recall

Examples

Complete working examples in the examples/ directory:

Example	Description
openai-client	OpenAI/Ollama client usage
anthropic-client	Anthropic Claude client usage
session-memory	Session management with Redis
long-term-memory	Long-term memory with PostgreSQL + pgvector
full-memory	Combined session + long-term memory

Quick Start

# Start services
docker run -d --name postgres -e POSTGRES_PASSWORD=postgres -p 5432:5432 pgvector/pgvector:pg16
docker run -d --name redis -p 6379:6379 redis:alpine
ollama pull qwen3:8b
ollama pull nomic-embed-text

# Run an example
go run ./examples/openai-client

Environment Variables

Variable	Default	Description
OPENAI_API_KEY	-	OpenAI API key (not needed for Ollama)
OPENAI_BASE_URL	-	OpenAI-compatible API endpoint
ANTHROPIC_API_KEY	-	Anthropic API key
MODEL_NAME	gpt-4o / claude-sonnet-4-5-20250929	Model name
EMBEDDING_BASE_URL	http://localhost:11434/v1	Embedding API endpoint
EMBEDDING_MODEL	nomic-embed-text	Embedding model
POSTGRES_URL	postgres://postgres:postgres@localhost:5432/postgres?sslmode=disable	PostgreSQL connection
REDIS_ADDR	localhost:6379	Redis address

Requirements

• Go 1.24+
• Google ADK v0.3.0+

License

Apache 2.0