Reusable Go library for building LLM agents
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Victor Vargas 0f835a0802 feat(agent): wire AGENTS.md discovery into the agent loop's system prompt
Export persona.DiscoverAgentsMD and add agent.Config.AgentsMD so project
and global AGENTS.md rules actually reach the model. Previously
buildInitialMessages always called AssembleSystemPrompt with an empty
string, so no AGENTS.md content was ever injected despite the discovery
logic already existing.

Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
2026-07-08 23:27:17 -07:00
.agents/skills/add-feature docs: add AGENTS.md guide and skill definitions for AI agents 2026-06-30 23:53:34 -07:00
docs feat: add history messages, reasoning content, and adaptive language support 2026-07-05 16:17:37 -07:00
examples docs(i18n): translate all docs to English (with .es.md as Spanish alternative) 2026-06-30 13:40:37 -07:00
pkg feat(agent): wire AGENTS.md discovery into the agent loop's system prompt 2026-07-08 23:27:17 -07:00
.gitignore chore: initial scaffold with design docs 2026-06-28 16:03:57 -07:00
AGENTS.md docs(AGENTS): update repo status to reflect Go source code exists 2026-07-03 14:22:46 -07:00
go.mod feat(rag): add SQLite+FTS5 backend, fix content/usage plumbing bugs 2026-07-06 00:05:30 -07:00
go.sum feat(rag): add SQLite+FTS5 backend, fix content/usage plumbing bugs 2026-07-06 00:05:30 -07:00
LICENSE chore: initial scaffold with design docs 2026-06-28 16:03:57 -07:00
README.es.md docs(i18n): translate all docs to English (with .es.md as Spanish alternative) 2026-06-30 13:40:37 -07:00
README.md docs(fix): fix go-llm-agent → rony-llm-agent 2026-06-30 14:43:00 -07:00

rony-llm-agent

🌐 Language: English | Español

🔑 Reusable core library for building LLM agents in Go.

This library is the heart of several Victor Vargas projects:

  • harness — AI agent harness for software development (TUI)
  • chat-bot — HTTP chatbot for portfolios and websites

It provides all the generic logic of an LLM agent:

Component Location Responsibility
Agent loop pkg/agent/ Iterative loop with guardrails
LLM clients pkg/llm/ Multi-provider abstraction (OpenAI, Anthropic, Ollama)
RAG / memory pkg/rag/ Short and long-term memory with semantic search
Persona system pkg/persona/ Configurable system prompts + AGENTS.md discovery
Tool registry pkg/tools/ JSON Schema + execution sandbox
Config loading pkg/config/ YAML loading with hierarchical precedence

🎯 Philosophy

  • Reusable, not opinionated. Does not force a UI type, deployment, or use case.
  • Pure Hexagonal. Ports & adapters — every external dependency is behind an interface.
  • Streaming-first. Uses iter.Seq2 from Go 1.23+ for natural streaming without callbacks.
  • Secure by default. Filesystem path sandbox with os.Root (Go 1.24+).
  • Zero magic. No reflection, no codegen, no DSLs. Idiomatic and explicit Go.
  • YAML configurable. Everything that affects behavior is declarative.

📦 Installation

go get github.com/VictorVargas/rony-llm-agent

🚀 Basic usage

package main

import (
    "context"
    "fmt"
    "github.com/VictorVargas/rony-llm-agent/pkg/agent"
    "github.com/VictorVargas/rony-llm-agent/pkg/llm"
    "github.com/VictorVargas/rony-llm-agent/pkg/persona"
)

func main() {
    // 1. Create LLM client
    llmClient, _ := llm.NewAnthropicClient(llm.AnthropicConfig{
        APIKey: os.Getenv("ANTHROPIC_API_KEY"),
        Model:  "claude-sonnet-4.5",
    })

    // 2. Load persona
    p := persona.Load("./persona.yaml")

    // 3. Create agent loop
    loop := agent.New(agent.Config{
        LLM:         llmClient,
        Persona:     p,
        MaxIters:    50,
        Sandbox:     agent.NewSandbox("./workspace"),
    })

    // 4. Run
    resp, err := loop.Run(context.Background(), "Refactor auth.go")
    if err != nil { panic(err) }

    fmt.Println(resp.Content)
}

🔌 Included adapters

LLM Providers (pkg/llm/providers/)

Provider Import Models
OpenAI providers/openai gpt-4o, gpt-4o-mini, gpt-4-turbo
Anthropic providers/anthropic claude-sonnet-4.5, claude-haiku-4
Ollama providers/ollama llama3.1, qwen2.5, mistral, etc.
llama.cpp providers/llamacpp Custom GGUF models

Vector DBs (pkg/rag/backends/)

Backend Status
ChromaDB embedded Stable
Qdrant embedded 🚧 In development
SQLite + sqlite-vec 📋 Planned

Embeddings (pkg/rag/embeddings/)

  • Ollama embeddings (nomic-embed-text, bge-m3, etc.)
  • Local sentence-transformers via ONNX

🧪 Testing

go test ./...
go test -race ./...
go test -bench=. ./pkg/agent/

Includes MockLLMClient for deterministic tests without burning API calls.

📐 Versions

  • Go minimum: 1.26 (uses os.Root, iter.Seq, unique.Handle, container-aware GOMAXPROCS)
  • Versioning policy: Strict semver. API breaking changes only on MAJOR.

📄 License

MIT — see LICENSE.

🔗 Projects that use this library

📚 Additional documentation