Reusable Go library for building LLM agents
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Victor Vargas e6830161bc fix(llamacpp,anthropic): SSE headroom, no-choices guard, real context window
- llamacpp: 4MB SSE scanner buffer (the 64KB bufio.Scanner default killed
  streams whose single line exceeded it, e.g. a write tool call carrying a
  whole file) and an empty-choices guard in toResponse instead of a panic;
  request payload now uses bytes.NewReader (drops a full string copy).
- anthropic: Capabilities() reported a 1M-token context window for any
  non-haiku model. Callers use that number to decide when to compact, so
  compaction would have fired far too late and requests overflowed the
  real window. Default is now the standard 200k, configurable via
  Config.ContextWindow for extended-window models/plans.

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
2026-07-12 16:14:15 -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(agent): add SubAgent runtime for nested, specialized agent loops 2026-07-09 12:08:32 -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 fix(llamacpp,anthropic): SSE headroom, no-choices guard, real context window 2026-07-12 16:14:15 -07:00
.gitignore chore: initial scaffold with design docs 2026-06-28 16:03:57 -07:00
AGENTS.md feat(agent): add SubAgent runtime for nested, specialized agent loops 2026-07-09 12:08:32 -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