floret

Floret

A Go library for building interactive, tool-using AI agents.
_{Floret handles the agent loop; your application keeps the UI, permissions, storage choices, and domain tools.}

Why Floret · At a glance · Quick Start · Using Floret · Architecture · Packages · License

Floret is a Go library for applications that need model streaming, tool execution, session state, context management, storage, compaction, and runtime events. It is not a graph workflow framework. It keeps the agent runtime small so your application can decide how users see and control it.

✨ Why Floret

Most AI agent applications end up rebuilding the same plumbing: prompt assembly, provider adapters, tool-call validation, approval hooks, session persistence, long conversation handling, retries, usage metrics, and events that a UI can render. Floret packages those pieces as small Go APIs.

• Agent loop: stream model output, continue after tool calls, enforce loop limits, and return a clear run result.
• Tools: register strict JSON-schema tools, ask for approval when needed, run safe read-only tools in parallel, and serialize mutating tools.
• Threads: start, resume, fork, retry, and recover interrupted conversations with agentharness.
• Context: estimate usage, keep a recent tail, and compact older history when a run exceeds the configured context policy.
• Events: send provider, tool, compaction, budget, and final-state events without tying them to a specific UI.
• Tests: use fake providers and scripted tool calls to test agent behavior without real model calls.

🧭 At a glance

🧩 Core building blocks

Runtime Shape

Context compaction replaces older assistant/tool history with a structured checkpoint while retaining a verbatim recent tail for execution continuity. Recent user inputs outside that tail are protected inside the checkpoint: the latest user message is always represented, and recent older user messages are preserved within a 15k-token user-input budget without replaying them as new standalone turns.

Most hosts should use runtime.NewHarness, then StartThread or ResumeThread, and finally Thread.Run for each user turn. That API keeps durable conversation state in sessiontree.Repo and serializes only the same durable ThreadID. Different threads and forked threads can run concurrently.

The project is intentionally not a workflow graph engine. It is designed for interactive agent hosts where a model, a tool registry, a session store, and a UI work around one turn loop that emits events.

Events are UI-neutral so a terminal UI, desktop app, test harness, or automation surface can render the same runtime facts without parsing human text. Public views should expose sanitized events and observations. Raw provider deltas, reasoning, tool arguments/results, prompt segments, and artifact paths are local debug data and require explicit opt-in at the host boundary.

Context Pressure

Floret keeps context-budget signals separate so hosts and storage do not have to guess what a token number means:

• provider.Usage is native provider usage and cost data from a successful response. WindowInputTokens is the context-window input; InputTokens may be cost-normalized. Cached prompt reads and writes are still model-visible input for window pressure.
• contextpolicy.RequestEstimate is a preflight prediction for the actual provider request, including prefix messages, active messages, local tool definitions, and provider-hosted tool options. It is stored with provider request records, not as fake provider usage.
• contextpolicy.ContextPressure is the only structure that drives ordinary auto-compaction. It distinguishes native usage, projected request pressure, and provider overflow. Provider overflow compacts, rebuilds the request, re-estimates pressure, and retries the same logical request once.
• contextpolicy.MessageContextEstimate and contextpolicy.Usage are compaction-internal message budgets. They are used for retained tail and summary prompts, not for deciding whether an ordinary provider request can be sent.

After a successful ordinary request with native usage, Floret stores a pressure anchor in the prompt cache. The next preflight projection can use that anchor plus a request delta when the session, provider, model, rendered request shape, and active message lineage still match; otherwise it falls back to a full request estimate.

🚀 Quick Start

1. Clone the repository and run the test suite:

   go test ./...
   

2. Start the local agent console:

   go run ./cmd/floret-test-ui
   

3. Open http://127.0.0.1:8765.

The console can run fake-provider turns immediately, manage local provider profiles, save the active profile to .env.local, inspect provider requests and stream events, view session messages, review token/tool metrics, and run local checks such as package tests, race tests, provider smoke tests, tool scenarios, and the deterministic eval demo. New Session keeps context policy controls in Advanced options by default; those values are derived from the active provider/model catalog and backend context defaults, while still being submitted with the session create request. Session tool runs expose local inspection details by default, including tool arguments, results, reasoning, projections, and metadata. Host-specific path references are still normalized for readable local output.

Install / Import

Use Floret as a Go module:

go get github.com/floegence/floret

Floret targets Go 1.22.

Provider Configuration

Floret reads .env.local by default through config.Load. The file is intentionally ignored by git so local API keys and model choices stay private. Environment variables override .env.local, which is useful for CI and one-off smoke tests.

When no prompt override is configured, Floret uses DefaultFloretAgentProfile() as the default agent identity, with the system prompt You are Floret.. Hosts can provide a config.AgentProfile in code to build their own role while keeping the same runtime, storage, tool, and provider contracts. FLORET_SYSTEM_PROMPT remains available as an environment-loaded system prompt override.

Tip: start with the fake provider first. It lets you validate the host loop, tool registry, storage, and UI wiring before adding any external model credentials.

A minimal fake-provider configuration:

FLORET_PROVIDER=fake
FLORET_MODEL=fake-model
FLORET_FAKE_RESPONSE=floret local provider ok
FLORET_RUN_ID=local

Common context and runtime controls:

FLORET_CONTEXT_WINDOW_TOKENS=256000
FLORET_MAX_OUTPUT_TOKENS=0
FLORET_RESERVED_OUTPUT_TOKENS=64000
FLORET_RESERVED_SUMMARY_TOKENS=20000
FLORET_RECENT_TAIL_TOKENS=12000
FLORET_RECENT_USER_TOKENS=15000
FLORET_WALL_TIME=30s

When FLORET_MAX_OUTPUT_TOKENS is omitted, a selected catalog model's max_tokens can provide the ordinary response cap. Setting FLORET_MAX_OUTPUT_TOKENS=0 explicitly leaves ordinary assistant responses uncapped by Floret. The reserved output and summary settings are context-budget controls; they are not ordinary response caps.

Built-in catalog defaults target models with at least a 256000-token context window. Custom or newly released models are still allowed, including smaller-context configurations, but Floret may warn that they can behave poorly on long agent tasks.

Built-in provider IDs include:

fake, openai, anthropic, google, moonshot, chatglm, deepseek, qwen,
openrouter, xai, groq, ollama, openai-compatible

Some provider entries, such as local or fast-changing OpenAI-compatible services, use a custom-model placeholder instead of predefined low-context model names. Set FLORET_MODEL, FLORET_CONTEXT_WINDOW_TOKENS, and related output budget values to match the model you intend to run.

When FLORET_MODEL is omitted, Floret uses the catalog default for that provider. When FLORET_BASE_URL is omitted, Floret uses the provider default endpoint. FLORET_API_KEY always works, and provider-specific environment variables such as OPENAI_API_KEY, ANTHROPIC_API_KEY, GEMINI_API_KEY, DEEPSEEK_API_KEY, DASHSCOPE_API_KEY, MOONSHOT_API_KEY, and OPENROUTER_API_KEY are also recognized.

For OpenAI:

FLORET_PROVIDER=openai
OPENAI_API_KEY=your-api-key

For a custom OpenAI-compatible gateway:

FLORET_PROVIDER=openai-compatible
FLORET_MODEL=your-model
FLORET_BASE_URL=https://api.example.com/v1
FLORET_API_KEY=your-api-key

Using Floret in a Host

The runtime package wires configuration, a provider adapter, prompt cache, system prompt assembly, durable session storage, and a tool registry into an agentharness.AgentHarness.

package main

import (
	"context"
	"fmt"
	"log"

	"github.com/floegence/floret/agentharness"
	"github.com/floegence/floret/config"
	floretruntime "github.com/floegence/floret/runtime"
	"github.com/floegence/floret/sessiontree"
	"github.com/floegence/floret/tools"
)

type echoArgs struct {
	Text string `json:"text"`
}

func main() {
	ctx := context.Background()

	cfg, err := config.Load()
	if err != nil {
		log.Fatal(err)
	}

	// Omit AgentProfile to use the default Floret identity.
	// Set it when your host wants its own agent role and use case.
	cfg.AgentProfile = config.AgentProfile{
		ID:           "acme-support",
		Name:         "Acme Support",
		Description:  "Support assistant for Acme product workflows.",
		SystemPrompt: "You are Acme Support. Help users troubleshoot Acme product workflows.",
	}

	registry := tools.NewRegistry()
	err = registry.Register(tools.Define[echoArgs](
		tools.Definition{
			Name:        "echo",
			Title:       "Echo",
			Description: "Return the supplied text.",
			InputSchema: tools.StrictObject(map[string]any{
				"text": tools.String("Text to echo."),
			}, []string{"text"}),
			ReadOnly: true,
		},
		nil,
		nil,
		func(ctx context.Context, inv tools.Invocation[echoArgs]) (tools.Result, error) {
			return tools.Result{Text: inv.Args.Text}, nil
		},
	))
	if err != nil {
		log.Fatal(err)
	}

	h, err := floretruntime.NewHarness(cfg, floretruntime.HarnessOptions{
		Store: sessiontree.NewMemoryRepo(),
		Tools: registry,
	})
	if err != nil {
		log.Fatal(err)
	}
	thread, err := h.StartThread(ctx, agentharness.StartThreadOptions{})
	if err != nil {
		log.Fatal(err)
	}

	result, err := thread.Run(ctx, "Say hello in one short sentence.", agentharness.RunOptions{})
	if err != nil {
		log.Fatal(err)
	}
	fmt.Println(result.Output)
}

Prompt precedence is intentionally small and explicit:

Config.SystemPrompt
  > Config.AgentProfile.SystemPrompt
  > env-loaded FLORET_SYSTEM_PROMPT
  > DefaultFloretAgentProfile().SystemPrompt

SystemPrompt is kept for compatibility and direct session-level overrides. When it is set, Floret marks the resolved identity as a custom session agent. Skills, MCP tools, and other capability disclosures are appended to the resolved base identity prompt; they do not replace or mutate the configured agent profile. Public session snapshots expose profile id/name/source/hash metadata, but not the raw system prompt. Raw prompt inspection in the test console requires -allow-debug-raw.

For lower-level hosts, construct engine.Engine with engine.New(engine.Config{...}) using your own provider.Provider, session.Store, tools.Registry, event.Sink, approver, stop hook, compaction generator, and engine options. Direct engine use is best for tests, eval runners, and specialized hosts that already own session persistence.

Threaded Agent Harness

agentharness builds on the engine for applications that need persistent threads instead of isolated runs. It supports:

• Starting and resuming threads.
• Forking from an earlier session entry.
• Retrying failed or waiting turns.
• Marking interrupted turns when a process restarts.
• Moving a thread leaf after branch selection.
• Emitting harness lifecycle events alongside engine events.

The harness stores entries in a sessiontree.Repo and projects the active path into engine context for each turn. Thread.Read() returns a host-safe snapshot with lifecycle state and display messages. Raw session-tree data is available through Thread.Journal() for tests, debug consoles, migrations, and admin tooling. This keeps thread operations separate from provider and tool execution.

Tools

Floret tools are registered through tools.Registry with strict JSON object schemas. The registry validates arguments before execution, extracts resource references for approval decisions, applies result limits, recovers from panics, and reports structured tool results back into the engine. Tool definitions are part of the host contract: the runtime owns validation, scheduling, permission hooks, and result shaping, while host applications decide which domain tools exist and what those tools do.

Tool scheduling is owned by the registry:

• Read-only tools may run in parallel.
• Mutating tools are serialized.
• PermissionAsk tools call the host approver before execution.
• PermissionDeny tools are not exposed to the provider and are rejected before execution.
• Safe read-only tools may omit Permission.Mode; mutating, shell, network, destructive, and open-world tools must declare Permission.Mode explicitly.
• Open-world tools cannot use PermissionAllow; prefer PermissionAsk or PermissionDeny for high-risk tools unless the host has a narrower policy gate.

tools/builtin is an optional default tool set for local host applications. It includes workspace reads (read, list, glob, grep), workspace mutations (apply_patch, write), shell execution, and web_search, but those tools are examples and conveniences rather than the whole project.

Storage

Floret separates session message storage, session-tree storage, prompt-cache storage, and host metadata:

• session.NewMemoryStore is the simplest in-memory store for isolated engine runs.
• sessiontree.NewMemoryRepo and sessiontree.NewFileRepo support threaded sessions.
• provider/cache.NewMemoryStore and provider/cache.NewFileStore store rendered prompt fragments and provider response records.
• runtime/storage/sqlite.Open provides one SQLite-backed store for session trees, prompt cache, metadata, and session deletion.

The local test UI defaults to SQLite at .floret-test-ui/floret.db. It can also run with file or memory storage through go run ./cmd/floret-test-ui --storage=file or --storage=memory.

Architecture

Floret keeps runtime concerns separated from your application code:

Your application
  UI / CLI / automation
  domain tools / permission policy / app state
        |
        v
agentharness or engine.Engine
        |
        +--> provider.Provider       model streaming and usage
        +--> tools.Registry          tool schemas, approvals, scheduling
        +--> session/sessiontree     messages, threads, forks, retries
        +--> provider/cache          provider-specific rendered context
        +--> session/contextpolicy   active context policy
        +--> event.Sink              UI-neutral runtime events

Important behavior is available through events or testable state. Hosts should render events rather than parse assistant text to infer progress. Provider-visible local tools always come from tools.Registry; host code should not hand-write raw provider tool definitions to bypass registry validation or permission policy.

📦 Packages

Testing and Evals

Run the primary quality gate:

go test ./...

Run race-enabled tests:

go test -race ./...

The test suite covers deterministic agent loop behavior, provider usage aggregation, trace redaction, OpenAI-compatible streaming tool arguments, registry-owned tool scheduling, context/tool-result pairing, session-tree branching, SQLite persistence, prompt-cache rendering, and a minimal oracle-based eval runner.

The local console also exposes quick checks for package tests, race tests, provider smoke tests, tool scenarios, live tool scenarios, and the deterministic eval demo. Console artifacts are written under .floret-test-ui/, which is ignored by git.

Project Status

Floret is under active development. APIs may evolve while the runtime contracts settle, especially around host integration, storage, provider-specific capabilities, and the local inspector UI.

Contributing

Keep changes small, visible in events or tests, and easy to test without real model calls. Prefer focused contracts over framework-style extension layers, and keep provider, context, tool runtime, session storage, and host UI concerns separated.

Before proposing integration, run:

go test ./...

License

Floret is licensed under the MIT License.