micro--go-micro
9fdcc24cce
* docs: design note for flow steps + Checkpoint durable execution
* docs: fold in durable-execution decisions (State struct, single Step, run retention, retry)
* docs: rename State.Payload to State.Data
* feat(flow): ordered steps + Checkpoint durable execution
A flow can now be an ordered list of steps (a task with stages) instead
of a single LLM turn. State carries typed Data plus a Stage marker; each
step is checkpointed before and after via a pluggable Checkpoint
(store-backed by default), so a run survives a crash and resumes where it
stopped without re-running completed steps. Flow-level Retry with a
per-step override; runs retained for audit unless DeleteOnSuccess.
Step actions: Call (RPC), LLM (augmented turn), Dispatch (to an agent),
or any StepFunc. Single-step and agent-dispatch flows are unchanged.
* feat(flow): top-level re-exports + durable flow example
Expose the step/checkpoint API from the micro package (FlowSteps,
FlowStep, FlowState, FlowRetry, FlowWithCheckpoint, FlowCall/LLM/Dispatch,
Checkpoint, StoreCheckpoint) and add a runnable, key-free example
demonstrating crash + resume.
* docs: document durable flow steps (guide, README, CLI help)
* docs: blog post + changelog for durable workflows
* fix(flow): scope checkpoint keys by flow name (flow/{name}/runs/{id})
Run keys were flow/runs/{id} — a single global keyspace shared by every
flow on the default store. Namespace them by flow name so each flow's
state is kept apart. StoreCheckpoint now takes a scope argument (the flow
passes its name by default).
* feat(store): Scope handle; scope agent and flow state by name
Add store.Scope(s, database, table) — a store handle that confines every
operation to a database/table without mutating the shared store, so
co-located components don't clobber each other's table (the failure mode
of the global Init(Table(...)) approach).
Use it to keep each agent's memory and plan in its own table
(agent/{name}) and each flow's runs in its own (flow/{name}), instead of
one global table partitioned only by key prefix. Services already scope
by service name.
* feat: consistent state model — service store scoping, flow registry, list/history CLI
- service: scope store via store.Scope (database service / table name),
retiring the Init(store.Table(name)) global-mutation hack; bridge the
default store so handlers using store.DefaultStore stay isolated.
- flow: register in the registry as type=flow while running (with trigger
and step count), deregister on Stop. Live discovery, like agents.
- cli: micro flow list (registry), micro flow runs <name> (durable store),
micro agent history <name> (durable store). list = running, runs/history
= durable, mirroring the service model.
* test: mini-universe end-to-end harness + scheduled GitHub Action
internal/harness/universe boots a small but real go-micro world — four
services, a durable checkout flow that crashes at payment and resumes,
and a guardrailed agent with a tool wrapper reached over RPC — drives the
scenario, asserts the end state (10 checks), and shuts down. Everything
is real except the LLM (mocked), so it's deterministic and needs no key;
-provider anthropic runs it live. Exits non-zero on failure, so it's an
end-to-end test, not just a demo.
Adds .github/workflows/universe.yml (push/PR/daily/dispatch) running the
universe + existing harnesses on the mock provider, plus an opt-in job
that runs live when ANTHROPIC_API_KEY is set. 'make harness' runs them
locally.
* ci: run the live universe job against AtlasCloud (ATLASCLOUD_API_KEY)
* ci: run the live universe job only on schedule or manual dispatch
The deterministic mock job still runs on push/PR/daily; the live
(AtlasCloud) job runs daily and on manual workflow_dispatch only, so
changes don't burn API credits on every PR but can still be checked
against a real model on demand.
---------
Co-authored-by: Claude <noreply@anthropic.com>
123 行
4.1 KiB
Go
123 行
4.1 KiB
Go
package flow
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// Options configures a Flow.
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type Options struct {
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// TriggerTopic is the broker topic that triggers this flow.
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TriggerTopic string
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// Prompt is a Go template string. {{.Data}} is the event payload.
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Prompt string
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// SystemPrompt is the system instruction for the LLM.
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SystemPrompt string
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// Provider is the AI provider name (e.g. "anthropic", "openai").
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Provider string
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// APIKey for the AI provider.
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APIKey string
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// Model overrides the provider's default model.
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Model string
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// BaseURL overrides the provider's default base URL.
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BaseURL string
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// HistoryLimit is the max messages per flow execution.
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HistoryLimit int
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// OnResult is called after each execution with the result.
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OnResult func(Result)
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// Agent, if set, names a registered agent the flow hands each event
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// to (over RPC). The flow triggers; the agent reasons. When empty,
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// the flow runs a single augmented-LLM step itself.
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Agent string
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// Steps, if set, makes the flow run an ordered list of steps per
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// event instead of a single LLM step — the deterministic-workflow
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// path. Checkpointed between steps when a Checkpoint is set.
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Steps []Step
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// Retry is the flow-level retry count applied to each step (0 = no
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// retry). A Step's own Retry field overrides this.
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Retry int
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// Checkpoint is the durability backend for stepped runs. Nil with
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// steps present means a store-backed default; set it to swap backends.
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Checkpoint Checkpoint
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// DeleteOnSuccess removes a run's checkpoint when it completes
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// successfully. Failed runs are always retained. Default: retain all.
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DeleteOnSuccess bool
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}
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// Option applies a configuration to Options.
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type Option func(*Options)
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// Trigger sets the broker topic that triggers this flow.
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func Trigger(topic string) Option {
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return func(o *Options) { o.TriggerTopic = topic }
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}
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// Prompt sets the prompt template. Use {{.Data}} for the event payload.
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func Prompt(p string) Option {
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return func(o *Options) { o.Prompt = p }
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}
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// SystemPrompt sets the system instruction for the LLM.
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func SystemPrompt(p string) Option {
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return func(o *Options) { o.SystemPrompt = p }
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}
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// Provider sets the AI provider name.
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func Provider(name string) Option {
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return func(o *Options) { o.Provider = name }
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}
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// APIKey sets the API key for the AI provider.
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func APIKey(key string) Option {
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return func(o *Options) { o.APIKey = key }
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}
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// Model sets the model name.
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func Model(name string) Option {
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return func(o *Options) { o.Model = name }
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}
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// BaseURL sets the provider base URL.
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func BaseURL(url string) Option {
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return func(o *Options) { o.BaseURL = url }
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}
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// HistoryLimit sets the max messages per execution.
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func HistoryLimit(n int) Option {
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return func(o *Options) { o.HistoryLimit = n }
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}
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// OnResult sets a callback for each execution result.
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func OnResult(fn func(Result)) Option {
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return func(o *Options) { o.OnResult = fn }
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}
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// Agent makes the flow hand each event to a named registered agent over
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// RPC instead of running its own LLM step. The flow triggers; the agent
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// reasons (with its plan, delegate, memory, and guardrails).
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func Agent(name string) Option {
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return func(o *Options) { o.Agent = name }
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}
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// Steps sets the ordered steps of the flow. A flow with steps runs them
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// in order per event, checkpointing between each, instead of the
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// single-step prompt/agent behavior. Step names must be unique.
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func Steps(steps ...Step) Option {
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return func(o *Options) { o.Steps = steps }
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}
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// Retry sets the flow-level retry count applied to each step (0 = no
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// retry). A Step's own Retry field overrides this.
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func Retry(n int) Option {
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return func(o *Options) { o.Retry = n }
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}
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// WithCheckpoint sets the durability backend. With a checkpoint, a run is
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// persisted before and after each step and can be resumed after a crash.
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// Stepped flows default to a store-backed checkpoint; use this to swap it.
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func WithCheckpoint(c Checkpoint) Option {
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return func(o *Options) { o.Checkpoint = c }
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}
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// DeleteOnSuccess removes a run's checkpoint when it completes
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// successfully. Failed runs are always retained. Default: retain all.
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func DeleteOnSuccess() Option {
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return func(o *Options) { o.DeleteOnSuccess = true }
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}
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