codex/devrel-3530
5 次代码提交
| 作者 | SHA1 | 备注 | 提交日期 | |
|---|---|---|---|---|
 Asim Aslam
|
48e05385c7 |
Add agent human input pause resume (#3281)
Co-authored-by: Codex <codex@openai.com> |
||
|
Asim Aslam
|
c7657f73f4 |
Refactor agent plan storage, update docs, and release v6 (#2977)
goreleaser / goreleaser (push) Has been cancelled
* test(harness): read agent plan from the scoped store
The store-scoping change moved an agent's plan from the default table
key agent/{name}/plan to its own table (database "agent", table {name},
key "plan"). The plan-delegate harness tests still read the old key and
failed with 'not found'; read through store.Scope(mem, "agent", name)
like the agent does.
* docs: orient agents-first across README, landing, and docs overview
Lead with agents (then services and flows), surface MCP + A2A as the
interop story, and frame agents as services. Landing hero and feature
grid reordered agents-first with an A2A gateway card.
* v6: module path go-micro.dev/v6, TLS secure by default, NewService
Cut v6. Three breaking changes, bundled so the major bump is paid once:
- Module path go-micro.dev/v5 -> go-micro.dev/v6 across all imports + go.mod.
- TLS verification on by default (was off). MICRO_TLS_SECURE removed;
MICRO_TLS_INSECURE=true opts out for self-signed/dev.
- micro.NewService(name, opts...) is the canonical service constructor,
symmetric with NewAgent/NewFlow; micro.New kept as a deprecated alias;
the old name-less NewService(opts...) removed. Generators emit NewService.
Also ports the JWT auth token provider in-module (go-micro.dev/v6/auth/jwt/token
on golang-jwt/jwt/v5), dropping the v5-pinned github.com/micro/plugins/v5/auth/jwt
and the deprecated dgrijalva/jwt-go.
Docs/README/landing updated to v6 and @latest; v5->v6 migration guide added;
CHANGELOG cut as [6.0.0]. Blog posts left at their historical versions.
---------
Co-authored-by: Claude <noreply@anthropic.com>
|
||
|
Asim Aslam
|
9fdcc24cce |
Implement durable execution and scoped state management for flows (#2972)
* 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>
|
||
|
Asim Aslam
|
5e5d253abd |
feat(agent): tool-execution wrappers via WrapTool (#2969)
Restructure ai.ToolHandler to the structured, ctx-carrying shape that
mirrors a go-micro RPC handler:
func(ctx context.Context, call ai.ToolCall) ai.ToolResult
This reuses the existing ToolCall (with its correlation ID) and
ToolResult types instead of the flat (name, input)->(any, string)
signature, and adds ToolCall.Scan for typed argument access.
Add ai.ToolWrapper and the agent option WrapTool / micro.AgentWrapTool —
the tool-side analogue of client.CallWrapper and server.HandlerWrapper.
Reframe the built-in guardrails (MaxSteps, LoopLimit, ApproveTool) as
composed wrappers around a base handler; developer wrappers compose
outermost, so they observe every call and result, including refusals.
Update all provider call sites, the MCP server and chat handlers, the
integration harnesses, and docs to the new signature.
Co-authored-by: Claude <noreply@anthropic.com>
|
||
|
Asim Aslam
|
cb33decd97 |
Add built-in plan and delegate tools for agents with examples (#2949)
* feat: add plan and delegate as built-in agent tools Give agents two self-capabilities, expressed as plain tools wired into the existing tool handler — no harness or graph, consistent with "services are the only abstraction": - plan: record/update an ordered plan, persisted to store-backed memory and surfaced in the system prompt on later turns (externalized planning). - delegate: hand a self-contained subtask to another agent. Delegate-first — if the target names a registered agent it is called via RPC; otherwise a focused ephemeral sub-agent is created with agent.New + Ask in a fresh, isolated context (loads/persists no history, no built-in tools, so it cannot re-delegate). Both are added automatically to any non-ephemeral agent, so existing micro.NewAgent services and micro chat routing get them for free. Tests are hermetic (memory store + memory registry). * feat: add agent-plan-delegate example and document plan/delegate - examples/agent-plan-delegate: coordinator that plans multi-step work, creates tasks with its own tools, and delegates notification to a separate registered comms agent over RPC. - integration tests driving the full Ask loop through a fake provider: plan tool exposure + persistence, ephemeral delegation with isolated context, delegate-first RPC routing to a registered agent. - docs: README (Building Agents + features + examples), AGENT_DESIGN (Built-in Capabilities), agent-patterns guide (Pattern 9), CLAUDE.md. * docs: blog post and guide for plan & delegate - blog/17: "Plan & Delegate: Deep Agents in Go" — what the feature is, how plan and delegate work, and a runnable getting-started path. - guides/plan-delegate: reference guide with the smallest-agent snippet, plan/delegate semantics, and the multi-agent example; linked in nav. - example: auto-detect provider/key from common env vars (ANTHROPIC_API_KEY, OPENAI_API_KEY, ...) so 'export KEY && go run main.go' just works. - onboarding: getting-started paths now include go mod init / go get and a clone-and-run path, so a reader can actually run it from a cold start. * refactor: reframe plan/delegate blog and clean up sub-agent construction - blog/17 retitled "Agents That Plan and Delegate" and reframed around intent (plan = state intent, delegate = direct it), positioned as the next beat after blog 15/16 and tied to the existing store + agent RPC rather than re-announcing them. "Deep agents" now a single in-passing nod, matching how blog 14 references LangChain. - agent: add unexported newEphemeral constructor for sub-agents instead of type-asserting the public Agent interface to set an internal field; matches the options-only construction idiom used elsewhere. * feat: expose plan & delegate in the micro chat fallback Add agent.Builtins(opts...) — returns the built-in tools plus a handler, so the plan/delegate capabilities can be wired into a tool loop that isn't a running Agent. micro chat's direct-service fallback now reuses it (single source of truth, no duplicated handler logic), so planning and delegation are available there too, not just for registered agents. Adds a test for the accessor; notes CLI availability in the guide. --------- Co-authored-by: Claude <noreply@anthropic.com> |