文件历史

7 次代码提交

作者 SHA1 备注 提交日期
Asim Aslam 153f178db6 docs: refresh coherence changelog (#4021)
Co-authored-by: Codex <codex@openai.com>
2026-07-05 09:10:28 +01:00
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>
2026-06-18 11:55:35 +01:00
Asim Aslam 550033dcce Optimize image formats and fix lease re-registration issue (#2959)
* perf: convert generated PNGs to optimized JPEGs (12MB -> 1.5MB)

The landing and docs loaded 18 AI-generated PNGs at 0.5-1MB each. They're
1200x800 RGB illustrations with no transparency, so they recompress ~8x
as progressive JPEG (quality 82) with no visible loss. Convert all,
update every reference (.png -> .jpg), and drop the originals (including
the unused hero.png). Generated images: 12.3MB -> 1.5MB.

* fix(registry/etcd): re-register when a lease silently expires (#2956)

The keepalive rework (long-lived KeepAlive instead of KeepAliveOnce)
moved lease renewal entirely onto the keepalive goroutine; the 30s
periodic Register now skips on the 'unchanged' check. The goroutine only
reacted to the keepalive channel closing, so a lease that expired
server-side without a prompt channel close (e.g. a partition that
outlasted the 90s TTL) left the node de-registered from etcd while the
cache still believed it was registered — and nothing re-registered it.
That is the hidden-failure mode reported in #2956.

React to a non-positive TTL keepalive response the same as a channel
close: drop the cached lease/hash so the next Register performs a full
re-registration. Extract the loop into keepAliveLoop and unit-test the
TTL-expired, channel-closed, and healthy paths (no etcd required).

---------

Co-authored-by: Claude <noreply@anthropic.com>
2026-06-10 08:24:49 +01:00
Asim Aslam 1bc886fa82 Introduce Agent abstraction and integrate with chat router (#2939)
* docs: Agent interface design sketch

Proposes Agent as a top-level abstraction alongside Service in the
micro package. Agent manages services — scoped tools, system prompt,
conversation memory, registry-discoverable.

Design only, no implementation.

https://claude.ai/code/session_01QTp4SshuVmLAvvEGJe4TJd

* feat: Agent as a first-class abstraction

Introduce micro.NewAgent() alongside micro.New() — Agent is to
intelligence what Service is to capability.

Agent interface:
- Chat(ctx, message) (*Response, error) — core interaction method
- Run() — registers in registry, subscribes to broker, blocks
- Stop() — graceful shutdown
- Scoped tools — only sees endpoints of its assigned services
- Persistent memory — conversation history stored in store
- Agent-to-agent — communication via broker topics

Top-level API:
  agent := micro.NewAgent("task-mgr",
      micro.AgentServices("task"),
      micro.AgentPrompt("You manage tasks."),
      micro.AgentProvider("anthropic"),
  )
  agent.Run()

https://claude.ai/code/session_01QTp4SshuVmLAvvEGJe4TJd

* feat: wire agents into chat router, add micro agent CLI, expose Flow

Three top-level abstractions:
  micro.New("task")              — Service (capability)
  micro.NewAgent("task-mgr")     — Agent (intelligence)
  micro.NewFlow("onboard-user")  — Flow (event-driven orchestration)

micro chat as router:
- Discovers agents from registry on startup
- Single agent: routes directly
- Multiple agents: LLM classifies intent, dispatches to right agent
  via route_to_agent tool
- No agents: falls back to current direct-service behaviour
- Banner shows discovered agents

micro agent CLI:
- micro agent list — shows registered agents and their services
- micro agent describe <name> — shows agent details from registry

https://claude.ai/code/session_01QTp4SshuVmLAvvEGJe4TJd

* feat: move flow to top level, update docs for three abstractions

Package structure now consistent:
  service/   — Service (capability)
  agent/     — Agent (intelligence)
  flow/      — Flow (event-driven orchestration)

ai/flow/ kept as backward-compatible re-export.

Updated across all surfaces:
- CLAUDE.md: added agent/ and flow/ to project structure
- README: added "Building Agents" section with NewAgent() examples,
  updated features table (Agents, Flows, Chat router), CLI table
  (agent list, agent describe), docs links
- Website: features grid shows Services, Agents, Flows as the three
  pillars alongside generation, MCP, and pluggable architecture
- micro.go: Flow imported from top-level flow/ package

https://claude.ai/code/session_01QTp4SshuVmLAvvEGJe4TJd

* docs: rewrite getting-started, fix ai-integration import paths

Getting started now covers all three abstractions:
- Service (write handlers, micro run, templates)
- Agent (micro.NewAgent, scoped tools, memory, CLI)
- Flow (event-driven LLM orchestration)
Leads with prompt-based generation, then manual service creation.

ai-integration.md: fixed flow import path from go-micro.dev/v5/ai/flow
to go-micro.dev/v5/flow, updated stack diagram to show agent/flow/chat.

https://claude.ai/code/session_01QTp4SshuVmLAvvEGJe4TJd

* blog: Introducing micro.NewAgent()

Post 16 — announces Agent as a first-class abstraction. Shows the
API (NewAgent, AgentServices, AgentPrompt, AgentProvider), scoped
tools, persistent memory, multi-service agents, multi-agent systems,
and the three-abstraction comparison table (Service/Agent/Flow).

https://claude.ai/code/session_01QTp4SshuVmLAvvEGJe4TJd

* feat: fix agent registration, blog post 16

Agent registration:
- Add node with address so mDNS can discover agents
- Store type and services in node metadata (mDNS requirement)
- Connect broker before subscribing, non-fatal if broker unavailable
- Print registration confirmation on Run()

Agent/chat discovery:
- Check both service-level and node-level metadata for type=agent
  (mDNS stores metadata on nodes, not services)

Blog post 16: "Introducing micro.NewAgent()" — announces the Agent
abstraction with code examples, comparison table, multi-agent patterns.

Tested end-to-end: micro run → micro agent list discovers the agent →
micro chat routes to it → agent calls service endpoints.

https://claude.ai/code/session_01QTp4SshuVmLAvvEGJe4TJd

* feat: agents are proper services with RPC Chat endpoint

Refactored agent to use server.Server instead of fake registry entries.
An agent now:
- Creates a real RPC server with server.Name(agentName)
- Registers an Agent.Chat handler callable via standard RPC
- Sets server metadata type=agent, services=x,y for discovery
- No more fake addresses or broker hacks

micro chat calls agents via RPC (client.Call) instead of creating
local agent instances. The registry stays clean — agents are real
services with real endpoints.

Removed broker dependency from agent options. Agent-to-agent
communication is just RPC like everything else.

https://claude.ai/code/session_01QTp4SshuVmLAvvEGJe4TJd

* feat: agent uses proto-defined RPC interface

Added agent/proto/agent.proto with Agent service definition:
  rpc Chat(ChatRequest) returns (ChatResponse)

Agent now implements the generated AgentHandler interface and
registers via pb.RegisterAgentHandler. The Chat endpoint is a
standard proto-based RPC callable by any go-micro client.

Renamed the programmatic API from Chat() to Ask() to avoid
collision with the proto handler method name.

micro chat calls agents via standard RPC with JSON-encoded
request/response — no special types needed on the caller side.

https://claude.ai/code/session_01QTp4SshuVmLAvvEGJe4TJd

* feat: generate agent alongside services, update all docs

micro run --prompt now generates an agent binary that manages all
the generated services. The agent reads MICRO_AI_PROVIDER and
MICRO_AI_API_KEY from the environment. micro run propagates these
when started with --prompt.

Run banner shows services and agents separately.

Updated README, getting-started guide, and landing page to show
the complete flow: generate → services + agent start → micro chat
routes to agent → agent orchestrates services.

https://claude.ai/code/session_01QTp4SshuVmLAvvEGJe4TJd

---------

Co-authored-by: Claude <noreply@anthropic.com>
2026-06-05 10:25:14 +01:00
Asim Aslam c4b4cbef25 refactor(ai): rename ToolSet to Tools, simplify wiring with WithTools (#2917)
Move tool discovery/execution fully into the ai package as ai.Tools
(formerly ai.ToolSet), and simplify the usage model:

- NewTools(reg, ai.ToolClient(c)) takes the execution client as an
  option instead of threading it through Handler(c) per call
- New ai.WithTools(tools) option wires the tool handler into a model
  in one call, replacing ai.WithToolHandler(set.Handler(c))
- ai.DiscoverTools(reg) for one-shot discovery

Before:
  set := ai.NewToolSet(reg)
  list, _ := set.Discover()
  m := ai.New(p, ai.WithToolHandler(set.Handler(client)))

After:
  tools := ai.NewTools(reg, ai.ToolClient(client))
  list, _ := tools.Discover()
  m := ai.New(p, ai.WithTools(tools))

Update ai/flow, micro chat, README, ai integration doc, Atlas Cloud
guide, and blog posts 3/8/9/10.

Co-authored-by: Claude <noreply@anthropic.com>
2026-05-30 14:21:35 +01:00
Asim Aslam 88aa0cc666 Update logo, add AI integration docs, and enhance CLI features (#2915)
* feat: update Go Micro logo to interconnected nodes design

Replace the text-on-blue-square logo with a modern icon: three
teal nodes connected in a triangle, representing distributed
systems. Generated via Atlas Cloud. Clean at all sizes — works
as GitHub avatar, favicon, and nav bar icon.

* feat: new logo, AI integration architecture doc, and landing page CTA

Update logo to triangle-nodes icon + "Go Micro" text wordmark.
Save icon-only variant for favicon/avatar use.

Add docs/ai-integration.md — a single page that explains how the
AI stack fits together: services → registry → MCP gateway →
ai/tools → ai.Model → micro chat. Layer-by-layer with code
examples, provider table, and "what you don't need" section.

Add AI Integration to docs sidebar navigation (after Getting
Started). Update the landing page AI section with a direct CTA
button linking to the new doc.

* fix: restore original logo and add border-radius to all renders

Revert logo to original. Add border-radius: 8px to the logo img
in the landing page nav, docs layout nav, and blog layout nav
so the square logo renders with rounded corners everywhere.
Remove unused icon.png.

* feat(ai): add ai/flow package and micro flow CLI

Add ai/flow — event-driven LLM orchestration for go-micro. A Flow
subscribes to a broker topic, discovers services as tools, and
feeds each event into an LLM that decides which RPCs to call.

Key types:
- flow.New(name, opts...) creates a flow with trigger topic,
  prompt template, provider config
- flow.Register(registry, broker, client) wires it into a service
- flow.Execute(ctx, data) runs the flow once (for testing/CLI)
- flow.Results() returns execution history

Add micro flow CLI with two subcommands:
- micro flow run: subscribe to a topic and react to events
- micro flow exec: one-shot execution with inline data

Both output JSON results with flow name, prompt, tool calls,
reply, answer, duration, and errors.

Example:
  micro flow run --trigger events.user.created \
    --prompt "New user: {{.Data}}. Send welcome email." \
    --provider anthropic

  micro flow exec --prompt "List all users" --provider anthropic

* docs: update flows blog post with ai/flow package and CLI examples

Add "Update: We Built It" section to blog/9 showing the ai/flow
package API, CLI usage for both event-driven and one-shot modes,
and what it does/doesn't do. Links the conceptual discussion to
the shipped implementation.

* feat(cli): add micro api gateway command, clarify run vs server

Add 'micro api' — a standalone lightweight HTTP-to-RPC gateway:
- POST /{service}/{endpoint} proxies to RPC calls
- GET / lists all services and endpoints
- GET /{service} describes a service
- GET /health returns ok
- Supports Micro-Endpoint header for endpoint routing
- No dashboard, no auth, no hot reload — just the proxy

Update help text to clarify the three gateway modes:
- micro api: bare HTTP-to-RPC proxy
- micro run: development mode (hot reload + gateway + agent playground)
- micro server: production mode (dashboard + auth + JWT)

* docs: update README, getting started, and AI integration for all new features

Update the development workflow table in both README and getting
started to include all CLI commands: micro new --template,
micro api, micro chat, micro flow, micro call.

Getting started:
- Add CRUD template example to quick start
- Update workflow table with 8 stages
- Add AI Integration, MCP, and gRPC Interop to Next Steps

README:
- Add template flag to quick start example
- Update workflow table
- Reorder User Guides with AI Integration prominent

AI Integration doc:
- Update stack diagram to include micro api and ai/flow
- Add micro flow section with Go API and CLI examples
- Add micro api section
- Renumber layers (now 8 instead of 7)

---------

Co-authored-by: Claude <noreply@anthropic.com>
2026-05-29 22:49:37 +01:00
Asim Aslam 985621f4b4 AI integration updates (#2911)
* feat: update Go Micro logo to interconnected nodes design

Replace the text-on-blue-square logo with a modern icon: three
teal nodes connected in a triangle, representing distributed
systems. Generated via Atlas Cloud. Clean at all sizes — works
as GitHub avatar, favicon, and nav bar icon.

* feat: new logo, AI integration architecture doc, and landing page CTA

Update logo to triangle-nodes icon + "Go Micro" text wordmark.
Save icon-only variant for favicon/avatar use.

Add docs/ai-integration.md — a single page that explains how the
AI stack fits together: services → registry → MCP gateway →
ai/tools → ai.Model → micro chat. Layer-by-layer with code
examples, provider table, and "what you don't need" section.

Add AI Integration to docs sidebar navigation (after Getting
Started). Update the landing page AI section with a direct CTA
button linking to the new doc.

* fix: restore original logo and add border-radius to all renders

Revert logo to original. Add border-radius: 8px to the logo img
in the landing page nav, docs layout nav, and blog layout nav
so the square logo renders with rounded corners everywhere.
Remove unused icon.png.

---------

Co-authored-by: Claude <noreply@anthropic.com>
2026-05-29 16:30:23 +01:00