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作者 SHA1 备注 提交日期
Asim Aslam 888dbbca4a Refactor AI tool handling and enhance CLI command documentation (#2920)
goreleaser / goreleaser (push) Has been cancelled
* refactor(ai): rename ToolSet to Tools, simplify wiring with WithTools

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.

* feat(cli): add per-interface commands (registry, broker, store, config)

Map go-micro's core interfaces onto the CLI so the framework's
building blocks are inspectable and manipulable from the terminal:

  micro registry list/get/watch       service discovery
  micro broker publish/subscribe      pub/sub messaging
  micro store read/write/delete/list  persistence
  micro config get/dump               dynamic config (from env)

Structured pluggably in cmd/micro/resource: each interface is one
file exposing a Command() func, all wired through a commandFuncs
slice in resource.go. Adding a new resource command is a single
file plus one slice entry. Shared printJSON/fail helpers keep
output and errors consistent across commands.

Each command's verbs mirror the interface methods. Output is JSON
for structured data, raw for single values. Update README and
getting-started with an "inspecting the framework" section.

* docs: update CLI README with all new commands

Add documentation for commands that were missing from the CLI README:
- micro new --template (crud, pubsub, api)
- micro api (standalone HTTP gateway)
- micro registry list/get/watch
- micro broker publish/subscribe
- micro store read/write/delete/list
- micro config get/dump
- micro chat (interactive LLM agent)
- micro flow run/exec (event-driven orchestration)
- micro mcp serve/list/test

Organized into sections: API Gateway, Inspecting the Framework
(registry, broker, store, config), and AI & Agents (chat, flow, mcp).

* refactor(ai): move History from caller to Request field

History is now pure state (no Generate method). Instead, pass it
via Request.History and call ai.Generate(ctx, model, req):

Before:
  hist := ai.NewHistory("system prompt", 50)
  resp, _ := hist.Generate(ctx, model, prompt, tools)

After:
  hist := ai.NewHistory(50)
  resp, _ := ai.Generate(ctx, model, &ai.Request{
      Prompt:       prompt,
      SystemPrompt: "system prompt",
      Tools:        tools,
      History:      hist,
  })

The model is always the thing you call. History is context you
pass in. ai.Generate() handles the bookkeeping: prepends
accumulated messages before the call, records the exchange after.

NewHistory no longer takes a system prompt (it belongs on the
Request, where it always did).

Update micro chat, ai/flow, and all blog posts/docs.

* refactor(ai): make History a plain message accumulator

History no longer has Generate or touches the model. It's just
Add/Messages/Reset/Len with truncation — a helper for building
Request.Messages across turns.

Before:
  hist := ai.NewHistory(50)
  resp, _ := ai.Generate(ctx, m, &ai.Request{History: hist, ...})

After:
  hist := ai.NewHistory(50)
  hist.Add("user", prompt)
  resp, _ := m.Generate(ctx, &ai.Request{Messages: hist.Messages(), ...})
  hist.Add("assistant", resp.Reply)

Remove History field from Request. Remove package-level
ai.Generate(ctx, model, req) wrapper — users call m.Generate()
directly, which is the interface method. History is a convenience
for accumulating messages, not a participant in generation.

Update micro chat, ai/flow, blog posts 9 and 10.

---------

Co-authored-by: Claude <noreply@anthropic.com>
2026-05-30 16:20:38 +01:00
Asim Aslam 86782e6d77 Add ImageModel interface and multi-turn conversation support (#2906)
* feat(ai): add ImageModel interface with Atlas Cloud and OpenAI support

Add ai.ImageModel interface for text-to-image generation alongside
the existing ai.Model for text. Uses the same options pattern
(WithAPIKey, WithBaseURL) and the same provider registration
system (RegisterImage/NewImage).

Implement GenerateImage for Atlas Cloud and OpenAI providers via
the OpenAI-compatible /v1/images/generations endpoint. Default
image model is gpt-image-1. Responses return images as URL,
base64, or both depending on the provider.

Update Atlas Cloud blog post and integration guide with image
generation examples. Update ai/README.md with ImageModel docs.

* fix(website): widen docs content by reducing layout max-width to 1100px

Remove the 800px max-width on .content (which left empty space on
the right) and reduce the overall .layout and footer from 1400px
to 1100px. With the 230px sidebar this gives ~830px of content
width — readable and fills the page properly on desktop.

* feat(ai): add History for multi-turn conversation state

Add ai.History — a lightweight message accumulator that tracks
user prompts, assistant replies, and tool call/result pairs
across turns. FIFO truncation when message count exceeds the
configured limit. System prompt is passed through on every
Generate call.

Wire History into micro chat so conversations are multi-turn by
default (limit 50 messages). Add 'reset' command to clear
history mid-session.

5 unit tests covering accumulation, truncation, reset, snapshot
isolation, and tool call recording.

---------

Co-authored-by: Claude <noreply@anthropic.com>
2026-05-28 14:44:46 +01:00