* atlascloud: env-selectable chat model; run conformance on a stronger model
The daily provider-conformance harness fails 4/5 harnesses on Atlas Cloud —
its default chat model answers agent/tool-use conformance prompts
conversationally instead of performing the task. Atlas is currently the only
provider with a key configured, so the whole live run is red.
Make the Atlas Cloud provider honor an ATLASCLOUD_MODEL env override (falling
back to the existing default), and set it in the harness workflow to a
stronger tool-use model (Qwen3, overridable via an Actions variable). No
change to the default for normal use.
* atlascloud: use minimaxai/minimax-m3 for conformance model
---------
Co-authored-by: Claude <noreply@anthropic.com>
Streaming is implemented now (v6.3.3); the old test expected
ErrStreamingUnsupported and failed. Replace it with a real SSE streaming
test (httptest) that also asserts stream_options.include_usage and the
final usage chunk.
* ai/atlascloud: surface token usage on streams
Request stream_options.include_usage and return the final usage chunk
as a Response with Usage set, so streaming callers can record usage.
* ai/openai: surface token usage on streams
Request stream_options.include_usage and return the final usage chunk
as a Response with Usage set, so streaming callers can record usage.
* ai: add WithMaxTokens option
Let callers cap response length; providers send max_tokens when set
(anthropic keeps its 8192 default otherwise).
* ai: add WithMaxTokens option
Let callers cap response length; providers send max_tokens when set
(anthropic keeps its 8192 default otherwise).
* ai: add WithMaxTokens option
Let callers cap response length; providers send max_tokens when set
(anthropic keeps its 8192 default otherwise).
* ai: add WithMaxTokens option
Let callers cap response length; providers send max_tokens when set
(anthropic keeps its 8192 default otherwise).
* ai/atlascloud: thread Request.Messages into the request
Fold conversation history (req.Messages) between the system prompt and
the final user prompt so multi-turn context reaches the model.
Refs #3292
* ai/openai: thread Request.Messages into the request
Fold conversation history (req.Messages) between the system prompt and
the final user prompt so multi-turn context reaches the model.
Refs #3292
* ai/anthropic: thread Request.Messages into the request
Fold conversation history (req.Messages) between the system prompt and
the final user prompt so multi-turn context reaches the model.
Refs #3292
* docs: compare Go Micro with Google ADK in the comparison guide
Adds a 'vs Agent Frameworks (Google ADK)' section: ADK builds an agent,
Go Micro builds the distributed system the agent lives in (agents are
services in the mesh). Covers the category difference, a feature table,
when to choose each, and MCP/A2A interoperability.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01CmdEY7pYmV5zzwCjNJ4ykL
* docs: replace ADK comparison slogan with concrete explanation
State plainly what each tool provides (ADK builds an agent process; Go Micro
builds the surrounding service mesh) instead of marketing phrasing.
* lint: apply golangci-lint autofixes; exclude ST1003 and demo errcheck
Mechanical, behaviour-preserving fixes applied by 'golangci-lint run --fix':
gofmt, misspell (US spelling), usestdlibvars (http.Method*/Status*), unconvert,
and the auto-fixable staticcheck simplifications (QF*, S1017/S1019/S1023/S1039).
Config: exclude ST1003 (remaining offenders are exported API renames, e.g.
web.Id, which would break compatibility) and skip errcheck for examples/ and
internal/harness/ (demo code where fire-and-forget is intentional).
Build and test compilation verified.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01CmdEY7pYmV5zzwCjNJ4ykL
* lint: WIP cleanup checkpoint (errcheck config + partial fixes)
Checkpoint of an in-progress golangci-lint cleanup (background pass). Builds
cleanly; lint is not yet zero. Follow-up commit will complete the cleanup and
switch CI to a blocking full-tree lint.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01CmdEY7pYmV5zzwCjNJ4ykL
---------
Co-authored-by: Claude <noreply@anthropic.com>
* 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>
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>
* feat(website): redesign docs and blog layouts, add blog header images
Redesign both layouts to match the new landing page:
- Consistent nav bar with logo, Docs, Blog, GitHub, Reference, Home
- Consistent footer with copyright and links
- CSS custom properties for theming
- Updated typography, spacing, and code block styling
- Active sidebar link highlighting in docs
- Dark mode support preserved
Generate 4 blog header images via Atlas Cloud:
- blog-deploy.png for post 1 (micro deploy)
- blog-mcp.png for posts 2, 3, 7 (MCP-related)
- blog-agents-demo.png for post 4 (agents demo)
- blog-dx.png for post 5 (DX cleanup)
- Reuse data-model.png for post 6 (model package)
All 7 existing blog posts now have header images.
* fix(website): prevent horizontal scroll on mobile landing page
Add overflow-x: hidden on html and body. Set max-width: 100% and
height: auto on all section and two-col images. Add overflow:
hidden to .two-col grid. Constrain hero pre with max-width and
overflow-x. Reduce font sizes and padding at mobile breakpoint.
* feat(website): add images to remaining core doc pages
Generate 5 more images via Atlas Cloud for docs:
- registry.png: service discovery diagram
- broker.png: pub/sub message broker pattern
- transport.png: multi-transport layers (HTTP, gRPC, NATS)
- config.png: dynamic configuration from multiple sources
- observability.png: monitoring dashboard with metrics/traces
Add images to registry.md, broker.md, transport.md, config.md,
observability.md, and architecture.md. All 11 main doc pages
now have header images.
* feat: add sponsor logos to landing page, README images, and flows blog post
Add Anthropic and Atlas Cloud sponsor logos to the landing page
with links to their respective blog posts. Logos display at 0.7
opacity with hover effect.
Add architecture and MCP agent images to the GitHub README for
the Overview and MCP sections.
Write blog post 9: "From Chat to Flows" — explores the concept
of LLM-powered service orchestration. Compares micro chat's
interactive model with persistent event-driven flows, shows how
the existing building blocks (ai/tools, History, broker) could
compose into a flow engine, discusses tradeoffs vs traditional
orchestration (Step Functions, Temporal), and includes a working
15-line code example. Explicitly positions it as a concept for
community feedback, not an announcement.
* feat(website): add animated hero video to landing page
Generate a 6-second hero video via Atlas Cloud's image-to-video
API (gemini-omni-flash). Shows the microservices network diagram
animating with data flowing between nodes.
Replace the static hero image with an autoplay muted looping
video element. Falls back to the static image via poster
attribute and img fallback for browsers without video support.
* feat(ai): add VideoModel interface with Atlas Cloud provider
Add ai.VideoModel interface for video generation alongside Model
and ImageModel. Supports text-to-video and image-to-video via
VideoRequest with prompt, reference images, duration, aspect
ratio, and resolution fields.
Implement GenerateVideo for Atlas Cloud using their async API:
POST /api/v1/model/generateVideo → poll /api/v1/model/prediction.
Default model is gemini-omni-flash image-to-video. Polls every
5 seconds until completion or context cancellation.
Register Atlas Cloud as a video provider via ai.RegisterVideo.
Add 3 tests: registration, no-key error, compile-time interface
check. Update ai/README.md with VideoModel docs.
The ai package now covers all three modalities:
- Model (text) — 7 providers
- ImageModel (image) — 2 providers (Atlas Cloud, OpenAI)
- VideoModel (video) — 1 provider (Atlas Cloud)
---------
Co-authored-by: Claude <noreply@anthropic.com>
* feat(cli): add CRUD, pub/sub, and API gateway templates for micro new
Add --template flag to 'micro new' with three preset templates:
- crud: CRUD service with Create/Read/Update/Delete/List, in-memory
store with sync.RWMutex, UUID generation, pagination, and doc
comments with @example tags for MCP tool discovery.
- pubsub: Event-driven service with Publish/Stats RPCs and a
Subscribe method that hooks into the broker. Includes event
types with ID, type, source, data, and timestamp.
- api: API gateway service with Health and Endpoint RPCs, an
internal HTTP route table, and a response recorder for
proxying requests through RPC.
All templates include MCP-ready doc comments and work with
--no-mcp. The default template (no flag) is unchanged.
Usage:
micro new myservice --template crud
micro new myservice --template pubsub
micro new myservice --template api
* fix(ai): update Atlas Cloud provider to use actual API formats
Fix the Atlas Cloud image generation to use their real async API:
POST /api/v1/model/generateImage → poll /api/v1/model/prediction/{id}
instead of the OpenAI-compatible endpoint which doesn't exist.
Add Quality and OutputFormat fields to ai.ImageRequest for
provider-specific image parameters.
Update default text model from llama-3.3-70b (doesn't exist) to
deepseek-ai/DeepSeek-V3-0324 (their flagship model). Update
default image model to openai/gpt-image-2/text-to-image.
* feat(website): add AI-generated images to landing page, docs, and blog
Generate 5 images via Atlas Cloud's image API (gpt-image-2) to
elevate the website experience:
- hero.png: microservices network graph for landing page
- architecture.png: registry + broker architecture diagram
- mcp-agent.png: AI agent calling services via MCP
- developer-experience.png: terminal showing micro run/chat
- blog-atlas.png: Atlas Cloud unified API illustration
Add visual sections to the landing page with architecture,
MCP integration, and developer experience showcases. Add
images to docs index, MCP docs, and Atlas Cloud blog post.
All images resized to 1200px wide and optimized for web.
Generated using Atlas Cloud sponsor credits.
* feat(website): redesign landing page and add images to docs
Redesign the landing page from a centered card layout to a
full-width modern site with:
- Top navigation bar
- Hero section with gradient background and CTA buttons
- Full-width image showcase sections
- Two-column layout for architecture, MCP, and DX sections
- Feature grid with 6 capabilities
- Footer with links
- Responsive breakpoints for mobile
Generate 3 more images via Atlas Cloud for docs:
- getting-started.png for the getting started guide
- deployment.png for the deployment guide
- data-model.png for the data model docs
Add images to getting-started.md, model.md, and deployment.md.
---------
Co-authored-by: Claude <noreply@anthropic.com>
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.
Co-authored-by: Claude <noreply@anthropic.com>
* docs: add AI provider integration guide and Supported AI Providers section
Add a step-by-step guide for AI infrastructure companies to implement
ai.Model and contribute a provider to go-micro. Covers the full
lifecycle: skeleton, tool call handling, tests, registration, and PR
checklist.
Add a "Supported AI Providers" section to the project README that lists
current providers (Anthropic, OpenAI) in a table and links to the
integration guide with a call-to-action for new providers and sponsors.
Streamline the "Adding a New Provider" section in ai/README.md to point
to the new guide instead of duplicating a full code listing.
* feat(ai): add Atlas Cloud provider
Add ai/atlascloud implementing ai.Model for Atlas Cloud's
OpenAI-compatible chat completions API. Registers as "atlascloud"
with default model llama-3.3-70b and base URL
https://api.atlascloud.ai. Supports tool calling via ToolHandler.
Includes 7 unit tests covering registration, defaults, init,
generate-without-key, and stream-not-implemented.
Update the Supported AI Providers table in README.md and the
Supported Providers section in ai/README.md.
* fix: remove nonexistent Discord link from README
---------
Co-authored-by: Claude <noreply@anthropic.com>
Asim Aslam