hugocasaandClaude Opus 4.8
d9b080f57f
* feat(ai): add Azure AI Foundry as a native AI provider Adds `azure_foundry` as a new AIProvider variant wired through the AI chat (copilot) and AI agent flow steps. Foundry's chat completions API is OpenAI-compatible and uses Azure conventions (api-key header, Azure URL building), so it reuses the existing OpenAI-compatible query builder and proxy path via the shared `is_azure` helper (renamed from `is_azure_openai`). Backend (windmill-ai): - New `AzureFoundry` enum variant (serde `azure_foundry`) - `get_base_url` requires a resource base URL (like Azure OpenAI / Custom) - `is_azure()` covers Azure OpenAI + Foundry (api-key auth, Azure URL) - Added to OpenAI-compatible proxy support and HttpForward proxy mode - New proxy URL unit test Frontend (copilot): - New provider entry, completion config, model-token handling, streamed usage tracking, and reasoning registry (all model-id-gated, so a no-op for Foundry's non-OpenAI catalog) - Treated as a chat-completions provider, not the OpenAI Responses API OpenAPI: - `azure_foundry` added to AIProvider (openapi.yaml) and AIProviderKind (openflow.openapi.yaml); regenerated CLI guidance Note: the `azure_foundry` resource type (base_url + optional api_key) is hub-managed and must be published to the Windmill Hub separately. Fixes WIN-2122 Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> * fix(ai): add azure_foundry to copilot flow Zod provider enum The tracked copilot flow schema (openFlowZod.gen.ts and its openFlow.json source) still carried the old AIProvider enum, so validateFlowModules / validateSpecialFlowModule rejected AI-generated flow edits that create or update an aiagent module with provider kind "azure_foundry" before they could be saved. Add the value to both (preserving the generated single-line format) and a regression test over the flow-module validation path. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> * feat(ai): lead provider list with OpenAI, Anthropic, Google AI Reorder AI_PROVIDERS so the three primary direct providers come first. The AIProviderPicker renders the first three entries as quick-access buttons, so these become the defaults (previously OpenAI, Azure OpenAI, Azure Foundry); Azure OpenAI / Azure Foundry stay adjacent right after. No logic depends on provider order (only per-provider defaultModels[0] is read). Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> --------- Co-authored-by: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
System Prompts
This directory contains the single source of truth for AI system prompts used by both the frontend copilot and CLI guidance.
Structure
system_prompts/
├── base/ # Core instruction templates (manually written)
│ ├── flow-base.md # Shared OpenFlow structure guidance
│ └── flow-cli.md # CLI/local-agent workflow guidance for write-flow skill
├── languages/ # Language-specific instructions (manually written)
└── auto-generated/ # Auto-generated files (DO NOT EDIT)
├── sdks/ # SDK documentation
├── cli/ # CLI command documentation
├── prompts.ts # TypeScript exports
└── index.ts # Helper functions
Usage
Regenerating Prompts
When SDK methods or the OpenFlow schema change, run:
python system_prompts/generate.py
To also refresh the standalone skills in a Claude plugin checkout:
python system_prompts/generate.py --plugin-dir ~/windmill-claude-plugin
--plugin-dir accepts:
- the
windmill-claude-pluginrepo root - a plugin root such as
plugins/windmill - a direct
skills/directory
To regenerate the public docs repo (consumed by context7):
python system_prompts/generate.py --context7-dir ~/windmill-cli-docs
--context7-dir writes a fully-rendered snapshot (AGENTS.md,
cli-commands.md, skills/<name>/SKILL.md, README.md, manifest.json
with the Windmill version) with all template placeholders resolved —
suitable for ingestion by docs aggregators. In CI this runs from
.github/workflows/publish-cli-docs.yml on every release tag. The
generator refuses to wipe the target directory unless it's empty or has
a context7 marker (context7.json, manifest.json, or a
windmill-cli-docs git remote), so a typo can't delete unrelated files.
This will:
- Parse TypeScript and Python SDK files to extract function signatures
- Parse the OpenFlow YAML schema
- Parse the CLI commands
- Assemble complete prompts from markdown files
- Generate TypeScript exports in
auto-generated/ - Optionally refresh plugin-ready standalone
SKILL.mdfiles in the target directory
Scope
These system prompts contain ONLY:
- How to write Windmill scripts (language syntax, conventions, SDK usage)
- How to structure Windmill flows (OpenFlow schema, module types, data flow)
- Resource type handling, S3 operations
They DO NOT contain:
- Tool usage instructions (edit_code, set_flow_json, etc.)
- IDE/editor specific commands
- Testing tool invocations
Tool instructions are added separately by the frontend and CLI.
CLI-only workflow instructions live in base/flow-cli.md and are included in the
generated write-flow skill for wmill init. They are intentionally excluded
from the frontend flow chat prompt.
Integration
Frontend
Uses Vite path alias $system_prompts pointing to auto-generated/:
import { FLOW_GUIDANCE } from "$system_prompts/flow";
import { getLangContext } from "$system_prompts/languages";
CLI
Generates /cli/src/guidance/skills.gen.ts with embedded skill content for wmill init.
Editing Guidelines
- Edit markdown files in
base/,languages/ - Never edit files in
auto-generated/directly - After editing, run
generate.pyto update exports