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- 删除全部 Python 源码 (src/) 及 Alembic 迁移脚本，归档至 _deprecated_py_src/ - 重构 Rust gateway ai_pipeline: 拆分 planner/finalize 模块，新增 contracts/adaptation 层 - 重组 handlers 模块为 admin/public/proxy/internal/shared 子模块结构 - 新增 executor 模块，引入 Rust 原生数据库迁移 (aether-data/migrations) - 简化 CI/Docker 构建流程，移除 base image 二级构建，统一为单一 app image - 移除 Python 相关基础设施文件 (entrypoint.sh, gunicorn_conf.py, Dockerfile.base)
249 lines
7.1 KiB
Python
249 lines
7.1 KiB
Python
"""预设模型管理模块
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为不支持自动获取模型的反代提供商（如 Kiro、Codex）提供统一的预设模型管理。
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使用方式：
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1. 在 PRESET_MODELS 中定义各 provider_type 的预设模型列表
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2. 在 plugin.py 中调用 create_preset_models_fetcher() 创建 fetcher 函数
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3. 将 fetcher 注册到 UpstreamModelsFetcherRegistry
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"""
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from __future__ import annotations
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from collections.abc import Awaitable, Callable
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from typing import Any
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# Fetcher 函数签名：与 UpstreamModelsFetcherRegistry 中的 _ModelsFetcher 保持一致
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# (ctx, timeout_seconds) -> (models, errors, has_success, upstream_metadata)
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ModelsFetcherFunc = Callable[
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[Any, float],
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Awaitable[tuple[list[dict], list[str], bool, dict[str, Any] | None]],
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]
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# ---------------------------------------------------------------------------
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# 预设模型定义
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# ---------------------------------------------------------------------------
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# 各 provider_type 对应的预设模型列表
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# 格式: provider_type -> list of model dicts
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PRESET_MODELS: dict[str, list[dict[str, Any]]] = {
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# GeminiCLI (Google Cloud Code / Gemini CLI OAuth upstream)
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"gemini_cli": [
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{
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"id": "gemini-2.5-pro",
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"object": "model",
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"owned_by": "google",
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"display_name": "Gemini 2.5 Pro",
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"api_format": "gemini:cli",
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},
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{
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"id": "gemini-2.5-flash",
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"object": "model",
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"owned_by": "google",
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"display_name": "Gemini 2.5 Flash",
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"api_format": "gemini:cli",
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},
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{
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"id": "gemini-3-pro-preview",
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"object": "model",
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"owned_by": "google",
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"display_name": "Gemini 3 Pro Preview",
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"api_format": "gemini:cli",
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},
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{
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"id": "gemini-3-flash-preview",
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"object": "model",
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"owned_by": "google",
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"display_name": "Gemini 3 Flash Preview",
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"api_format": "gemini:cli",
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},
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{
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"id": "gemini-3.1-pro-preview",
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"object": "model",
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"owned_by": "google",
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"display_name": "Gemini 3.1 Pro Preview",
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"api_format": "gemini:cli",
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},
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],
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# Kiro (Claude CLI 反代)
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"kiro": [
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{
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"id": "claude-sonnet-4.5",
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"object": "model",
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"owned_by": "anthropic",
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"display_name": "Claude Sonnet 4.5",
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},
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{
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"id": "claude-sonnet-4.6",
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"object": "model",
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"owned_by": "anthropic",
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"display_name": "Claude Sonnet 4.6",
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},
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{
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"id": "claude-opus-4.5",
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"object": "model",
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"owned_by": "anthropic",
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"display_name": "Claude Opus 4.5",
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},
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{
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"id": "claude-opus-4.6",
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"object": "model",
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"owned_by": "anthropic",
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"display_name": "Claude Opus 4.6",
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},
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{
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"id": "claude-haiku-4.5",
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"object": "model",
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"owned_by": "anthropic",
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"display_name": "Claude Haiku 4.5",
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},
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],
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# Claude Code (Claude CLI OAuth 反代)
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"claude_code": [
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{
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"id": "claude-opus-4-5-20251101",
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"object": "model",
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"owned_by": "anthropic",
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"display_name": "Claude Opus 4.5",
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},
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{
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"id": "claude-opus-4-6",
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"object": "model",
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"owned_by": "anthropic",
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"display_name": "Claude Opus 4.6",
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},
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{
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"id": "claude-sonnet-4-6",
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"object": "model",
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"owned_by": "anthropic",
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"display_name": "Claude Sonnet 4.6",
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},
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{
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"id": "claude-sonnet-4-5-20250929",
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"object": "model",
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"owned_by": "anthropic",
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"display_name": "Claude Sonnet 4.5",
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},
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{
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"id": "claude-haiku-4-5-20251001",
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"object": "model",
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"owned_by": "anthropic",
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"display_name": "Claude Haiku 4.5",
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},
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],
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# Codex (OpenAI CLI 反代)
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"codex": [
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{
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"id": "gpt-5",
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"object": "model",
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"owned_by": "openai",
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"display_name": "GPT-5",
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},
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{
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"id": "gpt-5-codex",
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"object": "model",
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"owned_by": "openai",
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"display_name": "GPT-5 Codex",
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},
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{
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"id": "gpt-5-codex-mini",
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"object": "model",
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"owned_by": "openai",
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"display_name": "GPT-5 Codex Mini",
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},
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{
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"id": "gpt-5.1",
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"object": "model",
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"owned_by": "openai",
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"display_name": "GPT-5.1",
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},
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{
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"id": "gpt-5.1-codex",
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"object": "model",
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"owned_by": "openai",
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"display_name": "GPT-5.1 Codex",
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},
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{
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"id": "gpt-5.1-codex-mini",
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"object": "model",
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"owned_by": "openai",
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"display_name": "GPT-5.1 Codex Mini",
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},
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{
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"id": "gpt-5.1-codex-max",
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"object": "model",
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"owned_by": "openai",
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"display_name": "GPT-5.1 Codex Max",
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},
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{
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"id": "gpt-5.2",
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"object": "model",
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"owned_by": "openai",
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"display_name": "GPT-5.2",
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},
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{
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"id": "gpt-5.2-codex",
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"object": "model",
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"owned_by": "openai",
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"display_name": "GPT-5.2 Codex",
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},
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{
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"id": "gpt-5.3-codex",
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"object": "model",
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"owned_by": "openai",
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"display_name": "GPT-5.3 Codex",
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},
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{
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"id": "gpt-5.4",
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"object": "model",
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"owned_by": "openai",
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"display_name": "GPT-5.4",
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},
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],
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}
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# ---------------------------------------------------------------------------
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# Fetcher 工厂函数
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# ---------------------------------------------------------------------------
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def get_preset_models(provider_type: str) -> list[dict[str, Any]]:
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"""获取指定 provider_type 的预设模型列表。"""
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return list(PRESET_MODELS.get(provider_type.lower(), []))
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def create_preset_models_fetcher(
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provider_type: str,
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) -> ModelsFetcherFunc:
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"""创建一个返回预设模型列表的 fetcher 函数。
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Args:
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provider_type: 提供商类型（如 "kiro", "codex"）
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Returns:
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符合 UpstreamModelsFetcherRegistry 签名的 async fetcher 函数
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"""
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models = get_preset_models(provider_type)
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async def fetch_preset_models(
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_ctx: Any,
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_timeout_seconds: float,
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) -> tuple[list[dict], list[str], bool, dict[str, Any] | None]:
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"""Return preset model catalog.
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This provider does not expose a /v1/models endpoint, so we skip the
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HTTP call entirely and return a hardcoded list.
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"""
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return list(models), [], True, None
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return fetch_preset_models
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__all__ = [
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"ModelsFetcherFunc",
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"PRESET_MODELS",
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"create_preset_models_fetcher",
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"get_preset_models",
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]
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