233 lines
7.9 KiB
Python
233 lines
7.9 KiB
Python
"""LLM provider presets used by Settings and the runtime AI provider bridge."""
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from __future__ import annotations
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from typing import Any
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import httpx
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MODELS_DEV_URL = "https://models.dev/api.json"
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OPENCODE_GO_MODELS_URL = "https://opencode.ai/zen/go/v1/models"
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class LLMProviderCatalogError(RuntimeError):
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"""The upstream catalog cannot supply a usable model list."""
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OPENCODE_GO_MODEL_PROVIDER_APIS = {
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"minimax-m2.7": "anthropic-messages",
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"minimax-m2.5": "anthropic-messages",
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}
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OPENCODE_GO_FALLBACK_MODELS = [
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"minimax-m2.7",
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"minimax-m2.5",
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"kimi-k2.6",
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"kimi-k2.5",
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"glm-5.1",
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"glm-5",
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"deepseek-v4-pro",
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"deepseek-v4-flash",
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"qwen3.6-plus",
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"qwen3.5-plus",
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"mimo-v2.5-pro",
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"mimo-v2.5",
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]
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FALLBACK_LLM_PROVIDER_PRESETS: dict[str, dict[str, Any]] = {
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"minimax": {
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"provider": "minimax",
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"label": "MiniMax",
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"provider_api": "anthropic-messages",
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"base_url": "https://api.minimaxi.com/anthropic",
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"model": "MiniMax-M2.7",
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"models": ["MiniMax-M2.7", "MiniMax-M2.7-highspeed", "MiniMax-M2.5", "MiniMax-M2"],
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"api_key_env": "MINIMAX_API_KEY",
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"source": "fallback",
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},
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"openai": {
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"provider": "openai",
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"label": "OpenAI",
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"provider_api": "openai-completions",
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"base_url": "https://api.openai.com/v1",
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"model": "gpt-5.1",
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"models": ["gpt-5.1", "gpt-5.1-codex", "gpt-4.1", "gpt-4o"],
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"api_key_env": "OPENAI_API_KEY",
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"source": "fallback",
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},
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"anthropic": {
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"provider": "anthropic",
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"label": "Anthropic",
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"provider_api": "anthropic-messages",
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"base_url": "https://api.anthropic.com/v1",
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"model": "claude-sonnet-4-6",
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"models": ["claude-sonnet-4-6", "claude-opus-4-5", "claude-3-5-haiku-20241022"],
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"api_key_env": "ANTHROPIC_API_KEY",
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"source": "fallback",
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},
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"deepseek": {
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"provider": "deepseek",
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"label": "DeepSeek",
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"provider_api": "openai-completions",
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"base_url": "https://api.deepseek.com/v1",
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"model": "deepseek-chat",
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"models": ["deepseek-chat", "deepseek-reasoner"],
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"api_key_env": "DEEPSEEK_API_KEY",
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"source": "fallback",
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},
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"alibaba": {
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"provider": "alibaba",
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"label": "Alibaba Qwen / DashScope",
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"provider_api": "openai-completions",
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"base_url": "https://dashscope.aliyuncs.com/compatible-mode/v1",
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"model": "qwen3-max",
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"models": ["qwen3-max", "qwen3.5-plus", "qwen-max", "qwen-plus"],
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"api_key_env": "DASHSCOPE_API_KEY",
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"source": "fallback",
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},
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"moonshotai": {
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"provider": "moonshotai",
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"label": "Moonshot AI / Kimi",
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"provider_api": "openai-completions",
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"base_url": "https://api.moonshot.ai/v1",
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"model": "kimi-k2.5",
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"models": ["kimi-k2.5", "kimi-k2-thinking", "kimi-k2-turbo-preview"],
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"api_key_env": "MOONSHOT_API_KEY",
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"source": "fallback",
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},
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"openrouter": {
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"provider": "openrouter",
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"label": "OpenRouter",
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"provider_api": "openai-completions",
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"base_url": "https://openrouter.ai/api/v1",
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"model": "openai/gpt-5.1",
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"models": ["openai/gpt-5.1", "anthropic/claude-sonnet-4.5", "qwen/qwen3-max"],
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"api_key_env": "OPENROUTER_API_KEY",
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"source": "fallback",
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},
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"opencode-go": {
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"provider": "opencode-go",
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"label": "OpenCode Go",
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"provider_api": "openai-completions",
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"base_url": "https://opencode.ai/zen/go/v1",
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"model": "glm-5.1",
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"models": OPENCODE_GO_FALLBACK_MODELS,
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"model_provider_apis": OPENCODE_GO_MODEL_PROVIDER_APIS,
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"api_key_env": "OPENCODE_GO_API_KEY",
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"source": "fallback",
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},
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"ollama": {
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"provider": "ollama",
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"label": "Ollama Local",
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"provider_api": "ollama-generate",
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"base_url": "http://127.0.0.1:11434",
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"model": "qwen2.5:7b",
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"models": ["qwen2.5:7b", "llama3.1:8b", "mistral:7b"],
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"api_key_env": "",
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"source": "fallback",
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},
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}
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MODELS_DEV_PROVIDER_KEYS = {
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"minimax": "minimax",
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"openai": "openai",
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"anthropic": "anthropic",
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"deepseek": "deepseek",
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"alibaba": "alibaba",
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"moonshotai": "moonshotai",
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"openrouter": "openrouter",
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}
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def list_fallback_llm_provider_presets() -> list[dict[str, Any]]:
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return [dict(value) for value in FALLBACK_LLM_PROVIDER_PRESETS.values()]
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def get_fallback_llm_provider_preset(provider: str) -> dict[str, Any]:
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key = provider.strip().lower()
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if key not in FALLBACK_LLM_PROVIDER_PRESETS:
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raise ValueError(f"Unsupported LLM provider preset: {provider}")
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return dict(FALLBACK_LLM_PROVIDER_PRESETS[key])
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def _opencode_go_model_provider_apis(model_ids: list[str]) -> dict[str, str]:
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return {
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model_id: OPENCODE_GO_MODEL_PROVIDER_APIS.get(model_id, "openai-completions")
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for model_id in model_ids
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}
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async def refresh_llm_provider_preset(provider: str, api_key: str | None = None) -> dict[str, Any]:
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fallback = get_fallback_llm_provider_preset(provider)
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if fallback["provider"] == "opencode-go":
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headers = {"User-Agent": "Planet/1.0"}
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if api_key:
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headers["Authorization"] = f"Bearer {api_key}"
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async with httpx.AsyncClient(timeout=15.0, follow_redirects=True) as client:
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response = await client.get(
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OPENCODE_GO_MODELS_URL,
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headers=headers,
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)
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response.raise_for_status()
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payload = response.json()
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data = payload.get("data") if isinstance(payload, dict) else []
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model_ids = [
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str(item.get("id"))
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for item in data
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if isinstance(item, dict) and item.get("id")
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]
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if not model_ids:
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raise LLMProviderCatalogError("The provider returned an empty model catalog")
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return {
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**fallback,
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"model": fallback["model"] if fallback["model"] in model_ids else model_ids[0],
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"models": model_ids,
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"model_provider_apis": _opencode_go_model_provider_apis(model_ids),
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"source": OPENCODE_GO_MODELS_URL,
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}
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models_dev_key = MODELS_DEV_PROVIDER_KEYS.get(fallback["provider"])
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if not models_dev_key:
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raise LLMProviderCatalogError("Live catalog refresh is unavailable for this provider")
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async with httpx.AsyncClient(timeout=15.0, follow_redirects=True) as client:
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response = await client.get(
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MODELS_DEV_URL,
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headers={"User-Agent": "Planet/1.0"},
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)
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response.raise_for_status()
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catalog = response.json()
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upstream = catalog.get(models_dev_key) if isinstance(catalog, dict) else None
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if not isinstance(upstream, dict):
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raise LLMProviderCatalogError("The provider is missing from the model catalog")
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upstream_models = upstream.get("models") if isinstance(upstream.get("models"), dict) else {}
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# Catalog insertion order is not release order; old entries can appear first.
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model_ids = sorted(
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(
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model_id
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for model_id, model in upstream_models.items()
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if model_id and isinstance(model, dict)
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),
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key=lambda model_id: (str(upstream_models[model_id].get("release_date") or ""), model_id),
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reverse=True,
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)
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if not model_ids:
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raise LLMProviderCatalogError("The provider returned an empty model catalog")
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base_url = upstream.get("api") or fallback["base_url"]
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if fallback["provider"] == "deepseek" and base_url == "https://api.deepseek.com":
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base_url = "https://api.deepseek.com/v1"
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refreshed = {
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**fallback,
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"label": upstream.get("name") or fallback["label"],
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"base_url": base_url,
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"model": model_ids[0],
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"models": model_ids,
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"api_key_env": (upstream.get("env") or [fallback["api_key_env"]])[0],
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"source": MODELS_DEV_URL,
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}
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return refreshed
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