File size: 5,642 Bytes
fa1140b | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 | """anuma.ai ModelRegistry：模型目录（探测自 GET portal.anuma.ai/api/v1/curated-models）。
字段：id（catalog id，即上游 curated-models 的 id 如 ``kimi/kimi-k3``）/
name / owner（provider）/ upstream_id（Fireworks 格式 ``accounts/fireworks/models/<短名>``）。
⚠️ 列表为 2026-08-01 探测快照；上游增删模型时用 scripts/probe_catalog.py 重新生成。
"""
from __future__ import annotations
import re
from typing import Any
from app.upstream.base import ModelRegistry
__all__ = [
"DEFAULT_MODEL", "MODEL_CATALOG", "IMAGE_MODEL_CATALOG",
"normalize_image_model", "DefaultModelRegistry",
]
DEFAULT_MODEL = "openai/gpt-5.6-luna" # 上游未识别 model 时的回退模型（实测所见）
# 生图模型（2026-08-08 从 chat.anuma.ai HAR 抓取）：/v1/images 路由用。
# key = AnumaMediaMCP-anuma_create_image 工具 model 参数值；name = 对外展示名。
# 前缀 * 为 GPT-5.6 Luna 生图实测可用模型；tier alias（auto/anuma-*）由上游按订阅分层。
IMAGE_MODEL_CATALOG: list[dict[str, Any]] = [
{"id": "gpt-image-2", "name": "GPT Image 2"},
{"id": "flux-2-pro", "name": "Flux 2 Pro"},
{"id": "flux-2-klein-4b", "name": "Flux 2 Klein 4B"},
{"id": "grok-imagine", "name": "Grok Imagine"},
{"id": "nano-banana", "name": "Nano Banana"},
{"id": "nano-banana-pro", "name": "Nano Banana Pro"},
{"id": "nano-banana-2", "name": "Nano Banana 2"},
{"id": "anuma-flash", "name": "Anuma Flash (tier alias)"},
{"id": "anuma-pro", "name": "Anuma Pro (tier alias)"},
{"id": "anuma-flash-private", "name": "Anuma Flash Private (tier alias)"},
{"id": "anuma-pro-private", "name": "Anuma Pro Private (tier alias)"},
]
_IMAGE_BY_KEY: dict[str, dict[str, Any]] = {}
for _im in IMAGE_MODEL_CATALOG:
_IMAGE_BY_KEY[_im["id"]] = _im
_IMAGE_BY_KEY[_im["name"].lower()] = _im
def normalize_image_model(model: str | None) -> str | None:
"""客户端传入的 gen 图片模型 → 上游 tool 参数值；空/未知 → None（由客户端容错）。"""
if not model:
return None
if model in _IMAGE_BY_KEY:
return _IMAGE_BY_KEY[model]["id"]
low = model.lower()
if low in _IMAGE_BY_KEY:
return _IMAGE_BY_KEY[low]["id"]
norm = re.sub(r"[^a-z0-9]", "", low)
for m in IMAGE_MODEL_CATALOG:
if re.sub(r"[^a-z0-9]", "", m["id"]) == norm:
return m["id"]
return None
# 探测自 /api/v1/curated-models（active=true 的 text/vision 模型为主）
MODEL_CATALOG: list[dict[str, Any]] = [
{"id": "inclusionai/ling-2.6-flash", "name": "Ling 2.6 Flash", "owner": "InclusionAI", "upstream_id": "accounts/fireworks/models/ling-2.6-flash"},
{"id": "kimi/kimi-k3", "name": "Kimi K3", "owner": "Kimi", "upstream_id": "accounts/fireworks/models/kimi-k3"},
{"id": "kimi/kimi-k2.7-code", "name": "Kimi K2.7 Code", "owner": "Kimi", "upstream_id": "accounts/fireworks/models/kimi-k2.7-code"},
{"id": "kimi/kimi-k2.6", "name": "Kimi 2.6", "owner": "Kimi", "upstream_id": "accounts/fireworks/models/kimi-k2.6"},
{"id": "openai/gpt-5.6-sol", "name": "GPT 5.6 Sol", "owner": "OpenAI", "upstream_id": "accounts/fireworks/models/gpt-5.6-sol"},
{"id": "openai/gpt-5.6-terra", "name": "GPT 5.6 Terra", "owner": "OpenAI", "upstream_id": "accounts/fireworks/models/gpt-5.6-terra"},
{"id": "openai/gpt-5.6-luna", "name": "GPT 5.6 Luna", "owner": "OpenAI", "upstream_id": "accounts/fireworks/models/gpt-5.6-luna"},
{"id": "anthropic/claude-sonnet-5", "name": "Claude Sonnet 5", "owner": "Anthropic", "upstream_id": "accounts/fireworks/models/claude-sonnet-5"},
{"id": "anthropic/claude-opus-5", "name": "Claude Opus 5", "owner": "Anthropic", "upstream_id": "accounts/fireworks/models/claude-opus-5"},
{"id": "openai/gpt-5.5", "name": "GPT 5.5", "owner": "OpenAI", "upstream_id": "accounts/fireworks/models/gpt-5.5"},
{"id": "qwen/qwen-3.7-plus", "name": "Qwen 3.7 Plus", "owner": "Qwen", "upstream_id": "accounts/fireworks/models/qwen-3.7-plus"},
{"id": "qwen/qwen-3.6-plus", "name": "Qwen 3.6 Plus", "owner": "Qwen", "upstream_id": "accounts/fireworks/models/qwen-3.6-plus"},
{"id": "glm/glm-5.2", "name": "GLM 5.2", "owner": "Zhipu", "upstream_id": "accounts/fireworks/models/glm-5.2"},
{"id": "minimax/minimax-m3", "name": "MiniMax M3", "owner": "MiniMax", "upstream_id": "accounts/fireworks/models/minimax-m3"},
{"id": "minimax/minimax-m2.7", "name": "Minimax 2.7", "owner": "MiniMax", "upstream_id": "accounts/fireworks/models/minimax-m2.7"},
]
_BY_KEY: dict[str, dict[str, Any]] = {}
for _m in MODEL_CATALOG:
_BY_KEY[_m["id"]] = _m
_BY_KEY[_m["name"].lower()] = _m
class DefaultModelRegistry(ModelRegistry):
def catalog(self) -> list[dict[str, Any]]:
return list(MODEL_CATALOG)
def normalize(self, model: str | None) -> str:
"""客户端传入的 model → catalog id；空或未知 → 默认。匹配：精确 id > 显示名(小写) > 模糊。"""
if not model:
return DEFAULT_MODEL
if model in _BY_KEY:
return _BY_KEY[model]["id"]
low = model.lower()
if low in _BY_KEY:
return _BY_KEY[low]["id"]
norm = re.sub(r"[^a-z0-9]", "", low)
for m in MODEL_CATALOG:
if (re.sub(r"[^a-z0-9]", "", m["id"]) == norm
or re.sub(r"[^a-z0-9]", "", m["name"].lower()) == norm):
return m["id"]
return DEFAULT_MODEL
def upstream_id_for(self, model_id: str) -> str | None:
m = _BY_KEY.get(model_id)
return m["upstream_id"] if m else None
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