GET /providers/models

GET http://localhost:8000/providers/models

{
  "openai": [
    {
      "id": "gpt-5-nano-2025-08-07",
      "name": "gpt-5-nano-2025-08-07",
      "tier": "small",
      "context_window": 128000,
      "cost_per_1k_prompt_tokens": 0.0001,
      "cost_per_1k_completion_tokens": 0.0004,
      "supports_tools": true,
      "supports_streaming": true,
      "available": true
    }
  ],
  "anthropic": [
    {
      "id": "claude-sonnet-4-5-20250929",
      "name": "claude-sonnet-4-5-20250929",
      "tier": "medium",
      "context_window": 200000,
      "cost_per_1k_prompt_tokens": 0.003,
      "cost_per_1k_completion_tokens": 0.015,
      "supports_tools": true,
      "supports_streaming": true,
      "available": true
    }
  ]
}

curl http://localhost:8000/providers/models | jq

# 仅小型模型
curl "http://localhost:8000/providers/models?tier=small" | jq

# 仅大型模型
curl "http://localhost:8000/providers/models?tier=large" | jq

import httpx

# 获取所有模型
response = httpx.get("http://localhost:8000/providers/models")
models = response.json()

# 打印 OpenAI 模型
for model in models.get("openai", []):
    print(f"{model['id']} - {model['tier']} - ${model['cost_per_1k_prompt_tokens']:.4f}/1K")

# 过滤小型层级
response = httpx.get("http://localhost:8000/providers/models?tier=small")
small_models = response.json()

model_catalog:
  openai:
    gpt-5-nano-2025-08-07:
      model_id: gpt-5-nano-2025-08-07
      tier: small
      context_window: 128000
      max_tokens: 4096
      supports_functions: true
      supports_streaming: true

pricing:
  models:
    openai:
      gpt-5-nano-2025-08-07:
        input_per_1k: 0.0001
        output_per_1k: 0.0004

curl http://localhost:8000/providers/models | jq 'keys'
# ["anthropic", "openai", "google", "xai", ...]

curl http://localhost:8000/providers/models | \
  jq '.openai[] | {id, input: .cost_per_1k_prompt_tokens, output: .cost_per_1k_completion_tokens}'

# 如果提供商返回空数组，可能缺少 API 密钥
curl http://localhost:8000/providers/models | jq '.anthropic | length'

const response = await fetch('http://localhost:8000/providers/models?tier=small');
const models = await response.json();

// 填充下拉列表
Object.entries(models).forEach(([provider, modelList]) => {
  modelList.forEach(model => {
    dropdown.add(new Option(`${provider}: ${model.id}`, model.id));
  });
});

# 特定阶段覆盖
COMPLEXITY_MODEL_ID=gpt-5-mini-2025-08-07
DECOMPOSITION_MODEL_ID=gpt-5-mini-2025-08-07
DEFAULT_MODEL_TIER=small