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feat: expand MiniMax provider registry #762

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137 changes: 135 additions & 2 deletions backend/app/services/llm/client.py
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Original file line number Diff line number Diff line change
Expand Up @@ -1896,6 +1896,28 @@ async def close(self) -> None:
# Factory and Utilities
# ============================================================================

@dataclass(frozen=True)
class ProviderModelSpec:
"""Model metadata exposed through the provider manifest."""

model_id: str
context_window: int | None = None
pricing_usd_per_million_tokens: dict[str, float | None] = field(default_factory=dict)
pricing_tiers_usd_per_million_tokens: tuple[dict[str, Any], ...] = ()
input_modalities: tuple[str, ...] = ()
thinking: tuple[str, ...] = ()


@dataclass(frozen=True)
class ProviderEndpoint:
"""Regional protocol endpoints exposed through the provider manifest."""

region: str
openai_base_url: str
anthropic_base_url: str
docs_root: str | None = None


@dataclass(frozen=True)
class ProviderSpec:
"""Provider registry entry."""
Expand All @@ -1907,6 +1929,9 @@ class ProviderSpec:
supports_tool_choice: bool = True
default_max_tokens: int = 4096
model_max_tokens: dict[str, int] = field(default_factory=dict)
default_model_id: str | None = None
models: tuple[ProviderModelSpec, ...] = ()
endpoints: tuple[ProviderEndpoint, ...] = ()


# Provider aliases accepted for compatibility
Expand Down Expand Up @@ -1971,8 +1996,83 @@ class ProviderSpec:
provider="minimax",
display_name="MiniMax",
protocol="openai_compatible",
default_base_url="https://api.minimaxi.com/v1",
default_base_url="https://api.minimax.io/v1",
default_max_tokens=16384,
default_model_id="MiniMax-M3",
models=(
ProviderModelSpec(
model_id="MiniMax-M3",
context_window=1000000,
pricing_usd_per_million_tokens={
"input": 0.3,
"output": 1.2,
"cache_read": 0.06,
"cache_write": None,
},
pricing_tiers_usd_per_million_tokens=(
{
"service_tier": "standard",
"input_tokens_lte": 512000,
"input": 0.3,
"output": 1.2,
"cache_read": 0.06,
"cache_write": None,
},
{
"service_tier": "standard",
"input_tokens_gt": 512000,
"input": 0.6,
"output": 2.4,
"cache_read": 0.12,
"cache_write": None,
},
{
"service_tier": "priority",
"input_tokens_lte": 512000,
"input": 0.45,
"output": 1.8,
"cache_read": 0.09,
"cache_write": None,
},
{
"service_tier": "priority",
"input_tokens_gt": 512000,
"input": 0.9,
"output": 3.6,
"cache_read": 0.18,
"cache_write": None,
},
),
input_modalities=("text", "image", "video"),
thinking=("adaptive", "disabled"),
),
ProviderModelSpec(
model_id="MiniMax-M2.7",
context_window=204800,
pricing_usd_per_million_tokens={
"input": 0.3,
"output": 1.2,
"cache_read": 0.06,
"cache_write": 0.375,
},
input_modalities=("text",),
thinking=("always_on",),
),
),
endpoints=(
ProviderEndpoint(
region="global_en",
openai_base_url="https://api.minimax.io/v1",
anthropic_base_url="https://api.minimax.io/anthropic",
docs_root="https://platform.minimax.io/docs",
),
ProviderEndpoint(
region="cn_zh",
openai_base_url="https://api.minimaxi.com/v1",
anthropic_base_url="https://api.minimaxi.com/anthropic",
docs_root="https://platform.minimaxi.com/docs",
),
),
),
"openrouter": ProviderSpec(
provider="openrouter",
Expand Down Expand Up @@ -2065,6 +2165,28 @@ def get_provider_manifest() -> list[dict[str, Any]]:
"default_max_tokens": spec.default_max_tokens,
"model_max_tokens": spec.model_max_tokens,
"aliases": [k for k, v in PROVIDER_ALIASES.items() if v == spec.provider],
"default_model_id": spec.default_model_id,
"model_ids": [model.model_id for model in spec.models],
"models": [
{
"model_id": model.model_id,
"context_window": model.context_window,
"pricing_usd_per_million_tokens": model.pricing_usd_per_million_tokens,
"pricing_tiers_usd_per_million_tokens": list(model.pricing_tiers_usd_per_million_tokens),
"input_modalities": list(model.input_modalities),
"thinking": list(model.thinking),
}
for model in spec.models
],
"endpoints": [
{
"region": endpoint.region,
"openai_base_url": endpoint.openai_base_url,
"anthropic_base_url": endpoint.anthropic_base_url,
"docs_root": endpoint.docs_root,
}
for endpoint in spec.endpoints
],
})
return out

Expand Down Expand Up @@ -2146,6 +2268,17 @@ def get_max_tokens(provider: str, model: str | None = None, max_output_tokens: i
return MAX_TOKENS_BY_PROVIDER.get(normalize_provider(provider), 4096)


def _uses_anthropic_endpoint(spec: ProviderSpec | None, base_url: str | None) -> bool:
"""Detect a configured native Anthropic-compatible endpoint for a provider."""
if not spec or not base_url:
return False
normalized_base_url = base_url.rstrip("/")
return any(
normalized_base_url == endpoint.anthropic_base_url.rstrip("/")
for endpoint in spec.endpoints
Comment on lines +2275 to +2278

@chatgpt-codex-connector chatgpt-codex-connector Bot Jul 15, 2026

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P2 Badge Normalize MiniMax Anthropic URLs before client selection

When an admin enters the full MiniMax Anthropic endpoint ending in /v1/messages (or /v1), this exact comparison returns false even though AnthropicClient._normalize_base_url() already supports those forms. The model then falls through to OpenAICompatibleClient, which appends /chat/completions and sends the wrong protocol to a URL like .../anthropic/v1/messages/chat/completions; normalize the candidate URL the same way before matching, or accept the documented full endpoint variants.

Useful? React with 👍 / 👎.

)


def create_llm_client(
provider: str,
api_key: str,
Expand Down Expand Up @@ -2175,7 +2308,7 @@ def create_llm_client(
final_base_url = get_provider_base_url(normalized_provider, base_url)

# Create appropriate client
if spec and spec.protocol == "anthropic":
if spec and (spec.protocol == "anthropic" or _uses_anthropic_endpoint(spec, final_base_url)):
return AnthropicClient(
api_key=api_key,
base_url=final_base_url,
Expand Down
56 changes: 56 additions & 0 deletions backend/tests/test_llm_provider_registry.py
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Original file line number Diff line number Diff line change
@@ -0,0 +1,56 @@
from app.services.llm.client import (
AnthropicClient,
OpenAICompatibleClient,
PROVIDER_REGISTRY,
create_llm_client,
get_provider_manifest,
)


def test_minimax_registry_contains_target_models_and_endpoints():
spec = PROVIDER_REGISTRY["minimax"]

assert spec.default_model_id == "MiniMax-M3"
assert [model.model_id for model in spec.models] == ["MiniMax-M3", "MiniMax-M2.7"]
assert {endpoint.region for endpoint in spec.endpoints} == {"global_en", "cn_zh"}
assert {
(endpoint.openai_base_url, endpoint.anthropic_base_url)
for endpoint in spec.endpoints
} == {
("https://api.minimax.io/v1", "https://api.minimax.io/anthropic"),
("https://api.minimaxi.com/v1", "https://api.minimaxi.com/anthropic"),
}
assert all(endpoint.anthropic_base_url.endswith("/anthropic") for endpoint in spec.endpoints)


def test_minimax_manifest_exposes_model_metadata_and_endpoint_choices():
manifest = next(item for item in get_provider_manifest() if item["provider"] == "minimax")

assert manifest["model_ids"] == ["MiniMax-M3", "MiniMax-M2.7"]
assert manifest["models"][0]["context_window"] == 1000000
assert manifest["models"][0]["input_modalities"] == ["text", "image", "video"]
assert manifest["models"][1]["thinking"] == ["always_on"]
assert {endpoint["region"] for endpoint in manifest["endpoints"]} == {"global_en", "cn_zh"}


def test_minimax_anthropic_base_uses_anthropic_client():
client = create_llm_client(
provider="minimax",
api_key="test-key",
model="MiniMax-M3",
base_url="https://api.minimax.io/anthropic",
)

assert isinstance(client, AnthropicClient)
assert client._normalize_base_url() == "https://api.minimax.io/anthropic"


def test_minimax_openai_base_uses_openai_compatible_client():
client = create_llm_client(
provider="minimax",
api_key="test-key",
model="MiniMax-M3",
base_url="https://api.minimaxi.com/v1",
)

assert isinstance(client, OpenAICompatibleClient)
69 changes: 63 additions & 6 deletions frontend/src/pages/enterprise-settings/tabs/LlmTab.tsx
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Original file line number Diff line number Diff line change
Expand Up @@ -30,14 +30,47 @@ interface LLMProviderSpec {
default_base_url?: string | null;
supports_tool_choice: boolean;
default_max_tokens: number;
default_model_id?: string | null;
model_ids?: string[];
endpoints?: LLMProviderEndpoint[];
}

interface LLMProviderEndpoint {
region: string;
openai_base_url: string;
anthropic_base_url: string;
docs_root?: string | null;
}

const FALLBACK_LLM_PROVIDERS: LLMProviderSpec[] = [
{ provider: 'anthropic', display_name: 'Anthropic', protocol: 'anthropic', default_base_url: 'https://api.anthropic.com', supports_tool_choice: false, default_max_tokens: 8192 },
{ provider: 'openai', display_name: 'OpenAI', protocol: 'openai_compatible', default_base_url: 'https://api.openai.com/v1', supports_tool_choice: true, default_max_tokens: 16384 },
{ provider: 'azure', display_name: 'Azure OpenAI', protocol: 'openai_compatible', default_base_url: '', supports_tool_choice: true, default_max_tokens: 16384 },
{ provider: 'deepseek', display_name: 'DeepSeek', protocol: 'openai_compatible', default_base_url: 'https://api.deepseek.com/v1', supports_tool_choice: true, default_max_tokens: 8192 },
{ provider: 'minimax', display_name: 'MiniMax', protocol: 'openai_compatible', default_base_url: 'https://api.minimaxi.com/v1', supports_tool_choice: true, default_max_tokens: 16384 },
{
provider: 'minimax',
display_name: 'MiniMax',
protocol: 'openai_compatible',
default_base_url: 'https://api.minimax.io/v1',
supports_tool_choice: true,
default_max_tokens: 16384,
default_model_id: 'MiniMax-M3',
model_ids: ['MiniMax-M3', 'MiniMax-M2.7'],
endpoints: [
{
region: 'global_en',
openai_base_url: 'https://api.minimax.io/v1',
anthropic_base_url: 'https://api.minimax.io/anthropic',
docs_root: 'https://platform.minimax.io/docs',
},
{
region: 'cn_zh',
openai_base_url: 'https://api.minimaxi.com/v1',
anthropic_base_url: 'https://api.minimaxi.com/anthropic',
docs_root: 'https://platform.minimaxi.com/docs',
},
],
},
{ provider: 'qwen', display_name: 'Qwen (DashScope)', protocol: 'openai_compatible', default_base_url: 'https://dashscope.aliyuncs.com/compatible-mode/v1', supports_tool_choice: true, default_max_tokens: 8192 },
{ provider: 'zhipu', display_name: 'Zhipu', protocol: 'openai_compatible', default_base_url: 'https://open.bigmodel.cn/api/paas/v4', supports_tool_choice: true, default_max_tokens: 8192 },
{ provider: 'baidu', display_name: 'Baidu (Qianfan)', protocol: 'openai_compatible', default_base_url: 'https://qianfan.baidubce.com/v2', supports_tool_choice: false, default_max_tokens: 4096 },
Expand Down Expand Up @@ -91,6 +124,14 @@ export default function LlmTab({ selectedTenantId }: LlmTabProps) {
queryFn: () => fetchJson<LLMProviderSpec[]>('/enterprise/llm-providers'),
});
const providerOptions = providerSpecs.length > 0 ? providerSpecs : FALLBACK_LLM_PROVIDERS;
const activeProviderSpec = providerOptions.find((p) => p.provider === modelForm.provider);
const modelOptions = activeProviderSpec?.model_ids || [];
const endpointOptions = Array.from(new Set(
(activeProviderSpec?.endpoints || []).flatMap((endpoint) => [
endpoint.openai_base_url,
endpoint.anthropic_base_url,
]),
));

const addModel = useMutation({
mutationFn: (data: any) => fetchJson(`/enterprise/llm-models${selectedTenantId ? `?tenant_id=${selectedTenantId}` : ''}`, { method: 'POST', body: JSON.stringify(data) }),
Expand Down Expand Up @@ -248,7 +289,11 @@ export default function LlmTab({ selectedTenantId }: LlmTabProps) {
const updates: any = { provider: newProvider };
updates.base_url = spec?.default_base_url || '';
if (spec) updates.max_output_tokens = String(spec.default_max_tokens);
setModelForm(f => ({ ...f, ...updates }));
setModelForm(f => ({
...f,
...updates,
model: f.model || spec?.default_model_id || '',
}));
}}>
{providerOptions.map((p) => (
<option key={p.provider} value={p.provider}>{p.display_name}</option>
Expand All @@ -257,15 +302,21 @@ export default function LlmTab({ selectedTenantId }: LlmTabProps) {
</div>
<div className="form-group">
<label className="form-label">{t('enterprise.llm.model')}</label>
<input className="form-input" placeholder={t('enterprise.llm.modelPlaceholder', 'e.g. claude-sonnet-4-20250514')} value={modelForm.model} onChange={e => setModelForm({ ...modelForm, model: e.target.value })} />
<input className="form-input" list="llm-model-options" placeholder={t('enterprise.llm.modelPlaceholder', 'e.g. claude-sonnet-4-20250514')} value={modelForm.model} onChange={e => setModelForm({ ...modelForm, model: e.target.value })} />
<datalist id="llm-model-options">
{modelOptions.map((modelId) => <option key={modelId} value={modelId} />)}
</datalist>
</div>
<div className="form-group">
<label className="form-label">{t('enterprise.llm.label')}</label>
<input className="form-input" placeholder={t('enterprise.llm.labelPlaceholder')} value={modelForm.label} onChange={e => setModelForm({ ...modelForm, label: e.target.value })} />
</div>
<div className="form-group">
<label className="form-label">{t('enterprise.llm.baseUrl')}</label>
<input className="form-input" placeholder={t('enterprise.llm.baseUrlPlaceholder')} value={modelForm.base_url} onChange={e => setModelForm({ ...modelForm, base_url: e.target.value })} />
<input className="form-input" list="llm-endpoint-options" placeholder={t('enterprise.llm.baseUrlPlaceholder')} value={modelForm.base_url} onChange={e => setModelForm({ ...modelForm, base_url: e.target.value })} />
<datalist id="llm-endpoint-options">
{endpointOptions.map((endpoint) => <option key={endpoint} value={endpoint} />)}
</datalist>
</div>
<div className="form-group" style={{ gridColumn: 'span 2' }}>
<label className="form-label">{t('enterprise.llm.apiKey')}</label>
Expand Down Expand Up @@ -334,15 +385,21 @@ export default function LlmTab({ selectedTenantId }: LlmTabProps) {
</div>
<div className="form-group">
<label className="form-label">{t('enterprise.llm.model')}</label>
<input className="form-input" placeholder={t('enterprise.llm.modelPlaceholder', 'e.g. claude-sonnet-4-20250514')} value={modelForm.model} onChange={e => setModelForm({ ...modelForm, model: e.target.value })} />
<input className="form-input" list="llm-model-options" placeholder={t('enterprise.llm.modelPlaceholder', 'e.g. claude-sonnet-4-20250514')} value={modelForm.model} onChange={e => setModelForm({ ...modelForm, model: e.target.value })} />
<datalist id="llm-model-options">
{modelOptions.map((modelId) => <option key={modelId} value={modelId} />)}
</datalist>
</div>
<div className="form-group">
<label className="form-label">{t('enterprise.llm.label')}</label>
<input className="form-input" placeholder={t('enterprise.llm.labelPlaceholder')} value={modelForm.label} onChange={e => setModelForm({ ...modelForm, label: e.target.value })} />
</div>
<div className="form-group">
<label className="form-label">{t('enterprise.llm.baseUrl')}</label>
<input className="form-input" placeholder={t('enterprise.llm.baseUrlPlaceholder')} value={modelForm.base_url} onChange={e => setModelForm({ ...modelForm, base_url: e.target.value })} />
<input className="form-input" list="llm-endpoint-options" placeholder={t('enterprise.llm.baseUrlPlaceholder')} value={modelForm.base_url} onChange={e => setModelForm({ ...modelForm, base_url: e.target.value })} />
<datalist id="llm-endpoint-options">
{endpointOptions.map((endpoint) => <option key={endpoint} value={endpoint} />)}
</datalist>
</div>
<div className="form-group" style={{ gridColumn: 'span 2' }}>
<label className="form-label">{t('enterprise.llm.apiKey')}</label>
Expand Down