feat(auth): add Alibaba DashScope provider

CHANGELOG.md

@@ -15,6 +15,7 @@ GitHub Releases page; `0.8.0` is the new starting line.
 
 ## Unreleased
 
+- **Alibaba DashScope provider and MiniMax M3 catalog.** `/login alibaba` now configures Alibaba Cloud Model Studio / DashScope Token Plan models, including workspace-compatible endpoints and native GLM thinking behavior. MiniMax API-key login now defaults to MiniMax M3 with its larger context and multimodal capabilities.
 - **Security review vulnerability intelligence.** `pythinker security-scan` can now parse dependency manifests, query OSV package advisories, look up CVE intelligence from NVD/EPSS/CISA KEV/GitHub/vendor feeds, and carry those leads into security-review prompts and reports as evidence-checked context.
 
 ## 0.34.0 (2026-06-03)

src/pythinker_code/auth/__init__.py

@@ -1,5 +1,6 @@
 from __future__ import annotations
 
+ALIBABA_PLATFORM_ID = "alibaba"
 PYTHINKER_CODE_PLATFORM_ID = "pythinker-code"
 OPENAI_API_PLATFORM_ID = "openai"
 OPENAI_CHATGPT_PLATFORM_ID = "openai-chatgpt"
@@ -14,6 +15,7 @@
 ZAI_PLATFORM_ID = "z-ai"
 
 __all__ = [
+    "ALIBABA_PLATFORM_ID",
     "ANTHROPIC_PLATFORM_ID",
     "DEEPSEEK_PLATFORM_ID",
     "LM_STUDIO_PLATFORM_ID",

src/pythinker_code/auth/alibaba.py

@@ -0,0 +1,298 @@
+from __future__ import annotations
+
+import os
+from collections.abc import AsyncIterator
+from dataclasses import dataclass
+from typing import Any, cast
+
+import aiohttp
+from pydantic import SecretStr
+
+from pythinker_code.auth import ALIBABA_PLATFORM_ID
+from pythinker_code.auth.oauth import OAuthEvent
+from pythinker_code.auth.platforms import managed_provider_key
+from pythinker_code.config import Config, LLMModel, LLMProvider, save_config
+from pythinker_code.llm import ModelCapability
+from pythinker_code.thinking import apply_login_thinking_defaults
+from pythinker_code.utils.aiohttp import new_client_session
+
+ALIBABA_BASE_URL = "https://dashscope-us.aliyuncs.com/compatible-mode/v1"
+ALIBABA_PROVIDER_KEY = managed_provider_key(ALIBABA_PLATFORM_ID)
+ALIBABA_DEFAULT_MODEL_ALIAS = f"{ALIBABA_PLATFORM_ID}/qwen3.6-plus"
+ALIBABA_MODEL_DISCOVERY_TIMEOUT = aiohttp.ClientTimeout(total=15, sock_connect=8, sock_read=10)
+
+
+@dataclass(frozen=True, slots=True)
+class AlibabaModel:
+    model_id: str
+    alias_suffix: str
+    display_name: str
+    provider_key: str = ALIBABA_PROVIDER_KEY
+    max_context_size: int = 131_072
+    capabilities: frozenset[ModelCapability] | None = None
+
+    @property
+    def alias(self) -> str:
+        return f"{ALIBABA_PLATFORM_ID}/{self.alias_suffix}"
+
+
+ALIBABA_MODELS: tuple[AlibabaModel, ...] = (
+    AlibabaModel(
+        model_id="qwen3.7-max",
+        alias_suffix="qwen3.7-max",
+        display_name="Qwen3.7 Max",
+        max_context_size=262_144,
+        capabilities=frozenset[ModelCapability]({"thinking"}),
+    ),
+    AlibabaModel(
+        model_id="qwen3.6-plus",
+        alias_suffix="qwen3.6-plus",
+        display_name="Qwen3.6 Plus",
+        max_context_size=1_000_000,
+        capabilities=frozenset[ModelCapability]({"thinking", "image_in"}),
+    ),
+    AlibabaModel(
+        model_id="qwen3.6-flash",
+        alias_suffix="qwen3.6-flash",
+        display_name="Qwen3.6 Flash",
+        max_context_size=1_000_000,
+        capabilities=frozenset[ModelCapability]({"thinking", "image_in"}),
+    ),
+    AlibabaModel(
+        model_id="deepseek-v4-pro",
+        alias_suffix="deepseek-v4-pro",
+        display_name="DeepSeek V4 Pro",
+        max_context_size=128_000,
+        capabilities=frozenset[ModelCapability]({"thinking"}),
+    ),
+    AlibabaModel(
+        model_id="deepseek-v4-flash",
+        alias_suffix="deepseek-v4-flash",
+        display_name="DeepSeek V4 Flash",
+        max_context_size=128_000,
+        capabilities=frozenset[ModelCapability]({"thinking"}),
+    ),
+    AlibabaModel(
+        model_id="deepseek-v3.2",
+        alias_suffix="deepseek-v3.2",
+        display_name="DeepSeek V3.2",
+        max_context_size=128_000,
+        capabilities=frozenset[ModelCapability]({"thinking"}),
+    ),
+    AlibabaModel(
+        model_id="kimi-k2.6",
+        alias_suffix="kimi-k2.6",
+        display_name="Kimi K2.6",
+        max_context_size=262_144,
+        capabilities=frozenset[ModelCapability]({"thinking", "image_in"}),
+    ),
+    AlibabaModel(
+        model_id="kimi-k2.5",
+        alias_suffix="kimi-k2.5",
+        display_name="Kimi K2.5",
+        max_context_size=262_144,
+        capabilities=frozenset[ModelCapability]({"thinking", "image_in"}),
+    ),
+    AlibabaModel(
+        model_id="glm-5.1",
+        alias_suffix="glm-5.1",
+        display_name="GLM-5.1",
+        max_context_size=262_144,
+        capabilities=frozenset[ModelCapability]({"always_thinking"}),
+    ),
+    AlibabaModel(
+        model_id="glm-5",
+        alias_suffix="glm-5",
+        display_name="GLM-5",
+        max_context_size=262_144,
+        capabilities=frozenset[ModelCapability]({"always_thinking"}),
+    ),
+    AlibabaModel(
+        model_id="MiniMax-M2.5",
+        alias_suffix="minimax-m2.5",
+        display_name="MiniMax M2.5",
+        max_context_size=204_800,
+        capabilities=frozenset[ModelCapability]({"thinking"}),
+    ),
+)
+
+
+def get_alibaba_api_key_from_env() -> str | None:
+    for env_var in ("DASHSCOPE_API_KEY", "ALIBABA_API_KEY"):
+        value = os.getenv(env_var)
+        if value and value.strip():
+            return value.strip()
+    return None
+
+
+def _normalize_alibaba_base_url(value: str) -> str:
+    base_url = value.strip().rstrip("/")
+    if not base_url:
+        return ALIBABA_BASE_URL
+    if "://" not in base_url:
+        base_url = f"https://{base_url}"
+    if base_url.endswith("/api/v1"):
+        return f"{base_url.removesuffix('/api/v1')}/compatible-mode/v1"
+    if base_url.endswith("/compatible-mode/v1"):
+        return base_url
+    return f"{base_url}/compatible-mode/v1"
+
+
+def get_alibaba_base_url_from_env() -> str:
+    for env_var in ("DASHSCOPE_BASE_URL", "ALIBABA_BASE_URL"):
+        value = os.getenv(env_var)
+        if value and value.strip():
+            return _normalize_alibaba_base_url(value)
+    return ALIBABA_BASE_URL
+
+
+def _apply_alibaba_config(
+    config: Config,
+    api_key: SecretStr,
+    models: tuple[AlibabaModel, ...] = ALIBABA_MODELS,
+) -> None:
+    config.providers[ALIBABA_PROVIDER_KEY] = LLMProvider(
+        type="openai_legacy",
+        base_url=get_alibaba_base_url_from_env(),
+        api_key=api_key,
+    )
+
+    provider_keys = {ALIBABA_PROVIDER_KEY}
+    for key, model in list(config.models.items()):
+        if model.provider in provider_keys:
+            del config.models[key]
+
+    for model in models:
+        config.models[model.alias] = LLMModel(
+            provider=model.provider_key,
+            model=model.model_id,
+            max_context_size=model.max_context_size,
+            capabilities=set(model.capabilities) if model.capabilities else None,
+            display_name=model.display_name,
+        )
+
+    fallback = next(
+        (m.alias for m in models),
+        next(iter(config.models), ""),
+    )
+    if ALIBABA_DEFAULT_MODEL_ALIAS in config.models:
+        config.default_model = ALIBABA_DEFAULT_MODEL_ALIAS
+    else:
+        config.default_model = fallback
+    apply_login_thinking_defaults(config, thinking=True, effort="high")
+
+
+def _model_by_id() -> dict[str, AlibabaModel]:
+    return {model.model_id: model for model in ALIBABA_MODELS}
+
+
+def _parse_discovered_models(data: object) -> tuple[AlibabaModel, ...]:
+    if not isinstance(data, dict):
+        return ()
+    d = cast(dict[str, Any], data)
+    items = d.get("data")
+    if not isinstance(items, list):
+        return ()
+    catalog = _model_by_id()
+    results: list[AlibabaModel] = []
+    for raw_item in cast(list[object], items):
+        if not isinstance(raw_item, dict):
+            continue
+        item = cast(dict[str, Any], raw_item)
+        model_id = item.get("id")
+        if not isinstance(model_id, str) or model_id not in catalog:
+            continue
+        base = catalog[model_id]
+        ctx = item.get("context_length")
+        max_ctx = base.max_context_size
+        if isinstance(ctx, int) and ctx > 0:
+            max_ctx = ctx
+        display_name_raw = item.get("display_name")
+        display_name = (
+            display_name_raw
+            if isinstance(display_name_raw, str) and display_name_raw
+            else base.display_name
+        )
+        results.append(
+            AlibabaModel(
+                model_id=base.model_id,
+                alias_suffix=base.alias_suffix,
+                display_name=display_name,
+                provider_key=base.provider_key,
+                max_context_size=max_ctx,
+                capabilities=base.capabilities,
+            )
+        )
+    return tuple(results)
+
+
+async def _discover_alibaba_models(api_key: str) -> tuple[AlibabaModel, ...]:
+    async with (
+        new_client_session(timeout=ALIBABA_MODEL_DISCOVERY_TIMEOUT) as session,
+        session.get(
+            f"{get_alibaba_base_url_from_env()}/models",
+            headers={"Authorization": f"Bearer {api_key}"},
+            raise_for_status=True,
+        ) as response,
+    ):
+        payload = await response.json(content_type=None)
+    return _parse_discovered_models(payload)
+
+
+async def login_alibaba_api_key(
+    config: Config, api_key: str | None = None
+) -> AsyncIterator[OAuthEvent]:
+    if not config.is_from_default_location:
+        yield OAuthEvent(
+            "error",
+            "Login requires the default config file; restart without --config/--config-file.",
+        )
+        return
+
+    resolved_key = (api_key or get_alibaba_api_key_from_env() or "").strip()
+    if not resolved_key:
+        yield OAuthEvent("error", "Alibaba API key is required.")
+        return
+
+    models = ALIBABA_MODELS
+    try:
+        discovered = await _discover_alibaba_models(resolved_key)
+        if discovered:
+            models = discovered
+    except aiohttp.ClientResponseError as exc:
+        if exc.status in {401, 403}:
+            yield OAuthEvent("error", "Invalid Alibaba API key; the key was not saved.")
+            return
+        yield OAuthEvent(
+            "info",
+            "Alibaba model listing is unavailable; using the built-in model list.",
+        )
+    except (aiohttp.ClientError, TimeoutError, ValueError):
+        yield OAuthEvent(
+            "info",
+            "Alibaba model listing is unavailable; using the built-in model list.",
+        )
+
+    _apply_alibaba_config(config, SecretStr(resolved_key), models=models)
+    save_config(config)
+    yield OAuthEvent("success", f"Alibaba configured with model {config.default_model}.")
+
+
+async def logout_alibaba(config: Config) -> AsyncIterator[OAuthEvent]:
+    if not config.is_from_default_location:
+        yield OAuthEvent(
+            "error",
+            "Logout requires the default config file; restart without --config/--config-file.",
+        )
+        return
+
+    provider_keys = {ALIBABA_PROVIDER_KEY}
+    config.providers.pop(ALIBABA_PROVIDER_KEY, None)
+    for key, model in list(config.models.items()):
+        if model.provider in provider_keys:
+            del config.models[key]
+
+    if config.default_model not in config.models:
+        config.default_model = next(iter(config.models), "")
+    save_config(config)
+    yield OAuthEvent("success", "Logged out of Alibaba successfully.")

src/pythinker_code/auth/minimax.py

@@ -20,11 +20,16 @@
 MINIMAX_ANTHROPIC_MODELS_URL = f"{MINIMAX_ANTHROPIC_BASE_URL}/v1/models"
 MINIMAX_OPENAI_MODELS_URL = f"{MINIMAX_OPENAI_BASE_URL}/models"
 MINIMAX_ANTHROPIC_PROVIDER_KEY = "managed:minimax-anthropic"
-MINIMAX_DEFAULT_MODEL_ALIAS = "minimax/m2.7"
-MINIMAX_DEFAULT_CONTEXT = 192_000
+MINIMAX_DEFAULT_MODEL_ALIAS = "minimax/m3"
+# Fallback context size for models without explicit specification (non-M3 models)
+MINIMAX_DEFAULT_CONTEXT = 204_800
 MINIMAX_TOKEN_PLAN_KEY_PREFIX = "sk-cp-"
 MINIMAX_MODEL_DISCOVERY_TIMEOUT = aiohttp.ClientTimeout(total=15, sock_connect=8, sock_read=10)
 MINIMAX_NATIVE_THINKING_CAPABILITIES: frozenset[ModelCapability] = frozenset({"always_thinking"})
+MINIMAX_M3_CAPABILITIES: frozenset[ModelCapability] = frozenset(
+    {"always_thinking", "image_in", "video_in"}
+)
+MINIMAX_M3_CONTEXT_SIZE = 1_000_000
 
 
 @dataclass(frozen=True, slots=True)
@@ -42,6 +47,13 @@ def alias(self) -> str:
 
 
 MINIMAX_MODELS: tuple[MiniMaxModel, ...] = (
+    MiniMaxModel(
+        "MiniMax-M3",
+        "m3",
+        "MiniMax M3",
+        max_context_size=MINIMAX_M3_CONTEXT_SIZE,
+        capabilities=MINIMAX_M3_CAPABILITIES,
+    ),
     MiniMaxModel("MiniMax-M2.7", "m2.7", "MiniMax M2.7"),
     MiniMaxModel("MiniMax-M2.7-highspeed", "m2.7-highspeed", "MiniMax M2.7 High-Speed"),
     MiniMaxModel("MiniMax-M2.5", "m2.5", "MiniMax M2.5"),