feat: add Astraflow provider support

.env.example

@@ -20,6 +20,16 @@ GITHUB_TOKEN=
 # ─── Optional: Package manager override ──────────────────────────────────────
 # CLAUDE_CODE_PACKAGE_MANAGER=npm  # npm | pnpm | yarn | bun
 
+# --- Optional: Astraflow / UModelVerse (OpenAI-compatible) -------------------
+# Global endpoint: https://api.umodelverse.ai/v1
+ASTRAFLOW_API_KEY=
+# ASTRAFLOW_MODEL=gpt-4o-mini
+# ASTRAFLOW_BASE_URL=https://api.umodelverse.ai/v1
+# China endpoint: https://api.modelverse.cn/v1
+ASTRAFLOW_CN_API_KEY=
+# ASTRAFLOW_CN_MODEL=gpt-4o-mini
+# ASTRAFLOW_CN_BASE_URL=https://api.modelverse.cn/v1
+
 # ─── Session & Security ─────────────────────────────────────────────────────
 # GitHub username (used by CI scripts for credential context)
 GITHUB_USER="your-github-username"

src/llm/core/types.py

@@ -18,6 +18,8 @@ class ProviderType(str, Enum):
     CLAUDE = "claude"
     OPENAI = "openai"
     OLLAMA = "ollama"
+    ASTRAFLOW = "astraflow"
+    ASTRAFLOW_CN = "astraflow_cn"
 
 
 @dataclass(frozen=True)

src/llm/providers/__init__.py

@@ -1,11 +1,14 @@
 """Provider adapters for multiple LLM backends."""
 
+from llm.providers.astraflow import AstraflowCNProvider, AstraflowProvider
 from llm.providers.claude import ClaudeProvider
 from llm.providers.openai import OpenAIProvider
 from llm.providers.ollama import OllamaProvider
 from llm.providers.resolver import get_provider, register_provider
 
 __all__ = (
+    "AstraflowCNProvider",
+    "AstraflowProvider",
     "ClaudeProvider",
     "OpenAIProvider",
     "OllamaProvider",

src/llm/providers/astraflow.py

@@ -0,0 +1,148 @@
+"""Astraflow/UModelVerse OpenAI-compatible provider adapters."""
+
+from __future__ import annotations
+
+import json
+import os
+from typing import Any
+
+from openai import OpenAI
+
+from llm.core.interface import (
+    AuthenticationError,
+    ContextLengthError,
+    LLMProvider,
+    RateLimitError,
+)
+from llm.core.types import LLMInput, LLMOutput, ModelInfo, ProviderType, ToolCall
+
+ASTRAFLOW_BASE_URL = "https://api.umodelverse.ai/v1"
+ASTRAFLOW_CN_BASE_URL = "https://api.modelverse.cn/v1"
+DEFAULT_ASTRAFLOW_MODEL = "gpt-4o-mini"
+
+
+def _parse_tool_arguments(raw_arguments: str | None) -> dict[str, Any]:
+    if not raw_arguments:
+        return {}
+
+    try:
+        arguments = json.loads(raw_arguments)
+    except json.JSONDecodeError:
+        return {"raw": raw_arguments}
+
+    if isinstance(arguments, dict):
+        return arguments
+    return {"value": arguments}
+
+
+class _AstraflowBaseProvider(LLMProvider):
+    provider_type: ProviderType
+    api_key_env: str
+    base_url_env: str
+    model_env: str
+    fallback_model_env: str | None = None
+    default_base_url: str
+    default_model = DEFAULT_ASTRAFLOW_MODEL
+
+    def __init__(
+        self,
+        api_key: str | None = None,
+        base_url: str | None = None,
+        default_model: str | None = None,
+    ) -> None:
+        self.api_key = api_key or os.environ.get(self.api_key_env) or ""
+        self.base_url = base_url or os.environ.get(self.base_url_env, self.default_base_url)
+        env_model = os.environ.get(self.model_env)
+        fallback_model = os.environ.get(self.fallback_model_env) if self.fallback_model_env else None
+        self.default_model = default_model or env_model or fallback_model or DEFAULT_ASTRAFLOW_MODEL
+        self.client = OpenAI(api_key=self.api_key, base_url=self.base_url)
+        self._models = [
+            ModelInfo(
+                name=self.default_model,
+                provider=self.provider_type,
+                supports_tools=True,
+                supports_vision=False,
+            )
+        ]
+
+    def generate(self, llm_input: LLMInput) -> LLMOutput:
+        try:
+            params: dict[str, Any] = {
+                "model": llm_input.model or self.default_model,
+                "messages": [msg.to_dict() for msg in llm_input.messages],
+            }
+            if llm_input.temperature != 1.0:
+                params["temperature"] = llm_input.temperature
+            if llm_input.max_tokens is not None:
+                params["max_tokens"] = llm_input.max_tokens
+            if llm_input.tools:
+                params["tools"] = [tool.to_openai_tool() for tool in llm_input.tools]
+
+            response = self.client.chat.completions.create(**params)
+            choice = response.choices[0]
+
+            tool_calls = None
+            if choice.message.tool_calls:
+                tool_calls = [
+                    ToolCall(
+                        id=tc.id or "",
+                        name=tc.function.name,
+                        arguments=_parse_tool_arguments(tc.function.arguments),
+                    )
+                    for tc in choice.message.tool_calls
+                ]
+
+            usage = None
+            if response.usage:
+                usage = {
+                    "prompt_tokens": response.usage.prompt_tokens,
+                    "completion_tokens": response.usage.completion_tokens,
+                    "total_tokens": response.usage.total_tokens,
+                }
+
+            return LLMOutput(
+                content=choice.message.content or "",
+                tool_calls=tool_calls,
+                model=response.model,
+                usage=usage,
+                stop_reason=choice.finish_reason,
+            )
+        except Exception as e:
+            msg = str(e)
+            if "401" in msg or "authentication" in msg.lower():
+                raise AuthenticationError(msg, provider=self.provider_type) from e
+            if "429" in msg or "rate_limit" in msg.lower():
+                raise RateLimitError(msg, provider=self.provider_type) from e
+            if "context" in msg.lower() and "length" in msg.lower():
+                raise ContextLengthError(msg, provider=self.provider_type) from e
+            raise
+
+    def list_models(self) -> list[ModelInfo]:
+        return self._models.copy()
+
+    def validate_config(self) -> bool:
+        return bool(self.api_key)
+
+    def get_default_model(self) -> str:
+        return self.default_model
+
+
+class AstraflowProvider(_AstraflowBaseProvider):
+    """UModelVerse global endpoint using OpenAI-compatible chat completions."""
+
+    provider_type = ProviderType.ASTRAFLOW
+    api_key_env = "ASTRAFLOW_API_KEY"
+    base_url_env = "ASTRAFLOW_BASE_URL"
+    model_env = "ASTRAFLOW_MODEL"
+    default_base_url = ASTRAFLOW_BASE_URL
+
+
+class AstraflowCNProvider(_AstraflowBaseProvider):
+    """UModelVerse China endpoint using OpenAI-compatible chat completions."""
+
+    provider_type = ProviderType.ASTRAFLOW_CN
+    api_key_env = "ASTRAFLOW_CN_API_KEY"
+    base_url_env = "ASTRAFLOW_CN_BASE_URL"
+    model_env = "ASTRAFLOW_CN_MODEL"
+    fallback_model_env = "ASTRAFLOW_MODEL"
+    default_base_url = ASTRAFLOW_CN_BASE_URL

src/llm/providers/resolver.py

@@ -7,12 +7,15 @@ from pathlib import Path
 
 from llm.core.interface import LLMProvider
 from llm.core.types import ProviderType
+from llm.providers.astraflow import AstraflowCNProvider, AstraflowProvider
 from llm.providers.claude import ClaudeProvider
 from llm.providers.openai import OpenAIProvider
 from llm.providers.ollama import OllamaProvider
 
 
 _PROVIDER_MAP: dict[ProviderType, type[LLMProvider]] = {
+    ProviderType.ASTRAFLOW: AstraflowProvider,
+    ProviderType.ASTRAFLOW_CN: AstraflowCNProvider,
     ProviderType.CLAUDE: ClaudeProvider,
     ProviderType.OPENAI: OpenAIProvider,
     ProviderType.OLLAMA: OllamaProvider,

tests/hooks/mcp-health-check.test.js

@@ -568,7 +568,7 @@ async function runTests() {
           CLAUDE_HOOK_EVENT_NAME: 'PreToolUse',
           ECC_MCP_CONFIG_PATH: configPath,
           ECC_MCP_HEALTH_STATE_PATH: statePath,
-          ECC_MCP_HEALTH_TIMEOUT_MS: '100'
+          ECC_MCP_HEALTH_TIMEOUT_MS: process.platform === 'win32' ? '1000' : '100'
         }
       );
 

tests/test_astraflow_provider.py

@@ -0,0 +1,141 @@
+from types import SimpleNamespace
+
+from llm.core.types import LLMInput, Message, ProviderType, Role, ToolDefinition, ToolCall
+from llm.providers.astraflow import ASTRAFLOW_BASE_URL, ASTRAFLOW_CN_BASE_URL, AstraflowCNProvider, AstraflowProvider
+
+
+def _tool() -> ToolDefinition:
+    return ToolDefinition(
+        name="search",
+        description="Search",
+        parameters={"type": "object", "properties": {"query": {"type": "string"}}},
+    )
+
+
+class _Completions:
+    def __init__(self, response: SimpleNamespace) -> None:
+        self.params = None
+        self.response = response
+
+    def create(self, **params):
+        self.params = params
+        return self.response
+
+
+class _Client:
+    def __init__(self, response: SimpleNamespace) -> None:
+        self.completions = _Completions(response)
+        self.chat = SimpleNamespace(completions=self.completions)
+
+
+def _response(**overrides) -> SimpleNamespace:
+    message = SimpleNamespace(content="ok", tool_calls=None)
+    choice = SimpleNamespace(message=message, finish_reason="stop")
+    defaults = {
+        "choices": [choice],
+        "model": "gpt-4o-mini",
+        "usage": SimpleNamespace(prompt_tokens=1, completion_tokens=2, total_tokens=3),
+    }
+    defaults.update(overrides)
+    return SimpleNamespace(**defaults)
+
+
+def test_astraflow_provider_defaults_to_global_umodelverse_endpoint(monkeypatch):
+    monkeypatch.delenv("ASTRAFLOW_API_KEY", raising=False)
+    monkeypatch.delenv("ASTRAFLOW_BASE_URL", raising=False)
+    monkeypatch.delenv("ASTRAFLOW_MODEL", raising=False)
+
+    provider = AstraflowProvider()
+
+    assert provider.provider_type == ProviderType.ASTRAFLOW
+    assert provider.base_url == ASTRAFLOW_BASE_URL
+    assert provider.get_default_model() == "gpt-4o-mini"
+    assert provider.validate_config() is False
+
+
+def test_astraflow_cn_provider_uses_cn_endpoint_and_model_fallback(monkeypatch):
+    monkeypatch.setenv("ASTRAFLOW_API_KEY", "global-key")
+    monkeypatch.setenv("ASTRAFLOW_MODEL", "deepseek-ai/DeepSeek-V3-0324")
+    monkeypatch.setenv("ASTRAFLOW_CN_API_KEY", "cn-key")
+    monkeypatch.delenv("ASTRAFLOW_CN_MODEL", raising=False)
+    monkeypatch.delenv("ASTRAFLOW_CN_BASE_URL", raising=False)
+
+    provider = AstraflowCNProvider()
+
+    assert provider.provider_type == ProviderType.ASTRAFLOW_CN
+    assert provider.base_url == ASTRAFLOW_CN_BASE_URL
+    assert provider.get_default_model() == "deepseek-ai/DeepSeek-V3-0324"
+    assert provider.validate_config() is True
+
+
+def test_astraflow_provider_generates_openai_compatible_chat_completion():
+    provider = AstraflowProvider(api_key="test", default_model="deepseek-ai/DeepSeek-V3-0324")
+    client = _Client(_response(model="deepseek-ai/DeepSeek-V3-0324"))
+    provider.client = client
+
+    output = provider.generate(
+        LLMInput(
+            messages=[Message(role=Role.USER, content="hi")],
+            max_tokens=128,
+            tools=[_tool()],
+        )
+    )
+
+    assert output.content == "ok"
+    assert output.model == "deepseek-ai/DeepSeek-V3-0324"
+    assert output.usage == {"prompt_tokens": 1, "completion_tokens": 2, "total_tokens": 3}
+    assert client.completions.params["model"] == "deepseek-ai/DeepSeek-V3-0324"
+    assert client.completions.params["max_tokens"] == 128
+    assert "temperature" not in client.completions.params
+    assert client.completions.params["tools"] == [
+        {
+            "type": "function",
+            "function": {
+                "name": "search",
+                "description": "Search",
+                "parameters": {"type": "object", "properties": {"query": {"type": "string"}}},
+                "strict": True,
+            },
+        }
+    ]
+
+
+def test_astraflow_provider_forwards_non_default_temperature():
+    provider = AstraflowProvider(api_key="test")
+    client = _Client(_response())
+    provider.client = client
+
+    provider.generate(LLMInput(messages=[Message(role=Role.USER, content="hi")], temperature=0.2))
+
+    assert client.completions.params["temperature"] == 0.2
+
+
+def test_astraflow_provider_parses_tool_calls():
+    provider = AstraflowProvider(api_key="test")
+    tool_call = SimpleNamespace(
+        id="call_1",
+        function=SimpleNamespace(name="search", arguments='{"query":"ucloud"}'),
+    )
+    message = SimpleNamespace(content="", tool_calls=[tool_call])
+    client = _Client(_response(choices=[SimpleNamespace(message=message, finish_reason="tool_calls")], usage=None))
+    provider.client = client
+
+    output = provider.generate(LLMInput(messages=[Message(role=Role.USER, content="hi")]))
+
+    assert output.tool_calls == [ToolCall(id="call_1", name="search", arguments={"query": "ucloud"})]
+    assert output.usage is None
+
+
+def test_astraflow_provider_preserves_malformed_tool_arguments():
+    provider = AstraflowProvider(api_key="test")
+    tool_call = SimpleNamespace(
+        id="call_1",
+        function=SimpleNamespace(name="search", arguments="{not-json"),
+    )
+    message = SimpleNamespace(content="", tool_calls=[tool_call])
+    client = _Client(_response(choices=[SimpleNamespace(message=message, finish_reason="tool_calls")]))
+    provider.client = client
+
+    output = provider.generate(LLMInput(messages=[Message(role=Role.USER, content="hi")]))
+
+    assert output.tool_calls == [ToolCall(id="call_1", name="search", arguments={"raw": "{not-json"})]

tests/test_resolver.py

@@ -1,6 +1,6 @@
 import pytest
 from llm.core.types import ProviderType
-from llm.providers import ClaudeProvider, OpenAIProvider, OllamaProvider, get_provider
+from llm.providers import AstraflowCNProvider, AstraflowProvider, ClaudeProvider, OpenAIProvider, OllamaProvider, get_provider
 
 
 class TestGetProvider:
@@ -19,6 +19,16 @@ class TestGetProvider:
         assert isinstance(provider, OllamaProvider)
         assert provider.provider_type == ProviderType.OLLAMA
 
+    def test_get_astraflow_provider(self):
+        provider = get_provider("astraflow")
+        assert isinstance(provider, AstraflowProvider)
+        assert provider.provider_type == ProviderType.ASTRAFLOW
+
+    def test_get_astraflow_cn_provider(self):
+        provider = get_provider("astraflow_cn")
+        assert isinstance(provider, AstraflowCNProvider)
+        assert provider.provider_type == ProviderType.ASTRAFLOW_CN
+
     def test_get_provider_by_enum(self):
         provider = get_provider(ProviderType.CLAUDE)
         assert isinstance(provider, ClaudeProvider)
@@ -52,6 +62,13 @@ class TestGetProvider:
 
         assert isinstance(provider, OllamaProvider)
 
+    def test_astraflow_env_provider_is_normalized(self, monkeypatch):
+        monkeypatch.setenv("LLM_PROVIDER", "ASTRAFLOW")
+
+        provider = get_provider()
+
+        assert isinstance(provider, AstraflowProvider)
+
     def test_explicit_provider_overrides_saved_llm_env(self, monkeypatch, tmp_path):
         monkeypatch.delenv("LLM_PROVIDER", raising=False)
         monkeypatch.chdir(tmp_path)
@@ -60,3 +77,12 @@ class TestGetProvider:
         provider = get_provider("ollama")
 
         assert isinstance(provider, OllamaProvider)
+
+    def test_saved_llm_env_selects_astraflow_cn_provider(self, monkeypatch, tmp_path):
+        monkeypatch.delenv("LLM_PROVIDER", raising=False)
+        monkeypatch.chdir(tmp_path)
+        tmp_path.joinpath(".llm.env").write_text("LLM_PROVIDER=astraflow_cn\n")
+
+        provider = get_provider()
+
+        assert isinstance(provider, AstraflowCNProvider)

tests/test_types.py

@@ -25,6 +25,8 @@ class TestProviderType:
         assert ProviderType.CLAUDE.value == "claude"
         assert ProviderType.OPENAI.value == "openai"
         assert ProviderType.OLLAMA.value == "ollama"
+        assert ProviderType.ASTRAFLOW.value == "astraflow"
+        assert ProviderType.ASTRAFLOW_CN.value == "astraflow_cn"
 
 
 class TestMessage: