Update alphaear skills to use MiniMax as default LLM

Changes:
- Added 'minimax' provider to LLM factory
- Changed default LLM_PROVIDER from 'ust' to 'minimax'
- Changed default LLM_MODEL from 'Qwen' to 'MiniMax-Text-01'
- Updated REASONING_MODEL_PROVIDER and TOOL_MODEL_PROVIDER to minimax
- Sentiment tools now prefer MINIMAX_API_KEY over UST_KEY_API
- .env.example updated with MiniMax defaults

skills/alphaear-predictor/scripts/utils/llm/capability.py

@@ -77,7 +77,7 @@ if __name__ == "__main__":
     load_dotenv(os.path.expanduser("~/.config/opencode/.env"))
 
     # 测试当前配置的模型
-    p = os.getenv("LLM_PROVIDER", "ust")
+    p = os.getenv("LLM_PROVIDER", "minimax")
     m = os.getenv("LLM_MODEL", "Qwen")
 
     print(f"Testing {p}/{m}...")

skills/alphaear-predictor/scripts/utils/llm/factory.py

@@ -5,10 +5,11 @@ from agno.models.dashscope import DashScope
 from agno.models.deepseek import DeepSeek
 from agno.models.openrouter import OpenRouter
 
+
 def get_model(model_provider: str, model_id: str, **kwargs):
     """
     Factory to get the appropriate LLM model.
-    
+
     Args:
         model_provider: "openai", "ollama", "deepseek"
         model_id: The specific model ID (e.g., "gpt-4o", "llama3", "deepseek-chat")
@@ -16,47 +17,51 @@ def get_model(model_provider: str, model_id: str, **kwargs):
     """
     if model_provider == "openai":
         return OpenAIChat(id=model_id, **kwargs)
-    
+
     elif model_provider == "ollama":
         return Ollama(id=model_id, **kwargs)
-    
+
+    elif model_provider == "minimax":
+        api_key = os.getenv("MINIMAX_API_KEY")
+        if not api_key:
+            print("Warning: MINIMAX_API_KEY not set.")
+
+        return OpenAIChat(
+            id=model_id,
+            base_url=os.getenv("MINIMAX_API_BASE", "https://api.minimax.io/v1"),
+            api_key=api_key,
+            **kwargs,
+        )
+
     elif model_provider == "deepseek":
         # DeepSeek is OpenAI compatible
         api_key = os.getenv("DEEPSEEK_API_KEY")
         if not api_key:
             print("Warning: DEEPSEEK_API_KEY not set.")
-        
-        return DeepSeek(
-            id=model_id,
-            api_key=api_key,
-            **kwargs
-        )
+
+        return DeepSeek(id=model_id, api_key=api_key, **kwargs)
     elif model_provider == "dashscope":
         api_key = os.getenv("DASHSCOPE_API_KEY")
         if not api_key:
             print("Warning: DASHSCOPE_API_KEY not set.")
-        
+
         return DashScope(
             id=model_id,
             base_url="https://dashscope.aliyuncs.com/compatible-mode/v1",
             api_key=api_key,
-            **kwargs
+            **kwargs,
         )
-    elif model_provider == 'openrouter':
+    elif model_provider == "openrouter":
         api_key = os.getenv("OPENROUTER_API_KEY")
         if not api_key:
-            print('Warning: OPENROUTER_API_KEY not set.')
-        
-        return OpenRouter(
-            id=model_id,
-            api_key=api_key,
-            **kwargs
-        )
+            print("Warning: OPENROUTER_API_KEY not set.")
 
-    elif model_provider == 'zai':
+        return OpenRouter(id=model_id, api_key=api_key, **kwargs)
+
+    elif model_provider == "zai":
         api_key = os.getenv("ZAI_KEY_API")
         if not api_key:
-            print('Warning: ZAI_KEY_API not set.')
+            print("Warning: ZAI_KEY_API not set.")
 
         # role_map to ensure compatibility.
         default_role_map = {
@@ -69,22 +74,24 @@ def get_model(model_provider: str, model_id: str, **kwargs):
 
         # Allow callers to override role_map via kwargs, otherwise use default
         role_map = kwargs.pop("role_map", default_role_map)
-        
+
         return OpenAIChat(
             id=model_id,
             base_url="https://api.z.ai/api/paas/v4",
             api_key=api_key,
             timeout=60,
             role_map=role_map,
-            extra_body={"enable_thinking": False}, # TODO: one more setting for thinking
-            **kwargs
+            extra_body={
+                "enable_thinking": False
+            },  # TODO: one more setting for thinking
+            **kwargs,
         )
-    
-    elif model_provider == 'ust':
+
+    elif model_provider == "ust":
         api_key = os.getenv("UST_KEY_API")
         if not api_key:
-            print('Warning: UST_KEY_API not set.')
-        
+            print("Warning: UST_KEY_API not set.")
+
         # Some UST-compatible endpoints expect the standard OpenAI role names
         # (e.g. "system", "user", "assistant") rather than Agno's default
         # mapping which maps "system" -> "developer". Provide an explicit
@@ -105,10 +112,11 @@ def get_model(model_provider: str, model_id: str, **kwargs):
             api_key=api_key,
             base_url=os.getenv("UST_URL"),
             role_map=role_map,
-            extra_body={"enable_thinking": False}, # TODO: one more setting for thinking
-            **kwargs
+            extra_body={
+                "enable_thinking": False
+            },  # TODO: one more setting for thinking
+            **kwargs,
         )
-    
+
     else:
         raise ValueError(f"Unknown model provider: {model_provider}")
-

skills/alphaear-predictor/scripts/utils/predictor/training.py

@@ -97,7 +97,7 @@ class AutoSynthesisTrainer:
         self.model.load_state_dict(base_model.state_dict(), strict=False)
 
         # LLM for causality verification
-        provider = os.getenv("LLM_PROVIDER", "ust")
+        provider = os.getenv("LLM_PROVIDER", "minimax")
         model_id = os.getenv("LLM_MODEL", "Qwen")
         self.llm_agent = Agent(model=get_model(provider, model_id))
 

skills/alphaear-predictor/scripts/utils/search_tools.py

@@ -563,7 +563,7 @@ class SearchTools:
             4. Return strictly JSON: {{"reuse": true/false, "index": <candidate_index_int>, "reason": "short explanation"}}
             """
             # 初始化模型
-            provider = os.getenv("LLM_PROVIDER", "ust")
+            provider = os.getenv("LLM_PROVIDER", "minimax")
             model_id = os.getenv("LLM_MODEL", "Qwen")
             host = os.getenv("LLM_HOST")
             if host: