Merge pull request #444 from ximiximi423/feat/add-minimax-provider

feat: add MiniMax as new LLM provider

.env.example

@@ -10,4 +10,8 @@ DEEPSEEK_API_KEY='xxxxx'
 OPENROUTER_API_KEY='xxxxx'
 TOGETHER_API_KEY='xxxxx'
 GOOGLE_API_KEY='xxxxx'
-ANTHROPIC_API_KEY='xxxxx'
+ANTHROPIC_API_KEY='xxxxx'
+MINIMAX_API_KEY='xxxxx'
+# Optional: MiniMax API base URL (default: https://api.minimax.io/v1)
+# For mainland China users: https://api.minimaxi.com/v1
+# MINIMAX_BASE_URL='https://api.minimax.io/v1'

README.md

@@ -240,6 +240,7 @@ provider_server_address = # Typically ignored or can be left blank when is_local
 | Hugging Face | `huggingface`   | No     | Use models from Hugging Face Inference API.       | [huggingface.co/settings/tokens](https://huggingface.co/settings/tokens) |
 | TogetherAI   | `togetherAI`    | No     | Use various open-source models via TogetherAI API.| [api.together.ai/settings/api-keys](https://api.together.ai/settings/api-keys) |
 | OpenRouter   | `openrouter`    | No     | Use OpenRouter Models| [https://openrouter.ai/](https://openrouter.ai/) |
+| MiniMax      | `minimax`       | No     | Use MiniMax M2.5 series models (e.g., MiniMax-M2.5).| [platform.minimax.io](https://platform.minimax.io/user-center/basic-information) |
 
 *Note:*
 *   We advise against using `gpt-4o` or other OpenAI models for complex web browsing and task planning as current prompt optimizations are geared towards models like Deepseek.

README_CHS.md

@@ -230,6 +230,7 @@ provider_server_address = # 当 is_local = False 时，对于大多数 API 通
 | Hugging Face | `huggingface`   | 否     | 使用 Hugging Face Inference API 中的模型。       | [huggingface.co/settings/tokens](https://huggingface.co/settings/tokens) |
 | TogetherAI   | `togetherAI`    | 否     | 通过 TogetherAI API 使用各种开源模型。| [api.together.ai/settings/api-keys](https://api.together.ai/settings/api-keys) |
 | OpenRouter   | `openrouter`    | No     | 通过 OpenRouter 使用各种开源模型| [https://openrouter.ai/](https://openrouter.ai/) |
+| MiniMax      | `minimax`       | 否     | 使用 MiniMax 的 M2.5 系列模型（如 MiniMax-M2.5）。 | [platform.minimax.io](https://platform.minimax.io/user-center/basic-information) |
 
 *注意：*
 *   我们不建议将 `gpt-4o` 或其他 OpenAI 模型用于复杂的网页浏览和任务规划，因为当前的提示优化针对 Deepseek 等模型。

sources/llm_provider.py

@@ -32,12 +32,13 @@ class Provider:
             "together": self.together_fn,
             "dsk_deepseek": self.dsk_deepseek,
             "openrouter": self.openrouter_fn,
+            "minimax": self.minimax_fn,
             "test": self.test_fn
         }
         self.logger = Logger("provider.log")
         self.api_key = None
         self.internal_url, self.in_docker = self.get_internal_url()
-        self.unsafe_providers = ["openai", "deepseek", "dsk_deepseek", "together", "google", "openrouter"]
+        self.unsafe_providers = ["openai", "deepseek", "dsk_deepseek", "together", "google", "openrouter", "minimax"]
         if self.provider_name not in self.available_providers:
             raise ValueError(f"Unknown provider: {provider_name}")
         if self.provider_name in self.unsafe_providers and self.is_local == False:
@@ -412,6 +413,37 @@ class Provider:
         except Exception as e:
             raise Exception(f"OpenRouter API error: {str(e)}") from e
 
+    def minimax_fn(self, history, verbose=False):
+        """
+        Use MiniMax API to generate text via OpenAI-compatible interface.
+        
+        Supported models:
+        - MiniMax-M2.5: Peak performance model (~60 tps), 204,800 context window
+        - MiniMax-M2.5-highspeed: Same performance, faster (~100 tps)
+        
+        Note: temperature must be in range (0.0, 1.0], default is 1.0
+        """
+        load_dotenv()
+        base_url = os.getenv("MINIMAX_BASE_URL", "https://api.minimax.io/v1")
+        
+        client = OpenAI(api_key=self.api_key, base_url=base_url)
+        if self.is_local:
+            raise Exception("MiniMax is not available for local use. Change config.ini")
+        try:
+            response = client.chat.completions.create(
+                model=self.model,
+                messages=history,
+                temperature=1.0,
+            )
+            if response is None:
+                raise Exception("MiniMax response is empty.")
+            thought = response.choices[0].message.content
+            if verbose:
+                print(thought)
+            return thought
+        except Exception as e:
+            raise Exception(f"MiniMax API error: {str(e)}") from e
+
     def dsk_deepseek(self, history, verbose=False):
         """
         Use: xtekky/deepseek4free

tests/test_minimax_provider.py

@@ -0,0 +1,196 @@
+import unittest
+from unittest.mock import patch, MagicMock
+import os
+import sys
+
+sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), '..')))
+
+from sources.llm_provider import Provider
+
+
+class TestMiniMaxProvider(unittest.TestCase):
+    """Test cases for MiniMax provider integration."""
+
+    def test_minimax_provider_registered(self):
+        """Test that minimax provider is registered in available_providers."""
+        with patch.object(Provider, 'get_api_key', return_value='test-key'):
+            provider = Provider("minimax", "MiniMax-M2.5", is_local=False)
+            self.assertIn("minimax", provider.available_providers)
+
+    def test_minimax_in_unsafe_providers(self):
+        """Test that minimax is in unsafe_providers list."""
+        with patch.object(Provider, 'get_api_key', return_value='test-key'):
+            provider = Provider("minimax", "MiniMax-M2.5", is_local=False)
+            self.assertIn("minimax", provider.unsafe_providers)
+
+    def test_minimax_api_key_required(self):
+        """Test that API key is fetched for minimax provider."""
+        with patch.object(Provider, 'get_api_key', return_value='test-minimax-key') as mock_get_key:
+            provider = Provider("minimax", "MiniMax-M2.5", is_local=False)
+            mock_get_key.assert_called_with("minimax")
+            self.assertEqual(provider.api_key, 'test-minimax-key')
+
+    @patch('sources.llm_provider.OpenAI')
+    @patch.dict(os.environ, {'MINIMAX_API_KEY': 'test-key'})
+    def test_minimax_local_not_supported(self, mock_openai_class):
+        """Test that minimax provider raises error when is_local=True."""
+        provider = Provider("minimax", "MiniMax-M2.5", is_local=True)
+        provider.api_key = 'test-key'
+        history = [{"role": "user", "content": "Hello"}]
+        with self.assertRaises(Exception) as context:
+            provider.minimax_fn(history)
+        self.assertIn("not available for local use", str(context.exception))
+
+    @patch('sources.llm_provider.OpenAI')
+    @patch.dict(os.environ, {'MINIMAX_API_KEY': 'test-key'})
+    def test_minimax_uses_correct_base_url(self, mock_openai_class):
+        """Test that minimax provider uses correct base URL."""
+        mock_client = MagicMock()
+        mock_openai_class.return_value = mock_client
+        mock_response = MagicMock()
+        mock_response.choices = [MagicMock(message=MagicMock(content="Hello!"))]
+        mock_client.chat.completions.create.return_value = mock_response
+
+        with patch.object(Provider, 'get_api_key', return_value='test-key'):
+            provider = Provider("minimax", "MiniMax-M2.5", is_local=False)
+            history = [{"role": "user", "content": "Hello"}]
+            provider.minimax_fn(history)
+
+            mock_openai_class.assert_called_with(
+                api_key='test-key',
+                base_url='https://api.minimax.io/v1'
+            )
+
+    @patch('sources.llm_provider.OpenAI')
+    @patch.dict(os.environ, {
+        'MINIMAX_API_KEY': 'test-key',
+        'MINIMAX_BASE_URL': 'https://api.minimaxi.com/v1'
+    })
+    def test_minimax_custom_base_url(self, mock_openai_class):
+        """Test that minimax provider uses custom base URL from env."""
+        mock_client = MagicMock()
+        mock_openai_class.return_value = mock_client
+        mock_response = MagicMock()
+        mock_response.choices = [MagicMock(message=MagicMock(content="Hello!"))]
+        mock_client.chat.completions.create.return_value = mock_response
+
+        with patch.object(Provider, 'get_api_key', return_value='test-key'):
+            provider = Provider("minimax", "MiniMax-M2.5", is_local=False)
+            history = [{"role": "user", "content": "Hello"}]
+            provider.minimax_fn(history)
+
+            mock_openai_class.assert_called_with(
+                api_key='test-key',
+                base_url='https://api.minimaxi.com/v1'
+            )
+
+    @patch('sources.llm_provider.OpenAI')
+    @patch.dict(os.environ, {'MINIMAX_API_KEY': 'test-key'})
+    def test_minimax_uses_temperature_one(self, mock_openai_class):
+        """Test that minimax provider uses temperature=1.0."""
+        mock_client = MagicMock()
+        mock_openai_class.return_value = mock_client
+        mock_response = MagicMock()
+        mock_response.choices = [MagicMock(message=MagicMock(content="Hello!"))]
+        mock_client.chat.completions.create.return_value = mock_response
+
+        with patch.object(Provider, 'get_api_key', return_value='test-key'):
+            provider = Provider("minimax", "MiniMax-M2.5", is_local=False)
+            history = [{"role": "user", "content": "Hello"}]
+            provider.minimax_fn(history)
+
+            call_kwargs = mock_client.chat.completions.create.call_args[1]
+            self.assertEqual(call_kwargs['temperature'], 1.0)
+
+    @patch('sources.llm_provider.OpenAI')
+    @patch.dict(os.environ, {'MINIMAX_API_KEY': 'test-key'})
+    def test_minimax_returns_response_content(self, mock_openai_class):
+        """Test that minimax provider returns response content."""
+        mock_client = MagicMock()
+        mock_openai_class.return_value = mock_client
+        mock_response = MagicMock()
+        mock_response.choices = [MagicMock(message=MagicMock(content="Test response"))]
+        mock_client.chat.completions.create.return_value = mock_response
+
+        with patch.object(Provider, 'get_api_key', return_value='test-key'):
+            provider = Provider("minimax", "MiniMax-M2.5", is_local=False)
+            history = [{"role": "user", "content": "Hello"}]
+            result = provider.minimax_fn(history)
+
+            self.assertEqual(result, "Test response")
+
+    @patch('sources.llm_provider.OpenAI')
+    @patch.dict(os.environ, {'MINIMAX_API_KEY': 'test-key'})
+    def test_minimax_handles_empty_response(self, mock_openai_class):
+        """Test that minimax provider handles empty response."""
+        mock_client = MagicMock()
+        mock_openai_class.return_value = mock_client
+        mock_client.chat.completions.create.return_value = None
+
+        with patch.object(Provider, 'get_api_key', return_value='test-key'):
+            provider = Provider("minimax", "MiniMax-M2.5", is_local=False)
+            history = [{"role": "user", "content": "Hello"}]
+
+            with self.assertRaises(Exception) as context:
+                provider.minimax_fn(history)
+            self.assertIn("response is empty", str(context.exception))
+
+    @patch('sources.llm_provider.OpenAI')
+    @patch.dict(os.environ, {'MINIMAX_API_KEY': 'test-key'})
+    def test_minimax_handles_api_error(self, mock_openai_class):
+        """Test that minimax provider handles API errors."""
+        mock_client = MagicMock()
+        mock_openai_class.return_value = mock_client
+        mock_client.chat.completions.create.side_effect = Exception("API rate limit exceeded")
+
+        with patch.object(Provider, 'get_api_key', return_value='test-key'):
+            provider = Provider("minimax", "MiniMax-M2.5", is_local=False)
+            history = [{"role": "user", "content": "Hello"}]
+
+            with self.assertRaises(Exception) as context:
+                provider.minimax_fn(history)
+            self.assertIn("MiniMax API error", str(context.exception))
+
+
+class TestMiniMaxProviderModels(unittest.TestCase):
+    """Test cases for MiniMax provider model configurations."""
+
+    @patch('sources.llm_provider.OpenAI')
+    @patch.dict(os.environ, {'MINIMAX_API_KEY': 'test-key'})
+    def test_minimax_m25_model(self, mock_openai_class):
+        """Test MiniMax-M2.5 model."""
+        mock_client = MagicMock()
+        mock_openai_class.return_value = mock_client
+        mock_response = MagicMock()
+        mock_response.choices = [MagicMock(message=MagicMock(content="Response"))]
+        mock_client.chat.completions.create.return_value = mock_response
+
+        with patch.object(Provider, 'get_api_key', return_value='test-key'):
+            provider = Provider("minimax", "MiniMax-M2.5", is_local=False)
+            history = [{"role": "user", "content": "Hello"}]
+            provider.minimax_fn(history)
+
+            call_kwargs = mock_client.chat.completions.create.call_args[1]
+            self.assertEqual(call_kwargs['model'], "MiniMax-M2.5")
+
+    @patch('sources.llm_provider.OpenAI')
+    @patch.dict(os.environ, {'MINIMAX_API_KEY': 'test-key'})
+    def test_minimax_m25_highspeed_model(self, mock_openai_class):
+        """Test MiniMax-M2.5-highspeed model."""
+        mock_client = MagicMock()
+        mock_openai_class.return_value = mock_client
+        mock_response = MagicMock()
+        mock_response.choices = [MagicMock(message=MagicMock(content="Response"))]
+        mock_client.chat.completions.create.return_value = mock_response
+
+        with patch.object(Provider, 'get_api_key', return_value='test-key'):
+            provider = Provider("minimax", "MiniMax-M2.5-highspeed", is_local=False)
+            history = [{"role": "user", "content": "Hello"}]
+            provider.minimax_fn(history)
+
+            call_kwargs = mock_client.chat.completions.create.call_args[1]
+            self.assertEqual(call_kwargs['model'], "MiniMax-M2.5-highspeed")
+
+
+if __name__ == '__main__':
+    unittest.main()