feat: upgrade MiniMax default model to M3

- Switch MINIMAX_LLM_MODEL default from MiniMax-M2.7 to MiniMax-M3
- Update sample query content to describe M3 as the new default and
  keep M2.7 / M2.7-highspeed as alternatives
- Update unit tests to assert the new default model name

Author: octo-patch

examples/minimax_integration_example.py

@@ -52,7 +52,7 @@
 # MiniMax configuration
 MINIMAX_BASE_URL = os.getenv("MINIMAX_BASE_URL", "https://api.minimax.io/v1")
 MINIMAX_API_KEY = os.getenv("MINIMAX_API_KEY", "")
-MINIMAX_LLM_MODEL = os.getenv("MINIMAX_LLM_MODEL", "MiniMax-M2.7")
+MINIMAX_LLM_MODEL = os.getenv("MINIMAX_LLM_MODEL", "MiniMax-M3")
 
 # Embedding configuration (MiniMax does not provide an embedding model;
 # configure a separate embedding service below)
@@ -257,14 +257,15 @@ async def simple_query_example(self):
                     "This integration connects MiniMax's powerful language models "
                     "with RAG-Anything's multimodal document processing pipeline.\n\n"
                     "Key features:\n"
-                    "- MiniMax-M2.7: Peak Performance. Ultimate Value. Master the Complex.\n"
-                    "- MiniMax-M2.7-highspeed: Same performance, faster and more agile.\n"
+                    "- MiniMax-M3: The latest flagship model and current default.\n"
+                    "- MiniMax-M2.7: Previous generation, available as alternative.\n"
+                    "- MiniMax-M2.7-highspeed: Same as M2.7, faster and more agile.\n"
                     "- OpenAI-compatible API — no SDK changes required.\n"
                     "- Supports text, table, and equation modalities.\n\n"
                     "Configuration:\n"
                     "  MINIMAX_API_KEY=your-api-key\n"
                     "  MINIMAX_BASE_URL=https://api.minimax.io/v1  (default)\n"
-                    "  MINIMAX_LLM_MODEL=MiniMax-M2.7  (default)\n"
+                    "  MINIMAX_LLM_MODEL=MiniMax-M3  (default)\n"
                 ),
                 "page_idx": 0,
             }

tests/test_minimax_integration.py

@@ -79,7 +79,7 @@ def _load_example(extra_env=None):
     env = {
         "MINIMAX_API_KEY": "test-key",
         "MINIMAX_BASE_URL": "https://api.minimax.io/v1",
-        "MINIMAX_LLM_MODEL": "MiniMax-M2.7",
+        "MINIMAX_LLM_MODEL": "MiniMax-M3",
         "EMBEDDING_BINDING_HOST": "https://api.openai.com/v1",
         "EMBEDDING_BINDING_API_KEY": "test-embed-key",
         "EMBEDDING_MODEL": "text-embedding-3-small",
@@ -124,7 +124,7 @@ def test_default_base_url(self):
             k: v
             for k, v in {
                 "MINIMAX_API_KEY": "test-key",
-                "MINIMAX_LLM_MODEL": "MiniMax-M2.7",
+                "MINIMAX_LLM_MODEL": "MiniMax-M3",
                 "EMBEDDING_BINDING_HOST": "https://api.openai.com/v1",
                 "EMBEDDING_BINDING_API_KEY": "test-embed-key",
                 "EMBEDDING_MODEL": "text-embedding-3-small",
@@ -149,7 +149,7 @@ def test_default_model(self):
         }
         with patch.dict(os.environ, env, clear=True):
             mod, _ = _load_example()
-        assert mod.MINIMAX_LLM_MODEL == "MiniMax-M2.7"
+        assert mod.MINIMAX_LLM_MODEL == "MiniMax-M3"
 
     def test_custom_model_env(self):
         mod, _ = _load_example({"MINIMAX_LLM_MODEL": "MiniMax-M2.7-highspeed"})
@@ -311,7 +311,7 @@ async def mock_complete(model, prompt, **kwargs):
 
         mod.openai_complete_if_cache = mock_complete
         await mod.minimax_llm_model_func("test")
-        assert captured["model"] == "MiniMax-M2.7"
+        assert captured["model"] == "MiniMax-M3"
 
     @pytest.mark.asyncio
     async def test_system_prompt_passed_through(self):
@@ -375,7 +375,7 @@ class TestMiniMaxRAGIntegration:
     def test_default_model_name(self):
         mod, _ = _load_example()
         integration = mod.MiniMaxRAGIntegration()
-        assert integration.model_name == "MiniMax-M2.7"
+        assert integration.model_name == "MiniMax-M3"
 
     def test_default_base_url(self):
         mod, _ = _load_example()