fix: address review feedback for the Minimax LLM provider

docs/components/llms/models/minimax.mdx

@@ -0,0 +1,56 @@
+---
+title: MiniMax
+description: "Configure MiniMax as an LLM provider in Mem0 with API key setup and optional custom endpoint configuration."
+---
+
+To use MiniMax LLM models, you have to set the `MINIMAX_API_KEY` environment variable. You can also optionally set `MINIMAX_API_BASE` if you need to use a different API endpoint (defaults to "https://api.minimax.io/v1").
+
+## Usage
+
+```python
+import os
+from mem0 import Memory
+
+os.environ["MINIMAX_API_KEY"] = "your-api-key"
+os.environ["OPENAI_API_KEY"] = "your-api-key" # for embedder model
+
+config = {
+    "llm": {
+        "provider": "minimax",
+        "config": {
+            "model": "MiniMax-M2.7",  # default model
+            "temperature": 0.2,
+            "max_tokens": 2000,
+            "top_p": 1.0
+        }
+    }
+}
+
+m = Memory.from_config(config)
+messages = [
+    {"role": "user", "content": "I'm planning to watch a movie tonight. Any recommendations?"},
+    {"role": "assistant", "content": "How about thriller movies? They can be quite engaging."},
+    {"role": "user", "content": "I'm not a big fan of thriller movies but I love sci-fi movies."},
+    {"role": "assistant", "content": "Got it! I'll avoid thriller recommendations and suggest sci-fi movies in the future."}
+]
+m.add(messages, user_id="alice", metadata={"category": "movies"})
+```
+
+You can also configure the API base URL in the config:
+
+```python
+config = {
+    "llm": {
+        "provider": "minimax",
+        "config": {
+            "model": "MiniMax-M2.7",
+            "minimax_base_url": "https://your-custom-endpoint.com",
+            "api_key": "your-api-key"  # alternatively to using environment variable
+        }
+    }
+}
+```
+
+## Config
+
+All available parameters for the `minimax` config are present in [Master List of All Params in Config](../config).

docs/components/llms/overview.mdx

@@ -31,6 +31,7 @@ See the list of supported LLMs below.
   <Card title="Google AI" href="/components/llms/models/google_AI" />
   <Card title="AWS bedrock" href="/components/llms/models/aws_bedrock" />
   <Card title="DeepSeek" href="/components/llms/models/deepseek" />
+  <Card title="MiniMax" href="/components/llms/models/minimax" />
   <Card title="xAI" href="/components/llms/models/xAI" />
   <Card title="Sarvam AI" href="/components/llms/models/sarvam" />
   <Card title="LM Studio" href="/components/llms/models/lmstudio" />

mem0/llms/minimax.py

@@ -34,13 +34,13 @@ class MiniMaxLLM(LLMBase):
         super().__init__(config)
 
         if not self.config.model:
-            self.config.model = "MiniMax-M2.1"
+            self.config.model = "MiniMax-M2.7"
 
         api_key = self.config.api_key or os.getenv("MINIMAX_API_KEY")
         base_url = (
             self.config.minimax_base_url
             or os.getenv("MINIMAX_API_BASE")
-            or "https://api.minimaxi.io/v1"
+            or "https://api.minimax.io/v1"
         )
         self.client = OpenAI(api_key=api_key, base_url=base_url)
 
@@ -103,6 +103,9 @@ class MiniMaxLLM(LLMBase):
             }
         )
 
+        if response_format:
+            params["response_format"] = response_format
+
         if tools:
             params["tools"] = tools
             params["tool_choice"] = tool_choice

tests/llms/test_minimax.py

@@ -20,11 +20,11 @@ def mock_minimax_client():
 def test_minimax_llm_default_base_url():
     """Default config uses MiniMax official base URL."""
     config = BaseLlmConfig(
-        model="MiniMax-M2.1", temperature=0.7, max_tokens=100, top_p=1.0, api_key="api_key"
+        model="MiniMax-M2.7", temperature=0.7, max_tokens=100, top_p=1.0, api_key="api_key"
     )
     llm = MiniMaxLLM(config)
     # OpenAI client may normalize URL with trailing slash
-    assert str(llm.client.base_url).rstrip("/") == "https://api.minimaxi.io/v1"
+    assert str(llm.client.base_url).rstrip("/") == "https://api.minimax.io/v1"
 
 
 def test_minimax_llm_env_base_url():
@@ -33,7 +33,7 @@ def test_minimax_llm_env_base_url():
     os.environ["MINIMAX_API_BASE"] = provider_base_url
     try:
         config = MinimaxConfig(
-            model="MiniMax-M2.1",
+            model="MiniMax-M2.7",
             temperature=0.7,
             max_tokens=100,
             top_p=1.0,
@@ -49,7 +49,7 @@ def test_minimax_llm_config_base_url():
     """Config uses minimax_base_url when provided."""
     config_base_url = "https://api.config.com/v1/"
     config = MinimaxConfig(
-        model="MiniMax-M2.1",
+        model="MiniMax-M2.7",
         temperature=0.7,
         max_tokens=100,
         top_p=1.0,
@@ -61,10 +61,10 @@ def test_minimax_llm_config_base_url():
 
 
 def test_minimax_llm_default_model(mock_minimax_client):
-    """Default model is MiniMax-M2.1 when not specified."""
+    """Default model is MiniMax-M2.7 when not specified."""
     config = MinimaxConfig(temperature=0.7, max_tokens=100, api_key="api_key")
     llm = MiniMaxLLM(config)
-    assert llm.config.model == "MiniMax-M2.1"
+    assert llm.config.model == "MiniMax-M2.7"
 
 
 def test_minimax_llm_env_api_key():
@@ -74,11 +74,11 @@ def test_minimax_llm_env_api_key():
         with patch("mem0.llms.minimax.OpenAI") as mock_openai:
             mock_client = Mock()
             mock_openai.return_value = mock_client
-            config = MinimaxConfig(model="MiniMax-M2.1", api_key=None)
+            config = MinimaxConfig(model="MiniMax-M2.7", api_key=None)
             MiniMaxLLM(config)
             mock_openai.assert_called_once_with(
                 api_key="env-api-key",
-                base_url="https://api.minimaxi.io/v1",
+                base_url="https://api.minimax.io/v1",
             )
     finally:
         os.environ.pop("MINIMAX_API_KEY", None)
@@ -87,7 +87,7 @@ def test_minimax_llm_env_api_key():
 def test_generate_response_without_tools(mock_minimax_client):
     """generate_response returns text when no tools provided."""
     config = BaseLlmConfig(
-        model="MiniMax-M2.1", temperature=0.7, max_tokens=100, top_p=1.0, api_key="api_key"
+        model="MiniMax-M2.7", temperature=0.7, max_tokens=100, top_p=1.0, api_key="api_key"
     )
     llm = MiniMaxLLM(config)
     messages = [
@@ -102,7 +102,7 @@ def test_generate_response_without_tools(mock_minimax_client):
     response = llm.generate_response(messages)
 
     mock_minimax_client.chat.completions.create.assert_called_once_with(
-        model="MiniMax-M2.1", messages=messages, temperature=0.7, max_tokens=100, top_p=1.0
+        model="MiniMax-M2.7", messages=messages, temperature=0.7, max_tokens=100, top_p=1.0
     )
     assert response == "I'm doing well, thank you for asking!"
 
@@ -110,7 +110,7 @@ def test_generate_response_without_tools(mock_minimax_client):
 def test_generate_response_with_tools(mock_minimax_client):
     """generate_response returns tool_calls when tools provided."""
     config = BaseLlmConfig(
-        model="MiniMax-M2.1", temperature=0.7, max_tokens=100, top_p=1.0, api_key="api_key"
+        model="MiniMax-M2.7", temperature=0.7, max_tokens=100, top_p=1.0, api_key="api_key"
     )
     llm = MiniMaxLLM(config)
     messages = [
@@ -147,7 +147,7 @@ def test_generate_response_with_tools(mock_minimax_client):
     response = llm.generate_response(messages, tools=tools)
 
     mock_minimax_client.chat.completions.create.assert_called_once_with(
-        model="MiniMax-M2.1",
+        model="MiniMax-M2.7",
         messages=messages,
         temperature=0.7,
         max_tokens=100,
@@ -162,8 +162,33 @@ def test_generate_response_with_tools(mock_minimax_client):
     assert response["tool_calls"][0]["arguments"] == {"data": "Today is a sunny day."}
 
 
+def test_generate_response_with_response_format(mock_minimax_client):
+    """generate_response passes response_format to the API."""
+    config = BaseLlmConfig(
+        model="MiniMax-M2.7", temperature=0.7, max_tokens=100, top_p=1.0, api_key="api_key"
+    )
+    llm = MiniMaxLLM(config)
+    messages = [{"role": "user", "content": "Return JSON."}]
+    response_format = {"type": "json_object"}
+
+    mock_response = Mock()
+    mock_response.choices = [Mock(message=Mock(content='{"key": "value"}'))]
+    mock_minimax_client.chat.completions.create.return_value = mock_response
+
+    llm.generate_response(messages, response_format=response_format)
+
+    mock_minimax_client.chat.completions.create.assert_called_once_with(
+        model="MiniMax-M2.7",
+        messages=messages,
+        temperature=0.7,
+        max_tokens=100,
+        top_p=1.0,
+        response_format={"type": "json_object"},
+    )
+
+
 def test_factory_creates_minimax_llm(mock_minimax_client):
     """LlmFactory.create returns MiniMaxLLM for provider 'minimax'."""
-    llm = LlmFactory.create("minimax", {"model": "MiniMax-M2.1", "api_key": "test-key"})
+    llm = LlmFactory.create("minimax", {"model": "MiniMax-M2.7", "api_key": "test-key"})
     assert isinstance(llm, MiniMaxLLM)
-    assert llm.config.model == "MiniMax-M2.1"
+    assert llm.config.model == "MiniMax-M2.7"