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fix: address review feedback for the Minimax LLM provider

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This commit is contained in:
Himanshu-Sangshetti
2026-03-20 16:09:35 +05:30
parent 68ee4389cd
commit 839352b132
4 changed files with 101 additions and 16 deletions
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docs/components/llms/models/minimax.mdx
+56
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@@ -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
+1
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@@ -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
+5 -2
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@@ -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
+39 -14
View File
@@ -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"