feat: add MiniMax LLM provider support (M3 default)

README.md

@@ -77,12 +77,25 @@ You can configure `~/.metagpt/config2.yaml` according to the [example](https://g
 
 ```yaml
 llm:
-  api_type: "openai"  # or azure / ollama / groq etc. Check LLMType for more options
+  api_type: "openai"  # or azure / ollama / minimax / groq etc. Check LLMType for more options
   model: "gpt-4-turbo"  # or gpt-3.5-turbo
   base_url: "https://api.openai.com/v1"  # or forward url / other llm url
   api_key: "YOUR_API_KEY"
 ```
 
+<details>
+<summary>Example: Using MiniMax</summary>
+
+```yaml
+llm:
+  api_type: "minimax"
+  model: "MiniMax-M3"  # or MiniMax-M2.7 / MiniMax-M2.7-highspeed
+  base_url: "https://api.minimax.io/v1"
+  api_key: "YOUR_MINIMAX_API_KEY"
+  temperature: 0.5  # MiniMax requires temperature in (0.0, 1.0]
+```
+</details>
+
 ### Usage
 
 After installation, you can use MetaGPT at CLI

config/config2.example.yaml

@@ -127,3 +127,8 @@ models:
 #    # timeout: 600 # Optional. If set to 0, default value is 300.
 #    # Details: https://azure.microsoft.com/en-us/pricing/details/cognitive-services/openai-service/
 #    pricing_plan: "" # Optional. Use for Azure LLM when its model name is not the same as OpenAI's
+#  "MiniMax-M3":  # MiniMax (OpenAI-compatible) — default recommended model
+#    api_type: "minimax"
+#    base_url: "https://api.minimax.io/v1"
+#    api_key: "YOUR_MINIMAX_API_KEY"
+#    temperature: 0.5  # MiniMax requires temperature in (0.0, 1.0]

metagpt/configs/llm_config.py

@@ -44,6 +44,7 @@ class LLMType(Enum):
     BEDROCK = "bedrock"
     ARK = "ark"  # https://www.volcengine.com/docs/82379/1263482#python-sdk
     LLAMA_API = "llama_api"
+    MINIMAX = "minimax"
 
     def __missing__(self, key):
         return self.OPENAI

metagpt/provider/openai_api.py

@@ -53,6 +53,7 @@
         LLMType.SILICONFLOW,
         LLMType.OPENROUTER,
         LLMType.LLAMA_API,
+        LLMType.MINIMAX,
     ]
 )
 class OpenAILLM(BaseLLM):
@@ -149,6 +150,9 @@ def _cons_kwargs(self, messages: list[dict], timeout=USE_CONFIG_TIMEOUT, **extra
             # compatible to openai o1-series
             kwargs["temperature"] = 1
             kwargs.pop("max_tokens")
+        if self.config.api_type == LLMType.MINIMAX and kwargs.get("temperature", 0) <= 0:
+            # MiniMax requires temperature in (0.0, 1.0]
+            kwargs["temperature"] = 0.01
         if extra_kwargs:
             kwargs.update(extra_kwargs)
         return kwargs

metagpt/utils/token_counter.py

@@ -117,6 +117,9 @@
     "llama-4-Maverick-17B-128E-Instruct-FP8": {"prompt": 0.0, "completion": 0.0},
     "llama-3.3-8B-Instruct": {"prompt": 0.0, "completion": 0.0},
     "llama-3.3-70B-Instruct": {"prompt": 0.0, "completion": 0.0},  # end, for Llama API
+    "MiniMax-M3": {"prompt": 0.0006, "completion": 0.0024},  # start, for MiniMax
+    "MiniMax-M2.7": {"prompt": 0.0014, "completion": 0.007},
+    "MiniMax-M2.7-highspeed": {"prompt": 0.0014, "completion": 0.007},  # end, for MiniMax
 }
 
 
@@ -350,6 +353,9 @@
     "qwen-7b-chat": 32000,
     "qwen-1.8b-longcontext-chat": 32000,
     "qwen-1.8b-chat": 8000,
+    "MiniMax-M3": 512000,  # start, for MiniMax
+    "MiniMax-M2.7": 204000,
+    "MiniMax-M2.7-highspeed": 204000,  # end, for MiniMax
 }
 
 # For Amazon Bedrock US region