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feat(llm): add MiniMax as a built-in provider

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Two regional endpoints (global api.minimax.io, China api.minimaxi.com)
with separate API keys. Models M2.7 / M2.5 plus -highspeed variants,
204K context. Follows the existing provider-preset pattern.

#789 #609 #577 #546 #395 #378
This commit is contained in:
Yijia-Xiao
2026-05-11 02:03:27 +00:00
parent 704b7627f2
commit 19d22b54a9
6 changed files with 35 additions and 3 deletions
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6
README.md
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@@ -144,6 +144,8 @@ export XAI_API_KEY=... # xAI (Grok)
export DEEPSEEK_API_KEY=... # DeepSeek
export DASHSCOPE_API_KEY=... # Qwen (Alibaba DashScope)
export ZHIPU_API_KEY=... # GLM (Zhipu)
export MINIMAX_API_KEY=... # MiniMax (global, api.minimax.io)
export MINIMAX_CN_API_KEY=... # MiniMax (China, api.minimaxi.com)
export OPENROUTER_API_KEY=... # OpenRouter
export ALPHA_VANTAGE_API_KEY=... # Alpha Vantage
```
@@ -184,7 +186,7 @@ An interface will appear showing results as they load, letting you track the age
### Implementation Details
We built TradingAgents with LangGraph to ensure flexibility and modularity. The framework supports multiple LLM providers: OpenAI, Google, Anthropic, xAI, DeepSeek, Qwen (Alibaba DashScope), GLM (Zhipu), OpenRouter, Ollama for local models, and Azure OpenAI for enterprise.
We built TradingAgents with LangGraph to ensure flexibility and modularity. The framework supports multiple LLM providers: OpenAI, Google, Anthropic, xAI, DeepSeek, Qwen (Alibaba DashScope), GLM (Zhipu), MiniMax (global + China), OpenRouter, Ollama for local models, and Azure OpenAI for enterprise.
### Python Usage
@@ -208,7 +210,7 @@ from tradingagents.graph.trading_graph import TradingAgentsGraph
from tradingagents.default_config import DEFAULT_CONFIG
config = DEFAULT_CONFIG.copy()
config["llm_provider"] = "openai" # openai, google, anthropic, xai, deepseek, qwen, glm, openrouter, ollama, azure
config["llm_provider"] = "openai" # openai, google, anthropic, xai, deepseek, qwen, glm, minimax, minimax-cn, openrouter, ollama, azure
config["deep_think_llm"] = "gpt-5.4" # Model for complex reasoning
config["quick_think_llm"] = "gpt-5.4-mini" # Model for quick tasks
config["max_debate_rounds"] = 2