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feat(llm): GLM dual-region split + catalog refresh

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Zhipu serves GLM under two brands with separate accounts (Z.AI
international vs BigModel China); the CLI URL pointed at one while
the openai_client default pointed at the other. Split into glm +
glm-cn with secondary region prompt (same UX as Qwen + MiniMax).
Catalog adds glm-5-turbo and glm-4.5-air per docs.z.ai.
This commit is contained in:
Yijia-Xiao
2026-05-11 04:19:50 +00:00
parent faaeebac70
commit d0dd0420ad
8 changed files with 72 additions and 17 deletions
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README.md
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@@ -142,8 +142,10 @@ export GOOGLE_API_KEY=... # Google (Gemini)
export ANTHROPIC_API_KEY=... # Anthropic (Claude)
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 DASHSCOPE_API_KEY=... # Qwen — International (dashscope-intl.aliyuncs.com)
export DASHSCOPE_CN_API_KEY=... # Qwen — China (dashscope.aliyuncs.com)
export ZHIPU_API_KEY=... # GLM via Z.AI (international)
export ZHIPU_CN_API_KEY=... # GLM via BigModel (China, open.bigmodel.cn)
export MINIMAX_API_KEY=... # MiniMax — Global (api.minimax.io, M2.x, 204K ctx)
export MINIMAX_CN_API_KEY=... # MiniMax — China (api.minimaxi.com, M2.x, 204K ctx)
export OPENROUTER_API_KEY=... # OpenRouter
@@ -186,7 +188,7 @@ 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), MiniMax (global + China), 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, international and China endpoints), GLM (Zhipu), MiniMax (global + China), OpenRouter, Ollama for local models, and Azure OpenAI for enterprise.
### Python Usage
@@ -210,7 +212,7 @@ 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, minimax, minimax-cn, openrouter, ollama, azure
config["llm_provider"] = "openai" # openai, google, anthropic, xai, deepseek, qwen, qwen-cn, glm, glm-cn, 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