Enhance LLM integration by adding OpenAI client support and enabling dynamic routing between DeepSeek and OpenAI services. Update environment configuration to include LLM_SERVICE_CODE for service selection, and modify API server to accommodate new request parameters for language and model. Implement streaming response improvements for chat interactions, allowing for segmented SSE output. Update documentation and impact analysis to reflect these changes.
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# 复制为 .env 并填入实际值
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# ========== DeepSeek API 配置 ==========
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DEEPSEEK_API_KEY=sk-2e3cc9f79a2c40e9a6b7c960d8c090d9
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# LLM 路由(deepseek | openai),不填则按 Key 自动选择(优先 deepseek)
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LLM_SERVICE_CODE=openai
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DEEPSEEK_API_KEY=sk-041b3995415c4445a1713750fcc9e023
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DEEPSEEK_BASE_URL=https://api.deepseek.com
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MODEL_PRIMARY=deepseek-chat
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OPENAI_API_KEY=sk-proj-FEb2ChHZK5Llm0tBkmNIT3BlbkFJbu0b0zQpTW8762yD6HDv
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OPENAI_BASE_URL=http://113.192.49.54:9080/v1
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OPENAI_MODEL=gpt-5.4
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# OPENAI_CHAT_MODEL=gpt-4o-mini
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# 模型配置
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# 主生成模型
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MODEL_PRIMARY=deepseek-chat
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TEMPERATURE=0 # 确定性模式:每次生成相同结果
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MAX_TOKENS=4096
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# 生成与校验默认 SQL Server(T-SQL);可改为 mysql / postgresql 等
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