{"repo": "azangalan/alan", "files": {"src/main/resources/application.properties": {"40753c1cb60611ceb5ee53de861ff10e2fc39009": {"t": 1785745398.538644, "n": 357, "h": "8bf308a0717b7e0e", "c": "spring.application.group=SpringBoot\n\n# ========== 大模型配置（由 AssistantFactory 读取）==========\n# DeepSeek（OpenAI 兼容协议）\napp.llm.deepseek.api-key=${DEEPSEEK_API_KEY}\napp.llm.deepseek.model-name=deepseek-chat\napp.llm.deepseek.base-url=https://api.deepseek.com/v1\n\n# 阿里云百炼 / 通义千问\napp.llm.dashscope.api-key=${DASHSCOPE_API_KEY}\n\n#启用日志debug级别\n#logging.level.root=debug\n"}, "ac29efab1b5694eb232958e6be1c71b9c84d05c4": {"t": 1785752559.514765, "n": 423, "h": "eac05e83fec0ee32", "c": "spring.application.group=SpringBoot\n#阿里百炼平台\nlangchain4j.community.dashscope.chat-model.api-key=sk-ws-H.EDEYLMH.iGL7.MEUCIQCs8-g9feEQ__DQu9nYIW0gA_z5Ejqruy7QF8Wb78TH9QIgeNKyTN5PADwXLp4JQl-EG8HD90Z8UNJ0tG1y2q65WRE\nlangchain4j.community.dashscope.chat-model.model-name=qwen3-max\n#请求和响应日志\nlangchain4j.open-ai.chat-model.log-requests=true\nlangchain4j.open-ai.chat-model.log-responses=true\n\n#启用日志debug级别\n#logging.level.root=debug"}, "99e2bcb45febb8209f1d7bdf3db3971c0361dd2b": {"t": 1785752562.3113396, "n": 327, "h": "844c1f684831a7fa", "c": "spring.application.group=SpringBoot\n#阿里百炼平台\nlangchain4j.community.dashscope.chat-model.api-key=${DASHSCOPE_API_KEY}\nlangchain4j.community.dashscope.chat-model.model-name=qwen3-max\n#请求和响应日志\nlangchain4j.open-ai.chat-model.log-requests=true\nlangchain4j.open-ai.chat-model.log-responses=true\n\n#启用日志debug级别\n#logging.level.root=debug"}, "35d05023d0f8ec1e4ecbb890d4c1c4825f0106a5": {"t": 1785752565.7309766, "n": 312, "h": "0f103af0dde2bb0e", "c": "spring.application.group=SpringBoot\n#阿里百炼平台\nlangchain4j.community.dashscope.chat-model.api-key=<KEY>\nlangchain4j.community.dashscope.chat-model.model-name=qwen3-max\n#请求和响应日志\nlangchain4j.open-ai.chat-model.log-requests=true\nlangchain4j.open-ai.chat-model.log-responses=true\n\n#启用日志debug级别\n#logging.level.root=debug"}}, "src/main/java/com/qcby/springbootmybatis/service/AssistantFactory.java": {"40753c1cb60611ceb5ee53de861ff10e2fc39009": {"t": 1786068305.893297, "n": 3664, "h": "fc9b0c3b8eadd9e1", "c": "package com.qcby.springbootmybatis.service;\n\nimport dev.langchain4j.community.model.dashscope.QwenChatModel;\nimport dev.langchain4j.community.model.dashscope.QwenStreamingChatModel;\nimport dev.langchain4j.model.chat.ChatModel;\nimport dev.langchain4j.model.chat.StreamingChatModel;\nimport dev.langchain4j.model.openai.OpenAiChatModel;\nimport dev.langchain4j.model.openai.OpenAiStreamingChatModel;\nimport dev.langchain4j.memory.chat.ChatMemoryProvider;\nimport dev.langchain4j.service.AiServices;\nimport org.springframework.beans.factory.annotation.Autowired;\nimport org.springframework.beans.factory.annotation.Value;\nimport org.springframework.stereotype.Component;\n\nimport java.util.Map;\nimport java.util.concurrent.ConcurrentHashMap;\n\n/**\n * 多模型工厂：根据前端传入的模型名，动态构建并缓存对应的 Assistant 实例。\n * 支持：\n *   - DeepSeek（OpenAI 兼容协议，deepseek-chat）\n *   - 阿里云百炼 / 通义千问（qwen-plus / qwen-max / qwen-turbo ...）\n * 记忆（chatMemoryProvider）在所有模型间共享，切换模型可无缝继续同一段对话。\n */\n@Component\npublic class AssistantFactory {\n\n    @Autowired\n    private ChatMemoryProvider chatMemoryProvider;\n\n    @Value(\"${app.llm.deepseek.api-key:${DEEPSEEK_API_KEY:}}\")\n    private String deepseekApiKey;\n    @Value(\"${app.llm.deepseek.model-name:deepseek-chat}\")\n    private String deepseekModelName;\n    @Value(\"${app.llm.deepseek.base-url:https://api.deepseek.com/v1}\")\n    private String deepseekBaseUrl;\n\n    @Value(\"${app.llm.dashscope.api-key:${DASHSCOPE_API_KEY:}}\")\n    private String dashscopeApiKey;\n\n    // 每个模型名 -> 对应的 Assistant 实例（懒加载 + 缓存，避免重复构建）\n    private final Map<String, Assistant> assistantCache = new ConcurrentHashMap<>();\n\n    private static final String DEFAULT_MODEL = \"deepseek-chat\";\n\n    public Assistant getAssistant(String model) {\n        if (model == null || model.isBlank()) {\n            model = DEFAULT_MODEL;\n        }\n        return assistantCache.computeIfAbsent(model, this::buildAssistant);\n    }\n\n    private StreamingChatModel buildStreamingChatModel(String model) {\n        if (model != null && model.startsWith(\"qwen\")) {\n            return QwenStreamingChatModel.builder().apiKey(dashscopeApiKey).modelName(model).build();\n        }\n        return OpenAiStreamingChatModel.builder()\n                .apiKey(deepseekApiKey).modelName(model != null ? model : \"deepseek-chat\")\n                .baseUrl(deepseekBaseUrl).build();\n    }\n\n    private Assistant buildAssistant(String model) {\n        ChatModel chatModel = buildChatModel(model);\n        return AiServices.builder(Assistant.class)\n                .chatModel(chatModel)\n                .chatMemoryProvider(chatMemoryProvider)\n                .streamingChatModel(buildStreamingChatModel(model))\n                .build();\n    }\n\n    private ChatModel buildChatModel(String model) {\n        // 阿里云百炼（通义千问）系列：以 qwen 开头\n        if (model != null && model.startsWith(\"qwen\")) {\n            return QwenChatModel.builder()\n                    .apiKey(dashscopeApiKey)\n                    .modelName(model)\n                    .build();\n        }\n        // 默认 / deepseek：走 OpenAI 兼容协议\n        if (model == null || model.isBlank() || \"deepseek-chat\".equals(model)) {\n            return OpenAiChatModel.builder()\n                    .apiKey(deepseekApiKey)\n                    .modelName(deepseekModelName)\n                    .baseUrl(deepseekBaseUrl)\n                    .logRequests(true)\n                    .logResponses(true)\n                    .build();\n        }\n        // 其他未知模型也走 OpenAI 兼容配置（可改 base-url 指向别家）\n        return OpenAiChatModel.builder()\n                .apiKey(deepseekApiKey)\n                .modelName(model)\n                .baseUrl(deepseekBaseUrl)\n                .build();\n\n    }\n}\n    "}}}}