4693ebcf83
- Add package.json for project configuration and dependencies. - Create src/index.ts as the entry point for the MCP server. - Implement vectorStore for managing embeddings with local and cloud providers. - Add embeddingProviders for local and cloud-based embedding services (OpenAI, Aliyun, SiliconFlow). - Define types for prompts and embeddings in types.ts. - Implement searchPersona tool for semantic search of expert personas. - Create test.ts for validating vector storage and search functionality. - Configure TypeScript with tsconfig.json for strict type checking and module resolution.
54 lines
2.1 KiB
Plaintext
54 lines
2.1 KiB
Plaintext
# ============================================================
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# MCP RAG Prompts - Embedding 配置
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# 复制此文件为 .env 并填入你的配置
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# ============================================================
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# 选择 Embedding 提供者
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# 可选值: local | openai | aliyun | siliconflow
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EMBEDDING_PROVIDER=siliconflow
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# ============================================================
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# 本地模型配置 (provider=local)
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# ============================================================
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# 默认使用多语言模型，支持中英文
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# LOCAL_MODEL_NAME=Xenova/paraphrase-multilingual-MiniLM-L12-v2
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# 其他可选模型:
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# LOCAL_MODEL_NAME=Xenova/all-MiniLM-L6-v2 # 英文效果更好，体积更小
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# LOCAL_MODEL_NAME=Xenova/multilingual-e5-small # 多语言 E5 模型
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# ============================================================
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# OpenAI 配置 (provider=openai)
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# ============================================================
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# OPENAI_API_KEY=sk-xxxxxxxxxxxxxxxxxxxxxxxx
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# OPENAI_BASE_URL=https://api.openai.com/v1
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# OPENAI_EMBEDDING_MODEL=text-embedding-3-small
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# 可选模型:
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# text-embedding-3-small (1536维，便宜)
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# text-embedding-3-large (3072维，更精准)
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# text-embedding-ada-002 (1536维，旧版)
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# ============================================================
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# 阿里云百炼 DashScope 配置 (provider=aliyun)
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# ============================================================
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# DASHSCOPE_API_KEY=sk-xxxxxxxxxxxxxxxxxxxxxxxx
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# ALIYUN_EMBEDDING_MODEL=text-embedding-v3
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# 可选模型:
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# text-embedding-v3 (最新版，推荐)
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# text-embedding-v2 (旧版)
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# text-embedding-v1 (更旧)
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# ============================================================
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# SiliconFlow 硅基流动配置 (provider=siliconflow)
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# ============================================================
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SILICONFLOW_API_KEY=sk-fwemdoaytkxelpbjlnohiqvkeqjxxraoduadokrpvtynxoej
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SILICONFLOW_EMBEDDING_MODEL=Qwen/Qwen3-Embedding-8B
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# 可选模型 (开源模型，性价比高):
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# BAAI/bge-m3 # 多语言，效果很好
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# BAAI/bge-large-zh-v1.5 # 中文专用
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# BAAI/bge-large-en-v1.5 # 英文专用
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# nomic-ai/nomic-embed-text-v1.5 # 多语言
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