digital-twin-portfolio
Verified Safeby TheaMarieM
Overview
AI-powered portfolio acting as a digital twin, offering interactive querying, interview simulation, and RAG-driven semantic search of professional experiences via the Model Context Protocol (MCP) for AI assistants like Claude Desktop and VS Code Copilot.
Installation
python mcp/server.pyEnvironment Variables
- OPENAI_API_KEY
- GROQ_API_KEY
- UPSTASH_VECTOR_REST_URL
- UPSTASH_VECTOR_REST_TOKEN
- UPSTASH_VECTOR_INDEX
- UPSTASH_REDIS_REST_URL
- UPSTASH_REDIS_REST_TOKEN
- USE_LOCAL_EMBEDDINGS
- LOCAL_EMBEDDING_SERVICE_URL
- OLLAMA_URL
- OLLAMA_MODEL
- EMBEDDING_MODEL
- EMBEDDING_DIM
- MAX_HISTORY_MESSAGES
- SESSION_TTL_SECONDS
- LLM_PROVIDER
- OPENAI_CHAT_MODEL
Security Notes
The project demonstrates good security practices with explicit rate limiting (Redis-based for chat, in-memory for RAG as implemented in `app/api/rag/route.ts`), comprehensive input validation, and content filtering for sensitive information and prompt injections. It uses secure session ID generation and sets security headers on API responses. Environment variables are correctly used for secrets. The use of `json.loads` on external API responses carries inherent risk, but is standard practice when interacting with LLM/embedding services and is handled within `try-except` blocks. In-memory rate limiting for RAG in the Next.js backend could be a concern for multi-instance production deployments, which the README addresses by suggesting Redis for production.
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