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XTraceAIEncrypted vector database for private AI memory and search
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XTraceAI/xtrace-sdk provides an open-source SDK for secure vector databases and AI agent memory, addressing data privacy concerns. It ensures documents and embedding vectors remain encrypted on the user's machine throughout storage and search operations on the XTrace server, enabling AI capabilities without compromising sensitive information.
How It Works
The SDK employs client-side encryption: documents are embedded locally, then vectors and text are encrypted using Paillier homomorphic encryption and AES-256, respectively. The secret key stays local. The XTrace server processes only ciphertexts, performing searches and returning encrypted results without ever accessing plaintext, ensuring zero-knowledge operations.
Quick Start & Requirements
Install via uv pip install xtrace-ai-sdk or uv pip install "xtrace-ai-sdk[embedding]". Requires Python 3.11+. Obtain an API key and org ID from app.xtrace.ai for the rate-limited free tier. Full documentation is at docs.xtrace.ai. The CLI (xtrace-ai-sdk[cli]) simplifies setup and search.
Highlighted Details
x-vec for encrypted vector search and x-mem for encrypted AI agent memory (upcoming).pytest tests/x_vec/) validate cryptographic primitives used in the SDK.Maintenance & Community
The README provides no specific details on contributors, sponsorships, or community channels (e.g., Discord/Slack). Assessment of community health and maintenance activity requires further repository investigation.
Licensing & Compatibility
Licensed under Apache 2.0, permitting commercial use and integration into closed-source applications.
Limitations & Caveats
The x-mem module for encrypted agent memory is currently in development ("coming soon"). The free tier is rate-limited, potentially affecting high-volume usage.
3 weeks ago
Inactive
tf-encrypted
nearai