lattica-fhe-core 0.1.5

Lattica FHE Core Python Bindings

Lattica FHE Core

This repository contains the source code for the Lattica Client FHE SDK, which powers encrypted inference for AI workloads using Fully Homomorphic Encryption (FHE). The SDK provides a portable FHE implementation that compiles into a shared library used both by the Lattica Python and JS clients.

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🛠️ Build Instructions

Requirements

• Linux x86_64
• C++17-compatible compiler (e.g. g++ ≥ 9)
• CMake ≥ 3.14
• Python ≥ 3.8
• pybind11 (auto-handled via CMake)
• setuptools, wheel (for Python packaging)

Build Steps

git clone https://github.com/Lattica-ai/lattica_fhe_core.git
cd lattica_fhe_core-main

mkdir build && cd build
cmake -DPYTHON_ENABLED=ON ..
make -j 32

This will generate a Python extension shared library named like:

cpp_sdk.cpython-312-x86_64-linux-gnu.so

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▶️ Using This Build in the Lattica Client

To replace the binary distributed by lattica-query:

1. Install the query client as described here:
   👉 https://platformdocs.lattica.ai/how-to-guides/client-installation/how-to-install-query-client

2. Locate the installed .so file by running:

pip show -f lattica-fhe-core

3. Replace the installed cpp_sdk.*.so file with the one you built.

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📁 Project Structure

A detailed breakdown of the major components in this repository:

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src/encryption_schemes/

Implements the supported encryption schemes used by the Lattica client.

• Includes ckks, rbgv, and two GSW-like variants (*_g, *_g_crt) based on gadget matrix decompositions.
• Each scheme provides:
  • Encoding and decoding of plaintext data
  • Encryption and decryption procedures
  • Key generation, including auxiliary key-switching keys
• All cryptographic randomness is generated via Libsodium

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src/context_utils/

Provides utilities for interpreting and validating encryption context parameters.

• Parameters are received from the backend per model — they are not generated locally.
• Includes logic for:
  • Representing data in double-CRT form
  • Managing modulus chains and per-prime decompositions
  • Ensuring structural compatibility of runtime contexts

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src/homomorphic_operations/

Implements apply-clear versions of homomorphic operations.

• These simulate encrypted computation by applying the logic directly to plaintext inputs.
• Used only for client-side validation and debugging — no encrypted computation is performed here.
• Actual homomorphic execution is handled remotely by the Lattica backend.

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src/binding/python/

Defines the Python interface via pybind11.

• These four functions are exposed:
  1. py_generate_key(...)
  2. py_enc(...)
  3. py_dec(...)
  4. py_apply_client_block(...)

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src/encryption_scheme_utils/

Implements abstractions for representing and manipulating the structure of plaintext data.

• Defines the pt_shape object, which describes logical dimensions, padding, and layout

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src/tensor_engine/

Implements the core arithmetic and layout handling logic for encrypted and plaintext data.

• All data — including ciphertexts, plaintexts, and context elements — is represented as tensors
• Built on PyTorch tensor operations, with select extensions for FHE-specific requirements
• Includes custom kernels for modular arithmetic routines: addition, multiplication, NTT, inverse NTT

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src/serialization/

Handles serialization and deserialization of all major objects.

• Implemented using Protocol Buffers (protobuf)
• Supports efficient encoding of ciphertexts, plaintexts, keys, and context objects

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src/slot_permutation/

Implements coefficient permutations, supports both:

• Permutations in the coefficient basis
• Permutations in the CRT basis

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src/ (top-level)

• num.cpp: Implements multi-precision integer arithmetic
• toolkit_python.cpp: Entry point for the Python integration layer

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🔐 License

See LICENSE.txt for license details.

For support, please contact the Lattica team or consult internal documentation.