emilandClaude Opus 4.7
75c9ee4576
C++ core (libmemba.so): - include/memba/state.h — C API (state_new/free/save/load/get_size) - src/state.cpp — MEMB file format: magic, version, SHA-256 model_id, CRC-32, opaque llama_state_*_data() blob - src/cli.cpp — minimal demo binary with greedy sampler - CMakeLists.txt + build.sh with llama.cpp submodule, CUDA auto-detect Python SDK (memba): - core.py — file I/O via llama-cpp-python's exposed C functions, unwraps _LlamaContext to access raw context pointer (≥0.3.x) - session.py — high-level Session with auto-save/load, ChatML wrapper for instruct models, raw mode for base models - cli.py — typer-based: chat (REPL), run (one-shot), list, rm, info Examples: - 01_basic_save_load.py, 02_chat_session.py Experiments (throwaway POCs documenting product-direction findings): - recall_poc.py — git log → state → cross-process query - mood_poc.py — batch sentiment trajectory, Mamba vs Transformer - mood_stream_poc.py, mood_batch_poc.py — variants - diag_saveload.py — minimal save/load isolation test - README.md documents the headline finding: save/load is byte-identical, but Falcon-Mamba-7B-Instruct does not retain facts across conversation turns even in-process — limits viable products to single-prompt analysis and persona priming. Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
65 lines
1.9 KiB
TOML
65 lines
1.9 KiB
TOML
[build-system]
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requires = ["setuptools>=68", "wheel"]
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build-backend = "setuptools.build_meta"
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[project]
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name = "memba"
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version = "0.1.0"
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description = "Persistent memory layer for SSM-based LLMs (Falcon-Mamba, Zamba)"
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readme = "README.md"
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license = { text = "MIT" }
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requires-python = ">=3.10"
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keywords = ["llm", "ssm", "mamba", "falcon-mamba", "memory", "llama-cpp"]
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classifiers = [
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"Development Status :: 3 - Alpha",
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"Intended Audience :: Developers",
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"Intended Audience :: Science/Research",
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"License :: OSI Approved :: MIT License",
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"Programming Language :: Python :: 3",
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"Programming Language :: Python :: 3.10",
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"Programming Language :: Python :: 3.11",
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"Programming Language :: Python :: 3.12",
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"Topic :: Scientific/Engineering :: Artificial Intelligence",
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]
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dependencies = [
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"llama-cpp-python>=0.2.0",
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"typer>=0.9.0",
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"rich>=13.0.0",
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"pydantic>=2.0.0",
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]
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[project.optional-dependencies]
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dev = [
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"pytest>=7.0",
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"pytest-cov",
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"ruff",
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"mypy",
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]
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[project.scripts]
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memba = "memba.cli:main"
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[project.urls]
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Homepage = "https://github.com/your-org/memba"
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Repository = "https://github.com/your-org/memba"
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# ── Package discovery ────────────────────────────────────────────
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[tool.setuptools.packages.find]
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where = ["python"]
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# ── Ruff (linting) ───────────────────────────────────────────────
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[tool.ruff]
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line-length = 100
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target-version = "py310"
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[tool.ruff.lint]
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select = ["E", "F", "W", "I"]
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ignore = ["E501"]
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# ── Mypy ────────────────────────────────────────────────────────
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[tool.mypy]
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python_version = "3.10"
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ignore_missing_imports = true
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