serversdown
ecf0b852f9
Derive a standing profile of the user from session gists and inject it into
every prompt, so identity/abstract questions ("what kind of player am I",
"what are my leaks") are answered from distilled knowledge instead of noisy
single-vector recall (which finds passages, not patterns).
- memory: profile table + get/set_profile, list_summaries
- lyra/profile.py: rebuild_profile map-reduces all gists (batch -> extract
durable facts -> fold-merge) into one profile doc; `lyra-profile` CLI
- chat.build_messages injects "What you know about Brian" after the persona
Run after lyra-summarize (needs gists). Verified (stubbed): map-reduce, storage,
and prompt injection.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
42 lines
793 B
TOML
42 lines
793 B
TOML
[project]
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name = "lyra"
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version = "0.1.0"
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description = "Persistent, autonomous AI assistant"
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readme = "README.md"
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requires-python = ">=3.11"
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dependencies = [
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"fastapi>=0.115",
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"httpx>=0.28.1",
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"numpy>=2.4.5",
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"openai>=2.37.0",
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"python-dotenv>=1.2.2",
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"uvicorn[standard]>=0.34",
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]
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[project.scripts]
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lyra = "lyra.__main__:main"
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lyra-web = "lyra.web.server:serve"
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lyra-import = "lyra.ingest:main"
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lyra-summarize = "lyra.summary:main"
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lyra-profile = "lyra.profile:main"
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[dependency-groups]
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dev = [
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"pytest>=8.0",
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"ruff>=0.6",
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]
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[build-system]
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requires = ["hatchling"]
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build-backend = "hatchling.build"
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[tool.hatch.build.targets.wheel]
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packages = ["lyra"]
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[tool.ruff]
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line-length = 100
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target-version = "py311"
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[tool.pytest.ini_options]
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testpaths = ["tests"]
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