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Core data retrieval and organisation library — SQLite DB, topic graph, corpus management, and LLM integration

Project description

eyecore

Core data retrieval and organisation library — SQLite DB management, topic graph, corpus management, and LLM integration.

Features

  • BaseDB — lazy SQLite connection with transparent .db.gz decompression to user cache
  • TopicGraph — generalized topic registry with parent/child relationships, BFS traversal, and typed links
  • CorpusManager — on-demand corpus checkout (Project Gutenberg, URL, git) with FTS5 indexing
  • LLMClient — lazy-loaded LLM wrapper with auto-detected backends (Ollama, llama-cpp, OpenAI-compatible)
  • compress_db / decompress_to_cache — platform-aware compression utilities for bake scripts

Installation

pip install eyecore

With optional extras:

pip install "eyecore[llm-ollama]"   # Ollama backend
pip install "eyecore[llm-cpp]"      # llama-cpp-python backend
pip install "eyecore[llm-openai]"   # OpenAI-compatible backend
pip install "eyecore[corpus]"       # corpus download support

Quick start

from pathlib import Path
from eyecore import BaseDB, TopicGraph, CorpusManager, LLMClient

# Lazy SQLite — decompresses .db.gz to user cache on first access
db = BaseDB("myapp", gz_path=Path("data/myapp.db.gz"))
rows = db.fetchall("SELECT * FROM entities LIMIT 10")

# Topic graph
graph = TopicGraph(db.conn)
related = graph.get_related("topic-id")
tree    = graph.subtree("root-id")

# LLM — auto-detects Ollama / llama-cpp / OpenAI
llm = LLMClient.get()
if llm.is_available():
    summary = llm.summarize("Some long text to summarize...")
    topics  = llm.extract_topics("Article text about AI and machine learning...")
    report  = llm.generate_report(articles, "Technology", "title", "summary")

LLM configuration

Configure via environment variables:

Variable Default Description
LLM_BACKEND auto ollama, llama-cpp, or openai
LLM_MODEL llama3 Model name (Ollama) or model ID (OpenAI)
LLM_HOST http://localhost:11434 Ollama server URL
LLM_MODEL_PATH Path to GGUF model file (llama-cpp)
OPENAI_API_KEY API key for OpenAI-compatible endpoints
OPENAI_BASE_URL Base URL for OpenAI-compatible endpoints

License

MIT — see LICENSE

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The following attestation bundles were made for eyecore-1.0.0-cp311-cp311-macosx_10_12_x86_64.whl:

Publisher: ci.yml on andrewkwatts-maker/EyeCore

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  • Download URL: eyecore-1.0.0-cp310-cp310-win_amd64.whl
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  • Size: 136.0 kB
  • Tags: CPython 3.10, Windows x86-64
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.1.0 CPython/3.13.12

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Hashes for eyecore-1.0.0-cp310-cp310-win_amd64.whl
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The following attestation bundles were made for eyecore-1.0.0-cp310-cp310-win_amd64.whl:

Publisher: ci.yml on andrewkwatts-maker/EyeCore

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Details for the file eyecore-1.0.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

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Hashes for eyecore-1.0.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
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Provenance

The following attestation bundles were made for eyecore-1.0.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl:

Publisher: ci.yml on andrewkwatts-maker/EyeCore

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

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