Local-first research framework for evidence-grounded idea generation.
Project description
Principia V1.3
Principia V1.3 is a local-first Python framework for research search, paper feature extraction, evidence-grounded idea generation, and prior-idea comparison.
The import package is principia. The initial PyPI distribution name is principia-ai because the principia distribution name is currently occupied on PyPI. If that ownership issue is resolved later, the import API remains unchanged.
Install
pip install principia-ai
For notebooks:
pip install principia-ai ipykernel
python -m ipykernel install --user --name principia-v13-python --display-name "Python 3.12 (Principia V1.3)"
Quickstart
import principia as pc
API_key = "sk-your-key-here"
goal = "provide real-time, calibrated, actionable process quality control for autonomous coding agents operating on large-scale repositories"
ws = pc.Workspace(
"./principia_project",
llm_config=pc.siliconflow_config(API_key, timeout=420, max_retries=2),
)
works = ws.research.search(goal, target_count=50)
features = ws.research.extract(
works[:20],
model="siliconflow:deepseek-ai/DeepSeek-V4-Pro",
overwrite=False,
)
selected_evidence = pc.select_evidence(features)
idea = ws.ideas.generate(
selected_evidence,
user_note=goal,
mode="calculus",
model="siliconflow:Qwen/Qwen3.5-397B-A17B",
)
comparison = ws.ideas.compare(idea, features, model="siliconflow:Qwen/Qwen3.5-397B-A17B")
export_path = ws.export(
goal=goal,
works=works,
features=features,
idea=idea,
comparison=comparison,
)
Continue From Existing Features
If research and extraction already finished in an earlier notebook, reopen the same workspace and load persisted features:
import principia as pc
API_key = "sk-your-key-here"
goal = "your research goal"
ws = pc.Workspace("./principia_project", llm_config=pc.siliconflow_config(API_key))
features = ws.load_features()
selected_evidence = pc.select_evidence(features)
idea = ws.ideas.generate(
selected_evidence,
user_note=goal,
mode="calculus",
model="siliconflow:Qwen/Qwen3.5-397B-A17B",
)
This does not rerun public search or LLM extraction.
What Principia Provides
- Hybrid research search over OpenAlex, Crossref, and arXiv.
- DOI/arXiv/OpenAlex/title deduplication with peer-reviewed venue promotion.
- Structured extraction of ideas, principles, baselines, benchmarks, takeaways, and result facts.
- Evidence selection through
pc.select_evidence(...). - Idea generation modes:
standard,calculus, andscidialect_evo. - Generation modes are internal strategies, not evidence; generated
source_evidenceis grounded to selected work/feature IDs. - Prior-idea comparison using lexical shortlisting plus the configured LLM.
- Notebook and terminal progress with ETA, heartbeat updates during long LLM calls, cancellation, and resume-by-cache behavior.
- Local SQLite storage with visible user-facing exports.
Workspace Layout
Principia creates visible files under the workspace root:
principia_project/
README.md
principia_outputs/
latest/
idea.md
result.json
works.json
exports/
<idea_id>/
idea.md
result.json
works.json
.principia/
principia.sqlite
artifacts/
source_json/
exports/
pdfs/
cache/
The .principia/ folder stores internal SQLite state, cache data, and canonical artifacts. The visible principia_outputs/ folder mirrors the latest readable outputs for inspection.
Inspect and compact storage:
ws.storage_report()
ws.compact()
ws.compact() checkpoints and vacuums SQLite without deleting works, features, ideas, or exports. Optional cleanup knobs such as keep_source_json=1 and remove_cache=True only remove regenerable artifacts.
Tutorial And Docs
- Official tutorial notebook: examples/principia_v13_tutorial.ipynb
- Example setup notes: examples/README.md
- API reference: docs/api.md
- Publishing checklist: docs/publishing.md
The official tutorial contains no real API key and no executed outputs. Replace YOUR_SILICONFLOW_API_KEY at runtime in your own local copy.
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