BOT050 Policy Graph
A policy knowledge-graph editor for qualitative policy research — a React Flow canvas backed by a FastAPI + DuckDB service with LLM-driven entity extraction.
BOT050 — Policy Graph is a policy knowledge-graph editor for qualitative policy research. It pairs a React Flow canvas (frontend package @bot050/ui) with a FastAPI service backed by DuckDB persistence and LLM-driven entity extraction.
What it does
- Manual graph editing — add entities and relationships on a canvas and edit their labels/properties in a side panel.
- LLM scene initialization — describe a policy scene in natural language (e.g. “商业保险支付链路中的主体和资金流”) and generate a starting graph.
- Single-document extraction — upload a policy document, run a Map-Reduce LLM extraction pass over its chunks, preview the result, and merge it into the scene.
- DuckDB-backed persistence behind a FastAPI + Swagger API, with a pluggable LLM provider (
glm/claude/openai).
Part of my pharma-policy research toolkit at PKU’s Dept. of Pharmacy Administration. Status: MVP implemented in standalone mode (manual editing, scene init, single-document extraction, preview, and merge); embedding into the Global Pharma Atlas dashboard (bot003) is post-MVP.
Stack: Python · FastAPI · DuckDB · React · React Flow · TypeScript
Repository: wcboy/BOT050