Ideator

Ideator generates, scores, and visualizes idea graphs with OpenAI + Plotly. It prompts GPT for seed ideas, parses them into structured nodes, computes relationships/embeddings, and renders an interactive graph (saved to last_run_graph.html) with cluster + relationship legends.

Features

• Structured ideation: prompts GPT for 20 ideas with rationale, constraints, cost, time, risk, and prerequisites.
• Graph intelligence: embeds ideas, clusters them, types relationships, and computes graph-aware scores.
• Interactive visualization: Plotly graph with hover cards containing full idea metadata, relationship legends, and side-by-side node/edge keys.
• Planning support: optional diversity filtering and plan solver to pick a feasible subset under budget/time rules.

Quickstart

1. Install deps (recommend a venv):

pip install -r requirements.txt

2. Set environment values in .env:

OPENAI_API_KEY=sk-...
QUESTION="How might we ..."
TITLE="Ideas Graph"
TOP_K=3
USE_ENHANCED_TYPING=true
MODEL=gpt-4o-mini

3. Run the pipeline:

python demo.py

This will generate ideas, build the graph, and write last_run_graph.html for interactive viewing.

Outputs

• last_run_graph.html: interactive graph (Plotly).
• runs/: per-run logs of ideas, edges, labels, and plans.

Key files

• demo.py: entry point; drives ideation → graph build → Plotly render → optional diversity + planning.
• ideator.py: core graph construction, scoring, and optional Matplotlib visualization helpers.
• modules/gui/gui.py: Plotly figure builder with hover cards, legends, and styling.
• modules/node.py: parsing LLM output into Nodes with metadata/questions.
• modules/idea.py: safe conversion from Nodes to Idea objects used across the graph pipeline.

Notes

• Plotly is used for visualization (no Matplotlib GUI). Each run overwrites last_run_graph.html.
• If you change the prompt format, ensure modules/node.py still matches the expected fields.