Initial commit: AI Dungeon clone (FastAPI backend + React frontend)
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01KFsGHju9szibJJa2YJcdbg
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# AI D&D — Local AI Dungeon Clone: Plan Overview
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A locally hosted web app replicating AI Dungeon's core experience: scenarios, adventures,
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AI-driven storytelling, AI Dungeon-style memory/context management, JavaScript scripting
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(compatible with real AI Dungeon scripts), and full transparency into what is sent to the AI.
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## Confirmed decisions
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| Area | Decision |
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|---|---|
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| Backend | Python — FastAPI + SQLAlchemy + SQLite (single-user, local) |
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| Frontend | React SPA (Vite), dark AI Dungeon-like theme |
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| AI provider | Provider-agnostic adapter layer; first adapter: **OpenAI-compatible** (`/v1/chat/completions`) — covers Ollama, LM Studio, OpenAI, OpenRouter, vLLM, Groq. Endpoint URL, API key, model name all configurable at runtime. |
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| Scripting | **JavaScript, AI Dungeon-compatible** (`onInput` / `onModelContext` / `onOutput` modifiers, shared `state`, `worldEntries` API) via an embedded JS engine (quickjs / py-mini-racer). Real AI Dungeon scripts should import and run. |
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| Import/export | AI Dungeon-compatible formats for scripts and scenarios; JSON export/import for everything. |
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## Architecture at a glance
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```
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frontend/ React + Vite SPA ──HTTP/SSE──► backend/ FastAPI
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├─ routers/ (scenarios, adventures, actions, scripts, settings, insights)
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├─ models/ (SQLAlchemy: Scenario, Adventure, Action, StoryCard, Script, Settings)
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├─ context/ (prompt assembly: memory, author's note, world info, history budget)
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├─ scripting/ (JS sandbox, AI Dungeon API surface, per-adventure state)
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├─ providers/ (base adapter + openai_compatible.py; streaming)
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└─ data.db (SQLite)
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```
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## Core domain model
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- **Scenario** — template: title, description, opening prompt (with `${placeholders}`), memory,
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author's note, story cards (world info), attached scripts, tags.
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- **Adventure** — a playthrough created from a scenario (or blank). Owns its own copy of memory,
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author's note, story cards, script state, and the action list.
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- **Action** — one entry in the story: type (`do` / `say` / `story` / `continue` / AI output),
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text, timestamp, plus the **context snapshot** (exact prompt sent to the AI) for Insights.
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- **Story Card / World Info** — keys (comma-separated keywords), entry text, optional type/notes.
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Injected into context only when a key matches recent story text.
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- **Script** — JS source per hook (input / context / output modifier), attachable to scenarios;
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copied into adventures with persistent `state`.
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## The turn pipeline (heart of the app)
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```
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player input
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→ onInput script modifier
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→ store player action
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→ assemble context: [AI instructions] + [plot essentials] + [story summary]
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+ [triggered story cards ("World Lore:")] + [story history, token-budgeted]
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+ [author's note inserted N lines from the end] + [player action]
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→ onModelContext script modifier
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→ snapshot context (Insights)
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→ provider adapter → AI (streamed)
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→ onOutput script modifier
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→ store AI action → render
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```
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## Phases
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1. **[Phase 1 — Foundation](01-phase-foundation.md)**: repo scaffold, FastAPI + SQLite models,
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React shell, scenario/adventure CRUD, settings (endpoint config).
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2. **[Phase 2 — Play loop + AI](02-phase-play-loop.md)**: provider adapter with streaming,
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Do/Say/Story/Continue, Retry/Undo/Edit, the adventure play screen.
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3. **[Phase 3 — Context engine + Insights](03-phase-context-insights.md)**: memory, author's note,
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story cards with keyword triggering, token budgeting, per-turn prompt snapshots + Insights UI.
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4. **[Phase 4 — Scripting](04-phase-scripting.md)**: embedded JS sandbox, AI Dungeon scripting API,
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script editor, script + scenario import/export (AI Dungeon-compatible).
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5. **[Phase 5 — Polish](05-phase-polish.md)**: AI Dungeon-like theming pass, placeholders on
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scenario start, adventure export/import, quality-of-life and hardening.
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6. **[Phase 6 — Auto Summarization + Memory Bank](06-phase-memory-bank.md)** *(optional)*:
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modern AI Dungeon memory system — AI-generated memories every 6 actions, Story Summary every
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15, embedding-based retrieval of relevant memories into context.
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Each phase ends with the app runnable and testable end-to-end.
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