Phase 7: MIT license, portfolio README, Docker, cross-platform start
- LICENSE: MIT - README: rewritten as portfolio-grade docs (features with code pointers, architecture, Docker/Windows/macOS quick starts, BYO-model table) - Dockerfile (3-stage: SPA build, pip wheels, slim runtime) + compose with a /data volume; .dockerignore keeps secrets and local data out - database.py: AIDND_DB_PATH env override so deployments can relocate the SQLite file; documented in backend/.env.example - start.sh: macOS/Linux dev script with first-run setup Verified locally: production SPA build served by the backend (deep links OK), DB created at the override path. Docker image itself untested here (Docker not installed); flagged in plan/07. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01KFsGHju9szibJJa2YJcdbg
This commit is contained in:
co-authored by
Claude Fable 5
parent
466d7bc0e4
commit
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.git
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.claude
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plan
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*.md
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LICENSE
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start.ps1
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start.sh
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# Secrets & local data — never in the image
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*.env
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backend/openrouter_key.env
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*.db
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# Build/runtime artifacts rebuilt inside the image
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backend/.venv
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**/__pycache__
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**/*.pyc
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frontend/node_modules
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frontend/dist
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# Stage 1 — build the React SPA
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FROM node:22-alpine AS frontend-build
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WORKDIR /build
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COPY frontend/package.json frontend/package-lock.json ./
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RUN npm ci
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COPY frontend/ ./
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RUN npm run build
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# Stage 2 — build Python wheels (quickjs compiles from source if no wheel
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# matches, so keep the toolchain out of the final image)
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FROM python:3.12-slim AS python-build
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RUN apt-get update && apt-get install -y --no-install-recommends gcc make \
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&& rm -rf /var/lib/apt/lists/*
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COPY backend/requirements.txt /tmp/requirements.txt
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RUN pip wheel --no-cache-dir -r /tmp/requirements.txt -w /wheels
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# Stage 3 — runtime
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FROM python:3.12-slim
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WORKDIR /app
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COPY --from=python-build /wheels /wheels
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RUN pip install --no-cache-dir /wheels/* && rm -rf /wheels
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# Layout mirrors the repo: main.py finds the SPA at ../../frontend/dist
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# relative to backend/app/main.py.
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COPY backend/app /app/backend/app
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COPY --from=frontend-build /build/dist /app/frontend/dist
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# Database lives on a volume; parent dir is created by the app if missing.
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ENV AIDND_DB_PATH=/data/data.db
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VOLUME /data
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EXPOSE 8000
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WORKDIR /app/backend
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CMD ["uvicorn", "app.main:app", "--host", "0.0.0.0", "--port", "8000"]
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MIT License
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Copyright (c) 2026 Parth Thakkar
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Permission is hereby granted, free of charge, to any person obtaining a copy
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of this software and associated documentation files (the "Software"), to deal
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in the Software without restriction, including without limitation the rights
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to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
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copies of the Software, and to permit persons to whom the Software is
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furnished to do so, subject to the following conditions:
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The above copyright notice and this permission notice shall be included in all
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copies or substantial portions of the Software.
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THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
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IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
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FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
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AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
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LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
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OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
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SOFTWARE.
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# AI D&D — local AI Dungeon-style storytelling app
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# AI D&D
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Python (FastAPI + SQLite) backend, React (Vite) frontend, connectable to any
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OpenAI-compatible AI endpoint (Ollama, LM Studio, OpenAI, OpenRouter, …).
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An AI Dungeon-style interactive storytelling app you can run entirely on your own machine —
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with your own AI model. Create scenarios, play open-ended adventures where an LLM narrates the
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world, and extend the engine with **JavaScript scripts compatible with real AI Dungeon
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scripting**.
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Plan: see [`plan/00-OVERVIEW.md`](plan/00-OVERVIEW.md). Currently completed: **Phase 4** (AI Dungeon-compatible scripting).
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Built with FastAPI + SQLite on the backend and React (Vite) on the frontend. Works with **any
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OpenAI-compatible endpoint**: Ollama and LM Studio locally, or OpenRouter / OpenAI / Groq / vLLM
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in the cloud — endpoint, key, and model are all runtime settings, and OpenRouter's free-tier
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models make the whole experience $0.
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## Run
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> 📸 *Screenshots and a demo GIF are coming; for now the fastest tour is running it — one
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> command with Docker.*
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## Features
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- **The full play loop** — Do / Say / Story / Continue actions, streamed AI responses (SSE),
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retry, undo, and edit. Reasoning models supported: "thinking" streams into a collapsible 💭
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panel with its own token budget.
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- **AI Dungeon-compatible context engine** — memory, author's note, and story cards (world
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info) triggered by keywords in recent story text, assembled under a token budget
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(`backend/app/context/builder.py`).
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- **Insights: total prompt transparency** — every turn stores the exact prompt sent to the
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model; open 🔍 on any AI action to see each context component and why it was included.
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- **JavaScript scripting, AI Dungeon-compatible** — `onInput` / `onModelContext` / `onOutput`
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modifiers with shared `state` and a `worldEntries` API, executed in an embedded quickjs
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sandbox (`backend/app/scripting/`). Real AI Dungeon scripts import and run. In-app
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CodeMirror editor included.
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- **Auto-summarization + Memory Bank** — the modern AI Dungeon memory system: AI-generated
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memories every few actions, a running story summary, and embedding-based retrieval that
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pulls old-but-relevant facts back into context, with similarity scores visible in Insights
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(`backend/app/memorybank.py`).
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- **Import/export** — AI Dungeon-compatible formats for scripts and scenarios; JSON for
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everything.
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## Quick start
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### Docker (any OS)
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```sh
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docker compose up --build
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```
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Open http://localhost:8000. Your data persists in a named volume across restarts.
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### Windows
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```powershell
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cd backend; python -m venv .venv; .\.venv\Scripts\pip.exe install -r requirements.txt; cd ..
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cd frontend; npm install; cd ..
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.\start.ps1
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```
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Then open http://localhost:5173. Backend API docs at http://localhost:8000/docs.
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Open http://localhost:5173 (dev servers; API docs at http://localhost:8000/docs).
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Or manually, in two terminals:
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### macOS / Linux
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```powershell
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# Terminal 1 — backend
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cd backend
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.\.venv\Scripts\uvicorn.exe app.main:app --port 8000 --reload
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# Terminal 2 — frontend
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cd frontend
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npm run dev
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```sh
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./start.sh # creates the venv and installs dependencies on first run
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```
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## First-time setup
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Open http://localhost:5173.
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```powershell
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cd backend
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python -m venv .venv
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.\.venv\Scripts\pip.exe install -r requirements.txt
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## Connect a model
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cd ..\frontend
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npm install
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Open **Settings** in the app and point it at any OpenAI-compatible endpoint:
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| Provider | Endpoint URL | Notes |
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|---|---|---|
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| Ollama (local) | `http://localhost:11434/v1` | free, private; also serves embedding models for the Memory Bank (e.g. `nomic-embed-text`) |
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| LM Studio (local) | `http://localhost:1234/v1` | free, private |
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| OpenRouter | `https://openrouter.ai/api/v1` | `:free` models cost nothing (no embeddings on the free tier) |
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| OpenAI / Groq / vLLM / … | provider's `/v1` URL | anything speaking `/v1/chat/completions` |
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Model name, API key, generation parameters, and (optionally) summary/embedding models for the
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Memory Bank are all configured there too — no config files, no rebuild.
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## How a turn works
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```
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player input
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→ onInput script modifier
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→ assemble context: [AI instructions] + [plot essentials] + [story summary]
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+ [retrieved memories] + [triggered story cards]
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+ [story history, token-budgeted] + [author's note] + [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 & render
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```
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## Production-ish serving (single port)
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## Architecture
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Build the frontend, then the backend serves it statically:
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```powershell
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cd frontend
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npm run build
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# then run the backend and open http://localhost:8000
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```
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frontend/ React + Vite SPA ──HTTP/SSE──► backend/ FastAPI
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├─ routers/ scenarios, adventures, story cards, scripts, settings, debug
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├─ models.py SQLAlchemy: Scenario, Adventure, Action, StoryCard, Script, Settings, Memory
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├─ context/ prompt assembly under a token budget
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├─ scripting/ quickjs sandbox + AI Dungeon API surface
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├─ memorybank.py auto-summarization + embedding retrieval
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├─ providers/ OpenAI-compatible adapter, streaming
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└─ data.db SQLite (path overridable via AIDND_DB_PATH)
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```
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## Layout
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In production the backend serves the built SPA from one port (see `Dockerfile`); in
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development Vite proxies `/api` to FastAPI.
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- `backend/app/` — FastAPI app: `models.py` (SQLAlchemy), `schemas.py` (Pydantic), `routers/`
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- `backend/data.db` — SQLite database (created on first run)
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- `frontend/src/` — React SPA: `pages/`, `api.js`
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- `plan/` — phased implementation plan
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## Repo notes
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- `plan/` — the phased implementation plan this was built from, kept as a build log
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(phases 1–6 complete; 7–10 cover the public release).
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- `backend/.env.example` — the few environment variables the backend reads.
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- `CODE_REVIEW_FINDINGS.md` — notes from a self-review pass.
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## License
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[MIT](LICENSE)
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# Environment variables read by the backend.
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#
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# NOTE: the app reads real environment variables — it does NOT auto-load this
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# file. Set them in your shell, in docker-compose.yml, or in your host's
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# dashboard. This file is documentation (and a template for deploy configs).
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# Absolute path for the SQLite database file. Parent directory is created if
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# missing. Default when unset: backend/data.db
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# Docker compose sets this to /data/data.db (a named volume).
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AIDND_DB_PATH=
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# --- Coming in later phases (documented here as they land) ---
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# Phase 8/9 will add: SECRET_KEY, MULTI_USER, DEMO_API_KEY, DEMO_ENDPOINT_URL,
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# DEMO_MODEL_WHITELIST, DEMO_TURNS_PER_DAY, CORS_ORIGINS.
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#
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# The AI endpoint/API key/model are NOT env vars — they are configured at
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# runtime in the app's Settings page and stored in the database.
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+10
-1
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import os
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from pathlib import Path
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from sqlalchemy import create_engine, event
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from sqlalchemy.orm import DeclarativeBase, sessionmaker
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DB_PATH = Path(__file__).resolve().parent.parent / "data.db"
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# AIDND_DB_PATH lets deployments (Docker volume, hosted disk) relocate the
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# database; default stays backend/data.db for local runs.
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_env_db_path = os.environ.get("AIDND_DB_PATH")
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DB_PATH = (
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Path(_env_db_path).resolve()
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if _env_db_path
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else Path(__file__).resolve().parent.parent / "data.db"
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)
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DB_PATH.parent.mkdir(parents=True, exist_ok=True)
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engine = create_engine(
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f"sqlite:///{DB_PATH}",
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@@ -0,0 +1,11 @@
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services:
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ai-dnd:
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build: .
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ports:
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- "8000:8000"
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volumes:
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- ai-dnd-data:/data
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restart: unless-stopped
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volumes:
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ai-dnd-data:
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@@ -10,36 +10,42 @@ immediately usable on a resume — before any hosted-deployment work.
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| License | **MIT** |
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| README media (screenshots/GIF) | **Skip for now** — text-only README; visuals in a later pass |
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**Ask before implementing:** GitHub repo name (default suggestion: `ai-dnd`) and whether the
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existing local commit history/message is fine to publish as-is.
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**Repo name (decided): `AI-DnD`.** Ask before publishing: whether the existing commit
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history/messages are fine to publish as-is.
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## Repo hygiene
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- [ ] Add `LICENSE` (MIT, current year, Parth Thakkar).
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- [ ] Verify no secrets or user data are tracked (`openrouter_key.env`, `data.db` — already
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- [x] Add `LICENSE` (MIT, current year, Parth Thakkar).
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- [x] Verify no secrets or user data are tracked (`openrouter_key.env`, `data.db` — already
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gitignored and never committed; re-verify before push).
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- [ ] Add `backend/.env.example` documenting every env var the app reads (grows in Phase 9).
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- [ ] Decide what to do with `CODE_REVIEW_FINDINGS.md` and `plan/` — keep (shows process, good
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- [x] Add `backend/.env.example` documenting every env var the app reads (grows in Phase 9).
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(Currently just `AIDND_DB_PATH`, added to `database.py` for Docker/hosted volumes.)
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- [x] Decide what to do with `CODE_REVIEW_FINDINGS.md` and `plan/` — keep (shows process, good
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for a portfolio) — just give them a one-line mention in the README.
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## README rewrite (portfolio-grade, text-only)
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- [ ] Pitch paragraph: what it is, what makes it interesting (AI Dungeon-compatible scripting,
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- [x] Pitch paragraph: what it is, what makes it interesting (AI Dungeon-compatible scripting,
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memory bank with embeddings, full prompt transparency/Insights, provider-agnostic).
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- [ ] Feature list with pointers into the code (scripting engine, context builder, memory bank).
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- [ ] Architecture diagram (reuse/refresh the one in `plan/00-OVERVIEW.md`).
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- [ ] Setup instructions for **Windows (start.ps1), macOS/Linux (manual), and Docker**.
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- [ ] "Bring your own model" section: Ollama / LM Studio / OpenRouter free models — emphasize it
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- [x] Feature list with pointers into the code (scripting engine, context builder, memory bank).
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- [x] Architecture diagram (reuse/refresh the one in `plan/00-OVERVIEW.md`).
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- [x] Setup instructions for **Windows (start.ps1), macOS/Linux (manual), and Docker**.
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- [x] "Bring your own model" section: Ollama / LM Studio / OpenRouter free models — emphasize it
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runs fully free.
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- [ ] Placeholder section for screenshots/GIF (added in a later pass).
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- [x] Placeholder section for screenshots/GIF (added in a later pass).
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## Docker (one-command run for non-Windows users)
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- [ ] `Dockerfile`: multi-stage — build frontend (`npm run build`), then Python image serving
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- [x] `Dockerfile`: multi-stage — build frontend (`npm run build`), then Python image serving
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FastAPI with the built SPA mounted (SPA fallback already exists in `app/main.py`).
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- [ ] `docker-compose.yml`: single service, volume for `data.db`, port mapping.
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- [ ] `start.sh` for macOS/Linux dev parity with `start.ps1` (optional, nice-to-have).
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(3 stages: node build → pip wheel build with gcc for quickjs → slim runtime.)
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- [x] `docker-compose.yml`: single service, named volume mounted at `/data`
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(`AIDND_DB_PATH=/data/data.db`), port mapping.
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- [x] `start.sh` for macOS/Linux dev parity with `start.ps1` (optional, nice-to-have).
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- [ ] Test: `docker compose up` from a clean clone → app works at `http://localhost:8000`.
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**Blocked locally: Docker is not installed on the dev machine.** Verified without Docker:
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production frontend build + backend serving the SPA (deep links OK) + DB-path override
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all work. Test the image on any Docker machine (or let Render build it in Phase 10).
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## Publish
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@@ -0,0 +1,23 @@
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#!/usr/bin/env bash
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# macOS/Linux equivalent of start.ps1: backend (FastAPI, :8000) and frontend
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# dev server (Vite, :5173). Ctrl-C stops both.
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set -euo pipefail
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cd "$(dirname "$0")"
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if [ ! -d backend/.venv ]; then
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echo "First-time setup: creating backend/.venv and installing dependencies..."
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python3 -m venv backend/.venv
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backend/.venv/bin/pip install -r backend/requirements.txt
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fi
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if [ ! -d frontend/node_modules ]; then
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echo "First-time setup: npm install..."
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(cd frontend && npm install)
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fi
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(cd backend && .venv/bin/uvicorn app.main:app --port 8000 --reload) &
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BACKEND_PID=$!
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trap 'kill "$BACKEND_PID" 2>/dev/null' EXIT
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echo "Backend: http://localhost:8000 (API docs: http://localhost:8000/docs)"
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echo "Frontend: http://localhost:5173"
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cd frontend && npm run dev
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Reference in New Issue
Block a user