70 lines
1.8 KiB
Markdown
70 lines
1.8 KiB
Markdown
# bmp-rewrite
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To install dependencies:
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```bash
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bun install
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bun run playwright:install
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```
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On a minimal Linux VPS, install Chromium's system libraries as well:
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```bash
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bun run playwright:install-deps
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```
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To run:
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```bash
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BMP_DEMO_PASSWORD="choose-a-long-client-demo-password" \
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OPENROUTER_API_KEY="..." \
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bun run index.ts
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```
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## Docker deployment
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Create a production env file:
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```bash
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cp .env.example .env
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```
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Set at least `BMP_DEMO_PASSWORD` and `OPENROUTER_API_KEY` in `.env`. For a public
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VPS with automatic HTTPS, also set:
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```bash
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APP_DOMAIN=demo.example.com
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```
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Then build and run the app behind Caddy:
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```bash
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docker compose up -d --build
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```
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Without `APP_DOMAIN`, Caddy serves the app on plain HTTP port 80 for local or
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private-network testing. With `APP_DOMAIN`, Caddy requests and renews TLS
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certificates automatically on ports 80 and 443.
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Generated extractor outputs, summarizer reports, and the editable template live
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in the `bmp_data` Docker volume. Caddy certificates live in `caddy_data`.
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The app is password-gated for demos. Set `BMP_DEMO_PASSWORD` before exposing it to
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any network. If it is omitted, the server prints a one-time password to the
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console for local development only.
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Security-related optional settings:
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```bash
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OPENROUTER_MODEL="openai/gpt-5.4-nano" # only this model is accepted by the API
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BMP_MAX_UPLOAD_BYTES=15728640 # default: 15 MB
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BMP_MAX_PDF_PAGES=35 # default: 35 pages
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BMP_MAX_ACTIVE_SUMMARY_JOBS=10 # default: 10 active LLM jobs
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```
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Protected surfaces include uploads, template save/load, summarizer jobs, result
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JSON, LLM trace metadata, and generated report downloads. Browser clients use a
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session cookie plus CSRF token for unsafe requests.
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This project was created using `bun init` in bun v1.3.2. [Bun](https://bun.com) is a fast all-in-one JavaScript runtime.
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