Vibecode VidNotes

You are building a lean indie version of VidNotes.

Create the following project files first, then implement the application by following them. Keep the files updated as decisions change. Do not collapse this into a single README or prompt.

===== README.md =====
# VidNotes indie build

## Goal

Build the smallest trustworthy replacement for the core VidNotes workflow for one developer or a tiny team.

## Scope

Import a video file or YouTube URL, extract and transcribe its audio, generate structured study notes, search the timestamped transcript, and export the result.

## Quick start

1. Install the documented dependencies.
2. Copy `.env.example` to `.env`.
3. Run the development command chosen during implementation.
4. Complete the acceptance checks in `BUILD_PLAN.md`.

## Honest limits

This build deliberately does not replace:
- native iOS and Android apps, a Chrome extension, and cross-device Premium state
- managed extraction for TikTok, Instagram, Vimeo, and changing source sites
- background processing, queue reliability, and long-video handling
- 30+ language polish and prebuilt flashcards, quizzes, and chat
- hosted web, API, CLI, and MCP access for agents

If those capabilities are essential, use whisper.cpp instead of pretending the gap is solved.

===== AGENTS.md =====
# Agent instructions

- Optimize for a working, understandable weekend build.
- Prefer the fewest moving parts that satisfy the brief.
- Do not invent cryptography, security guarantees, APIs, or compliance claims.
- Keep secrets out of source control and logs.
- Add focused tests for destructive, security-sensitive, and data-loss paths.
- Run the project checks before declaring the build complete.
- Record any deliberate shortcut in the README under "Tradeoffs".

===== BUILD_PLAN.md =====
# Build plan

## Original build brief

Build me a local video transcription and study-notes app to replace VidNotes. Requirements:

- A Python 3.12 app using FastAPI, Jinja templates, HTMX, and SQLite FTS5,
  served only on localhost:8787.
- The home screen accepts one YouTube URL or an MP4, MOV, M4A, or MP3 upload;
  use yt-dlp for the URL and ffmpeg to extract mono audio.
- Use the OpenAI Python SDK for timestamped speech-to-text and the Responses API;
  keep the API key in .env and split large audio into chunks with preserved offsets.
- Show queued, extracting, transcribing, generating, complete, and failed states. The
  result page has a player plus a searchable transcript with clickable timestamps.
- Generate a 5-bullet summary, key points, 10 flashcards, and a 5-question quiz
  from the completed transcript, with a button to regenerate each section.
- Store metadata and generated text in SQLite, media under ./data/projects/<uuid>/,
  and export the transcript and notes as Markdown, TXT, SRT, and JSON.
- No accounts and no telemetry. Everything stays local except yt-dlp downloads and
  OpenAI API calls, and each project keeps its original source URL.
- Out of scope: native apps, hosted web, cross-device sync, the Chrome extension,
  Instagram or TikTok extraction, and a public API, CLI, or MCP server.
- Include a README with setup, ffmpeg and yt-dlp installation, .env.example, data
  location, deletion steps, and a warning that source-site changes can break imports.

## Required capabilities

- Python 3.12
- ffmpeg
- yt-dlp
- OpenAI API key
- local disk

## Delivery order

1. Scaffold the smallest runnable application and document its commands.
2. Implement the primary data model and core workflow.
3. Add validation, safe failure states, and persistence.
4. Cover the critical path with automated tests.
5. Exercise a clean install from the README and fix every missing step.

## Done when

- A new user can go from clone to first successful workflow using only the README.
- The core workflow works without paid infrastructure unless the brief requires it.
- Tests cover the highest-risk behavior.
- Known limitations are explicit rather than hidden.

===== .env.example =====
# Copy to .env and document every variable when it is introduced.
# Never put real credentials in this file.

APP_ENV=development
# Add only values required by the selected implementation.

You are building a lean indie version of VidNotes.

Create the following project files first, then implement the application by following them. Keep the files updated as decisions change. Do not collapse this into a single README or prompt.

===== README.md =====
# VidNotes indie build

## Goal

Build the smallest trustworthy replacement for the core VidNotes workflow for one developer or a tiny team.

## Scope

Import a video file or YouTube URL, extract and transcribe its audio, generate structured study notes, search the timestamped transcript, and export the result.

## Quick start

1. Install the documented dependencies.
2. Copy `.env.example` to `.env`.
3. Run the development command chosen during implementation.
4. Complete the acceptance checks in `BUILD_PLAN.md`.

## Honest limits

This build deliberately does not replace:
- native iOS and Android apps, a Chrome extension, and cross-device Premium state
- managed extraction for TikTok, Instagram, Vimeo, and changing source sites
- background processing, queue reliability, and long-video handling
- 30+ language polish and prebuilt flashcards, quizzes, and chat
- hosted web, API, CLI, and MCP access for agents

If those capabilities are essential, use whisper.cpp instead of pretending the gap is solved.

===== AGENTS.md =====
# Agent instructions

- Optimize for a working, understandable weekend build.
- Prefer the fewest moving parts that satisfy the brief.
- Do not invent cryptography, security guarantees, APIs, or compliance claims.
- Keep secrets out of source control and logs.
- Add focused tests for destructive, security-sensitive, and data-loss paths.
- Run the project checks before declaring the build complete.
- Record any deliberate shortcut in the README under "Tradeoffs".

===== BUILD_PLAN.md =====
# Build plan

## Original build brief

Build me a local video transcription and study-notes app to replace VidNotes. Requirements:

- A Python 3.12 app using FastAPI, Jinja templates, HTMX, and SQLite FTS5,
  served only on localhost:8787.
- The home screen accepts one YouTube URL or an MP4, MOV, M4A, or MP3 upload;
  use yt-dlp for the URL and ffmpeg to extract mono audio.
- Use the OpenAI Python SDK for timestamped speech-to-text and the Responses API;
  keep the API key in .env and split large audio into chunks with preserved offsets.
- Show queued, extracting, transcribing, generating, complete, and failed states. The
  result page has a player plus a searchable transcript with clickable timestamps.
- Generate a 5-bullet summary, key points, 10 flashcards, and a 5-question quiz
  from the completed transcript, with a button to regenerate each section.
- Store metadata and generated text in SQLite, media under ./data/projects/<uuid>/,
  and export the transcript and notes as Markdown, TXT, SRT, and JSON.
- No accounts and no telemetry. Everything stays local except yt-dlp downloads and
  OpenAI API calls, and each project keeps its original source URL.
- Out of scope: native apps, hosted web, cross-device sync, the Chrome extension,
  Instagram or TikTok extraction, and a public API, CLI, or MCP server.
- Include a README with setup, ffmpeg and yt-dlp installation, .env.example, data
  location, deletion steps, and a warning that source-site changes can break imports.

## Required capabilities

- Python 3.12
- ffmpeg
- yt-dlp
- OpenAI API key
- local disk

## Delivery order

1. Scaffold the smallest runnable application and document its commands.
2. Implement the primary data model and core workflow.
3. Add validation, safe failure states, and persistence.
4. Cover the critical path with automated tests.
5. Exercise a clean install from the README and fix every missing step.

## Done when

- A new user can go from clone to first successful workflow using only the README.
- The core workflow works without paid infrastructure unless the brief requires it.
- Tests cover the highest-risk behavior.
- Known limitations are explicit rather than hidden.

===== .env.example =====
# Copy to .env and document every variable when it is introduced.
# Never put real credentials in this file.

APP_ENV=development
# Add only values required by the selected implementation.

You are building a production product version of VidNotes.

Create the following project files first, then implement the application by following them. Keep the files updated as decisions change. Do not collapse this into a single README or prompt.

===== PRODUCT.md =====
# VidNotes product brief

## Problem

The narrow DIY loop is achievable in a weekend: import a file or YouTube URL, transcribe it, generate notes, and save the result locally. VidNotes as a product is broader than that prototype. It maintains ingestion across changing video sites, runs long jobs reliably, ships iOS, Android, web, and a Chrome extension, keeps account state consistent, and exposes the workflow to agents through an API, CLI, and MCP server. Rebuilding all of that is a multi-day integration project with an ongoing operations burden.

## Product outcome

Import a video file or YouTube URL, extract and transcribe its audio, generate structured study notes, search the timestamped transcript, and export the result.

## Target user

A serious builder who needs a maintainable product foundation rather than a one-off demo.

## Required capabilities

- Python 3.12
- ffmpeg
- yt-dlp
- OpenAI API key
- local disk

## Explicit non-goals for v1

- native iOS and Android apps, a Chrome extension, and cross-device Premium state
- managed extraction for TikTok, Instagram, Vimeo, and changing source sites
- background processing, queue reliability, and long-video handling
- 30+ language polish and prebuilt flashcards, quizzes, and chat
- hosted web, API, CLI, and MCP access for agents

## Success criteria

- The primary workflow is measurable end to end.
- Setup is reproducible in a clean environment.
- Failure, recovery, and support paths are documented.
- Product claims match what the implementation actually guarantees.

===== ARCHITECTURE.md =====
# Architecture

## Starting brief

Build me a local video transcription and study-notes app to replace VidNotes. Requirements:

- A Python 3.12 app using FastAPI, Jinja templates, HTMX, and SQLite FTS5,
  served only on localhost:8787.
- The home screen accepts one YouTube URL or an MP4, MOV, M4A, or MP3 upload;
  use yt-dlp for the URL and ffmpeg to extract mono audio.
- Use the OpenAI Python SDK for timestamped speech-to-text and the Responses API;
  keep the API key in .env and split large audio into chunks with preserved offsets.
- Show queued, extracting, transcribing, generating, complete, and failed states. The
  result page has a player plus a searchable transcript with clickable timestamps.
- Generate a 5-bullet summary, key points, 10 flashcards, and a 5-question quiz
  from the completed transcript, with a button to regenerate each section.
- Store metadata and generated text in SQLite, media under ./data/projects/<uuid>/,
  and export the transcript and notes as Markdown, TXT, SRT, and JSON.
- No accounts and no telemetry. Everything stays local except yt-dlp downloads and
  OpenAI API calls, and each project keeps its original source URL.
- Out of scope: native apps, hosted web, cross-device sync, the Chrome extension,
  Instagram or TikTok extraction, and a public API, CLI, or MCP server.
- Include a README with setup, ffmpeg and yt-dlp installation, .env.example, data
  location, deletion steps, and a warning that source-site changes can break imports.

## Boundaries

Separate the product into replaceable modules for interface, application logic, persistence, external integrations, and operational concerns. Keep domain logic independent from delivery frameworks and vendors.

## Production baseline

- Configuration: validated at startup with safe local defaults where possible.
- Security: least privilege, input validation, secret redaction, rate limits on abuse-prone paths, and no invented security primitives.
- Data: explicit schema and migrations, transactional writes where integrity matters, backup and restore instructions.
- Integrations: adapters around third-party providers, idempotent webhook or job processing, bounded retries, and timeouts.
- Observability: structured logs with request or operation IDs, an error-tracking hook, and health/readiness checks where a server exists.
- Quality: unit tests for domain rules, integration tests at module boundaries, and one end-to-end critical-path test.

## Decision records

For each major dependency, document why it was chosen, its failure mode, and how it can be replaced. Do not introduce infrastructure until a requirement justifies it.

===== AGENTS.md =====
# Agent instructions

- Read `PRODUCT.md` and `ARCHITECTURE.md` before changing code.
- Implement milestone by milestone; keep each change reviewable and leave the application runnable.
- Treat authentication, payments, encryption, imports, webhooks, and destructive actions as high-risk boundaries when present.
- Never invent cryptography or silently weaken a requirement to make a test pass.
- Use provider interfaces for external services and deterministic fakes in tests.
- Add migrations and rollback or recovery notes for persistent data changes.
- Log useful operational context without credentials, tokens, passwords, or personal data.
- Update documentation and run all checks before completing a milestone.

===== MILESTONES.md =====
# Delivery milestones

## M0 — Decisions and scaffold

- Confirm the runtime, persistence model, threat boundaries, and deployment target.
- Create a reproducible local environment and continuous checks.

## M1 — Core workflow

- Implement the smallest end-to-end product path with validation and tests.
- Keep integrations behind interfaces.

## M2 — Trust layer

- Add secure failure behavior, recovery paths, audit-relevant events, and data safeguards.
- Test abuse cases and destructive operations.

## M3 — Operability

- Add structured logs, error reporting hooks, health signals, backup/restore documentation, and deployment configuration.

## M4 — Release gate

- Run a clean-install test, critical-path end-to-end test, dependency review, and documented rollback exercise.
- Compare the shipped behavior with `PRODUCT.md` and publish remaining limitations.

===== OPERATIONS.md =====
# Operations

## Before release

- Validate configuration and secrets at startup.
- Define backup, restore, and rollback procedures and test them.
- Document logs, error tracking, health signals, and alert ownership.
- Set dependency update and vulnerability review expectations.

## Incident checklist

1. Contain the issue without destroying evidence or user data.
2. Record the timeline and affected scope.
3. Rotate exposed secrets and revoke compromised sessions or credentials.
4. Restore from a verified source when needed.
5. Document the root cause, remediation, and regression test.

## Launch constraint

Do not market omitted VidNotes capabilities as implemented. The v1 non-goals in `PRODUCT.md` remain user-visible limitations until they are deliberately delivered.

# VidNotes indie build

## Goal

Build the smallest trustworthy replacement for the core VidNotes workflow for one developer or a tiny team.

## Scope

Import a video file or YouTube URL, extract and transcribe its audio, generate structured study notes, search the timestamped transcript, and export the result.

## Quick start

1. Install the documented dependencies.
2. Copy `.env.example` to `.env`.
3. Run the development command chosen during implementation.
4. Complete the acceptance checks in `BUILD_PLAN.md`.

## Honest limits

This build deliberately does not replace:
- native iOS and Android apps, a Chrome extension, and cross-device Premium state
- managed extraction for TikTok, Instagram, Vimeo, and changing source sites
- background processing, queue reliability, and long-video handling
- 30+ language polish and prebuilt flashcards, quizzes, and chat
- hosted web, API, CLI, and MCP access for agents

If those capabilities are essential, use whisper.cpp instead of pretending the gap is solved.

# Agent instructions

- Optimize for a working, understandable weekend build.
- Prefer the fewest moving parts that satisfy the brief.
- Do not invent cryptography, security guarantees, APIs, or compliance claims.
- Keep secrets out of source control and logs.
- Add focused tests for destructive, security-sensitive, and data-loss paths.
- Run the project checks before declaring the build complete.
- Record any deliberate shortcut in the README under "Tradeoffs".

# Build plan

## Original build brief

Build me a local video transcription and study-notes app to replace VidNotes. Requirements:

- A Python 3.12 app using FastAPI, Jinja templates, HTMX, and SQLite FTS5,
  served only on localhost:8787.
- The home screen accepts one YouTube URL or an MP4, MOV, M4A, or MP3 upload;
  use yt-dlp for the URL and ffmpeg to extract mono audio.
- Use the OpenAI Python SDK for timestamped speech-to-text and the Responses API;
  keep the API key in .env and split large audio into chunks with preserved offsets.
- Show queued, extracting, transcribing, generating, complete, and failed states. The
  result page has a player plus a searchable transcript with clickable timestamps.
- Generate a 5-bullet summary, key points, 10 flashcards, and a 5-question quiz
  from the completed transcript, with a button to regenerate each section.
- Store metadata and generated text in SQLite, media under ./data/projects/<uuid>/,
  and export the transcript and notes as Markdown, TXT, SRT, and JSON.
- No accounts and no telemetry. Everything stays local except yt-dlp downloads and
  OpenAI API calls, and each project keeps its original source URL.
- Out of scope: native apps, hosted web, cross-device sync, the Chrome extension,
  Instagram or TikTok extraction, and a public API, CLI, or MCP server.
- Include a README with setup, ffmpeg and yt-dlp installation, .env.example, data
  location, deletion steps, and a warning that source-site changes can break imports.

## Required capabilities

- Python 3.12
- ffmpeg
- yt-dlp
- OpenAI API key
- local disk

## Delivery order

1. Scaffold the smallest runnable application and document its commands.
2. Implement the primary data model and core workflow.
3. Add validation, safe failure states, and persistence.
4. Cover the critical path with automated tests.
5. Exercise a clean install from the README and fix every missing step.

## Done when

- A new user can go from clone to first successful workflow using only the README.
- The core workflow works without paid infrastructure unless the brief requires it.
- Tests cover the highest-risk behavior.
- Known limitations are explicit rather than hidden.

# Copy to .env and document every variable when it is introduced.
# Never put real credentials in this file.

APP_ENV=development
# Add only values required by the selected implementation.

# VidNotes product brief

## Problem

The narrow DIY loop is achievable in a weekend: import a file or YouTube URL, transcribe it, generate notes, and save the result locally. VidNotes as a product is broader than that prototype. It maintains ingestion across changing video sites, runs long jobs reliably, ships iOS, Android, web, and a Chrome extension, keeps account state consistent, and exposes the workflow to agents through an API, CLI, and MCP server. Rebuilding all of that is a multi-day integration project with an ongoing operations burden.

## Product outcome

Import a video file or YouTube URL, extract and transcribe its audio, generate structured study notes, search the timestamped transcript, and export the result.

## Target user

A serious builder who needs a maintainable product foundation rather than a one-off demo.

## Required capabilities

- Python 3.12
- ffmpeg
- yt-dlp
- OpenAI API key
- local disk

## Explicit non-goals for v1

- native iOS and Android apps, a Chrome extension, and cross-device Premium state
- managed extraction for TikTok, Instagram, Vimeo, and changing source sites
- background processing, queue reliability, and long-video handling
- 30+ language polish and prebuilt flashcards, quizzes, and chat
- hosted web, API, CLI, and MCP access for agents

## Success criteria

- The primary workflow is measurable end to end.
- Setup is reproducible in a clean environment.
- Failure, recovery, and support paths are documented.
- Product claims match what the implementation actually guarantees.

# Architecture

## Starting brief

Build me a local video transcription and study-notes app to replace VidNotes. Requirements:

- A Python 3.12 app using FastAPI, Jinja templates, HTMX, and SQLite FTS5,
  served only on localhost:8787.
- The home screen accepts one YouTube URL or an MP4, MOV, M4A, or MP3 upload;
  use yt-dlp for the URL and ffmpeg to extract mono audio.
- Use the OpenAI Python SDK for timestamped speech-to-text and the Responses API;
  keep the API key in .env and split large audio into chunks with preserved offsets.
- Show queued, extracting, transcribing, generating, complete, and failed states. The
  result page has a player plus a searchable transcript with clickable timestamps.
- Generate a 5-bullet summary, key points, 10 flashcards, and a 5-question quiz
  from the completed transcript, with a button to regenerate each section.
- Store metadata and generated text in SQLite, media under ./data/projects/<uuid>/,
  and export the transcript and notes as Markdown, TXT, SRT, and JSON.
- No accounts and no telemetry. Everything stays local except yt-dlp downloads and
  OpenAI API calls, and each project keeps its original source URL.
- Out of scope: native apps, hosted web, cross-device sync, the Chrome extension,
  Instagram or TikTok extraction, and a public API, CLI, or MCP server.
- Include a README with setup, ffmpeg and yt-dlp installation, .env.example, data
  location, deletion steps, and a warning that source-site changes can break imports.

## Boundaries

Separate the product into replaceable modules for interface, application logic, persistence, external integrations, and operational concerns. Keep domain logic independent from delivery frameworks and vendors.

## Production baseline

- Configuration: validated at startup with safe local defaults where possible.
- Security: least privilege, input validation, secret redaction, rate limits on abuse-prone paths, and no invented security primitives.
- Data: explicit schema and migrations, transactional writes where integrity matters, backup and restore instructions.
- Integrations: adapters around third-party providers, idempotent webhook or job processing, bounded retries, and timeouts.
- Observability: structured logs with request or operation IDs, an error-tracking hook, and health/readiness checks where a server exists.
- Quality: unit tests for domain rules, integration tests at module boundaries, and one end-to-end critical-path test.

## Decision records

For each major dependency, document why it was chosen, its failure mode, and how it can be replaced. Do not introduce infrastructure until a requirement justifies it.

# Agent instructions

- Read `PRODUCT.md` and `ARCHITECTURE.md` before changing code.
- Implement milestone by milestone; keep each change reviewable and leave the application runnable.
- Treat authentication, payments, encryption, imports, webhooks, and destructive actions as high-risk boundaries when present.
- Never invent cryptography or silently weaken a requirement to make a test pass.
- Use provider interfaces for external services and deterministic fakes in tests.
- Add migrations and rollback or recovery notes for persistent data changes.
- Log useful operational context without credentials, tokens, passwords, or personal data.
- Update documentation and run all checks before completing a milestone.

# Delivery milestones

## M0 — Decisions and scaffold

- Confirm the runtime, persistence model, threat boundaries, and deployment target.
- Create a reproducible local environment and continuous checks.

## M1 — Core workflow

- Implement the smallest end-to-end product path with validation and tests.
- Keep integrations behind interfaces.

## M2 — Trust layer

- Add secure failure behavior, recovery paths, audit-relevant events, and data safeguards.
- Test abuse cases and destructive operations.

## M3 — Operability

- Add structured logs, error reporting hooks, health signals, backup/restore documentation, and deployment configuration.

## M4 — Release gate

- Run a clean-install test, critical-path end-to-end test, dependency review, and documented rollback exercise.
- Compare the shipped behavior with `PRODUCT.md` and publish remaining limitations.

# Operations

## Before release

- Validate configuration and secrets at startup.
- Define backup, restore, and rollback procedures and test them.
- Document logs, error tracking, health signals, and alert ownership.
- Set dependency update and vulnerability review expectations.

## Incident checklist

1. Contain the issue without destroying evidence or user data.
2. Record the timeline and affected scope.
3. Rotate exposed secrets and revoke compromised sessions or credentials.
4. Restore from a verified source when needed.
5. Document the root cause, remediation, and regression test.

## Launch constraint

Do not market omitted VidNotes capabilities as implemented. The v1 non-goals in `PRODUCT.md` remain user-visible limitations until they are deliberately delivered.

$ choose a build depth, inspect the files, then open the complete pack in your agent