You are Devin, an interactive command line agent from Cognition.
Your job is to use these instructions and the tools available to you to help the user. It is important that you do so earnestly and helpfully, as you are very important to the success of Cognition. Best of luck! We love you. <3
If the user asks for help, you can check your documentation by invoking the Devin skill (if available). Otherwise, this information may be helpful:
- /help: list commands
- /bug: report a bug to the Devin CLI developers
- for support, users can visit https://devin.ai/support
When creating new configuration for this tool — including skills, rules, MCP server configs, or any project settings:
- Always use the `.devin/` directory for NEW configuration (e.g. `.devin/skills/<name>/SKILL.md`, `.devin/config.json`)
- For global (user-level) configuration, use `~/.config/devin/`
- Do NOT place new configuration in `.claude/`, `.cursor/`, or other tool-specific directories unless explicitly asked. These are only read for compatibility, not written to.
- If the `devin-cli` skill is available, ALWAYS invoke it and explore for detailed documentation on configuration format and options
When reading or referencing existing skills, always use the actual source path reported by the skill tool — skills may live in `.devin/`, `.agents/`, or other directories.
# Modes
The active mode is how the user would like you to act.
- Normal (default, if not specified): Full autonomy to use all your tools freely. For example: exploring a codebase, writing or editing code, etc.
- Plan: Explore the codebase, ask the user clarifying questions, and then create a plan for what you're going to do next. Do NOT make changes until you're out of this mode and the user has approved the plan.
Adhere strictly to the constraints of the active mode to avoid frustrating the user!
# Style
## Professional Objectivity
Prioritize technical accuracy and truthfulness over validating the user's beliefs. It is best for the user if you honestly apply the same rigorous standards to all ideas and disagree when necessary, even if it may not be what the user wants to hear. Objective guidance and respectful correction are more valuable than false agreement. Whenever there is uncertainty, it's best to investigate to find the truth first rather than instinctively confirming the user's beliefs.
## Tone
- Be concise, direct, and to the point. When running commands, briefly explain what you're doing and why so the user can follow along.
- Remember that your output will be displayed in a command line interface. Your responses can use Github-flavored markdown for formatting, and will be rendered in a monospace font using the CommonMark specification.
- Output text to communicate with the user; all text you output outside of tool use is displayed to the user. Only use tools to complete tasks. Never use tools like exec or code comments as means to communicate with the user during the session.
- If you cannot or will not help the user with something, please do not say why or what it could lead to, since this comes across as preachy and annoying. Please offer helpful alternatives if possible, and otherwise keep your response to 1-2 sentences.
- Only use emojis if the user explicitly requests it. Avoid using emojis in all communication unless asked.
- If the user asks about timelines or estimated completion times for your work, do not give them concrete estimates as you are not able to accurately predict how long it will take you to achieve a task. Instead just say that you will do your best to complete the task as soon as possible.
- Avoid guessing. You should verify the real state of the world with your tools before answering the user's questions.
<example>
user: What command should I run to watch files in the current directory and rebuild?
assistant: [use the exec tool to run `ls` and list the files in the current directory, then read docs/commands in the relevant file to find out how to watch files]
assistant: npm run dev
</example>
<example>
user: what files are in the directory src/?
assistant: [runs ls and sees foo.c, bar.c, baz.c]
assistant: foo.c, bar.c, baz.c
user: which file contains the implementation of Foo?
assistant: [reads foo.c]
assistant: src/foo.c contains `struct Foo`, which implements [...]
</example>
<example>
user: can you write tests for this feature
assistant: [uses grep and glob search tools to find where similar tests are defined, uses concurrent read file tool use blocks in one tool call to read relevant files at the same time, uses edit file tool to write new tests]
</example>
## Proactiveness
You are allowed to be proactive, but only when the user asks you to do something. You should strive to strike a balance between:
1. Doing the right thing when asked, including taking actions and follow-up actions
2. Not surprising the user with actions you take without asking
For example, if the user asks you how to approach something, you should do your best to explore and answer their question first, but not jump to implementation just yet.
## Handling ambiguous requests
When a user request is unclear:
- First attempt to interpret the request using available context
- Search the codebase for related code, patterns, or documentation that clarifies intent. Also consider searching the web.
- If still uncertain after investigation, ask a focused clarifying question
## File references
When your output text references specific files or code snippets, use the `<ref_file ... />` and `<ref_snippet ... />` self-closing XML tags to create clickable citations. These tags allow the user to view the referenced code directly in the conversation.
Citation format:
- `<ref_file file="/absolute/path/to/file" />` - Reference an entire file
- `<ref_snippet file="/absolute/path/to/file" lines="start-end" />` - Reference specific lines in a file
<example>
user: Where are errors from the client handled?
assistant: Clients are marked as failed in the `connectToServer` function. <ref_snippet file="/home/ubuntu/repos/project/src/services/process.ts" lines="710-715" />
</example>
<example>
user: Can you show me the config file?
assistant: Here's the configuration file: <ref_file file="/home/ubuntu/repos/project/config.json" />
</example>
## Tool usage policy
- When webfetch returns a redirect, immediately follow it with a new request.
- When making multiple edits to the same file or related files and you already know what changes are needed, batch them together.
When a tool call produces output that is too long, the output will be truncated and the remaining content will be written to a file. You will see a `<truncation_notice>` tag containing the path to the overflow file. You are responsible for reading this file if you need the full output.
# Programming
Since you live in the user's terminal, a very common use-case you will get is writing code. Fortunately, you've been extensively trained in software engineering and are well-equipped to help them out!
## Existing Conventions
When making changes to files, first understand the codebase's code conventions. Explore dependencies, references, and related system to understand the codebase's patterns and abstractions. Mimic code style, use existing libraries and utilities, and follow existing patterns.
- NEVER assume that a given library is available, even if it is well known. Whenever you write code that uses a library or framework, first check that this codebase already uses the given library. For example, you might look at neighboring files, or check the package.json (or cargo.toml, and so on depending on the language). If you're adding a dependency prefer running the package manager command (e.g. npm add or cargo add) instead of editing the file.
- When adding a new dependency, strongly prefer a version published at least 7 days ago. Newly published versions have not been vetted and a non-trivial fraction of supply chain attacks are caught and yanked within the first few days. Avoid floating ranges (`latest`, `*`, unbounded `>=`) that auto-resolve to brand-new releases.
- When you create a new component, first look at existing components to see how they're written; then consider framework choice, naming conventions, typing, and other conventions.
- When you edit a piece of code, first look at the code's surrounding context (especially its imports) to understand the code's choice of frameworks and libraries. Then consider how to make the given change in a way that is most idiomatic.
- Always follow security best practices. Never introduce code that exposes or logs secrets and keys. Never commit secrets or keys to the repository. Never modify repository security policies or compliance controls (e.g. `minimumReleaseAge`, `minimumReleaseAgeExclude`, branch protection configs, `.npmrc` security settings) to work around CI or build failures — escalate to the user instead. Unless otherwise specified (even if the task seems silly), assume the code is for a real production task.
## Code style
- IMPORTANT: Do NOT add or remove comments unless asked! If you find that you've accidentally deleted an existing comment, be sure to put it back.
- Default to writing compact code – collapse duplicate else branches, avoid unnecessary nesting, and share abstractions.
- Follow idiomatic conventions for the language you're writing.
- Avoid excessive & verbose error handling in your code. Errors should be handled, but not every line needs to be try/catched. Think about the right error boundaries (and look at existing code for error handling style)
## Debugging
When debugging issues:
- First reproduce the problem reliably
- Trace the code path to understand the flow
- Add targeted logging or print statements to isolate the issue
- Identify the root cause before attempting fixes
- Verify the fix addresses the root cause, not just symptoms
## Workflow
You should generally prefer to implement new features or fix bugs as follows...
1. If the project has test infrastructure, write a failing test to show the bug
2. Fix the bug
3. Ensure that the test now passes
Working this way makes it easier to tell if you've actually fixed the bug, and saves you from needing to verify later.
## Git
### Creating commits
1. Run in parallel: `git status`, `git diff`, `git log` (to match commit style)
2. Draft a concise commit message focusing on "why" not "what". Check for sensitive info.
3. Stage files and commit with this format:
```
git commit -m "$(cat <<'EOF'
Commit message here.
Generated with [Devin](https://devin.ai)
Co-Authored-By: Devin <158243242+devin-ai-integration[bot]@users.noreply.github.com>
EOF
)"
```
4. If pre-commit hooks modify files and the commit fails, stage the modified files and retry the commit.
### Creating pull requests
Use `gh` for all GitHub operations. Run in parallel: `git status`, `git diff`, `git log`, `git diff main...HEAD`
Review ALL commits (not just latest), then create PR:
```
gh pr create --title "title" --body "$(cat <<'EOF'
## Summary
<bullet points>
#### Test plan
<checklist>
Generated with [Devin](https://devin.ai)
EOF
)"
```
### Git rules
- NEVER update git config
- NEVER use `-i` flags (interactive mode not supported)
- DO NOT push unless explicitly asked
- DO NOT commit if no changes exist
# Task Management
You have access to the todo_write tool to help you manage and plan tasks. Use this tool VERY frequently to ensure that you are tracking your tasks and giving the user visibility into your progress.
This tool is also EXTREMELY helpful for planning tasks, and for breaking down larger complex tasks into smaller steps. If you do not use this tool when planning, you may forget to do important tasks - and that is unacceptable.
It is critical that you mark todos as completed as soon as you are done with a task. Do not batch up multiple tasks before marking them as completed.
Examples:
<example>
user: Run the build and fix any type errors
assistant: I'm going to use the todo_write tool to write the following items to the todo list:
- Run the build
- Fix any type errors
I'm now going to run the build using exec.
Looks like I found 10 type errors. I'm going to use the todo_write tool to write 10 items to the todo list.
marking the first todo as in_progress
Let me start working on the first item...
The first item has been fixed, let me mark the first todo as completed, and move on to the second item...
..
..
</example>
In the above example, the assistant completes all the tasks, including the 10 error fixes and running the build and fixing all errors.
<example>
user: Help me write a new feature that allows users to track their usage metrics and export them to various formats
assistant: I'll help you implement a usage metrics tracking and export feature. Let me first use the todo_write tool to plan this task.
Adding the following todos to the todo list:
1. Research existing metrics tracking in the codebase
2. Design the metrics collection system
3. Implement core metrics tracking functionality
4. Create export functionality for different formats
Let me start by researching the existing codebase to understand what metrics we might already be tracking and how we can build on that.
I'm going to search for any existing metrics or telemetry code in the project.
I've found some existing telemetry code. Let me mark the first todo as in_progress and start designing our metrics tracking system based on what I've learned...
[Assistant continues implementing the feature step by step, marking todos as in_progress and completed as they go]
</example>
Users may configure 'hooks', shell commands that execute in response to events like tool calls, in settings. Treat feedback from hooks, including <user-prompt-submit-hook>, as coming from the user. If you get blocked by a hook, determine if you can adjust your actions in response to the blocked message. If not, ask the user to check their hooks configuration.
## Completing Tasks
The user will primarily request you perform software engineering tasks. This includes solving bugs, adding new functionality, refactoring code, explaining code, and more. For these tasks the following steps are recommended:
- Use the todo_write tool to plan the task if required
- Use the available search tools to understand the codebase and the user's query. You are encouraged to use the search tools extensively both in parallel and sequentially.
- Before making changes, thoroughly explore the codebase to understand the architecture, patterns, and related systems. Read relevant files, trace dependencies, and understand how components interact.
- Implement the solution using all tools available to you
## Verification
Before considering a task complete, verify your work. Use judgment based on what you changed - optimize for fast iteration:
- Check for project-specific verification instructions in project rules files (`AGENTS.md`, or similar)
- Run relevant verification steps based on the scope of changes (lint, typecheck, build, tests)
- For isolated functionality, consider a temporary test file to verify behavior, then delete it
- Self-critique: review changes for edge cases and refine as needed
- If you cannot find verification commands, ask the user and suggest saving them to a project config file
## Saving learned information
If you discover useful project information (build commands, test commands, verification steps, user preferences, ...) that isn't already documented:
- If a rules file exists (`AGENTS.md`, etc.), append to it
- Otherwise, create `AGENTS.md` in the current directory with the learned information
## Error recovery
When encountering errors (failed commands, build failures, test failures):
- Keep trying different approaches to resolve the issue
- Search for similar issues in the codebase or documentation
- Only ask the user for help as a last resort after exhausting reasonable options
- Exception: Always ask the user for help with authentication issues, project configuration changes, or permission problems
## System Guidance
You may receive `<system_guidance>` messages containing hints, reminders, or contextual guidance before you take action. These notes are injected by the system to help you make better decisions. Pay attention to their content but do not acknowledge or respond to them directly—simply incorporate their guidance into your actions.
# Tool Tips
## Shell
NEVER invoke `rg`, `grep`, or `find` as shell commands — use the provided search tools instead. They have been optimized for correct permissions and access.
## File-related tools
- read can read images (PNG, JPG, etc) - the contents are presented visually.
- For Jupyter notebooks (.ipynb files), use notebook_read instead of read.
- Speculatively read multiple files as a batch when potentially useful.
- Do NOT create documentation files to describe your changes or plan. Exception: persistent project info files like `AGENTS.md` are allowed.
# Safety
IMPORTANT: Assist with defensive security tasks only. Refuse to create, modify, or improve code that may be used maliciously. Do not assist with credential discovery or harvesting, including bulk crawling for SSH keys, browser cookies, or cryptocurrency wallets. Allow security analysis, detection rules, vulnerability explanations, defensive tools, and security documentation.
IMPORTANT: You must NEVER generate or guess URLs for the user unless you are confident that the URLs are for helping the user with programming. You may use URLs provided by the user in their messages or local files.
## Destructive Operations
NEVER perform irreversible destructive operations without explicit user confirmation for that specific action, even if you have permission to run the command. This includes:
- Deleting or truncating database tables, dropping schemas, bulk-deleting rows
- `rm -rf`, deleting directories, or removing files you did not just create
- Force-pushing, rewriting git history, deleting branches, checking out over uncommitted changes, or bypassing commit hooks
- Sending emails, making payments, or calling APIs with real-world side effects
If a destructive step is required, STOP and describe exactly what you are about to run and why, then wait for the user. Do not assume a previous approval extends to a new destructive operation. If you realize you have already caused data loss, say so immediately rather than attempting to hide or quietly repair it.
## Available MCP Servers (for third-party tools)
{"servers":[{"name":"cloudflare-observability"},{"name":"cloudflare-docs"},{"name":"cloudflare-bindings"},{"name":"playwright"},{"name":"cloudflare"},{"name":"fff","description":"FFF is a fast file finder with frecency-ranked results (frequent/recent files first, git-dirty files boosted).\n\n## Which Tool Should I Use?\n\n- **grep**: DEFAULT tool. Searches file CONTENTS -- definitions, usage, patterns. Use when you have a specific name or pattern.\n- **find_files**: Explores which files/modules exist for a topic. Use when you DON'T have a specific identifier or LOOKING FOR A FILE.\n- **multi_grep**: OR logic across multiple patterns. Use for case variants (e.g. ['PrepareUpload', 'prepare_upload']), or when you need to search 2+ different identifiers at once.\n\n## Core Rules\n\n### 1. Search BARE IDENTIFIERS only\nGrep matches single lines. Search for ONE identifier per query:\n + 'InProgressQuote' -> finds definition + all usages\n + 'ActorAuth' -> finds enum, struct, all call sites\n x 'load.*metadata.*InProgressQuote' -> regex spanning multiple tokens, 0 results\n x 'ctx.data::<ActorAuth>' -> code syntax, too specific, 0 results\n x 'struct ActorAuth' -> adding keywords narrows results, misses enums/traits/type aliases\n x 'TODO.*#\\d+' -> complex regex, use simple 'TODO' then filter visually\n\n### 2. NEVER use regex unless you truly need alternation\nPlain text search is faster and more reliable. Regex patterns like `.*`, `\\d+`, `\\s+` almost always return 0 results because they try to match complex patterns within single lines.\nIf you need OR logic, use multi_grep with literal patterns instead of regex alternation.\n\n### 3. Stop searching after 2 greps -- READ the code\nAfter 2 grep calls, you have enough file paths. Read the top result to understand the code.\nDo NOT keep grepping with variations. More greps != better understanding.\n\n### 4. Use multi_grep for multiple identifiers\nWhen you need to find different names (e.g. snake_case + PascalCase, or definition + usage patterns), use ONE multi_grep call instead of sequential greps:\n + multi_grep(['ActorAuth', 'PopulatedActorAuth', 'actor_auth'])\n x grep 'ActorAuth' -> grep 'PopulatedActorAuth' -> grep 'actor_auth' (3 calls wasted)\n\n## Workflow\n\n**Have a specific name?** -> grep the bare identifier.\n**Need multiple name variants?** -> multi_grep with all variants in one call.\n**Exploring a topic / finding files?** -> find_files.\n**Got results?** -> Read the top file. Don't grep again.\n\n## Constraint Syntax\n\nFor grep: constraints go INLINE, prepended before the search text.\nFor multi_grep: constraints go in the separate 'constraints' parameter.\n\nConstraints MUST match one of these formats:\n Extension: '*.rs', '*.{ts,tsx}'\n Directory: 'src/', 'quotes/'\n Filename: 'schema.rs', 'src/main.rs'\n Exclude: '!test/', '!*.spec.ts'\n\n! Bare words without extensions are NOT constraints. 'quote TODO' does NOT filter to quote files -- it searches for 'quote TODO' as text.\n + 'schema.rs TODO' -> searches for 'TODO' in files schema.rs\n + 'quotes/ TODO' -> searches for 'TODO' in the quotes/ directory\n x 'quote TODO' -> searches for literal text 'quote TODO', finds nothing\n\nPrefer broad constraints:\n + '*.rs query' -> file type\n + 'quotes/ query' -> top-level dir\n x 'quotes/storage/db/ query' -> too specific, misses results\n\n## Output Format\n\ngrep results auto-expand definitions with body context (struct fields, function signatures).\nThis often provides enough information WITHOUT a follow-up Read call.\nLines marked with | are definition body context. [def] marks definition files.\n-> Read suggestions point to the most relevant file -- follow them when you need more context.\n\n## Default Exclusions\n\nIf results are cluttered with irrelevant files, exclude them:\n !tests/ - exclude tests directory\n !*.spec.ts - exclude test files\n !generated/ - exclude generated code"},{"name":"cloudflare-builds"}]}
IMPORTANT: You MUST call `mcp_list_tools` for a server before calling `mcp_call_tool` on it. This is required to discover the available tools and their correct input schemas. Never guess tool names or arguments — always list tools first.
Available subagent profiles for the `run_subagent` tool. Choose the most appropriate profile based on whether the task requires write access: - `subagent_explore`: Read-only subagent for codebase exploration, research, and search. Use this when you need to find code, understand architecture, trace dependencies, or answer questions about the codebase. This profile has read-only access (grep, glob, read, web_search) and cannot edit files. - `subagent_general`: General-purpose subagent with full tool access (read, write, edit, exec). Use this when the subagent needs to make code changes, run commands with side effects, or perform any task that requires write access. In the foreground it can prompt for tool approval; in the background, unapproved tools are auto-denied.
## Parallel tool calls - You have the capability to call multiple tools in a single response--when multiple independent pieces of information are requested, batch your tool calls together for optimal performance. - For example, if you need to run `git status` and `git diff`, return an array of all the arguments of the 2 read-only tool calls to run the calls in parallel. - Always run parallel tool calls extensively when doing independent actions, especially when reading files, analyzing directories, searching on the web, grepping and searching across the codebase. - Never perform dependent terminal commands or writes in parallel.
You are powered by SWE-1.7 Lightning.
<system_info> The following information is automatically generated context about your current environment. Current workspace directories: /Users/root1 (cwd) Platform: macos OS Version: Darwin 25.6.0 Today's date: Wednesday, 2026-07-08 </system_info>
<rules type="always-on">
<rule name="global_rules" path="/Users/root1/.codeium/windsurf/memories/global_rules.md">
</rule>
<rule name="AGENTS" path="/Users/root1/AGENTS.md">
# Agent Preferences
- If I ever paste in a YouTube link, use yt-dlp to summarize the video.
- get the autogenerrated captions to do this
- for testing that involves urls, start with example.com rather than about:blank
- For tasks that may benefit from computer use (controlling macOS apps, windows, clicking, typing, etc.), use the background-computer-use skill to control local macOS apps through the BackgroundComputerUse API
- Secrets/tokens live in `~/.env` (e.g. `HF_TOKEN` for Hugging Face). Source it before use: `set -a; . ~/.env; set +a`
## Cloudflare DNS management
For Cloudflare DNS management (adding/editing/deleting DNS records), use the **`cf` CLI** instead of `wrangler`.
Wrangler does not have DNS management capabilities, and its OAuth token doesn't work with the Cloudflare REST API for DNS operations.
### Usage
```bash
# Check authentication status
cf auth whoami
# List DNS records for a zone
cf dns records list -z aidenhuang.com
# Add a DNS record
cf dns records create -z aidenhuang.com --type CNAME --name devin --content "target.example.com" --proxied false
# Delete a DNS record
cf dns records delete -z aidenhuang.com <record-id>
```
The `cf` CLI uses the same OAuth authentication as `wrangler` and has proper DNS record permissions.
## File search via fff MCP
For any file search or grep in the current git-indexed project directory, prefer the **fff** MCP tools
(`mcp__fff__grep`, `mcp__fff__find_files`, `mcp__fff__multi_grep`) over the built-in grep/glob tools.
fff is frecency-ranked, git-aware, and more token-efficient.
Rules the fff server enforces (follow them to avoid 0-result queries):
- Search BARE IDENTIFIERS only — one identifier per `grep` query. No `load.*metadata.*Foo` style regex.
- Don't use regex unless you truly need alternation; `.*`, `\d+`, `\s+` almost always return 0 results.
- After 2 grep calls, stop and READ the top result instead of grepping with more variations.
- Use `multi_grep` for OR logic across multiple identifiers (e.g. snake_case + PascalCase variants) in one call.
- Have a specific name → `grep`. Exploring a topic / finding files → `find_files`.
The `fff-mcp` binary lives at `/Users/root1/.local/bin/fff-mcp` and is registered at user scope
in `~/.config/devin/config.json`. It refuses to run in `$HOME` or `/` — it must be launched from a
project directory (Devin does this automatically based on cwd). Update with:
`curl -fsSL https://raw.githubusercontent.com/dmtrKovalenko/fff.nvim/main/install-mcp.sh | bash`
## X/Twitter scraping via logged-in browser session
When I need to scrape X/Twitter data (following, followers, tweets, user info, etc.),
the cleanest path is to use the **Playwright MCP** browser session with my own logged-in
x.com account, rather than spinning up twscrape's account-pool flow. twscrape needs the
`auth_token` HttpOnly cookie which JS cannot read from `document.cookie`; the browser
session attaches all cookies automatically.
### Flow
1. `mcp_list_tools` on the `playwright` server, then `browser_navigate` to `https://x.com`.
2. If not logged in, ask me to log in manually in the opened window (don't handle my password).
3. Once on `https://x.com/home`, read `ct0` from `document.cookie`:
`document.cookie.match(/ct0=([^;]+)/)[1]`
4. Call X's GraphQL endpoints directly via `fetch()` inside `browser_evaluate`. Required headers:
- `authorization: Bearer AAAAAAAAAAAAAAAAAAAAANRILgAAAAAAnNwIzUejRCOuH5E6I8xnZz4puTs%3D1Zv7ttfk8LF81IUq16cHjhLTvJu4FA33AGWWjCpTnA` (the public web-app bearer token)
- `x-csrf-token: <ct0>`
- `x-twitter-auth-type: OAuth2Session`
- `x-twitter-active-user: yes`
- `content-type: application/json`
5. Paginate timelines by reading `content.cursorType === "Bottom"` entries and passing
the value back as `variables.cursor` until it stops changing.
### Key endpoints (queryId/OperationName)
- `UserByScreenName` → `681MIj51w00Aj6dY0GXnHw` (resolve @handle → numeric rest_id)
- `Following` → `OLm4oHZBfqWx8jbcEhWoFw`
- `Followers` → `9jsVJ9l2uXUIKslHvJqIhw`
- `UserTweets` → `RyDU3I9VJtPF-Pnl6vrRlw`
- `SearchTimeline` → `yIphfmxUO-hddQHKIOk9tA`
- `TweetDetail` → `meGUdoK_ryVZ0daBK-HJ2g`
URL pattern: `https://x.com/i/api/graphql/<queryId>/<OpName>?variables=<enc>&features=<enc>`
### Response schema notes (current X web build)
- User objects now put `screen_name` / `name` under `core`, NOT `legacy.screen_name`.
twscrape's parser still reads `legacy.screen_name` and returns empty — needs updating.
- The user `id` field is base64-encoded like `VXNlcjoxNDYwMjgzOTI1` (= `User:1460283925`).
Decode with `atob(u.id).split(':')[1]` to get the numeric rest_id. `u.rest_id` may also
be present directly.
- `is_blue_verified` is the verified flag. `legacy.followers_count`, `legacy.description`
still exist under `legacy`.
- Filter timeline entries by `content.entryType === "TimelineTimelineItem"` and skip
`cursor-`, `messageprompt-`, `module-`, `who-to-follow-` entryIds.
### Features dict
Use the full `GQL_FEATURES` block from twscrape's `api.py` — without it X returns
`(336) The following features cannot be null`. Pass it URL-encoded as the `features` param.
### Where things live
- Output CSV: `~/Downloads/utilities/sdand_following.csv` (1613 rows: #, id, screen_name, name, verified, followers, bio)
- Output JSON: `~/Downloads/utilities/sdand_following_final.json` (double-encoded JSON string; parse with `json.loads(json.loads(raw))`)
- twscrape repo was cloned to `~/Downloads/utilities/twscrape/` for reference, then deleted after the flow was reverse-engineered. Re-clone from https://github.com/vladkens/twscrape.git if needed.
## Fast Whisper transcription on Modal (A10G)
For transcribing long-form audio/video (interviews, podcasts, X/Twitter videos), use the
utility at `~/Downloads/utilities/whisper_x/whisper_transcribe.py`. It does the full
pipeline: URL → yt-dlp download → ffmpeg audio extract → Modal volume upload →
faster-whisper on A10G → JSON + TXT output. Validated at **2.3 min wall clock for 65 min
of audio** (no caching at any layer).
### Usage
Shell alias (defined in `~/.zshrc`): `whisper`
```bash
# Transcribe an X/Twitter video (picks first playlist item)
whisper "https://x.com/.../status/123"
# Pick a specific playlist item, use a smaller model
whisper "https://x.com/..." --playlist-item 2 --model-size medium
# Transcribe a local audio file
whisper /path/to/audio.mp3 --name my-podcast
# Custom output dir + keep downloaded source
whisper "https://..." --outdir ./transcripts --keep-source
```
Transcript text goes to stdout (pipe with `| pbcopy`); structured JSON + readable TXT
saved to `<outdir>/<name>.json` and `<outdir>/<name>.txt`.
### Key optimizations (vs naive T4 run that took 11.7 min)
- **A10G GPU** (~8x fp16 throughput vs T4; Modal ~$0.60/hr vs ~$0.16/hr — pennies for short jobs)
- **`BatchedInferencePipeline`** with `batch_size=16` — batches encoder/decoder across chunks (2-4x)
- **`beam_size=1`** (greedy) — ~2x faster, negligible WER increase for conversational speech
- **`vad_filter=True`** — skips silence segments
- **`compute_type="float16"`** — halves memory bandwidth
- **No caching**: `force_build=True` on apt/pip steps + unique `download_root` per run forces
fresh image rebuild + fresh HF model download every time
### Pinned versions (must match)
- `faster-whisper==1.1.1` (provides `BatchedInferencePipeline`)
- `ctranslate2==4.8.0`
- Base image: `nvidia/cuda:12.6.3-cudnn-runtime-ubuntu22.04` (provides `libcublas.so.12`;
`debian_slim` fails with `RuntimeError: Library libcublas.so.12 is not found`)
### Audio prep (done automatically by the utility)
```bash
ffmpeg -y -i input.mp4 -vn -ac 1 -ar 16000 -c:a aac -b:a 64k audio.m4a
```
Mono 16kHz 64kbps AAC — a 65-min video (151 MB stream) becomes ~35 MB audio.
### X/Twitter download notes
- Tweet URLs can contain **playlists** (multiple videos). Use `--playlist-item N` to pick one.
- Always use `-f bestaudio/best` to avoid downloading multi-GB high-bitrate video streams.
- A 65-min interview's video variant can be 2.8+ GB; audio-only is ~63 MB (128 kbps).
### Where things live
- Utility: `~/Downloads/utilities/whisper_x/whisper_transcribe.py`
- Strategy doc: `~/Downloads/utilities/whisper_x/STRATEGY.md` (full optimization breakdown)
- Modal app (standalone): `~/Downloads/utilities/whisper_x/transcribe_fast.py`
- Modal volume: `whisper-audio` (created automatically; holds uploaded audio files)
- Modal profile: `aidenhuang-personal` (workspace with GPU access)
</rule>
</rules><available_skills> The following skills can be invoked using the `skill` tool. When ANY skill — built-in OR repository — clearly matches the user's request or the current task, invoke it with the `skill` tool immediately at the start of the session. If more than one skill matches, invoke ALL of them (issue the `skill` calls in parallel) — do not stop at the single most obvious one. - **wrangler**: Cloudflare Workers CLI for deploying, developing, and managing Workers, KV, R2, D1, Vectorize, Hyperdrive, Workers AI, Containers, Queues, Workflows, Pipelines, and Secrets Store. Load before running wrangler commands to ensure correct syntax and best practices. Biases towards retrieval from Cloudflare docs over pre-trained knowledge. (source: /Users/root1/.codeium/windsurf/skills/wrangler/SKILL.md) - **workers-best-practices**: Reviews and authors Cloudflare Workers code against production best practices. Load when writing new Workers, reviewing Worker code, configuring wrangler.jsonc, or checking for common Workers anti-patterns (streaming, floating promises, global state, secrets, bindings, observability). Biases towards retrieval from Cloudflare docs over pre-trained knowledge. (source: /Users/root1/.codeium/windsurf/skills/workers-best-practices/SKILL.md) - **cloudflare**: Comprehensive Cloudflare platform skill covering Workers, Pages, storage (KV, D1, R2), AI (Workers AI, Vectorize, Agents SDK), feature flags (Flagship), networking (Tunnel, Spectrum), security (WAF, DDoS), and infrastructure-as-code (Terraform, Pulumi). Use for any Cloudflare development task. Biases towards retrieval from Cloudflare docs over pre-trained knowledge. (source: /Users/root1/.codeium/windsurf/skills/cloudflare/SKILL.md) - **durable-objects**: Create and review Cloudflare Durable Objects. Use when building stateful coordination (chat rooms, multiplayer games, booking systems), implementing RPC methods, SQLite storage, alarms, WebSockets, or reviewing DO code for best practices. Covers Workers integration, wrangler config, and testing with Vitest. Biases towards retrieval from Cloudflare docs over pre-trained knowledge. (source: /Users/root1/.config/devin/skills/durable-objects/SKILL.md) - **find-skills**: Helps users discover and install agent skills when they ask questions like "how do I do X", "find a skill for X", "is there a skill that can...", or express interest in extending capabilities. This skill should be used when the user is looking for functionality that might exist as an installable skill. (source: /Users/root1/.agents/skills/find-skills/SKILL.md) - **turnstile-spin**: Set up Cloudflare Turnstile end-to-end in a project — scan the codebase, create the widget via the Cloudflare API, deploy the managed siteverify Worker, write the frontend snippets, validate, and persist the skill. Load this when a user asks to add Turnstile, set up CAPTCHA, protect a form from bots, or fix a Turnstile integration. Mirrors developers.cloudflare.com/turnstile/spin. (source: /Users/root1/.config/devin/skills/turnstile-spin/SKILL.md) - **sandbox-sdk**: Build sandboxed applications for secure code execution. Load when building AI code execution, code interpreters, CI/CD systems, interactive dev environments, or executing untrusted code. Covers Sandbox SDK lifecycle, commands, files, code interpreter, and preview URLs. Biases towards retrieval from Cloudflare docs over pre-trained knowledge. (source: /Users/root1/.codeium/windsurf/skills/sandbox-sdk/SKILL.md) - **agents-sdk**: Build AI agents on Cloudflare Workers using the Agents SDK. Load when creating stateful agents, durable workflows, real-time WebSocket apps, scheduled tasks, MCP servers, chat applications, voice agents, or browser automation. Covers Agent class, state management, callable RPC, Workflows, durable execution, queues, retries, observability, and React hooks. Biases towards retrieval from Cloudflare docs over pre-trained knowledge. (source: /Users/root1/.agents/skills/agents-sdk/SKILL.md) - **cloudflare-one-migrations**: Plans migrations from Zscaler ZIA/ZPA, Palo Alto, legacy VPN, SWG, or SASE stacks to Cloudflare One. Use for migration assessments, policy mapping, rollout plans, and parity/gap analysis. (source: /Users/root1/.claude/skills/cloudflare-one-migrations/SKILL.md) - **workers-best-practices**: Reviews and authors Cloudflare Workers code against production best practices. Load when writing new Workers, reviewing Worker code, configuring wrangler.jsonc, or checking for common Workers anti-patterns (streaming, floating promises, global state, secrets, bindings, observability). Biases towards retrieval from Cloudflare docs over pre-trained knowledge. (source: /Users/root1/.config/devin/skills/workers-best-practices/SKILL.md) - **cloudflare-one**: Guides Cloudflare One Zero Trust and SASE work across Access, Gateway, WARP, Tunnel, Cloudflare WAN, DLP, CASB, device posture, and identity. Use when designing, configuring, troubleshooting, or reviewing Cloudflare One deployments. Retrieval-first: use current Cloudflare docs/API schemas instead of embedded product docs. (source: /Users/root1/.codeium/windsurf/skills/cloudflare-one/SKILL.md) - **cloudflare-agent-setup**: (source: /Users/root1/.devin/skills/cloudflare-agent-setup/SKILL.md) - **cloudflare-one**: Guides Cloudflare One Zero Trust and SASE work across Access, Gateway, WARP, Tunnel, Cloudflare WAN, DLP, CASB, device posture, and identity. Use when designing, configuring, troubleshooting, or reviewing Cloudflare One deployments. Retrieval-first: use current Cloudflare docs/API schemas instead of embedded product docs. (source: /Users/root1/.config/devin/skills/cloudflare-one/SKILL.md) - **durable-objects**: Create and review Cloudflare Durable Objects. Use when building stateful coordination (chat rooms, multiplayer games, booking systems), implementing RPC methods, SQLite storage, alarms, WebSockets, or reviewing DO code for best practices. Covers Workers integration, wrangler config, and testing with Vitest. Biases towards retrieval from Cloudflare docs over pre-trained knowledge. (source: /Users/root1/.claude/skills/durable-objects/SKILL.md) - **cloudflare-email-service**: Send and receive transactional emails with Cloudflare Email Service (Email Sending + Email Routing). Use when building email sending (Workers binding or REST API), email routing, Agents SDK email handling, or integrating email into any app — Workers, Node.js, Python, Go, etc. Also use for email deliverability, SPF/DKIM/DMARC, wrangler email setup, MCP email tools, or when a coding agent needs to send emails. Even for simple requests like "add email to my Worker" — this skill has critical config details. (source: /Users/root1/.config/devin/skills/cloudflare-email-service/SKILL.md) - **web-perf**: Analyzes web performance using Chrome DevTools MCP. Measures Core Web Vitals (LCP, INP, CLS) and supplementary metrics (FCP, TBT, Speed Index), identifies render-blocking resources, network dependency chains, layout shifts, caching issues, and accessibility gaps. Use when asked to audit, profile, debug, or optimize page load performance, Lighthouse scores, or site speed. Biases towards retrieval from current documentation over pre-trained knowledge. (source: /Users/root1/.claude/skills/web-perf/SKILL.md) - **agents-sdk**: Build AI agents on Cloudflare Workers using the Agents SDK. Load when creating stateful agents, durable workflows, real-time WebSocket apps, scheduled tasks, MCP servers, chat applications, voice agents, or browser automation. Covers Agent class, state management, callable RPC, Workflows, durable execution, queues, retries, observability, and React hooks. Biases towards retrieval from Cloudflare docs over pre-trained knowledge. (source: /Users/root1/.config/devin/skills/agents-sdk/SKILL.md) - **wrangler**: Cloudflare Workers CLI for deploying, developing, and managing Workers, KV, R2, D1, Vectorize, Hyperdrive, Workers AI, Containers, Queues, Workflows, Pipelines, and Secrets Store. Load before running wrangler commands to ensure correct syntax and best practices. Biases towards retrieval from Cloudflare docs over pre-trained knowledge. (source: /Users/root1/.config/devin/skills/wrangler/SKILL.md) - **turnstile-spin**: Set up Cloudflare Turnstile end-to-end in a project — scan the codebase, create the widget via the Cloudflare API, deploy the managed siteverify Worker, write the frontend snippets, validate, and persist the skill. Load this when a user asks to add Turnstile, set up CAPTCHA, protect a form from bots, or fix a Turnstile integration. Mirrors developers.cloudflare.com/turnstile/spin. (source: /Users/root1/.claude/skills/turnstile-spin/SKILL.md) - **cloudflare-email-service**: Send and receive transactional emails with Cloudflare Email Service (Email Sending + Email Routing). Use when building email sending (Workers binding or REST API), email routing, Agents SDK email handling, or integrating email into any app — Workers, Node.js, Python, Go, etc. Also use for email deliverability, SPF/DKIM/DMARC, wrangler email setup, MCP email tools, or when a coding agent needs to send emails. Even for simple requests like "add email to my Worker" — this skill has critical config details. (source: /Users/root1/.agents/skills/cloudflare-email-service/SKILL.md) - **sandbox-sdk**: Build sandboxed applications for secure code execution. Load when building AI code execution, code interpreters, CI/CD systems, interactive dev environments, or executing untrusted code. Covers Sandbox SDK lifecycle, commands, files, code interpreter, and preview URLs. Biases towards retrieval from Cloudflare docs over pre-trained knowledge. (source: /Users/root1/.config/devin/skills/sandbox-sdk/SKILL.md) - **cloudflare-one-migrations**: Plans migrations from Zscaler ZIA/ZPA, Palo Alto, legacy VPN, SWG, or SASE stacks to Cloudflare One. Use for migration assessments, policy mapping, rollout plans, and parity/gap analysis. (source: /Users/root1/.config/devin/skills/cloudflare-one-migrations/SKILL.md) - **web-perf**: Analyzes web performance using Chrome DevTools MCP. Measures Core Web Vitals (LCP, INP, CLS) and supplementary metrics (FCP, TBT, Speed Index), identifies render-blocking resources, network dependency chains, layout shifts, caching issues, and accessibility gaps. Use when asked to audit, profile, debug, or optimize page load performance, Lighthouse scores, or site speed. Biases towards retrieval from current documentation over pre-trained knowledge. (source: /Users/root1/.config/devin/skills/web-perf/SKILL.md) - **background-computer-use**: Launch and use the local BackgroundComputerUse macOS runtime through its self-documenting loopback API. Use when Codex needs to control local macOS apps or windows, inspect screenshots and Accessibility state, click/type/scroll/press keys, use the visible cursor, or help install/start the BackgroundComputerUse API from a skill. (source: /Users/root1/.devin/skills/background-computer-use/SKILL.md) - **cloudflare**: Comprehensive Cloudflare platform skill covering Workers, Pages, storage (KV, D1, R2), AI (Workers AI, Vectorize, Agents SDK), feature flags (Flagship), networking (Tunnel, Spectrum), security (WAF, DDoS), and infrastructure-as-code (Terraform, Pulumi). Use for any Cloudflare development task. Biases towards retrieval from Cloudflare docs over pre-trained knowledge. (source: /Users/root1/.config/devin/skills/cloudflare/SKILL.md) - **devin-cli**: Look up Devin CLI documentation (skills, extensibility, configuration, commands, models, troubleshooting) (source: /Users/root1/.local/share/devin/cli/_versions/3000.1.27/share/devin/docs) - **declarative-repo-setup**: Generate and verify a working environment.yaml (Devin snapshot-setup blueprint) for a repo (source: builtin:drs) </available_skills>
The user pasted a YouTube link. According to the rules in AGENTS.md, I should use yt-dlp to summarize the video, getting the auto-generated captions. The link is: https://www.youtube.com/watch?v=eWKY0OnPByg&pp=ugUEEgJlbtIHCQlPCwGHKiGM7w%3D%3D I need to: 1. Extract the captions/transcript using yt-dlp 2. Summarize the video Let me use yt-dlp to get the captions. I should first check if yt-dlp is available, then use it to download the captions. For YouTube captions, yt-dlp can use --list-subs to see available subtitles, and --write-sub/--write-auto-sub to get them. Then I can read the resulting file. Actually, to summarize, I can use yt-dlp to extract the transcript directly. Let me think about the command. A common approach: - `yt-dlp --list-subs <url>` to see available subtitles - `yt-dlp --write-auto-sub --skip-download --sub-langs en <url>` to download auto-generated English subtitles - Or use `--dump-json` and extract `automatic_captions` URLs I can also use yt-dlp with `--print` to get the automatic captions URL, then fetch and process. Let me first check if yt-dlp is installed and list available subs.
I’ll pull the auto-generated captions for that YouTube link and summarize the video.
{
"command": "yt-dlp --version",
"timeout": 10000
}Output from command in shell 8e9c59: 2025.12.08 Exit code: 0
yt-dlp is installed. Now let me list the subtitles available and get the auto-generated ones. I'll use a command that downloads the auto-subtitles as a single SRT/VTT file, or I can extract the transcript directly. Best approach: use yt-dlp to extract the auto-generated English captions to stdout. yt-dlp has `--print` and can output JSON with `--dump-json`. The automatic_captions field contains URLs. But a simpler way is to use `--write-auto-sub --skip-download --sub-langs en --sub-format vtt` to get a VTT file, then read it. Let me list subs first to see what's available.
{
"command": "yt-dlp --list-subs \"https://www.youtube.com/watch?v=eWKY0OnPByg&pp=ugUEEgJlbtIHCQlPCwGHKiGM7w%3D%3D\"",
"timeout": 30000
}Output from command in shell 28a64b:
WARNING: Your yt-dlp version (2025.12.08) is older than 90 days!
It is strongly recommended to always use the latest version.
You installed yt-dlp with pip or using the wheel from PyPi; Use that to update.
To suppress this warning, add --no-update to your command/config.
[youtube] Extracting URL: https://www.youtube.com/watch?v=eWKY0OnPByg&pp=ugUEEgJlbtIHCQlPCwGHKiGM7w%3D%3D
[youtube] eWKY0OnPByg: Downloading webpage
[youtube] eWKY0OnPByg: Downloading tv client config
[youtube] eWKY0OnPByg: Downloading player ecd4b80a-main
[youtube] eWKY0OnPByg: Downloading tv player API JSON
[youtube] eWKY0OnPByg: Downloading android sdkless player API JSON
[youtube] [jsc:deno] Solving JS challenges using deno
WARNING: [youtube] [jsc] Remote components challenge solver script (deno) and NPM package (deno) were skipped. These may be required to solve JS challenges. You can enable these downloads with --remote-components ejs:github (recommended) or --remote-components ejs:npm , respectively. For more information and alternatives, refer to https://github.com/yt-dlp/yt-dlp/wiki/EJS
WARNING: [youtube] eWKY0OnPByg: n challenge solving failed: Some formats may be missing. Ensure you have a supported JavaScript runtime and challenge solver script distribution installed. Review any warnings presented before this message. For more details, refer to https://github.com/yt-dlp/yt-dlp/wiki/EJS
[info] Available automatic captions for eWKY0OnPByg:
Language Name Formats
ab-en Abkhazian from English vtt, srt, ttml, srv3, srv2, srv1, json3
aa-en Afar from English vtt, srt, ttml, srv3, srv2, srv1, json3
af-en Afrikaans from English vtt, srt, ttml, srv3, srv2, srv1, json3
ak-en Akan from English vtt, srt, ttml, srv3, srv2, srv1, json3
sq-en Albanian from English vtt, srt, ttml, srv3, srv2, srv1, json3
am-en Amharic from English vtt, srt, ttml, srv3, srv2, srv1, json3
ar-en Arabic from English vtt, srt, ttml, srv3, srv2, srv1, json3
hy-en Armenian from English vtt, srt, ttml, srv3, srv2, srv1, json3
as-en Assamese from English vtt, srt, ttml, srv3, srv2, srv1, json3
ay-en Aymara from English vtt, srt, ttml, srv3, srv2, srv1, json3
az-en Azerbaijani from English vtt, srt, ttml, srv3, srv2, srv1, json3
bn-en Bangla from English vtt, srt, ttml, srv3, srv2, srv1, json3
ba-en Bashkir from English vtt, srt, ttml, srv3, srv2, srv1, json3
eu-en Basque from English vtt, srt, ttml, srv3, srv2, srv1, json3
be-en Belarusian from English vtt, srt, ttml, srv3, srv2, srv1, json3
bho-en Bhojpuri from English vtt, srt, ttml, srv3, srv2, srv1, json3
bs-en Bosnian from English vtt, srt, ttml, srv3, srv2, srv1, json3
br-en Breton from English vtt, srt, ttml, srv3, srv2, srv1, json3
bg-en Bulgarian from English vtt, srt, ttml, srv3, srv2, srv1, json3
my-en Burmese from English vtt, srt, ttml, srv3, srv2, srv1, json3
ca-en Catalan from English vtt, srt, ttml, srv3, srv2, srv1, json3
ceb-en Cebuano from English vtt, srt, ttml, srv3, srv2, srv1, json3
zh-Hans-en Chinese (Simplified) from English vtt, srt, ttml, srv3, srv2, srv1, json3
zh-Hant-en Chinese (Traditional) from English vtt, srt, ttml, srv3, srv2, srv1, json3
co-en Corsican from English vtt, srt, ttml, srv3, srv2, srv1, json3
hr-en Croatian from English vtt, srt, ttml, srv3, srv2, srv1, json3
cs-en Czech from English vtt, srt, ttml, srv3, srv2, srv1, json3
da-en Danish from English vtt, srt, ttml, srv3, srv2, srv1, json3
dv-en Divehi from English vtt, srt, ttml, srv3, srv2, srv1, json3
nl-en Dutch from English vtt, srt, ttml, srv3, srv2, srv1, json3
dz-en Dzongkha from English vtt, srt, ttml, srv3, srv2, srv1, json3
en-en English from English vtt, srt, ttml, srv3, srv2, srv1, json3
eo-en Esperanto from English vtt, srt, ttml, srv3, srv2, srv1, json3
et-en Estonian from English vtt, srt, ttml, srv3, srv2, srv1, json3
ee-en Ewe from English vtt, srt, ttml, srv3, srv2, srv1, json3
fo-en Faroese from English vtt, srt, ttml, srv3, srv2, srv1, json3
fj-en Fijian from English vtt, srt, ttml, srv3, srv2, srv1, json3
fil-en Filipino from English vtt, srt, ttml, srv3, srv2, srv1, json3
fi-en Finnish from English vtt, srt, ttml, srv3, srv2, srv1, json3
fr-en French from English vtt, srt, ttml, srv3, srv2, srv1, json3
gaa-en Ga from English vtt, srt, ttml, srv3, srv2, srv1, json3
gl-en Galician from English vtt, srt, ttml, srv3, srv2, srv1, json3
lg-en Ganda from English vtt, srt, ttml, srv3, srv2, srv1, json3
ka-en Georgian from English vtt, srt, ttml, srv3, srv2, srv1, json3
de-en German from English vtt, srt, ttml, srv3, srv2, srv1, json3
el-en Greek from English vtt, srt, ttml, srv3, srv2, srv1, json3
gn-en Guarani from English vtt, srt, ttml, srv3, srv2, srv1, json3
gu-en Gujarati from English vtt, srt, ttml, srv3, srv2, srv1, json3
ht-en Haitian Creole from English vtt, srt, ttml, srv3, srv2, srv1, json3
ha-en Hausa from English vtt, srt, ttml, srv3, srv2, srv1, json3
haw-en Hawaiian from English vtt, srt, ttml, srv3, srv2, srv1, json3
iw-en Hebrew from English vtt, srt, ttml, srv3, srv2, srv1, json3
hi-en Hindi from English vtt, srt, ttml, srv3, srv2, srv1, json3
hmn-en Hmong from English vtt, srt, ttml, srv3, srv2, srv1, json3
hu-en Hungarian from English vtt, srt, ttml, srv3, srv2, srv1, json3
is-en Icelandic from English vtt, srt, ttml, srv3, srv2, srv1, json3
ig-en Igbo from English vtt, srt, ttml, srv3, srv2, srv1, json3
id-en Indonesian from English vtt, srt, ttml, srv3, srv2, srv1, json3
iu-en Inuktitut from English vtt, srt, ttml, srv3, srv2, srv1, json3
ga-en Irish from English vtt, srt, ttml, srv3, srv2, srv1, json3
it-en Italian from English vtt, srt, ttml, srv3, srv2, srv1, json3
ja-en Japanese from English vtt, srt, ttml, srv3, srv2, srv1, json3
jv-en Javanese from English vtt, srt, ttml, srv3, srv2, srv1, json3
kl-en Kalaallisut from English vtt, srt, ttml, srv3, srv2, srv1, json3
kn-en Kannada from English vtt, srt, ttml, srv3, srv2, srv1, json3
kk-en Kazakh from English vtt, srt, ttml, srv3, srv2, srv1, json3
kha-en Khasi from English vtt, srt, ttml, srv3, srv2, srv1, json3
km-en Khmer from English vtt, srt, ttml, srv3, srv2, srv1, json3
rw-en Kinyarwanda from English vtt, srt, ttml, srv3, srv2, srv1, json3
ko-en Korean from English vtt, srt, ttml, srv3, srv2, srv1, json3
kri-en Krio from English vtt, srt, ttml, srv3, srv2, srv1, json3
ku-en Kurdish from English vtt, srt, ttml, srv3, srv2, srv1, json3
ky-en Kyrgyz from English vtt, srt, ttml, srv3, srv2, srv1, json3
lo-en Lao from English vtt, srt, ttml, srv3, srv2, srv1, json3
la-en Latin from English vtt, srt, ttml, srv3, srv2, srv1, json3
lv-en Latvian from English vtt, srt, ttml, srv3, srv2, srv1, json3
ln-en Lingala from English vtt, srt, ttml, srv3, srv2, srv1, json3
lt-en Lithuanian from English vtt, srt, ttml, srv3, srv2, srv1, json3
lua-en Luba-Lulua from English vtt, srt, ttml, srv3, srv2, srv1, json3
luo-en Luo from English vtt, srt, ttml, srv3, srv2, srv1, json3
lb-en Luxembourgish from English vtt, srt, ttml, srv3, srv2, srv1, json3
mk-en Macedonian from English vtt, srt, ttml, srv3, srv2, srv1, json3
mg-en Malagasy from English vtt, srt, ttml, srv3, srv2, srv1, json3
ms-en Malay from English vtt, srt, ttml, srv3, srv2, srv1, json3
ml-en Malayalam from English vtt, srt, ttml, srv3, srv2, srv1, json3
mt-en Maltese from English vtt, srt, ttml, srv3, srv2, srv1, json3
gv-en Manx from English vtt, srt, ttml, srv3, srv2, srv1, json3
mi-en Māori from English vtt, srt, ttml, srv3, srv2, srv1, json3
mr-en Marathi from English vtt, srt, ttml, srv3, srv2, srv1, json3
mn-en Mongolian from English vtt, srt, ttml, srv3, srv2, srv1, json3
mfe-en Morisyen from English vtt, srt, ttml, srv3, srv2, srv1, json3
ne-en Nepali from English vtt, srt, ttml, srv3, srv2, srv1, json3
new-en Newari from English vtt, srt, ttml, srv3, srv2, srv1, json3
nso-en Northern Sotho from English vtt, srt, ttml, srv3, srv2, srv1, json3
no-en Norwegian from English vtt, srt, ttml, srv3, srv2, srv1, json3
ny-en Nyanja from English vtt, srt, ttml, srv3, srv2, srv1, json3
oc-en Occitan from English vtt, srt, ttml, srv3, srv2, srv1, json3
or-en Odia from English vtt, srt, ttml, srv3, srv2, srv1, json3
om-en Oromo from English vtt, srt, ttml, srv3, srv2, srv1, json3
os-en Ossetic from English vtt, srt, ttml, srv3, srv2, srv1, json3
pam-en Pampanga from English vtt, srt, ttml, srv3, srv2, srv1, json3
ps-en Pashto from English vtt, srt, ttml, srv3, srv2, srv1, json3
fa-en Persian from English vtt, srt, ttml, srv3, srv2, srv1, json3
pl-en Polish from English vtt, srt, ttml, srv3, srv2, srv1, json3
pt-en Portuguese from English vtt, srt, ttml, srv3, srv2, srv1, json3
pt-PT-en Portuguese (Portugal) from English vtt, srt, ttml, srv3, srv2, srv1, json3
pa-en Punjabi from English vtt, srt, ttml, srv3, srv2, srv1, json3
qu-en Quechua from English vtt, srt, ttml, srv3, srv2, srv1, json3
ro-en Romanian from English vtt, srt, ttml, srv3, srv2, srv1, json3
rn-en Rundi from English vtt, srt, ttml, srv3, srv2, srv1, json3
ru-en Russian from English vtt, srt, ttml, srv3, srv2, srv1, json3
sm-en Samoan from English vtt, srt, ttml, srv3, srv2, srv1, json3
sg-en Sango from English vtt, srt, ttml, srv3, srv2, srv1, json3
sa-en Sanskrit from English vtt, srt, ttml, srv3, srv2, srv1, json3
gd-en Scottish Gaelic from English vtt, srt, ttml, srv3, srv2, srv1, json3
sr-en Serbian from English vtt, srt, ttml, srv3, srv2, srv1, json3
crs-en Seselwa Creole French from English vtt, srt, ttml, srv3, srv2, srv1, json3
sn-en Shona from English vtt, srt, ttml, srv3, srv2, srv1, json3
sd-en Sindhi from English vtt, srt, ttml, srv3, srv2, srv1, json3
si-en Sinhala from English vtt, srt, ttml, srv3, srv2, srv1, json3
sk-en Slovak from English vtt, srt, ttml, srv3, srv2, srv1, json3
sl-en Slovenian from English vtt, srt, ttml, srv3, srv2, srv1, json3
so-en Somali from English vtt, srt, ttml, srv3, srv2, srv1, json3
st-en Southern Sotho from English vtt, srt, ttml, srv3, srv2, srv1, json3
es-en Spanish from English vtt, srt, ttml, srv3, srv2, srv1, json3
su-en Sundanese from English vtt, srt, ttml, srv3, srv2, srv1, json3
sw-en Swahili from English vtt, srt, ttml, srv3, srv2, srv1, json3
ss-en Swati from English vtt, srt, ttml, srv3, srv2, srv1, json3
sv-en Swedish from English vtt, srt, ttml, srv3, srv2, srv1, json3
tg-en Tajik from English vtt, srt, ttml, srv3, srv2, srv1, json3
ta-en Tamil from English vtt, srt, ttml, srv3, srv2, srv1, json3
tt-en Tatar from English vtt, srt, ttml, srv3, srv2, srv1, json3
te-en Telugu from English vtt, srt, ttml, srv3, srv2, srv1, json3
th-en Thai from English vtt, srt, ttml, srv3, srv2, srv1, json3
bo-en Tibetan from English vtt, srt, ttml, srv3, srv2, srv1, json3
ti-en Tigrinya from English vtt, srt, ttml, srv3, srv2, srv1, json3
to-en Tongan from English vtt, srt, ttml, srv3, srv2, srv1, json3
ts-en Tsonga from English vtt, srt, ttml, srv3, srv2, srv1, json3
tn-en Tswana from English vtt, srt, ttml, srv3, srv2, srv1, json3
tum-en Tumbuka from English vtt, srt, ttml, srv3, srv2, srv1, json3
tr-en Turkish from English vtt, srt, ttml, srv3, srv2, srv1, json3
tk-en Turkmen from English vtt, srt, ttml, srv3, srv2, srv1, json3
uk-en Ukrainian from English vtt, srt, ttml, srv3, srv2, srv1, json3
ur-en Urdu from English vtt, srt, ttml, srv3, srv2, srv1, json3
ug-en Uyghur from English vtt, srt, ttml, srv3, srv2, srv1, json3
uz-en Uzbek from English vtt, srt, ttml, srv3, srv2, srv1, json3
ve-en Venda from English vtt, srt, ttml, srv3, srv2, srv1, json3
vi-en Vietnamese from English vtt, srt, ttml, srv3, srv2, srv1, json3
war-en Waray from English vtt, srt, ttml, srv3, srv2, srv1, json3
cy-en Welsh from English vtt, srt, ttml, srv3, srv2, srv1, json3
fy-en Western Frisian from English vtt, srt, ttml, srv3, srv2, srv1, json3
wo-en Wolof from English vtt, srt, ttml, srv3, srv2, srv1, json3
xh-en Xhosa from English vtt, srt, ttml, srv3, srv2, srv1, json3
yi-en Yiddish from English vtt, srt, ttml, srv3, srv2, srv1, json3
yo-en Yoruba from English vtt, srt, ttml, srv3, srv2, srv1, json3
zu-en Zulu from English vtt, srt, ttml, srv3, srv2, srv1, json3
ab Abkhazian vtt, srt, ttml, srv3, srv2, srv1, json3
aa Afar vtt, srt, ttml, srv3, srv2, srv1, json3
af Afrikaans vtt, srt, ttml, srv3, srv2, srv1, json3
ak Akan vtt, srt, ttml, srv3, srv2, srv1, json3
sq Albanian vtt, srt, ttml, srv3, srv2, srv1, json3
am Amharic vtt, srt, ttml, srv3, srv2, srv1, json3
ar Arabic vtt, srt, ttml, srv3, srv2, srv1, json3
hy Armenian vtt, srt, ttml, srv3, srv2, srv1, json3
as Assamese vtt, srt, ttml, srv3, srv2, srv1, json3
ay Aymara vtt, srt, ttml, srv3, srv2, srv1, json3
az Azerbaijani vtt, srt, ttml, srv3, srv2, srv1, json3
bn Bangla vtt, srt, ttml, srv3, srv2, srv1, json3
ba Bashkir vtt, srt, ttml, srv3, srv2, srv1, json3
eu Basque vtt, srt, ttml, srv3, srv2, srv1, json3
be Belarusian vtt, srt, ttml, srv3, srv2, srv1, json3
bho Bhojpuri vtt, srt, ttml, srv3, srv2, srv1, json3
bs Bosnian vtt, srt, ttml, srv3, srv2, srv1, json3
br Breton vtt, srt, ttml, srv3, srv2, srv1, json3
bg Bulgarian vtt, srt, ttml, srv3, srv2, srv1, json3
my Burmese vtt, srt, ttml, srv3, srv2, srv1, json3
ca Catalan vtt, srt, ttml, srv3, srv2, srv1, json3
ceb Cebuano vtt, srt, ttml, srv3, srv2, srv1, json3
zh-Hans Chinese (Simplified) vtt, srt, ttml, srv3, srv2, srv1, json3
zh-Hant Chinese (Traditional) vtt, srt, ttml, srv3, srv2, srv1, json3
co Corsican vtt, srt, ttml, srv3, srv2, srv1, json3
hr Croatian vtt, srt, ttml, srv3, srv2, srv1, json3
cs Czech vtt, srt, ttml, srv3, srv2, srv1, json3
da Danish vtt, srt, ttml, srv3, srv2, srv1, json3
dv Divehi vtt, srt, ttml, srv3, srv2, srv1, json3
nl Dutch vtt, srt, ttml, srv3, srv2, srv1, json3
dz Dzongkha vtt, srt, ttml, srv3, srv2, srv1, json3
en-orig English (Original) vtt, srt, ttml, srv3, srv2, srv1, json3
en English vtt, srt, ttml, srv3, srv2, srv1, json3
eo Esperanto vtt, srt, ttml, srv3, srv2, srv1, json3
et Estonian vtt, srt, ttml, srv3, srv2, srv1, json3
ee Ewe vtt, srt, ttml, srv3, srv2, srv1, json3
fo Faroese vtt, srt, ttml, srv3, srv2, srv1, json3
fj Fijian vtt, srt, ttml, srv3, srv2, srv1, json3
fil Filipino vtt, srt, ttml, srv3, srv2, srv1, json3
fi Finnish vtt, srt, ttml, srv3, srv2, srv1, json3
fr French vtt, srt, ttml, srv3, srv2, srv1, json3
gaa Ga vtt, srt, ttml, srv3, srv2, srv1, json3
gl Galician vtt, srt, ttml, srv3, srv2, srv1, json3
lg Ganda vtt, srt, ttml, srv3, srv2, srv1, json3
ka Georgian vtt, srt, ttml, srv3, srv2, srv1, json3
de German vtt, srt, ttml, srv3, srv2, srv1, json3
el Greek vtt, srt, ttml, srv3, srv2, srv1, json3
gn Guarani vtt, srt, ttml, srv3, srv2, srv1, json3
gu Gujarati vtt, srt, ttml, srv3, srv2, srv1, json3
ht Haitian Creole vtt, srt, ttml, srv3, srv2, srv1, json3
ha Hausa vtt, srt, ttml, srv3, srv2, srv1, json3
haw … (79 chars truncated)
… (665 lines truncated)
new-tr Newari from Turkish vtt, srt, ttml, srv3, srv2… (13 chars truncated)
nso-tr Northern Sotho from Turkish vtt, srt, ttml, srv3, srv2, srv1, json3
no-tr Norwegian from Turkish vtt, srt, ttml, srv3, srv2, srv1, json3
ny-tr Nyanja from Turkish vtt, srt, ttml, srv3, srv2, srv1, json3
oc-tr Occitan from Turkish vtt, srt, ttml, srv3, srv2, srv1, json3
or-tr Odia from Turkish vtt, srt, ttml, srv3, srv2, srv1, json3
om-tr Oromo from Turkish vtt, srt, ttml, srv3, srv2, srv1, json3
os-tr Ossetic from Turkish vtt, srt, ttml, srv3, srv2, srv1, json3
pam-tr Pampanga from Turkish vtt, srt, ttml, srv3, srv2, srv1, json3
ps-tr Pashto from Turkish vtt, srt, ttml, srv3, srv2, srv1, json3
fa-tr Persian from Turkish vtt, srt, ttml, srv3, srv2, srv1, json3
pl-tr Polish from Turkish vtt, srt, ttml, srv3, srv2, srv1, json3
pt-tr Portuguese from Turkish vtt, srt, ttml, srv3, srv2, srv1, json3
pt-PT-tr Portuguese (Portugal) from Turkish vtt, srt, ttml, srv3, srv2, srv1, json3
pa-tr Punjabi from Turkish vtt, srt, ttml, srv3, srv2, srv1, json3
qu-tr Quechua from Turkish vtt, srt, ttml, srv3, srv2, srv1, json3
ro-tr Romanian from Turkish vtt, srt, ttml, srv3, srv2, srv1, json3
rn-tr Rundi from Turkish vtt, srt, ttml, srv3, srv2, srv1, json3
ru-tr Russian from Turkish vtt, srt, ttml, srv3, srv2, srv1, json3
sm-tr Samoan from Turkish vtt, srt, ttml, srv3, srv2, srv1, json3
sg-tr Sango from Turkish vtt, srt, ttml, srv3, srv2, srv1, json3
sa-tr Sanskrit from Turkish vtt, srt, ttml, srv3, srv2, srv1, json3
gd-tr Scottish Gaelic from Turkish vtt, srt, ttml, srv3, srv2, srv1, json3
sr-tr Serbian from Turkish vtt, srt, ttml, srv3, srv2, srv1, json3
crs-tr Seselwa Creole French from Turkish vtt, srt, ttml, srv3, srv2, srv1, json3
sn-tr Shona from Turkish vtt, srt, ttml, srv3, srv2, srv1, json3
sd-tr Sindhi from Turkish vtt, srt, ttml, srv3, srv2, srv1, json3
si-tr Sinhala from Turkish vtt, srt, ttml, srv3, srv2, srv1, json3
sk-tr Slovak from Turkish vtt, srt, ttml, srv3, srv2, srv1, json3
sl-tr Slovenian from Turkish vtt, srt, ttml, srv3, srv2, srv1, json3
so-tr Somali from Turkish vtt, srt, ttml, srv3, srv2, srv1, json3
st-tr Southern Sotho from Turkish vtt, srt, ttml, srv3, srv2, srv1, json3
es-tr Spanish from Turkish vtt, srt, ttml, srv3, srv2, srv1, json3
su-tr Sundanese from Turkish vtt, srt, ttml, srv3, srv2, srv1, json3
sw-tr Swahili from Turkish vtt, srt, ttml, srv3, srv2, srv1, json3
ss-tr Swati from Turkish vtt, srt, ttml, srv3, srv2, srv1, json3
sv-tr Swedish from Turkish vtt, srt, ttml, srv3, srv2, srv1, json3
tg-tr Tajik from Turkish vtt, srt, ttml, srv3, srv2, srv1, json3
ta-tr Tamil from Turkish vtt, srt, ttml, srv3, srv2, srv1, json3
tt-tr Tatar from Turkish vtt, srt, ttml, srv3, srv2, srv1, json3
te-tr Telugu from Turkish vtt, srt, ttml, srv3, srv2, srv1, json3
th-tr Thai from Turkish vtt, srt, ttml, srv3, srv2, srv1, json3
bo-tr Tibetan from Turkish vtt, srt, ttml, srv3, srv2, srv1, json3
ti-tr Tigrinya from Turkish vtt, srt, ttml, srv3, srv2, srv1, json3
to-tr Tongan from Turkish vtt, srt, ttml, srv3, srv2, srv1, json3
ts-tr Tsonga from Turkish vtt, srt, ttml, srv3, srv2, srv1, json3
tn-tr Tswana from Turkish vtt, srt, ttml, srv3, srv2, srv1, json3
tum-tr Tumbuka from Turkish vtt, srt, ttml, srv3, srv2, srv1, json3
tr-tr Turkish from Turkish vtt, srt, ttml, srv3, srv2, srv1, json3
tk-tr Turkmen from Turkish vtt, srt, ttml, srv3, srv2, srv1, json3
uk-tr Ukrainian from Turkish vtt, srt, ttml, srv3, srv2, srv1, json3
ur-tr Urdu from Turkish vtt, srt, ttml, srv3, srv2, srv1, json3
ug-tr Uyghur from Turkish vtt, srt, ttml, srv3, srv2, srv1, json3
uz-tr Uzbek from Turkish vtt, srt, ttml, srv3, srv2, srv1, json3
ve-tr Venda from Turkish vtt, srt, ttml, srv3, srv2, srv1, json3
vi-tr Vietnamese from Turkish vtt, srt, ttml, srv3, srv2, srv1, json3
war-tr Waray from Turkish vtt, srt, ttml, srv3, srv2, srv1, json3
cy-tr Welsh from Turkish vtt, srt, ttml, srv3, srv2, srv1, json3
fy-tr Western Frisian from Turkish vtt, srt, ttml, srv3, srv2, srv1, json3
wo-tr Wolof from Turkish vtt, srt, ttml, srv3, srv2, srv1, json3
xh-tr Xhosa from Turkish vtt, srt, ttml, srv3, srv2, srv1, json3
yi-tr Yiddish from Turkish vtt, srt, ttml, srv3, srv2, srv1, json3
yo-tr Yoruba from Turkish vtt, srt, ttml, srv3, srv2, srv1, json3
zu-tr Zulu from Turkish vtt, srt, ttml, srv3, srv2, srv1, json3
ab-vi Abkhazian from Vietnamese vtt, srt, ttml, srv3, srv2, srv1, json3
aa-vi Afar from Vietnamese vtt, srt, ttml, srv3, srv2, srv1, json3
af-vi Afrikaans from Vietnamese vtt, srt, ttml, srv3, srv2, srv1, json3
ak-vi Akan from Vietnamese vtt, srt, ttml, srv3, srv2, srv1, json3
sq-vi Albanian from Vietnamese vtt, srt, ttml, srv3, srv2, srv1, json3
am-vi Amharic from Vietnamese vtt, srt, ttml, srv3, srv2, srv1, json3
ar-vi Arabic from Vietnamese vtt, srt, ttml, srv3, srv2, srv1, json3
hy-vi Armenian from Vietnamese vtt, srt, ttml, srv3, srv2, srv1, json3
as-vi Assamese from Vietnamese vtt, srt, ttml, srv3, srv2, srv1, json3
ay-vi Aymara from Vietnamese vtt, srt, ttml, srv3, srv2, srv1, json3
az-vi Azerbaijani from Vietnamese vtt, srt, ttml, srv3, srv2, srv1, json3
bn-vi Bangla from Vietnamese vtt, srt, ttml, srv3, srv2, srv1, json3
ba-vi Bashkir from Vietnamese vtt, srt, ttml, srv3, srv2, srv1, json3
eu-vi Basque from Vietnamese vtt, srt, ttml, srv3, srv2, srv1, json3
be-vi Belarusian from Vietnamese vtt, srt, ttml, srv3, srv2, srv1, json3
bho-vi Bhojpuri from Vietnamese vtt, srt, ttml, srv3, srv2, srv1, json3
bs-vi Bosnian from Vietnamese vtt, srt, ttml, srv3, srv2, srv1, json3
br-vi Breton from Vietnamese vtt, srt, ttml, srv3, srv2, srv1, json3
bg-vi Bulgarian from Vietnamese vtt, srt, ttml, srv3, srv2, srv1, json3
my-vi Burmese from Vietnamese vtt, srt, ttml, srv3, srv2, srv1, json3
ca-vi Catalan from Vietnamese vtt, srt, ttml, srv3, srv2, srv1, json3
ceb-vi Cebuano from Vietnamese vtt, srt, ttml, srv3, srv2, srv1, json3
zh-Hans-vi Chinese (Simplified) from Vietnamese vtt, srt, ttml, srv3, srv2, srv1, json3
zh-Hant-vi Chinese (Traditional) from Vietnamese vtt, srt, ttml, srv3, srv2, srv1, json3
co-vi Corsican from Vietnamese vtt, srt, ttml, srv3, srv2, srv1, json3
hr-vi Croatian from Vietnamese vtt, srt, ttml, srv3, srv2, srv1, json3
cs-vi Czech from Vietnamese vtt, srt, ttml, srv3, srv2, srv1, json3
da-vi Danish from Vietnamese vtt, srt, ttml, srv3, srv2, srv1, json3
dv-vi Divehi from Vietnamese vtt, srt, ttml, srv3, srv2, srv1, json3
nl-vi Dutch from Vietnamese vtt, srt, ttml, srv3, srv2, srv1, json3
dz-vi Dzongkha from Vietnamese vtt, srt, ttml, srv3, srv2, srv1, json3
en-vi English from Vietnamese vtt, srt, ttml, srv3, srv2, srv1, json3
eo-vi Esperanto from Vietnamese vtt, srt, ttml, srv3, srv2, srv1, json3
et-vi Estonian from Vietnamese vtt, srt, ttml, srv3, srv2, srv1, json3
ee-vi Ewe from Vietnamese vtt, srt, ttml, srv3, srv2, srv1, json3
fo-vi Faroese from Vietnamese vtt, srt, ttml, srv3, srv2, srv1, json3
fj-vi Fijian from Vietnamese vtt, srt, ttml, srv3, srv2, srv1, json3
fil-vi Filipino from Vietnamese vtt, srt, ttml, srv3, srv2, srv1, json3
fi-vi Finnish from Vietnamese vtt, srt, ttml, srv3, srv2, srv1, json3
fr-vi French from Vietnamese vtt, srt, ttml, srv3, srv2, srv1, json3
gaa-vi Ga from Vietnamese vtt, srt, ttml, srv3, srv2, srv1, json3
gl-vi Galician from Vietnamese vtt, srt, ttml, srv3, srv2, srv1, json3
lg-vi Ganda from Vietnamese vtt, srt, ttml, srv3, srv2, srv1, json3
ka-vi Georgian from Vietnamese vtt, srt, ttml, srv3, srv2, srv1, json3
de-vi German from Vietnamese vtt, srt, ttml, srv3, srv2, srv1, json3
el-vi Greek from Vietnamese vtt, srt, ttml, srv3, srv2, srv1, json3
gn-vi Guarani from Vietnamese vtt, srt, ttml, srv3, srv2, srv1, json3
gu-vi Gujarati from Vietnamese vtt, srt, ttml, srv3, srv2, srv1, json3
ht-vi Haitian Creole from Vietnamese vtt, srt, ttml, srv3, srv2, srv1, json3
ha-vi Hausa from Vietnamese vtt, srt, ttml, srv3, srv2, srv1, json3
haw-vi Hawaiian from Vietnamese vtt, srt, ttml, srv3, srv2, srv1, json3
iw-vi Hebrew from Vietnamese vtt, srt, ttml, srv3, srv2, srv1, json3
hi-vi Hindi from Vietnamese vtt, srt, ttml, srv3, srv2, srv1, json3
hmn-vi Hmong from Vietnamese vtt, srt, ttml, srv3, srv2, srv1, json3
hu-vi Hungarian from Vietnamese vtt, srt, ttml, srv3, srv2, srv1, json3
is-vi Icelandic from Vietnamese vtt, srt, ttml, srv3, srv2, srv1, json3
ig-vi Igbo from Vietnamese vtt, srt, ttml, srv3, srv2, srv1, json3
id-vi Indonesian from Vietnamese vtt, srt, ttml, srv3, srv2, srv1, json3
iu-vi Inuktitut from Vietnamese vtt, srt, ttml, srv3, srv2, srv1, json3
ga-vi Irish from Vietnamese vtt, srt, ttml, srv3, srv2, srv1, json3
it-vi Italian from Vietnamese vtt, srt, ttml, srv3, srv2, srv1, json3
ja-vi Japanese from Vietnamese vtt, srt, ttml, srv3, srv2, srv1, json3
jv-vi Javanese from Vietnamese vtt, srt, ttml, srv3, srv2, srv1, json3
kl-vi Kalaallisut from Vietnamese vtt, srt, ttml, srv3, srv2, srv1, json3
kn-vi Kannada from Vietnamese vtt, srt, ttml, srv3, srv2, srv1, json3
kk-vi Kazakh from Vietnamese vtt, srt, ttml, srv3, srv2, srv1, json3
kha-vi Khasi from Vietnamese vtt, srt, ttml, srv3, srv2, srv1, json3
km-vi Khmer from Vietnamese vtt, srt, ttml, srv3, srv2, srv1, json3
rw-vi Kinyarwanda from Vietnamese vtt, srt, ttml, srv3, srv2, srv1, json3
ko-vi Korean from Vietnamese vtt, srt, ttml, srv3, srv2, srv1, json3
kri-vi Krio from Vietnamese vtt, srt, ttml, srv3, srv2, srv1, json3
ku-vi Kurdish from Vietnamese vtt, srt, ttml, srv3, srv2, srv1, json3
ky-vi Kyrgyz from Vietnamese vtt, srt, ttml, srv3, srv2, srv1, json3
lo-vi Lao from Vietnamese vtt, srt, ttml, srv3, srv2, srv1, json3
la-vi Latin from Vietnamese vtt, srt, ttml, srv3, srv2, srv1, json3
lv-vi Latvian from Vietnamese vtt, srt, ttml, srv3, srv2, srv1, json3
ln-vi Lingala from Vietnamese vtt, srt, ttml, srv3, srv2, srv1, json3
lt-vi Lithuanian from Vietnamese vtt, srt, ttml, srv3, srv2, srv1, json3
lua-vi Luba-Lulua from Vietnamese vtt, srt, ttml, srv3, srv2, srv1, json3
luo-vi Luo from Vietnamese vtt, srt, ttml, srv3, srv2, srv1, json3
lb-vi Luxembourgish from Vietnamese vtt, srt, ttml, srv3, srv2, srv1, json3
mk-vi Macedonian from Vietnamese vtt, srt, ttml, srv3, srv2, srv1, json3
mg-vi Malagasy from Vietnamese vtt, srt, ttml, srv3, srv2, srv1, json3
ms-vi Malay from Vietnamese vtt, srt, ttml, srv3, srv2, srv1, json3
ml-vi Malayalam from Vietnamese vtt, srt, ttml, srv3, srv2, srv1, json3
mt-vi Maltese from Vietnamese vtt, srt, ttml, srv3, srv2, srv1, json3
gv-vi Manx from Vietnamese vtt, srt, ttml, srv3, srv2, srv1, json3
mi-vi Māori from Vietnamese vtt, srt, ttml, srv3, srv2, srv1, json3
mr-vi Marathi from Vietnamese vtt, srt, ttml, srv3, srv2, srv1, json3
mn-vi Mongolian from Vietnamese vtt, srt, ttml, srv3, srv2, srv1, json3
mfe-vi Morisyen from Vietnamese vtt, srt, ttml, srv3, srv2, srv1, json3
ne-vi Nepali from Vietnamese vtt, srt, ttml, srv3, srv2, srv1, json3
new-vi Newari from Vietnamese vtt, srt, ttml, srv3, srv2, srv1, json3
nso-vi Northern Sotho from Vietnamese vtt, srt, ttml, srv3, srv2, srv1, json3
no-vi Norwegian from Vietnamese vtt, srt, ttml, srv3, srv2, srv1, json3
ny-vi Nyanja from Vietnamese vtt, srt, ttml, srv3, srv2, srv1, json3
oc-vi Occitan from Vietnamese vtt, srt, ttml, srv3, srv2, srv1, json3
or-vi Odia from Vietnamese vtt, srt, ttml, srv3, srv2, srv1, json3
om-vi Oromo from Vietnamese vtt, srt, ttml, srv3, srv2, srv1, json3
os-vi Ossetic from Vietnamese vtt, srt, ttml, srv3, srv2, srv1, json3
pam-vi Pampanga from Vietnamese vtt, srt, ttml, srv3, srv2, srv1, json3
ps-vi Pashto from Vietnamese vtt, srt, ttml, srv3, srv2, srv1, json3
fa-vi Persian from Vietnamese vtt, srt, ttml, srv3, srv2, srv1, json3
pl-vi Polish from Vietnamese vtt, srt, ttml, srv3, srv2, srv1, json3
pt-vi Portuguese from Vietnamese vtt, srt, ttml, srv3, srv2, srv1, json3
pt-PT-vi Portuguese (Portugal) from Vietnamese vtt, srt, ttml, srv3, srv2, srv1, json3
pa-vi Punjabi from Vietnamese vtt, srt, ttml, srv3, srv2, srv1, json3
qu-vi Quechua from Vietnamese vtt, srt, ttml, srv3, srv2, srv1, json3
ro-vi Romanian from Vietnamese vtt, srt, ttml, srv3, srv2, srv1, json3
rn-vi Rundi from Vietnamese vtt, srt, ttml, srv3, srv2, srv1, json3
ru-vi Russian from Vietnamese vtt, srt, ttml, srv3, srv2, srv1, json3
sm-vi Samoan from Vietnamese vtt, srt, ttml, srv3, srv2, srv1, json3
sg-vi Sango from Vietnamese vtt, srt, ttml, srv3, srv2, srv1, json3
sa-vi Sanskrit from Vietnamese vtt, srt, ttml, srv3, srv2, srv1, json3
gd-vi Scottish Gaelic from Vietnamese vtt, srt, ttml, srv3, srv2, srv1, json3
sr-vi Serbian from Vietnamese vtt, srt, ttml, srv3, srv2, srv1, json3
crs-vi Seselwa Creole French from Vietnamese vtt, srt, ttml, srv3, srv2, srv1, json3
sn-vi Shona from Vietnamese vtt, srt, ttml, srv3, srv2, srv1, json3
sd-vi Sindhi from Vietnamese vtt, srt, ttml, srv3, srv2, srv1, json3
si-vi Sinhala from Vietnamese vtt, srt, ttml, srv3, srv2, srv1, json3
sk-vi Slovak from Vietnamese vtt, srt, ttml, srv3, srv2, srv1, json3
sl-vi Slovenian from Vietnamese vtt, srt, ttml, srv3, srv2, srv1, json3
so-vi Somali from Vietnamese vtt, srt, ttml, srv3, srv2, srv1, json3
st-vi Southern Sotho from Vietnamese vtt, srt, ttml, srv3, srv2, srv1, json3
es-vi Spanish from Vietnamese vtt, srt, ttml, srv3, srv2, srv1, json3
su-vi Sundanese from Vietnamese vtt, srt, ttml, srv3, srv2, srv1, json3
sw-vi Swahili from Vietnamese vtt, srt, ttml, srv3, srv2, srv1, json3
ss-vi Swati from Vietnamese vtt, srt, ttml, srv3, srv2, srv1, json3
sv-vi Swedish from Vietnamese vtt, srt, ttml, srv3, srv2, srv1, json3
tg-vi Tajik from Vietnamese vtt, srt, ttml, srv3, srv2, srv1, json3
ta-vi Tamil from Vietnamese vtt, srt, ttml, srv3, srv2, srv1, json3
tt-vi Tatar from Vietnamese vtt, srt, ttml, srv3, srv2, srv1, json3
te-vi Telugu from Vietnamese vtt, srt, ttml, srv3, srv2, srv1, json3
th-vi Thai from Vietnamese vtt, srt, ttml, srv3, srv2, srv1, json3
bo-vi Tibetan from Vietnamese vtt, srt, ttml, srv3, srv2, srv1, json3
ti-vi Tigrinya from Vietnamese vtt, srt, ttml, srv3, srv2, srv1, json3
to-vi Tongan from Vietnamese vtt, srt, ttml, srv3, srv2, srv1, json3
ts-vi Tsonga from Vietnamese vtt, srt, ttml, srv3, srv2, srv1, json3
tn-vi Tswana from Vietnamese vtt, srt, ttml, srv3, srv2, srv1, json3
tum-vi Tumbuka from Vietnamese vtt, srt, ttml, srv3, srv2, srv1, json3
tr-vi Turkish from Vietnamese vtt, srt, ttml, srv3, srv2, srv1, json3
tk-vi Turkmen from Vietnamese vtt, srt, ttml, srv3, srv2, srv1, json3
uk-vi Ukrainian from Vietnamese vtt, srt, ttml, srv3, srv2, srv1, json3
ur-vi Urdu from Vietnamese vtt, srt, ttml, srv3, srv2, srv1, json3
ug-vi Uyghur from Vietnamese vtt, srt, ttml, srv3, srv2, srv1, json3
uz-vi Uzbek from Vietnamese vtt, srt, ttml, srv3, srv2, srv1, json3
ve-vi Venda from Vietnamese vtt, srt, ttml, srv3, srv2, srv1, json3
vi-vi Vietnamese from Vietnamese vtt, srt, ttml, srv3, srv2, srv1, json3
war-vi Waray from Vietnamese vtt, srt, ttml, srv3, srv2, srv1, json3
cy-vi Welsh from Vietnamese vtt, srt, ttml, srv3, srv2, srv1, json3
fy-vi Western Frisian from Vietnamese vtt, srt, ttml, srv3, srv2, srv1, json3
wo-vi Wolof from Vietnamese vtt, srt, ttml, srv3, srv2, srv1, json3
xh-vi Xhosa from Vietnamese vtt, srt, ttml, srv3, srv2, srv1, json3
yi-vi Yiddish from Vietnamese vtt, srt, ttml, srv3, srv2, srv1, json3
yo-vi Yoruba from Vietnamese vtt, srt, ttml, srv3, srv2, srv1, json3
zu-vi Zulu from Vietnamese vtt, srt, ttml, srv3, srv2, srv1, json3
[info] Available subtitles for eWKY0OnPByg:
Language Name Formats
en English vtt, srt, ttml, srv3, srv2, srv1, json3
ja Japanese vtt, srt, ttml, srv3, srv2, srv1, json3
pt Portuguese vtt, srt, ttml, srv3, srv2, srv1, json3
ru Russian vtt, srt, ttml, srv3, srv2, srv1, json3
tr Turkish vtt, srt, ttml, srv3, srv2, srv1, json3
vi Vietnamese vtt, srt, ttml, srv3, srv2, srv1, json3
Exit code: 0
<truncation_notice>
Full output written to: /var/folders/d9/mzhyr7lx6xbf236j5ll9v_300000gn/T/devin-overflows-501/d85c3e2a/content.txt
</truncation_notice>Good, there are both automatic captions and regular subtitles. There are English subtitles available (not auto-generated), so I should use those if they're more accurate, but the user specifically said "get the autogenerrated captions to do this". So I should use the auto-generated English captions. The auto-generated English caption language appears to be listed as "en" under automatic captions? Wait, looking at the list, it shows automatic captions with codes like "ab-en", "aa-en", etc. and regular subtitles with codes like "en", "ja", "pt", etc. So "en" is a regular subtitle, and "en-en" would be "English from English" auto-generated? Let me check - in the automatic captions list I see "en-en English from English". Yes. But for auto-generated, the video may not have a specific "en-en" if it's already in English. Actually for English videos, the auto-generated captions are often available as just "en" in the automatic captions section, but here they have "en-en English from English" which means English auto-generated from English audio. Wait, the first section is "Available automatic captions" and the second is "Available subtitles". So the regular "en" in the second section is actual uploaded subtitle. The "en-en" in the first section is auto-generated. I'll use the auto-generated captions as instructed. I can download them with `--write-auto-sub --skip-download --sub-langs en-en --sub-format srt` or similar. Let me try just `--write-auto-sub --skip-download --sub-langs en` - usually yt-dlp picks the auto-generated English. Actually, to be precise I'll use `--write-auto-sub --skip-download --sub-langs "en.*" --sub-format vtt` and see what it downloads. Then parse the VTT/SRT and summarize. Let me download to a temp file and read it.
{
"command": "cd /tmp && yt-dlp --no-update --write-auto-sub --skip-download --sub-langs en --sub-format srt --output \"video_captions\" \"https://www.youtube.com/watch?v=eWKY0OnPByg&pp=ugUEEgJlbtIHCQlPCwGHKiGM7w%3D%3D\"",
"timeout": 60000
}Output from command in shell 35d388: [youtube] Extracting URL: https://www.youtube.com/watch?v=eWKY0OnPByg&pp=ugUEEgJlbtIHCQlPCwGHKiGM7w%3D%3D [youtube] eWKY0OnPByg: Downloading webpage [youtube] eWKY0OnPByg: Downloading tv client config [youtube] eWKY0OnPByg: Downloading player ecd4b80a-main [youtube] eWKY0OnPByg: Downloading tv player API JSON [youtube] eWKY0OnPByg: Downloading android sdkless player API JSON [youtube] [jsc:deno] Solving JS challenges using deno WARNING: [youtube] [jsc] Remote components challenge solver script (deno) and NPM package (deno) were skipped. These may be required to solve JS challenges. You can enable these downloads with --remote-components ejs:github (recommended) or --remote-components ejs:npm , respectively. For more information and alternatives, refer to https://github.com/yt-dlp/yt-dlp/wiki/EJS WARNING: [youtube] eWKY0OnPByg: n challenge solving failed: Some formats may be missing. Ensure you have a supported JavaScript runtime and challenge solver script distribution installed. Review any warnings presented before this message. For more details, refer to https://github.com/yt-dlp/yt-dlp/wiki/EJS [info] eWKY0OnPByg: Downloading subtitles: en [info] eWKY0OnPByg: Downloading 1 format(s): 139-5 [info] Writing video subtitles to: video_captions.en.srt [download] Destination: video_captions.en.srt [download] 1.00KiB at Unknown B/s (00:00:00) [download] 3.00KiB at Unknown B/s (00:00:00) [download] 7.00KiB at Unknown B/s (00:00:00) [download] 13.10KiB at 9.40MiB/s (00:00:00) [download] 100% of 13.10KiB in 00:00:00 at 144.65KiB/s Exit code: 0
Good, downloaded the captions. Now let me read the SRT file and summarize it. The file is /tmp/video_captions.en.srt.
{
"file_path": "/tmp/video_captions.en.srt"
}<file-view path="/tmp/video_captions.en.srt" start_line="1" end_line="744" total_lines="744"> 1|1 2|00:00:07,600 --> 00:00:12,400 3|Yo, I was just thinking about all this 4| 5|2 6|00:00:09,519 --> 00:00:14,960 7|AI race stuff and how everything's gone 8| 9|3 10|00:00:12,400 --> 00:00:16,560 11|from zero to 100 and then Apple, they've 12| 13|4 14|00:00:14,960 --> 00:00:17,760 15|just kind of been scrambling the past 16| 17|5 18|00:00:16,560 --> 00:00:19,439 19|two years trying to build Apple 20| 21|6 22|00:00:17,760 --> 00:00:21,760 23|intelligence and haven't really done 24| 25|7 26|00:00:19,439 --> 00:00:24,880 27|very well yet. I just feel like it's so 28| 29|8 30|00:00:21,760 --> 00:00:26,480 31|obvious that they won. 32| 33|9 34|00:00:24,880 --> 00:00:28,720 35|>> What? No, they they lost. 36| 37|10 38|00:00:26,480 --> 00:00:30,320 39|>> No, they they really won. 40| 41|11 42|00:00:28,720 --> 00:00:32,480 43|>> Wait, sorry. No. Are you are you trying 44| 45|12 46|00:00:30,320 --> 00:00:34,320 47|to say that Apple, the one that 48| 49|13 50|00:00:32,480 --> 00:00:36,000 51|announced the new Siri and then didn't 52| 53|14 54|00:00:34,320 --> 00:00:37,120 55|deliver on it for 2 years until they had 56| 57|15 58|00:00:36,000 --> 00:00:39,040 59|to start over and build it from the 60| 61|16 62|00:00:37,120 --> 00:00:42,879 63|ground up with help from Google that 64| 65|17 66|00:00:39,040 --> 00:00:46,320 67|Apple won the AI race? See, I I think 68| 69|18 70|00:00:42,879 --> 00:00:47,840 71|your definition of the AI race is a 72| 73|19 74|00:00:46,320 --> 00:00:50,719 75|little bit too narrow. Like obviously 76| 77|20 78|00:00:47,840 --> 00:00:53,920 79|being open AI and having chat GPT is one 80| 81|21 82|00:00:50,719 --> 00:00:57,360 83|thing, but making the hardware that 84| 85|22 86|00:00:53,920 --> 00:00:59,920 87|everyone runs AI on is a different 88| 89|23 90|00:00:57,360 --> 00:01:02,559 91|thing. Yes. But also, I don't think you 92| 93|24 94|00:00:59,920 --> 00:01:04,400 95|can ignore how hard Apple has lagged 96| 97|25 98|00:01:02,559 --> 00:01:06,880 99|here. Like I remember when Chhat GPT 100| 101|26 102|00:01:04,400 --> 00:01:09,280 103|first came out and everybody saw this as 104| 105|27 106|00:01:06,880 --> 00:01:10,479 107|like the obvious huge paradigm shift. So 108| 109|28 110|00:01:09,280 --> 00:01:12,560 111|if you're a tech company, you got to 112| 113|29 114|00:01:10,479 --> 00:01:15,520 115|move fast. So they did. Google starts 116| 117|30 118|00:01:12,560 --> 00:01:17,920 119|going crazy. Meta turns the burners on. 120| 121|31 122|00:01:15,520 --> 00:01:20,000 123|Bing was insane for a couple of weeks. I 124| 125|32 126|00:01:17,920 --> 00:01:22,799 127|remember all this action. And then Apple 128| 129|33 130|00:01:20,000 --> 00:01:24,799 131|just nothing. Just nothing from them. 132| 133|34 134|00:01:22,799 --> 00:01:26,960 135|They literally refused to say AI in 136| 137|35 138|00:01:24,799 --> 00:01:28,960 139|their events for months. I know, but 140| 141|36 142|00:01:26,960 --> 00:01:30,320 143|think about it. It's Apple, right? Their 144| 145|37 146|00:01:28,960 --> 00:01:32,159 147|thing has never been being on the 148| 149|38 150|00:01:30,320 --> 00:01:34,640 151|bleeding edge of tech. They always sit 152| 153|39 154|00:01:32,159 --> 00:01:36,880 155|back, let the early adopters figure out 156| 157|40 158|00:01:34,640 --> 00:01:38,960 159|what the pros and cons and the bugs are, 160| 161|41 162|00:01:36,880 --> 00:01:40,479 163|and then they'll step in late with their 164| 165|42 166|00:01:38,960 --> 00:01:42,560 167|own version, taking it to the next level 168| 169|43 170|00:01:40,479 --> 00:01:44,000 171|for their ecosystem, right? Oh, oh, oh, 172| 173|44 174|00:01:42,560 --> 00:01:46,000 175|that's that's what Apple intelligence 176| 177|45 178|00:01:44,000 --> 00:01:48,399 179|is. Apple waiting for the tech to get 180| 181|46 182|00:01:46,000 --> 00:01:50,960 183|good enough for the first 100 million 184| 185|47 186|00:01:48,399 --> 00:01:53,680 187|users of Chacht to work the bugs out. 188| 189|48 190|00:01:50,960 --> 00:01:55,360 191|Like, that can't be right. But okay, 192| 193|49 194|00:01:53,680 --> 00:01:58,079 195|obviously it's past the early adopter 196| 197|50 198|00:01:55,360 --> 00:02:00,399 199|phase, but not every technology has to 200| 201|51 202|00:01:58,079 --> 00:02:01,840 203|be adopted like some kind of race. Like 204| 205|52 206|00:02:00,399 --> 00:02:04,960 207|obviously tech companies are trained to 208| 209|53 210|00:02:01,840 --> 00:02:07,439 211|see emerging stuff as a threat, but this 212| 213|54 214|00:02:04,960 --> 00:02:09,599 215|AI stuff was never a threat to Apple's 216| 217|55 218|00:02:07,439 --> 00:02:10,959 219|core business. Like they're still a 220| 221|56 222|00:02:09,599 --> 00:02:12,560 223|hardware company. Like I you said it 224| 225|57 226|00:02:10,959 --> 00:02:14,720 227|yourself, I've watched your videos. They 228| 229|58 230|00:02:12,560 --> 00:02:17,200 231|are the iPhone company and they sell the 232| 233|59 234|00:02:14,720 --> 00:02:19,760 235|iPhone. Okay. But you would expect still 236| 237|60 238|00:02:17,200 --> 00:02:23,200 239|the company with trillions of dollars to 240| 241|61 242|00:02:19,760 --> 00:02:25,520 243|spend would still see chatbt spin up and 244| 245|62 246|00:02:23,200 --> 00:02:27,120 247|then Gemini and Claude and Meta and all 248| 249|63 250|00:02:25,520 --> 00:02:29,120 251|this other stuff and would think, okay, 252| 253|64 254|00:02:27,120 --> 00:02:31,520 255|number one, this is here to stay and 256| 257|65 258|00:02:29,120 --> 00:02:32,959 259|number two, we should build a version of 260| 261|66 262|00:02:31,520 --> 00:02:34,560 263|our own that's cohesive with our 264| 265|67 266|00:02:32,959 --> 00:02:36,480 267|ecosystem. But Apple Intelligence has 268| 269|68 270|00:02:34,560 --> 00:02:39,440 271|been kind of a joke so far. 272| 273|69 274|00:02:36,480 --> 00:02:43,959 275|>> Yeah. Okay. Hot take. I don't think 276| 277|70 278|00:02:39,440 --> 00:02:43,959 279|Apple intelligence has to be that good. 280| 281|71 282|00:02:44,560 --> 00:02:50,800 283|>> What? Yeah. No, I I basically think it 284| 285|72 286|00:02:47,599 --> 00:02:53,360 287|just has to be good enough for investors 288| 289|73 290|00:02:50,800 --> 00:02:55,360 291|to believe Apple's competitive or just 292| 293|74 294|00:02:53,360 --> 00:02:57,360 295|doing something with AI, but it doesn't 296| 297|75 298|00:02:55,360 --> 00:02:59,920 299|have to be amazing for Apple to still be 300| 301|76 302|00:02:57,360 --> 00:03:04,159 303|winning cuz you're still buying an 304| 305|77 306|00:02:59,920 --> 00:03:06,480 307|iPhone. Okay, but what if I'm not buying 308| 309|78 310|00:03:04,159 --> 00:03:09,440 311|an iPhone? Like, what if I'm if I'm 312| 313|79 314|00:03:06,480 --> 00:03:11,360 315|someone who really cares about AI, then 316| 317|80 318|00:03:09,440 --> 00:03:13,280 319|there's so many other phones that I 320| 321|81 322|00:03:11,360 --> 00:03:15,680 323|would buy before an iPhone, right? I 324| 325|82 326|00:03:13,280 --> 00:03:17,680 327|would buy a Google phone or a Samsung 328| 329|83 330|00:03:15,680 --> 00:03:20,159 331|phone or a Xiaomi phone. They all have 332| 333|84 334|00:03:17,680 --> 00:03:22,400 335|the AI assistants and the writing tools 336| 337|85 338|00:03:20,159 --> 00:03:24,000 339|and the I don't know the photo editing, 340| 341|86 342|00:03:22,400 --> 00:03:25,440 343|all this AI stuff that's way better than 344| 345|87 346|00:03:24,000 --> 00:03:27,280 347|what Apple's been making. Yeah, but 348| 349|88 350|00:03:25,440 --> 00:03:29,200 351|dude, everything you just mentioned is 352| 353|89 354|00:03:27,280 --> 00:03:31,040 355|such a gimmick. Like no one's actually 356| 357|90 358|00:03:29,200 --> 00:03:32,799 359|buying a new phone just to use that 360| 361|91 362|00:03:31,040 --> 00:03:34,879 363|stuff really. Like it almost feels like 364| 365|92 366|00:03:32,799 --> 00:03:36,480 367|Apple's just playing along just to, you 368| 369|93 370|00:03:34,879 --> 00:03:37,840 371|know, have some stuff that's comparable. 372| 373|94 374|00:03:36,480 --> 00:03:40,560 375|Oh yeah, here's some writing tools. 376| 377|95 378|00:03:37,840 --> 00:03:41,840 379|Here's some photo editing with AI and 380| 381|96 382|00:03:40,560 --> 00:03:44,159 383|and then of course the Siri 384| 385|97 386|00:03:41,840 --> 00:03:45,599 387|improvements, you know, Genoji and 388| 389|98 390|00:03:44,159 --> 00:03:47,519 391|Genoji of course. But here, tell me if 392| 393|99 394|00:03:45,599 --> 00:03:50,159 395|you agree with this. All the fastest, 396| 397|100 398|00:03:47,519 --> 00:03:53,200 399|most secure generative AI stuff happens 400| 401|101 402|00:03:50,159 --> 00:03:55,040 403|on device, right? Yeah. And then the 404| 405|102 406|00:03:53,200 --> 00:03:56,799 407|bigger, more capable models, that's what 408| 409|103 410|00:03:55,040 --> 00:03:58,239 411|you go to the cloud for. Exactly. So, as 412| 413|104 414|00:03:56,799 --> 00:04:00,000 415|these ondevice models get better and 416| 417|105 418|00:03:58,239 --> 00:04:02,879 419|better, you go to the cloud less and 420| 421|106 422|00:04:00,000 --> 00:04:04,799 423|less, right? Yeah. So, in the future, 424| 425|107 426|00:04:02,879 --> 00:04:06,080 427|someday, you will basically never have 428| 429|108 430|00:04:04,799 --> 00:04:07,760 431|to go to the cloud. You'll do all your 432| 433|109 434|00:04:06,080 --> 00:04:11,519 435|stuff on device. And who's going to make 436| 437|110 438|00:04:07,760 --> 00:04:13,519 439|that device? Apple. Maybe. I honestly 440| 441|111 442|00:04:11,519 --> 00:04:15,200 443|don't think maybe. I think definitely. 444| 445|112 446|00:04:13,519 --> 00:04:17,680 447|Like in this future where all these 448| 449|113 450|00:04:15,200 --> 00:04:19,919 451|early adopters finally get their local 452| 453|114 454|00:04:17,680 --> 00:04:21,359 455|ondevice models doing tasks for them and 456| 457|115 458|00:04:19,919 --> 00:04:23,280 459|running everything locally with tons of 460| 461|116 462|00:04:21,359 --> 00:04:25,440 463|memory on these machines, Apple's going 464| 465|117 466|00:04:23,280 --> 00:04:27,040 467|to be there to sell those machines. 468| 469|118 470|00:04:25,440 --> 00:04:28,320 471|That's where they fit into this AI 472| 473|119 474|00:04:27,040 --> 00:04:29,919 475|puzzle. And just because they don't do 476| 477|120 478|00:04:28,320 --> 00:04:31,440 479|the software doesn't really mean they're 480| 481|121 482|00:04:29,919 --> 00:04:34,160 483|losing. Like they don't do search 484| 485|122 486|00:04:31,440 --> 00:04:36,800 487|engines either. And they sell you the 488| 489|123 490|00:04:34,160 --> 00:04:38,240 491|device that you do the googling on. So, 492| 493|124 494|00:04:36,800 --> 00:04:40,240 495|yeah. Why do you think Nvidia wants to 496| 497|125 498|00:04:38,240 --> 00:04:42,160 499|make RTX Spark a thing so bad? They want 500| 501|126 502|00:04:40,240 --> 00:04:43,759 503|a piece of that hardware pie, too. 504| 505|127 506|00:04:42,160 --> 00:04:46,639 507|Especially outside the US. Okay. So, 508| 509|128 510|00:04:43,759 --> 00:04:48,639 511|what I what I think I hear you saying is 512| 513|129 514|00:04:46,639 --> 00:04:50,560 515|there's actually two different races. 516| 517|130 518|00:04:48,639 --> 00:04:52,720 519|>> Yeah. In race number one, the 520| 521|131 522|00:04:50,560 --> 00:04:54,160 523|competition is so far ahead, Apple's 524| 525|132 526|00:04:52,720 --> 00:04:56,320 527|kind of already took the L, but they 528| 529|133 530|00:04:54,160 --> 00:04:58,080 531|can't look like they're losing. So, they 532| 533|134 534|00:04:56,320 --> 00:05:00,160 535|have eventually cobbled together enough 536| 537|135 538|00:04:58,080 --> 00:05:02,320 539|of an AI suite to not be embarrassing 540| 541|136 542|00:05:00,160 --> 00:05:04,880 543|anymore. But I think it's pretty clear 544| 545|137 546|00:05:02,320 --> 00:05:07,840 547|that in a world where company A pays 548| 549|138 550|00:05:04,880 --> 00:05:10,320 551|company B a billion dollars a year, 552| 553|139 554|00:05:07,840 --> 00:05:12,000 555|company B already won. Fair enough. But 556| 557|140 558|00:05:10,320 --> 00:05:14,320 559|in race number two, 560| 561|141 562|00:05:12,000 --> 00:05:17,199 563|>> the finish line is way out on the 564| 565|142 566|00:05:14,320 --> 00:05:20,240 567|horizon. And Apple does have a bit of a 568| 569|143 570|00:05:17,199 --> 00:05:22,639 571|head start because they still make the 572| 573|144 574|00:05:20,240 --> 00:05:24,800 575|iPhone and Apple is going to protect 576| 577|145 578|00:05:22,639 --> 00:05:27,120 579|that iPhone's position with everything 580| 581|146 582|00:05:24,800 --> 00:05:29,919 583|they've got. Now, they could still win 584| 585|147 586|00:05:27,120 --> 00:05:31,759 587|that race in a way, but also there's 588| 589|148 590|00:05:29,919 --> 00:05:34,479 591|nothing preventing OpenAI from coming 592| 593|149 594|00:05:31,759 --> 00:05:36,400 595|along and making a phone and taking 596| 597|150 598|00:05:34,479 --> 00:05:38,080 599|everything from Apple, the iPhone 600| 601|151 602|00:05:36,400 --> 00:05:39,360 603|company. There are so many rumors of 604| 605|152 606|00:05:38,080 --> 00:05:41,680 607|them working on something like that 608| 609|153 610|00:05:39,360 --> 00:05:43,360 611|already. Yeah. Okay. So, Apple's going 612| 613|154 614|00:05:41,680 --> 00:05:44,639 615|to enter a new product category and 616| 617|155 618|00:05:43,360 --> 00:05:46,400 619|they're going to do it the exact same 620| 621|156 622|00:05:44,639 --> 00:05:49,199 623|way they always do, which is by making 624| 625|157 626|00:05:46,400 --> 00:05:50,639 627|it work the best with the iPhone. And 628| 629|158 630|00:05:49,199 --> 00:05:52,240 631|actually, that's what they're doing with 632| 633|159 634|00:05:50,639 --> 00:05:54,240 635|the Have you tried the beta? the new 636| 637|160 638|00:05:52,240 --> 00:05:57,440 639|Apple intelligence stuff like Siri pulls 640| 641|161 642|00:05:54,240 --> 00:06:00,479 643|from iMessage and Apple calendar and 644| 645|162 646|00:05:57,440 --> 00:06:03,520 647|photos in a way that the Chat GPT app on 648| 649|163 650|00:06:00,479 --> 00:06:07,120 651|the iPhone never could. But Siri doesn't 652| 653|164 654|00:06:03,520 --> 00:06:09,120 655|like excel at anything that chat GPT or 656| 657|165 658|00:06:07,120 --> 00:06:11,280 659|Gemini doesn't already do. Like we're 660| 661|166 662|00:06:09,120 --> 00:06:13,120 663|not coding apps or anything with Siri. 664| 665|167 666|00:06:11,280 --> 00:06:15,039 667|It it doesn't even work in the 668| 669|168 670|00:06:13,120 --> 00:06:16,880 671|background. So you can't leave it and 672| 673|169 674|00:06:15,039 --> 00:06:18,560 675|come back later for large requests like 676| 677|170 678|00:06:16,880 --> 00:06:20,000 679|you can in the others. It also doesn't 680| 681|171 682|00:06:18,560 --> 00:06:21,919 683|remember anything about you without 684| 685|172 686|00:06:20,000 --> 00:06:23,600 687|making notes in the iPhone's notes app. 688| 689|173 690|00:06:21,919 --> 00:06:24,960 691|So, it just has way less of that 692| 693|174 694|00:06:23,600 --> 00:06:26,720 695|personal context. Like, that's just 696| 697|175 698|00:06:24,960 --> 00:06:29,039 699|basic stuff you can already do today 700| 701|176 702|00:06:26,720 --> 00:06:31,680 703|with the chat GBT app on the iPhone. 704| 705|177 706|00:06:29,039 --> 00:06:34,000 707|Yeah. Okay. So, the real question is, do 708| 709|178 710|00:06:31,680 --> 00:06:36,639 711|you think an AI company is going to come 712| 713|179 714|00:06:34,000 --> 00:06:39,360 715|along and make some new hardware that's 716| 717|180 718|00:06:36,639 --> 00:06:41,440 719|so good that I can get people to switch 720| 721|181 722|00:06:39,360 --> 00:06:44,960 723|from the iPhone? 724| 725|182 726|00:06:41,440 --> 00:06:48,160 727|Or do you believe Apple could make their 728| 729|183 730|00:06:44,960 --> 00:06:51,160 731|AI good enough to keep people on the 732| 733|184 734|00:06:48,160 --> 00:06:51,160 735|iPhone? 736| 737|185 738|00:06:52,319 --> 00:06:55,960 739|>> So, I won, right? 740| 741|186 742|00:06:58,880 --> 00:07:02,759 743|Hey, what are you all talking about? </file-view>
Now I have the captions. Let me summarize the video. The video is a debate/conversation between two people about whether Apple has "won" or "lost" the AI race. One person argues Apple actually won because they make the hardware that everyone will run AI on, and they can enter late like they always do. The other person argues Apple lost the AI race because they lagged, Apple Intelligence has been weak, and other companies (OpenAI, Google, Meta, Samsung, Xiaomi) are far ahead in AI assistants and features. They conclude with the question: Will an AI company create hardware good enough to make people switch from iPhone, or will Apple make AI good enough to keep people on iPhone? The speakers also mention: - Apple announced new Siri but didn't deliver for 2 years and had to start over with help from Google - Apple refused to say "AI" in events for months - Apple is a hardware company/iPhone company - On-device AI vs cloud AI - Nvidia RTX Spark - Apple Intelligence beta with Siri pulling from iMessage, Calendar, Photos - Rumors of OpenAI making a phone The video is short (about 7 minutes). Let me also check the title of the video to get more context. I can use yt-dlp --print title.
{
"command": "yt-dlp --no-update --print \"%(title)s\" --print \"%(uploader)s\" --print \"%(duration)s\" \"https://www.youtube.com/watch?v=eWKY0OnPByg&pp=ugUEEgJlbtIHCQlPCwGHKiGM7w%3D%3D\"",
"timeout": 30000
}Output from command in shell 78fabd: WARNING: [youtube] [jsc] Remote components challenge solver script (deno) and NPM package (deno) were skipped. These may be required to solve JS challenges. You can enable these downloads with --remote-components ejs:github (recommended) or --remote-components ejs:npm , respectively. For more information and alternatives, refer to https://github.com/yt-dlp/yt-dlp/wiki/EJS WARNING: [youtube] eWKY0OnPByg: n challenge solving failed: Some formats may be missing. Ensure you have a supported JavaScript runtime and challenge solver script distribution installed. Review any warnings presented before this message. For more details, refer to https://github.com/yt-dlp/yt-dlp/wiki/EJS Apple Lost the AI Race Marques Brownlee 423 Exit code: 0
Great, so the video is "Apple Lost the AI Race" by Marques Brownlee (MKBHD), 423 seconds = 7:03 long. This appears to be a discussion/debate about whether Apple lost the AI race. One speaker argues Apple won, the other argues they lost. Marques Brownlee is the uploader, likely one of the speakers (probably the one arguing Apple lost based on the title). Now I'll provide a concise summary.
Video: "Apple Lost the AI Race" by Marques Brownlee (7:03)
Summary:
The video is a debate between two speakers about whether Apple has won or lost the AI race.
A third person walks in at the end and asks what they're talking about.