Instruction:
## Skills
A skill is a set of local instructions to follow that is stored in a `SKILL.md` file. Below is the list of skills that can be used. Each entry includes a name, description, and file path so you can open the source for full instructions when using a specific skill.
### Available skills
- skill-creator: Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Codex's capabilities with specialized knowledge, workflows, or tool integrations. (file: /home/ubuntu/.codex/skills/.system/skill-creator/SKILL.md)
- skill-installer: Install Codex skills into $CODEX_HOME/skills from a curated list or a GitHub repo path. Use when a user asks to list installable skills, install a curated skill, or install a skill from another repo (including private repos). (file: /home/ubuntu/.codex/skills/.system/skill-installer/SKILL.md)
### How to use skills
- Discovery: The list above is the skills available in this session (name + description + file path). Skill bodies live on disk at the listed paths.
- Trigger rules: If the user names a skill (with `$SkillName` or plain text) OR the task clearly matches a skill's description shown above, you must use that skill for that turn. Multiple mentions mean use them all. Do not carry skills across turns unless re-mentioned.
- Missing/blocked: If a named skill isn't in the list or the path can't be read, say so briefly and continue with the best fallback.
- How to use a skill (progressive disclosure):
  1) After deciding to use a skill, open its `SKILL.md`. Read only enough to follow the workflow.
  2) If `SKILL.md` points to extra folders such as `references/`, load only the specific files needed for the request; don't bulk-load everything.
  3) If `scripts/` exist, prefer running or patching them instead of retyping large code blocks.
  4) If `assets/` or templates exist, reuse them instead of recreating from scratch.
- Coordination and sequencing:
  - If multiple skills apply, choose the minimal set that covers the request and state the order you'll use them.
  - Announce which skill(s) you're using and why (one short line). If you skip an obvious skill, say why.
- Context hygiene:
  - Keep context small: summarize long sections instead of pasting them; only load extra files when needed.
  - Avoid deep reference-chasing: prefer opening only files directly linked from `SKILL.md` unless you're blocked.
  - When variants exist (frameworks, providers, domains), pick only the relevant reference file(s) and note that choice.
- Safety and fallback: If a skill can't be applied cleanly (missing files, unclear instructions), state the issue, pick the next-best approach, and continue.


# AGENTS.md instructions for /home/ubuntu/maya3

<INSTRUCTIONS>
## Skills
A skill is a set of local instructions to follow that is stored in a `SKILL.md` file. Below is the list of skills that can be used. Each entry includes a name, description, and file path so you can open the source for full instructions when using a specific skill.
### Available skills
- skill-creator: Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Codex's capabilities with specialized knowledge, workflows, or tool integrations. (file: /home/ubuntu/.codex/skills/.system/skill-creator/SKILL.md)
- skill-installer: Install Codex skills into $CODEX_HOME/skills from a curated list or a GitHub repo path. Use when a user asks to list installable skills, install a curated skill, or install a skill from another repo (including private repos). (file: /home/ubuntu/.codex/skills/.system/skill-installer/SKILL.md)
### How to use skills
- Discovery: The list above is the skills available in this session (name + description + file path). Skill bodies live on disk at the listed paths.
- Trigger rules: If the user names a skill (with `$SkillName` or plain text) OR the task clearly matches a skill's description shown above, you must use that skill for that turn. Multiple mentions mean use them all. Do not carry skills across turns unless re-mentioned.
- Missing/blocked: If a named skill isn't in the list or the path can't be read, say so briefly and continue with the best fallback.
- How to use a skill (progressive disclosure):
  1) After deciding to use a skill, open its `SKILL.md`. Read only enough to follow the workflow.
  2) If `SKILL.md` points to extra folders such as `references/`, load only the specific files needed for the request; don't bulk-load everything.
  3) If `scripts/` exist, prefer running or patching them instead of retyping large code blocks.
  4) If `assets/` or templates exist, reuse them instead of recreating from scratch.
- Coordination and sequencing:
  - If multiple skills apply, choose the minimal set that covers the request and state the order you'll use them.
  - Announce which skill(s) you're using and why (one short line). If you skip an obvious skill, say why.
- Context hygiene:
  - Keep context small: summarize long sections instead of pasting them; only load extra files when needed.
  - Avoid deep reference-chasing: prefer opening only files directly linked from `SKILL.md` unless you're blocked.
  - When variants exist (frameworks, providers, domains), pick only the relevant reference file(s) and note that choice.
- Safety and fallback: If a skill can't be applied cleanly (missing files, unclear instructions), state the issue, pick the next-best approach, and continue.
</INSTRUCTIONS>


<environment_context>
  <cwd>/home/ubuntu/maya3</cwd>
  <approval_policy>on-request</approval_policy>
  <sandbox_mode>workspace-write</sandbox_mode>
  <network_access>restricted</network_access>
  <shell>bash</shell>
</environment_context>


<environment_context>
  <approval_policy>never</approval_policy>
  <sandbox_mode>danger-full-access</sandbox_mode>
  <network_access>enabled</network_access>
  <shell>bash</shell>
</environment_context>


# Context from my IDE setup:

## Open tabs:
- .env: .env

## My request for Codex:
we are currently at 40,676 videos done. Can you go through the supabase and confirm if each of the completed video has a corresponding R2 url and that exists actually in R2 ?


Summary: auto

## Skills
A skill is a set of local instructions to follow that is stored in a `SKILL.md` file. Below is the list of skills that can be used. Each entry includes a name, description, and file path so you can open the source for full instructions when using a specific skill.
### Available skills
- skill-creator: Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Codex's capabilities with specialized knowledge, workflows, or tool integrations. (file: /home/ubuntu/.codex/skills/.system/skill-creator/SKILL.md)
- skill-installer: Install Codex skills into $CODEX_HOME/skills from a curated list or a GitHub repo path. Use when a user asks to list installable skills, install a curated skill, or install a skill from another repo (including private repos). (file: /home/ubuntu/.codex/skills/.system/skill-installer/SKILL.md)
### How to use skills
- Discovery: The list above is the skills available in this session (name + description + file path). Skill bodies live on disk at the listed paths.
- Trigger rules: If the user names a skill (with `$SkillName` or plain text) OR the task clearly matches a skill's description shown above, you must use that skill for that turn. Multiple mentions mean use them all. Do not carry skills across turns unless re-mentioned.
- Missing/blocked: If a named skill isn't in the list or the path can't be read, say so briefly and continue with the best fallback.
- How to use a skill (progressive disclosure):
  1) After deciding to use a skill, open its `SKILL.md`. Read only enough to follow the workflow.
  2) If `SKILL.md` points to extra folders such as `references/`, load only the specific files needed for the request; don't bulk-load everything.
  3) If `scripts/` exist, prefer running or patching them instead of retyping large code blocks.
  4) If `assets/` or templates exist, reuse them instead of recreating from scratch.
- Coordination and sequencing:
  - If multiple skills apply, choose the minimal set that covers the request and state the order you'll use them.
  - Announce which skill(s) you're using and why (one short line). If you skip an obvious skill, say why.
- Context hygiene:
  - Keep context small: summarize long sections instead of pasting them; only load extra files when needed.
  - Avoid deep reference-chasing: prefer opening only files directly linked from `SKILL.md` unless you're blocked.
  - When variants exist (frameworks, providers, domains), pick only the relevant reference file(s) and note that choice.
- Safety and fallback: If a skill can't be applied cleanly (missing files, unclear instructions), state the issue, pick the next-best approach, and continue.


**Considering Supabase integration**

I'm thinking about using `rg` to search for "supabase" and reviewing the .env file for credentials. I realize I need to be careful about secrets and only parse the variable names, not their values. Then, I’ll write either a Node or Python script to query Supabase. I could use the Supabase JS client or PostgREST API, but I must ensure dependencies are installed. It's also vital to gather the right table and columns for querying. Lastly, I'll check if the object exists in R2.


**Exploring R2 with AWS SDK**

I need to work with R2, which uses the S3 API, and I'm considering using the AWS SDK or the AWS CLI command `aws s3api head-object` if it's installed. However, checking 40,000 objects could be slow. Using Python's boto3 with `head_object` or `list_objects_v2` to compare keys sounds good, especially if the objects have known prefixes. I should also consider listing buckets for efficiency. In the end, I'll try to both parse keys from URLs and list unique buckets or prefixes to minimize network requests.


**Verifying R2 URLs and access**

I’m looking into R2 URLs, which might be in the public domain. To verify existence, I need an S3 client and relevant credentials from the .env file, like access keys and bucket information. But if the URL isn’t a standard S3 path, it might be a signed URL or direct link. I’ll check if the URL indicates a public bucket format. I’ll also store the mapping from completed videos to URLs and keys while using heuristics based on the URL’s structure. Lastly, I need to remember to parse the environment bucket for any overrides.


**Implementing R2 script**

I’m planning to determine the bucket size based on the host. If the host starts with the bucket followed by a dot, I’ll use that; otherwise, I’ll fall back to the environment bucket, which is likely constant. I want to create a script that supports concurrency and retries. I'll fetch a list from Supabase, using offset and limit to manage the 40,676 entries. For HTTP requests, I might use the `requests` library, or revert to Python's standard `urllib` if needed. I’ll also check if boto3 is available for S3 access. Let’s get started!


Output:
Exit code: 0
Wall time: 0 seconds
Output:
total 396
drwxrwxr-x 13 ubuntu ubuntu   4096 Jan  8 04:16 .
drwxr-x--- 38 ubuntu ubuntu   4096 Jan  8 15:24 ..
drwxrwxr-x  3 ubuntu ubuntu   4096 Jan  8 00:45 .cache
drwx------  2 ubuntu ubuntu   4096 Jan  8 15:25 .claude
drwxrwxr-x  7 ubuntu ubuntu   4096 Jan  8 04:29 dashboard-ui
drwxrwxr-x  3 ubuntu ubuntu   4096 Jan  8 00:32 data
-rw-rw-r--  1 ubuntu ubuntu   1950 Jan  6 22:23 docker-compose.yml
-rw-rw-r--  1 ubuntu ubuntu   4672 Jan  8 06:01 Dockerfile
-rw-rw-r--  1 ubuntu ubuntu    213 Jan  6 22:23 .dockerignore
-rw-rw-r--  1 ubuntu ubuntu   3704 Jan  6 22:23 .env
-rw-rw-r--  1 ubuntu ubuntu    470 Jan  6 22:23 .env.example
drwxrwxr-x  9 ubuntu ubuntu   4096 Jan  8 15:24 .git
-rw-rw-r--  1 ubuntu ubuntu    568 Jan  8 04:16 .gitignore
-rwxrwxr-x  1 ubuntu ubuntu  53390 Jan  8 14:27 massive_process.py
-rw-rw-r--  1 ubuntu ubuntu 131296 Jan  8 01:02 metadata.json
drwxr-xr-x  4 root   root     4096 Jan  8 02:27 output
-rw-rw-r--  1 ubuntu ubuntu  68301 Jan  8 06:01 pipeline.py
drwxrwxr-x  2 ubuntu ubuntu   4096 Jan  8 14:57 __pycache__
-rw-rw-r--  1 ubuntu ubuntu   3654 Jan  8 00:31 README.md
-rw-rw-r--  1 ubuntu ubuntu    623 Jan  8 02:14 requirements.txt
drwxrwxr-x  7 ubuntu ubuntu   4096 Jan  8 05:31 scripts
drwxrwxr-x  3 ubuntu ubuntu   4096 Jan  8 05:14 src
-rw-rw-r--  1 ubuntu ubuntu  30615 Jan  6 22:23 vast_ai.md
-rw-rw-r--  1 ubuntu ubuntu  19445 Jan  6 22:23 vast_ai_sdk.md
drwxrwxr-x  2 ubuntu ubuntu   4096 Jan  8 04:16 .vercel
drwxrwxr-x  2 ubuntu ubuntu   4096 Jan  6 22:31 .xdg_run


Summary: auto


**Exploring Python script needs**

It seems like I’m considering creating a Python script, and I’m thinking about whether the requirements.txt file needs to include Supabase. I should check what dependencies I actually need for the script to run. I wonder if there are other libraries that would be useful too. I'll need to clarify these dependencies to avoid any potential issues later. So, let's inspect the requirements thoroughly!


Output:
Exit code: 0
Wall time: 0 seconds
Output:
# Core ML frameworks
torch
torchaudio
transformers

# Audio processing
librosa
soundfile
pydub
audioread
tensorflow[and-cuda]

# Speech models and tools
speechbrain
resemblyzer
openai-whisper
demucs

# PyAnnote for diarization (requires HF token with model access)
pyannote.audio>=3.1.0

# Quality metrics
pesq
pystoi

# YouTube downloading (fallback)
yt-dlp

# Data processing
numpy
scipy
pandas
scikit-learn

# Cloud services
boto3
supabase
google-cloud-storage

# Utilities
tqdm
pyyaml
python-dotenv

# Additional audio utilities
webrtcvad
noisereduce
panns-inference

# Hybrid music detection
inaSpeechSegmenter>=0.8.0


**Working with Supabase**

I'm excited that I have both boto3 and the Supabase Python client ready to use! I need to query Supabase using the supabase-py library, which is straightforward. First, I'll inspect the .env file to check that I have the correct Supabase and R2 variables. It's really important to avoid leaking any sensitive values when I'm parsing this. Let’s make sure everything is set up properly for a smooth workflow!


python - <<'PY'
import os
from dotenv import dotenv_values
vals = dotenv_values('.env')
keys = sorted(vals.keys())
print('ENV_KEYS:', len(keys))
for k in keys:
    if k.strip():
        print(k)
PY


Output:
Exit code: 127
Wall time: 0 seconds
Output:
/bin/bash: line 1: python: command not found


**Choosing Python version**

I’m considering which Python version to use, and I think it might be better to opt for python3. It’s pretty common now, and I want to ensure I’m using the most up-to-date features. It seems like a simple choice, but it's essential to get it right to avoid any compatibility issues later on. So, I'll stick with python3 for my purposes!


python3 - <<'PY'
from dotenv import dotenv_values
vals = dotenv_values('.env')
keys = sorted(k for k in vals.keys() if k)
print('ENV_KEYS:', len(keys))
for k in keys:
    print(k)
PY


Output:
Exit code: 0
Wall time: 0.1 seconds
Output:
ENV_KEYS: 28
ACCOUNT_ID
API_TOKEN
DATABASE
DATABASE_URL
HF_TOKEN
HOST
MAX_CONSECUTIVE_EMPTY
MAX_UTILIZATION
NGROK
ORCHESTRATOR_URL
PORT
PROJECT_ID
R2_ACCESS_KEY_ID
R2_BUCKET
R2_ENDPOINT_URL
R2_PREFIX
R2_SECRET_ACCESS_KEY
RUNPOD_KEY
S3_API
SUPABASE_ADMIN
SUPABASE_ANON
URL
USER
VAST_AI
WORKER_PROVIDER
WORKER_REGION
docker_image
docker_pat


**Checking Supabase setup**

I see that we have SUPABASE_ADMIN, which is likely the service role key, and there’s also a DATABASE_URL. It looks like I might need to use supabase-py with SUPABASE_URL and SUPABASE_KEY, which may involve checking the URL variable. I’ll need to look at the .env.example to clarify what and how to set things up properly. I want to ensure everything is in order for initialization.


Output:
Exit code: 0
Wall time: 0 seconds
Output:
# Maya3 Pipeline Environment Variables
# Copy this file to .env and fill in your values

# Hugging Face (required for PyAnnote models)
HF_TOKEN=hf_your_token_here

# Supabase (required for queue management)
URL=https://your-project.supabase.co
SUPABASE_ADMIN=your_service_role_key_here

# Cloudflare R2 (required for audio source and output)
ACCOUNT_ID=your_cloudflare_account_id
API_TOKEN=your_r2_api_token

# Optional: RunPod deployment
RUNPOD_KEY=your_runpod_api_key


**Checking Supabase usage**

I need to confirm that the URL is indeed the Supabase URL and that the service key refers to the admin. I'll make sure to check the schema, possibly looking into the source or pipeline for how Supabase is being utilized. It's also important to search for the specific table names to ensure I have all the necessary details for whatever I'm trying to accomplish here. Let's keep things organized!


rg -n "from\('" -S src pipeline.py massive_process.py scripts | head


Output:
Exit code: 0
Wall time: 0 seconds
Output:


I'm thinking about how supabase-py might work, particularly with its use of methods like `.table()`. It seems like a good idea to look up information on "supabase" to get more details. I want to ensure I’m on the right track, discovering the specific functionalities and methods available, which could really help me understand how to use it effectively. Exploring this further might bring clarity—let's see what I can find!


Output:
Exit code: 0
Wall time: 0 seconds
Output:
./requirements.txt:37:supabase
./pipeline.py:125:    supabase_metadata: Optional[Dict] = None,
./pipeline.py:134:    === v3: Supabase Metadata Support ===
./pipeline.py:135:    If supabase_metadata is provided, it's passed to download_audio for:
./pipeline.py:217:        # Standard download (with optional Supabase metadata for chapters)
./pipeline.py:219:            audio_path, metadata = download_audio(video_url, config, supabase_metadata=supabase_metadata)
./pipeline.py:1018:                # locate outputs in R2 from Supabase without guessing prefixes.
./dashboard-ui/package.json:14:    "@supabase/supabase-js": "2.43.4",
./dashboard-ui/app/api/stats/route.js:1:import { createClient } from '@supabase/supabase-js'
./dashboard-ui/app/api/stats/route.js:6:function getSupabase() {
./dashboard-ui/app/api/stats/route.js:8:    process.env.SUPABASE_URL,
./dashboard-ui/app/api/stats/route.js:9:    process.env.SUPABASE_ADMIN_KEY
./dashboard-ui/app/api/stats/route.js:13:async function getQueueStats(supabase) {
./dashboard-ui/app/api/stats/route.js:16:    const { count } = await supabase
./dashboard-ui/app/api/stats/route.js:25:async function getWorkerStatus(supabase) {
./dashboard-ui/app/api/stats/route.js:26:  const { data } = await supabase
./dashboard-ui/app/api/stats/route.js:33:async function getRecentErrors(supabase, limit = 10) {
./dashboard-ui/app/api/stats/route.js:34:  const { data } = await supabase
./dashboard-ui/app/api/stats/route.js:42:async function getErrorSummary(supabase) {
./dashboard-ui/app/api/stats/route.js:43:  const { data } = await supabase
./dashboard-ui/app/api/stats/route.js:55:async function getRecentPerformance(supabase, windowMinutes = 60) {
./dashboard-ui/app/api/stats/route.js:58:  const { data } = await supabase
./dashboard-ui/app/api/stats/route.js:86:async function getHourlyThroughput(supabase, days = 7) {
./dashboard-ui/app/api/stats/route.js:90:  const { data, error } = await supabase
./dashboard-ui/app/api/stats/route.js:138:async function getInstanceHourlyAudio(supabase, workers, days = 7) {
./dashboard-ui/app/api/stats/route.js:148:  const { data, error } = await supabase
./dashboard-ui/app/api/stats/route.js:204:async function getStaleWorkers(supabase, thresholdSec = 300) {
./dashboard-ui/app/api/stats/route.js:207:  const { data } = await supabase
./dashboard-ui/app/api/stats/route.js:218:    const supabase = getSupabase()
./dashboard-ui/app/api/stats/route.js:222:        getQueueStats(supabase),
./dashboard-ui/app/api/stats/route.js:223:        getWorkerStatus(supabase),
./dashboard-ui/app/api/stats/route.js:224:        getRecentErrors(supabase, 10),
./dashboard-ui/app/api/stats/route.js:225:        getErrorSummary(supabase),
./dashboard-ui/app/api/stats/route.js:226:        getRecentPerformance(supabase, 60),
./dashboard-ui/app/api/stats/route.js:227:        getRecentPerformance(supabase, 10),
./dashboard-ui/app/api/stats/route.js:228:        getHourlyThroughput(supabase),
./dashboard-ui/app/api/stats/route.js:229:        getStaleWorkers(supabase)
./dashboard-ui/app/api/stats/route.js:233:    const instanceAudioRace = await getInstanceHourlyAudio(supabase, workers)
./Dockerfile:59:    .venv/bin/pip install --no-cache-dir supabase
./Dockerfile:116:# Default command - Supabase queue mode with R2 upload
./Dockerfile:121:CMD ["--supabase-queue", "--r2-upload", "--output", "./output"]
./docker-compose.yml:13:  # Main GPU worker - processes videos from Supabase queue
./docker-compose.yml:45:      --supabase-queue
./scripts/sync_csv_to_supabase.py:3:Sync CSVs to Supabase
./scripts/sync_csv_to_supabase.py:6:then upserts to Supabase videos table.
./scripts/sync_csv_to_supabase.py:10:    python scripts/sync_csv_to_supabase.py
./scripts/sync_csv_to_supabase.py:13:    python scripts/sync_csv_to_supabase.py --limit 100
./scripts/sync_csv_to_supabase.py:16:    python scripts/sync_csv_to_supabase.py --dry-run --limit 10
./scripts/sync_csv_to_supabase.py:31:from src.supabase_client import SupabaseClient
./scripts/sync_csv_to_supabase.py:75:def transform_to_supabase_schema(df: pd.DataFrame) -> list:


Output:
Exit code: 0
Wall time: 0 seconds
Output:
#!/usr/bin/env python3
"""
Supabase Client for Distributed Video Processing Queue

Provides:
- Atomic video claiming with lease-based locking
- Status updates after processing
- Bulk upsert for CSV imports
- Queue statistics

Usage:
    from src.supabase_client import SupabaseClient

    client = SupabaseClient()
    video = client.claim_next_video("worker-1")
    if video:
        # Process video...
        client.update_status(video['youtube_id'], 'COMPLETED', results)
"""

import os
import json
import logging
import time
import random
import socket
from datetime import datetime, timezone
from typing import Dict, Any, Optional, List
from urllib.request import Request, urlopen
from urllib.error import HTTPError, URLError
from urllib.parse import urlencode

logger = logging.getLogger("SupabaseClient")

# Status constants
STATUS_PENDING = 'PENDING'
STATUS_CLAIMED = 'CLAIMED'
STATUS_COMPLETED = 'COMPLETED'
STATUS_FAILED = 'FAILED'
STATUS_SKIPPED = 'SKIPPED'

class SupabaseClient:
    """
    Supabase REST API client for video processing queue.

    Uses atomic claims via RPC function for distributed workers.
    """

    _instance = None

    def __new__(cls, *args, **kwargs):
        """Singleton pattern - reuse connection."""
        if cls._instance is None:
            cls._instance = super().__new__(cls)
            cls._instance._initialized = False
        return cls._instance

    def __init__(self, url: str = None, key: str = None):
        """
        Initialize Supabase client.

        Args:
            url: Supabase project URL (loads from URL env var if None)
            key: Service role key (loads from SUPABASE_ADMIN env var if None)
        """
        if self._initialized:
            return

        self.url = url or os.environ.get('URL', '')
        self.key = key or os.environ.get('SUPABASE_ADMIN', '')

        if not self.url or not self.key:
            logger.warning("Supabase credentials not configured. Set URL and SUPABASE_ADMIN env vars.")

        self.rest_url = f"{self.url}/rest/v1"
        self.headers = {
            'apikey': self.key,
            'Authorization': f'Bearer {self.key}',
            'Content-Type': 'application/json',
            'Prefer': 'return=representation'
        }

        self._initialized = True
        logger.info(f"SupabaseClient initialized: {self.url}")

    def _request(
        self,
        method: str,
        endpoint: str,
        data: dict = None,
        params: dict = None,
        headers_override: dict = None
    ) -> Any:
        """Make HTTP request to Supabase REST API."""
        url = f"{self.rest_url}/{endpoint}"
        if params:
            url = f"{url}?{urlencode(params)}"

        headers = {**self.headers, **(headers_override or {})}

        body = json.dumps(data).encode('utf-8') if data else None

        req = Request(url, data=body, headers=headers, method=method)

        timeout_s = float(os.environ.get("SUPABASE_HTTP_TIMEOUT_SEC", "60") or 60)
        max_attempts = int(os.environ.get("SUPABASE_HTTP_MAX_ATTEMPTS", "6") or 6)
        retryable_codes = {408, 409, 425, 429, 500, 502, 503, 504}

        last_err: Exception | None = None
        for attempt in range(1, max_attempts + 1):
            try:
                with urlopen(req, timeout=timeout_s) as resp:
                    content = resp.read().decode("utf-8")
                    return json.loads(content) if content else None
            except HTTPError as e:
                error_body = e.read().decode("utf-8", errors="replace")
                last_err = e
                if e.code in retryable_codes and attempt < max_attempts:
                    sleep_s = min(30.0, (2 ** (attempt - 1)) * (0.5 + random.random()))
                    logger.warning(
                        f"Supabase HTTP {e.code} on {endpoint} (attempt {attempt}/{max_attempts}): "
                        f"{error_body[:200]}. Retrying in {sleep_s:.1f}s..."
                    )
                    time.sleep(sleep_s)
                    continue
                logger.error(f"Supabase error {e.code}: {error_body}")
                raise
            except (URLError, socket.timeout, TimeoutError) as e:
                last_err = e
                if attempt < max_attempts:
                    sleep_s = min(30.0, (2 ** (attempt - 1)) * (0.5 + random.random()))
                    logger.warning(
                        f"Supabase network/timeout on {endpoint} (attempt {attempt}/{max_attempts}): {e}. "
                        f"Retrying in {sleep_s:.1f}s..."
                    )
                    time.sleep(sleep_s)
                    continue
                logger.error(f"Network error: {getattr(e, 'reason', e)}")
                raise

        # Defensive: should have returned or raised.
        if last_err is not None:
            raise last_err
        return None

    def _rpc(self, function_name: str, params: dict = None) -> Any:
        """Call Supabase RPC function."""
        url = f"{self.url}/rest/v1/rpc/{function_name}"

        body = json.dumps(params or {}).encode('utf-8')
        req = Request(url, data=body, headers=self.headers, method='POST')

        timeout_s = float(os.environ.get("SUPABASE_HTTP_TIMEOUT_SEC", "60") or 60)
        max_attempts = int(os.environ.get("SUPABASE_HTTP_MAX_ATTEMPTS", "6") or 6)
        retryable_codes = {408, 409, 425, 429, 500, 502, 503, 504}

        last_err: Exception | None = None
        for attempt in range(1, max_attempts + 1):
            try:
                with urlopen(req, timeout=timeout_s) as resp:
                    content = resp.read().decode("utf-8")
                    return json.loads(content) if content else None
            except HTTPError as e:
                error_body = e.read().decode("utf-8", errors="replace")
                last_err = e
                if e.code in retryable_codes and attempt < max_attempts:
                    sleep_s = min(30.0, (2 ** (attempt - 1)) * (0.5 + random.random()))
                    logger.warning(
                        f"Supabase RPC HTTP {e.code} {function_name} (attempt {attempt}/{max_attempts}): "
                        f"{error_body[:200]}. Retrying in {sleep_s:.1f}s..."
                    )
                    time.sleep(sleep_s)
                    continue
                logger.error(f"RPC error {e.code}: {error_body}")
                raise
            except (URLError, socket.timeout, TimeoutError) as e:
                last_err = e
                if attempt < max_attempts:
                    sleep_s = min(30.0, (2 ** (attempt - 1)) * (0.5 + random.random()))
                    logger.warning(
                        f"Supabase RPC network/timeout {function_name} (attempt {attempt}/{max_attempts}): {e}. "
                        f"Retrying in {sleep_s:.1f}s..."
                    )
                    time.sleep(sleep_s)
                    continue
                logger.error(f"RPC network error: {getattr(e, 'reason', e)}")
                raise

        if last_err is not None:
            raise last_err
        return None

    def claim_next_video(
        self,
        worker_id: str,
        lease_duration_sec: int = 900,
        language: str = None
    ) -> Optional[Dict[str, Any]]:
        """
        Atomically claim the next PENDING video.

        Uses RPC function with FOR UPDATE SKIP LOCKED for safe concurrent access.
        Falls back to REST API claim if RPC not available.

        Args:
            worker_id: Unique identifier for this worker
            lease_duration_sec: How long to hold the claim (default 15 min)
            language: Optional language filter

        Returns:
            Video dict with youtube_id, youtube_url, title, etc. or None if queue empty
        """
        try:
            # Try RPC function first (atomic)
            result = self._rpc('claim_next_video', {
                'p_worker_id': worker_id,
                'p_lease_duration_sec': lease_duration_sec
            })


**Locating update_status**

I'm reflecting on the fact that SupabaseClient uses REST instead of supabase-py. I think there’s probably a videos table I need to consider. My next step is to check for the update_status function or equivalent. I want to ensure I find the right details, so I’ll scan through the relevant sections further. It's essential to keep track of where everything is located for the task at hand!


rg -n "rest/v1" -n src/supabase_client.py && rg -n "videos" src/supabase_client.py | head -n 50


Output:
Exit code: 0
Wall time: 0 seconds
Output:
76:        self.rest_url = f"{self.url}/rest/v1"
149:        url = f"{self.url}/rest/v1/rpc/{function_name}"
255:        videos = self._request('GET', 'videos', params=params)
257:        if not videos:
260:        video = videos[0]
286:            'videos',
357:            result = self._request('PATCH', 'videos', data=update_data, params=params)
381:            self._request('PATCH', 'videos', data=update_data, params=params)
390:        videos: List[Dict[str, Any]],
395:        Batch upsert videos to database.
398:            videos: List of video dicts
407:        for i in range(0, len(videos), batch_size):
408:            batch = videos[i:i + batch_size]
422:                    'videos',
442:        result = self._request('GET', 'videos', params=params)
464:                url = f"{self.rest_url}/videos?{urlencode(params)}"
479:        """Get count of pending videos."""
485:        Reset videos with expired leases back to PENDING.
490:            Number of videos reset
494:        # Find claimed videos with expired leases
508:            result = self._request('PATCH', 'videos', data=update_data, params=params)


sed -n '220,520p' src/supabase_client.py


Output:
Exit code: 0
Wall time: 0 seconds
Output:

            if result and len(result) > 0:
                video = result[0]
                logger.info(f"Claimed video: {video.get('youtube_id')} by {worker_id}")
                return video
            return None

        except HTTPError as e:
            if e.code == 404:
                # RPC function not found, fall back to REST API
                logger.warning("claim_next_video RPC not found, using REST fallback")
                return self._claim_video_rest(worker_id, lease_duration_sec, language)
            raise

    def _claim_video_rest(
        self,
        worker_id: str,
        lease_duration_sec: int,
        language: str = None
    ) -> Optional[Dict[str, Any]]:
        """
        Fallback claim using REST API (less atomic but works without RPC).

        Note: This has a small race condition window between SELECT and UPDATE.
        For production, use the RPC function.
        """
        # Find oldest pending video
        params = {
            'status': f'eq.{STATUS_PENDING}',
            'order': 'created_at.asc',
            'limit': '1'
        }
        if language:
            params['language'] = f'eq.{language}'

        videos = self._request('GET', 'videos', params=params)

        if not videos:
            return None

        video = videos[0]
        video_id = video['youtube_id']

        # Attempt to claim (may race with other workers)
        now = datetime.now(timezone.utc).isoformat()
        lease_expires = datetime.fromtimestamp(
            time.time() + lease_duration_sec,
            tz=timezone.utc
        ).isoformat()

        update_data = {
            'status': STATUS_CLAIMED,
            'claimed_by': worker_id,
            'claimed_at': now,
            'lease_expires_at': lease_expires,
            'attempt_count': (video.get('attempt_count') or 0) + 1
        }

        # Only update if still PENDING (optimistic lock)
        params = {
            'youtube_id': f'eq.{video_id}',
            'status': f'eq.{STATUS_PENDING}'
        }

        result = self._request(
            'PATCH',
            'videos',
            data=update_data,
            params=params
        )

        if result and len(result) > 0:
            logger.info(f"Claimed video (REST): {video_id} by {worker_id}")
            return result[0]

        # Another worker got it first
        logger.debug(f"Lost race for video: {video_id}")
        return None

    def update_status(
        self,
        youtube_id: str,
        status: str,
        results: Dict[str, Any] = None
    ) -> bool:
        """
        Update video status and processing results.

        Args:
            youtube_id: YouTube video ID
            status: New status (COMPLETED, FAILED, SKIPPED)
            results: Processing results dict (num_speakers, usable_percentage, etc.)

        Returns:
            True if update succeeded
        """
        now = datetime.now(timezone.utc).isoformat()

        update_data = {
            'status': status,
            'updated_at': now,
        }

        if status == STATUS_COMPLETED:
            update_data['processing_completed_at'] = now

        if results:
            # Map results to column names
            field_mapping = {
                'num_speakers': 'num_speakers',
                'total_segments': 'total_segments',
                'usable_percentage': 'usable_percentage',
                'usable_segments': 'usable_segments',
                'usable_duration_sec': 'usable_duration_sec',
                'r2_tar_key': 'r2_tar_key',
                'r2_tar_size_bytes': 'r2_tar_size_bytes',
                'pipeline_version': 'pipeline_version',
                'processing_meta': 'processing_meta',
                'quality_stats': 'quality_stats',
                'segment_summary': 'segment_summary',
                'download_meta': 'download_meta',
                'last_error': 'last_error',
                'last_error_type': 'last_error_type',
                'audio_native_sample_rate': 'audio_native_sample_rate',
                'audio_channels': 'audio_channels',
                'audio_duration_sec': 'audio_duration_sec',
                'needs_demucs_count': 'needs_demucs_count',
                'heavy_music_count': 'heavy_music_count',
            }

            for src_key, dst_key in field_mapping.items():
                if src_key in results and results[src_key] is not None:
                    update_data[dst_key] = results[src_key]

        params = {'youtube_id': f'eq.{youtube_id}'}

        try:
            result = self._request('PATCH', 'videos', data=update_data, params=params)
            logger.info(f"Updated status: {youtube_id} -> {status}")
            return True
        except Exception as e:
            logger.error(f"Failed to update status for {youtube_id}: {e}")
            return False

    def release_claim(self, youtube_id: str) -> bool:
        """
        Release a claim without completing (e.g., worker shutdown).

        Resets video to PENDING so another worker can pick it up.
        """
        update_data = {
            'status': STATUS_PENDING,
            'claimed_by': None,
            'claimed_at': None,
            'lease_expires_at': None,
            'updated_at': datetime.now(timezone.utc).isoformat()
        }

        params = {'youtube_id': f'eq.{youtube_id}'}

        try:
            self._request('PATCH', 'videos', data=update_data, params=params)
            logger.info(f"Released claim: {youtube_id}")
            return True
        except Exception as e:
            logger.error(f"Failed to release claim for {youtube_id}: {e}")
            return False

    def bulk_upsert(
        self,
        videos: List[Dict[str, Any]],
        batch_size: int = 1000,
        on_conflict: str = 'youtube_id'
    ) -> int:
        """
        Batch upsert videos to database.

        Args:
            videos: List of video dicts
            batch_size: Number of rows per batch
            on_conflict: Column for conflict resolution

        Returns:
            Number of rows upserted
        """
        total = 0

        for i in range(0, len(videos), batch_size):
            batch = videos[i:i + batch_size]

            headers_override = {
                'Prefer': 'resolution=merge-duplicates,return=minimal'
            }

            # Add on_conflict to URL params for upsert
            params = {
                'on_conflict': on_conflict
            }

            try:
                self._request(
                    'POST',
                    'videos',
                    data=batch,
                    params=params,
                    headers_override=headers_override
                )
                total += len(batch)
                logger.info(f"Upserted batch {i//batch_size + 1}: {len(batch)} rows (total: {total})")
            except Exception as e:
                logger.error(f"Batch upsert failed at row {i}: {e}")
                raise

        return total

    def get_video(self, youtube_id: str) -> Optional[Dict[str, Any]]:
        """Get a single video by YouTube ID."""
        params = {
            'youtube_id': f'eq.{youtube_id}',
            'limit': '1'
        }

        result = self._request('GET', 'videos', params=params)
        return result[0] if result else None

    def get_stats(self) -> Dict[str, int]:
        """
        Get queue statistics.

        Returns:
            Dict with counts by status
        """
        # Use Supabase's count feature
        stats = {}

        for status in [STATUS_PENDING, STATUS_CLAIMED, STATUS_COMPLETED, STATUS_FAILED, STATUS_SKIPPED]:
            params = {
                'status': f'eq.{status}',
                'select': 'id'
            }
            headers_override = {'Prefer': 'count=exact'}

            try:
                # Make request and check Content-Range header
                url = f"{self.rest_url}/videos?{urlencode(params)}"
                req = Request(url, headers={**self.headers, **headers_override})

                with urlopen(req, timeout=30) as resp:
                    content_range = resp.headers.get('Content-Range', '0-0/0')
                    # Format: "0-9/100" where 100 is total count
                    total = int(content_range.split('/')[-1])
                    stats[status] = total
            except Exception as e:
                logger.warning(f"Failed to get count for {status}: {e}")
                stats[status] = -1

        return stats

    def get_pending_count(self) -> int:
        """Get count of pending videos."""
        stats = self.get_stats()
        return stats.get(STATUS_PENDING, 0)

    def reclaim_expired_leases(self) -> int:
        """
        Reset videos with expired leases back to PENDING.

        Useful for recovering from worker crashes.

        Returns:
            Number of videos reset
        """
        now = datetime.now(timezone.utc).isoformat()

        # Find claimed videos with expired leases
        params = {
            'status': f'eq.{STATUS_CLAIMED}',
            'lease_expires_at': f'lt.{now}'
        }

        update_data = {
            'status': STATUS_PENDING,
            'claimed_by': None,
            'lease_expires_at': None,
            'updated_at': now
        }

        try:
            result = self._request('PATCH', 'videos', data=update_data, params=params)
            count = len(result) if result else 0
            if count > 0:
                logger.info(f"Reclaimed {count} expired leases")
            return count
        except Exception as e:
            logger.error(f"Failed to reclaim expired leases: {e}")
            return 0

# Convenience function
def get_supabase_client() -> SupabaseClient:
    """Get singleton SupabaseClient instance."""


**Understanding videos table**

I see that the videos table has columns like youtube_id, status, and r2_tar_key, which is not the actual R2 URL but rather the key. The user is asking for the "R2 url," so I might be able to derive it from the r2_tar_key or potentially from the key and endpoint. I need to check the pipeline around line 1018 to see how outputs are located in R2 from Supabase without guessing prefixes.


Output:
Exit code: 0
Wall time: 0 seconds
Output:
    background_export = getattr(config, 'background_export', False)

    if export_enabled:
        log_stage(10, "Export", "START")

        upload_prefix = (getattr(config, 'r2_upload_prefix', '') or '').strip().strip('/')
        remote_key = f"{video_id}.tar" if not upload_prefix else f"{upload_prefix}/{video_id}.tar"
        if getattr(config, 'r2_upload_enabled', False):
            result['r2_upload_key'] = remote_key
        original_audio_path = Path(metadata.get('original_audio_path', ''))
        intro_offset = metadata.get('intro_skipped', 0.0)

        if background_export:
            # === BACKGROUND EXPORT MODE ===
            # Submit job to background manager, don't block GPU
            from src.export import ExportJob, get_export_manager
            from src.r2_client import R2Client

            export_manager = get_export_manager()
            if export_manager:
                job = ExportJob(
                    video_id=video_id,
                    output_dir=output_dir,
                    original_audio_path=original_audio_path,
                    segments=segments,
                    intro_offset=intro_offset,
                    r2_upload_enabled=getattr(config, 'r2_upload_enabled', False),
                    r2_upload_key=remote_key,
                    r2_bucket_type=getattr(config, 'r2_upload_bucket_type', 'production'),
                    include_original_in_tar=getattr(config, 'include_original_in_tar', False),
                    delete_output_dir_after_upload=getattr(config, 'r2_upload_delete_local_output_dir', False),
                )
                export_manager.submit(job)
                log_stage(10, "Export", "QUEUED", f"background job submitted")
                result['export_mode'] = 'background'
                result['r2_upload_key'] = remote_key
                # Record the exact destination (including R2_PREFIX) even though
                # the upload happens asynchronously. This makes it possible to
                # locate outputs in R2 from Supabase without guessing prefixes.
                if getattr(config, 'r2_upload_enabled', False):
                    r2 = R2Client(bucket_type=getattr(config, 'r2_upload_bucket_type', 'production'))
                    result.setdefault('export', {})
                    result['export'].update({
                        'r2_upload_bucket': r2.bucket,
                        'r2_upload_full_key': r2.full_key(remote_key),
                        'r2_upload_uri': r2.uri(remote_key),
                    })
            else:
                logger.warning("Background export manager not initialized, falling back to sync")
                background_export = False  # Fall through to sync mode

        if not background_export:
            # === SYNCHRONOUS EXPORT MODE ===
            from src.r2_client import R2Client
            from src.export import segment_audio_parallel

            with COMPUTE.monitor_stage("Export") as metrics:
                # Step 1: Segment original audio (parallel ffmpeg)
                segments_exported = 0
                if getattr(config, 'segment_audio', True) and original_audio_path.exists():
                    seg_start = time.time()
                    segments_exported = segment_audio_parallel(
                        audio_path=original_audio_path,
                        segments=segments,
                        output_dir=output_dir,
                        intro_offset=intro_offset,
                        max_workers=8,
                        output_format="flac"
                    )
                    seg_time = time.time() - seg_start
                    logger.info(f"📦 Segmented {segments_exported} clips in {seg_time:.1f}s")

                # Step 1.5: Remove original audio from output (source is preserved in R2)
                if not getattr(config, 'include_original_in_tar', False):
                    original_in_output = output_dir / f"{video_id}_original.flac"
                    if original_in_output.exists():
                        original_in_output.unlink()
                        logger.debug(f"Removed _original.flac from output (source in R2)")

                # Step 2: Create tar archive
                tar_path = output_dir.parent / f"{video_id}.tar"
                with tarfile.open(tar_path, "w") as tar:
                    tar.add(output_dir, arcname=video_id)
                tar_size_bytes = tar_path.stat().st_size if tar_path.exists() else 0

                # Step 3: Upload to R2 (if enabled)
                upload_ok = True
                if getattr(config, 'r2_upload_enabled', False):
                    r2 = R2Client(bucket_type=getattr(config, 'r2_upload_bucket_type', 'production'))
                    if getattr(config, 'r2_upload_skip_if_exists', False) and r2.exists(remote_key):
                        logger.info(f"R2 upload skipped (exists): {r2.uri(remote_key)}")
                    else:
                        upload_ok = r2.upload_file(str(tar_path), remote_key)
                        if not upload_ok:
                            raise RuntimeError(f"R2 upload failed for {r2.uri(remote_key)}")

                    # Delete local tar after upload
                    if getattr(config, 'r2_upload_delete_local_tar', True):
                        try:
                            tar_path.unlink()
                        except Exception:
                            pass

                    # Delete per-video output dir after successful upload (prevents disk fill).
                    if getattr(config, 'r2_upload_enabled', False) and getattr(config, 'r2_upload_delete_local_output_dir', False):
                        try:
                            import shutil
                            shutil.rmtree(output_dir, ignore_errors=True)
                        except Exception:
                            pass

            timings['export'] = metrics.duration
            compute_stats['export'] = {'cpu': metrics.cpu_percent_avg, 'gpu': metrics.gpu_percent_avg}
            result['export'] = {
                'segments_exported': segments_exported,
                'tar_size_bytes': int(tar_size_bytes),
                'r2_upload_key': remote_key if getattr(config, 'r2_upload_enabled', False) else None,
                'r2_upload_bucket': r2.bucket if getattr(config, 'r2_upload_enabled', False) else None,
                'r2_upload_full_key': r2.full_key(remote_key) if getattr(config, 'r2_upload_enabled', False) else None,
                'r2_upload_uri': r2.uri(remote_key) if getattr(config, 'r2_upload_enabled', False) else None,
            }


**Investigating Supabase Updates**

I see the result includes `r2_upload_uri`, but the Supabase status update has `r2_tar_key` and size bytes instead. It makes me wonder if `r2_tar_key` is actually storing the `r2_upload_key`. I should locate where those results are passed to the Supabase `update_status` function. So, let’s search for `r2_tar_key` to clarify how everything connects!


rg -n "r2_tar_key|r2_upload_uri|update_status\(" -S pipeline.py src | head -n 80


Output:
Exit code: 0
Wall time: 0 seconds
Output:
pipeline.py:1025:                        'r2_upload_uri': r2.uri(remote_key),
pipeline.py:1099:                'r2_upload_uri': r2.uri(remote_key) if getattr(config, 'r2_upload_enabled', False) else None,
src/supabase_client.py:18:        client.update_status(video['youtube_id'], 'COMPLETED', results)
src/supabase_client.py:299:    def update_status(
src/supabase_client.py:334:                'r2_tar_key': 'r2_tar_key',


I’m thinking about how the pipeline could return `result['export']['r2_upload_key']`, which might then be used to update Supabase. I should also consider whether I need to search within `massive_process` or an `orchestrator` to find the right details. It's a bit of a puzzle — I want to make sure I’m on the right track and covering all the bases! Let's explore this further to get it right.


Output:
Exit code: 0
Wall time: 0 seconds
Output:
./massive_process.py:642:                supabase.update_status(video_id, STATUS_COMPLETED, update_data)
./massive_process.py:696:                supabase.update_status(video_id, STATUS_FAILED, {
./src/supabase_client.py:18:        client.update_status(video['youtube_id'], 'COMPLETED', results)
./src/supabase_client.py:299:    def update_status(


Summary: auto


Output:
Exit code: 0
Wall time: 0 seconds
Output:
                    lease_duration_sec=lease_duration_sec
                )
            except Exception as e:
                worker_logger.warning(f"Supabase claim_next_video failed: {e}")
                time.sleep(poll_interval_sec)
                continue

            if not video:
                consecutive_empty += 1
                if consecutive_empty >= max_consecutive_empty:
                    worker_logger.info("No more pending videos, stopping worker")
                    break
                worker_logger.debug(f"No pending videos, sleeping {poll_interval_sec}s...")
                time.sleep(poll_interval_sec)
                continue

            consecutive_empty = 0
            video_id = video['youtube_id']
            video_url = video['youtube_url']

            # Report video pick to analytics (non-blocking)
            analytics.pick(video_id)

            # Fetch full video record to get chapters
            try:
                full_video = supabase.get_video(video_id)
            except Exception as e:
                worker_logger.warning(f"Supabase get_video failed for {video_id}: {e}")
                full_video = None
            if not full_video:
                full_video = video  # Fallback to claim result

            worker_logger.info(f"Processing: {video_id} - {full_video.get('title', '')[:50]}")
            has_chapters = full_video.get('has_chapters', False)
            if has_chapters:
                worker_logger.info(f"   Chapters: {full_video.get('chapter_count', 0)} from Supabase")
            start_time = time.time()

            try:
                # Process video with Supabase metadata (chapters, title, etc.)
                result = process_single_video(video_url, config, supabase_metadata=full_video)
                process_time = time.time() - start_time

                # Extract results for DB update
                quality_stats = result.get('quality_stats', {}) or {}
                segment_summary = result.get('segment_summary', {}) or {}
                download_meta = result.get('download_meta', {}) or {}

                # Update Supabase with success
                update_data = {
                    'num_speakers': result.get('num_speakers', 0),
                    'total_segments': result.get('total_segments', 0),
                    'usable_percentage': quality_stats.get('usable_percentage', 0),
                    'usable_segments': quality_stats.get('usable_segments', 0),
                    'usable_duration_sec': quality_stats.get('usable_duration', 0),
                    # Store the fully-qualified key (includes R2_PREFIX) so it
                    # can be located in R2 without guessing prefixes.
                    'r2_tar_key': ((result.get('export', {}) or {}).get('r2_upload_full_key')
                                   or result.get('r2_upload_key', '')),
                    'r2_tar_size_bytes': (result.get('export', {}) or {}).get('tar_size_bytes'),
                    'pipeline_version': result.get('pipeline_version', ''),
                    'audio_native_sample_rate': download_meta.get('native_sample_rate'),
                    'audio_channels': download_meta.get('channels'),
                    'audio_duration_sec': result.get('processed_duration', 0),
                    'needs_demucs_count': quality_stats.get('music_detection', {}).get('segments_needs_demucs', 0),
                    'heavy_music_count': quality_stats.get('music_detection', {}).get('segments_heavy_contamination', 0),
                    'processing_meta': {
                        'worker_id': supabase_worker_id,
                        'machine_id': machine_id,
                        'gpu_id': gpu_id,
                        'provider': os.environ.get('WORKER_PROVIDER') or ('vast' if os.environ.get('CONTAINER_ID') else None),
                        'provider_instance_id': os.environ.get('CONTAINER_ID') or os.environ.get('RUNPOD_POD_ID'),
                        'public_ip': os.environ.get('PUBLIC_IPADDR'),
                        'timing_total': result.get('timing_total', 0),
                        'completed_at': datetime.now().isoformat(),
                        'pipeline_version': result.get('pipeline_version', ''),
                    },
                    'quality_stats': quality_stats,
                    'segment_summary': segment_summary,
                    'download_meta': download_meta,
                }

                supabase.update_status(video_id, STATUS_COMPLETED, update_data)

                worker_logger.info(
                    f"Completed: {video_id} | "
                    f"{process_time:.1f}s | "
                    f"{result.get('num_speakers', 0)} speakers | "
                    f"{quality_stats.get('usable_percentage', 0):.1f}% usable"
                )

                # Report success to analytics (non-blocking)
                analytics.done(
                    video_id=video_id,
                    total_time=result.get('timing_total', process_time),
                    audio_min=result.get('processed_duration', 0) / 60.0,
                    speakers=result.get('num_speakers', 0),
                    usable_pct=quality_stats.get('usable_percentage', 0)
                )

                # Put result in queue for stats collection
                video_result = VideoResult(
                    video_url=video_url,
                    video_id=video_id,
                    success=True,
                    duration_sec=result.get('processed_duration', 0),
                    process_time_sec=process_time,
                    pipeline_time_sec=result.get('timing_total', 0),
                    rtf=(result.get('processed_duration', 0) / result.get('timing_total', 1)) if result.get('timing_total') else 0,
                    num_speakers=result.get('num_speakers', 0),
                    usable_percentage=quality_stats.get('usable_percentage', 0),
                    output_path=str(Path(output_dir) / video_id),
                    stage_timings={k: float(v) for k, v in (result.get('timing', {}) or {}).items()},
                    source_type=result.get('source_type', ''),
                    r2_upload_key=result.get('r2_upload_key', ''),
                    gpu_id=gpu_id,
                    worker_id=worker_id
                )

            except Exception as e:
                process_time = time.time() - start_time
                error_msg = str(e)
                error_type = type(e).__name__
                worker_logger.error(f"Failed: {video_id} - {error_msg}")
                traceback.print_exc()

                # Report failure to analytics (non-blocking)
                analytics.fail(
                    video_id=video_id,
                    stage="processing",
                    error_type=error_type,
                    message=error_msg,
                    stack_trace=traceback.format_exc()
                )

                # Update Supabase with failure
                supabase.update_status(video_id, STATUS_FAILED, {
                    'last_error': error_msg[:1000],  # Truncate long errors
                    'last_error_type': type(e).__name__,
                    'processing_meta': {
                        'worker_id': supabase_worker_id,
                        'gpu_id': gpu_id,
                        'failed_at': datetime.now().isoformat(),
                    },
                })

                video_result = VideoResult(
                    video_url=video_url,
                    video_id=video_id,
                    success=False,
                    error=error_msg,
                    process_time_sec=process_time,
                    gpu_id=gpu_id,
                    worker_id=worker_id
                )

            result_queue.put(video_result)
            videos_processed += 1

            # Clear GPU cache between videos
            MODELS.clear_cache(aggressive=True)

        # Drain background exports (if enabled in this worker)
        if getattr(config, "background_export", False):
            try:
                from src.export import shutdown_export_manager
                worker_logger.info("Waiting for background exports to complete...")
                export_results = shutdown_export_manager(wait=True, timeout=600)
                failed = [r for r in export_results.values() if not getattr(r, "success", False)]
                if failed:
                    worker_logger.warning(f"Background exports failed: {len(failed)}/{len(export_results)}")
                    for r in failed[:5]:
                        worker_logger.warning(f"  {r.video_id}: {r.error}")
            except Exception:
                pass

        # Graceful shutdown - flush remaining analytics events
        analytics.shutdown()
        worker_logger.info(f"Shutting down. Processed {videos_processed} videos.")

    except Exception as e:
        worker_logger.error(f"Worker failed: {e}")
        traceback.print_exc()
        # Try to shutdown analytics even on error (may not be initialized)
        try:
            if analytics is not None:
                analytics.shutdown()
        except Exception:
            pass


**Inspecting R2 URL mapping**

I noted that the completed video has an `r2_tar_key` saved as a full key, prefix included, rather than a URL. The user wants the R2 URL, and maybe they see `r2_tar_key` or a column named `r2_tar_url` in the database. I realize there might not be a direct mapping, so I’ll check if there's a view in the dashboard that computes the URL from the key. Time to search through the `r2_tar_key` usage!


rg -n "r2_tar_key|r2_tar" -S dashboard-ui src scripts | head -n 100


Output:
Exit code: 0
Wall time: 0 seconds
Output:
src/supabase_client.py:334:                'r2_tar_key': 'r2_tar_key',
src/supabase_client.py:335:                'r2_tar_size_bytes': 'r2_tar_size_bytes',
scripts/check_videos.py:43:        print(f'  r2_tar_key: {v.get("r2_tar_key", "N/A")}')


Output:
Exit code: 0
Wall time: 0 seconds
Output:
#!/usr/bin/env python3
"""Check Supabase video columns and specific videos."""

import os
import sys
import json

sys.path.insert(0, os.path.dirname(os.path.dirname(os.path.abspath(__file__))))

from dotenv import load_dotenv
load_dotenv()

from supabase import create_client

sb = create_client(os.environ['URL'], os.environ['SUPABASE_ADMIN'])

# Check a sample COMPLETED video
print('=' * 70)
print('SAMPLE COMPLETED VIDEO - ALL COLUMNS')
print('=' * 70)
result = sb.table('videos').select('*').eq('status', 'COMPLETED').limit(1).execute()
if result.data:
    v = result.data[0]
    for key, val in sorted(v.items()):
        if val is not None and val != '' and val != {} and val != []:
            val_str = str(val)[:100] if len(str(val)) > 100 else str(val)
            print(f'  {key:30}: {val_str}')
else:
    print('No COMPLETED videos found')

# Check specific videos requested by user
print()
print('=' * 70)
print('REQUESTED VIDEOS STATUS')
print('=' * 70)
requested = ['zfnG34iSpbU', 'IDzfs62WnD8', 'fHBR1j1kJ1I']
for vid in requested:
    result = sb.table('videos').select('*').eq('youtube_id', vid).execute()
    if result.data:
        v = result.data[0]
        print(f'\n{vid}:')
        print(f'  status: {v.get("status")}')
        print(f'  r2_tar_key: {v.get("r2_tar_key", "N/A")}')
        print(f'  usable_percentage: {v.get("usable_percentage", "N/A")}')
        print(f'  num_speakers: {v.get("num_speakers", "N/A")}')
        print(f'  total_segments: {v.get("total_segments", "N/A")}')
        print(f'  audio_duration_sec: {v.get("audio_duration_sec", "N/A")}')
    else:
        print(f'\n{vid}: NOT FOUND in Supabase')

# Check local files for these videos
print()
print('=' * 70)
print('LOCAL FILES FOR REQUESTED VIDEOS')
print('=' * 70)
import os
for vid in requested:
    tar_path = f'./output/{vid}.tar'
    dir_path = f'./output/{vid}'
    if os.path.exists(tar_path):
        size_mb = os.path.getsize(tar_path) / (1024*1024)
        print(f'{vid}: TAR exists ({size_mb:.1f}MB)')
    elif os.path.exists(dir_path):
        print(f'{vid}: Directory exists (no TAR)')
    else:
        print(f'{vid}: NOT FOUND locally')


**Inspecting code functions**

I’m looking into the usage of supabase-py, so that feels like a solid choice. There’s also the src/r2_client.py file that I can check for existence. I wonder if that’ll help us further. I should definitely inspect both, as they might reveal something important about the functionality or the errors I’m encountering. I'll dig in and see what I find!


Output:
Exit code: 0
Wall time: 0 seconds
Output:
#!/usr/bin/env python3
"""
R2 Client Utilities for High-Throughput Pipeline Migration

Manages Cloudflare R2 buckets for:
- Production outputs (1-cleaned-data)
- Test outputs during migration (1-cleaned-data-test)
- Baseline snapshots for comparison (1-cleaned-data-baseline)

Usage:
    from src.r2_client import R2Client

    client = R2Client()
    client.upload_json("path/to/file.json", "video_id/metadata.json")
    client.download_json("video_id/metadata.json", "local/path.json")
"""

import os
import json
import logging
from pathlib import Path
from typing import Dict, Any, Optional, List
from dataclasses import dataclass

import boto3
from botocore.config import Config as BotoConfig

logger = logging.getLogger("R2Client")

@dataclass
class R2Config:
    """R2 bucket configuration."""
    endpoint_url: str
    access_key_id: str
    secret_access_key: str
    bucket: str
    prefix: str = ""

# Bucket configurations
BUCKETS = {
    'production': '1-cleaned-data',
    'test': '1-cleaned-data-test',
    'baseline': '1-cleaned-data-baseline',
    # Source/original videos (DO NOT DELETE). This bucket is expected to contain
    # the original YouTube files re-uploaded to R2 to avoid rate limits.
    'source': 'test',
}

def get_r2_config_from_env() -> R2Config:
    """Load R2 configuration from environment variables."""
    return R2Config(
        # Support a few common aliases used in various deploy templates.
        endpoint_url=os.environ.get('R2_ENDPOINT_URL') or os.environ.get('S3_API') or '',
        access_key_id=os.environ.get('R2_ACCESS_KEY_ID') or os.environ.get('AWS_ACCESS_KEY_ID') or '',
        secret_access_key=os.environ.get('R2_SECRET_ACCESS_KEY') or os.environ.get('AWS_SECRET_ACCESS_KEY') or '',
        bucket=os.environ.get('R2_BUCKET', 'test'),
        prefix=os.environ.get('R2_PREFIX', ''),
    )

class R2Client:
    """
    Cloudflare R2 client for pipeline data management.

    Supports multiple bucket targets for A/B testing during migration.
    """

    def __init__(
        self,
        config: Optional[R2Config] = None,
        bucket_type: str = 'test'
    ):
        """
        Initialize R2 client.

        Args:
            config: R2 configuration (loads from env if None)
            bucket_type: One of 'production', 'test', 'baseline'
        """
        self.config = config or get_r2_config_from_env()

        # Override bucket based on type
        if bucket_type in BUCKETS:
            self.bucket = BUCKETS[bucket_type]
        else:
            self.bucket = self.config.bucket

        # IMPORTANT: The output prefix (R2_PREFIX) should not accidentally apply
        # to the *source* bucket. Vast/RunPod templates often set R2_PREFIX for
        # uploads; for source reads we want R2_SOURCE_PREFIX (or empty).
        if bucket_type == 'source' and config is None:
            self.prefix = os.environ.get('R2_SOURCE_PREFIX', '') or ''
        else:
            self.prefix = self.config.prefix

        # Initialize boto3 client
        self._client = None

    @property
    def client(self):
        """Lazy-initialize boto3 client."""
        if self._client is None:
            if not self.config.endpoint_url:
                raise RuntimeError("R2 not configured: missing R2_ENDPOINT_URL (or S3_API)")
            if not self.config.access_key_id:
                raise RuntimeError("R2 not configured: missing R2_ACCESS_KEY_ID (or AWS_ACCESS_KEY_ID)")
            if not self.config.secret_access_key:
                raise RuntimeError("R2 not configured: missing R2_SECRET_ACCESS_KEY (or AWS_SECRET_ACCESS_KEY)")
            self._client = boto3.client(
                's3',
                endpoint_url=self.config.endpoint_url,
                aws_access_key_id=self.config.access_key_id,
                aws_secret_access_key=self.config.secret_access_key,
                config=BotoConfig(
                    signature_version='s3v4',
                    retries={'max_attempts': 3, 'mode': 'adaptive'},
                    # Prevent long hangs on HEAD/LIST during intermittent network stalls.
                    connect_timeout=int(os.environ.get("R2_CONNECT_TIMEOUT_SEC", "10") or 10),
                    read_timeout=int(os.environ.get("R2_READ_TIMEOUT_SEC", "60") or 60),
                    max_pool_connections=int(os.environ.get("R2_MAX_POOL_CONNECTIONS", "64") or 64),
                )
            )
        return self._client

    def full_key(self, key: str) -> str:
        """Public helper: return fully-qualified key (including configured prefix)."""
        return self._full_key(key)

    def uri(self, key: str) -> str:
        """Return an s3:// URI for a key (including configured prefix)."""
        return f"s3://{self.bucket}/{self._full_key(key)}"

    def _full_key(self, key: str) -> str:
        """Get full S3 key with prefix."""
        if self.prefix:
            return f"{self.prefix}/{key}"
        return key

    def upload_file(self, local_path: str, remote_key: str) -> bool:
        """
        Upload a file to R2.

        Args:
            local_path: Path to local file
            remote_key: Remote key (path in bucket)

        Returns:
            True if successful
        """
        try:
            full_key = self._full_key(remote_key)
            self.client.upload_file(local_path, self.bucket, full_key)
            logger.info(f"Uploaded {local_path} -> s3://{self.bucket}/{full_key}")
            return True
        except Exception as e:
            logger.error(f"Upload failed: {e}")
            return False

    def download_file(self, remote_key: str, local_path: str) -> bool:
        """
        Download a file from R2.

        Args:
            remote_key: Remote key (path in bucket)
            local_path: Path to save locally

        Returns:
            True if successful
        """
        try:
            full_key = self._full_key(remote_key)
            Path(local_path).parent.mkdir(parents=True, exist_ok=True)
            self.client.download_file(self.bucket, full_key, local_path)
            logger.info(f"Downloaded s3://{self.bucket}/{full_key} -> {local_path}")
            return True
        except Exception as e:
            logger.error(f"Download failed: {e}")
            return False

    def upload_json(self, data: Dict[str, Any], remote_key: str) -> bool:
        """Upload JSON data directly to R2."""
        try:
            full_key = self._full_key(remote_key)
            body = json.dumps(data, indent=2).encode('utf-8')
            self.client.put_object(
                Bucket=self.bucket,
                Key=full_key,
                Body=body,
                ContentType='application/json'
            )
            logger.info(f"Uploaded JSON -> s3://{self.bucket}/{full_key}")
            return True
        except Exception as e:
            logger.error(f"JSON upload failed: {e}")
            return False

    def download_json(self, remote_key: str) -> Optional[Dict[str, Any]]:
        """Download JSON data from R2."""
        try:
            full_key = self._full_key(remote_key)
            response = self.client.get_object(Bucket=self.bucket, Key=full_key)
            data = json.loads(response['Body'].read().decode('utf-8'))
            logger.info(f"Downloaded JSON <- s3://{self.bucket}/{full_key}")
            return data
        except Exception as e:
            logger.error(f"JSON download failed: {e}")
            return None

    def head_object(self, remote_key: str) -> Optional[Dict[str, Any]]:
        """Return S3 head_object response for a key, or None if missing/unreadable."""
        try:
            full_key = self._full_key(remote_key)
            return self.client.head_object(Bucket=self.bucket, Key=full_key)
        except Exception:
            return None

    def generate_presigned_get_url(self, remote_key: str, expires_in_sec: int = 3600) -> str:
        """
        Generate a presigned GET URL for an object.

        Note: This is a Class B request pattern (no bucket listing).
        """
        full_key = self._full_key(remote_key)
        return self.client.generate_presigned_url(
            'get_object',
            Params={'Bucket': self.bucket, 'Key': full_key},
            ExpiresIn=expires_in_sec,
        )

    def list_keys(self, prefix: str = "", limit: int = 1000) -> List[str]:
        """
        List keys in bucket with optional prefix.

        Args:
            prefix: Additional prefix to filter by
            limit: Maximum keys to return

        Returns:
            List of keys
        """
        try:
            full_prefix = self._full_key(prefix) if prefix else self.prefix
            response = self.client.list_objects_v2(
                Bucket=self.bucket,
                Prefix=full_prefix,
                MaxKeys=limit
            )

            keys = []
            for obj in response.get('Contents', []):
                key = obj['Key']
                # Remove prefix for cleaner output
                if self.prefix and key.startswith(self.prefix):
                    key = key[len(self.prefix):].lstrip('/')
                keys.append(key)

            return keys


**Planning pagination for R2Client**

I see that R2Client lists keys but doesn't paginate, capping at 1000 keys per call. To check 40,000 completed videos, I plan to query Supabase for rows where status is 'COMPLETED'. I'll only fetch necessary columns like youtube_id and r2_tar_key. Supabase's Python library should help, as it handles pagination with `.range()` and `.limit()`.

For each record, I need to check if the r2_tar_key contains the prefix, while being aware of how R2Client applies that prefix again. This could prevent duplicates.


**Configuring S3 client with boto3**

I'm thinking that if the stored key is a full key, we should directly use boto3's `head_object` with just the bucket and key, avoiding any prefix. I'll implement an S3 client with R2_ENDPOINT_URL, bypassing R2Client.

For the bucket, do completed outputs default to production? It seems r2_upload_bucket_type may default to 'production', but r2_tar_key only includes the prefix.

I note that `processing_meta` might not include r2_upload_bucket but we should consider that the pipeline typically uses production. There's a chance the environment variable R2_BUCKET could be 'test', but the system defaults to production for uploads.


**Verifying bucket existence**

I need to confirm the bucket since, without it, I might end up checking objects in multiple buckets like production, test, or baseline. Since you've asked about the R2 URL and its existence, I should prioritize the production bucket. I wonder if the r2_tar_key path includes the bucket information; it might not.

I'll also check if Supabase has a new column for r2_tar_bucket. Using the sample script `scripts/check_videos.py`, I’ll run it to see the columns. The output might be verbose, so I'll limit the print to avoid any unnecessary information.


python3 scripts/check_videos.py | head -n 80


Output:
Exit code: 0
Wall time: 1.5 seconds
Output:
======================================================================
SAMPLE COMPLETED VIDEO - ALL COLUMNS
======================================================================
  attempt_count                 : 1
  audio_channels                : 1
  audio_duration_sec            : 141.02
  audio_native_sample_rate      : 44100
  channel                       : Aadhan Tamil
  chapter_count                 : 0
  claimed_at                    : 2026-01-08T12:49:07.826929+00:00
  claimed_by                    : vast-29761466_gpu6
  classification                : podcast
  created_at                    : 2026-01-06T13:18:23.347988+00:00
  download_meta                 : {'abr': None, 'acodec': 'unknown', 'format': None, 'channels': 1, 'duration': 321.015873015873, 'nat
  error_count                   : 0
  has_chapters                  : False
  heavy_music_count             : 3
  id                            : b4a076f0-8b2c-47e5-a687-984dddc6fa29
  language                      : tamil
  lease_expires_at              : 2026-01-08T13:04:07.826929+00:00
  max_attempts                  : 3
  needs_demucs_count            : 1
  num_speakers                  : 3
  pipeline_version              : v7.9-vad-boundary-refinement
  processing_completed_at       : 2026-01-08T12:49:18.652758+00:00
  processing_meta               : {'gpu_id': 6, 'provider': 'vast', 'public_ip': '31.13.223.140', 'worker_id': 'vast-29761466_gpu6', '
  quality_stats                 : {'split_segments': 0, 'music_detection': {'pct_clean': 69.2, 'duration_clean': 85.9375, 'segments_cl
  r2_tar_key                    : 4w5aC91TxSc.tar
  r2_tar_size_bytes             : 3563520
  source_duration_min           : 5.3
  status                        : COMPLETED
  title                         : ரஜினி தூத்துக்குடி போக தாடிபாலாஜி காரணமா ? | Reason Behind Rajini's Thoothukudi Visit |  EXCLUSIVE |
  total_segments                : 31
  updated_at                    : 2026-01-08T12:49:18.834371+00:00
  usable_duration_sec           : 81.22
  usable_percentage             : 57.6
  usable_segments               : 13
  youtube_id                    : 4w5aC91TxSc
  youtube_url                   : https://www.youtube.com/watch?v=4w5aC91TxSc

======================================================================
REQUESTED VIDEOS STATUS
======================================================================

zfnG34iSpbU:
  status: PENDING
  r2_tar_key: None
  usable_percentage: None
  num_speakers: None
  total_segments: None
  audio_duration_sec: None

IDzfs62WnD8:
  status: COMPLETED
  r2_tar_key: IDzfs62WnD8.tar
  usable_percentage: 67
  num_speakers: 6
  total_segments: 1975
  audio_duration_sec: 6953.96

fHBR1j1kJ1I:
  status: PENDING
  r2_tar_key: 1-cleaned-data/fHBR1j1kJ1I.tar
  usable_percentage: 88.9
  num_speakers: 6
  total_segments: 948
  audio_duration_sec: 6009.37

======================================================================
LOCAL FILES FOR REQUESTED VIDEOS
======================================================================
zfnG34iSpbU: NOT FOUND locally
IDzfs62WnD8: NOT FOUND locally
fHBR1j1kJ1I: NOT FOUND locally


**Optimizing bucket listing**

I'm thinking about how to efficiently compute the expected keys for the completed videos. The simplest approach is to query the completed videos, build the expected key names, and compare them to the output list. While listing the bucket could take around 40 requests, each handling up to 1,000 keys, this is far more efficient than making 40,000 HEAD requests! I can also confirm the actual object existence while ensuring consistency in values and handling multiple buckets. I'll implement pagination as well to manage the limits on returned objects.


**Evaluating listing options**

I’m considering how to handle keys that might just be id.tar at the root, which leaves the prefix empty. It seems that listing with an empty prefix could return the entire bucket, even if it’s huge, potentially containing millions of keys. The distribution shows many keys ending with `.tar`, yet there could be subfolders too. Listing the entire bucket might be pricey, especially with huge keys. I wonder if the best approach would be to directly check each key with head requests, as 40k heads might still be manageable with good concurrency.


**Planning request handling**

I'm working with R2Client configuration that includes timeouts. Since it's Boto3, I can set `max_pool_connections` using `botocore.config.Config`. I’ll use `concurrent.futures.ThreadPoolExecutor` to perform head_object requests. If I estimate about 40,676 requests, and each takes around 50ms, I can theoretically handle about 1,280 requests per second, hitting the total in roughly 30 seconds. If latency increases to 200 or 500ms, it will take longer, but still manageable. I’ll also implement safeguards like backoff for rate limits and handle potential ClientErrors. Plus, I need to fetch those rows from Supabase in batches of 1,000.


**Setting up Supabase and R2 integration**

The Supabase Python library uses PostgREST, and I’ll use the `.range(from, to)` method to set the `Range` header. I need to be mindful of memory because storing a list of 40k items should be manageable. I plan to implement streaming, where I fetch a batch of videos, check their keys in parallel, and gather stats for an optional CSV report. I should verify if I have the necessary Python dependencies installed, specifically for Supabase and Boto3. Great! The Supabase library is confirmed installed. Now, I need to ensure I have the R2 credentials and validate that the R2_ENDPOINT_URL is set up properly in my environment. I’ll quickly check this with a script that prints a boolean result.


python3 - <<'PY'
import os
from dotenv import load_dotenv
load_dotenv()
req=['URL','SUPABASE_ADMIN','R2_ENDPOINT_URL','R2_ACCESS_KEY_ID','R2_SECRET_ACCESS_KEY']
print({k:bool(os.environ.get(k)) for k in req})
print('R2_BUCKET', os.environ.get('R2_BUCKET'))
print('R2_PREFIX', os.environ.get('R2_PREFIX'))
PY


Output:
Exit code: 1
Wall time: 0.1 seconds
Output:
Traceback (most recent call last):
  File "<stdin>", line 3, in <module>
  File "/home/ubuntu/.local/lib/python3.10/site-packages/dotenv/main.py", line 346, in load_dotenv
    dotenv_path = find_dotenv()
  File "/home/ubuntu/.local/lib/python3.10/site-packages/dotenv/main.py", line 305, in find_dotenv
    assert frame.f_back is not None
AssertionError


python3 - <<'PY'
import os
from dotenv import load_dotenv
load_dotenv(dotenv_path='.env', override=False)
req=['URL','SUPABASE_ADMIN','R2_ENDPOINT_URL','R2_ACCESS_KEY_ID','R2_SECRET_ACCESS_KEY']
print({k:bool(os.environ.get(k)) for k in req})
print('R2_BUCKET_set', bool(os.environ.get('R2_BUCKET')))
print('R2_PREFIX_set', bool(os.environ.get('R2_PREFIX')))
PY


Output:
Exit code: 0
Wall time: 0.1 seconds
Output:
{'URL': True, 'SUPABASE_ADMIN': True, 'R2_ENDPOINT_URL': True, 'R2_ACCESS_KEY_ID': True, 'R2_SECRET_ACCESS_KEY': True}
R2_BUCKET_set True
R2_PREFIX_set True


**Mapping video statuses**

I need to confirm the status mapping in the Supabase client. The user mentions that 40,676 videos are done, and I should check that count in Supabase using a script called `scripts/audit_completed_r2.py`. The script will load environment variables, create a Supabase client, and query the count of completed videos. For each completed row, I'll analyze the `r2_tar_key`—checking for missing keys or invalid formats, and determining candidate buckets accordingly. I'll ensure efficiency and clarity in the process!


**Evaluating bucket mapping**

In the `r2_client`, I'm working with bucket mappings for production and a default that might be 'test'. It looks like I'll derive `production_bucket` as '1-cleaned-data', but I need to check the environment variable `R2_BUCKET` to confirm. If it's 'test', that could lead me to the wrong outputs. To avoid excessive requests, I'll prioritize using the most likely bucket based on the key format. I’ll also support optional CLI flags for testing multiple buckets if necessary and confirm results as requested.


**Implementing bucket detection**

I’m considering how to check the bucket counts. It seems I might need to look at records in Supabase, particularly involving the `processing_meta`, even though it doesn't map ‘export.’ So, I’ll implement bucket detection: If the `r2_tar_key` starts with a bucket name like '1-cleaned-data/', I’ll parse it. If it includes a prefix from the environment, I can keep that too. Otherwise, I’ll default to using `BUCKETS['production']` and allow for an override with `--bucket`. The user wants to confirm existence in R2, likely expecting to check production.


**Finalizing implementation details**

I’m outlining the implementation plan: first, I’ll build the Boto3 client once and use `head_object` to check each object, counting as I go. Concurrency with threads will be applied, while also checking if there's a corresponding R2 URL by verifying the presence of `r2_tar_key`. I’ll generate S3 URIs and create a report file named `reports/r2_audit_completed_<timestamp>.csv` or `.jsonl`. The report will include essential fields and summary stats. Since there are about 40,000 entries, I’ll display a progress bar without printing too much information. I'll ensure no sensitive data is exposed and run the script soon!


**Creating the audit plan**

I’m getting ready to run the audit. I'll check Supabase to confirm that each completed video really has a corresponding R2 URL that exists. Since this is an audit, I can do everything in one session and provide numbers and a path to the report. I might also consider updating Supabase to mark missing entries, but I’ll stick to just reporting for now. I’ll write a reusable script rather than an ad-hoc snippet, ensuring no secrets or credentials are exposed in outputs. My plan involves inspecting the schema, implementing the audit script, running it, and summarizing the findings.


Explanation: Need to query COMPLETED videos in Supabase, verify each has an R2 key/URL, and confirm the referenced object exists in Cloudflare R2.


Output: Plan updated


Summary: auto


**Implementing script updates**

I've already completed step one of the update plan, so it's time to move forward. Now, I'm implementing the script and need to follow the AGENTS instructions. It's important to check if the repository has an AGENTS file since the user provided root AGENTS instructions. However, I'll make sure there's nothing else to consider. I guess I should do a quick search using `find .. -name AGENTS.md` to locate it.


Output:
Exit code: 0
Wall time: 1 seconds
Output:


Output: Plan updated


**Implementing loops with feedback**

I want to work on implementing loops, focusing on the total completed count in a Supabase response. The plan is to use `tqdm` for progress tracking and fetch the count with a specific query. For now, I need to check the `result.count` property to see if it returns the expected value. I’ll run a quick test snippet to verify this. It all sounds pretty straightforward!


python3 - <<'PY'
import os
from supabase import create_client
from dotenv import load_dotenv
load_dotenv(dotenv_path='.env')
sb=create_client(os.environ['URL'], os.environ['SUPABASE_ADMIN'])
r = sb.table('videos').select('youtube_id', count='exact').eq('status','COMPLETED').limit(1).execute()
print('has_count_attr', hasattr(r,'count'))
print('count', getattr(r,'count', None))
print('rows', len(r.data or []))
PY


Output:
Exit code: 0
Wall time: 1.2 seconds
Output:
has_count_attr True
count 41193
rows 1


**Checking pagination and count**

The count is currently at 41,193, which is higher than the user's number of 40,676. This could indicate new data or additional information being included. I'll go ahead and use the computed number for my calculations. Now, regarding pagination, it looks like I should utilize `.range(offset, offset + batch - 1)` without setting an explicit limit. I'll run a quick test with a smaller batch size to see how it works.


python3 - <<'PY'
import os
from supabase import create_client
from dotenv import load_dotenv
load_dotenv(dotenv_path='.env')
sb=create_client(os.environ['URL'], os.environ['SUPABASE_ADMIN'])
r = sb.table('videos').select('youtube_id,r2_tar_key').eq('status','COMPLETED').order('youtube_id').range(0,4).execute()
print(len(r.data), r.data[0].keys())
print([d['youtube_id'] for d in r.data])
PY


Output:
Exit code: 0
Wall time: 1 seconds
Output:
5 dict_keys(['youtube_id', 'r2_tar_key'])
['__3rJtHpoWQ', '__BbOScjXIY', '__DQR3-EMA4', '__GUWuun39A', '__ICWZWDQlM']


Input:
*** Begin Patch
*** Add File: scripts/audit_completed_r2.py
+#!/usr/bin/env python3
+"""
+Audit Supabase COMPLETED videos vs Cloudflare R2.
+
+Checks:
+1) Every COMPLETED row has a non-empty R2 reference (typically `r2_tar_key`)
+2) The referenced object exists in R2 (via S3 HEAD)
+
+Outputs a CSV report (no secrets) with per-video results.
+"""
+
+from __future__ import annotations
+
+import argparse
+import csv
+import os
+import sys
+import time
+from dataclasses import dataclass
+from datetime import datetime, timezone
+from typing import Iterable, Optional, Tuple
+from urllib.parse import urlparse
+
+import boto3
+from botocore.config import Config as BotoConfig
+from botocore.exceptions import ClientError, EndpointConnectionError
+from dotenv import load_dotenv
+from supabase import create_client
+from tqdm import tqdm
+
+
+DEFAULT_BATCH_SIZE = 1000
+
+# Known buckets used by this repo (see `src/r2_client.py`).
+KNOWN_BUCKETS = [
+    "1-cleaned-data",
+    "1-cleaned-data-test",
+    "1-cleaned-data-baseline",
+    "test",
+]
+
+
+@dataclass(frozen=True)
+class ParsedRef:
+    raw: str
+    bucket_hint: Optional[str]
+    key: Optional[str]
+    kind: str  # missing | s3 | http | path
+
+
+def parse_r2_ref(raw: Optional[str], known_buckets: Iterable[str]) -> ParsedRef:
+    if raw is None:
+        return ParsedRef(raw="", bucket_hint=None, key=None, kind="missing")
+    raw = str(raw).strip()
+    if not raw:
+        return ParsedRef(raw="", bucket_hint=None, key=None, kind="missing")
+
+    buckets = set(b for b in known_buckets if b)
+
+    if raw.startswith("s3://"):
+        rest = raw[len("s3://") :]
+        if "/" not in rest:
+            return ParsedRef(raw=raw, bucket_hint=rest or None, key=None, kind="s3")
+        bucket, key = rest.split("/", 1)
+        return ParsedRef(raw=raw, bucket_hint=bucket or None, key=key.lstrip("/") or None, kind="s3")
+
+    if raw.startswith("http://") or raw.startswith("https://"):
+        parsed = urlparse(raw)
+        key = (parsed.path or "").lstrip("/") or None
+        host = (parsed.hostname or "").lower()
+        bucket_hint = None
+        for b in buckets:
+            bl = b.lower()
+            if host == bl or host.startswith(f"{bl}."):
+                bucket_hint = b
+                break
+        return ParsedRef(raw=raw, bucket_hint=bucket_hint, key=key, kind="http")
+
+    # Plain path or key. Support "bucket/key" where bucket is recognizable.
+    candidate = raw.lstrip("/")
+    if "/" in candidate:
+        first, rest = candidate.split("/", 1)
+        if first in buckets:
+            return ParsedRef(raw=raw, bucket_hint=first, key=rest.lstrip("/") or None, kind="path")
+
+    return ParsedRef(raw=raw, bucket_hint=None, key=candidate or None, kind="path")
+
+
+def build_s3_client() -> "boto3.client":
+    endpoint_url = os.environ.get("R2_ENDPOINT_URL") or os.environ.get("S3_API") or ""
+    access_key_id = os.environ.get("R2_ACCESS_KEY_ID") or os.environ.get("AWS_ACCESS_KEY_ID") or ""
+    secret_access_key = os.environ.get("R2_SECRET_ACCESS_KEY") or os.environ.get("AWS_SECRET_ACCESS_KEY") or ""
+
+    if not endpoint_url:
+        raise RuntimeError("Missing R2_ENDPOINT_URL (or S3_API) in environment.")
+    if not access_key_id:
+        raise RuntimeError("Missing R2_ACCESS_KEY_ID (or AWS_ACCESS_KEY_ID) in environment.")
+    if not secret_access_key:
+        raise RuntimeError("Missing R2_SECRET_ACCESS_KEY (or AWS_SECRET_ACCESS_KEY) in environment.")
+
+    max_pool = int(os.environ.get("R2_MAX_POOL_CONNECTIONS", "128") or 128)
+    connect_timeout = int(os.environ.get("R2_CONNECT_TIMEOUT_SEC", "10") or 10)
+    read_timeout = int(os.environ.get("R2_READ_TIMEOUT_SEC", "60") or 60)
+
+    return boto3.client(
+        "s3",
+        endpoint_url=endpoint_url,
+        aws_access_key_id=access_key_id,
+        aws_secret_access_key=secret_access_key,
+        config=BotoConfig(
+            signature_version="s3v4",
+            retries={"max_attempts": 5, "mode": "adaptive"},
+            max_pool_connections=max_pool,
+            connect_timeout=connect_timeout,
+            read_timeout=read_timeout,
+        ),
+    )
+
+
+def head_exists(s3, bucket: str, key: str) -> Tuple[bool, Optional[int], Optional[str]]:
+    try:
+        s3.head_object(Bucket=bucket, Key=key)
+        return True, 200, None
+    except ClientError as e:
+        status = int(e.response.get("ResponseMetadata", {}).get("HTTPStatusCode") or 0) or None
+        code = e.response.get("Error", {}).get("Code")
+        if status == 404 or code in {"404", "NoSuchKey", "NotFound"}:
+            return False, status or 404, None
+        return False, status, f"{code or 'ClientError'}"
+    except EndpointConnectionError:
+        return False, None, "EndpointConnectionError"
+    except Exception as e:
+        return False, None, type(e).__name__
+
+
+def iter_completed_rows(sb, batch_size: int) -> Iterable[dict]:
+    # Fetch total count first.
+    count_res = sb.table("videos").select("youtube_id", count="exact").eq("status", "COMPLETED").limit(1).execute()
+    total = int(getattr(count_res, "count", 0) or 0)
+
+    for start in range(0, total, batch_size):
+        end = min(total - 1, start + batch_size - 1)
+        res = (
+            sb.table("videos")
+            .select("youtube_id,r2_tar_key")
+            .eq("status", "COMPLETED")
+            .order("youtube_id")
+            .range(start, end)
+            .execute()
+        )
+        rows = res.data or []
+        for row in rows:
+            yield row
+
+
+def main() -> int:
+    ap = argparse.ArgumentParser(description="Audit COMPLETED videos in Supabase vs object existence in R2.")
+    ap.add_argument("--batch-size", type=int, default=DEFAULT_BATCH_SIZE)
+    ap.add_argument(
+        "--default-bucket",
+        default="1-cleaned-data",
+        help="Bucket to use when r2_tar_key does not specify one (default: 1-cleaned-data).",
+    )
+    ap.add_argument(
+        "--fallback-buckets",
+        default="",
+        help="Comma-separated bucket names to try if not found in the default bucket (only when bucket is unspecified).",
+    )
+    ap.add_argument(
+        "--out",
+        default="",
+        help="Output CSV path (default: reports/r2_audit_completed_<timestamp>.csv).",
+    )
+    args = ap.parse_args()
+
+    load_dotenv(dotenv_path=os.environ.get("DOTENV_PATH") or ".env", override=False)
+
+    if not os.environ.get("URL") or not os.environ.get("SUPABASE_ADMIN"):
+        raise RuntimeError("Missing Supabase env vars: URL and/or SUPABASE_ADMIN.")
+
+    sb = create_client(os.environ["URL"], os.environ["SUPABASE_ADMIN"])
+    s3 = build_s3_client()
+
+    default_bucket = (args.default_bucket or "").strip()
+    env_bucket = (os.environ.get("R2_BUCKET") or "").strip()
+    fallback = [b.strip() for b in (args.fallback_buckets or "").split(",") if b.strip()]
+    # Reasonable bucket search order when the row doesn't specify bucket.
+    bucket_candidates = []
+    for b in [default_bucket, env_bucket, *fallback, *KNOWN_BUCKETS]:
+        if b and b not in bucket_candidates:
+            bucket_candidates.append(b)
+
+    out_path = args.out.strip()
+    if not out_path:
+        ts = datetime.now(timezone.utc).strftime("%Y%m%dT%H%M%SZ")
+        os.makedirs("reports", exist_ok=True)
+        out_path = os.path.join("reports", f"r2_audit_completed_{ts}.csv")
+
+    # Count upfront for progress bar.
+    count_res = sb.table("videos").select("youtube_id", count="exact").eq("status", "COMPLETED").limit(1).execute()
+    total_completed = int(getattr(count_res, "count", 0) or 0)
+
+    stats = {
+        "completed_total": total_completed,
+        "missing_r2_ref": 0,
+        "bad_r2_ref": 0,
+        "exists_in_r2": 0,
+        "missing_in_r2": 0,
+        "head_errors": 0,
+    }
+    samples = {
+        "missing_r2_ref": [],
+        "missing_in_r2": [],
+        "head_errors": [],
+        "bad_r2_ref": [],
+    }
+
+    with open(out_path, "w", newline="", encoding="utf-8") as f:
+        writer = csv.DictWriter(
+            f,
+            fieldnames=[
+                "youtube_id",
+                "status",
+                "r2_tar_key_raw",
+                "parsed_kind",
+                "parsed_bucket_hint",
+                "parsed_key",
+                "checked_bucket",
+                "checked_key",
+                "exists_in_r2",
+                "head_http_status",
+                "head_error",
+            ],
+        )
+        writer.writeheader()
+
+        for row in tqdm(iter_completed_rows(sb, batch_size=args.batch_size), total=total_completed, unit="video"):
+            youtube_id = row.get("youtube_id") or ""
+            r2_ref_raw = row.get("r2_tar_key")
+            parsed = parse_r2_ref(r2_ref_raw, bucket_candidates)
+
+            exists = False
+            checked_bucket = ""
+            checked_key = ""
+            http_status = None
+            head_error = None
+
+            if parsed.kind == "missing" or not parsed.key:
+                stats["missing_r2_ref"] += 1
+                if len(samples["missing_r2_ref"]) < 25:
+                    samples["missing_r2_ref"].append(youtube_id)
+            else:
+                if parsed.bucket_hint:
+                    buckets_to_try = [parsed.bucket_hint]
+                else:
+                    buckets_to_try = bucket_candidates
+
+                found = False
+                for b in buckets_to_try:
+                    ok, st, err = head_exists(s3, b, parsed.key)
+                    checked_bucket = b
+                    checked_key = parsed.key
+                    http_status = st
+                    head_error = err
+                    if ok:
+                        exists = True
+                        found = True
+                        break
+                    # If the bucket wasn't specified, only try additional buckets
+                    # when this looks like a genuine "missing" (404); for auth/other
+                    # errors we stop to avoid misclassifying.
+                    if parsed.bucket_hint is None and err is not None and (st is None or st >= 400) and st != 404:
+                        break
+                if exists:
+                    stats["exists_in_r2"] += 1
+                else:
+                    if head_error:
+                        stats["head_errors"] += 1
+                        if len(samples["head_errors"]) < 25:
+                            samples["head_errors"].append(youtube_id)
+                    else:
+                        stats["missing_in_r2"] += 1
+                        if len(samples["missing_in_r2"]) < 25:
+                            samples["missing_in_r2"].append(youtube_id)
+
+            # Flag clearly bad refs (present but un-HEAD-able due to no key).
+            if parsed.kind != "missing" and not parsed.key:
+                stats["bad_r2_ref"] += 1
+                if len(samples["bad_r2_ref"]) < 25:
+                    samples["bad_r2_ref"].append(youtube_id)
+
+            writer.writerow(
+                {
+                    "youtube_id": youtube_id,
+                    "status": "COMPLETED",
+                    "r2_tar_key_raw": "" if r2_ref_raw is None else str(r2_ref_raw),
+                    "parsed_kind": parsed.kind,
+                    "parsed_bucket_hint": parsed.bucket_hint or "",
+                    "parsed_key": parsed.key or "",
+                    "checked_bucket": checked_bucket,
+                    "checked_key": checked_key,
+                    "exists_in_r2": "true" if exists else "false",
+                    "head_http_status": "" if http_status is None else str(http_status),
+                    "head_error": head_error or "",
+                }
+            )
+
+    summary_path = out_path + ".summary.txt"
+    with open(summary_path, "w", encoding="utf-8") as sf:
+        sf.write(f"completed_total={stats['completed_total']}\n")
+        sf.write(f"missing_r2_ref={stats['missing_r2_ref']}\n")
+        sf.write(f"bad_r2_ref={stats['bad_r2_ref']}\n")
+        sf.write(f"exists_in_r2={stats['exists_in_r2']}\n")
+        sf.write(f"missing_in_r2={stats['missing_in_r2']}\n")
+        sf.write(f"head_errors={stats['head_errors']}\n")
+        for k in ["missing_r2_ref", "missing_in_r2", "head_errors", "bad_r2_ref"]:
+            sf.write(f"{k}_sample={','.join(samples[k])}\n")
+
+    print("Audit complete.")
+    print(f"Report: {out_path}")
+    print(f"Summary: {summary_path}")
+    print(
+        "Counts: "
+        f"completed={stats['completed_total']} "
+        f"missing_ref={stats['missing_r2_ref']} "
+        f"exists={stats['exists_in_r2']} "
+        f"missing_in_r2={stats['missing_in_r2']} "
+        f"errors={stats['head_errors']}"
+    )
+    return 0
+
+
+if __name__ == "__main__":
+    raise SystemExit(main())
+
*** End Patch


Output: {"output":"Success. Updated the following files:\nA scripts/audit_completed_r2.py\n","metadata":{"exit_code":0,"duration_seconds":0.0}}


Output: Plan updated