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url="https://hebbkx1anhila5yf.public.blob.vercel-storage.com/2G_86pv_9j4-Z9hXwOEXmpX5GjmdQpaQtW6dWtFj96.mp4" [V0_FILE]mp4:file="/.v0/channel-audit/videos/6N8aHJ8O2M0.mp4" url="https://hebbkx1anhila5yf.public.blob.vercel-storage.com/6N8aHJ8O2M0-KHRXK9lLNuZVUYU0by010qUMemGsS4.mp4" [V0_FILE]mp4:file="/.v0/channel-audit/videos/viTCUD_Ocdk.mp4" url="https://hebbkx1anhila5yf.public.blob.vercel-storage.com/viTCUD_Ocdk-mEF5ER66yezfhl6rIgVyqyTbBL6oDn.mp4" [V0_FILE]mp4:file="/.v0/channel-audit/videos/GQJC2WChbiw.mp4" url="https://hebbkx1anhila5yf.public.blob.vercel-storage.com/GQJC2WChbiw-r7vFtgQA22VyhZvwMqVUDyCBfOsxZ7.mp4" [V0_FILE]mp4:file="/.v0/channel-audit/videos/UC5osrI5QoE.mp4" url="https://hebbkx1anhila5yf.public.blob.vercel-storage.com/UC5osrI5QoE-lV4AdUNF8IG2cUsVvhWj8FGSgVprf4.mp4" [V0_FILE]mp4:file="/.v0/channel-audit/videos/9rger6xlLPI.mp4" url="https://hebbkx1anhila5yf.public.blob.vercel-storage.com/9rger6xlLPI-h2Mgxy9vSgsvutUc4GYblrEe4dLyNL.mp4" [V0_FILE]mp4:file="/.v0/channel-audit/videos/xriB2R8g5jI.mp4" url="https://hebbkx1anhila5yf.public.blob.vercel-storage.com/xriB2R8g5jI-Ylf96Ibrk9Q6M6gasMy5G773QsH55f.mp4" [V0_FILE]mp4:file="/.v0/channel-audit/videos/MPo688ABrTw.mp4" url="https://hebbkx1anhila5yf.public.blob.vercel-storage.com/MPo688ABrTw-BKXEBnDESNmnrl7TKAsWpqWOwJB0Tb.mp4" [V0_FILE]mp4:file="/.v0/channel-audit/videos/iFbaGq0ZqEU.mp4" url="https://hebbkx1anhila5yf.public.blob.vercel-storage.com/iFbaGq0ZqEU-dxsfrt50QTd4QE2A8XyxQ7A6y5v9am.mp4" [V0_FILE]mp4:file="/.v0/channel-audit/videos/HKEheriLxjw.mp4" url="https://hebbkx1anhila5yf.public.blob.vercel-storage.com/HKEheriLxjw-3oXan8xx7bSfFM8c5FxW1LJPygilMq.mp4" [V0_FILE]mp4:file="/.v0/channel-audit/videos/fFdvHhaDr8M.mp4" url="https://hebbkx1anhila5yf.public.blob.vercel-storage.com/fFdvHhaDr8M-uZsMXxNHvcEMhEM4sAGPmd9RpKoZpX.mp4" [V0_FILE]mp4:file="/.v0/channel-audit/videos/3N1-U0LbqCg.mp4" url="https://hebbkx1anhila5yf.public.blob.vercel-storage.com/3N1-U0LbqCg-MecG25TAfqVDCmWYqG6zyG6DYVM97P.mp4" 3c:oa,129:T12c1,3c:o12c1,[V0_FILE]python:file="/.v0/channel-audit/review_media.py" import argparse import json import math import os import time from pathlib import Path ROOT = Path(__file__).resolve().parent VIDEO_IDS = ['BLMQAUag_H8', 'e2_Pv-YDK_M', 'BAmdA5-ZM14', '3N1-U0LbqCg', 'HKEheriLxjw', '6N8aHJ8O2M0', 'XtM5GflNYQA', '9rger6xlLPI', '8FhAbv02PbU', 'HG_sjEoB7-E', 'sGUCQdsklYQ', 'P_n0zhp0ODg', 'R5i9mtuvz5M', 'xriB2R8g5jI', 'GQJC2WChbiw', '7-xvTdpvyOs', 'MPo688ABrTw', 'xSEiB72adgg', '2G_86pv_9j4', 'iFbaGq0ZqEU', 'viTCUD_Ocdk', 'fFdvHhaDr8M', 'UC5osrI5QoE'] def frames(ids): import av from PIL import Image, ImageDraw, ImageFont output = ROOT / 'sheets' output.mkdir(exist_ok=True) metadata = [] font = ImageFont.load_default(size=18) for video_id in ids: path = ROOT / 'videos' / f'{video_id}.mp4' with av.open(str(path)) as container: stream = container.streams.video[0] stream.thread_type = 'AUTO' stream.codec_context.thread_count = 2 duration = float(container.duration / av.time_base) if container.duration else float(stream.duration * stream.time_base) targets = sorted(set([0.05, 0.7, 1.5, 2.5, 3.5] + list(range(5, math.floor(duration), 5)) + [max(0, duration - 0.3)])) captured = [] target_index = 0 for frame in container.decode(stream): timestamp = float(frame.time or 0) if target_index < len(targets) and timestamp >= targets[target_index]: captured.append((timestamp, frame.to_image().convert('RGB'))) target_index += 1 if target_index == len(targets): break cell_w, cell_h, label_h, columns = 225, 400, 25, 5 sheet = Image.new('RGB', (columns * cell_w, 45 + math.ceil(len(captured) / columns) * (cell_h + label_h)), '#202124') draw = ImageDraw.Draw(sheet) draw.text((10, 12), f'{video_id} | duration {duration:.2f}s | {stream.width}x{stream.height}', font=font, fill='white') for index, (timestamp, image) in enumerate(captured): x = (index % columns) * cell_w y = 45 + (index // columns) * (cell_h + label_h) image.thumbnail((cell_w, cell_h)) sheet.paste(image, (x + (cell_w - image.width) // 2, y + (cell_h - image.height) // 2)) draw.text((x + 6, y + cell_h + 2), f'{timestamp:.2f}s', font=font, fill='white') sheet.save(output / f'{video_id}.jpg', quality=88) item = {'id': video_id, 'duration': duration, 'width': stream.width, 'height': stream.height, 'fps': str(stream.average_rate), 'audio_streams': len(container.streams.audio), 'sampled_times': [round(timestamp, 2) for timestamp, _ in captured]} metadata.append(item) print(json.dumps(item), flush=True) (ROOT / 'media_metadata.json').write_text(json.dumps(metadata, indent=2), encoding='utf-8') def transcribe(ids, model_name): os.environ['HF_HUB_DISABLE_XET'] = '1' from faster_whisper import WhisperModel output = ROOT / 'transcripts' output.mkdir(exist_ok=True) print(f'Loading multilingual {model_name} speech model locally', flush=True) model = WhisperModel(model_name, device='cpu', compute_type='int8', cpu_threads=2, num_workers=1) for video_id in ids: destination = output / f'{video_id}.json' if destination.exists(): print(f'SKIP {video_id}', flush=True) continue start = time.monotonic() print(f'START {video_id}', flush=True) segments, info = model.transcribe(str(ROOT / 'videos' / f'{video_id}.mp4'), language='hi', beam_size=1, vad_filter=True, condition_on_previous_text=False) records = [{'start': round(segment.start, 2), 'end': round(segment.end, 2), 'text': segment.text, 'avg_logprob': round(segment.avg_logprob, 3), 'no_speech_prob': round(segment.no_speech_prob, 3)} for segment in segments] result = {'id': video_id, 'method': f'faster-whisper {model_name}, Hindi, automatic transcript; not manually verified', 'duration': info.duration, 'segments': records} destination.write_text(json.dumps(result, ensure_ascii=False, indent=2), encoding='utf-8') print(f'DONE {video_id} wall_seconds={time.monotonic() - start:.1f} segments={len(records)}', flush=True) if __name__ == '__main__': parser = argparse.ArgumentParser() parser.add_argument('mode', choices=['frames', 'transcribe']) parser.add_argument('--ids', nargs='*') parser.add_argument('--model', default='small') args = parser.parse_args() ids = args.ids or VIDEO_IDS if args.mode == 'frames': frames(ids) else: transcribe(ids, args.model)3c:oa,12a:T12c1,3c:o12c1,[V0_FILE]python:file="/.v0/channel-audit/review_media.py" import argparse import json import math import os import time from pathlib import Path ROOT = Path(__file__).resolve().parent VIDEO_IDS = ['BLMQAUag_H8', 'e2_Pv-YDK_M', 'BAmdA5-ZM14', '3N1-U0LbqCg', 'HKEheriLxjw', '6N8aHJ8O2M0', 'XtM5GflNYQA', '9rger6xlLPI', '8FhAbv02PbU', 'HG_sjEoB7-E', 'sGUCQdsklYQ', 'P_n0zhp0ODg', 'R5i9mtuvz5M', 'xriB2R8g5jI', 'GQJC2WChbiw', '7-xvTdpvyOs', 'MPo688ABrTw', 'xSEiB72adgg', '2G_86pv_9j4', 'iFbaGq0ZqEU', 'viTCUD_Ocdk', 'fFdvHhaDr8M', 'UC5osrI5QoE'] def frames(ids): import av from PIL import Image, ImageDraw, ImageFont output = ROOT / 'sheets' output.mkdir(exist_ok=True) metadata = [] font = ImageFont.load_default(size=18) for video_id in ids: path = ROOT / 'videos' / f'{video_id}.mp4' with av.open(str(path)) as container: stream = container.streams.video[0] stream.thread_type = 'AUTO' stream.codec_context.thread_count = 2 duration = float(container.duration / av.time_base) if container.duration else float(stream.duration * stream.time_base) targets = sorted(set([0.05, 0.7, 1.5, 2.5, 3.5] + list(range(5, math.floor(duration), 5)) + [max(0, duration - 0.3)])) captured = [] target_index = 0 for frame in container.decode(stream): timestamp = float(frame.time or 0) if target_index < len(targets) and timestamp >= targets[target_index]: captured.append((timestamp, frame.to_image().convert('RGB'))) target_index += 1 if target_index == len(targets): break cell_w, cell_h, label_h, columns = 225, 400, 25, 5 sheet = Image.new('RGB', (columns * cell_w, 45 + math.ceil(len(captured) / columns) * (cell_h + label_h)), '#202124') draw = ImageDraw.Draw(sheet) draw.text((10, 12), f'{video_id} | duration {duration:.2f}s | {stream.width}x{stream.height}', font=font, fill='white') for index, (timestamp, image) in enumerate(captured): x = (index % columns) * cell_w y = 45 + (index // columns) * (cell_h + label_h) image.thumbnail((cell_w, cell_h)) sheet.paste(image, (x + (cell_w - image.width) // 2, y + (cell_h - image.height) // 2)) draw.text((x + 6, y + cell_h + 2), f'{timestamp:.2f}s', font=font, fill='white') sheet.save(output / f'{video_id}.jpg', quality=88) item = {'id': video_id, 'duration': duration, 'width': stream.width, 'height': stream.height, 'fps': str(stream.average_rate), 'audio_streams': len(container.streams.audio), 'sampled_times': [round(timestamp, 2) for timestamp, _ in captured]} metadata.append(item) print(json.dumps(item), flush=True) (ROOT / 'media_metadata.json').write_text(json.dumps(metadata, indent=2), encoding='utf-8') def transcribe(ids, model_name): os.environ['HF_HUB_DISABLE_XET'] = '1' from faster_whisper import WhisperModel output = ROOT / 'transcripts' output.mkdir(exist_ok=True) print(f'Loading multilingual {model_name} speech model locally', flush=True) model = WhisperModel(model_name, device='cpu', compute_type='int8', cpu_threads=2, num_workers=1) for video_id in ids: destination = output / f'{video_id}.json' if destination.exists(): print(f'SKIP {video_id}', flush=True) continue start = time.monotonic() print(f'START {video_id}', flush=True) segments, info = model.transcribe(str(ROOT / 'videos' / f'{video_id}.mp4'), language='hi', beam_size=1, vad_filter=True, condition_on_previous_text=False) records = [{'start': round(segment.start, 2), 'end': round(segment.end, 2), 'text': segment.text, 'avg_logprob': round(segment.avg_logprob, 3), 'no_speech_prob': round(segment.no_speech_prob, 3)} for segment in segments] result = {'id': video_id, 'method': f'faster-whisper {model_name}, Hindi, automatic transcript; not manually verified', 'duration': info.duration, 'segments': records} destination.write_text(json.dumps(result, ensure_ascii=False, indent=2), encoding='utf-8') print(f'DONE {video_id} wall_seconds={time.monotonic() - start:.1f} segments={len(records)}', flush=True) if __name__ == '__main__': parser = argparse.ArgumentParser() parser.add_argument('mode', choices=['frames', 'transcribe']) parser.add_argument('--ids', nargs='*') parser.add_argument('--model', default='small') args = parser.parse_args() ids = args.ids or VIDEO_IDS if args.mode == 'frames': frames(ids) else: transcribe(ids, args.model)3c:o11981,105:["$","$L107",null,{"params":{"chatId":"rMAYr9EoVIH"},"promises":{"attributes":"$@111","externalMeta":"$@112","latest":"$@113","messagesRange":"$@114","messages":"$@115","template":"$@116","gitStatus":"$@117"},"children":["$","$L119",null,{"chatId":"rMAYr9EoVIH","children":["$","$L11a",null,{"seedOnlyKeys":["@\"chat:state\",\"rMAYr9EoVIH\","],"data":{"block:output:initial":{"id":"b_09caPwi25id","result":"$@11b"},"/chat/api/snapshots/proxy?chatId=rMAYr9EoVIH&messageId=Ac0VHBfnLFnhY36yEtXIeAABJl0XThlk&v=v2":"$@11c","@\"block:mappings\",\"rMAYr9EoVIH\",":{"sqlBlockExecutionStates":"$Q11d","blocksForkedFrom":"$Q11e","blocksTemplateIds":"$Q11f","blocksCreatedAt":"$Q120","blocksShared":"$Q121","blocksDeployed":"$Q122","blocksSubdomains":"$Q123","brandedBlocks":"$Q124","unlistedBlocks":"$Q125","blockOutputs":"$Q126"},"@\"chat:state\",\"rMAYr9EoVIH\",":{"messages":[{"content":{"type":"parts","parts":[],"version":1},"role":"user","id":"7oamB5pe5f2CkP2F0yv4xSsgXpkZTrtV","type":"message","isContentLoading":true,"authorId":"","createdAt":"$D2026-09-05T16:11:50.064Z"},{"content":{"type":"message-binary-format","value":[[0,[["p",{},["text",{},"Loading..."]]]],[1,{"title":"Loading message"}]]},"loadingBlocks":[],"isContentLoading":true,"role":"assistant","id":"AGv6x6Sv51CzJFaQbt5p7t3cQbgAZbff","v0ModelId":"openai/gpt-6-astra","gitRevision":{"headSha":"e5f6af416c553ae98d5564fc4c53cd6d002da178","readyAt":"2026-09-05T16:14:15.408Z","version":1,"commitMessage":"Initial commit from v0\n\nV0-Initial-Commit: v1"},"streaming":false,"finishReason":"stop","parentId":"7oamB5pe5f2CkP2F0yv4xSsgXpkZTrtV","type":"message","createdAt":"$D2026-09-05T16:11:50.065Z"},{"content":{"type":"parts","parts":[{"type":"mdx","content":"can u watch the shorts yourself?"}],"version":1},"role":"user","id":"QwMx9FydABbQcw5vMnZlIHYobem50Mor","attachments":[],"parentId":"AGv6x6Sv51CzJFaQbt5p7t3cQbgAZbff","type":"message","authorId":"P04GCUEZUT5e21LsT8GRsnnL","createdAt":"$D2026-09-05T16:21:12.157Z"},{"v0ModelId":"openai/gpt-6-astra","content":{"type":"message-binary-format","value":[[0,[["AssistantMessageContentPart",{"part":{"createdAt":1788625283121,"finishedAt":1788625283139,"lastPartSentAt":1788625283137,"taskNameActive":"Loading video browsing tools","taskNameComplete":"Loaded video browsing tools","toolCallId":"call_i2kYNfV0Kt68wgZ2tJ49Ushx","agentTurnId":"turn_bXJRojr0HAx77Duw","filePath":null,"id":"OOn5QjTEpycFDzTC","type":"task-skill-v1","parts":[{"type":"executing-skill","skillName":"agent-browser"},{"type":"skill-result","skillName":"agent-browser","skillSource":"built-in","fileCount":1,"isDesignSystem":false}]}}],["AssistantMessageContentPart",{"part":{"createdAt":1788625289282,"finishedAt":1788625290656,"lastPartSentAt":1788625290656,"taskNameActive":"Inspecting video access","id":"fVQOKpjM8fNS3l1J","type":"task-thinking-v1","parts":[{"type":"thinking-end","duration":1,"thought":"I need to avoid a long introduction. I'll try opening the videos directly and be clear about whether I can view the actual footage or just the page information. Since we have previous attempts with videos not playing, maybe I'll check the normal version instead of continuing with the shorts. I should also look at the last output and navigate to the normal URL alongside to read the earlier attempts."}]}}],["p",{},["text",{},"Let me try the video player directly. I’ll be clear about whether I can review the actual footage or only the page information."]],["AssistantMessageContentPart",{"part":{"createdAt":1788625291413,"finishedAt":1788625298880,"lastPartSentAt":1788625298371,"taskNameActive":"Opening your Short directly","taskNameComplete":"Opened your Short directly","toolCallId":"call_suw7gTi5JdSj9IKx0I4qSQS1","agentTurnId":"turn_uFx9yQRewjC3bvVf","filePath":null,"id":"i8WT1Wr6GM0yOkl2","type":"task-subtask-v1","parts":[{"type":"subtask-started","data":{"subtaskType":"bash","command":"agent-browser open \"https://www.youtube.com/watch?v=BLMQAUag_H8\" && agent-browser wait 2500 && agent-browser snapshot && agent-browser eval \"JSON.stringify(Array.from(document.querySelectorAll('video')).map(v => ({duration: v.duration, currentTime: v.currentTime, readyState: v.readyState, paused: v.paused, error: v.error?.message})))\"","timeout":60000}},{"type":"subtask-log","data":{"logType":"created-terminal"},"id":"F7ZfPg6M74sWl7Fq"},{"type":"subtask-log","data":{"logType":"poll-terminal-output","delta":"✓ - YouTube\n https://www.youtube.com/watch?v=BLMQAUag_H8\n✓ Done\n- generic\n - generic\n - generic\n - banner\n - generic\n - generic\n - generic\n - button \"Guide\" [ref=e1]\n - generic\n "},"id":"1W0aTjSKipZjsdON"},{"type":"subtask-log","data":{"logType":"poll-terminal-output","delta":" - generic\n - link \"YouTube Home\" [ref=e2]\n - generic\n - button \"Skip navigation\" [\n\n...\n\n - button \"More actions\" [ref=e109]\n\"[{\\\"duration\\\":null,\\\"currentTime\\\":0,\\\"readyState\\\":0,\\\"paused\\\":true}]\"\n"},"id":"fNppzvcLzu12RsdY"}]}}],["AssistantMessageContentPart",{"part":{"createdAt":1788625291320,"finishedAt":1788625292559,"lastPartSentAt":1788625292559,"taskNameActive":"Checking earlier playback results","taskNameComplete":"Checked earlier playback results","toolCallId":"call_1G8c2XZAcyZdjnSCoSX64EIz","agentTurnId":"turn_uFx9yQRewjC3bvVf","filePath":null,"id":"HcmJYwsrUZ6gdH9o","type":"task-read-file-v1","parts":[{"type":"reading-file","filePath":"user_read_only_context/tool_content/examining-a-higher-performing-short-task-ti-i6.txt"}]}}],["p",{},["text",{},"I tried again, but YouTube blocks playback here with "],["strong",{},["text",{},"“Sign in to confirm you’re not a bot.”"]],["text",{}," To be clear, I haven’t watched your Shorts—my earlier feedback was based on public titles and view counts. "],["strong",{},["text",{},"Upload one Short here"]],["text",{},", preferably with captions or its script, and I can assess its visuals, opening hook, story, and payoff rather than guessing from the title."]]]],[1,{}]]},"context":[],"isContentLoading":false,"role":"assistant","id":"lNfo8JeFcr6yW8XcXNUCgRhbwk1PwPbP","gitRevision":{"baseSha":"e5f6af416c553ae98d5564fc4c53cd6d002da178","headSha":"e5f6af416c553ae98d5564fc4c53cd6d002da178","readyAt":"2026-09-05T16:22:09.137Z","version":1,"commitMessage":"Update from v0"},"streaming":false,"finishReason":"stop","parentId":"QwMx9FydABbQcw5vMnZlIHYobem50Mor","type":"message","creditCost":0.3948175,"workMetrics":{"diffMap":{},"linesRead":103,"agentActions":3},"createdAt":"$D2026-09-05T16:21:12.158Z","updatedAt":"$D2026-09-05T16:22:09.137Z"},{"content":{"type":"parts","parts":[{"type":"attachment","url":"https://hebbkx1anhila5yf.public.blob.vercel-storage.com/2G_86pv_9j4-Z9hXwOEXmpX5GjmdQpaQtW6dWtFj96.mp4","name":"2G_86pv_9j4.mp4","contentType":"video/mp4","size":7469697},{"type":"attachment","url":"https://hebbkx1anhila5yf.public.blob.vercel-storage.com/6N8aHJ8O2M0-FVgCnGsOqanaOOgT1zajeCo8nxyMzs.mp4","name":"6N8aHJ8O2M0.mp4","contentType":"video/mp4","size":5341928},{"type":"attachment","url":"https://hebbkx1anhila5yf.public.blob.vercel-storage.com/7-xvTdpvyOs-Bbs0nvHQhgQx10jTqLldJDISfuQmLK.mp4","name":"7-xvTdpvyOs.mp4","contentType":"video/mp4","size":6088935},{"type":"attachment","url":"https://hebbkx1anhila5yf.public.blob.vercel-storage.com/8FhAbv02PbU-uTxOh7aQCXyzylCQrkqNlCEdqGHC9H.mp4","name":"8FhAbv02PbU.mp4","contentType":"video/mp4","size":3892506},{"type":"attachment","url":"https://hebbkx1anhila5yf.public.blob.vercel-storage.com/9rger6xlLPI-h2Mgxy9vSgsvutUc4GYblrEe4dLyNL.mp4","name":"9rger6xlLPI.mp4","contentType":"video/mp4","size":6667230},{"type":"attachment","url":"https://hebbkx1anhila5yf.public.blob.vercel-storage.com/BAmdA5-ZM14-6uX8Uf5Sehferw799R6jgssANvLaoA.mp4","name":"BAmdA5-ZM14.mp4","contentType":"video/mp4","size":4518987},{"type":"attachment","url":"https://hebbkx1anhila5yf.public.blob.vercel-storage.com/BLMQAUag_H8-AtthLyncdjpg2G4fMaeibjy0a9wP7F.mp4","name":"BLMQAUag_H8.mp4","contentType":"video/mp4","size":6662828},{"type":"attachment","url":"https://hebbkx1anhila5yf.public.blob.vercel-storage.com/e2_Pv-YDK_M-Sa2SkVTzW6NxAqp27hS8EuNYQlUaIg.mp4","name":"e2_Pv-YDK_M.mp4","contentType":"video/mp4","size":5191378},{"type":"attachment","url":"https://hebbkx1anhila5yf.public.blob.vercel-storage.com/GQJC2WChbiw-r7vFtgQA22VyhZvwMqVUDyCBfOsxZ7.mp4","name":"GQJC2WChbiw.mp4","contentType":"video/mp4","size":2776248},{"type":"attachment","url":"https://hebbkx1anhila5yf.public.blob.vercel-storage.com/HG_sjEoB7-E-oqS5B8ENWyy9J7sP7Mlyqazl7ZBQUF.mp4","name":"HG_sjEoB7-E.mp4","contentType":"video/mp4","size":8109677},{"type":"attachment","url":"https://hebbkx1anhila5yf.public.blob.vercel-storage.com/iFbaGq0ZqEU-dxsfrt50QTd4QE2A8XyxQ7A6y5v9am.mp4","name":"iFbaGq0ZqEU.mp4","contentType":"video/mp4","size":5429159},{"type":"attachment","url":"https://hebbkx1anhila5yf.public.blob.vercel-storage.com/MPo688ABrTw-BKXEBnDESNmnrl7TKAsWpqWOwJB0Tb.mp4","name":"MPo688ABrTw.mp4","contentType":"video/mp4","size":3857557},{"type":"attachment","url":"https://hebbkx1anhila5yf.public.blob.vercel-storage.com/P_n0zhp0ODg-afSXva63aO0X5jFmT6IVnxhl0hwmTF.mp4","name":"P_n0zhp0ODg.mp4","contentType":"video/mp4","size":5679040},{"type":"attachment","url":"https://hebbkx1anhila5yf.public.blob.vercel-storage.com/R5i9mtuvz5M-6fNwzIAlcCfDguf13QTaAd4zJAkXHy.mp4","name":"R5i9mtuvz5M.mp4","contentType":"video/mp4","size":6548726},{"type":"attachment","url":"https://hebbkx1anhila5yf.public.blob.vercel-storage.com/sGUCQdsklYQ-ZOOYVRa4DtksIAcrsMGyvtLE1mI4C5.mp4","name":"sGUCQdsklYQ.mp4","contentType":"video/mp4","size":7161407},{"type":"attachment","url":"https://hebbkx1anhila5yf.public.blob.vercel-storage.com/UC5osrI5QoE-lV4AdUNF8IG2cUsVvhWj8FGSgVprf4.mp4","name":"UC5osrI5QoE.mp4","contentType":"video/mp4","size":2654802},{"type":"attachment","url":"https://hebbkx1anhila5yf.public.blob.vercel-storage.com/viTCUD_Ocdk-mEF5ER66yezfhl6rIgVyqyTbBL6oDn.mp4","name":"viTCUD_Ocdk.mp4","contentType":"video/mp4","size":5729725},{"type":"attachment","url":"https://hebbkx1anhila5yf.public.blob.vercel-storage.com/xriB2R8g5jI-Ylf96Ibrk9Q6M6gasMy5G773QsH55f.mp4","name":"xriB2R8g5jI.mp4","contentType":"video/mp4","size":4120678},{"type":"attachment","url":"https://hebbkx1anhila5yf.public.blob.vercel-storage.com/xSEiB72adgg-o5SVrHH5W7BEiOow0KQk6htKkEyUkg.mp4","name":"xSEiB72adgg.mp4","contentType":"video/mp4","size":3529261},{"type":"attachment","url":"https://hebbkx1anhila5yf.public.blob.vercel-storage.com/XtM5GflNYQA-k3wRICDVGHO3IdZMNz7uPShQHdheod.mp4","name":"XtM5GflNYQA.mp4","contentType":"video/mp4","size":3214162},{"type":"mdx","content":"these are 20 short videos from my youtube channel @harghartamasha . do not do anything yet. i will provide 3 more with analytics. then i will tell u what to do ok. 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I’ll wait for the remaining 3, the analytics, and your instructions before reviewing or analyzing anything."]]]],[1,{}]]},"context":[],"isContentLoading":false,"role":"assistant","id":"qIWujawTksmeecq77gJREgi4p84GMEUd","gitRevision":{"baseSha":"e5f6af416c553ae98d5564fc4c53cd6d002da178","headSha":"e5f6af416c553ae98d5564fc4c53cd6d002da178","readyAt":"2026-09-05T16:49:03.681Z","version":1,"commitMessage":"Update from 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