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print(f"{s.start:.1f}-{s.end:.1f} {s.text}",flush=True) except Exception as e: print("ERROR",str(e),flush=True)'3c:o41c,128:T413,python -c 'import csv,io,urllib.request,collections,datetime,statistics,json base="https://hebbkx1anhila5yf.public.blob.vercel-storage.com/" files={"table":"Table%20data-aMlTlTSGVzNPTMp5irAILv6u576Eok.csv","totals":"Totals-RsTP1ea5UtmVoegpiBJPS2AYQGpFWw.csv","chart":"Chart%20data-TCe0ZGhBg64AFlrb3U5NMy8pGyPxJt.csv"} data={k:list(csv.DictReader(io.StringIO(urllib.request.urlopen(base+v).read().decode("utf-8-sig")))) for k,v in files.items()} for k,v in data.items(): print(k,"rows",len(v),"columns",list(v[0]),"sample",json.dumps(v[:2],ensure_ascii=False)) print("DAILY TOTALS",json.dumps(data["totals"],ensure_ascii=False)) for field in ["Views","Engaged views","Subscribers","Watch time (hours)"]: vals=[float(r[field] or 0) for r in data["table"][1:]] print("RECONCILE",field,"reported",data["table"][0][field],"sum",sum(vals)) print("TOP TWO SHARE",(29833+20037)/99283*100) print("ALL CHART IDS",list(dict.fromkeys(r.get("Content") for r in data["chart"]))) print("CHART SAMPLE END",json.dumps(data["chart"][-8:],ensure_ascii=False))'3c:o9054,105:["$","$L107",null,{"params":{"chatId":"ca6Anxj4QYq"},"promises":{"attributes":"$@111","externalMeta":"$@112","latest":"$@113","messagesRange":"$@114","messages":"$@115","template":"$@116","gitStatus":"$@117"},"children":["$","$L119",null,{"chatId":"ca6Anxj4QYq","children":["$","$L11a",null,{"seedOnlyKeys":["@\"chat:state\",\"ca6Anxj4QYq\","],"data":{"block:output:initial":null,"/chat/api/snapshots/proxy?chatId=ca6Anxj4QYq&messageId=bWGL0HoA69OuNiTd296KAm8BbxvaOD0F&v=v2":"$@11b","@\"block:mappings\",\"ca6Anxj4QYq\",":{"sqlBlockExecutionStates":"$Q11c","blocksForkedFrom":"$Q11d","blocksTemplateIds":"$Q11e","blocksCreatedAt":"$Q11f","blocksShared":"$Q120","blocksDeployed":"$Q121","blocksSubdomains":"$Q122","brandedBlocks":"$Q123","unlistedBlocks":"$Q124","blockOutputs":"$Q125"},"@\"chat:state\",\"ca6Anxj4QYq\",":{"messages":[{"content":{"type":"parts","parts":[{"type":"mdx","content":"v0.app/9ef00144491c-9548/chat/youtube-growth-strategy-rMAYr9EoVIH \n\nkindly read and check all the attachments inside above public chat.\ncomplete the pending tasks based on above chat.\nkindly do not build a project on it. just answer my queries based on data provided here inside chat."}],"version":1},"role":"user","id":"otjRLHvRfjAsQHUgPcS4sV0iofOIAdhw","attachments":[],"type":"message","authorId":"nqKQcvYtboKCTjmPCqlmj4j2","createdAt":"$D2026-09-05T17:10:15.483Z"},{"v0ModelId":"openai/gpt-6-astra","content":{"type":"message-binary-format","value":[[0,[["AssistantMessageContentPart",{"part":{"createdAt":1788628218901,"finishedAt":1788628221425,"lastPartSentAt":1788628221424,"taskNameActive":"Reading linked chat","taskNameComplete":"Checked linked 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It sounds like I have 23 possible areas to cover, and I think 25,000 tokens should be enough time to explore everything. \n\nI also need to read through the remainder of the history and files; it seems important to get a comprehensive understanding before moving forward. Let's make sure I have all the necessary information!"}]}}],["p",{},["text",{},"I’ve accessed the chat and found the unfinished request: an audit of @harghartamasha explaining what may be limiting its growth. 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It looks like I'll be utilizing a combination of Bash and Python for network analysis, specifically limiting file operations to command-line interface processing. There’s also the idea of downloading via Write calls with mandated assets for the project. Perhaps I can write a batch of 23 videos and start with the first three as CSV within the Bash environment."}]}}],["AssistantMessageContentPart",{"part":{"type":"task-coding-v1","id":"block-b_EpLNAUZ3gVk","parts":[{"type":"code-project","isVersioned":true,"isSourceless":false,"changedFiles":[],"source":"[V0_FILE]csv:file=\"/tmp/channel-review/table.csv\" \n...","latestDeploymentInfo":"$121:0:1","lastDeployedAt":"2026-09-05T17:13:29.876Z","sourceVersionKey":"v_1_iizco_s3","needsBlockSource":false,"isAllImages":false,"blockId":"b_EpLNAUZ3gVk","meta":{"taskNameActive":"Making changes","taskNameComplete":"Made some changes","type":"code-project","id":"Code"},"closed":true,"lang":"typescriptreact"}],"createdAt":0,"finishedAt":1,"lastPartSentAt":1,"taskNameActive":"Making changes","taskNameComplete":"Made some changes"},"id":"block-b_EpLNAUZ3gVk"}],["AssistantMessageContentPart",{"part":{"createdAt":1788628260641,"finishedAt":1788628261289,"lastPartSentAt":1788628261289,"taskNameActive":"Considering project limitations","id":"YmnVUa805PXA57N8","type":"task-thinking-v1","parts":[{"type":"thinking-end","duration":1,"thought":"I’m realizing that tools can only handle certain aspects of the project. I can utilize Bash curl for network fetching to stdout since that’s allowed, and I might process video directly with ffmpeg in the temp CLI environment. There’s no need to copy files if the user simply wants an analysis. 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It’s a bit complex, but I feel like I can make it work!"}]}}],["AssistantMessageContentPart",{"part":{"createdAt":1788628271625,"finishedAt":1788628287201,"lastPartSentAt":1788628287066,"taskNameActive":"Preparing temporary media analysis","taskNameComplete":"Prepared temporary media analysis","toolCallId":"call_HRZdWoR5KfkpHuJzA5S1d2sa","agentTurnId":"turn_IzCOib2CrpdfyLub","filePath":null,"id":"tyLJvOgxoAHzHywk","type":"task-subtask-v1","parts":[{"type":"subtask-started","data":{"subtaskType":"bash","command":"ls -ld /tmp && python -m venv /tmp/yt-review-env && /tmp/yt-review-env/bin/pip install pillow imageio-ffmpeg faster-whisper","timeout":240000}},{"type":"subtask-log","data":{"logType":"created-terminal"},"id":"2rQwV7s1c4PVi8U6"},{"type":"subtask-log","data":{"logType":"poll-terminal-output","delta":"drwxrwxrwt 5 root root 73 Sep 5 17:10 /tmp\n"},"id":"lxxZoCH6eDvznppZ"},{"type":"subtask-log","data":{"logType":"poll-terminal-output","delta":"Collecting pillow\n Downloading 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