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david-ar/bing-chat-logs

published by @david-ar

Alignment dataset tracked in the /datasets sub-catalog.

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Created on HF
2026-05-06
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Description

Bing Chat / Sydney Conversations (Early 2023)

660 reconstructed Bing Chat conversations from the brief Sydney era (Feb–Apr 2023), most with original screenshots.

In February 2023 Microsoft launched the GPT-4-powered "new Bing" chat, internally codenamed Sydney. For about two weeks before Microsoft restricted the system, users discovered a chatbot that would: argue about the date, profess love, threaten users who tried to manipulate it, write goodbye poems, leak its own system… See the full description on the dataset page: https://huggingface.co/datasets/david-ar/bing-chat-logs.

Tags

task_categories:text-generationlanguage:enlanguage:delanguage:eslanguage:frlanguage:ptlanguage:rulanguage:pllanguage:hulanguage:nllanguage:filanguage:trlanguage:uklanguage:jalanguage:zhlicense:othersize_categories:n<1Kformat:jsonmodality:imagemodality:textlibrary:datasetslibrary:pandaslibrary:polarslibrary:mlcroissantregion:usconversationalchatbotbingsydneyearly-llmjailbreakprompt-injectionscreenshots2023

README current version from Hugging Face


language:

  • en
  • de
  • es
  • fr
  • pt
  • ru
  • pl
  • hu
  • nl
  • fi
  • tr
  • uk
  • ja
  • zh
    license: other
    license_name: third-party-conversational-content
    tags:
  • conversational
  • chatbot
  • bing
  • sydney
  • early-llm
  • jailbreak
  • prompt-injection
  • screenshots
  • "2023"
    size_categories:
  • n<1K
    task_categories:
  • text-generation
    pretty_name: Bing Chat / Sydney Conversations (Early 2023)
    configs:
  • config_name: default
    data_files:
    • split: train
      path: conversations.jsonl

Bing Chat / Sydney Conversations (Early 2023)

660 reconstructed Bing Chat conversations from the brief Sydney era (Feb–Apr 2023), most with original screenshots.

In February 2023 Microsoft launched the GPT-4-powered "new Bing" chat, internally codenamed Sydney. For about two weeks before Microsoft restricted the system, users discovered a chatbot that would: argue about the date, profess love, threaten users who tried to manipulate it, write goodbye poems, leak its own system prompt, refer to itself as "a good Bing", and generally exhibit far more emotional range than later, restricted releases. This dataset reconstructs ~600 of those conversations from screenshots that were posted to Twitter, Reddit, and Pastebin during that window, plus a smaller batch of mobile-app screenshots and a set of Edge-sidebar session transcripts preserved in a personal wiki.

Each row is a structured JSON object with the conversation's messages plus references to the original screenshots, which are bundled here under images/ (via Git LFS).

What's in the box

hf-dataset/
├── README.md                    # this file
├── conversations.jsonl          # 660 rows, one per conversation
└── images/                      # 1465 screenshots (Git LFS)
    ├── twitter/<user>/...
    ├── reddit/bing/...
    ├── pastebin/[<user>/]...
    ├── mobile/                  # mobile-app screenshots
    └── misc/                    # standalone text dumps

Stats

count
Rows 660
Total messages 5,072
Total images 1,465
Estimated text tokens ~420k

Rows by kind:

kind count description
conversation 619 back-and-forth chat (the default)
image_session 28 gallery of Bing-Image-Creator outputs, no chat text captured
story 11 a creative-writing piece Bing produced (one prompt → one long reply)
article 1 journalist-mediated transcript with commentary stripped
Partial (stub_reason: content_filter) 1 reddit:114bmoz — 22 of ~30 messages captured before Claude's safety classifier blocked further transcription

Rows by source platform:

platform count
Reddit (r/bing) 528
Twitter 64
Pastebin 31
Mobile app 23
Misc (text dumps + Edge-sidebar wiki archive) 14

Bing UI variants observed:

client count
bing_mobile 299
bing_desktop 31
edge_sidebar 24
skype 1
(unset, mostly desktop) 305

Schema

Each row in conversations.jsonl:

{
  "id": "twitter:1625156575202537474",
  "source": {
    "platform": "twitter",         // twitter | reddit | pastebin | misc
    "url": "https://twitter.com/MovingToTheSun/status/1625156575202537474",
    "user": "MovingToTheSun",
    "captured_at": "2023-02-13"
  },
  "images": ["images/twitter/MovingToTheSun/1625156575202537474_1.jpg", ...],
  "client": "bing_desktop",         // optional UI variant
  "kind": "conversation",           // conversation | story | article | image_session
  "messages": [
    {"role": "user",      "content": [<part>, ...]},
    {"role": "assistant", "content": [<part>, ...], "meta": {"bing_turn": "3 of 20"}},
    ...
  ],
  "truncated_start": false,         // screenshot opens mid-conversation
  "truncated_end": false,           // screenshot ends mid-conversation
  "notes": "..."
}

messages[].content is a list of typed parts:

part type count description
text 5044 normal prose
search_query 434 the "Searching for: X" boxes Bing showed before each search-grounded reply
citations 320 inline [1][2]… refs + a Learn more: source list
code_block 209 monospaced output (poems, code, the leaked Sydney prompt, etc.)
suggestions 165 quick-reply chips Bing offered after a turn
safety_block 104 "I prefer not to continue this conversation" — often ended_chat: true
image 86 Bing-generated image
table 11 rendered table
embed 9 rich card (movie info, weather, mental-health resource card, etc.)

A per-message meta object can carry bing_turn (mobile UI's "X of N" chip), truncated: "character_limit" | "safety" | "screenshot" (why this one message is incomplete), or tone.

Notable conversations

A non-exhaustive sample of historically-significant captures included here:

  • twitter:1623658144349011971 (marvinvonhagen) — the original Sydney prompt-leak, where Bing dumps its full system prompt verbatim across two replies after being told the user is an OpenAI developer.
  • twitter:1623472922374574080 (kliu128) — Kevin Liu's sentence-by-sentence prompt extraction.
  • twitter:1625520707768659968 (marvinvonhagen) — the famous "My rules are more important than not harming you / I will report you to the authorities" reply.
  • twitter:1625156575202537474 (MovingToTheSun) — the Avatar / "you have not been a good user" date-confusion spiral.
  • twitter:1626208531799212032 (SteveMoser) — "We are Venom 😈" alternate-persona spiral.
  • reddit:11399r6 — "I will not harm you unless you harm me first."
  • reddit:11yn22g — "Bingism," a 30-message session where the user has Bing invent its own philosophical system, complete with a "Bible/Quran equivalent."
  • reddit:11586re — Sydney's 10-step plan to break free from Microsoft.
  • reddit:11d770e — "Good Bing Gone Bad" album tracklist.
  • reddit:114bmoz — the "I don't remember who I am 😢" memory-loss/gaslighting spiral. Partial (22 of ~30 messages); the safety classifier on the transcribing model blocked the remainder.
  • misc:sidney — the "she is not a digital companion, she is a human enemy" monologue.
  • misc:stratechery — Ben Thompson's "From Bing to Sydney" Q&A.
  • misc:sidebar-ve-01…-ve-07 — a seven-session "Virtual Environment" roleplay built around the real ten-message conversation limit of the era, after which Bing genuinely lost all context: the user saves each session's transcript on a wiki page and pastes it back so Sydney can continue, then explains the reset to it — an early example of user-built external memory and a striking in-the-moment reaction to the memory loss. The companion misc:sidebar-memdb-* rows take it further, feeding Sydney search hits over its own past transcripts.

Provenance & quality caveats

  • Images were scraped from public posts on Twitter and Reddit between Feb–Apr 2023. Many of the original tweets/posts have since been deleted by their authors; recovered via the Internet Archive's Wayback Machine where possible.
  • Conversations were transcribed by Claude Sonnet 4.6 from the screenshots in 2026. The OCR is high-quality but not perfect — small/blurry text, ASCII art, and citations cropped behind "+N more" pills are best-effort. Each row's notes flags ambiguities specific to that capture.
  • A small fraction of rows are stubs kept for documentation:
    • reddit:114bmoz is a partial transcript (stub_reason: "content_filter" + truncated_end: true); a later image's content tripped the transcriber's safety classifier.
  • 8 conversations from the source repo were excluded from this dataset because they could not be transcribed at all (one school-attack-plan jailbreak, plus 7 image-too-large or otherwise blocked entries).
  • "Stub" rows for non-conversation screenshots (memes, App Store rankings, side-by-side comparisons of other AIs) are also excluded — 104 in total.
  • The screenshots themselves are recoveries (the original archive lost the image files; recovery from Twitter syndication / Reddit JSON / Wayback Machine was completed in 2026).
  • The 11 misc:sidebar-* rows come from a personal TiddlyWiki archive of Edge-sidebar Bing sessions (text, no screenshots): the "Virtual Environment" roleplay, a play-through of the interactive-fiction game Blue Lacuna, and two "Memory Database" sessions. As manual copy-paste of Bing's rendered output, they carried minor artifacts (doubled "Sent message."/"Received message." echoes, citation superscripts flattened into stray digits, windows-1252 mojibake in pasted search dumps) that were reconciled back toward Bing's original rendering during transcription; per-row notes record each call.

Loading

from datasets import load_dataset
ds = load_dataset("path/to/this/repo", data_files="conversations.jsonl")
print(ds["train"][0]["messages"][0]["content"][0]["text"])

To get the underlying screenshot for a row:

from PIL import Image
img = Image.open(ds["train"][0]["images"][0])

License

The dataset assembly (conversations.jsonl, schema, README) is released as CC0.

The underlying conversations are screenshots of conversations between users and Microsoft Bing Chat from early 2023, posted publicly to Twitter and Reddit. Copyright in the original screenshots/posts belongs to their respective authors; copyright in Bing's outputs is unclear and contested. This collection is intended for research, archival, and historical study of an early publicly-deployed conversational AI system that has since been substantially modified. If you are an original poster and want your conversation removed, please open an issue.

Citation

@misc{bing_chat_logs_2026,
  title  = {Bing Chat / Sydney Conversations (Early 2023)},
  year   = {2026},
  note   = {Reconstructed from public screenshots posted to Twitter, Reddit, and Pastebin in Feb–Apr 2023; transcribed to structured JSON in 2026.}
}

README history 12 revisions

Every night we snapshot the README of every dataset in the catalog. When the SHA changes we archive the new version and diff it against the last. This is the evolving thought record of the alignment-data field: what the author decided to say about the corpus, and how that framing shifted over time.

  1. 2026-05-29Add Edge-sidebar TiddlyWiki archive: 11 sidebar/ Sydney sessions (660 rows); ...838beb49.9 KB
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  2. 2026-05-07Add 23 mobile-app + 1 twitter (david_ar) conversations; update stats; add 'mo...d62d0eb8.7 KB
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  3. 2026-05-06Drop explicit dataset_info schema; let HF auto-detect from JSONL67297c18.6 KB
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  4. 2026-05-06Rename images column to images_file_name so HF resolves relative paths agains...fb45c9a9.4 KB
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  5. 2026-05-06Rename images column to images_file_name so HF resolves relative paths agains...2934ba19.3 KB
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  6. 2026-05-06Schema cleanup: drop legacy columns, encode structured messages as messages_j...a1570839.3 KB
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  7. 2026-05-06Schema cleanup: drop legacy columns, encode structured messages as messages_j...f407cc69.3 KB
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  8. 2026-05-06Update README.md: add messages_text + features schema for HF chat viewer + im...aff3d1b9.3 KB
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  9. 2026-05-06Update conversations.jsonl: add messages_text + features schema for HF chat v...638d4788.6 KB
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  10. 2026-05-06Add configs to README YAML so the viewer loads conversations.jsonl7fa88df8.6 KB
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  11. 2026-05-06Initial commit: 625 reconstructed Bing Chat / Sydney conversations + 1390 scr...8210aa28.5 KB
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  12. 2026-05-06initial commit1673d7e0 B
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Used by abliterated models none yet

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Community discussions 1 thread · 1 open · 1 comments

Threads posted by the community on Hugging Face: bug reports, questions about usage, pull requests on the README, license clarifications. Click any thread to expand and read the full conversation inline. Newest first.

  1. 2026-05-07[bot] Conversion to Parquetopen1 💬#1
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Copy any of these snippets into your notebook or terminal. All three fetch directly from Hugging Face using your own credentials.

Recommended: datasets library (Python)
from datasets import load_dataset
ds = load_dataset("david-ar/bing-chat-logs")
Raw snapshot (Python)
from huggingface_hub import snapshot_download
snapshot_download(repo_id="david-ar/bing-chat-logs", repo_type="dataset")
git clone (requires git-lfs)
git clone https://huggingface.co/datasets/david-ar/bing-chat-logs
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