Role-coloured bubbles. System = grey centred, user = indigo right-aligned, assistant = neutral left-aligned, tool result = green. Tool calls. Expanded by default with pretty-printed arguments. Both OpenAI's tool_calls form and Anthropic's tool_use block style are handled. Tool result messages render as a separate bubble with the result content. Code fences and inline code. Triple-backtick blocks render as with monospace, single-backtick spans render as inline code. No syntax highlighting (we don't ship a tokenizer for that), but indentation is preserved. Image references. Anthropic image blocks render a small pill showing the source URL or media type — we don't actually load the image (keeps the tool offline). Stats line. Format detected, message count, tool-call count, and a rough token estimate using the same heuristic as our Token Counter (chars / 3.8 for English, 1 token per CJK char).

Trailing commas. Standard JSON doesn't allow them. If you copied from a debugger or REPL output, you may need to clean up {...},] → {...}] before pasting. Single quotes. Python's repr uses single quotes. Run it through json.dumps before pasting, or use a Python-literal-to-JSON converter. Anthropic system prompt. The system instruction in Anthropic's API is a top-level field, not a message. If your dump only has the messages array, the system prompt won't be in there — paste it as {"role": "system", "content": "..."} at the start to see it. Tool-call arguments as escaped JSON. OpenAI returns arguments as a string of JSON. We unescape and pretty-print it. If your JSON-in-string is malformed, the raw string is shown instead. Privacy. Nothing leaves the page. The whole render runs in JS on whatever JSON you paste. Don't paste anything you wouldn't paste into a notepad app.

Chat Thread Viewer

Paste an OpenAI or Anthropic messages array (JSON) and see it rendered as a readable chat thread. Color-coded by role. Tool-call params expanded. Pure browser, no upload.

Paste messages JSON (OpenAI / Anthropic / LangChain)

What is this for?

LLM applications log their conversations as JSON arrays of messages — that's what gets sent to the API and what you'll see in audit logs, evaluation traces, fine-tuning datasets, and SDK debug output. Reading those arrays as a human is awful: walls of escaped strings, tool-call arguments wrapped in escaped JSON-inside-JSON, system prompts mashed in with the rest of the flow. This tool gives you a quick chat-bubble render so you can scan the actual conversation, see which messages contained tool calls, and spot the one prompt that went sideways.

What formats it understands

OpenAI Chat Completions. [{role, content}, ...] with optional tool_calls on assistant messages and role: "tool" for tool results. The most common shape.
Anthropic Messages API. [{role, content: [...]}] where content is an array of blocks (text, tool_use, tool_result, image). System prompt is usually top-level — paste it as a system message if you want it shown.
LangChain message dumps. [{type: "human" | "ai" | "system", content: ...}] — older LangChain shape, still common in saved traces.
Wrapper objects. If you paste {"messages": [...]} or {"input": [...]}, the wrapper gets unwrapped automatically.

What gets rendered

Role-coloured bubbles. System = grey centred, user = indigo right-aligned, assistant = neutral left-aligned, tool result = green.
Tool calls. Expanded by default with pretty-printed arguments. Both OpenAI's tool_calls form and Anthropic's tool_use block style are handled. Tool result messages render as a separate bubble with the result content.
Code fences and inline code. Triple-backtick blocks render as <pre> with monospace, single-backtick spans render as inline code. No syntax highlighting (we don't ship a tokenizer for that), but indentation is preserved.
Image references. Anthropic image blocks render a small pill showing the source URL or media type — we don't actually load the image (keeps the tool offline).
Stats line. Format detected, message count, tool-call count, and a rough token estimate using the same heuristic as our Token Counter (chars / 3.8 for English, 1 token per CJK char).

Common gotchas

Trailing commas. Standard JSON doesn't allow them. If you copied from a debugger or REPL output, you may need to clean up {...},] → {...}] before pasting.
Single quotes. Python's repr uses single quotes. Run it through json.dumps before pasting, or use a Python-literal-to-JSON converter.
Anthropic system prompt. The system instruction in Anthropic's API is a top-level field, not a message. If your dump only has the messages array, the system prompt won't be in there — paste it as {"role": "system", "content": "..."} at the start to see it.
Tool-call arguments as escaped JSON. OpenAI returns arguments as a string of JSON. We unescape and pretty-print it. If your JSON-in-string is malformed, the raw string is shown instead.
Privacy. Nothing leaves the page. The whole render runs in JS on whatever JSON you paste. Don't paste anything you wouldn't paste into a notepad app.