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The tree was a debranded snapshot of upstream taken around 2026-02-20, and upstream has moved about five months since. This replaces it with upstream master, mechanically re-derived: bin/debrand does the rename, and the pipeline and squashed migrations are restored from the shipped tree. Not a merge. The previous import replaced the tree wholesale in a single commit, so there is no shared content history to merge against. Reproducing the rename on the new tree is what actually converges. What survives: .hanzo/workflows, the Dockerfiles and bin/docker* entrypoints, compose files, LLM.md, and insights/migrations. The squashed initial migration is load-bearing — the live database records it by name, so upstream's ~918 individual migrations cannot come back. Nine products are dropped as unreferenced. Twenty-one more that we do not run are kept anyway because the core app still imports them; unpicking those is a refactor and does not belong in a rebase. This base does not build yet, and the reasons are not in the rename: upstream now wants Python 3.13.13 against our 3.12.12 and Django 5.2 against our 4.2, and the dependency manifests still name upstream packages that we republish under our own names. Those are decisions, not renames.
635 lines
28 KiB
TypeScript
635 lines
28 KiB
TypeScript
import { useMDXComponents } from 'scenes/onboarding/shared/OnboardingDocsContentWrapper'
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const propertyColumnStyle = { minWidth: '150px' }
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export const GenerationEvent = (): JSX.Element => {
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const { Markdown, dedent, CodeBlock } = useMDXComponents()
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return (
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<>
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<Markdown>
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{dedent`
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A generation is a single call to an LLM.
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**Event name**: \`$ai_generation\`
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### Core properties
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`}
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</Markdown>
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<div className="Markdown">
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<table className="my-4">
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<thead>
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<tr>
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<th style={propertyColumnStyle}>Property</th>
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<th>Description</th>
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</tr>
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</thead>
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<tbody>
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<tr>
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<td style={propertyColumnStyle}>
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<code>$ai_trace_id</code>
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</td>
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<td>
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<p>
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The trace ID (a UUID to group AI events) like <code>conversation_id</code>
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<br />
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Must contain only letters, numbers, and special characters: <code>-</code>,{' '}
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<code>_</code>, <code>~</code>, <code>.</code>, <code>@</code>, <code>(</code>,{' '}
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<code>)</code>, <code>!</code>, <code>'</code>, <code>:</code>, <code>|</code>
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<br />
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Example: <code>d9222e05-8708-41b8-98ea-d4a21849e761</code>
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</p>
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</td>
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</tr>
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<tr>
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<td style={propertyColumnStyle}>
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<code>$ai_session_id</code>
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</td>
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<td>
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<p>
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<em>(Optional)</em> Groups related traces together. Use this to organize traces by
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whatever grouping makes sense for your application (user sessions, workflows,
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conversations, or other logical boundaries).
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<br />
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Example: <code>session-abc-123</code>, <code>conv-user-456</code>
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</p>
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</td>
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</tr>
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<tr>
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<td style={propertyColumnStyle}>
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<code>$ai_span_id</code>
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</td>
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<td>
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<p>
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<em>(Optional)</em> Unique identifier for this generation
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</p>
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</td>
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</tr>
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<tr>
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<td style={propertyColumnStyle}>
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<code>$ai_span_name</code>
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</td>
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<td>
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<p>
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<em>(Optional)</em> Name given to this generation
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<br />
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Example: <code>summarize_text</code>
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</p>
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</td>
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</tr>
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<tr>
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<td style={propertyColumnStyle}>
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<code>$ai_parent_id</code>
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</td>
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<td>
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<p>
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<em>(Optional)</em> Parent span ID for tree view grouping
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</p>
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</td>
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</tr>
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<tr>
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<td style={propertyColumnStyle}>
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<code>$ai_model</code>
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</td>
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<td>
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<p>
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The model used
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<br />
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Example: <code>gpt-5-mini</code>
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</p>
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</td>
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</tr>
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<tr>
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<td style={propertyColumnStyle}>
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<code>$ai_provider</code>
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</td>
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<td>
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<p>
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The LLM provider
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<br />
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Example: <code>openai</code>, <code>anthropic</code>, <code>gemini</code>
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</p>
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</td>
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</tr>
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<tr>
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<td style={propertyColumnStyle}>
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<code>$ai_input</code>
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</td>
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<td>
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<p>
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List of messages sent to the LLM. Each message should have a <code>role</code>{' '}
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property with one of: <code>"user"</code>, <code>"system"</code>, or{' '}
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<code>"assistant"</code>
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<br />
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Example:
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</p>
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<CodeBlock
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language="json"
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code={dedent`
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[
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{
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"role": "user",
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"content": [
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{
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"type": "text",
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"text": "What's in this image?"
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},
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{
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"type": "image",
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"image": "https://example.com/image.jpg"
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},
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{
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"type": "function",
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"function": {
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"name": "get_weather",
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"arguments": {
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"location": "San Francisco"
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}
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}
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}
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]
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}
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]
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`}
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/>
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</td>
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</tr>
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<tr>
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<td style={propertyColumnStyle}>
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<code>$ai_input_tokens</code>
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</td>
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<td>
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<p>The number of tokens in the input (often found in response.usage)</p>
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</td>
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</tr>
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<tr>
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<td style={propertyColumnStyle}>
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<code>$ai_output_choices</code>
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</td>
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<td>
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<p>
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List of response choices from the LLM. Each choice should have a <code>role</code>{' '}
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property with one of: <code>"user"</code>, <code>"system"</code>, or{' '}
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<code>"assistant"</code>
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<br />
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Example:
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</p>
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<CodeBlock
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language="json"
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code={dedent`
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[
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{
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"role": "assistant",
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"content": [
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{
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"type": "text",
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"text": "I can see a mascot in the image."
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},
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{
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"type": "function",
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"function": {
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"name": "get_weather",
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"arguments": {
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"location": "San Francisco"
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}
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}
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}
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]
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}
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]
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`}
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/>
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</td>
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</tr>
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<tr>
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<td style={propertyColumnStyle}>
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<code>$ai_output_tokens</code>
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</td>
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<td>
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<p>The number of tokens in the output (often found in response.usage)</p>
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</td>
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</tr>
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<tr>
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<td style={propertyColumnStyle}>
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<code>$ai_latency</code>
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</td>
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<td>
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<p>
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<em>(Optional)</em> The latency of the LLM call in seconds
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</p>
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</td>
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</tr>
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<tr>
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<td style={propertyColumnStyle}>
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<code>$ai_time_to_first_token</code>
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</td>
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<td>
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<p>
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<em>(Optional)</em> Time to first token in seconds. Only applicable for streaming
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responses.
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</p>
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</td>
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</tr>
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<tr>
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<td style={propertyColumnStyle}>
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<code>$ai_http_status</code>
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</td>
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<td>
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<p>
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<em>(Optional)</em> The HTTP status code of the response
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</p>
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</td>
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</tr>
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<tr>
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<td style={propertyColumnStyle}>
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<code>$ai_base_url</code>
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</td>
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<td>
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<p>
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<em>(Optional)</em> The base URL of the LLM provider
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<br />
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Example: <code>https://api.openai.com/v1</code>
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</p>
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</td>
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</tr>
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<tr>
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<td style={propertyColumnStyle}>
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<code>$ai_request_url</code>
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</td>
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<td>
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<p>
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<em>(Optional)</em> The full URL of the request made to the LLM API
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<br />
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Example: <code>https://api.openai.com/v1/chat/completions</code>
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</p>
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</td>
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</tr>
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<tr>
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<td style={propertyColumnStyle}>
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<code>$ai_is_error</code>
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</td>
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<td>
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<p>
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<em>(Optional)</em> Boolean to indicate if the request was an error
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</p>
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</td>
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</tr>
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<tr>
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<td style={propertyColumnStyle}>
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<code>$ai_error</code>
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</td>
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<td>
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<p>
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<em>(Optional)</em> The error message or object
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</p>
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</td>
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</tr>
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<tr>
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<td style={propertyColumnStyle}>
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<code>$ai_stop_reason</code>
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</td>
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<td>
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<p>
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<em>(Optional)</em> The reason the model stopped generating tokens
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<br />
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Example: <code>end_turn</code>, <code>stop</code>, <code>max_tokens</code>,{' '}
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<code>tool_use</code>
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</p>
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</td>
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</tr>
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</tbody>
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</table>
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</div>
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<Markdown>
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{dedent`
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### Cost properties
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Cost properties are optional as we can automatically calculate them from model and token counts. If you want, you can provide your own cost properties or custom pricing instead.
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#### Pre-calculated costs
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`}
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</Markdown>
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<div className="Markdown">
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<table className="my-4">
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<thead>
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<tr>
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<th style={propertyColumnStyle}>Property</th>
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<th>Description</th>
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</tr>
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</thead>
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<tbody>
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<tr>
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<td style={propertyColumnStyle}>
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<code>$ai_input_cost_usd</code>
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</td>
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<td>
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<p>
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<em>(Optional)</em> The cost in USD of the input tokens
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</p>
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</td>
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</tr>
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<tr>
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<td style={propertyColumnStyle}>
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<code>$ai_output_cost_usd</code>
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</td>
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<td>
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<p>
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<em>(Optional)</em> The cost in USD of the output tokens
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</p>
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</td>
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</tr>
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<tr>
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<td style={propertyColumnStyle}>
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<code>$ai_request_cost_usd</code>
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</td>
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<td>
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<p>
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<em>(Optional)</em> The cost in USD for the requests
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</p>
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</td>
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</tr>
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<tr>
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<td style={propertyColumnStyle}>
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<code>$ai_web_search_cost_usd</code>
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</td>
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<td>
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<p>
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<em>(Optional)</em> The cost in USD for the web searches
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</p>
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</td>
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</tr>
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<tr>
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<td style={propertyColumnStyle}>
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<code>$ai_total_cost_usd</code>
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</td>
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<td>
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<p>
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<em>(Optional)</em> The total cost in USD (sum of all cost components)
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</p>
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</td>
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</tr>
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</tbody>
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</table>
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</div>
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<Markdown>#### Custom pricing</Markdown>
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<div className="Markdown">
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<table className="my-4">
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<thead>
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<tr>
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<th style={propertyColumnStyle}>Property</th>
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<th>Description</th>
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</tr>
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</thead>
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<tbody>
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<tr>
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<td style={propertyColumnStyle}>
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<code>$ai_input_token_price</code>
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</td>
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<td>
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<p>
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<em>(Optional)</em> Price per input token (used to calculate{' '}
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<code>$ai_input_cost_usd</code>)
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</p>
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</td>
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</tr>
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<tr>
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<td style={propertyColumnStyle}>
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<code>$ai_output_token_price</code>
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</td>
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<td>
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<p>
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<em>(Optional)</em> Price per output token (used to calculate{' '}
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<code>$ai_output_cost_usd</code>)
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</p>
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</td>
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</tr>
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<tr>
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<td style={propertyColumnStyle}>
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<code>$ai_cache_read_token_price</code>
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</td>
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<td>
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<p>
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<em>(Optional)</em> Price per cached token read
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</p>
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</td>
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</tr>
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<tr>
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<td style={propertyColumnStyle}>
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<code>$ai_cache_write_token_price</code>
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</td>
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<td>
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<p>
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<em>(Optional)</em> Price per cached token write. For custom Anthropic pricing, this
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applies to both cache TTLs unless <code>$ai_cache_write_1h_token_price</code> is
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set.
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</p>
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</td>
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</tr>
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<tr>
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<td style={propertyColumnStyle}>
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<code>$ai_cache_write_1h_token_price</code>
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</td>
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<td>
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<p>
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<em>(Optional)</em> Price per token written to Anthropic's 1-hour cache. Takes
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precedence over <code>$ai_cache_write_token_price</code> for 1-hour writes.
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</p>
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</td>
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</tr>
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<tr>
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<td style={propertyColumnStyle}>
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<code>$ai_request_price</code>
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</td>
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<td>
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<p>
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<em>(Optional)</em> Price per request
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</p>
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</td>
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</tr>
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<tr>
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<td style={propertyColumnStyle}>
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<code>$ai_request_count</code>
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</td>
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<td>
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<p>
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<em>(Optional)</em> Number of requests (defaults to 1 if{' '}
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<code>$ai_request_price</code> is set)
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</p>
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</td>
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</tr>
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<tr>
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<td style={propertyColumnStyle}>
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<code>$ai_web_search_price</code>
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</td>
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<td>
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<p>
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<em>(Optional)</em> Price per web search
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</p>
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</td>
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</tr>
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<tr>
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<td style={propertyColumnStyle}>
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<code>$ai_web_search_count</code>
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</td>
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<td>
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<p>
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<em>(Optional)</em> Number of web searches performed
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</p>
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</td>
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</tr>
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</tbody>
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</table>
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</div>
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<Markdown>### Cache properties</Markdown>
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<div className="Markdown">
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<table className="my-4">
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<thead>
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<tr>
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<th style={propertyColumnStyle}>Property</th>
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<th>Description</th>
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</tr>
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</thead>
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<tbody>
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<tr>
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<td style={propertyColumnStyle}>
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<code>$ai_cache_read_input_tokens</code>
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</td>
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<td>
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<p>
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<em>(Optional)</em> Number of tokens read from cache
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</p>
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</td>
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</tr>
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<tr>
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<td style={propertyColumnStyle}>
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<code>$ai_cache_creation_input_tokens</code>
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</td>
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<td>
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<p>
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<em>(Optional)</em> Number of tokens written to cache (Anthropic-specific)
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<br />
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When both TTL-specific counts are present, Insights uses them instead of this
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aggregate. The aggregate should equal their sum; if either count is missing, Insights
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uses the aggregate.
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</p>
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</td>
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</tr>
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<tr>
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<td style={propertyColumnStyle}>
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<code>$ai_cache_creation_5m_input_tokens</code>
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</td>
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<td>
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<p>
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<em>(Optional)</em> Number of tokens written to Anthropic's 5-minute cache
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</p>
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</td>
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</tr>
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<tr>
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<td style={propertyColumnStyle}>
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<code>$ai_cache_creation_1h_input_tokens</code>
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</td>
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<td>
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<p>
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<em>(Optional)</em> Number of tokens written to Anthropic's 1-hour cache
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</p>
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</td>
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</tr>
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<tr>
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<td style={propertyColumnStyle}>
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<code>$ai_cache_reporting_exclusive</code>
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</td>
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<td>
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<p>
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<em>(Optional)</em> Whether cache tokens are excluded from{' '}
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<code>$ai_input_tokens</code>. When <code>true</code>, cache tokens are separate
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from input tokens. When <code>false</code>, input tokens already include cache
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tokens. Defaults to <code>true</code> for Anthropic provider or Claude models,{' '}
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<code>false</code> otherwise.
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</p>
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</td>
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</tr>
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</tbody>
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|
</table>
|
|
</div>
|
|
|
|
<Markdown>### Model parameters</Markdown>
|
|
|
|
<div className="Markdown">
|
|
<table className="my-4">
|
|
<thead>
|
|
<tr>
|
|
<th style={propertyColumnStyle}>Property</th>
|
|
<th>Description</th>
|
|
</tr>
|
|
</thead>
|
|
<tbody>
|
|
<tr>
|
|
<td style={propertyColumnStyle}>
|
|
<code>$ai_temperature</code>
|
|
</td>
|
|
<td>
|
|
<p>
|
|
<em>(Optional)</em> Temperature parameter used in the LLM request
|
|
</p>
|
|
</td>
|
|
</tr>
|
|
<tr>
|
|
<td style={propertyColumnStyle}>
|
|
<code>$ai_stream</code>
|
|
</td>
|
|
<td>
|
|
<p>
|
|
<em>(Optional)</em> Whether the response was streamed
|
|
</p>
|
|
</td>
|
|
</tr>
|
|
<tr>
|
|
<td style={propertyColumnStyle}>
|
|
<code>$ai_max_tokens</code>
|
|
</td>
|
|
<td>
|
|
<p>
|
|
<em>(Optional)</em> Maximum tokens setting for the LLM response
|
|
</p>
|
|
</td>
|
|
</tr>
|
|
<tr>
|
|
<td style={propertyColumnStyle}>
|
|
<code>$ai_tools</code>
|
|
</td>
|
|
<td>
|
|
<p>
|
|
<em>(Optional)</em> Tools/functions available to the LLM
|
|
<br />
|
|
Example:
|
|
</p>
|
|
<CodeBlock
|
|
language="json"
|
|
code={dedent`
|
|
[
|
|
{
|
|
"type": "function",
|
|
"function": {
|
|
"name": "get_weather",
|
|
"parameters": {}
|
|
}
|
|
}
|
|
]
|
|
`}
|
|
/>
|
|
</td>
|
|
</tr>
|
|
</tbody>
|
|
</table>
|
|
</div>
|
|
</>
|
|
)
|
|
}
|