LLM Analytics

For instructions on how to authenticate to use this endpoint, see API overview.

Endpoints

POST
POST
POST

Create environments llm analytics summarization

Required API key scopes

llm_analytics:write

Path parameters

  • project_id
    string

Request parameters

  • summarize_type
  • mode
    Default: minimal
  • data
  • force_refresh
    boolean
    Default: false

Response


Example request

POST /api/environments/:project_id/llm_analytics/summarization
export POSTHOG_PERSONAL_API_KEY=[your personal api key]
curl 
    -H 'Content-Type: application/json'\
    -H "Authorization: Bearer $POSTHOG_PERSONAL_API_KEY" \
    <ph_app_host>/api/environments/:project_id/llm_analytics/summarization/\
	-d summarize_type=undefined,\
	-d data=undefined

Example response

Status 200
RESPONSE
{
  "summary": "## Summary\n- User initiated conversation with greeting [L5-8]\n- Assistant responded with friendly message [L12-15]\n\n## Interesting Notes\n- Standard greeting pattern with no errors",
  "metadata": {
    "text_repr_length": 450,
    "model": "gpt-4.1"
  }
}
Status 400
Status 403
Status 500

Create environments llm analytics summarization batch check

Check which traces have cached summaries available.

This endpoint allows batch checking of multiple trace IDs to see which ones have cached summaries. Returns only the traces that have cached summaries with their titles.

Use Cases:

  • Load cached summaries on session view load
  • Avoid unnecessary LLM calls for already-summarized traces
  • Display summary previews without generating new summaries

Path parameters

  • project_id
    string

Request parameters

  • trace_ids
    array
  • mode
    Default: minimal

Response


Example request

POST /api/environments/:project_id/llm_analytics/summarization/batch_check
export POSTHOG_PERSONAL_API_KEY=[your personal api key]
curl 
    -H 'Content-Type: application/json'\
    -H "Authorization: Bearer $POSTHOG_PERSONAL_API_KEY" \
    <ph_app_host>/api/environments/:project_id/llm_analytics/summarization/batch_check/\
	-d trace_ids="array"

Example response

Status 200
RESPONSE
{
  "summaries": [
    {
      "trace_id": "string",
      "title": "string",
      "cached": true
    }
  ]
}
Status 400
Status 403

Create environments llm analytics text repr

Generate a human-readable text representation of an LLM trace event.

This endpoint converts LLM analytics events ($ai_generation, $ai_span, $ai_embedding, or $ai_trace) into formatted text representations suitable for display, logging, or analysis.

Supported Event Types:

  • $ai_generation: Individual LLM API calls with input/output messages
  • $ai_span: Logical spans with state transitions
  • $ai_embedding: Embedding generation events (text input → vector)
  • $ai_trace: Full traces with hierarchical structure

Options:

  • max_length: Maximum character count (default: 4000000)
  • truncated: Enable middle-content truncation within events (default: true)
  • truncate_buffer: Characters at start/end when truncating (default: 1000)
  • include_markers: Use interactive markers vs plain text indicators (default: true)
    • Frontend: set true for <<<TRUNCATED|base64|...>>> markers
    • Backend/LLM: set false for ... (X chars truncated) ... text
  • collapsed: Show summary vs full trace tree (default: false)
  • include_hierarchy: Include tree structure for traces (default: true)
  • max_depth: Maximum depth for hierarchical rendering (default: unlimited)
  • tools_collapse_threshold: Number of tools before auto-collapsing list (default: 5)
    • Tool lists >5 items show <<<TOOLS_EXPANDABLE|...>>> marker for frontend
    • Or [+] AVAILABLE TOOLS: N for backend when include_markers: false
  • include_line_numbers: Prefix each line with line number like L001:, L010: (default: false)

Use Cases:

  • Frontend display: truncated: true, include_markers: true, include_line_numbers: true
  • Backend LLM context (summary): truncated: true, include_markers: false, collapsed: true
  • Backend LLM context (full): truncated: false

The response includes the formatted text and metadata about the rendering.

Required API key scopes

llm_analytics:write

Path parameters

  • project_id
    string

Request parameters

  • event_type
  • data
  • options

Response


Example request

POST /api/environments/:project_id/llm_analytics/text_repr
export POSTHOG_PERSONAL_API_KEY=[your personal api key]
curl 
    -H 'Content-Type: application/json'\
    -H "Authorization: Bearer $POSTHOG_PERSONAL_API_KEY" \
    <ph_app_host>/api/environments/:project_id/llm_analytics/text_repr/\
	-d event_type=undefined,\
	-d data=undefined

Example response

Status 200
RESPONSE
{
  "text": "INPUT:\n\n[1] USER\n\nWhat is the capital of France?\n\n...",
  "metadata": {
    "event_type": "$ai_generation",
    "event_id": "gen_123",
    "rendering": "detailed",
    "char_count": 150,
    "truncated": false
  }
}
Status 400
Status 500
Status 503

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