AI observability

Create llm analytics text repr

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

This endpoint converts AI observability 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: 2000000)
• 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.

---

---

Response

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/projects/:project_id/llm_analytics/text_repr/\
	-d event_type=undefined,\
	-d data=undefined

api_key = "[your personal api key]"
project_id = "[your project id]"
response = requests.post(
    "<ph_app_host>/api/projects/{project_id}/llm_analytics/text_repr/".format(
        project_id=project_id
    ),
    headers={"Authorization": "Bearer {}".format(api_key)},
	data={}
).json()

{
  "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
  }
}