Create Spans Bulk

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Request Body

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Span Fields

• name (string, required): The name of the span
• context (object, required): Contains trace_id, span_id, and trace_state
• kind (enum, required): One of SpanKind.CLIENT, SpanKind.CONSUMER, SpanKind.INTERNAL, SpanKind.PRODUCER, SpanKind.SERVER
• parent_id (string, optional): The ID of the parent span
• start_time (integer, required): Start time in nanoseconds since epoch
• end_time (integer, required): End time in nanoseconds since epoch
• status (object, required): Contains status_code (StatusCode.ERROR, StatusCode.OK, StatusCode.UNSET) and optional description
• attributes (object, required): Key-value pairs of span attributes
• events (array, optional): Array of span events
• links (array, optional): Array of span links
• resource (object, required): Contains attributes object and schema_url
• log_request (object, optional): Optional request log data to create alongside the span

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Log Request Fields (Optional)

• provider (string, required): The LLM provider (e.g., “openai”, “anthropic”)
• model (string, required): The model name
• input (object, required): The input template (chat or completion format)
• output (object, required): The output template (chat or completion format)
• request_start_time (datetime, required): ISO format datetime
• request_end_time (datetime, required): ISO format datetime
• parameters (object, optional): Model parameters used
• tags (array[string], optional): Tags to associate with the request
• metadata (object, optional): Metadata key-value pairs
• prompt_name (string, optional): Name of the prompt template
• prompt_version_number (integer, optional): Version number of the prompt
• prompt_input_variables (object, optional): Variables used in the prompt
• input_tokens (integer, optional): Number of input tokens
• output_tokens (integer, optional): Number of output tokens
• price (float, optional): Cost of the request
• function_name (string, optional): Name of the function called
• score (integer, optional): Score between 0-100

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Response

• success (boolean): Whether the operation succeeded
• spans (array): Array of created span objects
• request_logs (array, optional): Array of created request log objects (only present if log_request was provided)

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Example Request

{
  "spans": [
    {
      "name": "llm_call",
      "context": {
        "trace_id": "d4b5e2a1-3c8f-4e9a-b7d6-1a2b3c4d5e6f",
        "span_id": "a1b2c3d4-5e6f-7a8b-9c0d-1e2f3a4b5c6d",
        "trace_state": "promptlayer=enabled"
      },
      "kind": "SpanKind.CLIENT",
      "parent_id": "parent123",
      "start_time": 1630000000000000000,
      "end_time": 1630000001000000000,
      "status": {
        "status_code": "StatusCode.OK",
        "description": "Success"
      },
      "attributes": {
        "llm.provider": "openai",
        "llm.model": "gpt-3.5-turbo"
      },
      "resource": {
        "attributes": {
          "service.name": "my-app"
        },
        "schema_url": "https://opentelemetry.io/schemas/1.9.0"
      },
      "log_request": {
        "provider": "openai",
        "model": "gpt-3.5-turbo",
        "input": {
          "type": "chat",
          "messages": [
            {
              "role": "user",
              "content": [{"type": "text", "text": "Hello!"}]
            }
          ]
        },
        "output": {
          "type": "chat",
          "messages": [
            {
              "role": "assistant",
              "content": [{"type": "text", "text": "Hi there! How can I help you?"}]
            }
          ]
        },
        "request_start_time": "2024-01-20T10:00:00Z",
        "request_end_time": "2024-01-20T10:00:01Z",
        "prompt_name": "greeting_prompt",
        "prompt_version_number": 1,
        "input_tokens": 10,
        "output_tokens": 12,
        "tags": ["production", "greeting"],
        "metadata": {
          "user_id": "user123",
          "session": "abc123"
        }
      }
    }
  ]
}

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Notes

• Spans with names “openai.OpenAI” or “anthropic.Anthropic” are excluded from processing
• When log_request is provided, the created request log will be associated with the span via the span_id
• If a prompt_name is specified but not found, the span will still be created but the log_request creation will be skipped for that span
• All operations are atomic - if any span creation fails, the entire batch is rolled back