Bulk create spans | Respan Docs

Creates multiple span entries in a single request. Useful for batch imports and CSV upload workflows.

Up to 500 spans per request
Per-row error handling (partial failures do not abort the batch)
logs array required: Array of span objects (max 500). Each follows the same schema as the Create span endpoint.

Python

1 import requests
2 
3 url = "https://api.respan.ai/api/request-logs/bulk/"
4 api_key = "YOUR_RESPAN_API_KEY"
5 headers = {
6     "Authorization": f"Bearer {api_key}",
7     "Content-Type": "application/json"
8 }
9 data = {
10     "logs": [
11         {
12             "model": "gpt-4o",
13             "prompt_messages": [{"role": "user", "content": "What is 2+2?"}],
14             "completion_message": {"role": "assistant", "content": "4"},
15             "usage": {"prompt_tokens": 10, "completion_tokens": 1}
16         },
17         {
18             "model": "gpt-4o",
19             "prompt_messages": [{"role": "user", "content": "Summarize this."}],
20             "completion_message": {"role": "assistant", "content": "The document discusses..."},
21             "usage": {"prompt_tokens": 150, "completion_tokens": 50}
22         }
23     ]
24 }
25 
26 response = requests.post(url, headers=headers, json=data)
27 print(response.json())

TypeScript

1 fetch('https://api.respan.ai/api/request-logs/bulk/', {
2   method: 'POST',
3   headers: {
4     'Content-Type': 'application/json',
5     'Authorization': 'Bearer YOUR_RESPAN_API_KEY'
6   },
7   body: JSON.stringify({
8     logs: [
9       {
10         model: "gpt-4o",
11         prompt_messages: [{role: "user", content: "What is 2+2?"}],
12         completion_message: {role: "assistant", content: "4"},
13         usage: {prompt_tokens: 10, completion_tokens: 1}
14       },
15       {
16         model: "gpt-4o",
17         prompt_messages: [{role: "user", content: "Summarize this."}],
18         completion_message: {role: "assistant", content: "The document discusses..."},
19         usage: {prompt_tokens: 150, completion_tokens: 50}
20       }
21     ]
22   })
23 })
24 .then(response => response.json())
25 .then(data => console.log(data));

Creates multiple span entries in a single request. Useful for batch imports and CSV upload workflows. - Up to **500** spans per request - Per-row error handling (partial failures do not abort the batch) - `logs` *array* **required**: Array of span objects (max 500). Each follows the same schema as the [Create span](/api-reference/observe/logs/create-span) endpoint. ```Python Python import requests url = "https://api.respan.ai/api/request-logs/bulk/" api_key = "YOUR_RESPAN_API_KEY" headers = { "Authorization": f"Bearer {api_key}", "Content-Type": "application/json" } data = { "logs": [ { "model": "gpt-4o", "prompt_messages": [{"role": "user", "content": "What is 2+2?"}], "completion_message": {"role": "assistant", "content": "4"}, "usage": {"prompt_tokens": 10, "completion_tokens": 1} }, { "model": "gpt-4o", "prompt_messages": [{"role": "user", "content": "Summarize this."}], "completion_message": {"role": "assistant", "content": "The document discusses..."}, "usage": {"prompt_tokens": 150, "completion_tokens": 50} } ] } response = requests.post(url, headers=headers, json=data) print(response.json()) ``` ```TypeScript TypeScript fetch('https://api.respan.ai/api/request-logs/bulk/', { method: 'POST', headers: { 'Content-Type': 'application/json', 'Authorization': 'Bearer YOUR_RESPAN_API_KEY' }, body: JSON.stringify({ logs: [ { model: "gpt-4o", prompt_messages: [{role: "user", content: "What is 2+2?"}], completion_message: {role: "assistant", content: "4"}, usage: {prompt_tokens: 10, completion_tokens: 1} }, { model: "gpt-4o", prompt_messages: [{role: "user", content: "Summarize this."}], completion_message: {role: "assistant", content: "The document discusses..."}, usage: {prompt_tokens: 150, completion_tokens: 50} } ] }) }) .then(response => response.json()) .then(data => console.log(data)); ```

Authentication

AuthorizationBearer

API key authentication. Get your API key from https://platform.respan.ai/platform/api-keys

Request

This endpoint expects an object.

logslist of objectsRequired

Array of span objects (max 500). Each follows the same schema as the Create span endpoint.

Response

Spans created (may include partial failures)

success_countinteger

Number of successfully created spans

error_countinteger

Number of failed spans

errorslist of objects

Error details: [{index, error}]

Errors

401

Unauthorized Error

422

Unprocessable Entity Error

Creates multiple span entries in a single request. Useful for batch imports and CSV upload workflows.

Up to 500 spans per request
Per-row error handling (partial failures do not abort the batch)
logs array required: Array of span objects (max 500). Each follows the same schema as the Create span endpoint.

Python

1 import requests
2 
3 url = "https://api.respan.ai/api/request-logs/bulk/"
4 api_key = "YOUR_RESPAN_API_KEY"
5 headers = {
6     "Authorization": f"Bearer {api_key}",
7     "Content-Type": "application/json"
8 }
9 data = {
10     "logs": [
11         {
12             "model": "gpt-4o",
13             "prompt_messages": [{"role": "user", "content": "What is 2+2?"}],
14             "completion_message": {"role": "assistant", "content": "4"},
15             "usage": {"prompt_tokens": 10, "completion_tokens": 1}
16         },
17         {
18             "model": "gpt-4o",
19             "prompt_messages": [{"role": "user", "content": "Summarize this."}],
20             "completion_message": {"role": "assistant", "content": "The document discusses..."},
21             "usage": {"prompt_tokens": 150, "completion_tokens": 50}
22         }
23     ]
24 }
25 
26 response = requests.post(url, headers=headers, json=data)
27 print(response.json())

TypeScript

1 fetch('https://api.respan.ai/api/request-logs/bulk/', {
2   method: 'POST',
3   headers: {
4     'Content-Type': 'application/json',
5     'Authorization': 'Bearer YOUR_RESPAN_API_KEY'
6   },
7   body: JSON.stringify({
8     logs: [
9       {
10         model: "gpt-4o",
11         prompt_messages: [{role: "user", content: "What is 2+2?"}],
12         completion_message: {role: "assistant", content: "4"},
13         usage: {prompt_tokens: 10, completion_tokens: 1}
14       },
15       {
16         model: "gpt-4o",
17         prompt_messages: [{role: "user", content: "Summarize this."}],
18         completion_message: {role: "assistant", content: "The document discusses..."},
19         usage: {prompt_tokens: 150, completion_tokens: 50}
20       }
21     ]
22   })
23 })
24 .then(response => response.json())
25 .then(data => console.log(data));

1	curl -X POST https://api.respan.ai/api/request-logs/bulk/ \
2	-H "Authorization: Bearer <token>" \
3	-H "Content-Type: application/json" \
4	-d '{
5	"logs": [
6	{},
7	{}
8	]
9	}'

1	{
2	"success_count": 2,
3	"error_count": 1,
4	"errors": [
5	{
6	"index": 1,
7	"error": "Invalid logging format: Input should be a valid list"
8	}
9	]
10	}

1	import requests
2
3	url = "https://api.respan.ai/api/request-logs/bulk/"
4	api_key = "YOUR_RESPAN_API_KEY"
5	headers = {
6	"Authorization": f"Bearer {api_key}",
7	"Content-Type": "application/json"
8	}
9	data = {
10	"logs": [
11	{
12	"model": "gpt-4o",
13	"prompt_messages": [{"role": "user", "content": "What is 2+2?"}],
14	"completion_message": {"role": "assistant", "content": "4"},
15	"usage": {"prompt_tokens": 10, "completion_tokens": 1}
16	},
17	{
18	"model": "gpt-4o",
19	"prompt_messages": [{"role": "user", "content": "Summarize this."}],
20	"completion_message": {"role": "assistant", "content": "The document discusses..."},
21	"usage": {"prompt_tokens": 150, "completion_tokens": 50}
22	}
23	]
24	}
25
26	response = requests.post(url, headers=headers, json=data)
27	print(response.json())

1	fetch('https://api.respan.ai/api/request-logs/bulk/', {
2	method: 'POST',
3	headers: {
4	'Content-Type': 'application/json',
5	'Authorization': 'Bearer YOUR_RESPAN_API_KEY'
6	},
7	body: JSON.stringify({
8	logs: [
9	{
10	model: "gpt-4o",
11	prompt_messages: [{role: "user", content: "What is 2+2?"}],
12	completion_message: {role: "assistant", content: "4"},
13	usage: {prompt_tokens: 10, completion_tokens: 1}
14	},
15	{
16	model: "gpt-4o",
17	prompt_messages: [{role: "user", content: "Summarize this."}],
18	completion_message: {role: "assistant", content: "The document discusses..."},
19	usage: {prompt_tokens: 150, completion_tokens: 50}
20	}
21	]
22	})
23	})
24	.then(response => response.json())
25	.then(data => console.log(data));