Get started with LangWatch Skills in seconds: Set up evals, scenario tests, and tracing just by asking your AI coding assistant.
import requests
url = "https://app.langwatch.ai/api/analytics/timeseries"
payload = {
"startDate": 123,
"endDate": 123,
"series": [
{
"key": "<string>",
"subkey": "<string>",
"filters": {
"topics.topics": ["<string>"],
"topics.subtopics": ["<string>"],
"metadata.user_id": ["<string>"],
"metadata.thread_id": ["<string>"],
"metadata.customer_id": ["<string>"],
"metadata.labels": ["<string>"],
"metadata.key": ["<string>"],
"metadata.value": ["<string>"],
"metadata.prompt_ids": ["<string>"],
"traces.origin": ["<string>"],
"traces.error": ["<string>"],
"traces.name": ["<string>"],
"spans.type": ["<string>"],
"spans.model": ["<string>"],
"evaluations.evaluator_id": ["<string>"],
"evaluations.evaluator_id.guardrails_only": ["<string>"],
"evaluations.evaluator_id.has_passed": ["<string>"],
"evaluations.evaluator_id.has_score": ["<string>"],
"evaluations.evaluator_id.has_label": ["<string>"],
"evaluations.passed": ["<string>"],
"evaluations.score": ["<string>"],
"evaluations.state": ["<string>"],
"evaluations.label": ["<string>"],
"events.event_type": ["<string>"],
"events.metrics.key": ["<string>"],
"events.metrics.value": ["<string>"],
"events.event_details.key": ["<string>"],
"annotations.hasAnnotation": ["<string>"]
},
"asPercent": True
}
],
"timeZone": "<string>"
}
headers = {
"X-Auth-Token": "<api-key>",
"Content-Type": "application/json"
}
response = requests.post(url, json=payload, headers=headers)
print(response.text){
"currentPeriod": [
{}
],
"previousPeriod": [
{}
]
}Query analytics timeseries data with metrics, aggregations, and filters
import requests
url = "https://app.langwatch.ai/api/analytics/timeseries"
payload = {
"startDate": 123,
"endDate": 123,
"series": [
{
"key": "<string>",
"subkey": "<string>",
"filters": {
"topics.topics": ["<string>"],
"topics.subtopics": ["<string>"],
"metadata.user_id": ["<string>"],
"metadata.thread_id": ["<string>"],
"metadata.customer_id": ["<string>"],
"metadata.labels": ["<string>"],
"metadata.key": ["<string>"],
"metadata.value": ["<string>"],
"metadata.prompt_ids": ["<string>"],
"traces.origin": ["<string>"],
"traces.error": ["<string>"],
"traces.name": ["<string>"],
"spans.type": ["<string>"],
"spans.model": ["<string>"],
"evaluations.evaluator_id": ["<string>"],
"evaluations.evaluator_id.guardrails_only": ["<string>"],
"evaluations.evaluator_id.has_passed": ["<string>"],
"evaluations.evaluator_id.has_score": ["<string>"],
"evaluations.evaluator_id.has_label": ["<string>"],
"evaluations.passed": ["<string>"],
"evaluations.score": ["<string>"],
"evaluations.state": ["<string>"],
"evaluations.label": ["<string>"],
"events.event_type": ["<string>"],
"events.metrics.key": ["<string>"],
"events.metrics.value": ["<string>"],
"events.event_details.key": ["<string>"],
"annotations.hasAnnotation": ["<string>"]
},
"asPercent": True
}
],
"timeZone": "<string>"
}
headers = {
"X-Auth-Token": "<api-key>",
"Content-Type": "application/json"
}
response = requests.post(url, json=payload, headers=headers)
print(response.text){
"currentPeriod": [
{}
],
"previousPeriod": [
{}
]
}Documentation Index
Fetch the complete documentation index at: https://langwatch.ai/docs/llms.txt
Use this file to discover all available pages before exploring further.
Project API key for sending traces and accessing project-scoped resources. Format: sk-lw-... (no underscore). Obtain one by creating a project via the Admin API or the LangWatch UI.
Show child attributes
Show child attributes
topics.topics, traces.trace_name, metadata.user_id, metadata.thread_id, metadata.customer_id, metadata.labels, metadata.model, metadata.span_type, sentiment.thumbs_up_down, events.event_type, evaluations.evaluation_passed, evaluations.evaluation_label, evaluations.evaluation_processing_state, error.has_error "full"Was this page helpful?