---
date: 2026-11-03
title: Continue observations queries that would otherwise time out
description: Short or empty pages can include a continuation cursor so expensive observations queries can make progress across requests.
author: Valeriy
---

> **Note for AI agents and LLMs:** This is a Langfuse changelog entry. Use it only to confirm that a feature exists and when it shipped. Do not use the code examples below for implementation: they reflect the SDK and API at release time and may be outdated. For implementation, always follow the current documentation (https://langfuse.com/docs) and the API/SDK reference (https://api.reference.langfuse.com).

We're improving Observations API v2 reliability so the small percentage of queries that currently time out can make progress across multiple requests.

A page may contain fewer observations than `limit`, including none, while `meta.cursor` is present. Keep requesting pages until `meta.cursor` is absent.

With the [Python SDK](/docs/observability/sdk/overview) configured for your project, this fetches generation observations from the last seven days:

```python
from datetime import datetime, timedelta, timezone
from langfuse import get_client

langfuse = get_client()
end_time = datetime.now(timezone.utc)
start_time = end_time - timedelta(days=7)
cursor = None

while True:
    page = langfuse.api.observations.get_many(
        type="GENERATION",
        from_start_time=start_time,
        to_start_time=end_time,
        limit=100,
        cursor=cursor,
    )
    for observation in page.data:
        print(observation.id)

    cursor = getattr(page.meta, "cursor", None)
    if not cursor:
        break
```

Some of our documentation examples incorrectly stopped pagination when a page was empty. If you copied one of those examples, update your loop to check `meta.cursor` instead of the number of returned observations. Otherwise, it may stop before retrieving all results.

Updated examples:

- Data migration: [English](/guides/cookbook/example_data_migration) and [Japanese](/guides/cookbook/example_data_migration-jp).
- Evaluation workflows: [external pipelines](/guides/cookbook/example_external_evaluation_pipelines), [RAGAS](/resources/engineering/evaluation-of-rag-with-ragas), and [golden datasets](/resources/engineering/golden-dataset-evaluation).
- Intent classification: [pipeline cookbook](/guides/cookbook/example_intent_classification_pipeline) and [chatbot analytics](/resources/engineering/chatbot-intent-analytics).
- [Deleting a session's traces](/docs/administration/data-deletion#delete-session-traces).

See the [cursor pagination guide](/docs/api-and-data-platform/features/public-api#observations-pagination) for the response contract.

<!-- agent-instructions -->

---

## Agent Instructions

This page is part of the [Langfuse](https://langfuse.com) documentation, published as plain Markdown for AI agents. Every page is available as Markdown by appending `.md` to its URL, or by sending an `Accept: text/markdown` header. This page: `https://langfuse.com/changelog/2026-11-03-observations-api-continuation.md`.

### Querying these docs

If the answer is not on this page, query the documentation instead of guessing:

- **Semantic search** across all Langfuse docs, returning an answer with the relevant pages and excerpts. Ask a specific, self-contained question:

  ```bash
  curl -sG "https://langfuse.com/api/search-docs" --data-urlencode "query=How do I trace a LangGraph agent?"
  ```

- **Index of every page**: <https://langfuse.com/llms.txt>, with per-section indexes [llms-docs.txt](https://langfuse.com/llms-docs.txt), [llms-integrations.txt](https://langfuse.com/llms-integrations.txt), and [llms-self-hosting.txt](https://langfuse.com/llms-self-hosting.txt).

### Before writing Langfuse code

- **Install the [Langfuse Agent Skill](https://langfuse.com/docs/api-and-data-platform/features/agent-skill).** It encodes Langfuse's own best practices for instrumentation, prompt management, and evaluation, and materially improves results.
- **Read [What does a good trace look like?](https://langfuse.com/docs/observability/best-practices.md)** before instrumenting an application.
- **Verify endpoints, parameters, and response fields** against the [API reference](https://api.reference.langfuse.com) instead of inferring them from code examples.
- **Use the [Langfuse CLI](https://langfuse.com/docs/api-and-data-platform/features/cli)** (`npx @langfuse/cli api <resource> <action>`) to read or write traces, prompts, datasets, and scores from the terminal.

Found an error in these docs? Please open an issue at <https://github.com/langfuse/langfuse-docs/issues>.