Merge pull request #701 from langflow-ai/docs-22-dec-25
Docs: Add some troubleshooting advice
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5 changed files with 59 additions and 10 deletions
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@ -2,5 +2,9 @@
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* Install [Podman](https://podman.io/docs/installation) (recommended) or [Docker](https://docs.docker.com/get-docker/).
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The OpenRAG team recommends, at minimum, 8 GB of RAM for container VMs.
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However, if you plan to upload large files regularly, more RAM is recommended.
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For more information, see [Troubleshoot OpenRAG](/support/troubleshoot).
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* Install [`podman-compose`](https://docs.podman.io/en/latest/markdown/podman-compose.1.html) or [Docker Compose](https://docs.docker.com/compose/install/).
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To use Docker Compose with Podman, you must alias Docker Compose commands to Podman commands.
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@ -100,3 +100,11 @@ To simplify this integration, you can get pre-configured code snippets directly
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The following example demonstrates how to generate and use code snippets for the **OpenRAG OpenSearch Agent** flow:
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<PartialIntegrateChat />
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## Troubleshoot chat {#troubleshoot-chat}
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The following issues can occur when using the OpenRAG **Chat** feature:
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* Documents seem to be missing or interpreted incorrectly: See [Troubleshoot ingestion](/ingestion#troubleshoot-ingestion).
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* Service is suddenly unavailable when it was working previously: If there is no other obvious cause, such as the service or container VM being stopped or disconnected, there might be a problem with the flow configuration. Use the [**Restore flow** option](/agents#revert-a-built-in-flow-to-its-original-configuration) to revert the **OpenRAG OpenSearch Agent** flow to its original configuration.
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If you made customizations to the flow, make sure to [export your flow](https://docs.langflow.org/concepts-flows-import) before restoring the flow.
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@ -236,11 +236,22 @@ All errors were file-specific, and they didn't stop the pipeline.
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## Troubleshoot ingestion {#troubleshoot-ingestion}
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The following issues can occur during document ingestion.
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### Failed or slow ingestion
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If an ingestion task fails, do the following:
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* Make sure you are uploading supported file types.
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* Split excessively large files into smaller files before uploading.
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* Remove unusual embedded content, such as videos or animations, before uploading. Although Docling can replace some non-text content with placeholders during ingestion, some embedded content might cause errors.
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* Make sure your Podman/Docker VM has sufficient memory for the ingestion tasks.
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The minimum recommendation is 8 GB of RAM.
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If you regularly upload large files, more RAM is recommended.
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For more information, see [Memory issue with Podman on macOS](/support/troubleshoot#memory-issue-with-podman-on-macos) and [Container out of memory errors](/support/troubleshoot#container-out-of-memory-errors).
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* If OCR ingestion fails due to OCR missing, see [OCR ingestion fails (easyocr not installed)](/support/troubleshoot#ocr-ingestion-fails-easyocr-not-installed).
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### Problems when referencing documents in chat
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If the OpenRAG **Chat** doesn't seem to use your documents correctly, [browse your knowledge base](/knowledge#browse-knowledge) to confirm that the documents are uploaded in full, and the chunks are correct.
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@ -161,6 +161,16 @@ To reset your OpenRAG deployment _and_ delete all OpenRAG data, see [Reinstall O
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</TabItem>
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</Tabs>
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## Prune images
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Use image pruning to free up disk space by removing unused OpenRAG container images.
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For TUI-managed services, use the TUI's **Prune Images** option to clean up your OpenRAG container images.
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You can choose to prune unused images only or all images.
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If you prune all images, the OpenRAG services are stopped, all images are pruned, and then the required images are pulled the next time you start the OpenRAG services.
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For self-managed services, use [`docker image prune`](https://docs.docker.com/engine/reference/commandline/image_prune/) or [`podman image prune`](https://docs.podman.io/en/latest/markdown/podman-image-prune.1.html) to remove unused images.
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## See also
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* [Uninstall OpenRAG](/uninstall)
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@ -7,13 +7,17 @@ import PartialOllamaModels from '@site/docs/_partial-ollama-models.mdx';
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This page provides troubleshooting advice for issues you might encounter when using OpenRAG or contributing to OpenRAG.
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## OpenSearch fails to start
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## Installation and start up issues
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The following issues relate to OpenRAG installation and start up.
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### OpenSearch fails to start
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Check that the value of the `OPENSEARCH_PASSWORD` [environment variable](/reference/configuration) meets the [OpenSearch password complexity requirements](https://docs.opensearch.org/latest/security/configuration/demo-configuration/#setting-up-a-custom-admin-password).
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If you need to change the password, you must [reset the OpenRAG services](/manage-services).
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## OpenRAG fails to start from the TUI with operation not supported
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### OpenRAG fails to start from the TUI with operation not supported
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This error occurs when starting OpenRAG with the TUI in [WSL (Windows Subsystem for Linux)](https://learn.microsoft.com/en-us/windows/wsl/install).
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@ -21,7 +25,7 @@ The error occurs because OpenRAG is running within a WSL environment, so `webbro
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To access the OpenRAG application, open a web browser and enter `http://localhost:3000` in the address bar.
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## OpenRAG installation fails with unable to get local issuer certificate
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### OpenRAG installation fails with unable to get local issuer certificate
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If you are installing OpenRAG on macOS, and the installation fails with `unable to get local issuer certificate`, run the following command, and then retry the installation:
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@ -31,19 +35,27 @@ open "/Applications/Python VERSION/Install Certificates.command"
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Replace `VERSION` with your installed Python version, such as `3.13`.
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### Application onboarding gets stuck on Google Chrome
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If the OpenRAG onboarding process gets stuck when using Google Chrome, try clearing your browser's cache.
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## Langflow connection issues
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Verify that the value of the `LANGFLOW_SUPERUSER` environment variable is correct.
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For more information about this variable and how this variable controls Langflow access, see [Langflow settings](/reference/configuration#langflow-settings).
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## Container out of memory errors
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## Container out of memory errors {#container-out-of-memory-errors}
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Increase Docker memory allocation or use the CPU-only deployment (base `docker-compose.yml` without GPU override) to reduce memory usage.
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Increase your container VM's allocated memory, or use a CPU-only deployment to reduce memory usage.
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## Memory issue with Podman on macOS
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For TUI-managed deployments, you can enable **CPU mode** on the TUI's **Status** page.
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For self-managed deployments, CPU-only deployments use the `docker-compose.yml` file that doesn't have GPU overrides.
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## Memory issue with Podman on macOS {#memory-issue-with-podman-on-macos}
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If you're using Podman on macOS, you might need to increase VM memory on your Podman machine.
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This example increases the machine size to 8 GB of RAM, which should be sufficient to run OpenRAG.
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This example increases the machine size to 8 GB of RAM, which is the minimum recommended RAM for OpenRAG:
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```bash
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podman machine stop
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@ -63,7 +75,7 @@ With the default [environment variable](/reference/configuration) values, OpenRA
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* 8000: Docling API
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* 9200: OpenSearch service
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## OCR ingestion fails (easyocr not installed)
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## OCR ingestion fails (easyocr not installed) {#ocr-ingestion-fails-easyocr-not-installed}
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Docling ingestion can fail with an OCR-related error that mentions `easyocr` is missing.
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This is likely due to a stale `uv` cache when you [install OpenRAG with `uvx`](/install-uvx).
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@ -144,3 +156,7 @@ See [Troubleshoot ingestion](/ingestion#troubleshoot-ingestion).
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## Ollama model issues
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<PartialOllamaModels />
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## Chat issues
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See [Troubleshoot chat](/chat#troubleshoot-chat).
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