ragflow/docs/develop/switch_doc_engine.md

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3	Switch Document Engine	Switch Document Engine	/switch_doc_engine	categoryIcon LucideShuffle

Switch Document Engine

Switch your doc engine from Elasticsearch to Infinity or OpenSearch.

---

RAGFlow uses Elasticsearch by default for storing full text and vectors. To switch to Infinity, follow these steps:

1. Back up the existing deployment before switching engines. Switching engines creates a new document-index store; reindex the documents after startup.

2. Stop the Go deployment:

   docker compose --env-file docker/.env -f docker/docker-compose.yml down
   

:::caution WARNING Do not add -v unless you intentionally want to delete the deployment's data volumes. :::

3. Set DOC_ENGINE=infinity in docker/.env.

4. Start the Go deployment:

   docker compose --env-file docker/.env -f docker/docker-compose.yml up -d
   

5. Reindex the documents and verify retrieval before retiring the previous document-engine data.

Switch to OpenSearch

OpenSearch is supported as an alternative to Elasticsearch. Hybrid (BM25 + vector) retrieval requires OpenSearch 2.10 or later, which provides the normalization search pipeline the Go engine provisions on startup.

1. Set DOC_ENGINE=opensearch in docker/.env and configure the connection:

   OS_HOST=opensearch39        # compose service name of the OpenSearch container
   OS_PORT=1201                # host port; the container listens on 9201
   OS_USER=admin
   OPENSEARCH_PASSWORD=infini_rag_flow_OS_01
   

2. The os section of conf/service_conf.yaml mirrors these settings:

   os:
     hosts: 'http://opensearch39:9201'
     username: 'admin'
     password: 'infini_rag_flow_OS_01'
     # insecure_skip_verify: true   # HTTPS only, self-signed dev clusters
   

   For an https:// cluster the server certificate is verified against the system trust store. Set insecure_skip_verify: true only for a development cluster with a self-signed certificate.

3. Start the deployment and reindex the documents, as in the Infinity steps above. The index template in conf/os_mapping.json declares knn_vector fields for the common embedding dimensions (128–10240); an embedding model whose dimension is not listed there cannot be indexed until a matching template is added.