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skills/seekdb-docs/official-docs/300.integrations/200.frame/400.dify.md

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+---
+sidebar_label: Dify
+slug: /dify
+---
+
+# Integrate seekdb vector search with Dify
+
+seekdb supports vector data storage, vector indexing, and embedding-based vector search. You can store vectorized data in seekdb for further search.
+
+Dify is an open-source Large Language Model (LLM) application development platform. Combining Backend as Service (BaaS) and LLMOps concepts, it enables developers to quickly build production-ready generative AI applications. Even non-technical users can participate in defining AI applications and managing data operations.
+
+Dify includes essential technologies for building LLM applications: support for hundreds of models, an intuitive prompt orchestration interface, a high-quality RAG engine, a robust agent framework, flexible workflow orchestration, along with user-friendly interfaces and APIs. This eliminates redundant development efforts, enabling developers to focus on innovation and business needs.
+
+This topic describes how to integrate the vector search capability of seekdb with Dify.
+
+## Prerequisites
+
+* Before deploying Dify, ensure that your machine meets the following minimum system requirements:
+
+  * CPU: 2 cores
+  * Memory: 4 GB
+
+* This integration tutorial runs on Docker container platform. Ensure you have set up the [Docker platform](https://docs.docker.com/get-started/get-docker/).
+
+* You have deployed seekdb.
+
+## Step 1: Obtain the database connection information
+
+Contact the seekdb deployment personnel or administrator to obtain the database connection string. For example:
+
+```sql
+obclient -h$host -P$port -u$user_name -p$password -D$database_name
+```
+
+**Parameters:**
+
+* `$host`: The IP address for connecting to the seekdb database.
+* `$port`: The port for connecting to the seekdb database. The default value is `2881`.
+* `$database_name`: The name of the database to access.
+
+    <main id="notice" type='notice'>
+        <h4>Notice</h4>
+        <p>The user connecting to the database must have the <code>CREATE</code>, <code>INSERT</code>, <code>DROP</code>, and <code>SELECT</code> privileges on the database.</p>
+    </main>
+
+* `$user_name`: The database account.
+* `$password`: The password for the account.
+
+## Step 2: Deploy Dify
+
+### Method 1
+
+For Dify deployment, refer to [Deploy with Docker Compose](https://docs.dify.ai/getting-started/install-self-hosted/docker-compose) with these modifications:
+
+* Change the `VECTOR_STORE` variable value to `oceanbase` in `.env` file.
+* Start services using `docker compose --profile oceanbase up -d`.
+
+### Method 2
+
+Alternatively, you can refer to [Dify on MySQL](https://github.com/oceanbase/dify-on-mysql) to quickly start the Dify service.
+
+To start the service, run the following commands:
+
+```shell
+cd docker
+bash setup-mysql-env.sh
+docker compose up -d
+```
+
+## Step 3: Use Dify
+
+For information about connecting LLMs in Dify, refer to [Model Configuration](https://docs.dify.ai/guides/model-configuration).