--- title: "RAG Collections" slug: "rag-collections" updated: 2025-06-09T18:20:54Z published: 2025-06-09T18:20:54Z canonical: "docs.processmaker.com/rag-collections" --- > ## Documentation Index > Fetch the complete documentation index at: https://docs.processmaker.com/llms.txt > Use this file to discover all available pages before exploring further. # RAG Collections ## What is a RAG Collection? Retrieval-Augmented Generation (RAG) Collections are **content-based information repositories** that turn your organization’s files and web content into a semantically searchable, intelligent knowledge base. Using AI to analyze the **meaning and context** of documents, RAG Collections make this rich content available to [Genies](/v1/docs/flowgenie) - ProcessMaker’s AI automation assistants. This enables Genies to: - Provide answers rooted in your unique organizational knowledge - Adapt responses based on real-world documents your team relies on The result is smarter, more relevant AI behavior, tailored to your business, your content, and your language. RAG collections empower designers to efficiently manage and organize data from various sources, including files and URLs. By leveraging AI-powered semantic analysis, these collections enhance the context of stored data, making information retrieval more relevant and accurate. These collections are designed to serve as a powerful data source in the FlowGenie Studio, functioning as an organized database of information for the Genies. RAG Collections offer the following key benefits: - **Improved Efficiency:** Designers can create and configure RAG collections within the Designer tab, add documents and URLs. - **AI Analysis and Data Extraction:** ProcessMaker AI analyzes the data sources and extracts. - **Enhanced Contextual Insights:** AI-driven semantic analysis refines question-answering capabilities, delivering precise and contextually relevant responses that boost productivity and user experience. - **Integration with FlowGenie:** Genies can utilize RAG collections for enhanced question answering. Users can configure match thresholds and retrieval limits. - **Flexibility for External Systems:** API and data connector support enable external systems to interact with RAG collections, ensuring smooth data flow,and updates. - **Seamless Integration:** Files added through processes are automatically incorporated into a RAG collection, streamlining processes and enhancing workflow efficiency. Watch the following product tour to learn more about RAG Collections. [Embedded content](https://demos.processmaker.com/embed/cm8l1ou9e00yfzb0ipgrs47vx?embed_v=2) Creating and using a RAG Collection is a three step process: 1. [Create a RAG Collection](/v1/docs/rag-collections#create-a-rag-collection) 2. [Train a Genie using the RAG Collection](/v1/docs/rag-collections#train-a-genie-with-a-rag-collection) 3. [Add the Genie into a process](/v1/docs/rag-collections#add-the-genie-to-a-process) --- ## Create a RAG Collection Follow these steps to create a RAG collection: 1. Navigate to the **Designer** tab. 2. Hover over the **Collections** icon, and select **New Collection**. 3. In the **Name** setting, enter the name of the Collection. This name must be unique from all other Collections. This is a required setting. 4. In the **Description** setting, enter the description of the Collection. This is a required setting. 5. From the **Type** setting, select **RAG Collection**. ![](https://cdn.document360.io/2d311614-fcb7-4424-8b4c-d4d3091eebeb/Images/Documentation/Create RAG Collection.png) 6. Click **Save** to create an empty RAG Collection. 7. Click the **+Record** button to add a data source. Select from one of the following options: 1. Use the **Upload** **File** option to add a file as a data source. 2. Use the **Web** **URL** option to retrieve data from a publicly accessible URL. ![](https://cdn.document360.io/2d311614-fcb7-4424-8b4c-d4d3091eebeb/Images/Documentation/Add RAG Record.png) 8. Click **Add Source** to add it to the collection. The **Status** column of the added source shows that the file is processing and changes to complete when data has been extracted. 1. Pending: Indicates that the file is waiting to be processed. 2. Processing: Indicates that the file is currently being processed. 3. Completed: Indicates that the file was successfully processed and the metadata has been extracted. ![](https://cdn.document360.io/2d311614-fcb7-4424-8b4c-d4d3091eebeb/Images/Documentation/image(345).png) 9. After a source is successfully processed, it appears as a collection record. 10. Hover over the collection record, and select the **View** icon to review the highlights and keywords extracted from the data source. > [!NOTE] > Semantic Analysis in a RAG Collection > > - When a source is added to a RAG Collection, the system generates a contextual summary. > - For file uploads, the following file types are supported: pdf, docx, txt, md, html, htm, py, js, jsx, ts, tsx, vue, php, java, cpp, c, h, cs, rb, go, rs, swift, kt, scala, xml, xls, xlsx, pptx, csv, json --- ## Train a Genie with a RAG Collection Follow these steps to use RAG Collections in a Genie. For detailed information on FlowGenie, see [FlowGenie documentation](/v1/docs/flowgenie). 1. [Create a new Genie](/v1/docs/create-a-genie-in-the-flowgenie-studio) or [edit an existing one](/v1/docs/create-a-genie-in-the-flowgenie-studio). 2. From the **Sources** setting in the left menu, select a RAG Collection. ![](https://cdn.document360.io/2d311614-fcb7-4424-8b4c-d4d3091eebeb/Images/Documentation/Selelct RAG Collection.png) > [!NOTE] > Only fully analyzed RAG Collections are shown in the list. 3. Configure the **Match Threshold** which defines the minimum similarity score for document relevance. Select a value closer to 0 for vague matching and closer to 1 for exact matching results. 4. Set the **Limit** which denotes the number of relevant chunks to retrieve (1-25). Select a higher chunk value for higher volume of data retrieval. 5. Once configured, the Genie can provide answers based on the RAG collection’s context. --- ## Add the Genie to a Process Once the Genie has been trained to use a RAG Collection, the next step is to add the Genie to a Process. For complete details on using a Genie in a process, [see Add a Genie to a Process.](/v1/docs/add-a-genie-in-a-process) --- > [!NOTE] > Learn more > > - [Update a RAG Collection from a process](/v1/docs/update-a-rag-collection-from-a-process) > - [Edit/Configure a RAG Collection](/v1/docs/configure-a-rag-collection) ## Related - [Configure a RAG Collection](/configure-a-rag-collection.md) - [Update a RAG Collection from a Process](/update-a-rag-collection-from-a-process.md) - [Add a Genie in a Process](/add-a-genie-in-a-process.md) - [Collections](/collections.md)