Skip to main content
Version: V12

Read Content Tool

Use the Read Content tool to enable AI-powered workflows to read the text content of items in your VIDIZMO library. When you connect this tool to an AI node, the AI model can dynamically retrieve PDF document text, video transcripts, audio transcripts, and other text-based content based on user requests and workflow context.

In this article, you learn how to add, configure, and test the Read Content tool in your workflow.

Concept​

The Read Content tool is a VIDIZMO-specific tool node that provides AI models with access to the text content of items in your library. This includes PDF document text, video and audio transcripts, and other text-based content. While the Search Mashup tool finds content through search queries, the Read Content tool retrieves the actual text for specific content items using UUIDs returned by Search Mashup. Unlike regular workflow nodes that execute in sequence, this tool is invoked by an AI node only when the model determines that detailed content retrieval is needed.

Key capabilities:

  • Text content retrieval - Read PDF document text, video transcripts, audio transcripts, and other text-based content
  • UUID-based lookup - Retrieve content using UUIDs from Search Mashup results
  • Pagination and filtering - Control the portion of content retrieved using offset, limit, and regex pattern parameters
  • Permission-aware access - Respect content permissions and tenant isolation when retrieving data

Understand how the tool works​

This section explains how the Read Content tool operates within a workflow and how it connects to other nodes.

Tool connectors​

In the Workflow Designer, nodes use colored connectors to indicate the type of connection and data flow. The Read Content tool uses the green connector, which is specific to tool nodes.

Execution flow​

When a workflow runs, the Read Content tool operates in this sequence:

  1. The AI node receives user input from the chatbot.
  2. The AI model analyzes the input and determines whether content reading is needed.
  3. If content reading is needed, the AI invokes the Read Content tool through the green connector, passing a UUID from previous Search Mashup results along with optional offset, limit, and pattern parameters.
  4. The tool sends a request to the VIDIZMO API using the specified UUID and the user's authentication context.
  5. The VIDIZMO API returns the content text (PDF text, video transcript, or audio transcript).
  6. The content text is stored in the field specified in Output Field.
  7. The AI node accesses the content text and generates a response for the user.
┌─────────────┐      ┌─────────────┐      ┌──────────────────┐      ┌──────────────┐
│ User Query  │ ───► │  AI Node    │ ───► │  Read Content    │ ───► │ VIDIZMO API  │
└─────────────┘      └─────────────┘      │ (Green Connector)│      └──────────────┘
                            ▲              └──────────────────┘             │
                            │                                               │
                            └──── state.data.content_details ◄──────────────┘

When to use this tool​

Use the Read Content tool when your workflow requires:

  • Reading the text content of PDFs, video transcripts, or audio transcripts from your library
  • Retrieving content text for items identified through Search Mashup results
  • Providing the AI with full content text before performing operations such as summarization or translation
  • Extracting specific sections from content using regex patterns

Add the Read Content tool to your workflow​

Follow these steps to add the Read Content tool to your workflow canvas.

  1. Go to Portal Settings > Chatbot > Workflow.

  2. Select an existing workflow or create a new workflow.

  3. In the Node Library, expand the Tools category.

  4. Drag Read Content Tool onto the canvas.

Connect the tool to an AI node​

After you add the Read Content tool to the canvas, connect it to an AI node.

  1. Locate your AI node (such as an LLM node) on the canvas.

  2. Drag a connection line from the green connector to the input connector on the Read Content tool node.

  3. Release to create the connection. A green connector (●) indicates a successful tool connection.

NOTE: The green connector indicates that the tool is available to the AI node for on-demand invocation. The tool doesn't execute in sequence with other nodes, it executes only when the AI model decides to invoke it.

Configure the Read Content tool​

Select the Read Content node to open the Node Configuration Panel. You can configure the following options:

Description​

Instructions for the LLM on how and when to use this tool. The default description provides guidance including:

  • When to invoke content reading (user asks about a specific item's content, requests transcripts, or needs document text)
  • How to identify content from Search Mashup results using UUIDs
  • Supported arguments (uuid, offset, limit, pattern) and how to use them
  • Workflow for retrieving content: first search with Search Mashup, then read with Read Content

The AI uses this description to determine when content reading is appropriate. For example, when a user asks "What does the onboarding document say about benefits?", the AI reads the description to understand it should invoke the Read Content tool with the content's UUID and an appropriate pattern.

TIP: Keep the default description unless you need to customize the AI's content retrieval behavior for specific use cases.

Content parameters​

You can configure the following options:

  • Offset: The zero-based starting position within the content text. Use this to skip to a specific point in the content. For example, set to 0 to start from the beginning or use ${state.data.read_offset} for dynamic pagination. Default is 0.

  • Limit: The maximum number of characters to return from the content. Use this to control how much text the tool retrieves in a single invocation. Enter a fixed value or use ${state.data.read_limit} for dynamic values.

  • Pattern: A regular expression pattern to filter or extract specific sections from the content. Use this when you need to retrieve only portions of content that match a particular pattern. Enter a regex pattern or use ${state.data.search_pattern} for dynamic values.

All content parameters support Fixed (static value) and Expression (dynamic value using ${variable} syntax) input modes.

NOTE: The Read Content tool requires content UUIDs, which are returned by the Search Mashup tool. Use the Search Mashup tool first to find content, then pass the UUID to the Read Content tool. The AI determines the appropriate arguments (uuid, offset, limit, pattern) from the conversation context.

Model settings​

These optional settings let you override the default AI model. The model is used when the retrieved content exceeds the output size limit and needs to be condensed.

  • Model Provider: The AI provider to use for processing oversized content. When left empty, the tool uses the default model configured for the workflow. Specify a provider only when you need a particular model for content processing.

  • Model ID: The specific model identifier from the selected provider. When left empty, the tool uses the provider's default model.

  • Temperature: Controls the randomness of the model's output when processing oversized content. Lower values produce more deterministic results. Default is 0.3.

  • Max Token Limit: The maximum number of tokens the model can generate when condensing oversized content.

Output settings​

  • Output Field: Variable name where content details are stored for use by other nodes. Click to select an existing variable or create a new one. The AI node and subsequent workflow nodes access results using ${state.data.<variable_name>}. For example, if you name it content_details, access it as ${state.data.content_details}.

Test the configuration​

After you configure the Read Content tool, test the workflow to verify correct behavior.

  1. Go to Portal Settings > Chatbot > Agents.

  2. Select the agent associated with your workflow, or create a new agent and assign your workflow.

  3. Open the chatbot interface in the portal.

  4. Enter a query that should trigger content retrieval. For example:

    • "Tell me about this video" (with content selected in chat)
    • "What is the transcript of the onboarding training?"
    • "Show me the details of the compliance document"

  5. Verify that the agent returns accurate and complete content details.

  6. Check that the response includes the expected data parts (metadata, transcript, or descriptions).

  7. If results don't match expectations, return to the Workflow Designer and adjust your configuration.

Best practices​

  • Always use the Search Mashup tool before the Read Content tool. The Read Content tool requires content UUIDs, which are returned by Search Mashup results.
  • Pair the Read Content tool with the Summarize tool to retrieve content text and generate a summary in a single conversation turn.
  • Use the Offset and Limit parameters for large documents to retrieve content in manageable portions rather than loading the full text at once.
  • Use the Pattern parameter to extract specific sections from content when you need only a particular topic or keyword context.
  • The tool respects the user's content permissions. If a user doesn't have access to specific content, the tool returns an appropriate error.
Did you find this article helpful?