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Introduction

Integrate Tavily with Langflow to create powerful AI workflows using a visual interface. Langflow is an open-source tool that provides a visual builder for creating AI agents and workflows, making it easy to incorporate Tavily’s search and extraction capabilities into your applications.

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Installation

Langflow works with Python 3.10 to 3.13. You can install it using either UV (recommended) or pip:

# Using UV (recommended)
uv pip install langflow

# Using pip
pip install langflow

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Setting Up Tavily Components in Langflow

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Step 1: Launch Langflow

After installation, start Langflow:

langflow run

This will start the Langflow server locally at http://localhost:7860.

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Step 2: Using Tavily Components

Langflow provides two main Tavily components in the Tools section of the components library:

  1. Tavily Search API: Perform web searches and retrieve relevant information

    • Located under Tools > Tavily Search API
    • Configuration Options: Select the component and go to “Controls” to access all available settings. Here are some key examples:
      • Max Results: Number of results to return
      • Search Depth: “basic” or “advanced”
      • Note: Additional parameters are available in the Controls panel

  2. Tavily Extract API: Extract content from web pages

    • Located under Tools > Tavily Extract API
    • Configuration Options: Select the component and go to “Controls” to access all available settings. Here are some key examples:
      • Extract Depth: “basic” or “advanced”
      • Note: Additional parameters are available in the Controls panel

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Step 3: Configure Your Tavily API Key

To use Tavily components, you need to enter your Tavily API key under “Tavily API Key”

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Example Workflows

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Basic Search Workflow

  1. Add a Tavily Search component to your flow
  2. Connect it to a prompt template
  3. Configure the search parameters
  4. Add an LLM component to process the results
  5. Connect to an output component

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Content Extraction Workflow

  1. Add a Tavily Extract component
  2. Connect it to a URL input
  3. Configure extraction parameters
  4. Add processing components as needed
  5. Connect to your desired output

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Example Use Cases

  1. Research Assistant

    • Combine Tavily Search with LLMs for comprehensive research
    • Extract and summarize information from multiple sources

  2. Content Aggregation

    • Use Tavily Extract to gather content from specific websites
    • Process and format the extracted content

  3. Market Intelligence

    • Create workflows for competitive analysis
    • Monitor industry trends and news

  4. Documentation Search

    • Build custom documentation search interfaces
    • Extract and format technical documentation

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Additional Resources