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|  How to Integrate OpenAI with Miro

How to Integrate OpenAI with Miro

January 24, 2025

Seamlessly connect OpenAI with Miro using our step-by-step guide. Enhance collaboration and creativity in your projects with AI-powered insights.

How to Connect OpenAI to Miro: a Simple Guide

 

Integration of OpenAI with Miro

 

  • Before starting, ensure you have access to both OpenAI and Miro APIs. You'll need API keys for both set up in your environment.
  •  

  • Familiarize yourself with the OpenAI API documentation and understand Miro’s API capabilities and limitations.

 

Set Up Environment

 

  • Create a dedicated project folder on your local machine to manage this integration.
  •  

  • Set up a virtual environment to manage dependencies efficiently. Use Python as it's commonly used for OpenAI integrations:

 

python -m venv env
source env/bin/activate # On Windows use `env\Scripts\activate`

 

Install Required Libraries

 

  • Use pip to install the libraries necessary for interacting with OpenAI and Miro APIs:

 

pip install openai
pip install requests

 

Configure API Access

 

  • Create a configuration file, e.g., `.env`, to securely store your API keys for OpenAI and Miro:

 

OPENAI_API_KEY=your_openai_api_key
MIRO_API_KEY=your_miro_api_key

 

Initialize OpenAI Client

 

  • Set up authentication and initialize the OpenAI client in your Python script:

 

import openai
import os
from dotenv import load_dotenv

load_dotenv()

openai.api_key = os.getenv("OPENAI_API_KEY")

 

Create Miro Authentication Function

 

  • Create a function to handle the Miro API authentication and specific board interaction:

 

import requests

def miro_request(endpoint, method='GET', **kwargs):
    headers = {
        'Authorization': f'Bearer {os.getenv("MIRO_API_KEY")}',
        'Content-Type': 'application/json'
    }
    url = f'https://api.miro.com/v1{endpoint}'
    response = requests.request(method, url, headers=headers, **kwargs)
    return response.json()

 

Integrate OpenAI and Miro API Calls

 

  • Implement a function that utilizes OpenAI to generate content and then updates your Miro board:

 

def generate_openai_content(prompt):
    response = openai.Completion.create(
        engine="text-davinci-003",
        prompt=prompt,
        max_tokens=150
    )
    return response.choices[0].text.strip()

def update_miro_board(content, board_id):
    payload = {
        "data": {
            "title": content
        }
    }
    return miro_request(f'/boards/{board_id}/texts', 'POST', json=payload)

 

Execute Integration

 

  • Use the main function to execute the interaction between OpenAI and Miro:

 

def main():
    prompt = "Explain how OpenAI can be integrated with Miro."
    ai_content = generate_openai_content(prompt)
    board_id = 'your_miro_board_id'
    response = update_miro_board(ai_content, board_id)
    print(response)

if __name__ == "__main__":
    main()

 

Test and Debug

 

  • Run the Python script and ensure that the content generated by OpenAI is successfully updated on your Miro board.
  •  

  • If you encounter issues, use logging or print statements to inspect API responses and debug efficiently.

 

Enhance and Secure

 

  • Consider enhancing security by setting up robust error handling and logging practices.
  •  

  • Review and optimize your prompts for more contextual and useful content generation.
  •  

  • Explore advanced features such as webhook integrations or data validation before updating Miro.

 

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How to Use OpenAI with Miro: Usecases

 

Use Case: Collaborative Ideation and Conceptualization

 

  • Setting the Stage: Utilize OpenAI to brainstorm and generate a vast array of creative ideas based on initial input or prompts given by the team. OpenAI can help synthesize diverse perspectives and novel concepts that users might not initially consider.
  •  

  • Visual Representation: Take these ideas into Miro, a collaborative online whiteboard platform, where thoughts and concept sketches can be visually organized. Here, users can map out connections and create mind maps that represent the generated ideas.
  •  

  • Feedback Loop: As ideas develop, return to OpenAI to refine concepts by asking more targeted questions or seeking further elaboration. OpenAI can help expand on core ideas or suggest improvements.
  •  

  • Team Collaboration: Add comments, sticky notes, and additional ideas in Miro while continuously linking back the insights and elaborations from OpenAI. This ensures both textual and visual collaboration among team members, leveraging inputs from diverse teams.
  •  

  • Finalizing Ideas: Use Miro to finalize and present ideas in a structured format, allowing for clear communication among stakeholders. Refinements from OpenAI can be documented alongside, supporting argumentations or providing background research.

 


# Example of using OpenAI API to generate ideas
openai.ChatCompletion.create(
  model="text-davinci-002",
  prompt="Generate innovative ideas for a new augmented reality app."
)

 

Use Case: Interactive Workshop Planning and Execution

 

  • Initial Planning: Use OpenAI to generate an agenda for the workshop, drawing from best practices and innovative techniques suitable for the topic. By providing OpenAI with the workshop goals and audience profile, it can suggest dynamic activities and relevant discussion points.
  •  

  • Content Creation: Leverage OpenAI to create engaging content, such as introductory notes, discussion examples, or even potential issues and solutions for debate. This ensures workshop facilitators are well-prepared with a wealth of material at their disposal.
  •  

  • Structure Visualization: Import the content into Miro, utilizing its templates and tools to visually craft a structured and interactive workshop flow. Miro's features like sticky notes, flowcharts, and mind maps can help in organizing the plan aesthetically.
  •  

  • Interactive Engagement: During the workshop, use Miro for real-time collaboration where participants can add their inputs via comments, sketches, and newly formed ideas. OpenAI can assist by providing instantaneous, AI-driven insights or generating on-the-spot content as needed.
  •  

  • Post-Workshop Analysis: At the end of the workshop, gather all the materials and feedback from Miro. Use OpenAI to analyze this information and generate a comprehensive report. This report could include key takeaways, suggested improvements, and follow-up actions.

 


# Example of using OpenAI API to prep workshop content
openai.ChatCompletion.create(
  model="text-davinci-002",
  prompt="Create an outline for a workshop on sustainable business strategies."
)

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Troubleshooting OpenAI and Miro Integration

How do I connect OpenAI to Miro for automatic diagram creation?

 

Integrate OpenAI with Miro

 

  • Create an OpenAI API key from the OpenAI website to start and note it down for later use.
  •  

  • Use your Miro account to create a developer team and generate a Miro Developer App. You'll get a Client ID and Client Secret for OAuth 2.0 authentication.

 

Set Up Automatic Diagram Creation

 

  • Prepare a server or use a cloud function to host a script connecting both APIs. Ensure it supports secret environment variables for security.
  •  

  • Handle authentication and authorization for the Miro and OpenAI APIs using their respective credentials.
  •  

import openai
import requests

openai.api_key = 'YOUR_OPENAI_API_KEY'

def create_diagram(prompt):
  response = openai.Completion.create(engine="text-davinci-002", prompt=prompt, max_tokens=50)
  diagram_data = response.choices[0].text
  # Use Miro API to create a diagram
  headers = {"Authorization": "Bearer YOUR_MIRO_ACCESS_TOKEN"}
  requests.post("https://api.miro.com/v1/boards/BOARD_ID/widgets", headers=headers, json={"type": "card", "text": diagram_data})

create_diagram("Generate flowchart for project")

 

Deploy and Test

 

  • Test thoroughly to ensure that the integration works as expected. Make necessary adjustments according to API responses.
  •  

  • Deploy your solution and monitor for any issues or required updates based on API changes.

 

Why isn't my OpenAI-generated content updating on Miro boards?

 

Ensure Correct Integration

 

  • Check if the Miro app is authorized correctly to interact with OpenAI's API by verifying the API keys and permissions. Double-check that credentials are up-to-date and correctly configured.
  •  

  • Ensure that the content update script is running without errors. Use logging to identify any potential issues during execution that could prevent content updates.

 

Check Miro Board Settings

 

  • Verify that the board's permissions allow content updates. Restrictions could prevent new data from being displayed properly.
  •  

  • Look for refresh or update settings within Miro, as auto-update features may need to be enabled for real-time content reflection.

 

Debugging Code Examples

 


// Script example to fetch data from OpenAI and update a Miro board
fetch('your_openai_api_endpoint', {
  method: 'POST',
  headers: {
    'Authorization': `Bearer YOUR_OPENAI_API_KEY`,
    'Content-Type': 'application/json'
  },
  body: JSON.stringify({ prompt: 'Your prompt here' })
})
.then(response => response.json())
.then(data => {
  // Code to update Miro board with new content
  updateMiroBoard(data);
})
.catch(error => console.error('Error:', error));

 

Can OpenAI integrate with Miro to summarize meetings automatically?

 

Integration Feasibility

 

  • OpenAI's API can potentially integrate with Miro via custom applications to automate meeting summaries.
  •  

  • This involves using Miro's Web SDK to access board content and OpenAI's API for summarization tasks.

 

Implementation Steps

 

  • **Access Miro's API.** Use the following headers to authenticate your request:
    headers: {
      'Authorization': 'Bearer YOUR_MIRO_ACCESS_TOKEN',
    }
    
  •  

  • **Fetch Meeting Content.** Retrieve meetings or associated notes from Miro's boards.
  •  

  • **Utilize OpenAI's API.** Insert content into OpenAI's GPT model for summarization:
    import openai
    
    response = openai.Completion.create(
      engine="gpt-3.5-turbo",
      prompt="Summarize this meeting...",
      max_tokens=150
    )
    
  •  

  • **Integrate Results into Miro.** Use Miro's API to post summaries back to the board.

 

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