Building a Podcast Transcript Summarizer with Replit, Spotify API, and Google Gemini

Replit Project Link: https://replit.com/@prire-95/SpotifyPodcastSummarizer

In today's fast-paced world, we often don't have time to listen to entire podcast episodes. What if there was a tool that could summarize podcast content, allowing you to get the key points in just a few minutes? That's exactly what I built using Replit: a Podcast Transcript Summarizer that leverages the Spotify API to find podcasts and Google's Gemini AI to create concise summaries.

In this blog post, I'll walk you through how I used Replit to build this application from scratch and then deployed it to GitHub.

What We're Building

The Podcast Transcript Summarizer is a web application that allows users to:

1. Search for podcasts using keywords or specific podcast names

2. Fetch episodes and their transcripts from Spotify

3. Generate AI-powered summaries using Google's Gemini

4. View both the summary and full transcript in a clean interface

All of this is packaged in a user-friendly interface built with Streamlit.

Why Replit?

Replit provided the perfect environment for this project because:

• It offers a complete development environment without any local setup

• It integrates seamlessly with external APIs like Spotify and Google Gemini

• It provides secure secret management for API keys

• It has built-in workflows for running Streamlit applications

• It makes deployment and sharing incredibly simple

Step 1: Setting Up the Project on Replit

Getting started was as simple as creating a new Replit project and selecting Python as the primary language. Replit automatically set up a Python environment with all the necessary tools.

The first prompt I used to kick off the project was:

python langgrpah streamlit and gemini api to get transcripts from spotify api and then summarize them using llm and display that summary in website. So user enters query -> search that in spotify db using api, then get transcript, then summarize that transcript which is the final output displayed to user.

This clear description of what I wanted to build helped set the project direction from the beginning.

Step 2: Installing Dependencies

Replit made it incredibly easy to install the necessary packages. I needed:

• streamlit for the web interface

• spotipy for interacting with the Spotify API

• google-generativeai for accessing Google's Gemini AI

All dependencies were automatically managed in the pyproject.toml file.

Step 3: Setting Up API Keys

One of the most convenient features of Replit is its secure management of environment variables. I needed three important API keys:

• SPOTIFY_CLIENT_ID

• SPOTIFY_CLIENT_SECRET

• GEMINI_API_KEY

Adding these to Replit was straightforward using the Secrets tab. This kept my API keys secure while still making them accessible to my application.

Step 4: Building the Core Components

Spotify API Integration

First, I created a module to handle interaction with the Spotify API:

• Search for podcasts by keywords

• Filter searches by podcast name only

• Retrieve episode details

• Fetch episode transcripts when available

Gemini AI Integration

Next, I integrated Google's Gemini API to:

• Process podcast transcripts

• Generate concise, structured summaries

• Format the output for easy reading

Streamlit User Interface

The final piece was building a clean, intuitive interface with Streamlit that included:

• A search form with filtering options

• A direct episode lookup feature for Spotify URLs

• Tabs for viewing summaries and full transcripts

• Responsive layout with proper image handling

Step 5: Refining the Application

After building the basic functionality, I made several improvements:

1. Added a "Podcast Name Only" search filter for more precise results

2. Implemented direct episode lookup using Spotify URLs

3. Enhanced the display of podcast results with better image handling

4. Improved error handling for cases where transcripts aren't available

5. Optimized the Gemini prompt for better summary quality

Step 6: Version Control with Git and GitHub

Once the application was complete, I pushed it to GitHub for version control and sharing. While Replit has some limitations with direct Git commands, I was able to set up Git and push my repository to GitHub using the following commands:

git init

git add .

git commit -m "Add Podcast Transcript Summarizer using Spotify and Gemini APIs"

git remote add origin "Replace with Github Project Remote URL"

git push -u origin main

This made my project accessible outside of Replit and allowed for easier collaboration and version tracking.

Challenges and Solutions

Challenge 1: Spotify Transcript Access

The Spotify API doesn't always provide full transcripts for all podcasts. To address this, I implemented a fallback mechanism that uses episode descriptions when transcripts aren't available.

Challenge 2: Git Integration with Replit

Initially, I wanted to use the git integration in replit, but ran into errors for adding repo url. I resolved this by defaulting to the Git Bash by extracting project folder and then pushing using git commands to repository.

Challenge 3: UI Layout and Responsiveness

Getting the UI just right took some iteration, particularly with image sizing and result formatting. Streamlit's container and column features helped create a clean, responsive layout.

The Final Result

The finished Podcast Transcript Summarizer provides a seamless experience:

1. Users can search for podcasts or input direct Spotify URLs

2. Search results display with podcast images and relevant metadata

3. With a single click, users can fetch transcripts and generate summaries

4. The summary tab presents key points in a structured format

5. The full transcript is available for those who want more detail

Conclusion

Building this Podcast Transcript Summarizer with Replit demonstrated how quickly modern development tools allow us to create powerful applications. By combining Replit's development environment with Spotify's content API and Google's AI capabilities, I was able to build a useful tool that solves a real problem.

The entire project is open source and available on GitHub at SpotifyPodcastSummarizer. Feel free to check it out, contribute, or use it as inspiration for your own projects!

Next Steps

Some features I'm considering for future development:

1. Support for more podcast platforms beyond Spotify

2. Customizable summary length and style options

3. User accounts to save favorite episodes and summaries

4. Enhanced topic extraction and tagging

Resources

• GitHub Repository

• Spotify Developer Portal

• Google Gemini AI

• Streamlit Documentation

• Replit

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Have you built something interesting with Replit? I'd love to hear about your projects in the comments below!