Audio to Notion

This project automates the transcription of audio files into text, analyzes the content using OpenAI's API, and then creates a new page in a Notion database with the analyzed data. The system leverages AWS Lambda for processing and uses S3 for audio file storage.

Architecture Overview

• Whisper: Transcribes user-provided audio (.MP3) files to text.
• OpenAI API: Processes the transcript to generate structured JSON data.
• Notion API: Uses the JSON to create a new page in a Notion database.
• AWS Lambda: Hosts the processing logic.
• AWS S3 Bucket: Stores the audio files and triggers the Lambda function.
• Terraform: Manages the AWS infrastructure setup.

Prerequisites

• AWS Account
• Notion Account
• OpenAI API Key

Environment Variables

Before deploying the project, ensure you have set up the following environment variables:

• OPEN_AI_KEY: Your OpenAI API key.
• NOTION_TOKEN: Integration token from Notion.
• NOTION_PAGE_ID: ID of the Notion database where pages will be added.
• AWS_REGION: Your AWS region.

Project Structure

• /shared: Contains shared Golang code for the Lambda function.
• /lambda: Main entry point for the Lambda function.
• /infra: Terraform scripts for setting up AWS infrastructure including Lambda functions and S3 buckets.

Setup Instructions

Step 1: Prepare your AWS environment

1. Navigate to the /infra directory.
2. Use Terraform to deploy the infrastructure:

   terraform init
   terraform apply

Confirm the setup when prompted.

Step 2: Configure your Lambda function

Navigate to the /lambda folder. Ensure the Lambda function is set up with the necessary environment variables.

Step 3: Upload an audio file

Upload an .MP3 audio file to the designated S3 bucket. This will trigger the Lambda function to start the transcription and data processing workflow.

Step 4: Check Notion

Once the Lambda function has processed the audio file, check your Notion database for a new page with the analyzed data.