Memopin - AI-Enhanced Memory Recall Tool (Backend)

Project Description

Memopin is an AI-enhanced memory recall tool designed to address the challenges of fragmented memories and forgetfulness in the digital age. People often struggle to recall meaningful moments as photos, conversations, and videos are scattered across various platforms, making retrieval difficult. For individuals with Alzheimer's and other memory impairments, this struggle becomes even more pronounced, leading to confusion, disorientation, and emotional distress.

Memopin solves these challenges by providing a unified platform to store and retrieve key moments. Using advanced AI technologies like Retrieval-Augmented Generation (RAG), Large Language Models (LLMs), and Natural Language Processing (NLP), it helps users retrieve detailed, context-rich memories from multimedia content like audio, video, and photos. Memopin's video analysis adds an extra layer of depth to memory recall, ensuring a comprehensive understanding of multimedia content.

The solution organizes memories into a searchable, context-aware database, making it easy to reflect on past experiences and improve cognitive health, emotional well-being, and memory management.

Tech Stack

• React: Frontend framework for building the user interface and managing user interactions.
• ReactDOM: Renders the React components in the browser.
• NLP (Natural Language Processing): Analyzes speech and text within recorded content to enhance memory context and improve relevance.
• Retrieval-Augmented Generation (RAG) AI: Combines memory storage and querying to generate contextually accurate responses to user queries.
• Large Language Models (LLMs): Understands and contextualizes user queries, offering detailed and relevant memories reflecting personal experiences.
• Vector Databases: Efficiently stores and retrieves multimedia data, ensuring structured organization for quick access.

Setup Instructions

Follow these steps to set up the ai-backend project locally:

1. Ensure to go to the folder:

   • First, ensure that the ai-app project is set up . And go to the same folder where we cloned ai-app.

2. Open a New Terminal for ai-backend:

   • Open another terminal or command prompt for the ai-backend setup and follow these steps.

3. Initialize Git:

   • Inside your terminal, initialize a Git repository:

     git init

4. Clone the AI Backend Repository:

   • Clone the ai-backend repository to your local machine using the URL:

     git clone <this repository url>

5. Navigate to the ai-backend Directory:

   • Change to the ai-backend directory:

     cd ai-backend

6. Create a Virtual Environment:

   • Create a new virtual environment using conda (Python 3.8):

     conda create -n venv python=3.8

7. Activate the Virtual Environment:

   • Activate the newly created virtual environment:

     conda activate venv

8. Install Dependencies:

   • Install the required Python dependencies from the requirements.txt file:

     pip install -r requirements.txt

9. Create a .env File:

   • Create a .env file in the root directory of ai-backend with the following keys:

     LANGCHAIN_API_KEY=<your langchain api key> 
     GROQ_API_KEY=<your groq api key> 
     LANGCHAIN_TRACING_V2="true"
     

10. Run the Application:

    • Start the AI backend service by running:

      python app.py

11. Open the Frontend Application:

    • Go to the ai-app directory and run it using:

      npm run dev

    • Open your browser and go to http://localhost:5173/. You should now be able to process audio files either for storing or retrieving memories.

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Additional Repositories

Once you have the ai-backend set up, make sure you have ai-app set up. There are two repositories you should clone and set up:

1. AI Frontend Repository

The user interface of the Memopin project, where users can interact with the system.

• Repository URL: ai-app

2. Node Backend Repository

The Node Backend handles the MongoDB-related functionality, including user management, authentication, and storing login/signup related data.

• Repository URL: node-backend

After running node-backend run python app.py in cd ai-backend