Skip to content

Voice Chatbot with Flask#

This example demonstrates a simple chatbot using Flask and Quivr, where users can upload a .txt file and ask questions based on its content. It supports speech-to-text and text-to-speech capabilities for a seamless interactive experience.

Prerequisites#

  • Python: Version 3.8 or higher.
  • OpenAI API Key: Ensure you have a valid OpenAI API key.

Installation#

  1. Clone the repository and navigate to the project directory: 

    git clone https://github.com/QuivrHQ/quivr
cd examples/quivr-whisper

  2. Set the OpenAI API key as an environment variable: 

    export OPENAI_API_KEY='<your-key-here>'

  3. Install the required dependencies: 

    pip install -r requirements.lock

Running the Application#

  1. Start the Flask server: 

    python app.py

  2. Open your web browser and navigate to the URL displayed in the terminal (default: http://localhost:5000).

Using the Chatbot#

File Upload#

  1. On the interface, upload a .txt file.
  2. Ensure the file format is supported and its size is manageable.
  3. The file will be processed, and a "brain" instance will be created.

Asking Questions#

  1. Use the microphone to record your question (audio upload).
  2. The chatbot will process your question and respond with an audio answer.

How It Works#

File Upload#

  • Users upload a .txt file.
  • The file is saved to the uploads directory and used to create a "brain" using Quivr.

Session Management#

  • Each session is associated with a unique ID, allowing the system to cache the user's "brain."

Speech-to-Text#

  • User audio files are processed with OpenAI's Whisper model to generate transcripts.

Question Answering#

  • The "brain" processes the transcribed text, retrieves relevant answers, and generates a response.

Text-to-Speech#

  • The answer is converted to audio using OpenAI's text-to-speech model and returned to the user.

Workflow#

  1. Upload File:

    • The user uploads a .txt file.
    • A "brain" is created and cached for the session.

  2. Ask Questions:

    • The user uploads an audio file containing a question.
    • The question is transcribed, processed, and answered using the "brain."

  3. Answer Delivery:

    • The answer is converted to audio and returned to the user as a Base64-encoded string.

Features#

  1. File Upload and Processing:

    • Creates a context-aware "brain" from the uploaded text file.

  2. Audio-based Interaction:

    • Supports speech-to-text for input and text-to-speech for responses.

  3. Session Management:

    • Retains user context throughout the interaction.

  4. Integration with OpenAI:

    • Uses OpenAI models for transcription, answer generation, and audio synthesis.

Enjoy interacting with your text files through an intuitive voice-based interface!