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Gemini Development Guide

This guide provides context for using Gemini to assist with development in the conversational-insights-devkit-alpha repository.

Project Overview

The Conversational Insights DevKit is a Python-based toolkit for extracting insights from conversational data from various sources (e.g., AWS, Genesys). It provides tools for audio processing, content generation, and data formatting.

Development Setup

The project uses Python with a virtual environment.

  1. Create and activate a virtual environment:

    python3 -m venv .venv
source .venv/bin/activate

  2. Install dependencies:

    pip install -r requirements.txt

Running Quality Checks

This project uses pylint for linting, mypy for type checking, and pytest for testing.

  • Run tests:

    pytest

  • Run linter:

    pylint src tests

  • Run type checker:

    mypy src

Project Structure

  • src/cxidk/: The main source code for the devkit.
    • core/: Base classes and core abstractions.
    • workflow/: Components for building conversation processing workflows (audio, formatting, etc.).
    • wrapper/: Wrappers for external services (Vertex AI, Google Sheets, etc.).
  • tests/: Unit and integration tests.
    • unit/: Tests for individual components.
    • integration/: Tests for component interactions and workflows.
  • examples/: Example usage of the devkit.
  • pyproject.toml: Project metadata and dependencies.
  • .github/workflows/: CI/CD pipelines for linting, testing, and type checking.