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| title: Solution_2 | |
| app_file: app.py | |
| sdk: gradio | |
| sdk_version: 4.44.1 | |
| ## Prepare Development Environment | |
| We will be using `Poetry`, a versatile tool for Python projects that simplifying dependency management and packaging. It automates the process of declaring, installing, and updating the libraries your project relies on. By using a lockfile, `Poetry` guarantees consistent and reproducible builds, ensuring that your project's dependencies are always installed in the specified versions. Additionally, `Poetry` provides convenient features for building your project into distributable formats, making it easier to share and deploy your work. | |
| 1. Install [Python](https://www.python.org/downloads/) (both 3.10.12 and 3.12.6 were used in testing to offer a wide range of diversity.) | |
| 1. Install [Poetry](https://python-poetry.org/docs/#installing-with-the-official-installer).The flexibility of poetry makes it best of breed as it plays well with `pip` and `conda` alike. | |
| 1. Install [ffmpeg](https://www.ffmpeg.org/download.html) | |
| - Windows | |
| To simplify setup for windows users, `ffmpeg.exe` and `ffprode.exe` have been included in this repo under `libs` directory. For other operating systems, please reference below. | |
| - Mac | |
| - **For MacOS Monterey v12 and below:** We will be using MacPorts. Homebrew is no longer supported for these MacOSx versions. | |
| - Install Apple's CLI Developer Tools (If required): `xcode-select --install` | |
| - Download and install [**MacPorts**](https://www.macports.org/install.php) for the version of your Mac operating system. | |
| - **For Mac OSX Ventura and above:** We will be using `brew` but first we must make sure that it's up-to-date. | |
| 1. First update `brew`. | |
| ```bash | |
| brew update | |
| ``` | |
| > **NOTE:** if you get an error like `fatal: couldn't find remote ref refs/heads/master` when trying to run `brew update`, the possible culprit is `dart-lang` changing it's default branch from `master` to `main`. To resolve this run the following set of commands: | |
| ```bash | |
| brew tap --repair && brew cleanup && brew update-reset | |
| ``` | |
| Now you should be able to run `brew update`. | |
| 2. Next, we can upgrade the outdated `brew` formulae. | |
| ```bash | |
| brew upgrade | |
| ``` | |
| > **NOTE:** You might need to run this a few times to get all outdated formulae successfully updated. Depending on how outdated packages are, this may take some time to complete. Please be patient. This is a good time to grab a `brew` :) | |
| 1. We can now install the latest/stable version of `ffmpeg` in Homebrew. | |
| ```bash | |
| brew install ffmpeg | |
| ``` | |
| - Linux | |
| Install using the following command: | |
| ```bash | |
| apt install libasound2-dev portaudio19-dev libportaudio2 libportaudiocpp0 ffmpeg | |
| ``` | |
| 3. Create a Virtual Environment, and install libraries needed, using a Linux shell or **git bash** in Windows | |
| - Windows | |
| ```bash | |
| python -m venv .venv | |
| .venv/Scripts/activate | |
| ``` | |
| - Linux/Mac | |
| ``` bash | |
| python3 -m venv .venv | |
| source ./.venv/bin/activate | |
| ``` | |
| - Mac Only | |
| **Prerequisites** | |
| One of the requirements is [PyAudio](https://pypi.org/project/PyAudio/). According to their instructions we need to use Homebrew to install the prerequisite `portaudio` library before we can install `PyAudio`. | |
| ```bash | |
| brew install portaudio | |
| ``` | |
| 1. Install the code, from the root directory that contains `pyproject.toml` file, using `poetry`. | |
| ```bash | |
| poetry lock | |
| poetry install | |
| ``` | |
| 4. Install `playwright`, an open-source tool for auomating web testing in python. We'll use it to get some data for our LLM. | |
| ```bash | |
| playwright install | |
| ``` | |
| 5. Test Environment | |
| Run the command below to make sure the virtual environment is activated. | |
| ``` bash | |
| python -V | |
| ``` | |
| Create an OpenAI Account and Obtain a Key | |
| 1. Follow the instructions [here](https://platform.openai.com/docs/quickstart) to create your key. | |
| 2. Make a copy of [.env_template](.env_template) and rename it to `.env`. Then add your key in the `.env` file as shown: | |
| ```bash | |
| OPENAI_API_KEY="<YOUR_KEY_GOES_HERE>" | |
| ``` | |
| ## Project Directory Overview | |
| The project is structured in a modularized manner, focusing on building and running chatbots with voice capabilities. It has a good separation of concerns with well-defined directories for different functionalities. Such as `bots`, `data_utils`, and `models`, promoting code reusability and maintainability. It offers various voice capabilities, including text-to-speech, speech-to-text, and voice-based interactions, making it suitable for creating interactive chatbot applications. | |
| #### **Key Directories:** | |
| * **app:** Contains the main application files: | |
| * `chatbot_gradio_runner.ipynb`: Jupyter notebook for running the chatbot interactively. | |
| * `chatbot_gradio_runner.py`: Python script for running the chatbot with Gradio for a web interface. | |
| * **data:** Stores various types of data for chatbots. This is primarily used for LLM context for different bots: | |
| * `travel_bot_context.txt`: This is the context we'll use for the chat assistant today. | |
| * Other files with specific chatbot contexts (financial, call center, etc.). | |
| * CSV and JSON files formats to allow flexibility. | |
| * **genai_voice:** Core project code: | |
| * **bots:** Code specific to implementing chatbots (`chatbot.py`). | |
| * **config:** Configuration files (`defaults.py`). | |
| * **data_utils:** Utilities for data handling and gathering data from websites (e.g., `extract_web_data.py`). | |
| * **defintions:** Defines response formats and prompts for chatbots. | |
| * **logger:** Custom utility for logging information. | |
| * **models:** Code for managing and interacting with language models (`open_ai.py`). | |
| * **moderation:** Code for handling and filtering chatbot responses. | |
| * **processing:** Functions for processing audio data (`audio.py`). | |
| * **libs:** External libraries used by the project (ffmpeg binaries for Windows only). | |
| * **poetry.lock** and **pyproject.toml**: Poetry-related files for dependency management. | |
| ## Launch Notebook | |
| 1. We need to be able to point Jupyter notebook to our virtual environment that has the right packages and libraries. | |
| ```bash | |
| ipython kernel install --user --name=venv | |
| ``` | |
| 1. Run the command below from the virtual environment to launch the [notebook](app/chatbot_gradio_runner.ipynb) in a browser. Once ran, select the `venv` kernel and continue executing the cells. | |
|  | |
| ``` bash | |
| jupyter notebook app/chatbot_gradio_runner.ipynb | |
| ``` | |
| 2. You can also run the same chatbot directly from a python script using `poetry`. | |
| ```bash | |
| poetry run RunChatBotScript | |
| ``` | |
| ## Troubleshooting | |
| 1. Try and use a headset microphone | |
| 2. Record in a quiet room | |
| 3. Make sure that you have granted microphone permissions | |
| 4. Ensure the required audio libraries are installed | |