https://github.com/hitthecodelabs/rasatalks
A detailed walkthrough for setting up and developing a Rasa chatbot
https://github.com/hitthecodelabs/rasatalks
action actions api apis python rasa rasa-core rasa-nlu
Last synced: 10 months ago
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A detailed walkthrough for setting up and developing a Rasa chatbot
- Host: GitHub
- URL: https://github.com/hitthecodelabs/rasatalks
- Owner: hitthecodelabs
- License: mit
- Created: 2024-02-15T03:38:58.000Z (almost 2 years ago)
- Default Branch: main
- Last Pushed: 2024-03-05T21:13:18.000Z (almost 2 years ago)
- Last Synced: 2025-02-04T11:43:54.004Z (11 months ago)
- Topics: action, actions, api, apis, python, rasa, rasa-core, rasa-nlu
- Language: HTML
- Homepage:
- Size: 22.9 MB
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# Rasa Chatbot Project Guide
This guide provides a detailed walkthrough for setting up and developing a Rasa chatbot project using Visual Studio Code (VSCode).
## Step 1: Install Visual Studio Code
- Download and install VSCode from the official website: https://code.visualstudio.com/
## Step 2: Install Python
- Ensure Python 3.10 or newer is installed on your system. Download it from https://www.python.org/.
## Step 3: Install Rasa
1. Open VSCode and start a new terminal session (Terminal > New Terminal).
2. Create a project directory for your Rasa project files.
3. Navigate to your project directory in the terminal using the `cd` command.
4. Create a Python virtual environment for your project:
```bash
python3 -m venv ./rasa_venv
```
On Windows, you might use `python` instead of `python3`.
5. Activate the virtual environment:
- On Windows:
```
.\rasa_venv\Scripts\activate
```
- On macOS/Linux:
```
source rasa_venv/bin/activate
```
6. Install Rasa within the virtual environment:
```bash
pip install rasa==3.6.16
```
## Step 4: Initialize Your Rasa Project
1. In the VSCode terminal, ensure you're in your project directory and your virtual environment is activated.
2. Run the following command to create a new Rasa project:
```bash
rasa init
```
3. Follow the prompts to create the initial project structure and train a simple bot.
## Step 5: Explore and Modify Your Project
- Open the project directory in VSCode (File > Open Folder) to start editing your files.
- Modify the generated files to develop your chatbot's training data and logic.
## Step 6: Train Your Rasa Model
- Retrain your model by running:
```bash
rasa train
```
## Step 7: Test Your Bot in the Shell
- Test your chatbot by running:
```bash
rasa shell
```
## Step 8: Develop Custom Actions (Optional)
- Edit `actions/actions.py` for custom actions.
- Start the action server with `rasa run actions`.
## Step 9: Use Version Control
- Initialize a Git repository and commit your changes:
```bash
git init
git add .
git commit -m "Initial commit"
```
## Step 10: Continuous Learning and Improvement
- Continue developing your bot by adding more training data, refining the domain, and adding custom actions as needed.
## Additional Tips
- Consider installing the Python extension for VSCode.
- Refer to the Rasa Documentation for more information: https://rasa.com/docs/