I was using Flask few months ago, but when I discover FASTAPI my life change
The official documentation :
https://fastapi.tiangolo.com/tutorial/
To create a very easy and quick API on Python.
Select your python version, interpreter, and packge isntall pip or pip3
- Create folder
- Create git init
- Create via pip3 virtual environment :
https://realpython.com/python-virtual-environments-a-primer/
# Python 3
$ python3 -m venv env4. Install FastAPI lib and uviocorn
check that whole packe are installed on env/lib/bin
And run the code.
That’s all folks!
- Install in your PC
Take care with the command in my mac I am usign pip3 and python3
pip3 install flask
pip3 install nltk
pip3 install pandas
pip3 install scikit-learn
To close port : Identify port and kill it
lsof -i :5000
kill 38223
Go to repo and download the…
I will try to deploy a decision tree classifier model in my local machine and use predict via postman, the original post is :
https://towardsdatascience.com/deploy-your-machine-learning-model-as-a-rest-api-4fe96bf8ddcc
- Install joblib
pip install joblib
this import joblib create a new file (model) you can read and make prediction.
The sample if for classifier the flower with load_iris dataset from sklearn
This steps help me to understand What is a chatbot, how works and how to create one.
1 Document to read, help with code
2. Go to the original document
3. First try
4. Let`s Create a DepthLearning Chatbot
5. Using a library Chatterbot
