FastAPI and Docker

Recording the progress of deploying the NLP project by fastAPI, docker and streamlit.

FastAPI

Create an api for others to use to generate scripts by sending a prompt.

1. Create a new project of app.
2. Write codes needed to handle the inputs by users.
3. Start the api by uvicorn <filename>:app --reload. (Run this under the dir of app.py)

   from fastapi import FastAPI
   
   app = FastAPI()
   
   # define the input type class 
   class InputClass {
       prompt: str
   }
   
   @app.post('/generate')
   fun generate_script(input: InputClass):
       # deal with the input

Docker

Use docker to pack the fastAPI and project.

1. Derive the requirement.txt file.
2. Create the dockerfile.
3. Set up the docker mirror.
4. Run the docker container (local).

   # 1.derive requirement.txt
   pip freeze > requirements.txt
   
   # 2.create dockerfile
   # 使用官方 Python 镜像
   FROM python:3.9-slim
   
   # 设置工作目录
   WORKDIR /app
   
   # 拷贝依赖和代码
   COPY requirements.txt .
   RUN pip install --no-cache-dir -r requirements.txt
   
   COPY . .
   
   # 启动 FastAPI 服务
   CMD ["uvicorn", "app:app", "--host", "0.0.0.0", "--port", "8000"]
   
   # 3.setup docker mirror
   docker build -t fastapi-llama-app .
   
   # 4.run container locally
   docker run -p 8000:8000 fastapi-llama-app