Dockerize CAAI_AI (As per Request from Maran)

 This supplements to CAAI_AI repository

Dockerfile you can use to dockerize your FastAPI backend (main.py). I’ll assume your project structure looks like this:

project-root/
│── main.py
│── requirements.txt
│── Dockerfile

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✅ Dockerfile.txt

# Use an official lightweight Python image
FROM python:3.11-slim

# Set environment variables
ENV PYTHONUNBUFFERED=1 \
    PYTHONDONTWRITEBYTECODE=1

# Set work directory
WORKDIR /app

# Install system dependencies
RUN apt-get update && apt-get install -y --no-install-recommends \
    build-essential curl git && \
    rm -rf /var/lib/apt/lists/*

# Copy requirements first for efficient caching
COPY requirements.txt .

# Install Python dependencies
RUN pip install --no-cache-dir -r requirements.txt

# Copy the entire project
COPY . .

# Expose FastAPI port
EXPOSE 8000

# Run the FastAPI app with uvicorn
CMD ["uvicorn", "main:app", "--host", "0.0.0.0", "--port", "8000"]

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✅ requirements.txt

If you don’t already have one, here’s what your requirements.txt should contain based on your code:

fastapi
uvicorn[standard]
pydantic
langchain
langchain-community
langgraph

(If you know extra versions you want pinned, you can add == versions.)

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✅ Build & Run Docker Container

From your project root:

# Build the image
docker build -t company-recommender-backend .

# Run the container
docker run -d -p 8000:8000 company-recommender-backend

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⚡ Your FastAPI backend will now be available at:

http://localhost:8000

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Response :