- Added requirements file

- Modified server.py a bit

python_server/Dockerfile

@@ -1,18 +1,37 @@
-# 1. Start from a base image with Python installed
-FROM python:3.13.7
+# Build:
+# docker build -t myapp .
 
-# 2. Set the working directory in the container
+# Run:
+# docker run -p 8000:8000 myapp
+
+# Use Python 3.13.7 base image
+FROM python:3.13.7-slim
+
+# Set working directory
 WORKDIR /app
 
-# 3. Copy requirements file and install dependencies
-COPY requirements.txt .
-RUN pip install --no-cache-dir -r requirements.txt
+# Install dependencies for opentelemetry + ngrok
+RUN pip install --no-cache-dir \
+    opentelemetry-distro \
+    opentelemetry-instrumentation \
+    opentelemetry-exporter-otlp \
+    pyngrok
 
-# 4. Copy the rest of your app’s code
+# Copy project files
 COPY . .
 
-# 5. Expose port (optional, for web apps)
+# Install Python dependencies from requirements.txt
+RUN pip install --no-cache-dir -r requirements.txt
+
+# Download model at build time
+RUN python downloadModel.py
+
+# Expose FastAPI/Flask/HTTP server port
 EXPOSE 8000
 
-# 6. Default command to run the app
-CMD ["uvicorn", "main:app", "--host", "0.0.0.0", "--port", "8000"]
+# Copy entrypoint script
+COPY entrypoint.sh /entrypoint.sh
+RUN chmod +x /entrypoint.sh
+
+# Default command: run script
+CMD ["/entrypoint.sh"]

python_server/entrypoint.sh

@@ -0,0 +1,9 @@
+#!/bin/sh
+
+# This file exists to use Ngrok inside Dockerfile
+
+# Start server with OpenTelemetry in background
+opentelemetry-instrument python server.py &
+
+# Run ngrok to expose port 8000
+ngrok http --url=pegasus-working-bison.ngrok-free.app 8000

python_server/requirements.txt

@@ -0,0 +1,8 @@
+transformers
+torch
+# With CUDA support: pip install torch torchvision torchaudio
+pillow
+qdrant_client
+fastapi
+uvicorn
+python-multipart

python_server/server.py

@@ -9,6 +9,10 @@ import logging
 from fastapi import FastAPI, Request
 import uvicorn
 from fastapi.middleware.cors import CORSMiddleware
+import uvicorn
+import multiprocessing
+from fastapi import FastAPI, File, UploadFile
+from fastapi.responses import JSONResponse
 
 #from pyngrok import ngrok, conf
 
@@ -125,9 +129,6 @@ async def predict(request: Request):
     except Exception as e:
         logging.error(f"Error in /predict: {e}")
         return {"status": False, "error": str(e)}
-    
-from fastapi import FastAPI, File, UploadFile
-from fastapi.responses import JSONResponse
 
 @app.post("/predictfile")
 async def predict_file(file: UploadFile = File(...)):
@@ -148,9 +149,7 @@ async def predict_file(file: UploadFile = File(...)):
         return JSONResponse(content={"status": False, "error": str(e)})
 
 
-#from pyngrok import ngrokS
-import uvicorn
-import multiprocessing
+
 
 def run_server():
     uvicorn.run("server:app", host="0.0.0.0", port=8000)
@@ -164,6 +163,5 @@ if __name__ == "__main__":
     #p = multiprocessing.Process(target=run_server)
     #p.start()
     #p.join()
-    import uvicorn
     uvicorn.run("server:app", host="0.0.0.0", port=8000)