requirements.txt changed

Dockerfile

@@ -1,20 +1,33 @@
-# Use the official Python image
-FROM python:3.9-slim
+# # Use the official Python image
+# FROM python:3.9-slim
 
-# Set the working directory in the container
-WORKDIR /app
+# # Set the working directory in the container
+# WORKDIR /app
 
-# Copy the dependencies file to the working directory
-COPY requirements.txt .
+# # Copy the dependencies file to the working directory
+# COPY requirements.txt .
 
-# Install any dependencies
-RUN pip install --no-cache-dir -r requirements.txt
+# # Install any dependencies
+# RUN pip install --no-cache-dir -r requirements.txt
 
-# Copy the content of the local src directory to the working directory
-COPY . .
+# # Copy the content of the local src directory to the working directory
+# COPY . .
+
+# # Expose port 8000 to the outside world
+# EXPOSE 8000
+
+# # Command to run the FastAPI application
+# CMD ["uvicorn", "app:app", "--host", "0.0.0.0", "--port", "8000"]
+
+
+FROM python:3.9
 
-# Expose port 8000 to the outside world
-EXPOSE 8000
+WORKDIR /code
+
+COPY ./requirements.txt /code/requirements.txt
+
+RUN pip install --no-cache-dir --upgrade -r /code/requirements.txt
+
+COPY . .
 
-# Command to run the FastAPI application
-CMD ["uvicorn", "app:app", "--host", "0.0.0.0", "--port", "8000"]
+CMD ["uvicorn", "app.main:app", "--host", "0.0.0.0", "--port", "7860"]

app.py

@@ -0,0 +1,67 @@
+# from fastapi import FastAPI, File, UploadFile
+# from transformers import MarianMTModel, MarianTokenizer
+
+# app = FastAPI()
+
+# # Load the translation model and tokenizer
+# model_name = "Helsinki-NLP/opus-mt-de-en"
+# model = MarianMTModel.from_pretrained(model_name)
+# tokenizer = MarianTokenizer.from_pretrained(model_name)
+
+# @app.get("/")
+# def read_root():
+#     return {"message": "Welcome to the German to English Translation API!"}
+
+# @app.post("/translate/")
+# async def translate_text(text: str):
+#     # Perform translation
+#     input_text = f"translate German to English: {text}"
+    
+#     # Tokenize input text
+#     input_ids = tokenizer.encode(input_text, return_tensors="pt")
+    
+#     # Generate translation
+#     with torch.no_grad():
+#         output_ids = model.generate(input_ids)
+    
+#     # Decode the output
+#     translated_text = tokenizer.decode(output_ids[0], skip_special_tokens=True)
+    
+#     return {"translated_text": translated_text}
+
+
+
+from fastapi import FastAPI
+from transformers import MarianMTModel, MarianTokenizer
+import torch
+
+app = FastAPI()
+
+# Load the translation model and tokenizer
+model_name = "Helsinki-NLP/opus-mt-de-en"
+model = MarianMTModel.from_pretrained(model_name)
+tokenizer = MarianTokenizer.from_pretrained(model_name)
+
+@app.get("/")
+def read_root():
+    return {"message": "Welcome to the German to English Translation API!"}
+
+@app.post("/translate/")
+async def translate_text(input_text: dict):
+    # Extract the input text from the JSON payload
+    text = input_text.get("text", "")
+    
+    # Perform translation
+    input_text = f"translate German to English: {text}"
+    
+    # Tokenize input text
+    input_ids = tokenizer.encode(input_text, return_tensors="pt")
+    
+    # Generate translation
+    with torch.no_grad():
+        output_ids = model.generate(input_ids)
+    
+    # Decode the output
+    translated_text = tokenizer.decode(output_ids[0], skip_special_tokens=True)
+    
+    return {"translated_text": translated_text}