Update app.py

app.py

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+# new app
+import logging
+import os
+from fastapi import FastAPI, Request
+from contextlib import asynccontextmanager
+from transformers import pipeline
+import langid
+from huggingface_hub import login
+import socket
+import time
+
+# Global variables
+HF_HUB_TOKEN = os.getenv("HUGGINGFACEHUB_API_TOKEN")
+
+def current_time_gmt():
+    return time.gmtime().tm_hour+2,':',time.gmtime().tm_min,':',time.gmtime().tm_sec
+    
+# Verify Hugging Face token
+if not HF_HUB_TOKEN:
+     raise ValueError("Missing Hugging Face API token. Please set HUGGINGFACEHUB_API_TOKEN in environment variables.")
+login(token=HF_HUB_TOKEN)
+
+
+# Load Hebrew and English text generation models
+lang_generator = pipeline("text-generation", model="gpt2")
+
+
+# Function to detect language
+def detect_language(user_input):
+    try:
+        lang, _ = langid.classify(user_input) # langid.classify returns a tuple (language, confidence)
+        print(f"Detected language: {lang}, ", f"current time: {current_time_gmt()}") 
+        return "hebrew" if lang == "he" else "english" if lang == "en" else "unsupported"
+    except Exception as e:
+        print(f"Language detection error: {e}")
+        return "unsupported"
+
+
+def generate_response(text):
+    language = detect_language(text)
+    print(f"Detected language: {language}, ", f"current time: {current_time_gmt()}")
+
+    if language == "hebrew" or language == "english":
+        # hebrew_generator = pipeline("text-generation", model="onlplab/alephbert-base")
+        output = lang_generator(text, max_length=100, truncation=True)
+        print(f"Model output: {output}, ", f"current time: {current_time_gmt()}")  # Debugging
+        return output[0]["generated_text"]
+    
+    # elif language == "english":
+    #     #english_generator = pipeline("text-generation", model="mistralai/Mistral-Nemo-Instruct-2407", max_new_tokens=128)
+    #     # english_generator = pipeline("text-generation", model="distilgpt2")
+    #     output = english_generator(text, max_length=100, truncation=True)
+    #     print(f"English model output: {output}, ", f"current time: {current_time_gmt()}")  # Debugging
+    #     return output[0]["generated_text"]
+    
+   return "Sorry, I only support Hebrew and English."
+
+
+# FastAPI lifespan event
+@asynccontextmanager
+async def lifespan(app: FastAPI):
+    print("Starting application...")
+    yield  # Wait until app closes
+    print("Shutting down application...")
+
+
+# Create FastAPI app
+app = FastAPI(lifespan=lifespan)
+
+
+@app.get("/")
+async def root():
+    return {"message": "Decision Helper API is running!"}
+
+
+@app.post("/generate_response")
+async def generate_text(request: Request):
+    try:
+        data = await request.json()
+        if not data or "text" not in data:
+            logging.error("Invalid request received")
+            return {"error": "Invalid request. Please send JSON with a 'text' field."}
+
+        text = data["text"].strip()
+        if not text:
+            return {"error": "No text provided"}
+
+        print(f"Received text: {text}")  # Debugging
+        
+        response = generate_response(text)
+        print(f"Generated response: {response}")  # Debugging
+        return {"response": response}
+
+    except Exception as e:
+        logging.error(f"Error processing request: {e}")
+        return {"error": "An unexpected error occurred."}
+
+
+# Run the server
+if __name__ == "__main__":
+    import uvicorn
+    uvicorn.run(app, host="0.0.0.0", port=7860)
+