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 | |
# hebrew_generator = pipeline("text-generation", model="onlplab/alephbert-base") | |
# english_generator = pipeline("text-generation", model="vicgalle/gpt2-open-instruct-v1") | |
lang_generator = pipeline("text-generation", model="microsoft/Phi-3.5-mini-instruct") | |
# # hebrew_generator = pipeline("text-generation", model="Norod78/hebrew-gpt_neo-small") | |
# # english_generator = pipeline("text-generation", model="distilgpt2") | |
# # Function to detect language | |
def detect_language(user_input): | |
try: | |
# lang = detect(user_input) | |
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" | |
# Function to generate a response | |
# def generate_response(text): | |
# language = detect_language(text) | |
# if language == "hebrew": | |
# return hebrew_generator(text, max_length=100, truncation=True)[0]["generated_text"] | |
# elif language == "english": | |
# return english_generator(text, max_length=100, truncation=True)[0]["generated_text"] | |
# return "Sorry, I only support Hebrew and English." | |
# def generate_response(text): | |
# language = detect_language(text) | |
# print(f"Detected language: {language}, ", f"current time: {current_time_gmt()}") # Debugging | |
# if language == "hebrew": | |
# output = hebrew_generator(text, max_length=100, truncation=True) | |
# print(f"Hebrew model output: {output}, ", f"current time: {current_time_gmt()}") # Debugging | |
# return output[0]["generated_text"] | |
# elif language == "english": | |
# output = english_generator(text, max_length=50, 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." | |
def generate_response(text): | |
language = detect_language(text) | |
print(f"Detected language: {language}, ", f"current time: {current_time_gmt()}") | |
if language == "hebrew": | |
#hebrew_generator = pipeline("text-generation", model="onlplab/alephbert-base") | |
# output = hebrew_generator(text, max_length=100, truncation=True) | |
output = lang_generator(text, max_new_tokens=250, truncation=True) | |
print(f"Hebrew 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=50, truncation=True) | |
output = lang_generator(text, max_new_tokens=250, 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 | |
async def lifespan(app: FastAPI): | |
print("Starting application...") | |
yield # Wait until app closes | |
print("Shutting down application...") | |
# Create FastAPI app | |
app = FastAPI(lifespan=lifespan) | |
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() | |
# text = data.get("text", "").strip() # removes non-relevant spaces | |
# if not text: | |
# return {"error": "No text provided"} | |
# response = generate_response(text) | |
# return {"response": response} | |
# except Exception as e: | |
# logging.error(f"Error processing request: {e}") | |
# return {"error": "Invalid request. Please send JSON with a 'text' field."} | |
# @app.post("/generate_response") | |
# async def generate_text(request: Request): | |
# try: | |
# data = await request.json() | |
# logging.info(f"Received request: {data}") # Log the request data | |
# text = data.get("text", "").strip() # removes non-relevant spaces | |
# if not text: | |
# return {"error": "No text provided"} | |
# response = generate_response(text) | |
# logging.info(f"Generated response: {response}") # Log the response | |
# return {"response": response} | |
# except Exception as e: | |
# logging.error(f"Error processing request: {e}") | |
# return {"error": "Invalid request. Please send JSON with a 'text' field."} | |
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) | |