Update app.py

app.py

@@ -29,58 +29,6 @@ from flask import Flask, request, render_template
 from flask_cors import CORS
 from flask_socketio import SocketIO, emit
 
-
-# GROQ_API_KEY = os.getenv("GROQ_API_KEY")
-GROQ_API_KEY = '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'
-# load_dotenv(".env")
-USER_AGENT = os.getenv("USER_AGENT")
-GROQ_API_KEY = os.getenv("GROQ_API_KEY")
-SECRET_KEY = os.getenv("SECRET_KEY")
-
-
-# Set environment variables
-os.environ['USER_AGENT'] = USER_AGENT
-os.environ["GROQ_API_KEY"] = GROQ_API_KEY
-os.environ["TOKENIZERS_PARALLELISM"] = 'true'
-
-# Initialize Flask app and SocketIO with CORS
-app = Flask(__name__)
-CORS(app)
-app.config['MAX_CONTENT_LENGTH'] = 1e7
-app.config['SESSION_COOKIE_SECURE'] = True  # Use HTTPS
-app.config['SESSION_COOKIE_HTTPONLY'] = True
-app.config['SESSION_COOKIE_SAMESITE'] = 'Lax'
-socketio = SocketIO(app, cors_allowed_origins="*", logger=True, max_http_buffer_size=1e7)
-app.config['SECRET_KEY'] = SECRET_KEY
-
-import pandas as pd
-from PIL import Image
-import numpy as np
-import os
-
-import torch
-import torch.nn.functional as F
-
-# from src.data.embs import ImageDataset
-from src.model.blip_embs import blip_embs
-from src.data.transforms import transform_test
-
-from transformers import StoppingCriteria, StoppingCriteriaList, TextIteratorStreamer
-import gradio as gr
-# import spaces
-
-from langchain.chains import ConversationChain
-from langchain_community.chat_message_histories import ChatMessageHistory
-from langchain_core.runnables import RunnableWithMessageHistory
-from langchain_core.output_parsers import StrOutputParser
-from langchain_core.prompts import ChatPromptTemplate
-from langchain_groq import ChatGroq
-
-from dotenv import load_dotenv
-from flask import Flask, request, render_template
-from flask_cors import CORS
-from flask_socketio import SocketIO, emit
-
 import json
 from openai import OpenAI
 
@@ -100,12 +48,14 @@ os.environ["TOKENIZERS_PARALLELISM"] = 'true'
 # Initialize Flask app and SocketIO with CORS
 app = Flask(__name__)
 CORS(app)
-socketio = SocketIO(app, cors_allowed_origins="*", logger=True)
+app.config['MAX_CONTENT_LENGTH'] = 1e7
 app.config['SESSION_COOKIE_SECURE'] = True  # Use HTTPS
 app.config['SESSION_COOKIE_HTTPONLY'] = True
 app.config['SESSION_COOKIE_SAMESITE'] = 'Lax'
+socketio = SocketIO(app, cors_allowed_origins="*", logger=True, max_http_buffer_size=1e7)
 app.config['SECRET_KEY'] = SECRET_KEY
 
+
 # Initialize LLM
 llm = ChatGroq(model="llama-3.1-8b-instant", temperature=0, max_tokens=1024, max_retries=2)
 
@@ -179,15 +129,11 @@ model = blip_embs(
 
 model = model.to(device)
 model.eval()
-print("Model Loaded !")
-print("="*50)
 
 transform = transform_test(384)
 
-print("Loading Data")
 df = pd.read_json("my_recipes.json")
 
-print("Loading Target Embedding")
 tar_img_feats = []
 for _id in df["id_"].tolist():     
     tar_img_feats.append(torch.load("./datasets/sidechef/blip-embs-large/{:07d}.pth".format(_id)).unsqueeze(0))
@@ -234,7 +180,6 @@ class Chat:
 
 
 chat = Chat(model,transform,df,tar_img_feats, device)
-print("Chat Initialized !")
 
 
 def answer_generator(formated_input, session_id):
@@ -516,7 +461,7 @@ def handle_message(data):
     context = "No data available"
     session_id = request.sid
     if session_id not in session_store:
-        session_store[session_id] = {'image_data': b"", 'message': None, 'image_received': False}
+        session_store[session_id] = {'image_data': "", 'message': None, 'image_received': False}
 
     if 'message' in data:
         session_store[session_id]['message'] = data['message']
@@ -614,9 +559,6 @@ def handle_message(data):
     emit('response', response, room=session_id)
     return response
 
-
-
-
 # Home route
 @app.route("/")
 def index_view():