Update app.py

app.py

@@ -1,6 +1,5 @@
 # ==============================================================================
 # Part 1: Core Classes from the Original Script
-# All the necessary helper classes for the RAG system are defined here.
 # ==============================================================================
 import os
 import re
@@ -13,30 +12,19 @@ import torch
 import faiss
 from PIL import Image, ImageOps
 
-# Hugging Face Transformers & Sentence-Transformers
-from transformers import (
-    CLIPVisionModel,
-    CLIPImageProcessor,
-    AutoTokenizer,
-    AutoModel,
-)
+from transformers import (CLIPVisionModel, CLIPImageProcessor, AutoTokenizer, AutoModel)
 from sentence_transformers import SentenceTransformer
-
-# Google Generative AI
 import google.generativeai as genai
 from google.generativeai.types import GenerationConfig
-
-# Gradio for Web UI
 import gradio as gr
 
-
 # --- CONFIGURATION CLASS ---
 class Config:
     per_option_ctx: int = 5
     max_text_len: int = 512
     docstore_path: str = "indexes/docstore.parquet"
-    glot_model_hf: str = "Arshiaizd/Glot500-FineTuned"
-    mclip_text_model_hf: str = "Arshiaizd/MCLIP_FA_FineTuned"
+    glot_model_hf: str = "Arshiaizd/Glot500-Fine-Tuned"
+    mclip_text_model_hf: str = "Arshiaizd/MCLIP_FA-FineTuned"
     clip_vision_model: str = "SajjadAyoubi/clip-fa-vision"
     glot_index_out: str = "indexes/I_glot_text_fa.index"
     clip_index_out: str = "indexes/I_clip_text_fa.index"
@@ -105,7 +93,7 @@ class BaseRetriever:
         if os.path.isfile(self.index_path):
             self.index = faiss.read_index(self.index_path)
         else:
-            raise FileNotFoundError(f"Index file not found at {self.index_path}. Make sure it's uploaded to your Space.")
+            raise FileNotFoundError(f"Index file not found at {self.index_path}.")
     def search(self, query_vec: np.ndarray, k: int) -> List[Tuple[int, float]]:
         D, I = self.index.search(query_vec[None, :].astype(np.float32), k)
         return list(zip(I[0].tolist(), D[0].tolist()))
@@ -127,7 +115,7 @@ class TextIndexRetriever(BaseRetriever):
 class VLM_GenAI:
     def __init__(self, api_key: str, model_name: str, temperature: float = 0.1, max_output_tokens: int = 1024):
         if not api_key or "YOUR" in api_key:
-            raise ValueError("Gemini API Key is missing or is a placeholder. Please add it to your Hugging Face Space secrets.")
+            raise ValueError("Gemini API Key is missing. Add it to Space secrets.")
         genai.configure(api_key=api_key)
         self.model = genai.GenerativeModel(model_name)
         self.generation_config = GenerationConfig(temperature=temperature, max_output_tokens=max_output_tokens)
@@ -150,7 +138,6 @@ class RAGSystem:
 # Part 2: Gradio Web Application
 # ==============================================================================
 
-# --- 1. LOAD MODELS AND INDEXES (This runs only once when the app starts) ---
 print("Initializing configuration...")
 cfg = Config()
 print("Loading RAG system...")
@@ -160,7 +147,6 @@ api_key = os.environ.get("GEMINI_API_KEY")
 vlm = VLM_GenAI(api_key, model_name="models/gemini-1.5-flash")
 print("System ready.")
 
-# --- 2. DEFINE THE FUNCTION TO HANDLE USER INPUT ---
 def run_rag_query(question_text: str, question_image: Optional[Image.Image]) -> Tuple[str, str]:
     if not question_text.strip():
         return "Please ask a question.", ""
@@ -193,47 +179,29 @@ def run_rag_query(question_text: str, question_image: Optional[Image.Image]) ->
 
 # --- 3. CREATE THE GRADIO INTERFACE ---
 
-# Define your custom CSS for the background image
+# CORRECTED AND IMPROVED CSS
 custom_css = """
-body {
-    /* The URL to your background image in the HF Repo */
-    background-image: url('/file=background/back.jpg');
-    /* Make the image cover the whole background */
-    background-size: cover;
-    /* Don't repeat the image */
-    background-repeat: no-repeat;
-    /* Fix the background image so it doesn't scroll with content */
-    background-attachment: fixed;
-    /* Center the background image */
-    background-position: center;
-    color: white; /* Set default text color to white for readability */
-}
-
-/* Add a semi-transparent overlay to make text more readable */
-body::before {
-    content: "";
-    position: absolute;
-    top: 0; left: 0; right: 0; bottom: 0;
-    background-color: rgba(0, 0, 0, 0.5); /* Black overlay with 50% opacity */
-    z-index: -1; /* Place it behind the content */
+/* The #gradio-app selector is more specific and reliable */
+#gradio-app {
+    background-image: url('file/background/back.jpg') !important;
+    background-size: cover !important;
+    background-repeat: no-repeat !important;
+    background-attachment: fixed !important;
+    background-position: center !important;
 }
 
-/* Style the main container to have a semi-transparent background */
+/* Add a semi-transparent overlay to the main container for better text readability */
 .gradio-container {
-    background: rgba(0, 0, 0, 0.6) !important; /* Darker, semi-transparent background for the app area */
-    border-radius: 20px !important;
-    border: 1px solid rgba(255, 255, 255, 0.2);
+    background-color: rgba(0, 0, 0, 0.6) !important;
 }
 
-/* Make textboxes semi-transparent */
-textarea, input[type="text"] {
-    background-color: rgba(255, 255, 255, 0.1) !important;
+/* Style labels to be white so they are visible */
+.gradio-container .gr-label {
     color: white !important;
-    border: 1px solid rgba(255, 255, 255, 0.3) !important;
 }
 """
 
-with gr.Blocks(css=custom_css, title="Persian Culinary RAG") as demo:
+with gr.Blocks(css=custom_css, theme=gr.themes.Soft(), title="Persian Culinary RAG") as demo:
     gr.Markdown("# 🍲 Persian Culinary RAG Demo")
     gr.Markdown("Ask a question about Iranian food, with or without an image, to see the RAG system in action.")