Update app.py

app.py

@@ -16,6 +16,10 @@ from langchain.vectorstores import FAISS
 from langchain.chains import RetrievalQA
 import gradio as gr
 
+# Step 5: Initialize the LLM
+openai_api_key = os.getenv("tauhid")
+print(f"API key retrieved: {'[NOT FOUND]' if not openai_api_key else '[FOUND - first 4 chars: ' + openai_api_key[:4] + ']'}")
+
 # Step 1: Load the System Prompt
 prompt_path = "system_prompt.txt"  # Ensure this file is in the same directory
 if not os.path.exists(prompt_path):
@@ -56,9 +60,7 @@ if len(texts) != len(metadatas):
     raise ValueError("Mismatch between texts and metadata after preprocessing.")
 
 
-# Step 5: Initialize the LLM
-openai_api_key = os.getenv("tauhid")
-print(f"API key retrieved: {'[NOT FOUND]' if not openai_api_key else '[FOUND - first 4 chars: ' + openai_api_key[:4] + ']'}")
+
 
 # Step 4: Create the Vector Store
 embeddings = OpenAIEmbeddings()