Update app.py

app.py

@@ -7,9 +7,7 @@ from getpass import getpass
 
 openai_api_key = os.getenv('OPENAI_API_KEY')
 
-# -------------------------------------------------------
-# Configure LlamaIndex with OpenAI LLM and Embeddings
-# -------------------------------------------------------
+
 from llama_index.llms.openai import OpenAI
 from llama_index.embeddings.openai import OpenAIEmbedding
 from llama_index.core import Settings
@@ -17,14 +15,12 @@ from llama_index.core import Settings
 Settings.llm = OpenAI(model="gpt-3.5-turbo", temperature=0.4)
 Settings.embed_model = OpenAIEmbedding(model="text-embedding-ada-002")
 
-# -------------------------------------------------------
-# Import document readers, index, vector store, memory, etc.
-# -------------------------------------------------------
+
 from llama_index.core import SimpleDirectoryReader, VectorStoreIndex, StorageContext
 from llama_index.vector_stores.qdrant import QdrantVectorStore
 from llama_index.core.memory import ChatMemoryBuffer
 
-# Global variables to hold the index and chat engine.
+
 chat_engine = None
 index = None
 query_engine = None
@@ -33,32 +29,22 @@ client = None
 vector_store = None
 storage_context = None
 
-# -------------------------------------------------------
-# Function to process uploaded files and build the index.
-# -------------------------------------------------------
+
 def process_upload(files):
-    """
-    Accepts a list of uploaded file paths, saves them to a local folder,
-    loads them as documents, and builds the vector index and chat engine.
-    """
     upload_dir = "uploaded_files"
     if not os.path.exists(upload_dir):
         os.makedirs(upload_dir)
     else:
-        # Clear any existing files in the folder.
         for f in os.listdir(upload_dir):
             os.remove(os.path.join(upload_dir, f))
     
-    # 'files' is a list of file paths (Gradio's File component with type="file")
     for file_path in files:
         file_name = os.path.basename(file_path)
         dest = os.path.join(upload_dir, file_name)
         shutil.copy(file_path, dest)
     
-    # Load documents from the saved folder.
     documents = SimpleDirectoryReader(upload_dir).load_data()
     
-    # Build the index and chat engine using Qdrant as the vector store.
     global client, vector_store, storage_context, index, query_engine, memory, chat_engine
     client = qdrant_client.QdrantClient(location=":memory:")
     
@@ -88,12 +74,9 @@ def process_upload(files):
     
     return "Documents uploaded and index built successfully!"
 
-# -------------------------------------------------------
-# Chat function that uses the built chat engine.
-# -------------------------------------------------------
+
 def chat_with_ai(user_input, chat_history):
     global chat_engine
-    # Check if the chat engine is initialized.
     if chat_engine is None:
         return chat_history, "Please upload documents first."
     
@@ -101,7 +84,6 @@ def chat_with_ai(user_input, chat_history):
     references = response.source_nodes
     ref, pages = [], []
     
-    # Extract file names from the source nodes (if available)
     for node in references:
         file_name = node.metadata.get('file_name')
         if file_name and file_name not in ref:
@@ -114,23 +96,17 @@ def chat_with_ai(user_input, chat_history):
         chat_history.append((user_input, str(response)))
     return chat_history, ""
 
-# -------------------------------------------------------
-# Function to clear the chat history.
-# -------------------------------------------------------
+
 def clear_history():
     return [], ""
 
-# -------------------------------------------------------
-# Build the Gradio interface.
-# -------------------------------------------------------
+
 def gradio_interface():
     with gr.Blocks() as demo:
         gr.Markdown("# Chat Interface for LlamaIndex with File Upload")
         
-        # Use Tabs to separate the file upload and chat interfaces.
         with gr.Tab("Upload Documents"):
             gr.Markdown("Upload PDF, Excel, CSV, DOC/DOCX, or TXT files below:")
-            # The file upload widget: we specify allowed file types.
             file_upload = gr.File(
                     label="Upload Files",
                     file_count="multiple",
@@ -158,5 +134,5 @@ def gradio_interface():
     
     return demo
 
-# Launch the Gradio app.
+
 gradio_interface().launch(debug=True)