Introduced app.py: a rag chatbot

app.py

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+import gradio as gr
+from src.rag import RAG
+
+def upload_files(files, filepaths):
+    verbose = False
+    filepaths_new = [file.name for file in files]
+    if verbose:
+        print(f'previous files: {filepaths}')
+        print(f'new files: {filepaths_new}')
+    filepaths = filepaths + filepaths_new
+    return filepaths, filepaths
+
+def initialize_rag(pdfs):
+    print(f'Initializing RAG-Chatbot with:\npdfs:\n{pdfs}')
+    # Initialize RAG instance
+    try:
+        rag = RAG(
+            urls=[],
+            pdfs=pdfs,
+            k=2
+            )
+        message = "RAG-Chatbot initialized successfully!"
+    except Exception as e:
+        rag = None
+        message = f"Error initializing RAG-Chatbot:\n{e}"
+    return message, rag
+
+def get_rag_response(message, history, rag):
+    if rag is None:
+        return "Error: RAG-Chatbot is not initialized yet!"
+    print(f"Question: {message}")
+    response = rag.ask_QAbot(message)
+    answer_str = response['answer']
+    sources = [f"{i+1}. {source.split('/')[-1]}" for i, source in enumerate(response['sources'])]
+    sources_str = ';'.join(sources)
+    print(sources_str)
+    response_str = f"""
+    {answer_str}
+    
+    Sources: 
+    {sources_str}
+    """
+
+    return response_str
+
+with gr.Blocks() as demo:
+    gr.Markdown("Define References")
+    # PDFs
+    pdfpaths = gr.State([])
+    file_output = gr.File()
+    upload_button = gr.UploadButton("Upload PDF(s)",  file_count="multiple")
+    upload_button.upload(
+        fn=upload_files, 
+        inputs=[upload_button, pdfpaths], 
+        outputs=[file_output, pdfpaths])
+    # State to store the RAG instance
+    rag_instance = gr.State(None)  # Initially None
+    init_button = gr.Button("Initialize RAG-Chatbot")
+    init_status = gr.Textbox(label="Initialization Status", interactive=False)
+    # Event handlers
+    init_button.click(
+        initialize_rag,
+        inputs=[pdfpaths],
+        outputs=[init_status, rag_instance]  # Output: status message and the RAG instance
+    )
+    gr.Markdown('## Chat with Rag-Chatbot')
+    # Chat Interface for RAG-Chatbot
+    gr.ChatInterface(
+        fn=get_rag_response,
+        additional_inputs=[rag_instance],
+        type="messages"
+    )
+
+if __name__ == "__main__":
+    demo.launch()
+