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| import gradio as gr | |
| from advanced_rag import ElevatedRagChain | |
| rag_chain = ElevatedRagChain() | |
| def load_pdfs(pdf_links): | |
| if not pdf_links: | |
| gr.Warning("Please enter non-empty URLs") | |
| return "Please enter non-empty URLs" | |
| try: | |
| pdf_links = pdf_links.split("\n") # get individual PDF links | |
| rag_chain.add_pdfs_to_vectore_store(pdf_links) | |
| gr.Info("PDFs loaded successfully into a new vector store. If you had an old one, it was overwritten.") | |
| return "PDFs loaded successfully into a new vector store. If you had an old one, it was overwritten." | |
| except Exception as e: | |
| gr.Warning("Could not load PDFs. Are URLs valid?") | |
| print(e) | |
| return "Could not load PDFs. Are URLs valid?" | |
| def submit_query(query): | |
| if not query: | |
| gr.Warning("Please enter a non-empty query") | |
| return "Please enter a non-empty query" | |
| if hasattr(rag_chain, 'elevated_rag_chain'): | |
| try: | |
| response = rag_chain.elevated_rag_chain.invoke(query) | |
| return response | |
| except Exception as e: | |
| gr.Warning("LLM error. Please re-submit your query") | |
| print(e) | |
| return "LLM error. Please re-submit your query" | |
| else: | |
| gr.Warning("Please load PDFs before submitting a query") | |
| return "Please load PDFs before submitting a query" | |
| def reset_app(): | |
| global rag_chain | |
| rag_chain = ElevatedRagChain() # Re-initialize the ElevatedRagChain object | |
| gr.Info("App reset successfully. You can now load new PDFs") | |
| return "App reset successfully. You can now load new PDFs" | |
| # custom css for different age elements | |
| custom_css = """ | |
| // customize button | |
| button { | |
| background-color: grey !important; | |
| font-family: Arial !important; | |
| font-weight: bold !important; | |
| color: blue !important; | |
| } | |
| // customize background color and use it as "app = gr.Blocks(css=custom_css)" | |
| //.gradio-container {background-color: #E0F7FA} | |
| """ | |
| # Define the Gradio app using Blocks for a flexible layout | |
| app = gr.Blocks(css=custom_css) # theme=gr.themes.Base(), Soft(), Default(), Glass(), Monochrome(): https://www.gradio.app/guides/theming-guide | |
| with app: | |
| gr.Markdown('''# Query your own data | |
| ## Llama 2 RAG | |
| - Type in one or more URLs for PDF files - one per line and click on Load PDFs. Wait until the RAG system is built. | |
| - Type your query and click on Submit Query. Once the LLM sends back a reponse, it will be displayed in the Reponse field. | |
| - The system "remembers" the source documents, but has no memory of past user queries. | |
| - Click on Reset App to clear / reset the RAG system | |
| ''') | |
| with gr.Row(): | |
| with gr.Column(): | |
| pdf_input = gr.Textbox(label="Enter your PDF URLs (one per line)", placeholder="Enter one URL per line", lines=4) | |
| load_button = gr.Button("Load PDF") | |
| with gr.Column(): | |
| query_input = gr.Textbox(label="Enter your query here", placeholder="Type your query", lines=4) | |
| submit_button = gr.Button("Submit") | |
| response_output = gr.Textbox(label="Response", placeholder="Response will appear here", lines=4) | |
| reset_button = gr.Button("Reset App") | |
| load_button.click(load_pdfs, inputs=pdf_input, outputs=response_output) | |
| submit_button.click(submit_query, inputs=query_input, outputs=response_output) | |
| reset_button.click(reset_app, inputs=None, outputs=response_output) | |
| # Run the app | |
| app.launch() | |