| |
| """ |
| Usage: python scripts/launch_ui.py |
| |
| Gradio web UI for the RAG system. |
| Provides a user-friendly interface for asking questions. |
| """ |
| import gradio as gr |
| from query.retriever import retrieve |
| from query.prompt_builder import build_prompt |
| from query.generator import generate |
|
|
|
|
| def answer_question_generator(question: str, show_sources: bool = False, tutor_mode: bool = False): |
| """ |
| Answer a question using the RAG system with streaming status updates. |
| |
| Args: |
| question: The user's question |
| show_sources: Whether to display retrieved sources |
| tutor_mode: If True, use Socratic tutor mode; if False, use direct answer mode |
| |
| Yields: |
| Tuples of (answer_markdown, sources_markdown) for progressive UI updates |
| """ |
| if not question.strip(): |
| yield "Please enter a question.", "" |
| return |
| |
| |
| yield "🔍 **Retrieving relevant sources...**\n\n*(This may take 5-10 seconds)*", "" |
| |
| try: |
| chunks = retrieve(question) |
| count = len(chunks) |
| |
| mode_label = "🎓 **Tutor Mode**" if tutor_mode else "📚 **Regular Mode**" |
| yield f"✓ **Retrieved {count} relevant sources**\n\n⏳ **Generating response ({mode_label})...**\n\n*(This may take 15-30 seconds with local Ollama. Please wait.)*", "" |
| |
| |
| prompt = build_prompt(question, chunks, tutor_mode=tutor_mode) |
| |
| |
| response = generate(prompt) |
| |
| |
| sources_text = "" |
| if show_sources and chunks: |
| sources_text = "## Retrieved Sources\n\n" |
| for i, chunk in enumerate(chunks, 1): |
| source = chunk["metadata"].get("source", "unknown") |
| page = chunk["metadata"].get("page", chunk["metadata"].get("slide", "?")) |
| category = chunk["metadata"].get("category", "unknown") |
| distance = chunk.get("distance", "?") |
| sources_text += f"### Source {i}\n" |
| sources_text += f"**Category:** {category}\n" |
| sources_text += f"**Location:** {source} (page/slide {page})\n" |
| sources_text += f"**Relevance:** {distance:.4f}\n" |
| sources_text += f"**Excerpt:** {chunk['text'][:200]}...\n\n" |
| |
| |
| yield response, sources_text |
| |
| except Exception as e: |
| yield f"❌ **Error:** {str(e)}", "" |
|
|
|
|
| def main(): |
| """Launch the Gradio interface.""" |
| with gr.Blocks(title="ENGR 445 RAG Assistant") as demo: |
| gr.Markdown("# ENGR 445 Course Assistant") |
| gr.Markdown("Ask questions about ENGR 445 course material — lectures, datasheets, application notes, and source code.") |
| |
| with gr.Row(): |
| question_input = gr.Textbox( |
| label="Your Question", |
| placeholder="E.g., How do I configure GPIO pins as push-pull?", |
| lines=2 |
| ) |
| |
| with gr.Row(): |
| submit_btn = gr.Button("Ask", scale=1) |
| show_sources_cb = gr.Checkbox(label="Show Retrieved Sources", value=False) |
| tutor_mode_cb = gr.Checkbox(label="🎓 Tutor Mode (hints instead of answers)", value=False) |
| |
| with gr.Row(): |
| answer_output = gr.Markdown(label="Answer", value="*Ask a question to get started...*") |
| |
| with gr.Row(): |
| sources_output = gr.Markdown(label="Sources") |
| |
| with gr.Row(): |
| gr.Markdown(""" |
| **Mode Explanation:** |
| - **Regular Mode**: Provides direct answers with citations |
| - **Tutor Mode**: Acts as a Socratic tutor, providing hints and guiding you to resources instead of answers |
| """) |
| |
| |
| submit_btn.click( |
| fn=answer_question_generator, |
| inputs=[question_input, show_sources_cb, tutor_mode_cb], |
| outputs=[answer_output, sources_output] |
| ) |
| |
| |
| question_input.submit( |
| fn=answer_question_generator, |
| inputs=[question_input, show_sources_cb, tutor_mode_cb], |
| outputs=[answer_output, sources_output] |
| ) |
| |
| gr.Markdown("---") |
| gr.Markdown("**Note:** All inference runs locally via Ollama. Ensure Ollama is running before using this interface.") |
| |
| demo.launch(server_name="127.0.0.1", server_port=7860, share=False) |
|
|
|
|
| if __name__ == "__main__": |
| main() |
