update setup notes

.gitignore

@@ -1 +1,2 @@
-/data/
+/data/
+*__pycache__*

demo.py

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+import gradio as gr
+from infer import run_search, question_list
+
+def gradio_answer(question: str) -> str:
+    print(f"\nReceived question for Gradio: {question}")
+    try:
+        # Call the core inference function, passing the pre-loaded assets
+        trajectory, answer = run_search(question)
+        answer_string = f"Final answer: {answer.strip()}"
+        answer_string += f"\n\n====== Trajectory of reasoning steps ======\n{trajectory.strip()}"
+        return answer_string
+    except Exception as e:
+        # Basic error handling for the Gradio interface
+        return f"An error occurred: {e}. Please check the console for more details."
+
+
+iface = gr.Interface(
+    fn=gradio_answer,
+    inputs=gr.Textbox(
+        lines=3,
+        label="Enter your question",
+        placeholder="e.g., Who invented the telephone?"
+    ),
+    outputs=gr.Textbox(
+        label="Answer",
+        show_copy_button=True, # Allow users to easily copy the answer
+        elem_id="answer_output" # Optional: for custom CSS/JS targeting
+    ),
+    title="Demo of AutoRefine: Question Answering with Search and Refine During Thinking",
+    description=("Ask a question and this model will use a multi-turn reasoning and search mechanism to find the answer."),
+    examples=question_list, # Use the list of example questions
+    live=False, # Set to True if you want real-time updates as user types
+    allow_flagging="never", # Disable flagging functionality
+    theme=gr.themes.Soft(), # Apply a clean theme
+    cache_examples=True, # Cache the examples for faster loading
+)
+
+iface.launch(share=True)
+

setup.sh

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+# Installation guidance for this space
+
+```bash
+bash install_cuda.sh
+conda create -n faiss_env python=3.10 && conda activate faiss_env
+bash install_env.sh
+
+bash download_corpus.sh
+python download_model.py
+
+bash retrieval_launch.sh
+# sanity check
+python infer.py
+python demo.py
+```