Create app.py

app.py

@@ -0,0 +1,36 @@
+import gradio as gr
+import os
+from rag_pipeline import RAGPipeline
+import openai
+openai.api_key = os.environ.get('OPENAI_API_KEY')
+
+# Initialize the RAG pipeline
+rag = RAGPipeline("metadata_map.json", "pdfs")
+
+def process_query(question, response_format):
+    response = rag.query(question)
+    
+    if response_format == "Markdown":
+        return response["markdown"]
+    else:
+        return response["raw"]
+
+# Define the Gradio interface
+iface = gr.Interface(
+    fn=process_query,
+    inputs=[
+        gr.Textbox(lines=2, placeholder="Enter your question here...", label="Question"),
+        gr.Radio(["Markdown", "Raw Text"], label="Response Format", value="Markdown")
+    ],
+    outputs=gr.Markdown(label="Response"),
+    title="Vaccine Coverage and Hesitancy Research QA",
+    description="Ask questions about vaccine coverage and hesitancy. The system will provide answers based on the available research papers.",
+    examples=[
+        ["What are the main factors contributing to vaccine hesitancy?", "Markdown"],
+        ["What are the current vaccine coverage rates in African countries?", "Raw Text"],
+    ],
+    allow_flagging="never"
+)
+
+# Launch the app
+iface.launch()