Create app

app.py

@@ -0,0 +1,52 @@
+import gradio as gr
+import requests
+import fitz  # PyMuPDF
+from pleias_rag_interface import RAGWithCitations
+
+# Initialize the Pleias RAG model
+rag = RAGWithCitations(model_path_or_name="PleIAs/Pleias-RAG-350M")
+
+def extract_text_from_pdf_url(url):
+    try:
+        response = requests.get(url)
+        response.raise_for_status()
+        doc = fitz.open(stream=response.content, filetype="pdf")
+        text = ""
+        for page in doc:
+            text += page.get_text()
+        return text.strip()
+    except Exception as e:
+        return f"[Error loading PDF: {str(e)}]"
+
+def generate_answer(query, pdf_urls_str):
+    pdf_urls = [url.strip() for url in pdf_urls_str.strip().split("\n") if url.strip()]
+    
+    sources = []
+    for url in pdf_urls:
+        text = extract_text_from_pdf_url(url)
+        if not text.startswith("[Error"):
+            sources.append({
+                "text": text,
+                "metadata": {"source": url}
+            })
+    
+    if not sources:
+        return "No valid PDFs found or unable to extract text."
+
+    response = rag.generate(query, sources)
+    return f"### Query:\n{query}\n\n### Answer:\n{response['raw_response']}\n\n### Source Info:\nBackend used: {response['backend_used']}"
+
+# Gradio UI
+iface = gr.Interface(
+    fn=generate_answer,
+    inputs=[
+        gr.Textbox(label="Your Question", placeholder="What is this document about?"),
+        gr.Textbox(lines=5, label="PDF URLs (one per line)", placeholder="https://example.com/doc1.pdf\nhttps://example.com/doc2.pdf")
+    ],
+    outputs=gr.Markdown(label="Model Response"),
+    title="Pleias RAG PDF QA",
+    description="Ask a question and get answers grounded in the content of the uploaded PDF URLs using the Pleias RAG model."
+)
+
+if __name__ == "__main__":
+    iface.launch()