Update app.py

app.py

@@ -1,36 +1,158 @@
 import gradio as gr
+import os
 from rag_engine import RAGEngine
 
+# Initialize engine
 engine = RAGEngine()
 
-def upload_source(file=None, url=None):
+# ── Helpers ──────────────────────────────────────────────────────────────────
+
+def process_pdf(file):
+    if file is None:
+        return "⚠️ No file uploaded.", gr.update(interactive=False)
+    try:
+        msg = engine.load_pdf(file.name)
+        return msg, gr.update(interactive=True)
+    except Exception as e:
+        return f"❌ Error: {e}", gr.update(interactive=False)
+
+def process_url(url):
+    if not url.strip():
+        return "⚠️ Please enter a URL.", gr.update(interactive=False)
+    try:
+        msg = engine.load_url(url.strip())
+        return msg, gr.update(interactive=True)
+    except Exception as e:
+        return f"❌ Error: {e}", gr.update(interactive=False)
+
+def process_text(text):
+    if not text.strip():
+        return "⚠️ Please paste some text.", gr.update(interactive=False)
     try:
-        if file: msg = engine.load_pdf(file.name)
-        elif url: msg = engine.load_url(url)
-        else: return "❌ No source provided.", gr.update(interactive=False)
-        return msg, gr.update(interactive=True, placeholder="Ask me anything!")
+        msg = engine.load_text(text.strip())
+        return msg, gr.update(interactive=True)
     except Exception as e:
-        return f"❌ Error: {str(e)}", gr.update(interactive=False)
+        return f"❌ Error: {e}", gr.update(interactive=False)
+
+def chat(message, history):
+    if not message.strip():
+        return history, ""
+    answer = engine.answer(message)
+    history = history or []
+    history.append((message, answer))
+    return history, ""
+
+def reset_all():
+    engine.reset()
+    return [], "", "🔄 Knowledge base cleared. Load a new source to begin."
+
+# ── UI ────────────────────────────────────────────────────────────────────────
+
+DESCRIPTION = """
+# 🤖 RAG Chatbot — Chat with Your Data
+Upload a **PDF**, paste a **website URL**, or drop in **raw text** — then ask anything.
+
+Built with 🤗 HuggingFace · FAISS · spaCy · Sentence-Transformers
+"""
 
-def chat(msg, history):
-    ans, nlp = engine.answer_with_nlp(msg)
-    history.append((msg, ans))
-    return history, "", nlp
+with gr.Blocks(
+    title="RAG Chatbot",
+    theme=gr.themes.Soft(primary_hue="violet", secondary_hue="slate"),
+    css="""
+    #chatbot { min-height: 420px; }
+    .source-box { border: 1px solid #e2e8f0; border-radius: 12px; padding: 16px; background: #f8fafc; }
+    .status-bar { font-size: 13px; padding: 6px 12px; border-radius: 8px; }
+    footer { display: none !important; }
+    """,
+) as demo:
+    gr.Markdown(DESCRIPTION)
 
-with gr.Blocks(theme=gr.themes.Soft()) as demo:
-    gr.Markdown("# 🤖 Your Pro RAG Chatbot")
     with gr.Row():
-        with gr.Column(scale=1):
-            file_in = gr.File(label="Step 1: Upload PDF")
-            url_in = gr.Textbox(label="OR Paste URL")
-            btn = gr.Button("🚀 Process Knowledge", variant="primary")
-            status = gr.Label("Status: Waiting for data...")
+        # ── Left column: source loader ──────────────────────────────────────
+        with gr.Column(scale=1, elem_classes="source-box"):
+            gr.Markdown("### 📂 Load a Knowledge Source")
+
+            with gr.Tab("📄 PDF"):
+                pdf_input = gr.File(
+                    label="Upload PDF",
+                    file_types=[".pdf"],
+                    type="filepath",
+                )
+                pdf_btn = gr.Button("Load PDF", variant="primary")
+
+            with gr.Tab("🌐 Website URL"):
+                url_input = gr.Textbox(
+                    label="Website URL",
+                    placeholder="https://example.com/page",
+                )
+                url_btn = gr.Button("Load URL", variant="primary")
+
+            with gr.Tab("📝 Raw Text"):
+                text_input = gr.Textbox(
+                    label="Paste your text",
+                    lines=8,
+                    placeholder="Paste any text here...",
+                )
+                text_btn = gr.Button("Load Text", variant="primary")
+
+            status = gr.Textbox(
+                label="Status",
+                value="⏳ Load a source to start chatting.",
+                interactive=False,
+                elem_classes="status-bar",
+            )
+
+            with gr.Accordion("ℹ️ NLP Insights", open=False):
+                nlp_output = gr.JSON(label="Last query analysis")
+
+        # ── Right column: chat ──────────────────────────────────���───────────
         with gr.Column(scale=2):
-            chatbot = gr.Chatbot(height=400)
-            msg_in = gr.Textbox(placeholder="Locked until data is processed...", interactive=False)
-            nlp_out = gr.JSON(label="AI Analysis")
+            gr.Markdown("### 💬 Chat")
+            chatbot = gr.Chatbot(
+                elem_id="chatbot",
+                bubble_full_width=False,
+                avatar_images=(None, "https://huggingface.co/front/assets/huggingface_logo-noborder.svg"),
+            )
+
+            with gr.Row():
+                msg_box = gr.Textbox(
+                    placeholder="Ask a question about your loaded content...",
+                    show_label=False,
+                    scale=4,
+                    interactive=False,
+                )
+                send_btn = gr.Button("Send ➤", variant="primary", scale=1)
+
+            reset_btn = gr.Button("🗑️ Clear & Reset", variant="secondary")
+
+    # ── Example questions ────────────────────────────────────────────────────
+    gr.Examples(
+        examples=[
+            "What is the main topic of this document?",
+            "Summarise the key points in 3 bullet points.",
+            "What are the most important entities mentioned?",
+            "Give me a short conclusion based on the content.",
+        ],
+        inputs=msg_box,
+        label="💡 Example questions",
+    )
+
+    # ── Wire events ──────────────────────────────────────────────────────────
+    def chat_with_nlp(message, history):
+        if not message.strip():
+            return history, "", {}
+        answer, nlp_info = engine.answer_with_nlp(message)
+        history = history or []
+        history.append((message, answer))
+        return history, "", nlp_info
+
+    pdf_btn.click(process_pdf, pdf_input, [status, msg_box])
+    url_btn.click(process_url, url_input, [status, msg_box])
+    text_btn.click(process_text, text_input, [status, msg_box])
 
-    btn.click(upload_source, [file_in, url_in], [status, msg_in])
-    msg_in.submit(chat, [msg_in, chatbot], [chatbot, msg_in, nlp_out])
+    send_btn.click(chat_with_nlp, [msg_box, chatbot], [chatbot, msg_box, nlp_output])
+    msg_box.submit(chat_with_nlp, [msg_box, chatbot], [chatbot, msg_box, nlp_output])
+    reset_btn.click(reset_all, outputs=[chatbot, msg_box, status])
 
-demo.launch()
+if __name__ == "__main__":
+    demo.launch(share=False)