Create app.py

app.py

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+import gradio as gr
+import time
+import sys
+import os
+
+# Add the repo root to path so we can import the /app modules
+sys.path.append(os.path.dirname(__file__))
+
+# Import your three RAG implementations
+from app.rag_naive import NaiveRAG
+from app.rag_optimized import OptimizedRAG
+from app.no_compromise_rag import NoCompromiseRAG
+
+# -------------------------------------------------------------------
+# Initialize the three RAG systems once at startup.
+# If memory becomes an issue, we can lazy‑load them inside each function.
+# -------------------------------------------------------------------
+print("Initializing Naive RAG...")
+naive_rag = NaiveRAG()           # loads embedding model + FAISS index
+print("Initializing Optimized RAG...")
+optimized_rag = OptimizedRAG()   # loads the same + SQLite cache
+print("Initializing No‑Compromise RAG...")
+no_compromise_rag = NoCompromiseRAG()
+print("All RAG systems ready.")
+
+# -------------------------------------------------------------------
+# Define the query functions for each mode
+# -------------------------------------------------------------------
+def query_naive(question):
+    start = time.perf_counter()
+    answer, chunks_used, cache_hit = naive_rag.query(question)
+    latency = (time.perf_counter() - start) * 1000
+    return answer, f"{latency:.1f} ms", chunks_used, "Yes" if cache_hit else "No"
+
+def query_optimized(question):
+    start = time.perf_counter()
+    answer, chunks_used, cache_hit = optimized_rag.query(question)
+    latency = (time.perf_counter() - start) * 1000
+    return answer, f"{latency:.1f} ms", chunks_used, "Yes" if cache_hit else "No"
+
+def query_no_compromise(question):
+    start = time.perf_counter()
+    answer, chunks_used, cache_hit = no_compromise_rag.query(question)
+    latency = (time.perf_counter() - start) * 1000
+    return answer, f"{latency:.1f} ms", chunks_used, "Yes" if cache_hit else "No"
+
+# -------------------------------------------------------------------
+# Build the Gradio interface
+# -------------------------------------------------------------------
+with gr.Blocks(title="RAG Latency Optimization", theme=gr.themes.Soft()) as demo:
+    gr.Markdown("""
+    # ⚡ RAG Latency Optimization
+    ### Compare Naive, Optimized, and No‑Compromise RAG on CPU‑only hardware
+    **Proven 2.7× speedup (247ms → 92ms)** – now interactive!
+    """)
+
+    with gr.Tabs():
+        # ----- Naive RAG tab -----
+        with gr.TabItem("🐢 Naive RAG (Baseline)"):
+            with gr.Row():
+                question_naive = gr.Textbox(label="Your Question", lines=2)
+                submit_naive = gr.Button("Ask", variant="primary")
+            with gr.Row():
+                answer_naive = gr.Textbox(label="Answer", lines=4)
+            with gr.Row():
+                latency_naive = gr.Textbox(label="Latency", interactive=False)
+                chunks_naive = gr.Textbox(label="Chunks Used", interactive=False)
+                cache_naive = gr.Textbox(label="Cache Hit", interactive=False)
+            submit_naive.click(
+                query_naive,
+                inputs=question_naive,
+                outputs=[answer_naive, latency_naive, chunks_naive, cache_naive]
+            )
+
+        # ----- Optimized RAG tab -----
+        with gr.TabItem("⚡ Optimized RAG (Production)"):
+            with gr.Row():
+                question_opt = gr.Textbox(label="Your Question", lines=2)
+                submit_opt = gr.Button("Ask", variant="primary")
+            with gr.Row():
+                answer_opt = gr.Textbox(label="Answer", lines=4)
+            with gr.Row():
+                latency_opt = gr.Textbox(label="Latency", interactive=False)
+                chunks_opt = gr.Textbox(label="Chunks Used", interactive=False)
+                cache_opt = gr.Textbox(label="Cache Hit", interactive=False)
+            submit_opt.click(
+                query_optimized,
+                inputs=question_opt,
+                outputs=[answer_opt, latency_opt, chunks_opt, cache_opt]
+            )
+
+        # ----- No‑Compromise RAG tab -----
+        with gr.TabItem("🚀 No‑Compromise RAG (Max Speed)"):
+            with gr.Row():
+                question_nc = gr.Textbox(label="Your Question", lines=2)
+                submit_nc = gr.Button("Ask", variant="primary")
+            with gr.Row():
+                answer_nc = gr.Textbox(label="Answer", lines=4)
+            with gr.Row():
+                latency_nc = gr.Textbox(label="Latency", interactive=False)
+                chunks_nc = gr.Textbox(label="Chunks Used", interactive=False)
+                cache_nc = gr.Textbox(label="Cache Hit", interactive=False)
+            submit_nc.click(
+                query_no_compromise,
+                inputs=question_nc,
+                outputs=[answer_nc, latency_nc, chunks_nc, cache_nc]
+            )
+
+    gr.Markdown("""
+    ---
+    **Architecture**: CPU‑only | **Embeddings**: `all-MiniLM-L6-v2` | **Vector Store**: FAISS  
+    **Caching**: SQLite (Optimized) + LRU memory | **Generation**: Simulated (real LLM can be plugged in)
+    """)
+
+# Launch the app
+if __name__ == "__main__":
+    demo.launch(server_name="0.0.0.0", server_port=7860)