Update app.py

app.py

@@ -1,65 +1,74 @@
 import gradio as gr
-import time, os, uuid, datetime as dt
-from stt import transcribe_file
-from summarize import mmr_summarize
-from rag_store import add_text, search
-from llm import answer
+from rag_store import add_memory, search
+from llm import generate_answer
 
-def ingest(audio_path: str, notes: str):
-    if not audio_path:
-        return "No audio provided.", ""
-    t0 = time.time()
-    text = transcribe_file(audio_path) or ""
-    if not text.strip():
-        return "Couldn't transcribe. Try speaking closer to the mic.", ""
-    summary = mmr_summarize(text, max_sentences=4)
-    meta = {
-        "id": str(uuid.uuid4()),
-        "ts": dt.datetime.utcnow().isoformat(),
-        "tags": [t.strip() for t in (notes or "").split(",") if t.strip()]
-    }
-    add_text(summary, meta)
-    dt_ms = int((time.time()-t0)*1000)
-    return f"Indexed summary in {dt_ms} ms (text-only).", summary
+DESCRIPTION = """
+### 🧠 MnemoSense – Tiny External Memory Demo
 
-def ask(q: str, audio_q: str):
-    query = (q or "").strip()
-    if (not query) and audio_q:
-        query = transcribe_file(audio_q)
-    if not query.strip():
-        return "", "", "Please provide a question (text or audio)."
+- **Add memory**: type a short summary of something that happened.
+- **Ask**: query MnemoSense and it will retrieve the most relevant memories
+  and answer using only those.
+- This demo stores **only text summaries** on-disk, no audio or video.
+"""
+
+def ingest_memory(text: str):
+    text = (text or "").strip()
+    if not text:
+        return "⚠️ Please type something to remember.", ""
+    add_memory(text)
+    return "✅ Saved to MnemoSense memory.", text
+
+def ask_question(query: str):
+    query = (query or "").strip()
+    if not query:
+        return "⚠️ Please ask a question."
     hits = search(query, k=5)
-    ctxs = [h.get("text","") for h in hits]
-    ans = answer(query, ctxs)
-    refs = "\n\n".join([f"- {h.get('text','')[:160]}…" for h in hits])
-    return query, ans, refs if refs else "(no references yet)"
+    contexts = [h["text"] for h in hits]
+    answer = generate_answer(query, contexts)
+    return answer
+
+def build_demo():
+    with gr.Blocks(title="MnemoSense", theme="soft") as demo:
+        gr.Markdown("# 🧠 MnemoSense\nYour tiny external memory assistant.")
+        gr.Markdown(DESCRIPTION)
+
+        with gr.Tab("Add memory"):
+            mem_in = gr.Textbox(
+                label="What happened?",
+                lines=4,
+                placeholder="Example: I met Felix at the lab and we discussed MRI-compatible ECG patches…",
+            )
+            save_btn = gr.Button("Save memory")
+            status = gr.Markdown()
+            echo = gr.Textbox(label="Saved snippet", interactive=False)
 
-with gr.Blocks(title="MnemoSense — Spaces Demo") as demo:
-    gr.Markdown("# MnemoSense — Text-only Memory (HF Spaces)")
-    gr.Markdown("**Privacy-first**: Only summaries are stored. Try the **Ingest** tab, then ask questions.")
+            save_btn.click(
+                ingest_memory,
+                inputs=mem_in,
+                outputs=[status, echo],
+            )
 
-    with gr.Tab("Ingest"):
-        with gr.Row():
-            mic = gr.Audio(sources=["microphone","upload"], type="filepath", label="Record or Upload (<= 60s)")
-            notes = gr.Textbox(label="Optional tags (comma-separated)", placeholder="demo, meeting, idea")
-        btn_ingest = gr.Button("Transcribe → Summarize → Index")
-        status = gr.Textbox(label="Status", interactive=False)
-        summary = gr.Textbox(label="Summary stored", lines=4, interactive=False)
-        btn_ingest.click(ingest, inputs=[mic, notes], outputs=[status, summary])
+        with gr.Tab("Ask"):
+            q = gr.Textbox(
+                label="Ask MnemoSense",
+                lines=2,
+                placeholder="Example: What did we say about the mission?",
+            )
+            ask_btn = gr.Button("Ask")
+            ans = gr.Textbox(label="Answer", lines=6)
 
-    with gr.Tab("Ask"):
-        with gr.Row():
-            q = gr.Textbox(label="Question", placeholder="What did we say about the mission?")
-            q_audio = gr.Audio(sources=["microphone","upload"], type="filepath", label="Or ask by voice")
-        btn_ask = gr.Button("Retrieve → Answer")
-        out_q = gr.Textbox(label="You asked", interactive=False)
-        out_ans = gr.Textbox(label="Answer", lines=6, interactive=False)
-        out_refs = gr.Textbox(label="References (summaries)", lines=6, interactive=False)
-        btn_ask.click(ask, inputs=[q, q_audio], outputs=[out_q, out_ans, out_refs])
+            ask_btn.click(
+                ask_question,
+                inputs=q,
+                outputs=ans,
+            )
+
+        gr.Markdown("⚠️ Demo note: this Space keeps only text memories in `memories.jsonl`.")
+
+    return demo
 
 demo = build_demo()
 
 if __name__ == "__main__":
-    # On Hugging Face Spaces: bind to 0.0.0.0 and disable API docs
+    # HF Spaces: bind to 0.0.0.0 and hide API docs (they were causing a schema crash)
     demo.launch(server_name="0.0.0.0", show_api=False)
-