Final Commit

.streamlit/config.toml

@@ -3,6 +3,8 @@ gatherUsageStats = false
 
 [server]
 headless = true
-enableCORS = true
-enableXsrfProtection = true
+enableCORS = false
+enableXsrfProtection = false
 fileWatcherType = "auto"
+
+maxUploadSize = 2000

Dockerfile

@@ -1,18 +1,4 @@
-# FROM python:3.12-slim
-
-# RUN apt-get update && apt-get install -y --no-install-recommends \
-#     libgl1 libglib2.0-0 && \
-#     rm -rf /var/lib/apt/lists/*
-
-# WORKDIR /app
-# COPY requirements.txt .
-# RUN pip install --no-cache-dir -r requirements.txt
-
-# COPY app.py .
-# ENV PORT=7860
-# CMD ["streamlit", "run", "app.py", "--server.port=7860", "--server.address=0.0.0.0"]
-
-FROM python:3.11-slim
+FROM python:3.12-slim
 
 # System deps
 RUN apt-get update && apt-get install -y --no-install-recommends \

app.py

@@ -3,6 +3,8 @@ from typing import Optional, Tuple
 import requests
 from PIL import Image, ImageOps, ImageDraw
 import streamlit as st
+from streamlit_mic_recorder import mic_recorder, speech_to_text
+from gtts import gTTS
 
 # -----------------------
 # Config
@@ -23,7 +25,6 @@ with st.sidebar:
     if _tok.strip():
         HF_TOKEN = _tok.strip()
 
-# Helpers
 def _headers():
     h = {"Accept": "application/json"}
     if HF_TOKEN:
@@ -50,19 +51,15 @@ def pil_from_upload(file) -> Optional[Image.Image]:
         return None
 
 def compress_and_b64(img: Image.Image, max_side: int = 1280, quality: int = 85):
-    img = ImageOps.exif_transpose(img)  # same orientation as backend
+    img = ImageOps.exif_transpose(img)
     w0, h0 = img.size
     scale = max(w0, h0) / max_side if max(w0, h0) > max_side else 1.0
-    if scale > 1.0:
-        img_proc = img.resize((int(w0/scale), int(h0/scale)))
-    else:
-        img_proc = img
+    img_proc = img.resize((int(w0/scale), int(h0/scale))) if scale > 1.0 else img
 
     buf = io.BytesIO()
     img_proc.save(buf, format="JPEG", quality=quality, optimize=True)
     b64 = base64.b64encode(buf.getvalue()).decode()
-    return b64, img_proc, (w0, h0), img_proc.size  # also return sizes if you ever want to rescale back
-
+    return b64, img_proc, (w0, h0), img_proc.size
 
 def draw_bbox(img: Image.Image, bbox: list[int], color=(0, 255, 0), width: int = 4) -> Image.Image:
     out = img.copy()
@@ -71,6 +68,173 @@ def draw_bbox(img: Image.Image, bbox: list[int], color=(0, 255, 0), width: int =
     draw.rectangle([x1, y1, x2, y2], outline=color, width=width)
     return out
 
+def tts_gtts_bytes(text: str, lang: str = "en", tld: str = "com", slow: bool = False) -> bytes:
+    buf = io.BytesIO()
+    gTTS(text=text, lang=lang, tld=tld, slow=slow).write_to_fp(buf)
+    return buf.getvalue()
+
+# --- Chat state helpers ---
+if "chat" not in st.session_state:
+    st.session_state.chat = []   # list of {"role": "user"|"assistant", "text": str}
+
+def add_chat(role: str, text: str):
+    st.session_state.chat.append({"role": role, "text": text})
+
+def render_chat_transcript():
+    st.subheader("🗨️ Conversation")
+    for m in st.session_state.chat[-100:]:  # show last 100 turns
+        with st.chat_message("user" if m["role"]=="user" else "assistant"):
+            st.markdown(m["text"])
+
+# -----------------------
+# Small UI renderers (so we can reorder cleanly)
+# -----------------------
+def render_examples_buttons(key_prefix: str = "main"):
+    cols = st.columns(2)
+    examples = [
+        "What is total sales (revenue) of Ramesh?",
+        "Revenue for BLR on 2025-09-06",
+        "Monthly revenue for Electronics in BLR for 2025-09",
+        "Top 5 SKUs by revenue in HYD on 2025-09-06 (include category)",
+        "Ramesh's total sales in NCR on 2025-09-06",
+    ]
+    for i, ex in enumerate(examples):
+        if cols[i % 2].button(ex, key=f"{key_prefix}_ex_{i}"):
+            st.session_state["q_text"] = ex
+            st.rerun()
+
+
+def render_bi_question_section(section_heading=True, key_prefix: str = "main"):
+    if section_heading:
+        st.subheader("3) Ask a BI question")
+
+    with st.expander("Examples", expanded=False):
+        render_examples_buttons(key_prefix=key_prefix)
+
+    # Use a unique key for the textarea.
+    default_q = st.session_state.get("q_text", "What is total sales (revenue) of Ramesh?")
+    q_text = st.text_area("Your question", value=default_q, height=100,
+                          key=f"{key_prefix}_q_textarea")
+
+    with st.expander("Optional: visual context (JSON)", expanded=False):
+        vis_str = st.text_area("visual_ctx", value="{}", height=80,
+                               key=f"{key_prefix}_vis_text")
+
+    try:
+        visual_ctx = json.loads(vis_str) if vis_str.strip() else {}
+    except Exception:
+        visual_ctx = {}
+        st.warning("`visual_ctx` is not valid JSON; ignored.")
+
+    if st.button("Ask", key=f"{key_prefix}_ask"):
+        payload = {
+            "user_id": st.session_state.user_name or None,
+            "text": q_text.strip(),
+            "visual_ctx": visual_ctx,
+        }
+        try:
+            with st.spinner("Querying…"):
+                r = post_json("/query", payload)
+
+            if r.ok:
+                resp = r.json()
+                answer = resp.get("answer_text", "")
+                st.success(answer)
+                st.session_state["last_answer_text"] = answer
+
+                sqls = [c[4:] for c in resp.get("citations", [])
+                        if isinstance(c, str) and c.startswith("sql:")]
+                if sqls:
+                    with st.expander("SQL used", expanded=True):
+                        st.code(sqls[0], language="sql")
+                        for s in sqls[1:]:
+                            st.code(s, language="sql")
+
+                if resp.get("metrics"):
+                    with st.expander("Metrics", expanded=False):
+                        st.json(resp["metrics"])
+                if resp.get("chart_refs"):
+                    with st.expander("Charts", expanded=False):
+                        st.json(resp["chart_refs"])
+                if "uncertainty" in resp:
+                    st.caption(f"Uncertainty: {resp['uncertainty']:.2f}")
+            else:
+                try:
+                    err = r.json()
+                except Exception:
+                    err = {"detail": r.text}
+                st.error(f"Backend error {r.status_code}: {err.get('detail')}")
+                if "SQLGenTool disabled" in str(err.get("detail", "")):
+                    st.info("Add your Hugging Face token in the sidebar (or set the HF_TOKEN env var).")
+        except Exception as e:
+            st.error(f"Request error: {e}")
+
+def render_voice_to_text():
+    st.caption("Voice → Text (browser STT)")
+    c1, c2 = st.columns([2, 1])
+    with c1:
+        st.write("Click to speak; recognized text will fill the question box.")
+    with c2:
+        stt_lang = st.selectbox("STT language", ["en", "hi"], index=0, key="stt_lang_dd")
+        if "prev_stt_lang" not in st.session_state:
+            st.session_state["prev_stt_lang"] = stt_lang
+        elif st.session_state["prev_stt_lang"] != stt_lang:
+            st.session_state["prev_stt_lang"] = stt_lang
+            st.rerun()
+
+    stt_text = speech_to_text(
+        language=st.session_state.get("stt_lang_dd", "en"),
+        use_container_width=True,
+        just_once=True,
+        start_prompt="🎙️ Start recording",
+        stop_prompt="⏹️ Stop recording",
+        key="stt_main_btn",
+    )
+
+    if stt_text:
+        st.session_state["q_text"] = stt_text
+        st.success(f"Recognized: {stt_text}")
+        st.rerun()
+
+    st.markdown("---")
+    st.caption("Optional: record & play raw audio (no transcription)")
+    rec = mic_recorder(
+        start_prompt="🎙️ Start",
+        stop_prompt="⏹️ Stop",
+        just_once=True,
+        key="mic_raw_btn",
+    )
+    if rec and rec.get("bytes"):
+        st.audio(rec["bytes"], format="audio/wav")
+
+def render_tts_controls():
+    st.markdown("---")
+    st.caption("Text → Voice (gTTS)")
+    tts_lang = st.selectbox("TTS language", ["en", "hi"], index=0, key="tts_lang_dd")
+    tld_label = st.selectbox(
+        "Accent / region (tld)",
+        ["Default (.com)", "India (.co.in)", "US (.us)", "UK (.co.uk)"],
+        index=1,
+        key="tts_tld_dd"
+    )
+    tld_map = {
+        "Default (.com)": "com",
+        "India (.co.in)": "co.in",
+        "US (.us)": "us",
+        "UK (.co.uk)": "co.uk",
+    }
+    
+    if st.button("🔊 Speak last answer", key="tts_speak_btn"):
+        ans = st.session_state.get("last_answer_text", "")
+        if not ans.strip():
+            st.warning("Ask a question first to generate an answer.")
+        else:
+            try:
+                mp3 = tts_gtts_bytes(ans, lang=tts_lang, tld=tld_map[tld_label], slow=False)
+                st.audio(mp3, format="audio/mp3")
+            except Exception as e:
+                st.error(f"TTS error: {e}")
+
 # -----------------------
 # UI
 # -----------------------
@@ -91,48 +255,9 @@ if not ok and info:
 if "user_name" not in st.session_state:
     st.session_state.user_name = "mohit"
 
-# # -----------------------
-# # 1) Enroll / Upsert face
-# # -----------------------
-# with st.expander("1) Enroll / Upsert face (optional)", expanded=False):
-#     st.session_state.user_name = st.text_input("User name", value=st.session_state.user_name, key="user_name_input")
-#     c1, c2 = st.columns(2)
-#     with c1:
-#         upload_img = st.file_uploader("Upload a face image (jpg/png)", type=["jpg","jpeg","png"])
-#     with c2:
-#         cam_img = st.camera_input("Or capture from camera")
-
-#     chosen = None
-#     if cam_img is not None:
-#         chosen = pil_from_upload(cam_img)
-#     elif upload_img is not None:
-#         chosen = pil_from_upload(upload_img)
-
-#     if st.button("Upsert to local index"):
-#         if not chosen:
-#             st.error("Please provide an image (upload or camera).")
-#         elif not st.session_state.user_name.strip():
-#             st.error("Please enter a user name.")
-#         else:
-#             buf = io.BytesIO()
-#             chosen.save(buf, format="JPEG", quality=90)
-#             buf.seek(0)
-#             try:
-#                 with st.spinner("Upserting…"):
-#                     resp = post_multipart(
-#                         "/index/upsert_image",
-#                         files={"image": ("face.jpg", buf, "image/jpeg")},
-#                         params={"user": st.session_state.user_name.strip()},
-#                     )
-#                 if resp.ok:
-#                     st.success("Face vector upserted ✅")
-#                     st.json(resp.json())
-#                 else:
-#                     st.error(f"Upsert failed: {resp.status_code}")
-#                     st.text(resp.text)
-#             except Exception as e:
-#                 st.error(f"Request error: {e}")
-
+# -----------------------
+# 1) Bulk enroll via ZIP (Images/<UserName>/*)
+# -----------------------
 with st.expander("1) Bulk enroll via ZIP (Images/<UserName>/*)", expanded=False):
     zip_up = st.file_uploader("Upload ZIP", type=["zip"], key="zip_enroll")
     if st.button("Enroll ZIP"):
@@ -152,6 +277,9 @@ with st.expander("1) Bulk enroll via ZIP (Images/<UserName>/*)", expanded=False)
             except Exception as e:
                 st.error(f"Request error: {e}")
 
+# -----------------------
+# 2) Identify from image
+# -----------------------
 with st.expander("2) Identify from image", expanded=False):
     col_u, col_c = st.columns(2)
     with col_u:
@@ -165,13 +293,7 @@ with st.expander("2) Identify from image", expanded=False):
     elif test_upload is not None:
         test_img = pil_from_upload(test_upload)
 
-    # --- helpers -------------------------------------------------------------
     def encode_for_backend(img: Image.Image):
-        """
-        Returns (b64_str, sent_img) where sent_img is decoded from the exact
-        bytes we POST to the backend so bbox coords align 1:1.
-        Works whether compress_and_b64 returns a str or a tuple/list.
-        """
         b64_out = compress_and_b64(img)
         if isinstance(b64_out, (tuple, list)):
             b64_str = b64_out[0]
@@ -189,7 +311,6 @@ with st.expander("2) Identify from image", expanded=False):
         return b64_str, sent_img
 
     def draw_many(img: Image.Image, dets: list[dict]) -> Image.Image:
-        from PIL import ImageDraw
         out = img.copy()
         draw = ImageDraw.Draw(out)
         for d in dets:
@@ -197,15 +318,11 @@ with st.expander("2) Identify from image", expanded=False):
             name = d.get("decision", "Unknown")
             score = float(d.get("best_score", 0.0))
             label = f"{name} ({score:.3f})"
-
-            # box
             draw.rectangle([x1, y1, x2, y2], outline=(0, 255, 0), width=3)
-
             try:
                 tb = draw.textbbox((x1, y1), label)
                 tw, th = tb[2] - tb[0], tb[3] - tb[1]
             except Exception:
-                # fallback: approximate height
                 tw, th = max(60, len(label) * 7), 14
             by1 = max(0, y1 - th - 6)
             draw.rectangle([x1, by1, x1 + tw + 6, y1], fill=(0, 0, 0))
@@ -217,7 +334,7 @@ with st.expander("2) Identify from image", expanded=False):
             st.warning("Please provide an image first.")
         else:
             try:
-                b64, sent_img = encode_for_backend(test_img)  # <- draw on sent image
+                b64, sent_img = encode_for_backend(test_img)
                 with st.spinner("Identifying…"):
                     r = post_json("/identify_many", {"image_b64": b64, "top_k": 3})
                 if not r.ok:
@@ -234,74 +351,76 @@ with st.expander("2) Identify from image", expanded=False):
             except Exception as e:
                 st.error(f"Request error: {e}")
 
-
 # -----------------------
-# 3) Ask a BI question
+# 2.5) Voice mode (frontend-only) with requested order
 # -----------------------
-st.subheader("3) Ask a BI question")
+st.subheader("🎙️ Voice mode (optional)")
+with st.expander("Speak your question / hear the answer", expanded=True):
+    # (1) Voice → Text first
+    render_voice_to_text()
 
-with st.expander("Examples", expanded=False):
-    cols = st.columns(2)
-    examples = [
-        "What is total sales (revenue) of Ramesh?",
-        "Revenue for BLR on 2025-09-06",
-        "Monthly revenue for Electronics in BLR for 2025-09",
-        "Top 5 SKUs by revenue in HYD on 2025-09-06 (include category)",
-        "Ramesh's total sales in NCR on 2025-09-06",
-    ]
-    for i, ex in enumerate(examples):
-        if cols[i % 2].button(ex, key=f"ex_{i}"):
-            st.session_state.setdefault("q_text", ex)
-
-default_q = st.session_state.get("q_text", "What is total sales (revenue) of Ramesh?")
-q_text = st.text_area("Your question", value=default_q, height=100)
-
-with st.expander("Optional: visual context (JSON)", expanded=False):
-    vis_str = st.text_area("visual_ctx", value="{}", height=80)
-try:
-    visual_ctx = json.loads(vis_str) if vis_str.strip() else {}
-except Exception:
-    visual_ctx = {}
-    st.warning("`visual_ctx` is not valid JSON; ignored.")
-
-if st.button("Ask"):
-    payload = {
-        "user_id": st.session_state.user_name or None,
-        "text": q_text.strip(),
-        "visual_ctx": visual_ctx,
-    }
-    try:
-        with st.spinner("Querying…"):
-            r = post_json("/query", payload)
+    # (2) Ask a BI question (same logic as main section)
+    render_bi_question_section(section_heading=False, key_prefix="voice")
+
+    # (3) Listen response (TTS button)
+    render_tts_controls()
 
+# -----------------------
+# 2.6) Talk → Ask → Speak (voice chat with transcript)
+# -----------------------
+st.subheader("🗣️ Talk → Ask → Speak")
+c_left, c_right = st.columns([2, 3])
+with c_left:
+    st.caption("Press to speak; we'll answer, speak back, and log the chat below.")
+with c_right:
+    # voice settings reuse your TTS controls' state if present; else defaults
+    tts_lang = st.session_state.get("tts_lang_dd", "en")
+    tld_map = {"Default (.com)": "com", "India (.co.in)": "co.in", "US (.us)": "us", "UK (.co.uk)": "co.uk"}
+    tld_label = st.session_state.get("tts_tld_dd", "India (.co.in)")
+
+# Mic widget (one utterance per click)
+spoken = speech_to_text(
+    language=st.session_state.get("stt_lang_dd", "en"),
+    use_container_width=True,
+    just_once=True,
+    start_prompt="🎙️ Speak",
+    stop_prompt="⏹️ Stop",
+    key="stt_conv_btn",
+)
+
+if spoken:
+    user_text = spoken.strip()
+    if user_text:
+        add_chat("user", user_text)
+        payload = {"user_id": st.session_state.user_name or None, "text": user_text, "visual_ctx": {}}
+        with st.spinner("Thinking…"):
+            r = post_json("/query", payload)
         if r.ok:
             resp = r.json()
-            st.success(resp.get("answer_text", ""))
-
-            sqls = [c[4:] for c in resp.get("citations", []) if isinstance(c, str) and c.startswith("sql:")]
-            if sqls:
-                with st.expander("SQL used", expanded=True):
-                    st.code(sqls[0], language="sql")
-                    if len(sqls) > 1:
-                        for s in sqls[1:]:
-                            st.code(s, language="sql")
-
-            if resp.get("metrics"):
-                with st.expander("Metrics", expanded=False):
-                    st.json(resp["metrics"])
-            if resp.get("chart_refs"):
-                with st.expander("Charts", expanded=False):
-                    st.json(resp["chart_refs"])
-            if "uncertainty" in resp:
-                st.caption(f"Uncertainty: {resp['uncertainty']:.2f}")
-
+            answer = resp.get("answer_text", "").strip()
+            add_chat("assistant", answer or "_(no rows)_")
+            st.session_state["last_answer_text"] = answer
+            # speak the answer
+            try:
+                mp3 = tts_gtts_bytes(answer or "I have no rows to report.",
+                                     lang=tts_lang,
+                                     tld=tld_map.get(tld_label, "co.in"),
+                                     slow=False)
+                st.audio(mp3, format="audio/mp3")
+            except Exception as e:
+                st.error(f"TTS error: {e}")
         else:
             try:
                 err = r.json()
             except Exception:
                 err = {"detail": r.text}
+            add_chat("assistant", f"Backend error {r.status_code}: {err.get('detail')}")
             st.error(f"Backend error {r.status_code}: {err.get('detail')}")
-            if "SQLGenTool disabled" in str(err.get("detail", "")):
-                st.info("Add your Hugging Face token in the sidebar (or set the HF_TOKEN env var).")
-    except Exception as e:
-        st.error(f"Request error: {e}")
+
+# Show running transcript
+render_chat_transcript()
+
+# -----------------------
+# 3) Ask a BI question (also kept as a main section for non-voice users)
+# -----------------------
+# render_bi_question_section(section_heading=True, key_prefix="main")

requirements.txt

@@ -1,3 +1,5 @@
 streamlit
 requests
-Pillow
+Pillow
+streamlit-mic-recorder
+gTTS