Upload 10 files

app_pages/image_analyser.py

@@ -0,0 +1,129 @@
+from __future__ import annotations
+import os, base64, json
+import streamlit as st
+from typing import Any, Dict
+from openai import OpenAI
+from dotenv import load_dotenv
+
+from database.operations import insert_image_analysis
+from database.connections import get_image_collection
+from schema.pydantic_schema_image import AdAnalysis
+from prompt.image_analyzer_prompt import SYSTEM_PROMPT, USER_PROMPT_TEMPLATE
+from components.image_render_analysis import render_analyzer_results
+
+load_dotenv()
+client = OpenAI(api_key=os.getenv("OPENAI_API_KEY"))
+
+
+def get_analysis(img_bytes: bytes, img_ext: str) -> Dict[str, Any]:
+    b64 = base64.b64encode(img_bytes).decode("utf-8")
+    data_uri = f"data:image/{img_ext};base64,{b64}"
+
+    messages = [
+        {"role": "system", "content": [{"type": "text", "text": SYSTEM_PROMPT}]},
+        {
+            "role": "user",
+            "content": [
+                {"type": "text", "text": USER_PROMPT_TEMPLATE},
+                {"type": "image_url", "image_url": {"url": data_uri}},
+            ],
+        },
+    ]
+
+    completion = client.chat.completions.parse(
+        model="gpt-4o",
+        messages=messages,
+        response_format=AdAnalysis,
+    )
+
+    ad_analysis = completion.choices[0].message.parsed
+    return ad_analysis.model_dump()
+
+
+def render_image_analyser_page(uid: str) -> None:
+    st.subheader("Image Analyzer")
+
+    category = st.text_input("Category", key="ia_category")
+    uploaded = st.file_uploader(
+        "Upload image",
+        type=["jpg", "jpeg", "png", "webp"],
+        key="ia_upload",
+    )
+
+    img_bytes, img_ext, file_name, thumb_b64 = None, "jpg", None, ""
+
+    if uploaded is not None:
+        img_bytes = uploaded.read()
+        file_name = uploaded.name
+        if "." in file_name:
+            img_ext = file_name.rsplit(".", 1)[-1].lower()
+
+        thumb_b64 = base64.b64encode(img_bytes).decode("utf-8")
+        st.caption("Preview")
+        st.markdown(
+            f"""
+            <img src="data:image/{img_ext};base64,{thumb_b64}" 
+                 alt="Uploaded image" 
+                 style="max-width: 400px; border-radius: 8px;"/>
+            """,
+            unsafe_allow_html=True,
+        )
+
+    go = st.button("Analyze", key="ia_analyse")
+
+    if go:
+        if not img_bytes or not category.strip():
+            st.warning("Please provide a category and upload an image.")
+        else:
+            try:
+                with st.spinner("Analyzing image..."):
+                    result = get_analysis(img_bytes, img_ext)
+                st.session_state["analysis_result"] = result
+                st.session_state["file_name"] = file_name
+                st.session_state["thumb_b64"] = thumb_b64
+                st.session_state["category"] = category
+            except Exception as e:
+                st.error(f"Analysis failed: {e}")
+
+
+
+    if "analysis_result" in st.session_state:
+        result = st.session_state["analysis_result"]
+        file_name = st.session_state.get("file_name", "uploaded_image")
+        thumb_b64 = st.session_state.get("thumb_b64", "")
+        category = st.session_state.get("category", "general")
+
+        st.success("Analysis completed successfully")
+        render_analyzer_results(result)
+
+        res = json.dumps(result, indent=2, ensure_ascii=False)
+        col1, col2 = st.columns(2)
+
+        with col1:
+            st.download_button(
+                "Download JSON",
+                data=res.encode("utf-8"),
+                file_name=f"{file_name}_analysis.json",
+                mime="application/json",
+                use_container_width=True,
+            )
+
+        with col2:
+            if st.download_button("Save to DB",
+                                  data=res.encode("utf-8"),
+                                  file_name=f"{file_name}_analysis.json",
+                                  mime="application/json",
+                                  use_container_width=True):
+                try:
+                    doc_id = insert_image_analysis(
+                        image_name=file_name,
+                        response=result,
+                        category=category,
+                        created_by=uid,
+                        analyzer_model="gpt-4o",
+                        thumbnail=thumb_b64,
+                    )
+                    st.success(f"Saved to AI Library )")
+
+                except Exception as e:
+                    st.error(f"Failed to save to DB: {e}")

app_pages/image_analyser_library.py

@@ -0,0 +1,103 @@
+from __future__ import annotations
+
+import json
+from datetime import datetime, timedelta, date
+from typing import Any, Dict, List, Optional
+import streamlit as st
+
+from database.operations import find_image_analyses, list_image_categories
+from components.image_render_analysis import render_analyzer_results
+
+def _coerce_dt(val: Any) -> Optional[datetime]:
+    if isinstance(val, datetime):
+        return val
+    try:
+        return datetime.fromisoformat(str(val))
+    except Exception:
+        return None
+
+
+def _label_for_item(doc: Dict[str, Any]) -> str:
+    """Shown in the wide dropdown."""
+    ts = _coerce_dt(doc.get("created_at"))
+    ts_s = ts.strftime("%Y-%m-%d %H:%M") if ts else "Unknown time"
+    cat = doc.get("category") or "—"
+    model = doc.get("analyzer_model") or "—"
+    return f"{ts_s} · {cat} · {model}"
+
+def render_image_analysis_library(uid: Optional[str] = None, prefix: str = "img_ana_lib") -> None:
+    st.subheader("Image Analysis Library")
+
+    today = datetime.utcnow().date()
+    default_start = today - timedelta(days=30)
+
+    c1, c2, c3 = st.columns([1, 1, 1])
+    with c1:
+        start_date: date = st.date_input("Start date", value=default_start, key=f"{prefix}_start")
+    with c2:
+        end_date: date = st.date_input("End date", value=today, key=f"{prefix}_end")
+    with c3:
+        try:
+            cats: List[str] = list_image_categories(created_by=uid)  # <-- filter per user
+            if "All" not in cats:
+                cats = ["All"] + cats
+        except Exception:
+            cats = ["All"]
+        category = st.selectbox("Category", options=cats, index=0, key=f"{prefix}_cat")
+
+    st.markdown("---")
+
+    try:
+        start_dt = datetime.combine(start_date, datetime.min.time())
+        end_dt = datetime.combine(end_date + timedelta(days=1), datetime.min.time())
+        query_cat = None if (not category or category == "All") else category
+        docs: List[Dict[str, Any]] = find_image_analyses(
+            category=query_cat, start_date=start_dt, end_date=end_dt, limit=200, created_by=uid
+        )
+    except Exception as e:
+        st.error(f"Failed to load image analyses: {e}")
+        return
+
+    if not docs:
+        st.info("No image analysis for the selected filters.")
+        return
+
+    labels = [_label_for_item(d) for d in docs]
+    selected_label = st.selectbox(
+        "Select an analysis",
+        options=labels,
+        index=0,
+        key="img_lib_sel",
+    )
+    sel_idx = labels.index(selected_label) if selected_label in labels else 0
+    doc = docs[sel_idx]
+
+    thumb_b64 = doc.get("thumbnail")
+    if thumb_b64:
+        try:
+            st.image(
+                f"data:image/jpeg;base64,{thumb_b64}",
+                caption="Thumbnail",
+                width=220,
+            )
+        except Exception:
+            pass
+
+
+    analysis = doc.get("results") or {}
+    if analysis:
+        render_analyzer_results(analysis)
+        try:
+            res = json.dumps(analysis, indent=2, ensure_ascii=False)
+            st.download_button(
+                "Download JSON",
+                data=res.encode("utf-8"),
+                file_name=f"image_analysis_{doc.get('_id','item')}.json",
+                mime="application/json",
+                use_container_width=True,
+                key="img_lib_json_dl",
+            )
+        except Exception:
+            pass
+    else:
+        st.info("No analysis  stored for this item.")

app_pages/image_generation.py

@@ -6,19 +6,24 @@ from generator_function.image_processor import process_zip_and_generate_images
 logging.basicConfig(level=logging.INFO, format="%(asctime)s [%(levelname)s] %(message)s")
 logger = logging.getLogger(__name__)
 
+
 def _zip_gallery_images(gallery_items):
-    if not gallery_items: return None
+    if not gallery_items:
+        return None
     image_urls = [item[0] if isinstance(item, tuple) else item for item in gallery_items]
     temp_dir = tempfile.mkdtemp()
     try:
         zip_path = tempfile.NamedTemporaryFile(delete=False, suffix=".zip").name
         for i, url in enumerate(image_urls):
             try:
-                ext = url.split('?')[0].split('.')[-1]; ext = ext if ext and len(ext) <= 5 else "png"
+                ext = url.split('?')[0].split('.')[-1]
+                ext = ext if ext and len(ext) <= 5 else "png"
                 file_path = os.path.join(temp_dir, f"image_{i}.{ext}")
                 if url.startswith(("http://", "https://")):
-                    resp = requests.get(url, timeout=10); resp.raise_for_status()
-                    with open(file_path, "wb") as f: f.write(resp.content)
+                    resp = requests.get(url, timeout=10)
+                    resp.raise_for_status()
+                    with open(file_path, "wb") as f:
+                        f.write(resp.content)
                 elif os.path.exists(url):
                     shutil.copy(url, file_path)
             except Exception as e:
@@ -33,26 +38,42 @@ def _zip_gallery_images(gallery_items):
     finally:
         shutil.rmtree(temp_dir, ignore_errors=True)
 
+
 def render_bulk_image_generator(prefix: str = "ig_img"):
-    zip_file = st.file_uploader("Upload Zip or Single File", type=["zip", "png", "jpg", "jpeg"], key=f"{prefix}_upload")
+    zip_file = st.file_uploader(
+        "Upload Zip or Single File",
+        type=["zip", "png", "jpg", "jpeg"],
+        key=f"{prefix}_upload"
+    )
     category = st.text_input("Category", key=f"{prefix}_category")
-    col1, col2, col3, col4, col5, col6 = st.columns([2,2.5,2.5,2.5,2.5,2])
-    with col1:  blur = st.checkbox("Blur Image", key=f"{prefix}_blur")
-    with col2:  size = st.selectbox("Image Size", ["auto","1024x1024","1536x1024","1024x1536"], key=f"{prefix}_size")
-    with col3:  quality = st.selectbox("Quality", ["auto","low","medium"], key=f"{prefix}_quality")
-    with col4:  sentiment = st.selectbox("Sentiment", ["as original image","positive","negative"], key=f"{prefix}_sentiment")
-    with col5:  platform = st.selectbox("Platform", ["Facebook","Native","Newsbreak","Google Display Network"], key=f"{prefix}_platform")
-    with col6:  num_images = st.slider("No. of Images to be generated:", 1, 10, value=2, step=1, key=f"{prefix}_num_images")
+
+    col1, col2, col3, col4, col5, col6 = st.columns([2, 2.5, 2.5, 2.5, 2.5, 2])
+    with col1:
+        blur = st.checkbox("Blur Image", key=f"{prefix}_blur")
+    with col2:
+        size = st.selectbox("Image Size", ["auto", "1024x1024", "1536x1024", "1024x1536"], key=f"{prefix}_size")
+    with col3:
+        quality = st.selectbox("Quality", ["auto", "low", "medium"], key=f"{prefix}_quality")
+    with col4:
+        sentiment = st.selectbox("Sentiment", ["as original image", "positive", "negative"], key=f"{prefix}_sentiment")
+    with col5:
+        platform = st.selectbox("Platform", ["Facebook", "Native", "Newsbreak", "Google Display Network"], key=f"{prefix}_platform")
+    with col6:
+        num_images = st.slider("No. of Images to be generated:", 1, 10, value=2, step=1, key=f"{prefix}_num_images")
     user_prompt = st.text_area("User Prompt", height=100, key=f"{prefix}_user_prompt")
 
-    colA, colB, colC = st.columns([1,1,1])
-    with colA: demo_btn = st.button("Generate Demo Image", key=f"{prefix}_demo")
-    with colB: gen_all_btn = st.button("Generate All Images", key=f"{prefix}_gen_all")
-    with colC: download_btn = st.button("Download All", key=f"{prefix}_download_all")
+    colA, colB, colC = st.columns([1, 1, 1])
+    with colA:
+        demo_btn = st.button("Generate Demo Image", key=f"{prefix}_demo")
+    with colB:
+        gen_all_btn = st.button("Generate All Images", key=f"{prefix}_gen_all")
+    with colC:
+        download_btn = st.button("Download All", key=f"{prefix}_download_all")
 
     gallery_key = f"{prefix}_gallery"
     gallery = st.session_state.setdefault(gallery_key, [])
 
+
     if demo_btn or gen_all_btn:
         if zip_file and category and user_prompt:
             with st.spinner(" Generating image variations..."):
@@ -98,7 +119,11 @@ def render_bulk_image_generator(prefix: str = "ig_img"):
         else:
             st.warning("Please upload a file and fill all required fields.")
 
+    # ----------------------------
+    # Download all images
+    # ----------------------------
     if download_btn:
+        with st.spinner(" Preparing  for download..."):
             zip_path = _zip_gallery_images(st.session_state.get(gallery_key, []))
             if zip_path:
                 with open(zip_path, "rb") as f:
@@ -115,4 +140,4 @@ def render_bulk_image_generator(prefix: str = "ig_img"):
                 except Exception:
                     pass
             else:
-                st.warning("No images to zip and download.")
+                st.warning("No images to zip and download.")

app_pages/image_generation_library.py

@@ -1,16 +1,24 @@
 from __future__ import annotations
 
 from datetime import datetime, timedelta, date
-from typing import Any, Dict, List
+from typing import Any, Dict, List,Optional
 
 import streamlit as st
 
 from database.connections import get_results_collection
 
 
-def _distinct_options(col, field: str, source: str, uid: str) -> List[str]:
+def _distinct_options(col, field: str, source: str, created_by: Optional[str] = None) -> List[str]:
     try:
-        vals = col.distinct(field, {"source": source, "created_by": uid})
+        q: Dict[str, Any] = {"source": source}
+        if created_by:
+            q["created_by"] = created_by
+
+        if field == "platform":
+            vals = col.distinct("settings.platform", q) + col.distinct("platform", q)
+        else:
+            vals = col.distinct(field, q)
+
         vals = [v for v in vals if v not in (None, "", [])]
         vals = sorted(set(vals))
         return ["All"] + vals if vals else ["All"]
@@ -18,16 +26,18 @@ def _distinct_options(col, field: str, source: str, uid: str) -> List[str]:
         return ["All"]
 
 
+
 def _query_docs(
-        col,
-        source: str,
-        start_d: date,
-        end_d: date,
-        category: str,
-        platform: str,
-        uid: str,
-        limit: int = 200,
+    col,
+    source: str,
+    start_d: date,
+    end_d: date,
+    category: str,
+    platform: str,
+    uid: str,
+    limit: int = 200,
 ) -> List[Dict[str, Any]]:
+
     try:
         start_dt = datetime.combine(start_d, datetime.min.time())
         end_dt = datetime.combine(end_d + timedelta(days=1), datetime.min.time())
@@ -39,7 +49,13 @@ def _query_docs(
         if category and category != "All":
             q["category"] = category
         if platform and platform != "All":
-            q["platform"] = platform
+            q["$or"] = [
+                {"platform": platform},
+                {"settings.platform": platform},
+                {"provider_settings.platform": platform},
+                {"metadata.platform": platform},
+            ]
+
         cursor = col.find(q).sort("created_at", -1).limit(limit)
         return list(cursor)
     except Exception:
@@ -64,15 +80,14 @@ def _render_grid(docs: List[Dict[str, Any]]) -> None:
     for i, (url, meta) in enumerate(items):
         with cols[i % 4]:
             try:
-                st.image(url, width="content")
+                st.image(url, use_container_width=True)
                 cat = meta.get("category") or "—"
-
                 plat = (
-                        meta.get("platform")
-                        or (meta.get("settings") or {}).get("platform")
-                        or (meta.get("provider_settings") or {}).get("platform")
-                        or (meta.get("metadata") or {}).get("platform")
-                        or "—"
+                    meta.get("platform")
+                    or (meta.get("settings") or {}).get("platform")
+                    or (meta.get("provider_settings") or {}).get("platform")
+                    or (meta.get("metadata") or {}).get("platform")
+                    or "—"
                 )
                 ts = meta.get("created_at")
                 ts_str = ts.strftime("%Y-%m-%d %H:%M UTC") if isinstance(ts, datetime) else "—"
@@ -81,7 +96,8 @@ def _render_grid(docs: List[Dict[str, Any]]) -> None:
                 st.error("Failed to load image")
 
 
-def render_image_variations_library(uid: str) -> None:
+def render_image_variations_library(uid: str, prefix: str = "img_var") -> None:
+
     col = get_results_collection()
     if col is None:
         st.warning("Database not available. Set MONGO_URI and restart.")
@@ -92,19 +108,20 @@ def render_image_variations_library(uid: str) -> None:
 
     c1, c2 = st.columns(2)
     with c1:
-        start_date = st.date_input("Start date", value=default_start, key="img_var_start")
+        start_date = st.date_input("Start date", value=default_start, key=f"{prefix}_start")
     with c2:
-        end_date = st.date_input("End date", value=today, key="img_var_end")
+        end_date = st.date_input("End date", value=today, key=f"{prefix}_end")
 
-    cat_opts = _distinct_options(col, "category", source="variation", uid=uid)
-    plat_opts = _distinct_options(col, "platform", source="variation", uid=uid)
+    cat_opts = _distinct_options(col, "category", source="variation")
+    plat_opts = _distinct_options(col, "platform", source="variation")
 
     r1, r2 = st.columns(2)
     with r1:
-        category = st.selectbox("Category", options=cat_opts, key="img_var_cat")
+        category = st.selectbox("Category", options=cat_opts, key=f"{prefix}_cat")
     with r2:
-        platform = st.selectbox("Platform", options=plat_opts, key="img_var_plat")
+        platform = st.selectbox("Platform", options=plat_opts, key=f"{prefix}_plat")
 
     st.markdown("---")
     docs = _query_docs(col, "variation", start_date, end_date, category, platform, uid=uid)
-    _render_grid(docs)
+    _render_grid(docs)
+

app_pages/script_library.py

@@ -1,11 +1,13 @@
 from datetime import datetime, timedelta
 from typing import Any, Dict
 
-from database.operations import find_script_results
 import streamlit as st
 import pandas as pd
 
-def render_script_library(uid: str) ->None:
+from database.operations import find_script_results
+
+
+def render_script_library(uid: str, prefix: str = "scripts") -> None:
     st.subheader("Generated Scripts")
 
     today = datetime.utcnow().date()
@@ -13,9 +15,9 @@ def render_script_library(uid: str) ->None:
 
     f1, f2, _ = st.columns([1, 1, 1.2])
     with f1:
-        start_date_scripts = st.date_input("Start date", value=default_start, key="scripts_start")
+        start_date_scripts = st.date_input("Start date", value=default_start, key=f"{prefix}_start")
     with f2:
-        end_date_scripts = st.date_input("End date", value=today, key="scripts_end")
+        end_date_scripts = st.date_input("End date", value=today, key=f"{prefix}_end")
 
     if "scripts_page" not in st.session_state:
         st.session_state.scripts_page = 0
@@ -23,6 +25,7 @@ def render_script_library(uid: str) ->None:
     start_dt = datetime.combine(start_date_scripts, datetime.min.time())
     end_dt = datetime.combine(end_date_scripts + timedelta(days=1), datetime.min.time())
 
+
     records, total_count = find_script_results(
         start_date=start_dt,
         end_date=end_dt,
@@ -33,7 +36,7 @@ def render_script_library(uid: str) ->None:
 
     if total_count == 0 or not records:
         st.info("No script generations for the selected filters.")
-        st.stop()
+        return
 
     start_idx = st.session_state.scripts_page * 20 + 1
     end_idx = min(start_idx + len(records) - 1, total_count)
@@ -46,46 +49,49 @@ def render_script_library(uid: str) ->None:
         return f"{ts_s} · {vn}"
 
     options = [_label(d) for d in records]
-    selected_label = st.selectbox("Select generated script", options=options, index=0, key="scripts_sel_dropdown")
+    selected_label = st.selectbox("Select generated script", options=options, index=0, key=f"{prefix}_sel_dropdown")
     sel_idx = options.index(selected_label) if selected_label in options else 0
     doc = records[sel_idx]
 
+
     if doc.get("thumbnail"):
         try:
             st.image("data:image/jpeg;base64," + doc["thumbnail"], width=160, caption="Thumbnail")
         except Exception:
             pass
 
+
     json_response = doc.get("response")
     if not json_response:
         st.info("No variations saved.")
-    else:
-        all_tables = []
-        if isinstance(json_response, list):
-            for round_idx, round_data in enumerate(json_response, 1):
-                st.markdown(f"#### Generation Round {round_idx}")
-                st.text_input(
-                    "Prompt used:",
-                    round_data.get("prompt_used", "N/A"),
-                    disabled=True,
-                    key=f"hist_prompt_{doc.get('_id')}_{round_idx}",
-                )
-                for i, variation in enumerate(round_data.get("variations", []), 1):
-                    st.markdown(f"**Variation {i}: {variation.get('variation_name', 'Var')}**")
-                    df = pd.DataFrame(variation.get("script_table", []))
-                    st.table(df)
-                    if not df.empty:
-                        df["Variation"] = variation.get("variation_name", f"Var{i}")
-                        df["Round"] = round_idx
-                        all_tables.append(df)
-
-        if all_tables:
-            csv_scripts = pd.concat(all_tables, ignore_index=True).to_csv(index=False)
-            st.download_button(
-                "Download CSV",
-                data=csv_scripts,
-                file_name=f"{(doc.get('video_name') or doc.get('file_name') or 'scripts')}_scripts.csv",
-                mime="text/csv",
-                use_container_width=True,
-                key="scripts_download_csv",
-            )
+        return
+
+    all_tables = []
+    if isinstance(json_response, list):
+        for round_idx, round_data in enumerate(json_response, 1):
+            st.markdown(f"#### Generation Round {round_idx}")
+            st.text_input(
+                "Prompt used:",
+                round_data.get("prompt_used", "N/A"),
+                disabled=True,
+                key=f"{prefix}_hist_prompt_{doc.get('_id')}_{round_idx}",
+            )
+            for i, variation in enumerate(round_data.get("variations", []), 1):
+                st.markdown(f"**Variation {i}: {variation.get('variation_name', 'Var')}**")
+                df = pd.DataFrame(variation.get("script_table", []))
+                st.table(df)
+                if not df.empty:
+                    df["Variation"] = variation.get("variation_name", f"Var{i}")
+                    df["Round"] = round_idx
+                    all_tables.append(df)
+
+    if all_tables:
+        csv_scripts = pd.concat(all_tables, ignore_index=True).to_csv(index=False)
+        st.download_button(
+            "Download CSV",
+            data=csv_scripts,
+            file_name=f"{(doc.get('video_name') or doc.get('file_name') or 'scripts')}_scripts.csv",
+            mime="text/csv",
+            use_container_width=True,
+            key=f"{prefix}_download_csv",
+        )

app_pages/text_image_generation.py

@@ -29,12 +29,13 @@ def render_multimodel_ad_generator(prefix: str = "img_text"):
         prompt = st.text_area("Prompt", placeholder="Describe the image you want to generate...", height=160, key=f"{prefix}_prompt")
 
     if st.button("Generate Images", type="primary", key=f"{prefix}_go"):
+        uid = st.session_state.get("uid")
         handle_image_generation_optimized(
+            uid=uid,
             model_key=model_key,
             aspect_ratio=aspect_ratio,
             prompt=prompt,
             num_images=num_images,
-            debug_mode=False,
             category=(category.strip() or None),
             platform=platform or None,
         )

app_pages/text_image_generation_library.py

@@ -1,19 +1,25 @@
 from __future__ import annotations
 
 from datetime import datetime, timedelta, date
-from typing import Any, Dict, List, Optional
+from typing import Any, Dict, List
 
 import streamlit as st
 
 from database.connections import get_results_collection
 
 
-def _distinct_options(col, field: str, source: str, created_by: Optional[str] = None) -> List[str]:
+def _distinct_options(col, field: str, source: str) -> List[str]:
     try:
-        q: Dict[str, Any] = {"source": source}
-        if created_by:
-            q["created_by"] = created_by
-        vals = col.distinct(field, q)
+        if field == "platform":
+            vals = (
+                col.distinct("platform", {"source": source})
+                + col.distinct("settings.platform", {"source": source})
+                + col.distinct("provider_settings.platform", {"source": source})
+                + col.distinct("metadata.platform", {"source": source})
+            )
+        else:
+            vals = col.distinct(field, {"source": source})
+
         vals = [v for v in vals if v not in (None, "", [])]
         vals = sorted(set(vals))
         return ["All"] + vals if vals else ["All"]
@@ -28,7 +34,6 @@ def _query_docs(
     end_d: date,
     category: str,
     platform: str,
-    created_by: Optional[str] = None,
     limit: int = 200,
 ) -> List[Dict[str, Any]]:
     try:
@@ -38,16 +43,19 @@ def _query_docs(
         if category and category != "All":
             q["category"] = category
         if platform and platform != "All":
-            q["platform"] = platform
-        if created_by:
-            q["created_by"] = created_by
-
+            q["$or"] = [
+                {"platform": platform},
+                {"settings.platform": platform},
+                {"provider_settings.platform": platform},
+                {"metadata.platform": platform},
+            ]
         cursor = col.find(q).sort("created_at", -1).limit(limit)
         return list(cursor)
     except Exception:
         return []
 
 
+
 def _render_grid(docs: List[Dict[str, Any]], key_prefix: str) -> None:
     seen = set()
     items = []
@@ -82,7 +90,8 @@ def _render_grid(docs: List[Dict[str, Any]], key_prefix: str) -> None:
                 st.error("Failed to load image")
 
 
-def render_text_image_library(uid: Optional[str] = None) -> None:
+def render_text_image_library() -> None:
+
     col = get_results_collection()
     if col is None:
         st.warning("Database not available. Set MONGO_URI and restart.")
@@ -97,8 +106,8 @@ def render_text_image_library(uid: Optional[str] = None) -> None:
     with c2:
         end_date = st.date_input("End date", value=today, key="img_text_end")
 
-    cat_opts = _distinct_options(col, "category", source="text", created_by=uid)
-    plat_opts = _distinct_options(col, "platform", source="text", created_by=uid)
+    cat_opts = _distinct_options(col, "category", source="text")
+    plat_opts = _distinct_options(col, "platform", source="text")
 
     r1, r2 = st.columns(2)
     with r1:
@@ -107,5 +116,5 @@ def render_text_image_library(uid: Optional[str] = None) -> None:
         platform = st.selectbox("Platform", options=plat_opts, key="img_text_plat")
 
     st.markdown("---")
-    docs = _query_docs(col, "text", start_date, end_date, category, platform,created_by=uid)
-    _render_grid(docs, key_prefix="text")
+    docs = _query_docs(col, "text", start_date, end_date, category, platform)
+    _render_grid(docs, key_prefix="text")

app_pages/video_analyser.py

@@ -1,18 +1,14 @@
 from __future__ import annotations
-import os, tempfile
+import os, tempfile, base64, json
 import streamlit as st
-import base64
 from typing import Any, Dict
+
 from background_task.generation_tasks import run_and_store_video_analysis
 from app_pages.video_library import render_analyzer_results
+from database.operations import insert_video_analysis
 
 
-def render_video_library_page() -> None:
-    from app_pages.video_library import render_video_library
-    render_video_library()
-
-
-def render_video_analyser_page(task_manager=None, uid: str = "anonymous") -> None:
+def render_video_analyser_page(uid: str ) -> None:
     st.markdown("### Video Analyser")
 
     category_va = st.text_input("Category", key="va_category")
@@ -26,21 +22,19 @@ def render_video_analyser_page(task_manager=None, uid: str = "anonymous") -> Non
     video_ext = "mp4"
 
     if uploaded is not None:
-
         video_bytes = uploaded.read()
         if uploaded.name and "." in uploaded.name:
             video_ext = uploaded.name.rsplit(".", 1)[-1].lower() or "mp4"
 
-
         b64 = base64.b64encode(video_bytes).decode("utf-8")
         st.caption("Preview")
         st.markdown(
             f"""
-                        <video controls width="720">
-                            <source src="data:video/{video_ext};base64,{b64}">
-                            Your browser does not support the video tag.
-                        </video>
-                        """,
+            <video controls width="720">
+                <source src="data:video/{video_ext};base64,{b64}">
+                Your browser does not support the video tag.
+            </video>
+            """,
             unsafe_allow_html=True,
         )
 
@@ -50,7 +44,6 @@ def render_video_analyser_page(task_manager=None, uid: str = "anonymous") -> Non
         if not video_bytes or not category_va.strip():
             st.warning("Please provide a category and upload a video.")
         else:
-
             suffix = f".{video_ext}" if video_ext else ".mp4"
             with tempfile.NamedTemporaryFile(delete=False, suffix=suffix) as tmp:
                 tmp.write(video_bytes)
@@ -63,6 +56,7 @@ def render_video_analyser_page(task_manager=None, uid: str = "anonymous") -> Non
                         uploaded_file_path=tmp_path,
                         created_by=uid,
                     )
+
             finally:
                 try:
                     os.remove(tmp_path)
@@ -70,8 +64,23 @@ def render_video_analyser_page(task_manager=None, uid: str = "anonymous") -> Non
                     pass
 
             if isinstance(result, dict) and result.get("results"):
-                st.success(f"Saved analysis (_id: {result.get('_id', 'N/A')})")
+                st.success("Analysis completed successfully ")
                 render_analyzer_results(result["results"])
-            else:
-                st.error("Analysis failed. Check GEMINI_API_KEY and try again.")
 
+
+                res = json.dumps(result["results"], indent=2, ensure_ascii=False)
+                st.download_button(
+                    "Download JSON",
+                    data=res.encode("utf-8"),
+                    file_name=f"video_analysis_{result.get('_id', 'item')}.json",
+                    mime="application/json",
+                    width='content',
+                    key="va_json_dl",
+                )
+
+                if st.button("Save to Database", key="va_save_db"):
+                    try:
+                        insert_video_analysis(result)
+                        st.success("Analysis saved to database ")
+                    except Exception as e:
+                        st.error(f"Failed to save: {e}")

app_pages/video_library.py

@@ -27,19 +27,17 @@ def _label_for_item(doc: Dict[str, Any]) -> str:
     model = doc.get("analyzer_model") or "—"
     return f"{ts_s} · {cat} · {model}"
 
-
-def render_video_library(uid: str) -> None:
+def render_video_library(uid: Optional[str] = None,prefix: str = "vid_lib") -> None:
     st.subheader("Video Library")
 
-    # --- Filters (unchanged layout) ---
     today = datetime.utcnow().date()
     default_start = today - timedelta(days=30)
 
     c1, c2, c3 = st.columns([1, 1, 1])
     with c1:
-        start_date: date = st.date_input("Start date", value=default_start, key="vid_lib_start")
+        start_date: date = st.date_input("Start date", value=default_start, key=f"{prefix}_start")
     with c2:
-        end_date: date = st.date_input("End date", value=today, key="vid_lib_end")
+        end_date: date = st.date_input("End date", value=today, key=f"{prefix}_end")
     with c3:
         try:
             cats: List[str] = list_video_categories()
@@ -47,7 +45,7 @@ def render_video_library(uid: str) -> None:
                 cats = ["All"] + [c for c in cats if c != "All"]
         except Exception:
             cats = ["All"]
-        category = st.selectbox("Category", options=cats, index=0, key="vid_lib_cat")
+        category = st.selectbox("Category", options=cats, index=0, key=f"{prefix}_cat")
 
     st.markdown("---")
 
@@ -57,7 +55,7 @@ def render_video_library(uid: str) -> None:
         end_dt = datetime.combine(end_date + timedelta(days=1), datetime.min.time())
         query_cat = None if (not category or category == "All") else category
         docs: List[Dict[str, Any]] = find_video_analyses(
-            category=query_cat,start_date=start_dt,end_date=end_dt,limit=200,created_by=uid,
+            category=query_cat, start_date=start_dt, end_date=end_dt, limit=200,created_by=uid,
         )
     except Exception as e:
         st.error(f"Failed to load video analyses: {e}")
@@ -94,10 +92,10 @@ def render_video_library(uid: str) -> None:
     if analysis:
         render_analyzer_results(analysis)
         try:
-            pretty = json.dumps(analysis, indent=2, ensure_ascii=False)
+            res = json.dumps(analysis, indent=2, ensure_ascii=False)
             st.download_button(
                 "Download JSON",
-                data=pretty.encode("utf-8"),
+                data=res.encode("utf-8"),
                 file_name=f"video_analysis_{doc.get('_id','item')}.json",
                 mime="application/json",
                 use_container_width=True,
@@ -106,4 +104,6 @@ def render_video_library(uid: str) -> None:
         except Exception:
             pass
     else:
-        st.info("No analysis  stored for this item.")
+        st.info("No analysis  stored for this item.")
+
+