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Update app_pages/script_generator.py
Browse files- app_pages/script_generator.py +131 -135
app_pages/script_generator.py
CHANGED
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@@ -3,153 +3,149 @@ import tempfile
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import pandas as pd
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import streamlit as st
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from services.
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from utils.video import get_video_thumbnail_base64
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from
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from database import
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def
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if selected_tab == "Script Generator":
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st.subheader("Script Generator")
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uploaded_video = st.file_uploader(
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"Upload Video
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type=['mp4','mov','avi','mkv',
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)
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specific_hooks = st.text_area("Specific Hooks to Test", placeholder="e.g., Government rebate angle...")
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additional_context = st.text_area("Additional Context", placeholder="Compliance requirements, brand guidelines...")
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script_button = st.button("Generate Scripts", use_container_width=True)
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if script_button and uploaded_video:
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with tempfile.NamedTemporaryFile(delete=False, suffix=os.path.splitext(uploaded_video.name)[1]) as tmp:
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tmp.write(uploaded_video.read())
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video_path = tmp.name
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result =
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st.session_state["video_path"] = video_path
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st.session_state["thumbnail"] = get_video_thumbnail_base64(video_path)
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st.session_state["meta"] = {
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"offer_details": offer_details,
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"target_audience": target_audience,
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"specific_hook": specific_hooks,
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"additional_context": additional_context
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}
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if "scripts" in st.session_state and st.session_state["scripts"]:
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for round_idx, round_data in enumerate(st.session_state["scripts"], 1):
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st.markdown(f"### Generation Round {round_idx}")
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st.text_input("Prompt used:", round_data["prompt_used"], disabled=True, key=f"prompt_{round_idx}")
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for i, variation in enumerate(round_data["variations"], 1):
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st.markdown(f"#### Variation {i}: {variation.get('variation_name','Var')}")
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df = pd.DataFrame(variation.get("script_table", []))
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st.table(df)
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st.divider()
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save_button = st.button("Save to DB", use_container_width=True)
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if save_button:
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try:
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video_name=st.session_state.get("video_name", "unknown"),
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target_audience=st.session_state["meta"].get("target_audience", ""),
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specific_hook=st.session_state["meta"].get("specific_hook", ""),
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additional_context=st.session_state["meta"].get("additional_context", ""),
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response=st.session_state["scripts"],
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thumbnail=st.session_state.get("thumbnail", "")
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)
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st.success("
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except Exception as e:
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st.error(f"Failed to save
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st.subheader("Generate More Scripts")
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more_num = st.slider("How many more scripts?", 1, 5, 1, key="more_scripts_slider")
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more_prompt = st.text_area("Required Prompt", placeholder="Add specific guidance")
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if st.button("Generate More Scripts", use_container_width=True):
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if not more_prompt.strip():
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st.error("Please provide a prompt before generating more scripts.")
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else:
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video_path = st.session_state.get("video_path")
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if not video_path:
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st.error("No video available. Please upload again.")
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else:
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with st.spinner("Generating more scripts..."):
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extra_result = generate_scripts(
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video_path,
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st.session_state["meta"]["offer_details"],
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st.session_state["meta"]["target_audience"],
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st.session_state["meta"]["specific_hook"],
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st.session_state["meta"]["additional_context"] + "\n\n" + more_prompt,
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num_scripts=more_num,
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duration=script_duration
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)
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if extra_result and "script_variations" in extra_result:
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st.session_state["scripts"].append({
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"prompt_used": more_prompt,
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"variations": extra_result["script_variations"]
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})
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else:
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import pandas as pd
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import streamlit as st
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from services.video_analyzer import analyze_video_only
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from components.render_analysis import render_analyzer_results
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from utils.video import get_video_thumbnail_base64
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from utils.dataframe import analysis_to_csv
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from database import insert_video_analysis, get_all_video_analyses
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def analyzer_page():
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st.sidebar.header("Analyzer")
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selected_tab = st.sidebar.radio("Select Mode", ["Video Analyser", "History"], index=0)
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if selected_tab == "Video Analyser":
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st.subheader(" Video Analyser")
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uploaded_video = st.file_uploader(
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"Upload Video",
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type=['mp4', 'mov', 'avi', 'mkv'],
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help="Upload a video for analysis"
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)
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analyse_button = st.button("Run Analysis", use_container_width=True)
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if uploaded_video and analyse_button:
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# Save to a temp file
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suffix = os.path.splitext(uploaded_video.name)[1]
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with tempfile.NamedTemporaryFile(delete=False, suffix=suffix) as tmp:
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tmp.write(uploaded_video.read())
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video_path = tmp.name
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with st.spinner("Analyzing video..."):
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result = analyze_video_only(video_path)
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st.session_state["video_name"] = uploaded_video.name
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st.session_state["video_path"] = video_path
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st.session_state["thumbnail"] = get_video_thumbnail_base64(video_path)
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st.session_state["analysis"] = result
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analysis = st.session_state.get("analysis")
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if analysis is None:
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return
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if not analysis:
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st.error("Analysis returned no data.")
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return
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if "__error__" in analysis:
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st.error(f"Analysis failed: {analysis['__error__']}")
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return
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render_analyzer_results(analysis)
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col1, col2 = st.columns(2)
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# CSV export
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with col1:
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frames = []
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if "storyboard" in analysis:
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df_storyboard = pd.DataFrame(analysis["storyboard"])
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df_storyboard["section"] = "Storyboard"
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frames.append(df_storyboard)
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if "script" in analysis:
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df_script = pd.DataFrame(analysis["script"])
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df_script["section"] = "Script"
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frames.append(df_script)
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if "video_analysis" in analysis and "video_metrics" in analysis["video_analysis"]:
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df_metrics = pd.DataFrame(analysis["video_analysis"]["video_metrics"])
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df_metrics["section"] = "Metrics"
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frames.append(df_metrics)
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if "timestamp_improvements" in analysis:
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df_improvements = pd.DataFrame(analysis["timestamp_improvements"])
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df_improvements["section"] = "Improvements"
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frames.append(df_improvements)
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if frames:
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csv_content = pd.concat(frames, ignore_index=True).to_csv(index=False)
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st.download_button(
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"Download CSV",
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data=csv_content,
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file_name=f"{st.session_state.get('video_name', 'analysis')}.csv",
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mime="text/csv",
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use_container_width=True,
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)
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else:
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st.info("No tabular data available for CSV export.")
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# Save to DB
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with col2:
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if st.button("Save to DB", use_container_width=True):
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try:
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insert_video_analysis(
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video_name=st.session_state.get("video_name", "unknown"),
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response=analysis,
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thumbnail=st.session_state.get("thumbnail", "")
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)
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st.success("Analysis saved to database ")
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except Exception as e:
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st.error(f"Failed to save analysis: {e}")
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else:
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# History tab
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st.subheader(" History")
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try:
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history_items = get_all_video_analyses(limit=20)
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except Exception as e:
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st.error(f"Failed to load history: {e}")
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return
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if not history_items:
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st.info("No saved history available.")
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return
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video_titles = [
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f"{item['video_name']} ({item['created_at'].strftime('%Y-%m-%d %H:%M')})"
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for item in history_items
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]
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selected = st.sidebar.radio("History Items", video_titles, index=0)
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idx = video_titles.index(selected)
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selected_data = history_items[idx]
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st.subheader(f"Analysis for: {selected_data['video_name']}")
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if selected_data.get("thumbnail"):
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st.image("data:image/jpeg;base64," + selected_data["thumbnail"], width=150)
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json_response = selected_data.get("response")
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if not json_response:
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st.info("No analysis payload found for this item.")
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return
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tabs = st.tabs(["Video Analysis"])
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with tabs[0]:
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render_analyzer_results(json_response)
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try:
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csv_data = analysis_to_csv(json_response)
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st.download_button(
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"Download CSV",
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data=csv_data,
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file_name=f"{selected_data['video_name']}_analysis.csv",
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mime="text/csv",
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use_container_width=True,
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)
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except Exception as e:
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st.error(f"CSV export failed: {e}")
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