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import streamlit as st
import pandas as pd
from typing import Dict, Any
def render_analyzer_results(result: Dict[str, Any]) -> None:
"""Render AdAnalysis results in Streamlit UI (table format)."""
# --- Headline ---
if "copywriting_breakdown" in result:
headline = result["copywriting_breakdown"].get("headline", "Ad Analysis Result")
st.header(f" {headline}")
# --- Visual Layout ---
if "visual_structure_layout" in result:
st.subheader(" Visual Structure Layout")
vsl = result["visual_structure_layout"]
table_data = [
["Background", vsl.get("background_color")],
["Psychological Association", vsl.get("psychological_association")],
["Minimalism Level", vsl.get("minimalism_level")],
["Flow Summary", vsl.get("hierarchy", {}).get("flow_summary")],
["Key Elements Order", ", ".join(vsl.get("hierarchy", {}).get("key_elements_order", []))],
]
df = pd.DataFrame(table_data, columns=["Property", "Value"])
st.table(df)
# --- Psychological Triggers ---
if "psychological_behavioral_triggers" in result:
st.subheader(" Psychological & Behavioral Triggers")
df = pd.DataFrame(result["psychological_behavioral_triggers"].items(), columns=["Trigger", "Description"])
st.table(df)
# --- Storytelling ---
if "story_creative_tells" in result:
st.subheader(" Storytelling Elements")
df = pd.DataFrame(result["story_creative_tells"].items(), columns=["Element", "Content"])
st.table(df)
# --- Strengths & Weaknesses ---
if "strengths" in result or "weaknesses" in result:
col1, col2 = st.columns(2)
with col1:
st.subheader("Strengths")
strengths = result.get("strengths", [])
if strengths:
df = pd.DataFrame(strengths)
df.rename(columns={"point": "Point", "why_it_matters": "Why It Matters"}, inplace=True)
st.table(df)
else:
st.info("No strengths found.")
with col2:
st.subheader("Weaknesses")
weaknesses = result.get("weaknesses", [])
if weaknesses:
df = pd.DataFrame(weaknesses)
df.rename(columns={"point": "Point", "why_it_matters": "Why It Matters"}, inplace=True)
st.table(df)
else:
st.info("No weaknesses found.")
# --- Risks ---
if "risks_in_arbitrage_context" in result:
st.subheader(" Risks in Arbitrage Context")
df = pd.DataFrame(result["risks_in_arbitrage_context"].items(), columns=["Risk", "Level"])
st.table(df)
# --- Optimization Next Steps ---
if "optimization_next_steps" in result:
st.subheader(" Optimization Next Steps")
opt = result["optimization_next_steps"]
if "creative_variants" in opt:
st.markdown("**Creative Variants**")
df = pd.DataFrame(opt["creative_variants"])
df.rename(
columns={
"hypothesis": "Hypothesis",
"change": "Change",
"expected_effect": "Expected Effect",
"metric_to_watch": "Metric to Watch",
},
inplace=True,
)
st.table(df)
with st.expander(" Raw JSON Result", expanded=False):
st.json(result)
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