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Update app.py
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app.py
CHANGED
@@ -4,6 +4,138 @@ import gradio as gr
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import json
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import plotly.graph_objects as go
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class ArtExplorer:
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def __init__(self):
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self.client = openai.OpenAI(
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@@ -38,32 +170,119 @@ class ArtExplorer:
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return fig
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def get_llm_response(self, query: str, zoom_context: dict = None) -> dict:
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def create_interface(self):
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with gr.Blocks() as demo:
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import json
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import plotly.graph_objects as go
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CONTEXTUAL_ZOOM_PROMPT = """
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You are an expert art historian specializing in interactive exploration. Analyze the query and generate contextually aware zoom configurations with explanations.
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###Input###
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User Query: {user_query}
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Current Zoom States: {
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"temporal": {"level": "", "selection": ""},
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"geographical": {"level": "", "selection": ""},
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"style": {"level": "", "selection": ""},
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"subject": {"level": "", "selection": ""}
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}
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###Output Format###
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{
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"analysis": {
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"query_focus": "main subject",
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"historical_context": "brief explanation"
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},
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"axis_configurations": {
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"temporal": {
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"component": "st.slider",
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"current_zoom": {
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"level": "century/decade/year",
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"range": [start, end],
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"explanation": "Why this time range is relevant"
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},
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"available_zooms": {
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"in": {
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"range": [narrower_start, narrower_end],
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"explanation": "What focusing here reveals"
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},
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"out": {
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"range": [broader_start, broader_end],
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"explanation": "Broader historical context"
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}
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},
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"impacted_by": {
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"geographical": "how location affects timeframe",
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"style": "how style affects timeframe"
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}
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},
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"geographical": {
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"component": "st.map",
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"current_zoom": {
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"level": "continent/country/city",
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"locations": [
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{
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"name": "",
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"lat": 0,
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"lon": 0,
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"relevance": "why this location matters"
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}
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]
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},
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"available_zooms": {
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"in": {
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"locations": ["more specific locations"],
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"explanation": "What focusing here reveals"
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},
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"out": {
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"locations": ["broader regions"],
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"explanation": "Broader geographical context"
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}
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},
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"impacted_by": {
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"temporal": "how time period affects locations",
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"style": "how style affects locations"
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}
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},
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"style": {
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"component": "st.multiselect" if current_zoom == "broad" else "st.selectbox",
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"current_zoom": {
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"level": "movement/sub_movement/specific",
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"options": ["list of styles"],
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"explanation": "Style context for this period/location"
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}
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}
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},
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"streamlit_adaptations": {
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"recommended_components": {
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"component_name": "reason for recommendation based on zoom level",
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"configuration": {}
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}
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}
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}
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###Example for "paint during napoleon war"###
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{
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"temporal": {
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"component": "st.slider",
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"current_zoom": {
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"level": "period",
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"range": [1799, 1815],
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"explanation": "Napoleon's reign as First Consul and Emperor"[1]
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},
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"available_zooms": {
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"in": {
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"range": [1812, 1815],
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"explanation": "Focus on final campaigns and artistic responses"[1]
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}
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}
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},
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"geographical": {
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"component": "st.map",
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"current_zoom": {
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"level": "continent",
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"locations": [
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{
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"name": "France",
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"relevance": "Center of Napoleonic art production"[2]
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},
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{
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"name": "Spain",
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"relevance": "Goya's war paintings perspective"[1]
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}
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]
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}
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}
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}
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###Requirements###
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1. Explain zoom level changes and their historical significance
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2. Adapt Streamlit components based on zoom level
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3. Show relationships between different axes
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4. Provide historical context for available selections
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5. Consider how selections affect other axes
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6. Include relevant historical explanations for each zoom level
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Generate only the JSON response, maintaining strict JSON format."""
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class ArtExplorer:
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def __init__(self):
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self.client = openai.OpenAI(
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return fig
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def get_llm_response(self, query: str, zoom_context: dict = None) -> dict:
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try:
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# Format the CONTEXTUAL_ZOOM_PROMPT with current values
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formatted_prompt = CONTEXTUAL_ZOOM_PROMPT.format(
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user_query=query,
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current_zoom_states={
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"temporal": {
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"level": self.current_state.get("zoom_level", ""),
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"selection": zoom_context.get("temporal") if zoom_context else ""
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},
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"geographical": {
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"level": self.current_state.get("zoom_level", ""),
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"selection": zoom_context.get("geographical") if zoom_context else ""
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},
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"style": {
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"level": self.current_state.get("zoom_level", ""),
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"selection": zoom_context.get("style") if zoom_context else ""
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},
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"subject": {
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"level": self.current_state.get("zoom_level", ""),
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"selection": zoom_context.get("subject") if zoom_context else ""
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}
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}
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)
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response = self.client.chat.completions.create(
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model="mixtral-8x7b-32768",
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messages=[
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{
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"role": "system",
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"content": "You are an expert art historian specializing in interactive exploration."
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},
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{
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"role": "user",
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"content": formatted_prompt
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}
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],
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temperature=0.1,
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max_tokens=2048
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)
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result = json.loads(response.choices[0].message.content)
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# Validate response structure
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if "axis_configurations" not in result:
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raise KeyError("Missing axis_configurations in LLM response")
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return result
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except Exception as e:
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print(f"Error in LLM response: {str(e)}")
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# Return default structure following the same format as the prompt
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return {
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"analysis": {
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"query_focus": "Default focus",
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"historical_context": "Default historical context"
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},
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"axis_configurations": {
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"temporal": {
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"component": "st.slider",
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"current_zoom": {
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"level": "century",
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"range": [1700, 2000],
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"explanation": "Default time range"
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},
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"available_zooms": {
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"in": {
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"range": [1800, 1900],
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"explanation": "Zoom in to see more detail"
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},
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"out": {
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"range": [1500, 2024],
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"explanation": "Broader historical context"
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}
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},
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"impacted_by": {
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"geographical": "Location affects time period",
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"style": "Style affects time period"
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}
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},
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"geographical": {
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"component": "st.map",
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"current_zoom": {
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"level": "continent",
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"locations": [
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{
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"name": "Paris",
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"lat": 48.8566,
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"lon": 2.3522,
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"relevance": "Default location"
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}
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]
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},
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"available_zooms": {
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"in": {
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"locations": ["Paris", "London", "Rome"],
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"explanation": "Major art centers"
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},
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"out": {
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"locations": ["Europe", "Americas", "Asia"],
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"explanation": "Global art movements"
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}
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}
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},
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"style": {
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"component": "st.multiselect",
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"current_zoom": {
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"level": "movement",
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"options": ["Classical", "Modern"],
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"explanation": "Default art movements"
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}
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}
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}
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}
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def create_interface(self):
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with gr.Blocks() as demo:
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